§U.5. Dept. of Health, Education and Welfare} DHEW publication no. WV OSH kihess ns-1bd Behavioral Effects of Occupational Exposure to Lead [SH] Research Report PUBL BEHAVIORAL EFFECTS OF OCCUPATIONAL EXPOSURE TO LEAD \ John D. Repko,| Ben B. Morgan, Jr., and John Nicholson - Performance Research Laboratory Graduate School University of Louisville Louisville, Kentucky 40208 Contract No. HSM-99-72-123 U. S. DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE Public Health Service Center for Disease Control National Institute for Occupational Safety and Health Division of Laboratories and Criteria Development Cincinnati, Ohio 45202 May 1975 For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402 The opinions, findings, and conclusions expressed in this publication are those of the authors and not necessarily those of the National Institute for Occupational Safety and Health. NIOSH Project Officers Barry L. Johnson and Charles Xintaras HEW Publication No. (NIOSH) 75-164 RA 1231 L4 FOREWORD [41 PUBL This report was prepared by Drs. John D. Repko (Assistant Research Professor and Acting Director), Ben B. Morgan, Jr. (Associate Research Professor), and John A. Nicholson (Assistant Professor of Pharmacology), Performance Research Laboratory, University of Louisville, Louisville, Kentucky 40208. The research program under which this work was completed was supported by the National Institute for Occupational Safety and Health, Department of Health, Education and Welfare, under Contract No. HSM 99-72-123, "Evaluation of Behavioral Functions in Workers Exposed to Lead," and monitored by Drs. Barry L. Johnson and Charles Xintaras, Behavioral Studies Laboratory, Behavioral and Motivational Factors Branch, NIOSH, 1014 Broadway, Cincinnati, Ohio 45202. The authors acknowledge the assistance of Dr. Earl A. Alluisi, Mr. John M. Lyddan, Mr. Kenneth T. Hunt, and Mr. Karl E. Rothrock who contributed in the preparation of the appendices. Special appreciation is also extended to Drs. Michel Loeb, Bill R. Brown, and Lipman J. Klein, each of whom read and criticized earlier versions of this report. The contribution of time and effort on the part of Mr. Donald Corson, Mr. Robert W. Welch, Ms. Regina Hunt, and Ms. Hollie Moore, each of whom participated in various aspects of data collection and laboratory clinical analyses, is gratefully acknowledged. The authors also acknowledge the assistance of many corporate and union personnel who assisted us in obtaining volunteers from among the workers employed in the various plants involved in this study. Appreciation is also expressed to Mmes. Kathy Blagrove, Jo Ann Begley, and Ginny Berg for their assistance in typing the several drafts of this manuscript. * * * The findings in this report are not to be considered as an official NIOSH position, unless so designated by other authorized documents. 3 SUMMARY Eighty behavioral measures of task performance and five measures of body burden of lead were obtained from 316 experimental and 112 control subjects. The experimental subjects were volunteers from among workers exposed to inorganic lead at their jobs in three storage (lead-acid) battery manufacturing companies. The controls were volunteers from five companies involved in various types of light manufacturing; they were selected (a) because they had never been exposed to inorganic lead, (b) on the basis of their membership in the same national labor unions as the experimentals, and (¢) so as to match the experimentals as closely as possible in terms of sex, race, age, education, duration of employment, and similar geographic location. The data were collected either in space provided by the companies (near an entrance to the plant) or in nearby buildings provided by the labor unions involved. The results obtained with the five measures of body burden indicate that for the experimental subjects the measures were intercorrelated, and each measure could be predicted from each of the other measures; the measures for the control subjects were not all intercorrelated. These data also indicate that blood lead is not a sensitive measure of changes in functional (performance) capacity. Aminolevulinic acid dehydrase in the blood (blood ALA-D) was found to be the most sensitive predictor of task performance. The relationships among the measures of task performance and body burden of lead were examined through the use of correlation and multiple-regression analyses, analyses of variance and covariance (where appropriate), and a factor analysis. The results of these analyses indicate that the intellectual functions measured in this study were unaffected by increases in body burden of lead. On the other hand, sensory (hearing), neuromuscular or psychomotor (tremor, eye- hand coordination, muscular strength and endurance), and psychological (hostility, aggression, and general dysphoria) functions were all influenced by body burden of lead. The strongest relationships were obtained with tests of neuromuscular and psychomotor functions; major changes occurred on the preferred side of the body at PbB levels between 70 and 79ug%. The results are discussed in terms of their significance for occupational safety and health and in relation to the needs for future research. Recommendations are made concerning industrial exposure standards to lead and systems for monitoring the health and welfare of exposed workers. | . a soe ou . ES . - - FE “ . ’ “ - “ = TABLE OF CONTENTS BUMMARY.. si vvunin cis asa anna s ena hE R a8 hho 8 etn semns esses wes ss LIST OF ILLUSTRATIONS. .cvxnuuensonnavnnmnnmonsanen HR LIST OF TABLES. ccvcinuiicinsitsssssosssrasarvennannenns Cees INTRODUCTION. «4 vveoxsn erasssss ansans sosananonsnsnomnosesssss METHOD: vs unsnt vrasns vrsssnsevosannvsnssesss nnvnss Ce DESCRIPTION OF STUDY POPULATION. .....eeeeereennnnceenns Protection of Subjects......ciieeieennerenncannnnn GENERAL TEST PROTOCOL. vcxuvvenunsnsnasssus anssnsasnsnnns TESTING OF WORKERS. csvscvnsntonssatonssasnssansnosnnnes Tasks of the MIPB........cciiiiinniinnnnnnnnnnnnnas Visual ACUHILY cu cuvnsnasnnrssmssisnnnmansenmavosnns AUGILOTY ACUALY . ssusnnsrensssssvesnseissserdtosnanse TOMO cus snnmnis covabss sistas panssssnansesns naeense Strength, Endurance, and Recovery...........cceue.. Eye-Hand Coordination... usessumesnsssnsveesnaneses Digit-BPafl.vennumvcnsnnuasisssannsssasisisssasosene Multiple Affect Adjective Check List.......ccco... Personal-Data Questionnaire.........ceeeeeeenennn. CLINICAL DETERMINATIONS... sues ssnononsnnsnamvnonsnassive Blood HematoeTit. cviisnissnsssisensonsnonsenronns Blood delta-Aminolevulinic Acid Dehydrase (ALA-D) ...viieieeneeeeeeeensneanananns Urine delta-Aminolevulinic Acid (ALA).....veveun.. Urine CoproporTphyYTin..cisssesscnsenssnsensonnensnes Blood Lead. ccoiivnrrrsansunssensnnssnsnmsnsnnn une Urine Lead. ....civiiiininennnneeneneneenennnnns v RESULTS. vo unsnnn sinenunsenintsss 4asssstonsnnte vanssenssssesens STUDY GROUPS. «itt itiiiit ii titiereeenneneennsennnnnnas CLINICAL MEASURES. ..cuvsavt sussnensnnnnnsrusnesesosnsns Distribution and Intercorrelation of the Clinical Measures ® © 00 00 0000000000000 00000000000 15 15 15 16 16 17 17 20 22 TABLE OF CONTENTS (Continued) PERFORMANCE MEASURES. conew svvnssmm nnvsnains susnsndnnensnn Individual Performance TESTS... ccaunissnssnsrsennns Multiple Task Performance Battery (MIPB)..... Visual acuity....ovoueiinienennnnneneannninns AMditory aCUitY. vivesnvnnsnnnvnnrenrornnnsene Strength, Endurance, and Recovery (SER)...... TROMOP es 0 ssa Tha 2 hE HRT AS LE FRRS SEG HSRO SEES R SE os Digit SPAN. ..eietrinereneenrereccaccsenesnans Multiple Affect Adjective Check List {MAACLY vunsns snsnnasusnnassriismens nogadness Eye-Hand coordination........ceeeeeeeeeeannns FUNCTIONAL CAPACITY... tttetreeeesecnsessonsnnsscnsannns Intellectual FUunCtionsS......cieeieeerreneeenaaeanns Sensory-Perceptual FunctionS........oeeeeeenecanns Neuromuscular Functions.....ccceieeenennnnnssnness Psychological FunctionsS....cieicovenssnmsnssninosss CONCLUSIONS, RECOMMENDATIONS, AND FUTURE RESEARCH NEEDS..... SUMMARY OF FINDINGS. coi vivanniovsssns nassnas st sassvw tives Biomedical Measures. cc ce snsvves sanessn «oneness oewe Intellectual FumctionS...sessessanusenmnuvnsic voy Sensory-Perceptual Functions...........c.cuievnnnnn Neuromuscular Functions........cceeeeeeeeeacenenas Psychological Functions. esses wvenennmonnssnsnnss RECOMMENDATIONS. «it it titi teeta eeeneoaaneassscasanasnnns Lowering of PbB Criteria. eoncvrvvvessrnnnssnonene Utilization of ALA-D Criteria. .conssssmsunsnins nenns Utilization of Functional Tests... ees eenvsunsvannse FUTURE RESEARCH NEEDS. ....iiiiiiiierereeeeeennnnnnnnns Need for Longitudinal Study... .vcsvosvrennvnennsss Need for Neurophysiological Correlates............ Need for Latency MeasuresS.........ceeeeeeeeeecnans Need for Further Auditory Data.......... eececene CONCLUSION: iq sovnnnvssavstims hnbans voconins vasanssnonnni REFERENCES, \ vsnnnucmrnsnmevasusnseasnnsinssnsnssnsvavasnnseowens APPENDIX A: TRADITIONAL METHODS FOR MONITORING OCCUPATIONAL EXPOSURE OF WORKERS, prepared by John D. Repko, Donald L. Corson, and Ben B. MOTE, Jluwsussasnnevansnsmsossnsmanusess 61 63 65 65 66 68 69 71 71 71 71 71 72 72 72 72 72 73 73 74 74 74 75 75 77 119 APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX APPENDIX TABLE OF CONTENTS (Continued) BEHAVIORAL EFFECTS OF LEAD POISONING, prepared by John D. Repko, Donald L. Corson, and Ben B., Morgan, Jresscevseeessevnssns DESCRIPTION OF TASKS EMPLOYED IN THE COMPREHENSIVE BEHAVIORAL TEST BATTERY, prepared by John D. Repko, Kenneth Hunt, Karl E. Rothrock, and John M. Lyddan........... RESEARCH METHODOLOGY OF THE SYNTHETIC- WORK TECHNIQUE, prepared by Ben B. Morgan, Jr. and Earl A. Alluisi...ccieveeenenns SUMMARY OF LABORATORY PROCEDURES EMPLOYED IN THE CLINICAL ANALYSES, prepared by John A. Nicholson........... PN INDUSTRIAL AND PERSONAL HYGIENE PRACTICES, prepared by John D. Repko and Ben B. Morgan, Jr...c.eeeeeeeeenns sun EVALUATION OF HEALTH STATUS OF WORKERS EXPOSED TO INORGANIC LEAD, prepared by John D. Repko and John M, Lyddan..cisse sosassrssassisssvassnsssss OFFICIAL FORMS, prepared by John M. LYyd0oMa suns ssnsecnn ansasss aesssavnoussssnssss SCHEDULES OF BEHAVIORAL TESTING, prepared by John M. Lyddan. ceveesvssvsvsenscnnn PROCEDURES FOR SCORING THE MICHIGAN EYE-HAND COORDINATION DATA, prepared by Karl E. Rothrock and John M. Lyddan......... REPORT FROM THE BUREAU OF COMMUNITY ENVIRONMENTAL MANAGEMENT (DEPARTMENT OF HEALTH, EDUCATION AND WELFARE) .i.i.ivviveennnnn 129 137 161 171 175 185 195 215 221 239 Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure 10. 11. LIST OF ILLUSTRATIONS Schematic diagram of the front view of a modified MIPB operator panel. Letters in circles represent indicator lights, A--amber, B--blue, G--green, and R--red; the smaller circles with crossing diagonals represent push Buttons. cesseuvsssvess ne BERRA EEN ENE Cun EEE Photograph of the visual acuity test showing the Ortho-Rater, test subject (seated), and EXPOLAMENtOY cs vrssanssnssimonssnssvasnsnmponeie Photograph of the auditory acuity test showing the Maico audiometer, test subject (right) and experimenter (left)......... Photograph of the tremor test showing the testing apparatus, test subject (left), and experimenteY (TIGHT) ean svsseen sanrsnsmeneiminne Photograph of the strength, endurance, and recovery test showing the support equipment (on table), hand dynamometer, test subject (seated), and experimenter ..c.cosivevcssscsonnes Photograph of the eye-hand coordination test showing the test maze and recorder, test subject (seated), and experimenter.............. Percentage decomposition of ALA-D in frozen blood samples as a function of time.....eeeen... Distribution of (experimental group) workers within each of eight PbB subgroupS.......eec.... Predictive equations and regression lines for linear and quadratic trends; shown are PbU (upper panel) and ALA-D (lower panel) as functions OF PDBucssvnnnenrnsvensssnsnsnunnsnsnnsnenonnnss Predictive equations and regression lines for linear and quadratic trends; shown are ALA (upper panel) and CPU (lower panel) as functions of POBut rannssvunvsnnrsuvssvanssnssssssnensnsnsnssinn Predictive equations and regression lines for linear and quadratic trends; shown are ALA (top panel), CPU (middle panel), and ALA-D (bottom panel) as functions Of PhlU..ceccerssnerssnennonns Page 10 10 12 12 13 91 92 93 94 95 LIST OF ILLUSTRATIONS (Continued) Figure 12. Predictive equations and regression lines for linear and quadratic trends; shown is ALA-D as a function of ALA... ..cieeereenerenenns 96 Figure 13. Predictive equations and regression lines for linear and quadratic trends; shown is ALA-D as a function of CPU....ccvvevennranenenns 97 Figure 14. Predictive equations and regression lines for linear and quadratic trends; shown is CPU as a function of ALA. ....iiiiiiieenenacananns 98 Figure 15. Mean percentage of target identification problems correct (upper panel) and mean percentage improvement (lower panel) for the experimental and control groups and as functions of PB Subgroups. .eessnceveeseevreness 99 Figure 16. Mean percentage of target identification problems attempted (upper panel) and mean percentage improvement (lower panel) for the experimental and control groups and as functions of PbB subgroups........ccievieeeeaeannn 100 Figure 17. Mean percentage of arithmetic computations correct (upper panel) and mean percentage improvement (lower panel) for the experimental and control groups and as functions of PbB SUD GTOUPS et tv iieiiiteteeiiieeensneonnnnnnaannnns 101 Figure 18. Mean percentage of arithmetic computations attempted (upper panel) and mean percentage improvement (lower panel) for the experimental and control groups and as functions of PbB SUDGTOUPS st wuss adhe GssaR A ws seRNE FALCAB HUUCE 0050 102 Figure 19. Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the PbB subgroup less than 40Ug%. vei ii iii iie tein eennnnnacacasanas 103 Figure 20. Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 40-49ug% PbB SUDGTOUD x vhs stnsnnd hotadns sranssrnssases srsndss 104 Figure Figure Figure Figure Figure Figure Figure Figure Figure 21. 22. 23. 24. 25. 26. 27. 28. 20. LIST OF ILLUSTRATIONS (Continued) Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 50-59ug% PbB SUDGTOUP...vceteeereccnnsseconannas Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 60-6912% POE SUDZLOUD susnvavs uesssnnwrnsnn nrsvene Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 70-79ug% PbB SUDGrOUpP.... ceiver ececeacnnnnnas Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 80-89ug% PbB SUDGTOUP. verre tecrrstsetcacsacnns Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 90-991g% PbB SUDETOUP. eve veeerenseceseencnnans Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the PbB subgroup greater than 100ug%.....cecceeeenes Mean duration of tone decay for the experimental and control groups and as a function of PbB BUDSPOUPS «vv nss hes iB ows RE RES BRFFENSE LENDS RRAPRW Strength (top panel), endurance (middle panel), and impulse (bottom panel) for the experimental and control groups and as functions of PbB SubgroupsS......eeeeeeeessccacaes Mean tremor for the preferred hand of the experimental and control groups and as functions of PbB subgroups; the first and second pre-test trials are given in the top panel and the post-test trials are given in the bottom panel. .....ciiiieiinereneeeneeannnennn 105 106 107 108 109 110 111 112 113 Figure Figure Figure Figure 30. 31. 32. 33. LIST OF ILLUSTRATIONS (Continued) Mean tremor for the non-preferred hand of the experimental and control groups and as functions of PbB subgroups; the first and second pre-test trials are given in the top panel and the post-test trials are given in the bottom panel.....ccvevevevenenns crv wean 114 Measures of Affect (anxiety, hostility depression, and dysphoria) for the experimental and control groups and as functions of PHB SUDGTOUPS cx sun sesnsnwanasns wiv 115 Mean response latency (upper panel) and mean response variability (lower panel) for the experimental and control groups and as functions of PHB SubgIrOUPS.euvcssvsesnsrensnvene 116 Mean endurance/strength ratio for the experimental and control groups and as a function of PbB subgroupS............. ceeeenas 117 Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table 10. 11. 12. 13. 14. 15. LIST OF TABLES Summary of Tests Included in the Comprehensive Behavioral Test Battery.....cceeeeeeeeeosscccacas Basic 1-Hour Task-Performance Schedule........... Demographic Summary of Experimental and Control Groups in Terms of Sex, Race, and Workshift...... Demographic Summary of Experimental and Control Groups in Terms of Age, Height, Weight, Education and Employment. .....ciieiiierereneecnccccccsnnans Summary of Analyses for the Duplicate Blood- Lead Determinations Within and Between LAbOratOrieS.cviciiinssvsvsesns ssnssabruansssmeves Rate of Decomposition of ALA-D in Frozen Human. Blood. cexas conven snvennnnrannsnrovesnnnnns Statistical Summary of the Distribution of Clinical Measures in the Study Groups...... venens Means and Standard Deviations of the Clinical Measures Within Each Experimental PbB Subgroup... Intercorrelations of Seven Clinical Determinations ccossssevsssssssssisgssssssnnonaees Intercorrelations of Eighty Behavioral Measures with Six Clinical Measures of Body Burden OF Lead... over rrvennennennnsnsssnsnssannssssvone Summary of Normalized Regression Coefficients (BETA) from Ten Predictor Variables for Each of Eighty Behavioral MeasureS........... Pam EEE Summary of F-ratios from Analyses of Eighty Behavioral Measures. cu cusssssssnsvnnvenssnsssnsasnse Summary of Means (and Standard Errors) from Analyses of Eighty Behavioral MeOaSUrCS cvsernmtvunsnsmmovsnnnmurnessssnsns cseceene Summary of Final Rotated Factor Matrix (22 FACLOTS) et eeeeesaecnsssonnssnnonss PREG MEN ERE Summary of Functional Changes in Workers Exposed to Inorganic Lead. isvivivivus FREES 18 19 21 21 23 25 26 28 34 42 46 53 62 1 em ia FINAL REPORT ON THE BEHAVIORAL EFFECTS OF OCCUPATIONAL EXPOSURE TO LEAD INTRODUCTION The health hazards associated with lead usage have been recognized since at least the first century B.C. when the Roman author Horace referred to lead as a 'pestilential and noxious metal" (see Hoover and Hoover, 1950). Today, the medical manifestations of lead poisoning are well documented (see especially Goodman and Gilman, 1965; Kehoe, 1972a; Lane, 1965; Zavon, 1964). The commonly occurring symptoms consist of alimentary, neuromuscular, and encephalopathic disturbances that are reflected as loss of appetite, constipation, nausea, abdominal colic, pain in muscles and joints, weakness, peripheral neuritis, tremor, wrist drop, intellectual defects, behavioral disorders, and central nervous system dysfunction (for a more complete discussion of the possible symptoms of lead poisoning, see Appendix A). Potential health hazards from industrial exposures are created in the United States by the use of over one million tons of lead each year, the release of hundreds of thousands of tons of lead into the atmosphere each year from automobile exhaust emissions, and the occu- pational exposure to lead of workers in at least 110 occupations (Jacobsen § Seiter, 1972; Table X-3, p. X-3). Recognizing the potential health problems associated with the industrial use of lead, employers have provided for the protection of their employees through the environ- mental monitoring of airborne lead as well as medical and biomedical monitoring of workers (see Appendix A for a full discussion of the methods used in protecting and monitoring the health of workers exposed to lead). In this regard, NIOSH has recommended as an industry standard that workers be exposed to worksite ambient air-lead concentrations no greater than 0.15 mg Pb/m3, determined as a time-weighted average of exposures over an eight-hour day (Jacobsen § Seiter, 1972). The work of some researchers, however, has suggested that this standard is too stringent (Ansi, 1969; Elkins, 1959, p. 49-57), whereas others recommend that a standard of 0.10 mg/m3 would be more appropriate, especially for workers exposed for more than 40 hours per week (Tsuchiya & Harashima, 1965). It is interesting to note also that the Soviet Union has suggested that exposure levels should not exceed 0.007 mg/m3; Soviet research involving conditioned reflexes indicates that American exposure levels are much too high (Stofen, 1968). Uncertainty concerning the maximum allowable exposure levels still exists because clear relationships among exposure levels, body burden of lead, and biomedical effects of lead have not yet been established. The effects of increasing body burden levels of lead on the functional capacity of an individual is particularly poorly understood. A great deal of clinical and laboratory research has been concerned with the etiology of lead poisoning and the physiological, biomedical, pharmacological, neurological, and symptomatological effects of lead. However, most of these studies have employed small groups of subjects, typically those with acute lead poisoning. Most studies have been descriptive in nature and have dealt only with the symptoms or clinical signs associated with lead absorption. Very few studies have systematically investigated the effects of lead on human performance or psychological processes; few have been concerned with the effects of long-term, low- level exposure to lead in adults; and few have measured large samples of workers or attempted to relate body burden of lead to the behavioral functions of adult workers. Thus, the nature and pathogenesis of work- performance decrements associated with lead poisoning have received little systematic study. Although certain studies indicate that excessively high body burdens of lead may result in psychological, intellectual, sensory, and neuromuscular dysfunction (see Appendix B for complete discussion of the behavioral effects of lead poisoning), there are few quantitative data from systematic investigations concerning the behavioral or functional effects of occupational exposure to inorganic lead (Repko, Corson, Morgan, in preparation). The purpose of the current study was to provide a quantitative assessment (measurement and evaluation) of changes in performance which could result from occupational exposure to lead. This goal was based on the expectation that man's performance of certain functions involved in occupationally meaningful tasks changes during the course of his long-term exposure to low levels of airborne lead, and that an appropriately sensitive battery of tasks could be used to measure and evaluate these changes in relation to concomitant changes in body burdens of lead, thus indicating the vulnerability of the workers' behavior to disturbances of lead poisoning. A second purpose of this study was to determine whether the measurement and evaluation of the behavioral functions of adult workers could provide a health-monitoring approach that is more sensitive and meaningful than either environmental monitoring of airborne lead, biological monitoring of workers, or medical monitoring of workers (see Appendix A). That is to say, an attempt was made to identify tasks which are sensitive to the effects of low body burdens of lead and which, therefore, might be useful as an early-warning device against lead poisoning. METHOD The research reported herein was conducted during an 18-month period from 29 June 1972 through 31 December 1973. The first 3 months of the research project were devoted to the development and pilot- testing of a multifactor test battery for the assessment of functional changes that result from exposure to inorganic lead. The data col- lection phase of the research project was completed during the 11- month period from 16 October 1972 through 2 November 1973; performance and behavioral test measurements, as well as clinical determinations, were obtained individually from a group of 428 workers. The final 2 months of the project were devoted to the analysis of the data and preparation of this report. DESCRIPTION OF STUDY POPULATION The subjects employed in this study were 428, physically normal, male and female volunteers from eight different industrial plants in three states. Of this total sample, 316 workers from three different plants constituted the experimental or lead-exposed group, while the remaining 112 workers from five other plants constituted the control or non- lead-exposed group. The individuals in the experimental group were all engaged in various aspects of the manufacture of storage batteries (lead-acid batteries). The workers in the control group, on the other hand, were not currently exposed to, nor had they ever knowingly worked with, inorganic lead. This latter group of workers was selected on the basis of (a) membership in the same national labor organizations as the workers in the experimental group, (b) living in a similar geographic location as the experimentals, and (e) working in a light manufacturing industry. In so far as possible and practical, the two groups of subjects were matched (according to a ratio of one control to three experimental workers) in terms of sex, age, race, education, geographic location, and length of continuous employment with a given company. An attempt was also made to select an equal number of subjects from each of three daily work-shifts, but matching along this dimension was not feasible because of the small number of workers available from the second and third work-shifts. Protection of Subjects In order to ensure that the subjects were properly informed, each volunteer was given a complete and comprehensive explanation of the study (describing the objectives, experimental procedures, and expected results of the research) by the principal investigators. It was explained that certain minimal elements of psychological and physical risk may be involved, and that no one was under any obligation to partici- pate in the research. After at least a 24-hr period, volunteers were given the opportunity to ask questions concerning the study and to express their desires concerning participation in the study. Although volunteers were allowed to withdraw from the study at any time, no one did so. A registered nurse (provided by the company where workers were being tested or by the Performance Research Laboratory) was always available during the time of performance testing and was responsible for obtaining blood samples from each worker. Each worker who volunteered for the study prior to the performance testing was asked to read and sign a statement regarding the purposes, risks, and confidentiality of the results of the study (the specific forms each worker was required to sign are attached to this report in Appendix I). In addition, each volunteer was asked to designate a physician--other than the company physician--to whom any significant behavioral or medical test results should be sent. Workers whose blood- lead level exceeded 80 micrograms per cent (ug%), and their designated physician, were notified directly by the National Institute for Occupational Safety and Health as to the results of their blood-lead determinations. Such a procedure was followed in order to preclude the possibility of a lead-poisoned worker remaining uninformed or untreated. GENERAL TEST PROTOCOL The cooperation of workers at each of the eight plants involved in this study was obtained through correspondence and subsequent meetings with representatives of the companies, and/or with officers of local and national labor unions representing the workers. The performance testing was conducted either within space provided by the company (near an entrance to the plant) or in nearby buildings provided by the labor union representing the workers from a given plant. The specific schedules of testing at each of the eight companies--at three geographic locations--are given in Appendix J. A general description of the events at each company is given in the paragraphs which follow. The initial activity at each location involved setting up the apparatus used in the behavioral test battery and the supplies and equipment used by the nurse. The next step was to coordinate with the plant nurse or labor union officer the scheduling of volunteers to be tested before and after each daily work-shift. During these initial steps in the procedure, the principal investigator was available to the workers individually for the purpose of answering questions regarding the study. On the day prior to testing, each subject was given a copy of the comprehensive personal-data questionnaire, which was to be filled out prior to the time of testing, and two polypropylene containers in which the subject was to place his urine samples; both of these urine containers and the completed questionnaire were to be returned to the experimenters at the time of testing. Five or fewer subjects were scheduled to report for testing at the same time (the tests were administered so as to allow the concurrent testing of groups of five individuals) and approximately 2 to 2 1/2 hr were allotted for the testing of each group of subjects; between one and four groups were tested during each day of testing. Testing was scheduled at the beginning or end of the workers' work-shift so as not to interfere with their normal work schedule. At the beginning of the testing period each subject was required to complete the necessary consent and release forms. Performance testing was then conducted, and a blood sample was collected in a 10 ml heparinized, lead-free Vacutainer. Each worker was paid ten dollars for his participation in the study. General descriptions of the behavioral test battery, including the modified Multiple Task Performance Battery (MIPB; see Alluisi, 1969; Alluisi & Chiles, 1967; Chiles, Alluisi, §& Adams, 1968; Morgan & Alluisi, 1972), the performance measures, and the procedures involved in the blood and urine clinical analyses are given in the following sections. More comprehensive and detailed descriptions, however, are provided in Appendices C and E, respectively; in addition, a comprehensive description of the full-scale MTPB is given in Appendix D. TESTING OF WORKERS A total of 12 behavioral tests and a comprehensive personal-data questionnaire were selected for use in this research. Each instrument was chosen on the basis of its potential usefulness in measuring a behavioral function that might be expected to change as a result of increases in the body burden of lead. A review of the literature dealing with the behavioral and biologic effects of lead provided a list of symptoms which typically occur in cases of lead poisoning (Repko, et al., in preparation). Based on this review, tasks which appeared to be sensitive to such symptomalogical changes were then selected for use in the test battery. The core of the test battery consisted of five tasks from the Multiple Task Performance Battery (MIPB) of the Performance Research Laboratory. These tasks provided measurements of watchkeeping, vigilance, and attentive functions, sensory-perceptual functions, memory functions, and time-sharing functions. For the purpose of the current research project, the use of the MIPB was modified so that reliable measurements could be obtained during a 1-hr period of testing; thus, about half of the total testing period was required for the performance of these tasks. In addition to the functions assessed with MTPB tasks, other sensory, psychomotor, and psychological functions were assessed by tests of the following: (a) visual acuity, (b) auditory acuity, (ec) tremor, (d) muscular strength, endurance and recovery, (e) eye-hand coordination, (f) immediate recall (memory), and (g) mood or affect. These seven tasks were scheduled so that each of five subjects could be tested on each test during the second hr of the testing period. Table 1 provides a summary of all 12 tests in terms of the functional category assessed by the test, the specific name of the test, and the approximate time required for its administration. Table 1 Summary of Tests Included in the Comprehensive Behavioral Test Battery Test Specific Functional Time Area Instrument Category Tested Required Signal Detection Warning-Lights Watchkeeping 10 min Blinking-Lights and Probability Monitoring (MTPB) Pattern Target Identifi- Sensory-Perceptual 20 min Discrimination cation (MIPB) Mental Arithmetic Arithmetic Com- Intellectual 20 min putations (MTPB) Visual Acuity Bausch & Lomb Sensory 5 min Ortho-Rater Auditory Acuity Maico Audiometer Sensory 10 min Tremor SAM Hand Neuromuscular 5 min Steadiness Test Muscular Strength, SER Apparatus Neuromuscular 10 min Endurance, § Recovery Eye-Hand Coordination Michigan Eye-Hand Neuromuscular 5 min Coordination Test Immediate Recall Digit-Span Intellectual 5 min Subjective Feelings MAACL Psychological 5 min Tasks of the MTPB The MTPB tasks as modified for use in this study were essentially identical to those employed previously in investigations of the effects of alcohol and altitude on behavior and in the selection of air traffic controller trainees (cf., Chiles & Jennings, 1970; Jennings, Chiles § West, 1972). The tasks were displayed on each of five identical operator panels (one for each member of a 5-man worker group) similar to the one shown schematically in Figure 1. PROBABILITY MONITORING TARGET CODE-LOCK IDENTIFICATION A \ SOLVING NO J 1 x x 7 \ \ Et 1 Lz. J 1 RE ®® BR &@X © ® ® oO ~® ®® ® XR jd 1 3 3|7,+0]|9|-[3]|5] itd I ] \ 7 3X L 2 — I \ — 1 WARNING -LIGHTS \ ARITHMETIC J BLINKING -LIGHTS _| MONITORING COMPUTATION MONITORING Figure 1. Schematic diagram of the front view of a modified MTPB operator panel. Letters in circles represent indicator lights, A--amber, B--blue, G--green, and R--red; the smaller circles with crossing diagonals represent push buttons. The first of the watchkeeping tasks was presented by a pair of warning-lights, one green and one red, located on the extreme left of the panel. This task required that the worker respond to the lighting of a red light or the unlighting of a green light. Located on the extreme right of the panel was a pair of vertically arranged amber lights which flashed alternately at an over-all rate of two flashes per sec. This task, blinking-lights monitoring, required that the subject respond to a cessation of the alternation of the two amber lights by pressing the button underneath the two lights. The third watchkeeping task, probability monitoring, was displayed along the top of the operator's panel and consisted of four semi-circular scales, each with a pointer which normally rested at zero (the vertical or 12 o'clock position). The critical signal was an introduction of a bias which shifted one of the pointers by approximately 20 scale units (1/5 of the scale) to the right or to the left. Each worker was required to detect this shift and press the appropriate button under the meter in question. Critical signals were presented at an over-all rate of 72 signals per hr for each of these watchkeeping tasks. Inter-signal intervals were scheduled randomly and independently for each task. The target identification task (TID), was presented to the worker by a 4-inch square array of 36 close-butted lights which form a 6 by 6 matrix used to present "metric histoforms.'" Each problem consisted of the sequential presentation of two metric histoforms for 5 and 2 sec, respectively. The worker was required to report whether the two histoforms were the same or different and to respond by pressing the appropriate push button located to the left of the TID display. Knowledge of results was provided to the subject by a blue indicator light which was illuminated above the correct response button just prior to the presentation of the next problem. The task was force- paced at a rate of two problems per min. An amber light on each panel provided a 30-sec warning or ''ready' signal prior to the beginning of the first problem. The arithmetic computations (MATH) task required that a worker add two, 2-digit numbers and then subtract from that sum a third 2-digit number. The answer was indicated by manipulation of four decade thumb switches, located immediately to the right of the numerical indicators, and a push button just to the left and slightly above the switches. If the answer were correct, a blue indicator was lighted as the problem was removed and prior to the presentation of the next problem. The task was force-paced at a rate of three problems per min during the task presentation. The beginning of this task presentation was also signaled by an amber light which was lighted 30 sec prior to the first problem. In this modified version of the MIPB, workers were required to time-share the various tasks so that they were responsible all of the time for the three watchkeeping tasks (warning-lights, blinking-lights, and probability monitoring), but only part of the time for each of the other tasks (target identification and arithmetic computations). Thus, the relative demands on performance during a 1l-hr period were varied from low to medium to high depending on whether the watchkeeping tasks were presented alone or with one of the other tasks. | The basic 1-hr task program is shown in Table 2. As indicated, there were 5 min of preliminary instructions about the tasks of the MIPB, followed by 5 min of low-demand performance (monitoring tasks only) and 20 min of medium demand performance (monitoring and target identification). This sequence of testing was then repeated for a second 25 min during which the arithmetic computations task was used in place of the target identification task so as to provide for 20 min of high-demand performance. Visual Acuity The near and far visual acuity of each worker was determined separately for his right and left eyes. As shown in Figure 2, these measures were obtained individually for each subject by means of a Bausch and Lomb Ortho-Rater, Type 71-21-31. Tests of near acuity of the right eye, near acuity of the left, far acuity of the right eye, and far acuity of the left eye (Ortho-Rater slides N-2, N-3, F-4, and F-5, respectively) were counterbalanced in order to control for effects due to practice. Standard procedures for use of the Ortho-Rater were Table 2 Basic 1-Hour Task-Performance Schedule 5-Minute Interval in Each 1-Hour Period Performance Task T 2 3 4 5 6 7 8 9 10 11 12 Blinking-Lights Monitoring ~ X X X X X X X X X X wn ~~ — wn Warning-Lights Monitoring - X X X xX X § X X XX X o + Probability Monitoring A X ¥ X XX 3 X X X X X 2 + Target Identification 5 X X X X 5 Arithmetic Computations X X X X Level of Demand 2 © © © oO = 5 eh Wm Qo [9] [5] Q QQ Oo ~ ~ eH ~ —- ES == 5 S © TE § FE employed throughout this test. Since this was a test of absolute visual acuity, testing was performed without visual correction. The average duration of this test was approximately 5 min. Auditory Acuity Two assessments of auditory acuity were made for each worker. Initial threshold values were acquired by means of a Maico Audiometer, Model F-1, for both left and right ears at frequencies of 500, 1000, 2000, 4000, and 8000 Hz (the earphones were '"Calibrated Audiometric Headset Noise Barriers,' Model M-7, which were fitted with Maico, Circumaural, Air Seal cushions to attenuate the ambient noise levels of the testing situation). A single tone-decay test was then made on the ear in which, and using the frequency at which, the highest threshold value was recorded. As shown in Figure 3, these tests were made individually for each subject using the standard procedures for audiometric testing. It should be noted that threshold tests were conducted without the use of a sound chamber and with an ambient background sound-level of between 65 and 80 dBA. Tremor Tremor was measured in conjunction with muscular strength, endurance and recovery in the following manner: tremor was tested in both the preferred and non-preferred hands, then strength, endurance, and recovery (SER) were tested for the preferred hand only, and finally, the tremor test was repeated with each hand. Both tasks were performed at a single testing station and as little time as possible was allowed to elapse between tremor and SER tasks. Figure 2. Photograph of the visual acuity test showing the Ortho- Rater, test subject (seated), and experimenter. Figure 3. Photograph of the auditory acuity test showing the Maico Audiometer, test subject (right), and experimenter (left). 10 The test of tremor used in this study was similar, if not identical, to the SAM Arm-Hand Steadiness Test produced by the Department of Psychology, AAF School of Aviation Medicine (Melton, 1947, p. 501-557). The basic dimensions of the apparatus, including stylus and target, were adapted from Model CM103A4 of the SAM Arm-Hand Steadiness test, and the pro- cedures in administering the test were the same as those employed by Melton (1947). As shown in Figure 4, the worker was seated in the chair and positioned with his preferred shoulder directly in front of the apparatus so that he had room to fully extend his preferred arm. The subject was required to insert the stylus into a 1/4 in hole and hold it there for 1 min. This procedure was repeated for the non-preferred hand, at the end of which the worker performed the SER tasks. Immediately upon the cessation of the SER tasks, the tremor task was repeated in exactly the same manner and order (preferred hand, non-preferred hand) in which it was performed originally. Strength, Endurance, and Recovery The apparatus for this task was a portable ergometric system which provided for a dynamic input from the worker and a dual output of information to the subject (a meter display) and the experimenter (a permanent recording). This system is one of a series of similar devices used in the research of Dr. Lee S. Caldwell of the Experimental Psychology Division of the U.S. Army Medical Research Laboratory (AMRL), Fort Knox, Kentucky (Caldwell, 1963). As shown in Figure 5, the worker was seated in the chair so that the hand-grip dynamometer was positioned on his preferred side. The hand-grip was adjusted at approximately the height of the worker's knee and at a depth such that his elbow formed a 90° angle. Each worker's SER was then recorded according to Caldwell's (1963) procedure: the subject was required to pull his original maximum strength; then, exactly 1 min later, he was required to pull, for as long as possible, a load equal to 50% of the original maximum strength; this was followed by a 1-min rest and then a final maximum strength response. Eye-Hand Coordination The test of eye-hand coordination used in this study was developed originally by Poock (1967) and later by Chaffin and his co-workers at the University of Michigan in their studies of the behavioral effects of the occupational exposure to low-levels of inorganic mercury (Chaffin, Dinman, Miller, Smith § Zontine, 1973). The apparatus used in this study was made by the Performance Research Laboratory according to specifications furnished by Dr. Donald Chaffin. 11 Figure 4. Photograph of the tremor test showing the testing apparatus, test subject (left), and experimenter (right). Figure 5. Photograph of the strength, endurance, and recovery test showing the support equipment (on table), hand dynamometer, test subject (seated), and experimenter. 12 Figure 6. Photograph of the eye-hand coordination test showing the test maze and recorder, test subject (seated), and experimenter. The apparatus consisted of a hole plate (on which inter-connecting lines form a maze pattern which the workers were required to follow in performing the task), a sounding board, a contact microphone, a tape recorder, and a stylus. As shown in Figure 6, the worker was seated facing the apparatus and was required to grasp the stylus in his pre- ferred hand. He was then instructed to insert the stylus into each of -the 119 holes in the hole plate in the order indicated by the black lines, proceeding as quickly as possible without missing any holes; this procedure was then repeated for the non-preferred hand. The sound of the stylus striking the sounding plate beneath the hole plate was sensed by a contact microphone and recorded on a tape recorder and the latency between successive sounds was later scored by use of a digital computer. Digit-Span Each worker was individually instructed to listen to, and then repeat (in the same sequence), a series of single-digit numbers read aloud by the experimenter. The experimenter began by reading a series (Trial 1) of three numbers. If the worker was able to correctly repeat the series, a sequence of four numbers was then presented. For every correct repetition of a series by the worker, a subsequent sequence was presented, in which the number of digits was increased by one unit to a maximum of nine digits. Whenever the worker answered incorrectly, 13 a second series (Trial 2) was presented which contained the same number of digits as occurred in the previous (incorrect) trial. If the second trial of a series was repeated correctly, the procedure continued, until two trials of a given series were missed. The average duration of the test was approximately 5 min. Multiple Affect Adjective Check List The Multiple Affect Adjective Check List (MAACL), developed by Zuckerman and Lubin (see Zuckerman, 1960; Zuckerman, Lubin, Vogel, § Valerius, 1964) and published by the Educational and Industrial Testing Service, San Diego, California, was also employed in this study. The MAACL consisted of a list of 132 adjectives, for which each worker was required to check those words which described how he felt at the time of testing. Although no time limit was given, the MAACL was usually completed within 5 min. Personal-Data Questionnaire A comprehensive demographic, medical-history, and job-satisfaction questionnaire was used to obtain pertinent background information on each worker. This questionnaire is attached to this report in Appendix I. On the day prior to performance testing, each worker was given a copy of the questionnaire and requested to complete it at their convenience and return it at the time of testing. The major thrust of this part of the study was to obtain information concerning the medical history, the number and types of accidents and illnesses incurred by workers, and the medically-related domestic and social consequences of working in lead-laden atmospheres. In addition, the questionnaire included several questions related to each worker's subjective feelings of job satisfaction. CLINICAL DETERMINATIONS Blood and urine samples were obtained individually from each worker at the time of performance testing. In addition, confirmatory blood samples were collected later from individuals whose blood-lead levels exceeded 80ug% in the initial sampling. The subject's blood sample was collected in a 10 ml 'lead-free' Vacutainer (Becton-Dickinson Co.) from which approximately 1.0 ml was immediately decanted into a 12 x 75 mm polypropylene test tube. This small test tube of blood was immediately frozen to inhibit the breakdown of delta-aminolevulinic acid dehydrase (ALA-D), while the remaining sample of Vacutainer blood was sealed and stored under normal refrigeration prior to delivery to the Laboratory. The two 150 ml polypropylene containers used for each subject's urine sample were prepared in the following manner: the containers were washed, rinsed with distilled water, washed with 1:1 nitric acid, rinsed several times with glass-distilled/deionized water and 14 air dried. To one of these containers was added 1.0 ml of glacial acetic acid which brought the urine pH to approximately 2.0, thereby inhibiting the breakdown of delta-aminolevulinic acid (ALA). The other container contained 1.0 ml of a 1.3% solution of sodium carbonate which gave a urine pH of approximately 8.0, required to inhibit the breakdown of coproporphyrin (N.A.S., 1972). Upon receipt of the blood and urine samples by the Laboratory, all samples were refrigerated, with the exception of the small test tube of frozen blood which was placed in a freezer. The analyses were performed in the following order: hematocrit, blood ALA-D, urine ALA, urine coproporphyrin, blood lead and urine lead. A brief description of the methodology involved in each of these determinations is provided in the paragraphs which follow; detailed descriptions of the clinical methodologies are provided in Appendix E. Each of the measures chosen was based on their respective sensitivity to long- or short-term exposure to inorganic lead (see Appendix A for biological monitoring methods; see also Zielhuis, 1971). During each series of analyses, appropriate standard curves were run. When instrument drift was evidenced by periodic analysis of the standards, instruments were recalibrated and the unknowns were reanalyzed. Blood Hematocrit Blood hematocrits were determined in duplicate using standard hemat- ocrit capillaries. The average value of the duplicate analysis was reported for each sample. Blood delta-Aminolevulinic Acid Dehydrase (ALA-D) This determination was performed according to the method of Bon- signore, Calissano, and Cartasegna (1965) as modified by Weissberg, Lipschutz, and Oski (1971). Basically the method consisted of adding an excess of the ALA-D substrate, delta-aminolevulinic acid (ALA), incubating the mixture for one hr and then colorimetrically deter- mining the amount of porphobilinogen which had been enzymatically synthesized. The extent of porphobilinogen formation then served as an indicator of the enzymatic activity of the blood ALA-D. Urine delta-Aminolevulinic Acid (ALA) The determination of urine ALA was performed by the method of Mauzerall and Granick (1956) as modified by Davis and Andelman (1967). This consisted of double ion-exchange column chromatography to remove interfering substances, followed by a colorimetric analysis of the ALA. Urine Coproporphyrin Urine coproporphyrin determinations were performed according to the method of Schwartz, Zieve, and Watson (1951). This consisted of extracting the coproporphyrin from urine with an organic solvent, removal of interfering substances, and re-extraction of the coproporphyrin from the organic solvent into dilute hydrochloric acid. The coproporphyrin levels in the acid solution were then determined by fluorometry. 15 Blood Lead Blood lead determinations were performed according to the method of Hessel (1968). This consisted of extracting the blood lead, which had previously been chelated and thus rendered soluble, into an organic solvent. The organic solvent in turn was analyzed for its lead content by atomic absorption spectroscopy. Urine Lead The method of Yeager, Cholak, and Henderson (1971) was selected for this determination because of its utilization of atomic absorption spectroscopy and because this particular method eliminated interferences from iron, copper or zinc. As with the blood lead analysis, this consisted of extracting chelated lead into an organic solvent followed by atomic absorption determination of the resulting lead concentration. 16 RESULTS STUDY GROUPS As indicated previously, a total of 428 industrial workers served as subjects in one of two primary groups; namely, (a) the experimental group--316 workers who were exposed to inorganic lead in their jobs, and (b) the control group--112 workers who were not and had never been exposed to lead in their jobs. However, for a variety of different reasons, it was impossible to collect a complete set of data from each of these subjects. Some of the analyses described below included data from fewer than 316 experimental and/or 112 control subjects. In those cases where data were missing, the analyses were computed on the basis of all available data, and a notation has been made as to the number of observations included in each analysis. An attempt was made at the outset of the study to match the con- trol group to the experimental group in terms of sex, race, workshift, age, body build (height and weight), education, and duration of employ- ment. Since subjects were selected strictly on a voluntary basis, perfect matching along each of these dimensions was not achieved. In addition, since manufacturing plant Locations 1 and 2 were geograph- ically similar, and since no compatible control industry was available at plant Location 2, the controls for these two experimental groups (1E and 2E) were all obtained at Location 1 (1C); both experimental subjects (3E) and suitable controls (3C) were available for testing at Location 3. Demographic summaries of the experimental and control groups are provided in Tables 3 and 4. The data presented in Table 3 give the percentage distributions by sex, race (white, black, and Latin American), and workshift (first, second, or third) for the workers tested at each of three geographic locations and for the combined experimental and control groups. These data show that the percentage of workers within each main group was approximately similar. The only notable difference was that approxi- mately 12% more of the experimental subjects were drawn from the second workshift and a correspondingly large percentage of controls were drawn from the first shift. It is evident, however, that both subjects groups consisted mainly of white males drawn from the first daily workshift. The data in Table 4 provide statistical descriptions of the age, height, weight, level of education, and length of employment of each of the subject groups. Given for each of these parameters are the mean, median, mode, range, and standard deviation; also note that the number of missing cases (i.e., subjects not providing the requested information) is denoted as 'Missing Data.'" From these data it is clear that the combined experimental and control groups were closely matched in all categories except the number of years a person worked within the same industry. This category produced the largest discrepancies between the experimental and control groups and among the different location groups. The mean number of years worked in each of the three storage battery companies were 3.42, 15.94, and 6.18 17 Demographic Summary of Experimental and Control Groups in Terms of Sex, Race, and Workshift TABLE 3 Experimental Groups Control Groups 1E 2E ZEB TOTAL 1C IC TOTAL NUMBER (In Each Group) 80 110 126 316 63 49 112 SEX (Per Cent) Female 10.0 13.6 2.4 ‘8.5 20.6 2.0 12.5 Male 90.0 86.4 97.6 91.5 79.4 98.0 87.5 RACE (Per Cent) White 82.5 97.3 90.5 90.8 87.3 98.0 92.0 Black 17.5 2.7 3.2 6.6 12.7 2.0 8.0 Latin American 0.0 0.0 6.3 2.5 0.0 0.0 0.0 WORKSHIFT (Per Cent) First 46.20 73.60 65.1 63.3 77.8 71.4 75.0 Second 41.20 21.80 20.7 26.3 9.5 20.4 14.3 Third 12.50 4.50 14.3 10.5 12.7 8.1 10.7 18 TABLE 4 Demographic Summary of Experimental and Control Groups in Terms of Age, Height, Weight, Education and Employment Experimental Groups Control Groups 1B 2E 3E TOTAL 1C 3C TOTAL NUMBER (In Each Group) 80 110 126 316 63 49 112 AGE (Years) Mean 31.59 41.69 34.68 36.45 37.82 39,12 38.40 Median 29.00 43.83 33.00 35.25 39.25 37.00 38.80 Mode 25.00 44.00 18.00 25.00 39.00 35.00 39.00 Range 19-62 21-59 18-64 18-64 18-58 20-60 18-60 Standard Deviation 0.17 10.18 12.56 11.75 10.27 11.35 10.78 Missing Data 9 2 0 11 1 0 1 HEIGHT (Inches) Mean 68.99 69.17 68.81 68.98 68.79 68.82 68.80 Median 69.00 69.56 68.94 69.14 68.92 68.29 68.64 Mode 68.00 70.00 69.00 69.00 68.00 66.00 68.00 Range 66-76 60-76 62-76 60-76 60-75 61-77 66-77 Standard Deviation 3.44 2.83 2.96 3.04 3.38 3.34 3.36 Missing Data 11 4 2 17 2 0 2 WEIGHT (Pounds) Mean 167.41 170.25 170.62 169.72 169.65 176.52 172.62 Median 164.00 169.75 163.25 165.14 172.75 178.00 174.58 Mode 150.00 160.00 145.00 150.00 160.00 180.00 180.00 Range 115-230 105-225 117-270 105-270 94-270 127-270 94-270 Standard Deviation 25,91 23.50 32.07 27.93 34.81 30.41 33.16 Missing Data 9 8 3 20 0 1 1 EDUCATION (Highest Grade Completed) Mean 11.24 10.67 10.40 10.69 10.72 10.29 10.53 Median 11.74 11.58 10.75 11.55 11.19 10.75 11.04 Mode 12.00 12.00 12.00 12.00 12,00 12.00 12,00 Range 7-16 6-15 3-17 3-17 7-14 5-14 5-14 Standard Deviation 1.90 2.00 2,25 2.11 1.68 2.02 1.85 Missing Data 9 2 2 13 2 1 3 EMPLOYMENT (Years in Same Industry) Mean 3.42 15.94 6.18 9.01 12,53 13.22 12.84 Median 2:29 19.71 3.44 4.64 14.00 10.08 11.00 Mode 1.00 25.00 1.00 1.00 1.00 5.00 5.00 Range 1-29 1-25 1-25 1-29 1-31 2-29 1-31 Standard Deviation 4.08 9.24 6.09 8.79 8.69 8.45 8.59 Missing Data 9 1 0 10 1 0 1 19 years of continuous employment, respectively, with an overall mean of 9.01 (SD = 8.79) years. On the other hand, the number of continuous years of employment in the other industries from which the control groups were drawn were essentially the same at Locations 1C and 3C. These data indicate that while parameters such as age, height, weight, and education seem to be fairly constant between the two study groups, the average control workers had worked within the same industry for a longer period (X = 12.84, SD = 8.59) than had the average worker in the lead industry (X = 9.01, SD = 8.79). CLINICAL MEASURES In reporting the results obtained with the biomedical indices of the body burden of lead, the following abbreviations will be used hereafter in this report: blood lead, in micrograms per cent, will be designated as PbB; urine lead, in micrograms per cent, as PbU; delta-aminolevulinic acid in the urine, in milligrams per cent, as ALA; aminoleuvilinic acid dehydrase in the blood, in units of enzyme activity, as ALA-D; and urinary coproporphyrin in micrograms per cent, as CPU. Prior to conducting any of the assays for this study the Laboratory underwent an evaluation by the Bureau of Community Environmental Management (BCEM), Department of Health, Education, and Welfare, Cincinnati, Ohio, with respect to the accuracy of its PbB determination. It was found that the obtained values were within + 3 per cent of the known values--the BCEM Laboratory considers values within + 15 per cent of known values to be acceptable for their monitoring program. A copy of their report is attached as Appendix L. It should be noted also that two sets of PbB values were obtained (the second being a confirmatory assay) for those individuals whose initial PbB determina- tion was greater than 80ug%. The results of analyses comparing the initial PbB determinations with the confirmatory determinations are given in Table 5. It can be seen from the table that the values obtained with the two samples were significantly correlated (r = .96, p < .01); a t-test of the difference between the paired observations was not significant. Thus, the "test-retest reliability of the procedures employed was apparently quite high. Also summarized in Table 5 is a comparison of the independent PbB determinations, based on samples drawn from workers at plant Location 1E, conducted by this Laboratory and the monitoring laboratory employed by the company at Location 1E. (Subsequent to our receiving the list of PbB determinations, company officials cancelled all communications between their company and this Laboratory; therefore, the methodology employed in their PbB determinations was not ascertained. 20 TABLE 5 Summary of Analyses for the Duplicate Blood-Lead Determinations Within and Between Laboratories Standard Standard Group Mean Deviation Error t r Within Laboratories] Initial Sample 96.44 32.15 2.714 0.75 0.96% Confirmatory Sample 94.40 36.35 0 ===== emeee amen Between Laboratories’ Study Sample 59.90 17.82 0.750 9.92%* 0,89%** Company Sample 52.46 16.37 ~~ e-=== mmeee ema ly = 25 Paired observations; 2y = 79 Paired observations; *p < .01, df = 23; **p < .01, df = 78; ***p < 01, df = 77 TABLE 6 Rate of Decomposition of ALA-D in Frozen Human Blood Mean Percent Standard Day Decomposition Error 0 - - 4 21.1 +2.0 7 29.8 +2.5 11 34.4 ¥1.1 14 35.1 ¥1.9 18 42.0 “1.1 21 44.6 +2.4 25 48.9 *2.1 28 49.8 +1.8 33 54.0 *1.5 leach mean represents nine subjects with each subject serving as his own control. Subjects showed a PbB range of 6 to 17ug% and a hematocrit range of 39.80 to 49.20. 21 It can be seen that although there was a significant difference between the paired observations from this laboratory and theirs (t = 9.92, p < .01), the correlation between the two groups was quite high (r = .89, p < .01.) It should be noted that their PbB determinations were approximately 12% lower than those values obtained by this Laboratory. This difference is only slightly larger than the previously reported +10% variability in PbB determinations (Zielhuis, 1971). The significant correlation between two sets of determinations indicates again that the procedures employed by this Laboratory are highly reliable. Since it is well known that certain enzymes will undergo a loss of biological activity, even though maintained in a frozen medium, the frozen blood samples were examined to determine if this were happen- ing in the case of ALA-D. When it was found that significant decom- position was occurring, a kinetic study was performed in order to determine the rate of decomposition of ALA-D. This was accomplished by dividing each blood sample from each of nine normal subjects into ten portions, conducting immediate determinations of PbB, hematocrit, and ALA-D activity on one aliquot, and freezing the remaining aliquots. At three and four day intervals a sample of each subject's frozen blood was thawed and assayed for ALA-D activity. The results showing the rate of decomposition of ALA-D in frozen human blood are presented in Table 6 and shown graphically in Figure 7*. These results were used to correct the obtained ALA-D value for each subject by accounting for the spontaneous loss of enzyme activity during the period which had elapsed between the time of sampling and the time of analysis. Distribution and Intercorrelation of the Clinical Measures The data presented in Table 7 provide a statistical summary of each clinical measure for both the experimental and control groups in terms of the mean, standard deviation, standard error, and range. It can be seen that for the experimental (lead-exposed) workers the values ranged from within normal levels (i.e., < 40ug% to those far exceeding dangerous limits (i.e., > 100ug%; for a discussion of diagnostic levels, see Lane, Hunter, Malcolm, Hudson, Browne, McCallum, Thompson, deKretser, Zielhuis, Cramer, Barry, Goldberg, Beritic, Vigliani, Truhant, Kehoe, and King, 1968 p. 501). On the other hand, the range of values for the control group was well within normal limits; in fact, the distribution of PbB values for the controls is normally distributed around a mean of 15.07ug%. Similarly, each of the remaining biomedical indices shows a characteristically large difference between the means of the two study groups. * Figure 7 and all subsequent figures are grouped for convenience at the end of this report, just prior to the appendices, on pages 91 to 117. 22 TABLE 7 Statistical Summary of the Distribution of Clinical Measures in the Study Groups Observed Urine Urine Urine Blood Blood Lead Lead ALA CPU ALA-D Experimental Group (N = 316) Mean 63.09 123.99 0.885 66.66 21.81 Standard Deviation 21.68 121.92 1.153 72.68 13.54 Standard Error 1.22 6.86 0.065 4.09 0.76 Range 23-243 4-1247 0.0-6.8 0-550 0.0-120.4 Control Group (N = 112) Mean 15.07 19.74 0.029 6.39 75.12 Standard Deviation 7.91 10.64 0.089 10.99 30.78 Standard Error 0.75 1.01 0.008 1.04 2.91 Range 0-44 6-64 0.0-0.7 0-60 0.0-188.3 Total Both Groups (N = 428) Mean 50.52 96.71 0.661 50.89 35.76 Standard Deviation 28.45 114.45 1.061 68.06 30.53 Standard Error 1.38 5.53 0.051 3.29 1.48 Range 0-243 4-1247 0.0-6.8 0-550 0.0-188.3 23 In order to examine the functional changes which result from systematic increases in the body burden of lead, the data of the experimental group were divided into eight subgroups with PbB values of (1) 39ug% or less, (2), 40 to 49ug%, (3) 50 to 59ug%, (4) 60 to 69ug%, (5) 70 to 79ug%, (6) 80 to 89ug%, (7) 90 to 99ug%, and (8) greater than 100ug%. It should be noted that although these groupings are somewhat arbitrary, they were selected for two important reasons; (a) to provide a larger continuum of PbB categories than is provided by the four categories of Lane, et al. (1968) and (b) to keep the number of observations or subjects in each group reasonable and statistically adequate. A histogram showing the number of experimental subjects in each PbB subgroup is presented in Figure 8. Examination of this figure indicates that the PbB values are somewhat positively skewed toward the higher end of the "acceptable range,' between 40 and 80ug%. The incidence of workers showing PbB levels in either excessive or dangerous amounts (i.e., above 80ug%) includes approximately 18% of the total experimental group. A breakdown showing the means and standard deviations of the remaining four clinical measures (PbU, ALA, CPU, and ALA-D) within each PbB subgroup is given in Table 8. From these data it is clear that as the PbB values increase there is a con- comitant increase in the means for PbU, ALA, and CPU, and a decrease in mean ALA-D activity. Notice also that there is a tendency toward increased variability as the value of these measures increases. The degree of relationship was determined by computing inter- correlations of the various clinical measures. The five main measures, as well as the hematocrit reading for each worker and the expected PbB (EPbB) level, were also included in this correlational analysis. This latter value, the EPbB, was included on the basis of a recent National Academy of Science (1972) recommendation which indicated that this derived measure is useful because it takes into account the normal and observed hematocrits. Intercorrelations of these seven clinical measures for both the experimental and control groups are presented in Table 9. For the experimental group these correlations statistically confirm the relationships seen in Table 8. Specifically there is a statistically significant negative correlation (p < .01) between PbB and ALA-D. Moreover, all other intercorrelations are statistically significant (p < .0l in each case except the correlation between the hematocrit and CPU, where p < .05) except the correlation between the hematocrit and ALA-D (p > .10). For the control group, on the other hand, not all of the intercorrelations are significant. While the blood measures for this control group all correlate well among themselves, they do not correlate with either the ALA or CPU measures. PbU is the only urine measure which correlates signifi- cantly (p < .01) with any of the blood measures. There is no common clinical measure, however, which correlates with all other measures. A polynomial regression analysis was performed in order to determine the nature and degree of the relationship among several of these measures. The results of these analyses are presented in Figures 9 through 14, which show the linear and quadratic regression lines, their equations, 24 Means and Standard Deviations of the Clinical Measures Table 8 within each Experimental PbB Subgroup Urine Urine Urine Blood Lead ALA CPU ALA-D (1) Values Less than 39ug% Mean 45.94 0.232 17.56 31.19 Standard Deviation 29.68 0.331 12.73 21.80 N = 32 (2) Between 40 and 49ug% Mean 65.86 0.201 26.11 27.18 Standard Deviation 33.80 0.384 18.92 12.44 N = 56 (3) Between 50 and 59ug% Mean 86.93 0.599 48.17 22.76 Standard Deviation 43.05 0.952 55.67 10.09 N = 60 (4) Between 60 and 69ug% Mean 127.82 0.939 74.66 18.94 Standard Deviation 78.54 1.032 79.18 10.33 N = 62 (5) Between 70 and 79ug% Mean 188.98 0.281 99.69 16.95 Standard Deviation 199.00 1.173 68.77 10.13 N = 48 (6) Between 80 and 89ug% Mean 206.40 1.866 123.753 20.08 Standard Deviation 178.69 1.425 102.09 15.89 N = 30 (7) Between 90 and 99ug% Mean 186.35 2.080 111.12 15.38 Standard Deviation 93.21 1.754 63.64 9.18 N= 17 (8) Values Greater than 100ug% Mean 222.73 1.275 103.27 14.21 Standard Deviation 115.24 0.946 96.13 9.61 N =11 25 9¢ TABLE 9 Intercorrelations of Seven Clinical Determinations CLINICAL DETERMINATION CLINICAL Adjusted Observed Urine Urine Urine Blood DETERMINATION Blood Lead Blood Lead Lead ALA CPU ALA-D Exp.! Cont. > Exp. Cont. Exp. Cont. Exp. Cont. Exp. Cont. Exp. Cont. Hematocrit -0.460** 0.238% -0,222*%* {(,310** -0,155%** 0.213% -0.160** 0.011 -0.127* 0.075 -0.048 -0.342% Adjusted Blood Pb 0.932** (0.991** 0.414** 0.305%* 0.422** -0,001 0.388** -0.099 -0.240** -0,337* Observed Blood Pb 0.440** 0.312% 0.428** -0.012 0.435** -0.106** -0,293** -0,373* Urine Pb 0.340** 0.230% 0.432** 0.150 -0.243** -0.146 Urine ALA 0.708** 0,383** -0,163** -0.039 Urine CPU -0.243%** -0.073 lg yperimental Group, N = 316, df = 314; 2control Group, N = 112, df = 110; *p < .05; **p < ,01 and the F-ratios (from the analysis of variance of the regression) pertaining to ten correlations given in Table 9; namely, PbB and ALA-D, PbB and PbU (Figure 9); PbB and ALA, PbB and CPU (Figure 10); PbU and ALA, PbU and CPU, PbU and ALA-D (Figure 11); ALA-D and ALA (Figure 12); ALA-D and CPU (Figure 13); and CPU and ALA (Figure 14). It should be noted that while each of these ten relationships is characterized by a significant linear component (p < .001), the quadratic component is also significant (p < .001), in each case, as are the cubic and quartic components in some cases (a result which must be expected because of the large number of degrees of freedom involved in the equations; df = 1,315). Thus, predictability for this sample of data may be improved by using the higher order equations. The important finding here, however, is that ALA-D, PbU, ALA, and CPU concentrations may be significantly (p < .001) predicted for any given PbB concentration (see Figures 9 and 10), and similarly, each of the other biomedical measures may act as significant predictors (see Figures 11 through 14). PERFORMANCE MEASURES A total of 80 behavioral measures was obtained from the per- formances of 12 different performance tasks. A full description of each of the measures in terms of the specific behavior they represent (for example, latency, auditory threshold, or muscular force) and the descriptive nature of each measure (for example, mean response time, decibel value, or number of pounds) are given in Appendix C along with a discussion of their derivation. In addition, each measure is identi- fied by a reference number (i.e., 1 through 80) to assist the reader. For purposes of this section of the report, the measures are merely identified in the order of their reference numbers. All the data were reduced with the use of standard analytical procedures which are de- scribed adequately in other sources (see Baggaley, 1964; Winer, 1962; and Harmon, 1967). In the analysis of the performance data, four primary analysis techniques were employed; namely, (1) correlation, (2) multiple regression, (3) analysis of covariance (ANCOVA) or analysis of variance (ANOVA), and (4) factor analysis. Each of these techniques is discussed in the following paragraphs as it relates to the overall analysis of the data. A presentation of the results obtained with the 12 specific behavioral tests follows thereafter. The first step in analyzing these data involved the computation of intercorrelations among all 80 behavioral and six clinical measures; these computations were performed separately for the experimental and control groups. Within the context of this report, the important results to be interpreted are the correlations of the 80 behavioral measures with each of the clinical measures. These correlations are provided for both study groups in Table 10. A complete discussion and interpreta- tion of the specific correlations will be presented in later sections. The data were further analyzed by means of regression analyses in order to determine the relative contribution of several clinical and demographic parameters to the obtained behavioral scores. For each of the 80 performance measures, 10 independent measures were used 27 nN oo Table 10 Intercorrelations of Eighty Behavioral Measures with Six Clinical Measures of Body Burden of Lead CLINICAL MEASURES BEHAVIORAL Adjusted Observed Urine Urine Urine MEASURE Blood Lead Blood Lead Lead ALA ALA-D Exp.! Cont. > Exp. Cont. Exp. Cont. Exp. Cont. Exp. Cont. Exp. Cont. Warning-Lights (Red) (1) Latency -0.036 0.122 -0.029 0.116 -0.076 0.110 -0.039 -0.031 -0.027 -0.164 0.011 0.061 Warning-Lights (Green) (2) Latency 0.039 0.016 0.027 0.026 -0.007 -0.082 0.007 -0.114 -0.009 -0.190* -0.054 0.124 Blinking-Lights (3) Latency 0.062 0.074 0.061 0.057 -0.038 0.001 -0.071 0.010 -0.039 -0.055 0.034 0.168 Probability Monitoring (4) Latency 0.013 0.055 0.022 0.048 -0.008 0.039 0.068 0.049 0.047 -0.098 -0.058 0.180 (5) Correct Detections 0.085 -0.024 0.053 -0.015 0.238** -0.027 0.023 -0.036 -0.016 0.101 -0.058 -0.140 (6) False Responding -0.034 0.128 -0.022 0.126 -0.057 0.084 -0.071 -0.116 -0.063 -0.167 0.022 0.015 Target Identification (7) Accuracy 0.058 -0.104 0.073 -0.098 0.054 -0.058 0.085 0.088 0.018 0.145 0.020 0.063 (8) Attempted 0.034 -0.037 0.050 -0.030 0.052 0.018 0.076 0.086 0.021 0.161 -0.027 0.078 Arithmetic Computations (9) Accuracy -0.028 0.028 -0.054 0.041 0.017 0.154 0.061 0.153 0.021 0.202% -0.029 -0.210% (10) Attempted -0.058 -0.060 -0.073 -0.049 0.022 0.132 0.051 0.112 0.010 0.231% -0.056 -0.196* Warning-Lights (Red) Low an Latency 0.014 0.112 0.012 0.121 -0.069 0.057 -0.005 -0.067 0.010 -0.141 0.005 0.030 Med (12) Latency -0.016 0.194 -0.014 0.195% -0.130% 0.106 -0.055 -0.030 -0.062 -0.124 0.078 -0.044 High (13) Latency -0.038 0.096 -0.036 0.088 -0.030 0.103 -0.016 -0.023 -0.011 -0.156 -0.016 0.079 Warning-Lights (Green) Low (14) Latency 0.075 -0.009 0.049 -0.008 -0.012 0.035 -0.019 -0.050 0.041 -0.105 -0.003 0.117 Med (15) Latency 0.015 0.130 0.031 0.140 -0.007 0.060 -0.026 -0.043 -0.007 -0.140 -0.048 0.081 High (16) Latency 0.053 -0.054 0.038 -0.048 0.018 -0.077 0.003 -0.120 0.006 -0.138 -0.065 0.136 nN ©O Blinking-Lights Low (17) Latency 0.054 Med (18) Latency 0.059 High (19) Latency 0.085 Probability Monitoring Low (20) Latency 0.062 Med (21) Latency 0.035 High (22) Latency -0.003 Low (23) Correct Detections -0.035 Med (24) Correct Detections 0.003 High (25) Correct Detections 0.023 Low (26) False Responding -0.030 Med (27) False Responding -0.028 High (28) False Responding 0.010 Target Identification First 10 Minutes (29) Accuracy 0.045 Second 10 Minutes (30) Accuracy 0.061 First 10 Minutes (31) Attempted 0.031 Second 10 Minutes (32) Attempted 0.033 Arithmetic Computations First 10 Minutes (33) Accuracy -0.007 Second 10 Minutes (34) Accuracy -0.047 First 10 Minutes (35) Attempted -0.049 Second 10 Minutes (36) Attempted -0.064 0.030 0.114 0.054 0.113 0.049 0.011 0.056 0.000 -0.013 0.082 0.233% 0.025 -0.139 -0.043 -0.041 -0.026 0.088 -0.033 -0.027 -0.090 0.030 0.072 0.081 0.059 0.022 0.016 -0.050 -0.032 -0.017 -0.008 -0.019 0.008 0.045 0.089 0.026 0.068 -0.036 -0.069 -0.065 -0.077 0.023 0.114 0.032 0.111 0.044 0.005 0.085 0.000 -0.006 0.078 0.240% 0.017 -0.133 -0.039 -0.027 -0.027 0.101 -0.020 -0.013 -0.083 -0.016 -0.075 0.003 -0.071 -0.042 0.016 0.008 0.021 -0.012 -0.033 -0.064 -0.052 0.031 0.061 0.018 0.080 0.034 -0.002 0.042 0.001 0.023 0.084 -0.040 0.075 0.125 -0.001 -0.020 0.000 -0.017 0.033 0.090 0.036 -0.031 -0.070 0.026 0.007 0.153 0.143 0.144 0.111 -0.030 -0.076 -0.002 -0.001 0.058 0.085 -0.001 -0.022 -0.093 -0.031 -0.078 -0.048 0.074 0.082 0.051 0.091 0.062 0.056 0.056 0.043 0.033 0.037 -0.038 0.107 0.056 0.016 -0.248%** 0.000 -0.026 -0.123 -0.095 -0.108 0.156 -0.000 0.067 0.090 0.153 0.143 0.121 0.096 -0.048 -0.057 -0.014 -0.002 0.039 0.056 -0.031 -0.025 -0.023 -0.006 -0.076 -0.033 0.017 0.016 0.005 0.035 0.021 0.020 0.024 -0.003 -0 -0 -0 -0. -0 -0. -0 0. 0. .010 0 .062 0. .071 -0 101 -0 .047 -0 104 -0 .005 0. .000 0. .105 0. .178 0. .175 0. .118 -0. .206* -0. .048 0. «133 -0. .159 -0. .166 -0. «222% 0. 217% -0. 231* -0. .061 082 .013 .009 .039 .088 005 076 031 044 039 016 005 041 006 045 032 023 052 058 0.100 0.104 0.168 0.095 0.055 0.205° -0.196° 0.000 -0.159 0.038 -0.030 0.015 0.037 0.073 0.048 0.094 -0.216° -0.190° -0.196° -0.185° 0g TABLE 10 (CONTINUED) CLINICAL MEASURES BEHAVIORAL Adjusted Observed Urine Urine Urine Blood MEASURE Blood Lead Blood Lead Lead ALA CPU ALA-D Exp.! Cont.? Exp. Cont. Exp. Cont. Exp. Cont. Exp. Cont. Exp. Cont. Far Vision (37) Right Visual -0.014 0.068 0.006 0.059 -0.016 -0.112 0.091 0.094 0.079 0.035 -0.039 -0.013 Acuity (38) Left Visual -0.047 -0.043 -0.031 -0.029 -0.059 -0.121 0.042 0.043 0.022 0.017 0.068 -0.072 Acuity Near Vision (39) Right Visual -0.028 0.133 0.001 0.137 0.062 0.043 0.064 0.080 0.053 0.010 -0.036 -0.135 Acuity (40) Left Visual -0.084 0.149 -0.064 0.172 0.041 0.002 0.007 0.034 0.007 0.022 0.052 -0.216* Acuity Right Ear Threshold 500 Hz (41) Auditory 0.060 -0.045 0.046 -0.050 0.142* 0.040 -0.133* 0.176 0.005 -0.014 -0.110 -0.052 Threshold 1000 Hz (42) Auditory 0.108 -0.024 0.120* -0.023 0.204** 0.081 -0.104 0.154 0.063 -0.027 -0.145** -0.034 Threshold 2000 Hz (43) Auditory 0.072 -0.065 0.080 -0.055 0.124% -0.037 -0.104 0.079 0.010 -0.137 -0.163** -0.,050 Threshold 4000 Hz (44) Auditory 0.143* -0.002 0.180** 0.010 0.051 -0.029 -0.047 -0.010 0.074 -0.169 -0.153%%* 0.093 Threshold 8000 Hz (45) Auditory 0.181** -0.026 0.186** -0.020 0.038 -0.069 -0.031 -0.021 0.076 0.011 -0.156** -0.037 Threshold Ie Left Ear Threshold 500 Hz (46) Auditory 0 Threshold 1000 Hz (47) Auditory 0 Threshold 2000 Hz (48) Auditory 0. Threshold 4000 Hz (49) Auditory 0. Threshold 8000 Hz (50) Auditory 0, Threshold .042 .056 014 119% 120% Tone Decay First Trial (51) Duration of Tone -0. Second Trial (52) Duration of Tone 139% 0.056 Strength, Endurance and Recovery Original Strength (Sp) (53) Muscular Force 0.119* Endurance (E) (54) Muscular -0.069 Endurance Secondary Strength (Sj3) (55) Muscular Force 0.120% Strength Recovery (Rg) (56) Recovery -0.025 Impulse (I) (57) Impulse (Force X Duration) 0.046 0 0 .181 .134 .054 .069 .076 .194* +115 .146 .063 .106 «117 .009 0.032 0.028 0.009 0.130* 0.119* -0.154** 0.067 0.139% -0.071 0.139% -0.024 0.057 0.185% 0.137 0.057 0.078 -0.061 0.191% -0.129 -0.116 0.064 -0.084 0.104. 0.022 0.136* 0.131* 0.087 0.081 -0.028 -0.014 0.041 0.320** -0.105 0.261** -0.118** 0.110 0.104 0.057 -0.039 -0.113 -0.055 0.084 -0.128 0.007 -0.061 -0.054 '-0.104 -0.037 -0. -0. -0. =. -0. -0 -0 .058 .047 101 100 .097 .018 .018 046 016 060 .036 .041 -0. -0. -0. 0s .104 .040 .087 .180 136 092 .008 086 .160 .089 021 171 -0 -0 .005 .031 .025 .005 .048 .114%* «117% .042 .018 .001 .072 .040 -0 -0 125 +138 .204* «192% 033 .030 L112 .025 .089 .031 .040 .075 .063 .150%* .196** .148%* L141%* .085 .082 . 324% .080 .320%* .062 .178* 0.053 0.054 0.044 0.048 -0.007 -0.085 -0.008 0.084 0.053 0.140 0.040 0.096 ze TABLE 10 (CONTINUED) BEHAVIORAL MEASURE CLINICAL MEASURES Adjusted Blood Lead Observed Blood Lead Urine Lead Urin ALA e Urine CPU Blood ALA-D Exp. Cont Exp. Cont. Exp. Cont. Exp. Cont. Exp. Cont. Exp. Cont. Tremor: Pre-Test Trials Preferred Hand First 30 sec. (58) Muscular Control Second 30 sec. (59) Muscular Control Non-Preferred Hand First 30 sec. (60) Muscular Control Second 30 sec. (61) Muscular Control Tremor: Post-Test Trials 0.053 0.034 0.118% 0.086 Preferred Hand First 30 sec. (62) Muscular Control Second 30 sec. (63) Muscular Control Non-Preferred Hand First 30 sec. (64) Muscular Control Second 30 sec. (65) Muscular Control 0.005 -0.023 0.100 0.057 0.029 -0.006 -0.035 -0.003 -0.107 -0.062 -0.161 -0.048 0.055 0.042 0.115% 0.071 0.007 -0.027 0.110 0.062 0.055 0.031 -0.003 0.035 -0.083 -0.046 -0.137 -0.009 0.091 0.076 0.025 0.027 0.050 0.037 0.091 0.055 -0.057 0.04 -0.097 0.04 -0.038 0.11 -0.081 0.08 -0.056 0.00 -0.078 -0.02 -0.073 0.06 -0.067 6 1 2% 4 4 4 7 0.039 -0.128 -0.131 -0.080 -0.036 0.017 -0.013 -0.065 -0.020 -0.011 0.007 0.068 0.043 -0.004 -0.040 0.080 0.015 0.051 0.085 0.111 0.080 0.094 0.006 0.188* 0.143 -0.166** -0.147%** ~0,233%#% -0.199%* -0.157** -0);153%% -0.219** -0 ;151%% -0.049 0.099 -0.089 -0.150 -0.051 -0.054 -0.084 -0.239 Digit-Span Test (66) Immediate Recall 0.003 -0.110 -0.028 -0.089 0.070 -0.036 0.019 0.015 0.011 0.176 -0.038 -0.004 MAACL (67) Anxiety 0.049 0.057 0.065 0.057 -0.033 -0.062 -0.069 -0.041 0.063 0.056 0.060 -0.019 (68) Depression 0.099 0.080 0.100 0.078 0.004 -0.106 -0.013 -0.015 0.035 0.114 0.018 -0.057 (69) Hostility 0.046 0.150 0.048 0.146 0.018 -0.147 0.024 -0.014 0.026 0.045 0.088 -0.077 (70) Dysphoria 0.076 0.100 0.082 0.098 -0.003 -0.113 -0.034 -0.024 0.006 0.085 0.052 -0.055 Eye-Hand Coordination Preferred Hand (71) Total Responses 0.009 0.043 -0.010 0.040 0.038 0.221% 0.061 0.025 0.067 -0.145* 0.003 -0.157 (72) Latency 0.137* 0.050 0.138* 0.037 0.132% 0.004 0.002 -0.015 0.029 -0.141* -0.154** 0.196% (73) Latency 0.137* 0.049 0.142* 0.037 0.127* -0.020 -0.006 -0.018 0.021 -0.120* -0.159** 0.208* (74) Response 0.084 0.032 0.089 0.025 0.155** 0.001 0.008 -0.076 0.044 0.069 -0.157** 0.200% Variability (75) Response 0.083 0.030 0.089 0.023 0.153** -0.006 0.006 -0.075 0.042 0.076 -0.156** 0.204% Variability a Non-preferred Hand (76) Total Responses 0.001 0.077 -0.015 0.073 -0.022 0.053 -0.039 -0.009 0.031 -0.017 -0.011 0.172 (77) Latency 0.092 -0.109 0.061 -0.115 0.184** -0.070 -0.034 0.031 0.052 -0.074 -0.012 0.269** (78) Latency 0.095 -0.112 0.067 -0.117 0.193** -0.071 -0.026 0.027 0.060 -0.071 -0.121* 0.221% (79) Response -0.022 -0.179 -0.032 -0.186 0.151** -0.012 -0.066 0.052 0.078 -0.061 -0.170** 0.319** Variability (80) Response -0.021 -0.178 -0.030 -0.184 0.152** -0.,013 -0.064 0.050 0.079 -0.061 -0.170** 0.305** Variability le xperimental Group, N = 316, df = 314; 2control Group, N = 112, df = 110; *p < .05; **p < .01 ve TABLE 11 Summary of Normalized Regression Coefficients (BETA) from Ten Predictor Variables for Each of Eighty Behavioral Measures BEHAVIORAL MEASURES PREDICTOR VARIABLES Clinical Measures Demographic Measures Blood ALA-D Education Employment Height Weight Warning-Lights (Red) (1) Latency Warning-Lights (Green) (2) Latency Blinking-Lights (3) Latency Probability Monitoring (4) Latency (5) Correct Detections (6) False Responding Target Identification (7) Accuracy (8) Attempted Arithmetic Computations (9) Accuracy (10) Attempted Warning-Lights (Red) Low (11) Latency Med (12) Latency High (13) Latency -0.013 -0.081 0.029 -0.085 -0.030 -0.009 0.035 -0.001 -0.030 -0.070 -0.003 0.055 -0.040 -0.120 -0.009 -0.127 -0.059 -0.063 0.020 -0.084 -0.064 -0.013 0.101 -0.166 -0.118 0.149 0.092 0.071 N.C. 0.347%* 0.115 0.384%** 0.077 -0.146 -0.062 -0.053 0.059 -0.134 -0.019 -0. -0 -0. -0. 0. -0 0. 0. 0. 0. -0.172* -0. -0. 133 .074 152 103 046 037 129 137 094 088 081 139 0.009 -0.038 0,137 0.062 -0.112 N.C.2 -0.113 -0.034 0.009 0.026 0.090 -0.077 0.041 Se Warning-Lights (Green) Low (14) Latency Med (15) Latency High (16) Latency Blinking-Lights Low (17) Latency Med (18) Latency High (19) Latency Probability Monitoring Low (20) Latency Med (21) Latency High (22) Latency Low (23) Correct Detections Med (24) Correct Detections High (25) Correct Detections Low (26) False Responding Med (27) False Responding High (28) False Responding Target Identification First 10 Minutes (29) Accuracy Second 10 Minutes (30) Accuracy First 10 Minutes (31) Attempted Second 10 Minutes (32) Attempted -0.035 0.010 0.040 0.031 -0.054 0.007 -0.102 -0.046 0.001 0.065 0.061 0.029 -0.031 -0.047 -0.065 -0.014 -0.038 0.031 0.032 -0.024 -0.061 0.016 0.028 -0.085 0.012 -0.021 0.114 0.132 0.069 N.C. -0.180 -0.073 -0.043 -0.051 0.104 0.052 0.101 0.099 0.054 0.033 0.007 -0.024 0.022 -0.014 0.041 0.041 0.001 -0.080 -0.030 0.078 0.078 0.001 0.035 -0.139 -0.089 -0.142 -0.107 0.049 0.007 -0.025 0.003 0.131 0.062 0.063 -0.072 -0.086 -0.058 -0.012 0.034 -0.025 -0.017 0.003 0.095 0.070 0.144 0.052 -0.015 -0.066 -0.071 0.052 0.077 -0.005 -0.011 -0.061 -0.108 -0.019 0.087 0.043 0.031 N.C. -0.029 -0.005 0.010 0.068 -0.012 0.141 0.352** 0.377%% 0,281%% 0.236% 0.243% 0.263% 0.,318%% 0.229% 0.028 0.020 -0.070 0.188 0.156 0.262% -0.255* -0.213 -0.221* -0.186* -0.127 -0.098 -0.107 -0.126 -0.053 -0.042 -0.127 -0.090 -0.054 0.115 N.C. -0.014 -0.085 -0.160 -0.112 0.117 0.048 0.155 0.085 -0.021 -0.148 -0.073 -0.017 0.061 -0.015 -0.108 -0.011 -0.064 0.077 N.C. 0.014 -0.151 -0.089 -0.140 0.102 -0.012 0.066 N.C. -0.055 -0.063 -0.058 -0.141 -0.143 -0.134 -0.063 -0.201* -0.069 0.015 0.136 0.093 -0.040 -0.074 0.038 0.151 0.180* 0.086 0.083 -0.101 -0.064 N.C. 0.105 0.082 0.156 0.012 0.128 0.044 -0.033 -0.063 -0.066 -0.046 0.023 -0.011 -0.142 -0.068 -0.065 N.C. 9¢ TABLE 11 (Continued) PREDICTOR VARIABLES! BEHAVIORAL Clinical Measures Demographic Measures MEASURES Urine Urine Urine Blood Blood Age Education Employment Height Weight Lead ALA CPU Lead ALA-D Arithmetic Computations First 10 Minutes (33) Accuracy 0.026 0.097 -0.073 -0.034 -0.031 -0.267** 0. 327%% 0.128 0.084 0.037 Second 10 Minutes (34) Accuracy 0.047 0.084 -0.063 -0.086 -0.056 -0.194 0.360** 0.088 0.123 0.029 First 10 Minutes (35) Attempted -0.006 0.010 -0.049 -0.058 -0.026 -0.240%* 0.343*%* 0.095 0.097 -0.020 Second 10 Minutes (36) Attempted 0.011 0.090 -0.082 -0.078 -0.081 -0.172 0.39 5%= 0.063 0.051 0.022 Far Vision (37) Right Visual -0.095 0.040 0.051 0.001 -0.017 -0.223* 0.051 -0.063 0.028 -0.059 Acuity (38) Left Visual -0.111 0.035 0.010 0.041 0.087 -0.304%** 0.022 0.052 0.104 -0.035 Acuity Near Vision (39) Right Visual -0.036 -0.029 0.010 0.019 -0.007 -0.511%*%* 0.063 -0.101 N.C. N.C. Acuity (40) Left Visual -0.005 -0.071 0.020 0.002 0.095 -0.512%*%* 0.139% -0.082 0.036 0.041 Acuity Right Ear Threshold 500 Hz (41) Auditory 0.170% -0.312%* 0.149 -0.013 -0.111 0.220% -0.130 -0.103 -0.137 0.023 Threshold 1000 Hz (42) Auditory 0.213%% -0.340*%* 0.181 0.051 -0.126 0.216% -0.110 -0.073 -0.124 -0.073 Threshold 2000 Hz (43) Auditory 0.163** -0.,213* 0.065 0.019 -0.191%* 0.269%* -0.108 0.067 -0.063 -0.084 Threshold Right Ear Threshold 4000 Hz (44) Auditory 0.011 Threshold 8000 Hz (45) Auditory -0.017 Threshold Left Ear Threshold 500 Hz (46) Auditory 0.208% Threshold 1000 Hz (47) Auditory 0.204% Threshold 2000 Hz (48) Auditory 0.153 Threshold 4000 Hz (49) Auditory 0.107 Threshold 8000 Hz (50) Auditory -0.035 Threshold Tone Decay First Trial (51) Duration of Tone 0.049 Second Trial (52) Duration of Tone -0.012 LS Strength, Endurance and Recovery Original Strength (Sj) (53) Muscular Force 0.276%* Endurance (E) (54) Muscular -0.102 Endurance Secondary Strength (Sj) (55) Muscular Force 0.210** Strength Recovery (Rg) (56) Recovery -0.114 Impulse (I) (57) Impulse (Force) 0.054 X Duration) -0 + 208% .183 .134 .087 .129 .204* +127 A227 .156 .209* .026 .200* .037 .190 -0 -0 .170 .153 .011 .021 JL13 .059 .007 .169 .209 .009 .068 .043 .037 .113 0.154% 0.177% -0.029 -0.087 -0.067 0.112 0.153 -0.170 0.038 -0.013 -0.044 0.042 0.093 -0.010 -0 -0. 112 118 .072 .169* 228% .134 .158* .063 .068 .256%* .050 .266%* .028 .155 0.519** 0.469** 0.110 0.136 0.216* 0.445%* 0.383%* -0.176 0.136 -0.030 0.117 N.C. 0.124 0.092 -0. -0. .124 .095 .042 .043 +115 .107 .108 .116 .107 132 .041 .088 .149 069 -0. .032 0. .028 0. .022 -0. .084 -0. .066 -0. .016 0. .020 0. .165 -0. .026 0. .199* -0. .044 0. «217%* .039 0. 192 0. 119 114 194* 182* 062 057 101 065 101 023 077 .018 036 080 -0. -0. -0. -0 026 035 .052 .061 .063 .037 .025 058 .187** .030 +137 .029 .093 8¢ TABLE 11 (Continued) PREDICTOR VARIABLES! BEHAVIORAL MEASURES Clinical Measures Urine Lead Urine Urine Blood Blood ALA CPU Lead ALA-D Demographic Measures Age Education Employment Height Weight Tremor: Pre-Test Trials Preferred Hand First 30 sec. (58) Muscular 0.089 Control Second 30 sec. (59) Muscular 0.066 Control Non-Preferred Hand First 30 sec. (60) Muscular -0.082 Control Second 30 sec. (61) Muscular -0.050 Control Tremor: Post-Test Trials Preferred Hand First 30 sec. (62) Muscular 0.044 Control Second 30 sec. (63) Muscular 0.056 Control Non-Preferred Hand First 30 sec. (64) Muscular 0.001 Control Second 30 sec. (65) Muscular 0.010 Control 0.113 -0.183 -0.007 -0.166* 0.072 -0.107 -0.017 -0.143 0.146 -0.074 0.048 -0 ,222%#% 0.127 -0.102 0.030 -0.193* 0.014 -0.076 -0.045 -0.176* 0.053 -0.134 -0.057 -0.172* 0.005 -0.025 0.067 -0.195* 0.040 -0.087 0.039 -0.141 -0.115 -0.044 -0.015 -0.135 -0.056 -0.142 -0.098 -0.079 -0. -0. -0 067 027 .130 .091 .055 .049 .090 .077 0.068 0.041 0.057 0.103 0.058 0.135 0.080 0.050 .010 .055 .057 .073 .029 .012 .128 .098 -0. 0. -0. -0. -0 040 054 .062 .010 .036 01% 030 011 62 Digit-Span Test (66) Immediate Recall 0.090 0.022 -0.046 -0.070 -0.050 0.033 0.216* -0.095 0.017 -0.019 MAACL i -0.151 -0.049 0.195 0.023 -0.081 67) Anxiet -0.017 -0.023 -0.090 0.170 0.078 . on Depression -0.020 -0.046 0.050 0.137 0.068 -0.019 -0.073 0.116 0.026 -0.024 (69) Hostility 0.024 -0.059 0.049 0.107 0.134 -0.117 -0.114 0.153 0.026 -0.071 (70) Dysphoria -0.008 -0.046 0.011 0.149 0.095 -0.088 -0.082 0.159 0.027 -0.056 Eye-Hand Coordination Preferred Hand (71) Total Responses 0.038 0.062 0.061 -0.074 0.013 -0.043 -0.035 0.072 -0.044 0.068 (72) Latency 0.123 -0.095 0.003 0.078 -0.123 0.317** -0.074 -0.163 -0.151 0.053 (73) Latency 0.116 -0.104 -0.006 0.091 -0.129 0.316%* -0.069 -0.169 -0.145 0.042 (74) Response 0.127 -0.160 0.059 -0.005 -0.139 0.170 -0.130 -0.273** -0.150 0.066 Variability (75) Response 0.125 -0.162 0.058 -0.003 -0.139 0.171 -0.130 -0.274** -0.148 0.063 Variability Non-Preferred Hand (76) Total Responses -0.024 -0.043 0.028 -0.038 -0.047 -0.027 -0.066 N.C. -0.055 0.146 (77) Latency 0.206* -0.190 0.120 -0.039 -0.075 0.320** -0.037 -0.225*% -0.127 0.079 (78) Latency 0.215% -0.183 0.114 -0.031 -0.072 0.327% -0.025 -0.223% -0.118 0.052 (79) Response 0.175% -0.269*% 0.242* -0.155 -0.151 0.235% -0.023 -0.234% -0.103 0.064 Variability (80) Response 0.176* -0.265%* 0.238* -0.152 -0.149 0.235% -0.020 -0.231*% -0.099 0.057 Variability Iy = 291 observations; N_ = 10 predictor variables; 2N.C.: Tolerance level insufficient for computation; *»< 01, F> 6.73; *%p < 001, F > 11.20; dF = 1,280 = as predictor variables; they consisted of five clinical (PbB, PbU, ALA, CPU, and ALA-D) and five demographic measures (age, education level, years on the job, height, and weight). A step-wise multiple regression was used to obtain the optimum predictive equation, and the Beta weights for this equation are presented in Table 11. Based on the results of the correlational and regression analyses, the performance data were analyzed further by means of analyses of covariance (ANCOVA). The design employed in the ANCOVA analyses involved a single analysis-of-variance variable (PbB subgroups) with multiple covariates and unequal treatment-group sizes. The treatment groups were the eight experimental subgroups, established according to the PbB levels described in the preceeding section and in Table 8. The covariates were selected on the basis of the significant Beta weights obtained in the multiple regression analyses. Since in most cases PbB is unrelated to the covariates, the assumption of homogeneity of between-and within-group regression holds; ANCOVA is therefore appropriate for the purpose of adjusting treatment means for dif- ferences in the covariate means (see Winer, 1962). In those cases where the variance of the covariate may be confounded (linearly correlated with that of the variate), the data were analyzed by means of an analysis of variance (ANOVA) with unequal treatment-group sizes. The analyses were conducted in two parts: (1) analysis for differences in treatment levels within the experimental group, and (2) analysis for differences between the experimental and control groups. The F-ratios obtained from the analyses of each of the 80 behavioral measures are presented in Table 12. Furthermore, the treatment means and standard errors of the means for the behavioral measures are presented in Table 13--where ANCOVA was employed, the adjusted means and adjusted standard errors are given. Finally, the data from the experimental group were analyzed by means of a factor analysis involving 316 observations on each of 87 variables (80 behavioral and 7 clinical measures). A principal component solution and a Varimax rotation of the factor matrix were performed; the results from the final rotated factor matrix are given in Table 14. Only those eigenvalues (of correlation coefficients) greater than or equal to 1.0 were retained in the analysis, and this restriction resulted in the extraction of 22 factors which accounted for approximately 80 percent of the total variance. Also shown in Table 14 is the percent of variance accounted for by each of the 22 factors along with the factor loadings on each of the variables (only loadings greater than or equal to .35 are included). From these data it is clear that variables associated with latency accounted for the greatest proportion of the variance; moreover, three separate latency factors emerged in the final rotated matrix (Factors 1, 12, and 18). Other factors which predominate from the test battery were those associated with the lack of muscular control (Factor 2), arithmetic accuracy (Factor 3), increased auditory threshold at low frequencies (Factor 4), and eye-hand coordination (Factor 5). These seven factors (i.e., 1, 2, 3, 4, 5, 12, 18) account for approximately 46 percent of the variance while the remaining 15 factors contribute only 34 percent of the variance. While each of these remaining factors may be important, they need not be described further. A detailed description of these results and those from previous analyses are presented in the sections which follow. 40 Individual Performance Tests Multiple Task Performance Battery (MIPB).--Significant correlations between the 36 measures obtained from the tasks of the MIPB and the six clinical measures of the body burden of lead were sparse. Considering the large number of correlations involved, the few that were significant would be expected by chance alone. Nevertheless, the multiple regression analysis revealed that two predictor variables, namely, age and level of education, contribute significantly to the observed levels of performance on the MIPB tasks. Specifically, from the data given in Table 11, it can be seen that the Beta weights obtained for the age variable were significant predictors of the criterion performances on the monitoring tasks (i.e., performance scores on warning lights, blinking lights, and probability monitoring) and target identification (p < .01). Moreover, both age and level of education were significant factors for most of the arithmetic computation measures (p < .01). On the basis of these data, age was employed as a covariate in the analyses of covariance of the MTPB data; both age and level of education were employed, however, in the arithmetic computation analyses. The F-ratios summarizing the ANCOVA results of analyses between experimental blood-lead subgroups as well as analyses between the total experimental and control groups are presented in Table 12. From these data it is evident that there were no significant differences among the experimental subgroups. However, with certain measures, significant differences in the levels of performance were obtained between the experimental and control groups. Mean latency of responses to red and green warning-lights (measures 1 and 2 respectively; Tables 12 and 13) was significantly longer (p < .05 and p < .001, respectively) for the control group than for the experimental group. In terms of the three work-load measures for each of these tasks, there was no difference between study groups for either the low (monitoring alone) or medium (monitoring plus target identification) work-load conditions. Only the high work-load condition (monitoring plus arithmetic computation) produced a significant difference in the latency of responding to these tasks (measures 13 and 16). As was the case of the overall or main warning-lights measures, response time was somewhat longer for the control group (see Table 13). The performance measures obtained from the blinking-lights task produced no significant difference in overall performance. However, during blinking-lights alone (i.e., low work-load condition; measure 17), the difference between the levels of performance of the experimental and control groups was significant (p < .05); the experimental group performed significantly slower (X = 4.19 sec) than the control group (X = 3.64 sec). Overall performance by the experimental and control groups on the probability-monitoring task differed only in terms of the mean latency of detecting signals (measure 4). Results of the ANCOVAs within work- loads indicated that this difference was contributed by the significantly slower performance of the control group during the high work-load condition (measure 22; p < .05). 41 TABLE 12 Summary of F-ratios from Analyses of Eighty Behavioral Measures Performance Between Between Between Measure Experimental Subgroups Experimental Subgroups Experimental and (ancovaly (ANOVA?) Control Groups Warning-Lights (Red) (1) Latency 0.522 = mmme- 4.438% Warning-Lights (Green) (2) Latency 0.878 000 mmemes 29.210%%* Blinking-Lights (3) Latency 0.643 0000 mmm 0.235 Probability Monitoring (4) Latency 0.514 mmeme- 5.3%6* (5) Correct Detections 0.923 ~~ meee- 2.393 (6) False Responding 0.913 000000 eeeme- 0.753 Target Identification (7) Accuracy 0.789 meme 2.882 (8) Attempted 1.280 = mmme- 1.165 Arithmetic Computations (9) Accuracy 0.702 ~~ =e=-- 0.015 (10) Attempted 0.918 ~~ =-=-- 0.624 Warning-Lights (Red) Low (11) Latency 0.645 ~~ emme- 0.011 Med (12) Latency 0.238 aee-- 0.062 High (13) Latency 0.880 ~~ ae--- 9.,179%* Warning-Lights (Green) Low (14) Latency 0.692 ~~ e--=- 3.017 Med (15) Latency 1.1383 mmm 1.832 High (16) Latency 1.254 === 22 .,034%%% Blinking-Lights Low (17) Latency 0.624 0 ese 5.333% Med (18) Latency 1.107 eee. 0.565 High (19) Latency 0.601 ~~ eee-- 2.833 Probability Monitoring Low (20) Latency 0.610 ~~ =e--- 0.625 Med (21) Latency 1.100 meme . 0.421 High (22) Latency 0.763 === 7.644%* Low (23) Correct Detections 1.146 00 meee 0.362 Med (24) Correct Detections 1.023 === 0.000 High (25) Correct Detections 0.8s¢ =e--- 6.688% Low (26) False Responding 1.169 ~~ emee- 3.513 Med (27) False Responding 0.467 ~~ ==--- 0.289 High (28) False Responding 1.280 0 meee 0.015 42 TABLE 12 (CONTINUED) Performance Between Between Between Measure Experimental Subgroups Experimental Subgroups Experimental and (ANCOVA) (ANOVAZ2) Control Groups? Target Identification First 10 Minutes (29) Accuracy 0.892 eee 6.956** Second 10 Minutes (30) Accuracy 1.137 eee 0.193 First 10 Minutes (31) Attempted 1.488 eee 1.707 Second 10 Minutes (32) Attempted 1.0s¢ eee 0.504 Arithmetic Computations First 10 Minutes (33) Accuracy 0.78 aeee- 0.436 Second 10 Minutes (34) Accuracy 0.710 emma 0.829 First 10 Minutes (35) Attempted 0.991r eee 0.041 Second 10 Minutes (36) Attempted 0.81 eee 3.053 Far Vision (37) Right Visual 1.225 eeees 0.167 Acuity (38) Left Visual 0.757 eee 0.872 Acuity Near Vision (39) Right Visual 0.84 aes 1.102 Acuity (40) Left Visual 1.202 = eee-- 0.544 Acuity Right Ear Threshold 500 Hz (41) Auditory Threshold 0.472 a 0.314 1000 Hz (42) Auditory Threshold 1.030 eee 1.331 2000 Hz (43) Auditory Threshold 0.744 = emma 0.246 4000 Hz (44) Auditory Threshold 1.800 eee 2.613 8000 Hz (45) Auditory Threshold 2,255 eee 0.997 Left Ear Threshold 500 Hz (46) Auditory Threshold 1.522 aeeea 1.642 1000 Hz (47) Auditory Threshold 2.307 eeea- 0.011 2000 Hz (48) Auditory Threshold 0.614 aaa 3.330 4000 Hz (49) Auditory Threshold 1.662 ~~ aeeea 7.538%# 8000 Hz (50) Auditory Threshold 2.023 eee 3.226 43 TABLE 12 (CONTINUED) Performance Between Between Between Measure Experimental Subgroups Experimental Subgroups Experimental and (ANCOVAL) (ANOVA?) Control Groups3 Tone Decay First Trial (51) Duration of Tone = ----- 1.480 Second Trial (52) Duration of Tone (Not Computed) Strength, Endurance and Recovery Original Strength (Sj) (53) Muscular Force 2.722% ame Endurance (E) (54) Muscular Endurance 1.255 ame Secondary Strength (Sj) (55) Muscular Force 3.319% meee Strength Recovery (Ry) (56) Recovery 0.642 eee Impulse (I) (57) Impulse (Force X 0.836 === Duration) Tremor: Pre-Test Trials Preferred Hand First 30 sec. (58) Muscular Control = ----- 0.908 Second 30 sec. (59) Muscular Control = ----- 1.193 Non-Preferred Hand First 30 sec. (60) Muscular Control = ----- 1.002 Second 30 sec. (61) Muscular Control = ----- 0.475 Tremor: Post-Test Trials Preferred Hand First 30 sec. (62) Muscular Control = ----- 1.392 Second 30 sec. (63) Muscular Control = ----- 1.403 Non-Preferred Hand First 30 sec. (64) Muscular Control = ----- 1.186 Second 30 sec. (65) Muscular Control = ----- 1.188 1.861 21.2920%%# 9.2p63%* 39 .109*** 3.694 35.445%%* 1.437 4.549% 3.364 2.526 6.052% 13,.858%* 7.845%% 10.624%** 44 TABLE 12 (CONTINUED) Performance Between Between Between Measure Experimental Subgroups Experimental Subgroups Experimental and (ANCOVA) (ANOVAZ) Control Groups3 Digit-Span Test (66) Immediate Recall 0.591 eee 0.229 MAACL (67) Anxiety —--e- 1.447 3.847 (68) Depression = ----- 1.238 7.081** (69) Hostility ----- 1.433 7+234%%* (70) Dysphoria ~~ ----- 1.380 7.094** Eye-Hand Coordination Preferred Hand (71) Total Responses 0.331 ~~ —eee- 0.001 (72) Latency 1.412 aeee- 12 537 %%* (73) Latency 1.423 —=ee- 12,32 5% (74) Response 2.615» aaa 6.264% Variability (75) Response 2.595 eee 6.241 Variability Non-Preferred Hand (76) Total Responses 0.762 ~~ aeee- 0.003 (77) Latency 1.181 eee 9.094** (78) Latency 1.416 eee 9.364** (79) Response 1.667 ame 3.127 Variability (80) Response 1.00 —=ee- 3.126 Variability 3 Lap > 7,304; 237 = 7,308; “df > 1,424; *p < .01; ***p < .001 45 S [<2 TABLE 13 Summary of Means and Standard Errors (In Parentheses) from Analyses of Eighty Behavioral Measures! Experimental Subgroups Total Sample BEHAVIORAL MEASURES Less Between Between Between Between Between Between Greater than 39ug% 40 § 49ug% 50 § 59ug% 60 & 69ug% 70 & 79ug% 80 & 89ug% 90 § 99ug% than 100ug% Exp. Cont. Warning-Lights (Red) (1) Latency 2.54 2.54 2.68 2,69 2.70 2.39 2.78 2.13 2.61 2.96 (0.23) (0.17) (0.17) (0.16) (0.19) (0.23) (0.31) (0.39) (0.08) (0.14) Warning-Lights (Green) (2) Latency 4.89 4.93 4.49 5.26 5.29 4.62 5.34 4.89 4.96 6.55 (0.39) (0.29) (0.29) (0.28) (0.32) (0.40) (0.54) (0.66) (0.15) (0.25) Blinking-Lights (3) Latency 6.79 7.25 6.59 7.19 7.20 7.33 6.99 8.06 7.09 7.23 (0.48) (0.36) (0.35) (0.34) (0.39) (0.50) (0.66) (0.82) (0.15) (0.25) Probability Monitoring (4) Latency 6.20 6.64 6.16 6.61 6.77 6.73 6.45 6.28 6.51 7.10 (0.39) (0.29) (0.28) (0.28) (0.32) (0.40) (0.53) (0.66) (0.13) (0.22) (5) Correct Detections 99.32 99.10 99.66 99.24 98.99 99.98 99.18 99.74 99.55 98.62 (1.06) (0.80) (0.78) (0.76) (0.87) (1.10) (1.46) (1.81) (0.31) (0.52) (6) False Responding 6.94 3.61 4.33 3.46 5.39 4.54 4.80 3.93 4.49 3.82 (1.30) (0.99) (0.96) (0.94) (1.07) (1.35) (1.79) (2.22) (0.39) (0.67) Target Identification (7) Accuracy 78.47 82.60 82.13 81.49 80.89 86.83 82.57 82.83 82.01 79.01 (2.61) (1.98) (1.92) (1.88) (2.14) (2.70) (3.60) (4.46) (0.80) {1.35) (8) Attempted 90.47 95.23 94.87 95.14 93.00 98.04 95.76 91.39 94.48 93.12 (2.04) (1.54) (1.50) (1.47) (1.67) (2.11) (2.81) (3.49) (0.64) (1.08) Arithmetic Computations (9) Accuracy 51.14 58.77 57.92 54.19 50.35 55.76 56.73 59.40 55.09 55.43 (4.46) (3.35) (3.25) (3.18) (3.63) (4.58) (6.09) (7.57) (1.38) (2.31) (10) Attempted 72.98 79.31 79.96 73.40 71.11 72.77 79.69 79.89 75.50 77.55 (4.38) (3.30) (3.19) (3.13) (3.57) (4.50) (5.99) (7.45) (1.32) (2.23) Warning-Lights (Red) Low (11) Latency 1.69 1.54 1.84 1.55 1.64 1.75 1.82 1.76 1.67 1.68 0.17) (0.13) (0.13) (0.12) (0.14) (0.18) (0.24) (0.29) (0.06) (0.09) Med (12) Latency 2.24 2.04 2.23 2.20 2.13 2.04 2.07 1.98 2.14 2.18 (0.20) (0.15) (0.15) (0.15) (0.17) (0.21) (0.28) (0.35) (0.07) (0.12) High (13) Latency 3.30 3.56 3.42 3.72 3.74 2.97 4.04 2.65 3.51 4.37 (0.38) (0.29) (0.28) (0.28) (0.31) (0.40) (0.53) (0.65) (0.15) (0.25) Warning-Lights (Green) Low (14) Latency 2.38 1.97 2.42 2.61 2,52 2.30 2.78 2.81 2.41 2.83 (0.35) (0.26) (0.25) (0.25) (0.29) (0.36) (0.47) (0.59) (0.12) (0.21) Med (15) Latency 4.63 4.07 3.43 4.24 4.67 4.31 3.48 4.35 4.13 4.56 (0.49) (0.37) (0.36) (0.35) (0.40) (0.51) (0.67) (0.83) (0.16) (0.27) High (16) Latency 6.31 7.75 6.47 7.74 7.70 6.82 7.94 6.73 7.25 9.44 (0.65) (0.59) (0.48) (0.47) (0.63) (0.67) (0.89) (1.11) (0.24) (0.40) Blinking-Lights = Low (17) Latency 4.24 4.26 3.71 4.13 4.50 4.36 4.24 4.78 4.19 3.64 (0.41) (0.31) (0.30) (0.30) (0.34) (0.43) (0.57) (0.70) (0.12) (0.21) Med (18) Latency 5.69 5.79 5.14 5.80 5.75 5.56 5.89 7.58 5.70 5.48 (0.49) (0.37) (0.36) (0.35) (0.40) (0.51) (0.67) (0.84) (0.15) (0.26) High (19) Latency 9.63 10.32 9.67 10.68 10.36 10.94 10.08 11.43 10.29 11.04 (0.70) (0.53) (0.51) (0.50) 0.57) (0.72) (0.96) (1.19) (0.23) (0.38) Probability Monitoring Low (20) Latency 3.21 3.47 3.31 3.20 3.44 3.57 3.57 4.09 3.40 3.26 (0.29) (0.22) (0.21) (0.21) (0.24) (0.30) (0.30) (0.50) (0.09) (0.15) Med (21) Latency 4.87 4.55 4.47 4.99 5.29 4.70 4.63 4.45 4.78 4.92 (0.32) (0.25) (0.24) (0.23) 0.27) (0.34) (0.45) (0.55) (0.11) (0.19) High (22) Latency 8.98 10.30 9.23 10.15 10.06 10.38 9.74 9.20 9.84 11.12 (0.68) (0.51) (0.50) (0.49) (0.56) (0.70) (0.94) (1.16) (0.24) (0.40) Low (23) Correct 99.78 99.59 99.99 99.99 99.50 99.69 99.99 98.60 99.75 99.93 Detections (0.33) (0.25) (0.24) (0.24) (0.27) (0.34) (0.45) (0.56) (0.09) (0.16) Med (24) Correct 99.99 99.92 99.99 99.99 99.73 99.86 99.99 99.99 99.93 99.99 Detections (0.11) (0.09) (0.c (0.08) (0.09) (0.12) (0.16) (0.20) (0.03) (0.05) 8v TABLE 13 (CONTINUED) Experimental Subgroups Total Sample BEHAVIORAL MEASURES Less Between Between Between Between Between Between Greater than 39ug% 40 § 49ug% 50 & 59ug% 60 § 69ug% 70 & 79ug% 80 & 89ug% 90 § 99ug% than 100ug% Exp. Cont. Probability Monitorin High (25) Correct 98.71 98.42 98.92 98.08 98.21 97.08 98.20 99.99 98.36 96.75 Detections (0.75) (0.56) (0.55) (0.54) (0.61) (0.77) (1.03) 1.27) (0.32) {0.53) Low (26) False 1.96 0.76 0.99 1.01 1.32 1.16 1.57 0.63 1.14 0.71 Responding (0.39) (0.29) (0.29) (0.28) (0.32) (0.40) (0.54) (0.67) (0.11) (0.19) Med (27) False 2.18 1.19 1.46 1.17 1.64 1:65 1.33 1.34 1.46 1.29 Responding (0.53) (0.40) (0.39) (0.38) (0.43) (0.54) (0.72) (0.90) (0.17) (0.28) High (28) False 2.83 1.64 1.73 1.41 2.58 1.67 3.67 1.87 2.00 1.95 Responding (0.65) (0.49) (0.48) (0.47) (0.53) (0.67) (0.90) (1.11) (0.20) (0.34) Target Identification First 10 Minutes (29) Accuracy 75.03 79.29 81.63 79.00 78.27 83.22 80.00 74.97 79.34 74.78 (2.86) (2.16) (2.10) (2.06) (2:34) (2.96) (3.94) (4.88) (0.88) (1.49) Second 10 Minutes (30) Accuracy 81.91 85.90 82.62 83.98 83.51 90.44 85.13 90.70 84.68 83.92 (2.85) (2.16) (2.09) (2.05) 2.34) (2.95) (3.92) (4.87) (0.89) (1.49) First 10 Minutes (31) Attempted 89.45 94.72 95.00 93.96 91.16 96.64 95.59 89.79 93.60 91.85 (2.14) (1.62) A.57) (1.54) (1.76) (2.22) (2.95) (3.66) (0.68) (1.15) Second 10 Minutes (32) Attempted 91.49 95.73 94.74 96.33 194.84 99.45 95.93 92.98 95.36 94.39 2.20) (1.67) (1.62) (1.58) £1.81) (2.28) (3.03) (3.76) (0.70) 1:17) Arithmetic Computations First 10 Minutes (33) Accuracy 47.95 55.29 55.73 51.63 47.66 54.15 51.04 61.19 52.45 50.59 (4.66) (3.51) (3.40) (3.32) (3.80) (4.79) (6.37) (7.93) (1.44) (2.41) Second 10 Minutes (34) Accuracy 54.32 62.25 60.11 56.74 53.05 57.38 62.43 57.62 57.74 60.27 (4.59) (3.46) (3.35) (3.28) (3.74) (4.72) (6.28) (7.81) (1.42) (2.39) 6v Arithmetic Computations First 10 Minutes (35) Attempted Second 10 Minutes (36) Attempted Far Vision (37) Right Visual Acuity (38) Left Visual Acuity Near Vision (39) Right Visual Acuity (40) Left Visual Acuity Right Ear Threshold 500 Hz (41) Auditory Threshold 1000 Hz (42) Auditory Threshold 2000 Hz (43) Auditory Threshold 4000 Hz (44) Auditory Threshold 8000 Hz (45) Auditory Threshold 70.30 (4.47) 75.66 (4.49) 6.21 (0.56) 7.80 (0.58) 6.42 (0.59) 7.89 (0.58) 15.19 (1.91) 16.13 (2.14) 14.57 {2.51) 4.69 (3.80) -3.14 (3.97) 14 1 13. (1. 10 (1 -6 (3. 70 .36) 93 .38) «32 42) .26 .44) .82 .44) .67 .43) .54 .44) 45 62) 41 .90) .54 .87) .66 00) 14 (1 14 (1 12. (1. 2 2 12 +25) .81 .27) .88 41) +53 .43) .92 .43) .49 .42) .22 .40) .25 .57) 15 84) x91 .79) +31 .91) 71. (3. 75, (3. 13 (1 14 1 13, .80) (1 -0 2 46 19) 35 21) .02 .40) .26 .42) .41 .42) «72 .41) .58 +37) .93 .54) 54 .82 .73) .49 .85) 63 .64) «59 .66) .11 .46) .50 .48) +39 .48) .88 47) .44 .56) .70 .76) .90 .06) .53 .12) .64 .25) 11 .59) 44 .62) 71 .58) .84 .60) .70 .60) «11 +59) D3 57) 44 .22) +32 .59) .70 .93) .74 .10) 77. 81 (6. 16 20 (2 17 14 (5. 4. 5. 48 11) .90 14) +77 77) .96 .80) .20 .81) .11 .79) +13 .62) .09 .95) .51 .45) .00 23) 35 46) 74. (7. 77. 33 59) 46 .64) «32 .95) 77 .99) v2 .00) «21 .98) .47 +25) .84 .66) .26 .28) +57 .49) .07 77) 73.95 (1.35) 77.06 (1.36) 6.62 (0.18) 7.29 (0.18) 6.87 (0.19) 7.45 (0.18) 14.98 (0.61) 15.61 (0.68) 13.23 (0.80) 8.78 (1.20) -0.22 1.25) 7 ( 8 ( ( ( 6 © 7 0) 14 (1 14 (1. 14 1 ( ( 3.41 2.28) 1.70 2.28) 6.47 0.30) 6.96 0.31) .49 +31) +19 .30) .31 .03) .07 14) .01 .35) 2.58 2.02) 2.22 2.10) TABLE 13 (CONTINUED) Experimental Subgroups Total Sample BEHAVIORAL MEASURES Less Between Between Between Between Between Between Greater than 39ug% 40 § 49ug% 50 § 59ugh 60 & 69ug% 70 § 79ug% 80 §& 89ugh 90 & 99ug% than 100ug% Exp. Cont. Left Ear Threshold 500 Hz (46) Auditory 16.31 14.94 13,12 13.49 17.82 13.82 18.13 14.62 14.94 16.40 Threshold (1.70) (1.28) (1.24) (1.22) (1.39) (1.75) (2.34) (2.90) (0.58) (0.98) 1000 Hz (47) Auditory 15.08 11.61 11.06 10.52 15.36 11.46 18.87 10.32 12.55 12.43 Threshold (1.85) (1.40) (1.36) (1.33) (1.52) (1.92) (2.55) (3.16) (0.59) (0.98) 2000 Hz (48) Auditory 3.82 2.87 0.94 2.20 4.41 1.22 6.02 0.52 2.65 5.27 Threshold (2.22) (1.68) (1.63) (1.60) (1.82) (2.29) (3.05) (3.79) (0.74) (1.24) 4000 Hz 10). - 57 Because none of the demographic parameters contributed signifi- cantly to criterion performance, an ANOVA was employed in the analyses of these measures. The results of these analyses, as summarized in Table 12, indicate that there was no significant difference among the experimental subgroups. From the means and standard errors presented in Table 13, non-significance is not surprising based on the large amount of within-subject variability. Because of the small N in each subgroup at both ends of the PbB continuum, the standard errors are expected to be about twice the value as those obtained from the subgroups comprising the mid-range of the PbB continuum (from 40 to 89ug%). From the standard errors given in Table 13 it is clear that not only are the standard errors about the same across all PbB subgroups, many of the mid-range groups show standard errors greater than those seen at the extremes of the continuum, The data from the first and second 30-sec trials for both the pre-test and post-test measures are presented in Figures 29 (preferred hand) and 30 (non-preferred hand). Although there was no statistically significant difference among the subgroup means, it is evident in Figure 29 that both the first and second 30-sec trials during the pre-test showed an increase in the mean number of hits (increased tremor) with increases in PbB. Indeed, the four subgroups above 70ug% PbB exhibit considerably more tremor than the four subgroups below 70ug%. This trend, although not as clear, is also seen in the data of the post-test trials as well. Since the correlation between PbB and ALA-D is significant (p < .01) and the correlation between ALA-D and amount of tremor is significant (p < .001), the inference can be made that there is a progressively greater amount of tremor associated with progressively larger quantities of PbB. Furthermore, the data indicate that the largest increase in tremor occurs at levels between 70 and 79ug% of Pb in the blood. From the data given in Figures 29 and 30 it is also evident that the experimental group, on the average, performed better than the controls. With respect to the pre-test trials, these differences be- tween study groups were not significant (p > .10; except measure 59 where p < .05); the differences were significant, however, with respect to the four post-test trials (measures 62 through 65; p < .05). Never- theless, certain of the experimental subgroups above 70ug% did exhibit a greater amount of tremor than the control group. Digit span.--The digit-span subtest yielded only one performance measure, a number indicating the longest sequence of digits repeated without error. From all the analyses conducted on this measure it is clear that this test did not produce any significant differences in intellectual functioning. From the means given in Table 13, one can see that the means ranged from a low of 6.04 to a high of 6.70 between experimental subgroups, and between study groups the means were Xg= 6.30 for the experimentals and X; = 6.36 for the controls. Such small differences suggest that this test was not sufficiently discrimi- nating to detect significant differences in intellectual (i.e., retention) functioning. 58 Multiple Affect Adjective Check List (MAACL).--The MAACL consists of 132 adjectives related to feelings of anxiety, depression, and hostility. The overall subjective state of the worker, dysphoria, was obtained by summing scores for anxiety, depression, and hostility, which are themselves simple frequency counts of selected adjectives. The results of the correlation analyses (Table 10), indicate that no significant relationship exits between MAACL scores and the clinical measures for either the experimental or control group. Moreover, an ANOVA (Table 12) comparing experimental PbB subgroups also failed to produce significant differences even though workers in PbB subgroups greater than 70ug% tended to have higher depression scores than those workers in PbB subgroups below 69ug% (see Figure 31). As can be seen in Figure 31 there is a great deal of variability in the data of all the MAACL measures. The dysphoria function for the experimental subgroups amplified the variability of the other three measures because of the summation process by which this measure is derived. A further comparison of the absolute levels of affect shows a surprisingly large difference between the two study groups. With each measure, there is a higher level of affect exhibited by the total experimental group than the control group, and except for anxiety (where p > .10) these differences are statistically significant (measures 68, 69, 70; Table 12; p < ,01). Eye-hand coordination.--The test of eye-hand coordination produced 10 separate performance measures; five were based on performances of the preferred hand and five of the non-preferred hand. Of the five measures for each hand, latency, (defined as the mean hole-to-hole movement time), and response variability, (defined as the standard deviation of the mean hole-to-hole time), are the primary measures of interest. The remaining three measures, total responses, total response latency, and standard error of the mean hole-to-hole time, are directly related to the primary measures and do not provide additional information. In the discussion which follows, latency refers to measures 73 (preferred hand) and 78 (non-preferred hand) and response variability refers to measures 74 (preferred hand) and 79 (non-preferred hand). Significant correlations were obtained between ALA-D and the perform- ance measures for both study groups, although the correlation co- efficients differed in sign. The analyses of the experimental data produced significant negative correlations for ALA-D with increases in response latency (p < .05) and with increases in response variability (p < .01). On the other hand, the analyses of the control data produced significant positive correlations for ALA-D with these performance measures (p < .05). Considering that ALA-D activity decreases as a func- tion of the inhibitory action of Pb, it is not too surprising that the correlations between ALA-D and these performance measures for the experimental group were negative. Moreover, since ALA-D activity is not inhibited in normal (i.e., control) workers and therefore free to vary over a wider range (see Table 7) than that of the lead-exposed workers, the positive correlation does not contradict the results of the experimental group. 59 From the results of the regression analyses (Table 11), it can be seen that the most important variables in affecting response latency and response variability were the age of the individual (p < .01; except measure 74 where p > .10) and the length of employment (p < .01; except measure 73 where p > .10). In addition, for the preferred hand, PbU, ALA, and CPU were significant contributors to response variability (p < .01); PbU was also a significant (p < .01) contributor to var- iability of response latency. None of these clinical measures significantly affected performances with the preferred hand. Based on the preceeding analyses, an ANCOVA was performed in which age and length of employment were employed as covariates. The results of these analyses are summarized in Tables 12 (F-ratios) and 13 (Means and standard errors); a plot of the data is also presented in Figure 32. It can be seen from these data that the control group showed not only a significantly slower response time but also a significantly greater amount of variability in their performances (see measures 72, 73, 74, 77, and 78; Table 12). These data also indicate that, in terms of both response latency and response variability, poorer performance was obtained with the non-preferred hand. In terms of differences between experimental subgroups, there was a small, though significant (p < .05), increase in response variability with the preferred hand (measures 74 and 75; Table 12) as PbB increased across subgroups. Although the differences in the means were not significant, response latency for the preferred hand also showed an increase as a function of PbB; the pattern of this function, moreover, is supported by the significant correlation between latency and PbB. Because of within- group variability and lack of significance, no overall pattern of results can be determined in the performances of the non-preferred hand. The curves showing the performances of the preferred hand suggest that separate functions can be isolated depending upon the specific PbB subgroups. Those subgroups above 70ug% show a somewhat poorer overall performance level, in terms of both latency and response variability, than those below 69ug%. Except for the group between 90 and 99ug%, the means for these high PbB subgroups approach the level of performance of the controls (Table 13 and Figure 32)--which was significantly poorer than the performances of the overall experimental group. 60 DISCUSSION The primary question to which the present study was addressed concerned the extent to which functional capacity, as assessed by a comprehensive behavioral test battery, changes as a result of increases in body burden of lead caused by occupational exposure to inorganic lead. Previous studies have been merely descriptive in nature and have dealt primarily with symptoms or clinical signs associated with lead absorption. The specific nature and pathogenesis of diminished functional capacity associated with long-term exposure to low levels of airborne Pb have received little systematic study. An attempt was made, therefore, to measure and evaluate over a broad spectrum of body-burden measures the changes in functional capacity which result from occupational exposure to Pb. Data from a total of 428 industrial workers from eight different plants were compiled for analysis in this study. Two primary study groups consisted of 316 experimental or lead-exposed workers and 112 control workers possessing no known exposure to lead or other toxic industrial agent. Although workers were selected on a voluntary basis, the two study groups were approximately matched for sex, race, age, body-build (weight and height), and education. An overall summary of the results from the evaluations of behavioral functions as measured by subtests of the comprehensive behavioral test battery is given in Table 15. The results are organized in this table so as to show a composite view of the predominant findings in each test area, even though not every measure from a given area produced significant statistical. differences in performance or a significant relationship to the body burden of Pb. This summary, therefore, represents the generalization of specific test-area results to the broader functional category. Presented in Table 15 are the primary and secondary predictors of criterion performance (based on the relative rankings of the Beta weights), the significant correlations, the direction of change in functional capacity, and the PbB level at which the largest change occurred for each test area, and the func- tional category it represents. These data point to four general conclusions which can be summarized as follows: (a) Individual differences--e.g., age, education, and, to a lesser extent, length of employment--accounted for a significant portion of the variance related to those performance measures which were used to assess functional capacity. (b) Clinical measures of the body burden of lead were significant correlates of functional capacity in terms of sensory, physiological, or motor functions, whereas, because of their complexity, cognitive, psycho- logical, perceptual, or watchkeeping functions were not directly related to any single clinical measure. (c) PbB was correlated with a large number of individual measures from the test battery (see Table 10), but was not a primary or secondary predictor of the performance scores in any of the functional categories assessed; however, ALA-D was a signifi- cant predictor of physiological functioning. (d) Those measures which yielded significant differences in functional capacity between subgroups indicate that the largest changes in performance capacity occurred between PbB levels of 70 and 79ug%. 61 [4 TABLE 15 Summary of Functional Changes in Workers Exposed to Inorganic Lead Test Area Functional Predictors of Criterion Performance Significant Change in Functional Capacity Category Primary Secondary Correlations Direction Indicated PbB Level of Change Where Change Occurs Signal Detection Watchkeeping Age Education = ----- e---— meee Pattern Sensory-Perceptual Age Education 0 o---== eee meme Discrimination Mental Arithmetic Intellectual Education Age e-e-- Decrease @ = ----- Visual Acuity Sensory Age === eeee meee meee Auditory Acuity Sensory Age ALA PbU, PbB, ALA-D Decrease 80-89ug% Tremor Neuromuscular ALA-D = mee ALA-D Decrease 70-79ug% Muscular Strength, Neuromuscular ALA-D PbU PbU, PbB, ALA-D Increase 70-79ug% Endurance § Recovery Eye-Hand Coordination Neuromuscular Age Employment PbU, ALA-D Decrease 70-79ug% Immediate Recall Intellectual Education = ----- —=—-= meme =m Subjective Feelings Psychological Employment ~~ ----- -==-- Decrease 70-79ug% CLINICAL INDICATORS OF FUNCTIONAL CAPACITY As indicated by the summary presented in Table 15 and the corre- lation and regression analyses given in Tables 10 and 11, respectively, it can be seen that PbB was not found to be the best indicator of changes in functional capacity. This finding is consistent with the well- established fact that PbB provides an indication of the amount of exposure and not the biochemical effect of that exposure (Haeger-Aronsen, 1971; Goodman § Gilman, 1965). The current results also support the findings of previous studies which seriously question the value of PbB as a diagnostic indicator. For example, this identical result has been observed by others who have demonstrated that high PbB levels may not be accompanied by symptoms of lead poisoning, and that such symptoms have been reported for low PbB levels (Beritic, 1971; Rennert, Weiner, § Madden, 1970). Moreover, Kehoe (1961, 1972b) has shown that PbB is proportional to the rate of PbB intake rather than the absolute amount of lead ingested or the level of exposure, (Because occupational exposures to inorganic lead are typically long-term and at low levels, it is not surprising that a measure which reflects rate of intake rather than the absolute amount, or more importantly, the effect of intake is not indicative of changes in functional capacity.) A final technical problem noted in these (see Table 5) and other studies is that laboratories are subject to variability of as much as + 10% in the results of their assays of PbB (Zielhuis, 1971; Stankovic, 1971; Kehoe, 1971, 1972b). Thus, it must be suggested that as a quantitative measure of body burden, PbB is neither adequately reliable nor sufficiently related to the effect of exposure to provide a sensitive index of changes in functional capacity. Similarly, the three urine measures examined in this study also failed to produce systematic relationships with the functional categories of performance. PbU, ALA, and CPU provided very little correspondence to the behavioral measures, although PbU was a good deal more promising than either ALA or CPU (see Tables 10 and 11). Unlike PbB, PbU is a measure of the amount of lead removed from the blood, but like PbB, it reflects the amount of exposure and not the effect. A final problem with all urine measures is that they are dependent on the amount of fluid in the bladder, a factor which varies widely between workers and within workers during the day and between days (Kehoe, 1972b). This variability in measurement, therefore, decreases the reliability of urine indices for predicting changes in functional capacity. By far the strongest clinical indicator of functional capacity in this study was blood ALA-D. Blood ALA-D was not only a primary predictor of criterion performance in tests of tremor and muscular strength (Table 11), it also correlated significantly with measures of auditory acuity and eye-hand coordination (Table 10). The usefulness of ALA-D as a diagnostic measure of changes in functional capacity is predicated on two facts: (a) ALA-D is a quantitative measure of the effect of Pb on body biochemistry; specifically, ALA-D is inhibited by Pb in the biosynthesis of heme. Since biochemical events are basic to particular behaviors which define an individual's functional capacity, a direct measure of biochemical dynamics should be more useful in defining 63 the relationship between functional capacity and body burden than is a measure representing a biochemical condition, per se. With the development of knowledge about biochemical substrates of behavior, specific hypotheses about interactions between biochemical events and behavior can be elucidated. However, a discussion of the biochemical bases of behavior is beyond the scope of this report. (b) Inhibited ALA-D activity is detectable in the absence of urinary responses and at extremely low concentrations of PbB (deBruin, 1971). The data from this study support the finding that decreases in ALA-D are detectable as a result of exposure to low levels of Pb. The control group (with an average PbB level of 15.07ug%), showed a significant (negative) correlation between PbB and ALA-D (r = -.37; p < .01) but did not show any significant relationship between PbB and PbU, ALA, or CPU. Because of this sensitivity to low levels of Pb, deBruin and Hoolboom (1967) note that ALA-D is an excellent test for monitoring occupational exposure to lead and the results from this study indicate concurrence with this observation. Moreover, the data of Hernberg, Nikkanen, Mellin, and Lilius (1970) show that decreased ALA-D activity is the earliest indicator of exposure to lead. In their study of 158 persons environmentally and occupationally exposed to lead, they obtained a large negative correlation of r = -.90 (p < .001) between ALA-D activity and PbB. This correlation was based upon the universal linear relationship which they found to exist between the logarithm of ALA-D activity and concentrations of PbB in the range of 5 to 95ug% (Hernberg, et al., 1970). Based on the data of this study, however, the levels of ALA-D which are associated with various levels of PbB may be derived by use of the regression equation, y = ax + b (where x = PbB). Specifically, the current data indicate that ALA-D is related to PbB according to the equation, ALA-D = -0.1827 PbB + 33.3398 (see Figure 9). Calculations based on this equation indicate that the following ALA-D values can be utilized for health monitoring purposes in place of the PbB levels: PbB (ug%) ALA-D (units of activity) <40 >26 40 - 80 26 - 19 (70) (21) 80 - 120 19 - 11 >120 . <11 Since the current data indicate that functional capacity may be altered at PbB levels as low as 70 to 79ug%, corresponding reductions in functional capacity must be expected to occur at less than 21 units of ALA-D activity. In addition, the current exposure standard of 801g% corresponds to an ALA-D level of 19 units of activity. Corresponding values of ALA-D can be determined from the Hernberg, et al. (1970) data. However their data would indicate that the categories suggested above are somewhat conservative. Considering that the correlation between PbB and ALA-D in this study was a good deal smaller than that obtained by Hernberg (1970), it is not surprising that the proposed categories of ALA-D are conservative, especially at the higher levels of ALA-D activity. 64 FUNCTIONAL CAPACITY The comprehensive behavioral test battery employed in this study attempted to assess the effects of occupational exposure to Pb on four broad functional categories; namely, (a) intellectual functions (learning and memory); (b) sensory-perceptual functions (watchkeeping, vigilance, attention, pattern perception, audition, and vision); (ec) neuromuscular functions (psychophysiological and psychomotor); and (d) psychological functions (affect). Results related to each of these functional categories are discussed in the paragraphs which follow. Intellectual Functions Although impairment of learning and memory has been cited in case descriptions of lead poisoning (Mentesana, 1953; Kiryakov, 1959), the data from this study do not suggest that intellectual functioning is related to the body burden of lead. It is clear from the summary presented in Table 15 that the body-burden measures employed in this study bore no quantitative relationship to the types of intellectual functioning measured here. This is not to say, however, that different measures of different types of intellectual functions (e.g., measures of long-term memory, problem-solving, decision making, etc.) would not be affected by exposure to inorganic lead. There are indications in the current data that the intellectual tasks used here failed to discriminate because one was too simple and the other was too difficult for the population of subjects who were tested. For example, the small range of scores obtained with the digit-span subtest indicates that all the subjects obtained nearly maximum scores. Thus, this test might have been so easily performed that it failed to discriminate among workers in terms of memory functioning. Moreover, the data of the arithmetic com- putations task (from the MTPB) indicate that the subjects did not reach asymptotic levels of performance within the allotted (20 min) perform- ance on this task. Reference to Table 13 (Measures 33 and 34) shows that even at the end of the second 10 min trial, both study groups were performing correctly on less than 61 percent of the problems. Previous research (as well as unreported pilot data collected at the beginning of this study) had indicated that scores greater than 85 percent are obtainable with college-population subjects in a 20 min period (Chiles § Jennings, 1970). Thus, it seems that this task was too difficult for the study population, and therefore, it failed to discriminate on the basis of the absolute levels of responding. It is interesting to note, however, that a derived measure re- presenting the amount of improvement from the first to the second 10-min period of arithmetic computations suggests that leaded workers did not improve performance with practice as effectively as did the non-leaded workers. Whether this is due to a slowness in learning or the con- founded effect of fatigue cannot be determined from the current data. It is sufficient to note that either a decrease in learning capacity or an increase in intellectual fatigue did interact with the arithmetic computation performances of workers occupationally exposed to Pb, where- as no such interaction occurred with the control subjects. In addition, 65 it should be noted that there is evidence to suggest that intellectual information is encoded by way of nucleic acids (Russell, 1966) and that altered nucleic acid content--of the leukocytes--occurs in individuals suffering from lead poisoning (deBruin, 1971; Nunziante § Granata, 1957). Thus, it is possible that at body-burden levels below 100ug%, altera- tions in intellectual functioning would be better assessed by relating that capacity to molecular changes in DNA (deoxyribonucleic acid) or RNA (ribonucleic acid). Thus, failure to find significant differences between study groups or among the PbB subgroups in this study should not be taken to mean that all intellectual functions are affected by lead. Given an adequate number of learning trials, the arithmetic-computation task might become an appropriate task for assessing differences in intellectual functioning of workers exposed to lead. In addition, there are other tasks of intellectual functioning (which might prove to be more sensitive) which should be investigated in this regard. Sensory-Perceptual Functions Adverse effects of elevated body burden of lead on watchkeeping, vigilance, and attentive functions were not found in the current data. It is important to note, however, that under the high work-load condition of the MTPB, the experimental subjects performed better than the controls in terms of the speed of responding to red and green warning-lights and probability monitoring. This result is quite possible considering that the subjects are able to trade-off their performances on one MIPB task in favor of another which they feel is more important (Repko, 1972; Alluisi & Morgan, 1971). Thus, it seems that the experimentals attended to the monitoring task during arithmetic computations to a greater extent than did the controls; this perhaps is related to the experimentals' smaller improvement on math during the second 10 min. This conclusion is supported by the data of blinking-lights alone, which indicate that on this task, in this condition, the lead-exposed workers performed significantly poorer than the control group (see Table 12). Just why the experimentals traded off their attention to the monitoring tasks during high work-load performances cannot be as- certained from the present data. It is also important that the response latency measures obtained from warning-lights, blinking-lights, and probability monitoring (as well as work-load measures for each task) each showed high positive loadings on a general latency factor. Three latency factors, based on the monitoring measures, emerged in the final rotated matrix (Factors 1, 12, and 18; Table 14); together, these factors account for 20 per- cent of the total variance in the assessment of overall functional capacity. Thus, even though the ANCOVA did not show significant differences among the PbB subgroups--the large amount of individual variability is the suspected reason for insignificance--the data of the factor analysis clearly indicate that measures of latency (as well as measures of operator load in the latency dependent tasks) should be included in any future test battery used to assess functional capacity. 66 The data from the pattern perception task, (target identification of the MTPB) and the visual acuity task did not show any detrimental effects due to increases in the body burden of Pb. Although previous research has attributed a large number of visual dysfunctions to Pb intoxication (Sonkin, 1963; Lange, 1969; Klopp, 1955), the data from this study indicate that these dysfunctions do not occur at the PbB levels studied here; the body burdens of lead were typically quite high in the earlier studies. It is suggested that changes in visual functioning might be detected at low body burden levels, if threshold measures of light and dark adaptation (see Ryazanov, 1962) or a measure of the detection threshold of light (analogous to the auditory threshold test discussed below) were employed. In the past, where auditory dysfunctions have been attributed to lead intoxication, the actual effects were unclear. Reports of hearing deficiencies were often based on relatively few workers with limited control for aging and with limited information concerning noise exposure. Differential results have also been reported; deficits have been found at low frequencies (Atchabarov, Moshdevich, & Pyataev, 1967), middle frequencies (Balzano, 1952; Koch § Serra, 1962), and at high frequencies (Gammarrota § Bartoli, 1964; Valcie § Manojlovic, 1969; Balzano, 1952; Koch § Serra, 1962; Atchabarov, et al., 1967). After adjustments to account for hearing losses because of age (see Tables 12 and 13, and Figures 19 through 26), the results of this study confirm that losses may occur at all frequency ranges, particularly at high levels of body burden of lead. Moreover, loss of hearing was signi- ficantly correlated to decreases in ALA-D, thereby suggesting that as the body burden of lead increases, there is a commensurate loss of auditory function. It should be noted that in two of three plants from which experimental data were collected, the ambient levels of indus- trial noise exposure ranged from 70 to 85 dBA--only in one isolated area did noise levels exceed 90 dBA, and here workers were required to wear ear protectors of various sorts. In the third plant (wherein the authors were not given access) data provided by others indicated that the levels there also did not exceed 90 dB. Not only do increases in threshold hearing levels (between 1000 and 8000 Hz) bear a relationship to decreases in ALA-D, hearing levels at 500 and 1000 Hz correlated positively with PBU, and at 4000 and 8000 Hz hearing levels correlated positively with PbB. Hypotheses accounting for these differential significant correlations cannot be offered without further examination of the neurophysiological and biochem- ical substrates of auditory function. Reference to Figures 19 through 26 clearly indicates, however, that there is a commensurate increase in threshold hearing level with increases in body burden of Pb. Further- more, initial increases in hearing level are evidenced at PbB levels between 70 and 79ug% for all frequencies tested. Data from the tone decay test also provide some suggestive evidence of auditory pathology. Specifically, there was a significant negative correlation between the audible duration of the tone and PbB and a similar significant correlation occurred with CPU. Normal functioning of the auditory system should produce no tone decay; Glorig (1965) has indicated that for low tone levels a loss in audibility may be indicative 67 of retrocochlear pathology and at high tone levels the loss may be due to a tumor of the eighth cranial nerve. Since most of the tone decay tests occurred at low tone levels (less than 60 dB) the data are sugges- tive of retrocochlear pathology. This suggested result must be con- firmed by further testing of additional workers occupationally exposed to Pb and by physiological examination of animals exposed to varying quantities of Pb. Neuromuscular Functions As indicated in Table 15, the strongest relationships between body burden of lead and functional capacity occurred with tests of neuromuscular function. The specific correlations (Table 10), show that with increases in body burden of lead, functional capacity decreased in terms of tremor and eye-hand coordination and increased in terms of muscular strength. In addition, the data suggest that these changes began to occur at PbB levels as low as 70 to 79ug%. One of the classical early signs of neuromuscular dysfunction, especially in cases of chronic lead intoxication, is tremor (Ravasini, 1961; Simpson, Seaton, & Adams, 1964). The experimental data from this study confirm this earlier finding; the pre-test data in Figures 29 and 30 show an increase in tremor with increases in body burden, and these increases correlate significantly with decreases in ALA-D. Moreover, the subgroups above 70ug% exhibit considerably more tremor-- indicated by an increase in hits--than those subgroups below 70ug%. A similar trend is also suggested by the data of the post-test trials, even though there is a good deal more within-group variability (Table 13) in these data. Decreases in neuromuscular function were also evidenced in the measures of eye-hand coordination (Figure 32). As PbB levels increased, there was a significant increase in response variability and a suggested increase in response latency with the preferred hand (Table 12); these increases occur initially at PbB levels between 70 and 79ug%. Similar increases in response variability on this specific task have also been observed in workers occupationally exposed to other heavy metals, such as inorganic measures (Chaffin, et al., 1973). Moreover, in this study, measures of latency and response variability were significantly related to PbB (positive relationship) and ALA-D (negative relationship). Although these systematic changes in function are not as clear with the non-preferred hand, the trend is suggested by the data. Thus, it would seem that a loss of eye-hand coordination occurs at between 70 and 79ug% of PbB and on the preferred side. There is some supporting evidence for these data which indicates that neuromuscular dysfunction may initially occur on the preferred side, presumably because of its frequency of use (Goodman § Gilman, 1965). In addition, the increase in latency which was observed is consistent with the data showing decreases in nerve conduction velocity (NCV) rates. Seppalainen and Hernberg (1972) have demonstrated that excessive occupational ex- posure produces a reduction of NCV rates which is brought about by either segmental demyelation or Wallerian degeneration. In either case, an NCV reduction would be expected to increase the latency of the overt behavioral act. 68 While the tremor and eye-hand coordination data show a decrease in function, (and the same is suggested by the muscular endurance data), the data of muscular strength show an overall increase with increases in body burden. The relationship between strength and body burden, however, is not linear; strength decreases in the range of PbB from 39 to 69ug%, but increases beyond that level (see Figure 28). It should also be noted that there is a trade-off between the measures of muscular strength and endurance (this is evidenced in Figure 28) such that subjects who exert a large force on the initial strength measurement are typically unable to maintain their endurance as long as subjects who exert a relatively small initial strength. The negative relationship between impulse and ALA-D and the data of Figure 28 also indicate that an increase in impulse occurs with increases in body burden. The obtained inverse relationship between muscular strength and endurance across experimental subgroups suggests that subjects in different PbB subgroups adopted different response strategies in re- sponding to this task. Specifically, it seems that subjects in the higher PbB subgroups (above 60-69ug%) exerted themselves to a much greater extent on the strength pulls than did subjects in the lower subgroups (60-69ug% and below), and therefore were unable to main- tain their endurance for as long as the lower subgroups. This is clearly reflected in the fact that the endurance of the highest three subgroups was considerably shorter than that of the other subgroups. On the other hand, those subgroups whose original strength was on the order of 82 1b. of force (or less) were able to maintain endurance for a relatively longer time. This relationship is shown clearly in Figure 33 which presents a plot of the ratio of endurance to original strength, This curve demonstrates that the endurance of the lower four subgroups was about equal to their level of strength (ratio of approximately 1.0) and that the ratio increased across these four sub- groups. However, relative to their own level of strength, the endurance of the highest four subgroups was relatively small and the ratio decreases across the subgroups--indicating that as PbB increases, endurance gets progressively poorer relative to the given level of strength. It is hypothesized that subjects in the higher PbB subgroups felt (perhaps because they were aware of their elevated PbB, or because of previous experiences of weakness) that it was necessary for them to overcompensate (for their possible weakness) by exerting greater forces on the strength pulls. Having done so, they were then less able to maintain their endurance. This type of trade-off was possible because none of the subjects exerted their maximum strength on the original strength pull (as evidenced by the improvement in strength from the first to the second strength pulls). Future usage of this task should include more practice and instruction to insure that maximum strength is exerted on the first strength pull. Psychological Functions A comparison of the experimental and control groups in terms of their absolute levels of affect revealed surprisingly large dif- ferences. Workers occupationally exposed to Pb showed a significantly 69 greater amount of hostility, depression, and general dysphoria than non-exposed workers. These data confirm previous reports that irrita- bility and emotionality are measured in leaded individuals (Byers §& Lord, 1943; Eisler §& Bartousek, 1960; Freed, 1963; Lane, 1965). The present data indicate that increases in PbB are associated with increases in depression (see Figure 31), with the largest increase occurring within the range of 70 to 79ug% of PbB. However, the precise rela- tionships between body burden and the other measures of affect were not so clear and will require further research for clarification. The present data are sufficient to support the conclusion that, on the average, the psychological impact of working in a leaded environment is one of increased hostility, depression, and general dysphoria. Future research should seek to determine whether this is caused directly by the lead exposure or by the concomitant conditions in the work environment. 70 CONCLUSIONS, RECOMMENDATIONS, AND FUTURE RESEARCH NEEDS This section of the report is devoted to the summary conclusions and recommended changes in health monitoring protocol which are suggested by this investigation. Conclusions and recommendations resulting from the plant and employee questionnaire are provided in Appendices F (Industrial Hygiene Practices) and G (Composite Medical Profile and Subjective Evaluation of Worker Population). Furthermore, suggestions are given concerning basic research necessary to (a) assess the specific extent and nature of functional disorders noted in this study and (b) develop and implement behavioral health evaluation tests. SUMMARY OF FINDINGS Biomedical Measures The data of this study suggest that as a quantitative measure of body burden, PbB is neither reliably stable nor sufficiently re- lated to the effect of exposure to provide a sensitive measure of changes in functional capacity. Blood ALA-D was found to be the strongest clinical measure of changes in the functional capacities assessed in this study. Blood ALA-D was not only a primary predictor of cri- terion performances in tests of tremor and muscular strength, it also correlated significantly with measures of auditory acuity and eye- hand coordination. The usefulness of ALA-D as a correlate of perform- ance is predicated on two facts; namely, (a) ALA-D is a quantitative measure of the effect of Pb on body biochemistry, and (b) inhibited ALA-D activity is detectable in the absence of urinary responses and at extremely low concentrations of PbB. Intellectual Functions Significant differences in intellectual functions between study groups or between PbB subgroups were not found in this study. However, this should not be taken to mean that all intellectual functions are unaltered. Additional research using different types of intellectual tasks is needed. Particular attention should be paid to the ability of leaded subjects to learn new skills or to improve performance through practice and to the performance of intellectual functions under stress- ful conditions (heavy work-loads, etc.). Sensory-Perceptual Functions Loss of hearing, as evidenced by an increase in auditory threshold, was significantly correlated with decreases in ALA-D, thereby suggesting that as the body burden of lead increases, there is a commensurate loss of auditory function. Moreover, initial increases in hearing level were evidenced at PbB levels between 70 and 79ug% for all frequencies tested. Finally, there was a significant correlation between decreases in the audible duration of a tone and increases in PbB, thereby pro- viding some suggestive evidence of auditory pathology. Changes in watchkeeping, vigilance, and attentive as well as visual functions were not indicated in the current data. 71 Neuromuscular Functions By far the strongest relationships between body burden of lead and functional capacity occurred with tests of neuromuscular function. On the basis of significant correlations between performances and decreases in ALA-D, the data show a decrease in functional capacity in terms of tremor and eye-hand coordination (there is also a suggestion of a decrease in muscular endurance), and an increase in performance in terms of muscular strength. In addition, the data further suggest that these changes occur on the preferred side and at PbB levels between 70 and 79ug%. Psychological Functions The present data are sufficient to support the conclusion that on the average, the psychological impact of working in a leaded environ- ment is one of increased hostility, depression, and general dysphoria. Future research should try to determine whether this is caused by the lead or by other factors in the environment. RECOMMENDATIONS Lowering of PbB Criteria Because most industrial hygienists and governmental regulatory agencies employ PbB as an index of the extent of exposure, any indicated changes in biomedical monitoring criteria must include this specific measure. Since the purpose of any exposure criterion is to provide maximum protection to the health and safety of the greatest proportion of the worker population, criteria should be based on actual changes in functional capacity as well as changes in medical measures. It is not sufficient that standards of exposure be based solely on medical criteria. Therefore, based on the behavioral data of this study, a biomedical standard of 70ugh of PbB is recommended. Once this level is exceeded, a worker should be examined to determine (a) the occurrence of deterioration in medical status, (b) the occurrence of deterioration in functional capacity, and (ec) the specific level of ALA-D. If any of these additional examinations are positive, the worker should be removed from his current level of exposure. Utilization of ALA-D Criteria Since ALA-D was found to be the strongest clinical measure of functional capacity, ALA-D should be employed as a measure of the effect of exposure. Although PbB and ALA-D were significantly correlated (r = -.29), the data of this study indicates that ALA-D is the dominant predictor of functional disorder. Based, therefore, on the behavioral data and the relationship between PbB and ALA-D, a biomedical standard of 21 units of ALA-D activity is recommended. Any ALA-D level less than 21 units of activity (and a PbB in excess of 70ug%) indicate not only that the exposure is excessive, but that the effect of that exposure is potentially hazardous to the worker's functional capacity. 72 Utilization of Functional Tests Based on the data of this study, it is recommended that functional measures be utilized in routine health-monitoring programs. As soon as possible and practical, such programs should specifically include auditory and neuromuscular assessments. Appropriate auditory and visual tests are currently available to industrial hygienists; feasible neuromuscular tests must be developed and made available. As additional data of functional capacity are compiled by scientists, the utility of other intellectual, psychological and sensory-perceptual tests in controlling industrial lead intoxication may be demonstrated. Any industrial test finally developed and implemented for health- monitoring programs must meet certain criteria of validity, sensitivity, engineering feasibility, reliability, flexibility, trainability, control- data (i.e., normal-data) availability, and parsimony. The data of this study are inadequate to recommend specific tests which meet the above criteria, but do suggest that consideration be given to eye-hand coordination tests, tremor tests, and tests of strength and endurance. Further research and development is needed in order to determine the precise nature and degree of utility of functional tests in con- trolling and evaluating industrial lead intoxication. The areas of research necessary for the further assessments of functional capacity and the development of specific functional tests are discussed in the next section of this report. FUTURE RESEARCH NEEDS Current industrial practice involves the use of a number of well- known neurotoxic materials in many industrial processes. These materials range from organic solvents used in degreasing operations to the heavy metals used in foundries and smelters. The adverse effects on the nervous system of acute and chronic exposure to neurotoxic materials are well documented (Repko, et al., in preparation; Tuttle, Reed, § Grether, 1973; Tuttle, Killian, Reed, § Grether, 1973; Hanninen, 1971; 1972; Seppalainen § Hernberg, 1972; Chaffin, et al., 1973; Catton, et al., 1970; Salvini, Binaschi, § Riva, 1971a, 1971b; Stewart, 1968). In the long run, research should be directed toward the development of common tests sensitive to behavioral impairments and associated neurophysiological disturbances caused by exposure to a variety of chemical and physical agents at the workplace. In the short run, however, development must be based on evaluation of functional capacity in select worker groups subjected to specific neurotoxic agents. It is from these specific data that general tests of functional disorder can then be constructed. Based on the data of this study and others (cf., Repko, et al., in preparation) the adverse effects of exposure to inorganic lead on certain functional capacities have been demonstrated. There are, however, several additional basic research areas which must be investigated to assess the extent and nature of specific functional disorders and the relationship between these disorders and occupational safety and health. 73 Need for Longitudinal Study The data of the current investigation indicate that a longitudinal study of workers exposed to lead is necessary. This conclusion is based on several aspects of the data; namely: (a) Certain performances are dependent on intervening factors such as age, education, and employment duration. Because of these variables and a demonstrated variability in performance, which are unrelated to the effects of acute or chronic exposure, it becomes more difficult to establish normal population limits. (bh) On many of the behavioral tests, learning was a critical factor. In fact, the data of the MTPB and SER tasks indicate that the workers may not have attained asymptotic levels of performance in the allotted time. (ec) Although there was an opportunity to evaluate the test-retest reliability of the PbB determinations, it was not possible to evaluate the reliability of the remaining four clinical determinations and 80 behavioral measures. Finally, (d), it was not possible to determine if decrements in functional capacity were reversible when the body burden of lead was reduced. Such problems and inadequacies, however, can be mitigated by the replication and administration of this functional test battery to a smaller, select group of workers over an extended period of time. Need for Neurophysiological Correlates The data of the tremor, eye-hand coordination, and SER tasks indicate that neurophysiological measures, such as from electromyography (EMG), are necessary in order to determine the precise relationship between fine and gross muscular functioning. Indeed, the data of muscular functioning between tasks suggest that the amplitude and frequency of a neuromuscular response may be differentially affected by lead. Where electrophysiological techniques have been employed in the detection of lead intoxication, differential results have been obtained depending upon the specific nerves involved (Catton, et al., 1970; Seppalainen & Hernberg, 1972) or the specific EMG measure employed (Sessa, Ferrari, § Colluci, 1965; Catton, et al., 1970). Moreover, the data from electrophysiological research has demonstrated neuropathy in the absence of medical evidence of neurological dysfunction (Catton, et al., 1970; Sessa, et al., 1965; Seppalainen § Hernberg, 1972). Further research is necessary in order to evaluate the relationships among the extent of lead absorption, the neurophysiological effects of various absorption levels, and the overt behavioral changes brought about by neurological dysfunction. Need for Latency Measures Based on the data of the factor analysis, it is quite clear that response latency is the predominant factor accounting for the variance among workers occupationally exposed to lead. Although response latency was indirectly assessed by performances of other, sensory-perceptual and neuromuscular tasks, no direct measure of simple or choice reaction time (RT) was included in the comprehensive test battery. Previous researchers have demonstrated that increased latency occurs in a variety 74 of experimental situations, specifically to auditory (Boyadzhiev, Stoev, & Petkov, 1962), to visual (Boyadzhiev, et al., 1962), and to electrical stimuli (Cupcea, Raucher, Derevenco, Deleanu, Pop, § Gross, 1954). Moreover, neurophysiological data indicate that excessive occupational exposure produces a reduction of nerve con- duction velocity (NCV) rates--brought about by either segmental de- myelination or Wallerian degeneration (Seppalainen § Hernberg, 1972; Catton, et al., 1970; Schlaepfer, 1969; Fullerton, 1966). It would appear, therefore, that future studies should not only include simple, choice, or disjunctive RT paradigms, but also NCV measures in order to evaluate the precise relationship between latency and neuropathy. Need for Further Auditory Data Even though the data of this study show that auditory functions are adversely affected by exposure to inorganic lead, it is important that these findings be replicated. This is especially true with respect to the finding that retrocochlear pathology may be present in workers with high PbB levels. In future studies, auditory tests should be conducted under conditions of maximum ambient noise at- tenuation (i.e., in an acoustical chamber) and with an expanded tone- decay test. A tone-decay test such as that proposed by Green (1972, p. 254) is an appropriate diagnostic test for retrocochlear pathology. CONCLUSION In conclusion, it is believed by these authors that the data obtained in this study greatly enhance the knowledge concerning the behavioral and biochemical effects of occupational exposure to in- organic lead. The task of evaluating the effects of such exposure is by no means completed. Although the data of this study answered many questions concerning the functional status of workers suspected of lead intoxication, the data produced many new and exciting chal- lenges. Only with future research designed to solve these critical problems can the development and implementation of health-monitoring tests be accomplished. 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Archives of Environmental Health, 1964, 8, 262-265. Zielhuis, R. L. Interrelationship of biochemical responses to the absorption of inorganic lead. Archives of Environmental Health, 1971, 23, 299-311. Zuckerman, M. The development of an affect adjective check list for the measurement of anxiety, Journal of Consulting Psychology, 1960, 24, 457-462. Zuckerman, M., Lubin, B., Vogel, L., § Valerius, Elizabeth. Measure- ment of experimentally induced affects. Journal of Consulting Psychology, 1964, 28, 418-425. 90 PERCENTAGE DECOMPOSITION 60 — | | | | | l 5 10 15 20 25 30 35 40 TIME (IN DAYS) Figure 7. Percentage decomposition of ALA-D in frozen blood samples as a function of time. 91 NUMBER OF OBSERVATIONS Figure 8. <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD LEAD (IN MICROGRAMS PERCENT) Distribution of (experimental group) workers within each of eight PbB subgroups. 92 120 p= E 100 | ml |] x m = Re 80 |— x oe ay = 2.477% - 32,279 53 60 f— LIN : * 53 (F = 75.576, p < .001; s r = 0.440, p < .01) — = YouaD = -.01X° + 4.25X - 99.29 20: fee / (F = 42,049, p < .001) ! I | | | 1 | 1 | | | | —_ = - 33.3398 120 Yoon 0.1827X + 2 (F = 29.367, p < .001; r = -0.293, p < .01) Sx 100 2 E~ — Wp = - .464X + 43.93 25 YouaD .0020X AE F = 21.670, p < .001) =< 80 p— << o oO — 25 60 2 25 mz SZ 0s. a 2 20 20 40 60 80 100 120 140 160 180 BLOOD LEAD (IN MICROGRAMS PERCENT) Figure 9. Predictive equations and regression lines for linear and quad- ratic trends; shown are PbU (upper panel) and ALA-D (lower panel) as functions of PbB. 93 ren = .02 - .5514 6.0 Y py = -0227X 1 (F = 70.448, p < .001; r = 0.428, p < .01) 5.0p -—- -.0001X* + .0447X - 1.3816 =Yquap ~ (F = 42.549, p < .001) 4.0 3.0 |r 2.0 §-AMINOLEVULINIC ACID (IN MILLIGRAMS PERCENT) 1.0 p— 600 |— — YIN = 1.4576X - 25.2980 (F = 73.195, p < .001; r = 0.435, p < .01) EC 500= ----y = -.0080X° + 2.8603X - 78.1814 _& QUAD cS (F = 44.194, p < .001) > A E, ‘01 + 23 300f C0 O —~ = z 200 | 100 |— | : | | | | | | 1 20 40 60 80 100 120 140 160 180 BLOOD LEAD (IN MICROGRAMS PERCENT) Figure 10. Predictive equations and regression lines for linear and quad- ratic trends; shown are ALA (upper panel) and CPU (lower panel) as functions of PbB. 94 —— Y [y= -0032X + .4862 SZ 4.0 (F = 41.101, p < .001; » = 0.340, p < .01) Ny: 2 93 0070 — = -.00001X° + .0093X - . = 8 sol Yquap 1 og : (F = 43.771, p < .001) 232 32 2.0p a ">: i oO 3 -—-— - ae - = zz 1.0 — oo e YN = -2576X + 34.7254 I (F = 72.0728, p < .001; r = 0.432, p < .01) Zz ox Ea “00 Yquap = =-0005X" + .6356X + 4.4103 52 (F = 62.2131, p < .001) Ox oD SS 200 a OO OH - —— Sw"; qe; Oo = —— w-— — Z 100 —-— — i | | | | | | | | 7 2 m— gy = 027% + 25.1635 Sz 8 (F = 19.742, p < .001; » = -0.243, p < 01) 22 2 _ .0635X + 28.0910 Fk ————y = ,00005X° - . + 28, 25 eof QUAD §= (F = 14.627, p < .001) TR [- ao — 40 p=— — 25 H8 30 p— mz 20 ~ 2 Teese eeee————— 10 p— 0.5 1.0 1.5 2.0 2.5 3.0 2:3 4.0 4.5 §-AMINOLEVULINIC ACID (IN MILLIGRAMS PERCENT) Figure 12. Predictive equations and regression lines for linear and quad- ratic trends; shown is ALA-D as a function of ALA. 96 — = -.0453X + 24.8353 ev] I LIN (F = 19.750, p < .001; r = -0.243, p < .01) 2 2 ———— = - .1069X + 27.0190 2 60 }— YQUAD .0002X 1 & ~ (F = 14.8959, p < .001) gs = S50 b— a> Io a oO = 2 40 }— [$9 Lo zZ Wn aE 20 = = i ml - ZZ QO Ad = Z | ] | | | | | | 1 50 100 150 200 250 300 350 400 450 COPROPORPHYRIN (IN MICROGRAMS PERCENT) Figure 13. Predictive equations and regression lines for linear and quad- ratic trends; shown is ALA-D as a function of CPU. 97 350 —— Y [y= 44.6404X + 27.1476 (F = 316.1089, p < .001; r» = 0.708, p < .001) 2 es —_— g = .9373 17.1109 _ 300 Youap 6.2777X° + 70.9373X + > (F = 181.4026, p < .001) 0 =2 250 | = A See EQ EE 200 a OO £28 150 Ss = =~ 100 50 ] | [1 l | | ] 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 § -AMINOLEVULINIC ACID (IN MILLIGRAMS PERCENT) Figure 14. Predictive equations and regression lines for linear and quad- trends; shown is CPU as a function of ALA. 98 1 TARGET IDENTIFICATION | po AN >” 5 90 | ’” Sa 7 I , -—~ ’ ~~ & o oD _-° Sem mee——— 3 80 es | TT 8 PY | x = 70 | | = ( = | FIRST 10 MIN (MEASURE 29) a me ’ -——= SECOND 10 MIN (MEASURE 30) | | > | | | | | | 1 <4 l fr | E1201 \ 2 1 = » S 110} i oa | = ", 5 100 }= 3 100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Figure 15. Mean percentage of target identification problems correct (upper panel) and mean percentage improvement (lower panel) for the experimental and control groups and as functions of PbB subgroups. 99 1 TARGET IDENTIFICATION a © 100 f= | om oO 0 l > -— mr - =o = ® a | o> ~ =~ 90 p= < | by | 2 E 80 j= | O | FIRST 10 MIN (MEASURE 31) Ti —=== SECOND 10 MIN (MEASURE 32) EW 70 p= | l S | z | | | l | | | | | | E z 120 & 5 | £ 110 |= = mn E | z ul | 2 ~ 90 — a. | i sg TLL Cont Exp <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Figure 16. Mean percentage of target identification problems attempted (upper panel) and mean percentage improvement (lower panel) for the experimental and control groups and as functions of PbB subgroups. 100 | | = FIRST 10 MIN (MEASURE 33) 70 | === SECOND 10 MIN (MEASURE 34) f= | i pz) | & o 60 p—© 9 | ml QO | = 50 |—@ | 2 on O & a 40 | SN. ; | | | E 120 oo | & | S 2 110 ® a | Z | a | QO 100 = | < E | = O = 90 I~ I a I - Toolbar rrr19 Cont Exp <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Figure 17. Mean percentage of arithmetic computations correct (upper panel) and mean percentage improvement (lower panel) for the experimental and control groups and as functions of PbB subgroups. 101 Figure 18. Lg | | 0 | 8 80 p- = ao | & ms | = . = 70 [~ < | & I = 60 | | FIRST 10 MIN (MEASURE 35) Zz | ==== SECOND 10 MIN (MEASURE 36) © | = | c ; eo 0 ARITHMETIC COMPUTATIONS L : < | 1! 1 | 1 ] | | | | | | = Z 120 p= = | mn 2 I £ 110 © | = a I £ | tr mn O | ol ba m 90 | [a®) | Cont Exp <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Mean percentage of arithmetic computations attempted (upper panel) and mean percentage improvement (lower panel) for the experimental and control groups and as functions of PbB subgroups. 102 MEAN HEARING LEVEL (IN dB) RIGHT EAR —=== CONTROL GROUP = == EXPERIMENTAL GROUP SUBGROUP LESS THAN 40ug% 25 |— LEFT EAR | | | 0.5 Figure 19. 1.0 2.0 4.0 8.0 FREQUENCY (IN KILOHERTZ) Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the PbB subgroup less than 40ug%. 103 MEAN HEARING LEVEL (IN dB) RIGHT LEAR 25 p= = === CONTROL GROUP I = =— EXPERIMENTAL GROUP SUBGROUP BETWEEN 40 AND 49ug% 20 p= LEFT EAR 25 r— eit 20 }— l l | | | 8.8 1.0 2.0 4.0 8.0 FREQUENCY (IN KILOHERTZ) Figure 20. Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 40-49ug% PbB subgroup. 104 MEAN HEARING LEVEL (IN dB) 25 fw 20 — = === CONTROL GROUP —= = — EXPERIMENTAL GROUP SUBGROUP BETWEEN 50 AND 59ug% 25 rm 201 LEFT EAR | | 1 0.5 1.0 2.0 4.0 8.0 FREQUENCY (IN KILOHERTZ) Figure 21. Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 50-59ug% PbB subgroup. 105 MEAN HEARING LEVEL (IN dB) 25 | 20 |= 15 10 - === CONTROL GROUP — - — EXPERIMENTAL GROUP SUBGROUP BETWEEN 60 AND 69ug% I | 1 0.5 1.0 2.0 4.0 8.0 FREQUENCY (IN KILOHERTZ) Figure 22. Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 60-69ug% PbB subgroups. 106 MEAN HEARING LEVEL (IN dB) 25 | ====CONTROL GROUP — - — EXPERIMENTAL GROUP " SUBGROUP BETWEEN 70 AND 79ug% 15 | 10 8 i 0 [oe See -5 | 1 | | | LEFT EAR 25 er 20 p— 0.5 Figure 23. 1.0 2.0 4.0 8.0 FREQUENCY (IN KILOHERTZ) Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 70-79ug% PbB subgroup. 107 MEAN HEARING LEVEL (IN dB) RIGHT EAR == == CONTROL GROUP — = — EXPERIMENTAL GROUP SUBGROUP BETWEEN 80 AND 89ug% ] l 25 p—- -5 = | 25 [~~ 20 l 0.5 Figure 24. 8.0 2.0 4.0 1.0 FREQUENCY (IN KILOHERTZ) Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 80-89ug% PbB subgroup. 108 MEAN HEARING LEVEL (IN dB) RIGHT EAR 25 | = === CONTROL GROUP === EXPERIMENTAL GROUP 20 == SUBGROUP BETWEEN 90 AND 99ug% 15 |— 10 | 5S j— 0 rm 5 j< ] | | | | 25 ]~ 20 ~~ -5 p— l | | | | 0.5 1.0 2.0 4.0 8.0 FREQUENCY (IN KILOHERTZ) Figure 25. Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the 90-99ug% PbB subgroup. 109 MEAN HEARING LEVEL (IN dB) 25 p— = === CONTROL GROUP RIGHT EAR = = == EXPERIMENTAL GROUP SUBGROUP GREATER THAN 100ug% LEFT EAR | l l l 0.5 Figure 26. 1.0 2.0 4.0 8.0 FREQUENCY (IN KILOHERTZ) Mean hearing level of the right (upper panel) and left ear (lower panel) as functions of five test frequencies for the control and experimental groups and the PbB subgroup greater than 100ug%. 110 45 40 35 30 25 20 DURATION OF TONE (IN SECONDS) 15 10 11 Figure 27. TONE DECAY TEST (MEASURE 51) i I l I ] l | Cont Exp <40 40- 50- 60- 70- 80- 90- 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) LT >100 Mean duration of tone decay for the experimental and control groups and as a function of PbB subgroups. 111 | — ORIGINAL STRENGTH (MEASURE 53) ~ 130 === =SECONDARY STRENGTH (MEASURE 55) wn | Q a © | a 110 p— | Z 0 ~— — @ | = 90 p= | a | Z im | & . 5 70 p= | 4 | | | | | | | | | | | ° | » — ENDURANCE (MEASURE 54) a | Z 80 p— 3S | |} ml i | [95] = a I & | z 60 — | - | : | i 50 p= | | <<. | || | ] | | 1 | | | ~® | IMPULSE (MEASURE 57) 4000 p= ’ = | = 3500 p= | © > i = 2 | = 3000 | @ - 2 . | & 2500 |— I — | | 1 2000 b= STRENGTH, ENDURANCE, AND RECOVERY (SER) | <7 111 1 1 1 1 1 1 1T Cont Exp <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Figure 28. Strength (top panel), endurance (middle panel), and impulse (bottom panel) for the experimental and control groups and as functions of PbB subgroups. 112 I TREMOR TEST I 70 p= | | o | ® “ | o | 60 | pi | 2 Sr [ = PRE-TEST: PREFERRED HAND = FIRST TRIAL (MEASURE 58) S 50 ! === =SECOND TRIAL (MEASURE 59) x | d 2 = ] | | | ] | | l ] - = | Z o I g 70 I x ° z 65 p= | = | a | | S55 p= | I POST-TEST: PREFERRED HAND | FIRST TRIAL (MEASURE 62) S50 = | -===SECOND TRIAL (MEASURE 63) oe | | 1 1 EEE EER Figure 29. Cont Exp <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Mean tremor for the preferred hand of the experimental and control groups and as functions of PbB subgroups; the first and second pre-test trials are given in the top panel and the post-test trials are given in the bottom panel. 113 70 = | TREMOR TEST | | I 65 p= | a | LI 60 }— | | £2 55}- ! = | PRE-TEST: NON-PREFERRED HAND 5 | FIRST TRIAL (MEASURE 60) o 50 = \ - -==SECOND TRIAL (MEASURE 61) ZL o = 19 troy Zz T = | go | Fo | : £ 65 — | | 8 60 [= | \ 55 I~ | POST-TEST: NON-PREFERRED HAND | FIRST TRIAL (MEASURE 64) so l -===SECOND TRIAL (MEASURE 65) 5 < | 1 L411 I I 1 | LT Cont Exp <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Figure 30. Mean tremor for the non-preferred hand of the experimental and control groups and as functions of PbB subgroups; the first and second pre-test trials are given in the top panel and the post-test trials are given in the bottom panel. 114 10 |— MULTIPLE AFFECT ADJECTIVE CHECK LIST ANXIETY (MEASURE 67) ] l l | ] ] ] ] Lr 14 f 12 p— 10 — oe DEPRESSION (MEASURE 68) Ls MEAN MAACL SCORE S I HOSTILITY (MEASURE 69) I I l l | l | 30 fr 28 26 24 — 22e | Figure 31. Cont I Exp DYSPHORIA (MEASURE 70) et | | | | l ] | lL ~ <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Measures of Affect (anxiety, hostility, depression, and dys- phoria) for the experimental and control groups and as functions of PbB subgroups. 115 550 530 510 490 MEAN RESPONSE LATENCY (IN MILLISECONDS) 470 230 210 190 170 MEAN RESPONSE VARIABILITY 150 Figure 32. RESPONSE LATENCY — EYE-HAND COORDINATION I Cont Exp <40 40- 50- 60- 70- 80- 90- 49 59 69 79 89 09 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) | 0 [ PREFERRED HAND (MEASURE 73) / - ! - === NON-PREFERRED HAND (MEASURE 78) | ™ —w Wen. -N — Oo I 7 “. / | ~ ’ i" / Sa? v — | ~ ® = | | I = y He | | | | ] ] I | | ] 5 | RESPONSE VARIABILITY | PREFERRED HAND (MEASURE 74) | —=-=NON-PREFERRED HAND (MEASURE 79) = I . | \ __ | A | Oo -= | . ~ \ | o | NG 2? LY ° . | | | . Mean response latency (upper panel) and mean response varia- bility (lower panel) for the experimental and control groups and as functions of PbB subgroups. 116 I 1.3 — ENDURANCE/STRENGTH RATIO 1.2 le 1.1 f— 1.0 j— 0.9 0.8 f— ENDURANCE/STRENGTH RATIO 0.6 f— 0.5 |— 0.4 |— I I | | | I I l T Cont Exp <40 40- 50- 60- 70- 80- 90- >100 49 59 69 79 89 99 BLOOD-LEAD LEVEL (IN MICROGRAMS PERCENT) Figure 33. Mean endurance/strength ratio for the experimental and control groups and as a function of PbB subgroups. 117 118 APPENDIX A TRADITIONAL METHODS FOR MONITORING OCCUPATIONAL EXPOSURE OF WORKERS Prepared by John D. Repko, Donald L. Corson, and Ben B., Morgan, Jr. There are three primary approaches employed in the surveil- lance of workers exposed to lead; namely, (a) environmental moni- toring of airborne lead, (b) biological monitoring of workers, and (¢) medical monitoring of workers (see Jacobson § Seiter, 1972; NAS, 1972; Repko, et al., in preparation). As indicated by the following discussion of each of these methods, none of the monitoring techniques, by itself, provides an adequate pic- ture of the immediate health status of a particular worker, nor is any sufficiently reliable as an early warning device. In addition, none of the methods provides data which relate the results of environmental, biological, and medical monitoring to human performance and functional capacity. It is suggested that the usefulness and sensitivity of these monitoring techniques could be significantly improved if they were also used in con- junction with a system for monitoring the behavioral functioning of workers. ENVIRONMENTAL MONITORING OF AIRBORNE LEAD In discussing the environmental monitoring of airborne lead, two aspects must be considered; namely, (a) the establishment of universal measuring and analysis techniques, and (b) the estab- lishment of allowable exposure levels--i.e., the Threshold Limit Value (TLV). While these two aspects may be considered separately, they are not independent problems; for example, enforcement of a TLV is only as effective as the device used in measuring a given airborne concentration, The most recently recommended standard for occupational ex- posure to inorganic lead is described in the recent NIOSH criteria document, Occupational Exposure to Inorganic Lead (for a complete description of the development of the NIOSH standard, see Jacobson and Seiter, 1972). This report recommends that workers not be ex- posed to inorganic lead concentrations greater than 0.15mg Pb/m3, determined as a time-weighted average (TWA) exposure for an 8-hr work- day. It is interesting to note that this recommended TLV is the same as that established in the early 30's based, at that time, on a Public Health Service (Russell, Jones, Bloomfield, Britton, § Thompson, 1933) report concerning lead poisoning in a storage battery plant. Prior to the PHS standard of 0.15mg/m”, the accepted air limit value was 0.50mg/m3; this value, however, was not documented in terms of its 119 (A-1) value in protecting the health of the worker (Jacobson §& Seiter, 1972). In 1957 the American Conference of Governmental Industrial Hygienists (ACGIH) increased the TLV from 0.15mg/m3 to 0.20mg/m3 and the Occupational Safety and Health Act (OSHA) of 1970 re-established 0.20mg/m3 as the current TLV (TWA). The International Subcommittee for Occupational Health, Permanent Commission and International Association of Occupational Health (1969), on the other hand, recommended a return to a TLV of 0,15mg/m3 (TWA). ’ In spite of the disagreement between the International Sub- committee and OSHA standards, there appear to be very few data provided in support of either standard. The original ACGIH stan- dard was based on a study by Elkins (1959, p.49-57) indicating that a urinary lead concentration of 0.20mg/1 would result from expo- sures at or below 0.20mg/m3, The International Subcommittee re- commended their standard on the basis that 0.15mg/m3 corresponded to a blood-lead level of 0.07mg/100 ml; the OSHA standard of 0.20mg/m3 was based on a recommendation of the American National Standards In- stitute which, incidentally, provided no basis for its recommendation (Jacobson § Seiter, 1972). On the other hand, the current NIOSH recommendation for inor- ganic lead exposure (0.15mg/m3 TWA for an 8-hr workday) is based on several studies relating blood and urinary lead concentrations to exposure levels. In developing their recommendations, they con- cluded that the standard should be based on data providing a clear relationship between airborne lead and biomedical data, especially blood lead (Jacobson §& Seiter, 1972). Of the studies cited, the most relevant is the work by Williams, King, and Walford (1969). Their data were obtained from studies of storage battery workers who showed that exposure at 0.15mg/m> yielded a mean blood-lead of 0.06 mg/100 ml, These findings were supported, in part, by early PHS findings (Dreesen, Edwards, Reinhart, Page, Webster, Armstrong, §& Sayers, 1941) and those by Stankovic (1971). Moreover, Tsuchiya and Harashima (1965), in a study based on concentrations of lead in the urine, recommended an even lower TLV of 0.10 mg/m3; this study, how- ever, dealt with workers who worked 8 to 10 hr per day, 6 days per week, Thus, it is not clear from available data what the maximum standard should be. Irrespective of the standard finally adopted, other problems of exposure are involved which do not so much depend upon the TLV or concentration of airborne lead. For example, lead particles on the hands, face, clothing, or even food may be ingested; work habits may significantly increase the concentration of airborne lead in the worker's immediate work area; other chemical and physical states of lead may add to increased absorption; overtime--extension of the work week beyond 40 hr--may result in insufficient time for the body to excrete the lead particles; finally, susceptibility to identical doses of lead is subject to a great deal of individual variability. Whether the standard adopted is 0.20mg/m3 or 0.15mg/m3, there are still other, technical problems associated with the use of en- vironmental monitoring as an occupational hygiene technique. In 120 (A-2) determining the amount of lead in the air of an industrial environ- ment, several factors must be considered. In fact, the measurement of airborne lead involves so many problems that no standard of measurement nor specific techniques for analysis have been universally agreed upon (N.A.8., 1972). The determination of lead concentrations in ambient air samples depends on seasonal as well as diurnal differences. Moreover, dif- ferences in lead concentrations for a given area may be obtained de- pending on the type of measuring device and how and where it is employed. Specifically, the location of the measuring device can have an important effect on the readings obtained. A device immediately adjacent to a lead source will record higher levels than one somewhat removed. Furthermore, the height of the sampling device will deter- mine the characteristics of the particles collected; filters near the floor of a plant will collect larger particles which settle out, while devices placed somewhat higher will collect relatively smaller particles. Even the nature of the 'best'" measuring device has not been established. In a brief review of sampling methods, Haley (1969) points out that filters which are efficient at collecting large particles often pass small ones, and some filters which collect all particles well do not permit separation of particle sizes. Thus, most devices permit either a counting of particles or a determination of particle size, but no single device is able to perform both anal- yses to desired levels of precision. NIOSH has recently recommended criteria for standard measuring and analysis techniques, but as of this writing that proposal has not been established as a universal standard (Jacobson § Seiter, 1972). BIOLOGICAL MONITORING OF WORKERS In a review of the pharmacological properties of the heavy metals, Passow, Rothstein, and Clarkson (1961) have indicated that functions associated with the cell membrane are very susceptible to interaction with heavy metals. For example, one of the actions of lead on the cell membrane is to inhibit active potassium ion transport; higher concentrations of lead are associated with a high total potassium loss from the cell (Joyce, Moore, and Weatherhall, 1954). Another action of lead is seen in the peripheral nerve fibers wherein pronounced segmental demyelination takes place (Fullerton, 1966; Chisolm, 1971). Direct evidence of lead effects in the peripheral nerve fibers of workers has been demonstrated by Catton, Harrison, Fullerton, and Kazantis (1970). They observed decreased lateral popliteol nerve conduction velocity in a group of British lead-exposed workers. The subjects in this study were engaged in the manufacture of lead-acid accumulators for durations greater than 5 months and up to 13 years. Similar observations of lead effects in peripheral nerve fibers have been reported by Seppalainen and Hernberg (1971, 1972). 121 (A-3) While these types of subclinical observations serve to demon- strate the biochemical action of lead, the practicality of their use in terms of single-test monitoring of workers in industry is minimal, The consensus of the available literature seems to be that single- test monitoring is best accomplished by measuring the body's burden of blood or urine lead, with blood lead being the preferred test (Jacob- son and Seiter, 1972; Kehoe, 1971; 1972b). Some other measures, specifically, blood aminolevulinic acid-dehydrase (ALA-D), urine amino- levulinic acid (ALA), and urine coproporphyrin (CPU), are also use- ful, but since they are not lead specific, they are considered to be of less value as a single criterion. However, since these tests were selected for inclusion in this study along with tests of blood and urine lead, the rationale for their use is also included in the discussion which follows. Blood-Lead Since it is impractical to attempt to measure the actual amount of lead stored in living tissues and organs, inferential measures must be used. One of the most obvious tests, and the one favored by various governmental agencies (Jacobson § Seiter, 1972; California Department of Public Health, 1967) is the amount of lead in the blood. However, because blood-lead levels provide an indication of the amount of exposure and not the effect of that exposure, (Berman, 1966; Haeger-Aronsen, 1971; Goodman & Gilman, 1965), some writers question its value. The problem is that very high blood-lead levels are not always accompanied by other symptoms of lead poisoning (Beritic, 1971; Rennert, Weiner, § Madden, 1970) and occasionally such symptoms are seen with low blood levels (Beritic, 1971). That is to say, the relationship between blood-lead level and the occurrence of medical symptoms is somewhat less than perfect. For example, Rennert, et al., (1970) studied 85 pre-school children in Chicago who had blood-1lead levels greater than 60pug/100 mg of blood. Some 90% of his sample showed no clinical symptoms and 54% failed to show any evidence of lead absorption in five laboratory tests other than blood-lead level. On the other hand, Beritic (1971) observed that 13 of 64 patients in Yugoslavia complaining of abdominal colic had blood levels below 80ug/100 mg. The results of a recent study, in which rhesus monkeys were fed large amounts of lead (up to 5.00 mg/kg/day; such levels represent as much as 1000 times the average daily human intake), indicate that blood-lead levels reached a peak after about one week (82pg%) but then dropped to a stable plateau around 50ug% even though the high dose rate was continued (Calandra, 1969). Those findings essentially confirm with high dose rates in monkeys what Kehoe (1961) found with low dose rates in humans; namely, that blood-1lead is roughly proportional to intake but that the elevation of blood- lead level occurs more as a function of the rate of intake than the absolute amount of lead ingested (Kehoe, 1961, 1972b). Kehoe (1972b) has also observed that studies reporting the oc- currence of symptoms associated with poisoning at low blood-lead levels 122 (A-4) usually do not report the rate nor time course of ingestion. If exposure occurred some time before the blood test, the lead levels may have decreased significantly without a concomitant reduction in total intoxication, especially if the duration of exposure were short (Kehoe, 1972b). A technical difficulty in using blood-lead levels is that even the best laboratories may be subject to variability in reports of as much as +10%, depending upon the specific analytical technique (Zielhuis, 1971). Thus, any value provided by a laboratory for a specific blood sample must be taken as a guide rather than an ab- solute value. Urine Lead A second commonly used test for body burden is the amount of lead in the urine, a measure of the amount of lead removed from the blood. Because of the variability of laboratory analysis of blood, Goodman and Gilman (1965) recommend urine-lead level as the best test of severity of exposure. Urine-lead levels following chelation have frequently been cited as a measure of body burden (Zielhuis, 1971; Teisinger, 1971). This measure generally correlates well (r=,90) with blood-lead levels (Zielhuis, 1971), but changes even more rapidly following industrial exposure than does blood-lead. A problem with urine-lead measurements is that they are dependent on the functioning of the kidneys as well as the amount of lead in the body. If lead is not being removed, even though it is present, it will not be measured. The test is also dependent on the amount of fluid in the bladder, a factor which varies widely between workers and within workers during the day and between days (Kehoe, 1972b). To avoid this difficulty, it is often the practice to collect all voidings during a 24 hour period and measure the "average" daily lead content of the urine. Unfortunately, this procedure lends itself to contamination which may make the results extremely misleading (Kehoe, 1972b). Kehoe (1972b) recommends single voidings taken relatively frequently, especially including times of stress or risk (at which time lead stored in bones is apt to be released; Hardy, Chamberlain, Maloof, Boyler, & Howell, 1971) under careful supervision after workers have showered, Nevertheless, there is good correlation between an increased industrial exposure to lead and the resulting urine output of lead in a single urine sample (Stankovic, 1971). Generally, 150 g/liter is considered to be the upper safe limit but asymptomatic patients have been reported with levels of 300ug/liter (Malcolm, 1965). Aminolevulinic Acid A test which corresponds well with blood-lead (Kehoe, 1971) and with urine-lead (Stankovic, 1971; Zielhuis, 1971) is the measure of delta-aminolevulinic acid (ALA) in the urine. The inhibition of ALA-D by lead results in the accumulation of substrate ALA and will ultimately result in an increased urine level of ALA. A significant increase in urine ALA is brought about only in those instances where the blood- lead level exceeds 'normal' values, thereby bringing about the inhibition 123 (A-5) of blood ALA-D (N.A.S., 1972, p. 110). As mentioned previously, urine ALA is best evaluated in conjunction with the determination of blood ALA-D activity. Cramer and Selander (1965) devised a scale of lead intoxication which gave point ratings to various behavioral and clinical symptoms so that each was assigned a specific score as an overall index of intoxication. Their medico-behavioral index was compared with several laboratory tests, including urinary ALA, and was found to correlate most highly with it. Buckup and Mappes (1962) felt that determination of urinary ALA took too long to be useful as a moni- toring test, but others find it to be highly useful in this regard (Haeger-Aronsen, 1971; deBruin, 1971; Kehoe, 1971). Nevertheless, urinary excretion of ALA does correlate well with lead in the blood (r = .90; Cramer § Selander, 1965) and urine (r = .92; Haeger-Aronsen, 1960). Urine Coproporphyrin As with ALA, industrial exposure to lead will result in an in- creased output of urine coproporphyrin which parallels the observed increase in blood and urine-lead levels (Stankovic, 1971). Further- more, urinary coproporphyrin (CPU) has been shown to correlate well (r = .70) with urinary-lead measures but poorly (from r = -.57 to r = +.79) with blood-lead measures (Zielhuis, 1971). The test is extremely sensitive to any effect and can barely discriminate between groups with normal exposure to lead and those with mild exposure (Malcolm, 1965). While CPU is not specific to lead intoxication, it can be used as a screening test; high values indicate the need for further testing (Haeger-Aronsen, 1971). Aminolevulinic Acid-Dehydrase A secondary test of ALA is the test for ALA dehydrase (ALA-D) in the blood. Since the activity of erythrocyte ALA-D is inhibited by lead in the biosynthesis of heme, it is quite useful as an indication of over-exposure to lead (Bonsignore, Callisano & Cartasegna, 1965; Millar, Cumming, Battistini, Carswell, & Goldberg, 1970; Nakao, Wada, Kitamura, §& Uono, 1966). It is particularly important because decreases in ALA-D are detectable with extremely low dosages of lead. Dosage levels (as low as 10-7 M) which do not otherwise produce any detect- able differences in urinary lead, CPU, or ALA, produce detectable changes in ALA-D (deBruin, 1971; Rubino, Pagliardi, Prato, §& Gian- grandi, 1958). Because of this sensitivity to low level concentrations, deBruin and Hoolboom (1967) have noted that it is an excellent test for occupational exposure to lead. Furthermore, because of the lack of suppression of ALA-D activity by other disease states, blood ALA-D activity coupled with urine ALA levels is believed to constitute a valid picture of the extent of biochemical alteration which has re- sulted from the presence of lead (N.A.S., 1972). 124 (A-6) Subclinical Classification of Lead Absorption Representative values of four categories of lead absorption are presented in Table A-1, reprinted from the British Medical Journal (Lane, Hunter, Malcolm, Williams, Hudson, Browne, McCallum, Thompson, deKretser, Zielhuis, Cramer, Barry, Goldberg, Beritic, Vigliani, Truhaut, Kehoe, § King, 1968) for four indices of overall body burden of lead. A recommendation for standards of frequency of testing, techniques of testing, and criteria for judging results has been recently published by the National Institute for Occupational Safety and Health (Jacob- son § Seiter, 1972). These criteria, which are similar to those published by several authors working in the area (Lane, et al., 1968), indicate that NIOSH (Jacobson § Seiter, 1972) considers blood-lead values in the Normal (A) and Acceptable (B) ranges to be permissible in lead-exposed workers, but values in the Excessive (C) and Dangerous (D) levels are unacceptable and require appropriate corrective action. TABLE A-1%* Categories of Lead Absorption A B c D Test Normal Acceptable Excessive Dangerous Blood lead 40 ug/ 40-80 ng/ 80-120 ug/ 120 ug/ 100 ml 100 ml 100 ml 100 ml Urine lead 80 ug/l 80-150 ug/1 150-250 ng/1 250 ug/1 Urine copro- porphyrin 150 ug/1 150-500 ng/1 500-1500 ugl 1500 ng/1 Urine aminole- vulinic acid 0.6 mg/ 0.6-2 mg/ 2-4 mg/ 4 mg/ 100 ml 100 ml 100 ml 100 ml * Reprinted by permission, British Medical Journal, 1968. MEDICAL MONITORING OF WORKERS Knowing the actual concentration of lead particles in the atmo- sphere gives only an indication of the environmental exposure, not an actual measurement of the amount of lead absorbed into the body. Once lead has been absorbed, its effects may be monitored either by medi- cal or biological monitoring of workers. Medical monitoring consists of a direct assessment of the effects of lead by observing certain clinical signs or symptoms without laboratory analysis and examination, Biological monitoring, on the other hand, involves worker examination at the cellular and biochemical levels through the use of laboratory assays. 125 (A-7) Lead poisoning in lead-related industries is usually chronic, rather than acute, in nature; under industrial exposure conditions, lead poisoning develops over a period of months or even years (Kubasik & Voldsin, 1973; Bryce-Smith, 1972; Haley, 1971). The medical mani- festations of chronic increase in body-burden of lead--usually directly observable--are as varied as the number of individuals who exhibit them. There are, however, recognizable syndromes which depend upon the extent of intoxication. At low levels of intoxication, i.e., blood-lead levels less than 80ug%, the effects of lead may not only be too subtle to detect, but may not exist at all. Kehoe (1961, 1964, 1972a, 1972b), basing his observations on lead-exposed workers and carefully controlled studies, is adamant that no insidious effects occur. On the other hand, there has been no definitive research on latent effects in lead-exposed workers wherein the effects of low levels of intoxication are con- sidered, At higher blood-lead levels, between 80 and 120ug%, medical monitor- ing may result in the detection of emerging lead poisoning symptoms. Exposure at this level may be reflected by a wide range of symptoms, from no noticeable effects (Rennert, et al., 1970) to very severe effects (Beritic, 1971). This level can be particularly dangerous to a worker whose symptoms are so mild that he may not be aware of them. In this situation, he continues to work, maintaining the exposure and increasing his body burden of lead. He may feel as though he has a "touch of a cold" or may not be aware of any difficulty until he is away from work for an extended period of time during which he may have more energy, enjoy getting out and doing things, and enjoy food again (Lane, 1965). If he is not aware of this subtle deterioration, the body burden of lead may slowly accumulate to very dangerous levels. At blood-lead levels above 120ug%, symptoms become more common and the lead poisoning may become dangerous and even potentially fatal (Hardy, 1968). The symptoms occurring at these levels have been classified according to three general symptom categories: ali- mentary type, neuromuscular type, and encephalopathy (Kehoe, 1972b). These categories tend to follow absorption levels with alimentary disturbances occurring at lower levels of absorption, and encephalo- pathy occurring at the highest levels of blood-lead. However, any symptom can occur at any level of absorption, and they all, of course, are detected at the higher levels. Alimentary symptoms Some of the earliest clinical symptoms of lead poisoning are associated with dysfunction of the alimentary tract (Kehoe, 1972a; Zavon, 1964), The types of symptoms which have been observed include loss of appetite, digestive disturbances, constipation, nausea, and colicky abdominal pain. Pallor due to anemia is also frequently cited (Goodman & Gilman, 1965). The severity of these symptoms varies with each case, however. 126 (A-8) Abdominal colic is usually the symptom which most often brings the individual to a physician. Kehoe (1972a) cites cases in which the colic was extremely painful. Colic may be periodic or continuous, lasting as long as a week. It may occur after a lengthy buildup of lead or after stored lead is released from specific stor- age areas (for example, long bones of the skeletal system) or after a very rapid, intense exposure. Peripheral neuritis, tremor and wrist drop are infrequently associated with the gastrointestinal aspects of lead intoxication (Johnstone, 1964). Neuromuscular dysfunction Distinct from, though not exclusive of, the alimentary type of symptoms are those of neuromuscular dysfunction. Kehoe (1972a) lists pain in muscles and joints, increased sensitivity of reflexes in the arms and legs, weakness, lower muscle tonus, and atrophy of extensor muscles in the forearm and hand as characteristic of neuromuscular symptoms. This form of symptomatology occurs primarily after active muscle use and occurs in the most active groups of muscles, usually in the extensor group (Zavon, 1964). There seems to be little sensory impairment (Zavon, 1964; Jacobson §& Seiter, 1972). Rather, the effect is seen as a weakness in the extensor muscles which may progress over a prolonged period of time and eventually cause muscular paralysis (Zavon, 1964; Campbell, Williams, & Baltrok, 1970; Lane, 1965). Severe weakness in the extensors of the wrist or foot is identified as wrist drop or foot drop and has been common to painters and other active workers exposed to lead. Lead encephalopathy Encephalopathy, as the name suggests, is a dysfunction of the central nervous systems, specifically the brain, and is usually associated with extremely high body burdens of lead. Encephalopathy is rarely seen in the United States in occupationally exposed adults (Kehoe, 1972a; Lane, 1965); indeed, most of the data related to lead encephalopathy are based on observations of children (Chisolm, 1971; Wiener, 1970). Permanent intellectual defects and behavioral disorders have been cited (Goodman & Gilman, 1965; Byers § Lord, 1943; Chisolm, 1971), but these studies do not possess the requisite controls, thereby making interpretation of data difficult (Wiener, 1970). Damage of this type is ultimately due to direct degeneration of neurons or their myelin sheath, or due to intracranial pressure. 127 (A-9) APPENDIX B BEHAVIORAL EFFECTS OF LEAD POISONING Prepared by John D. Repko, Donald L. Corson, and Ben B. Morgan, Jr. A great deal of clinical and laboratory research has been concerned with the environmental, physiological, biomedical, and non-specific symptomatological reactions to lead. Much careful work has been devoted to biochemical and biomedical monitors of lead and to the identification of underlying mechanisms that in- itiate and sustain a biochemical response. Yet, and in sharp con- trast, the nature and pathogenesis of the psychophysiological and mental impairments and the work-performance decrements that appear in patients incapacitated with lead poisoning have received little systematic study; until recently, there have been no quantitative data from controlled experiments on the behavioral or functional effects of inorganic lead exposure. Most of the studies relevant to occupational exposure describe behavior patterns that result from either excessive or dangerous body burdens of lead. Moreover, no study has attempted to system- atically relate an individual's functional capacity to wide ranges of specific indices of the body burden of lead. This lack of systematic research is probably due to the fact that medical and functional problems associated with lower body burdens of lead have been considered to be inconsequential and have, therefore, received little medical attention and no systematic research. Thus, most reports in the literature are based on advanced stages of some re- duced functional capacity and excessive levels of the body burden of lead; little is known of the behavioral (or performance) effects of low or "acceptable' body burdens of lead. FUNCTIONAL EFFECTS OF LEAD From the studies dealing specifically with the evaluation of psychological and behavioral functioning, one is able to identify functional categories in the types of behavior affected. Specifi- cally, these studies have identified psychological and behavioral patterns which demonstrate the effects of lead poisoning on four broad functional categories; namely, (a) intellectual functions (learning, memory, and intelligence); (b) sensory functions (involving the visual and auditory senses); (c) neuromuscular functions; and (d) psychological functions (subjective, personality, social behavior). Research related to each of these functional categories is discussed in the paragraphs which follow. Intellectual Functions Learning and memory.--Although the impairment of learning and memory has been cited in case descriptions of lead poisoning (Men- tesana, 1953; Kiryakov, 1959), experimental investigations of the effects of lead on learning and on memory are sparse. Brown, Dragann, 129 (B-1) and Vogel (1971) studied the effects of lead, injected intraperit- oneally, on the ability of rats to learn a water-filled T-maze. They found no impairment of either learning rates or recall when lead was injected either before the learning trials or between learning and memory test trials. They concluded that since such impairments have been reported for humans, lead must affect rats and humans differently. However, since the task employed by Brown, et al. (1971) has not been directly or indirectly replicated by human subjects, their comparison to human learning functions is tenuous at best. Although there are no studies assessing human learning func- tions directly, Mentesana (1953) and Kiryakov (1959) both describe subjective reports of progressive deterioration in mental capacity. In each study the case histories describe individuals with several years of excessive, industrial-lead exposure. The data, however, were based on subjective observations made by the patients and their families and leave much to be desired in terms of the quanti- tative effects of lead. Intelligence.,--Almost all studies of the effects of lead on intelligence have been with children. The classic study was done by Byers and Lord (1943) who followed the cases of 20 children hospitalized for lead poisoning. At the time of hospitalization, nine children showed no evidence of nervous system involvement, three showed peripheral neuritis but no clinical signs of cerebral involvement, and eight were mildly encephalopathic. All were treated and re- leased as being completely cured. However, testing of the child- ‘ren at a later time indicated problems with respect to motor and intel- lectual development. These types of results have serious implications for a child in the early grades attempting to learn to read and write since those skills require visual form discriminination and an ability to translate a perceived form into a motor response. It is apparent from the available literature that lead poisoned children may be able to learn in school but cannot manage the motor coordination required to read and write. The obvious result of this deficiency, therefore, is decreased intellectual development, and thus, limited intellectual capacity. Although they are rare, cases of intellectual deterioration in adults have also been reported (Rageth, 1953; Hay, 1950). In Hay's (1950) study, a 30 year old man who worked in a British cooperage developed encephalopathy. A large number of the classical symptoms of lead intoxication were evident and treatment was initiated. About four to seven months later, the Wechsler-Bellevue intelligence test and the Shipley-Hartford test showed intellectual deterio- ration. Although the observed intellectual deterioration seen in Hay's (1950) individual was directly attributable to lead, excessive use of alcohol may have been a contributing factor. On the other hand, Rageth (1953) reports the case of a 60 year old man who clearly showed reduced learning ability, retardation, and failing concentration. These behavioral changes, however, were not evident until 6 years after an injury from metallic lead chips, and in both studies the intellectual deterioration was as- sociated with extreme levels of lead intoxication. 130 (B-2) Sensory Functions Vision.--Several researchers have indicated that there may be a large number of visual dysfunctions which can be attributed to lead intoxication (Sonkin, 1963; Lange, 1969; Klopp, 1955). Sonkin (1963, p. 780) lists amblyopia, retinal edema, retrobulbar neuritis, scotoma, cataracts, extra-ocular muscle paralysis, choked disks, and partial or total blindness as sensory dysfunctions which may be directly or indirectly associated with lead poisoning. Such symptoms may occur not only with other overt symptoms of lead poi- soning (Collier, 1952; Klopp, 1955; Francois & Evens, 1963), but also in the absence of other symptoms (Baghdassarian, 1968). For example, shortly after the onset of colic or constipation, a patient may experience amaurosis resulting in a deterioration to partial, temporary, or, in the extreme, permanent blindness (Lange, 1969; Francois § Evens, 1963; Klopp, 1955); such effects, however, are reversible with deleading procedures (Unseld, 1966; Georgia Medi- cal College, 1959). Lead apparently affects three areas which specifically support visual functioning. First, neuritis may occur within the visual system (Lange, 1969); if this optic neuritis is intraocular, it is associated with papiloedema; if it is retrobulbar, only the sub- sequent atrophy at the nerves behind the eye will be seen. More- over, a scotoma--which may be limited to certain colors--is usually present in optic neuritis and some degree of atrophy usually occurs (Francois § Evens, 1963; Lange, 1969; Mosci, 1956). Second, with- in the circulatory systems changes in the character of the red blood cells and supporting fluids and tissue may lead to changes in intraocular tension (Mosci, 1956). As pointed out previously, (Mel'nikova, 1964), this effect may result from reflex regulation rather than changes in the character of the circulatory system per se. Finally, lead apparently affects the intrinsic muscles and oculomotor nerves of the visual system. Interference with the normal functioning of these areas may lead to mydriasis--pupillary dilation--or visual paralysis (Mosci, 1956; Francois & Evens, 1963; Lange, 1969). In addition, excessive visual sensitivity has been reported (N.A.S. 1972; Ryazanov, 1962); Ryazanov (1962) suggested that threshold measures of light and dark adaptation might be used to indicate the existence of lead poisoning. Audition.--While some auditory dysfunctions have been attri- buted to lead intoxication (Rageth, 1953; Ilic, 1963; Valcie and Manojlovic, 1971), the actual effects are unclear. A deficit of up to 30 or 40 dB at the high frequencies has been reported in workers in European battery plants (Gammarrota & Bartoli, 1964; Carducci § De Judicibus, 1961; Balzano, 1952). For example, Valcie and Manojlovic (1971) studied the effects of carbon mon- oxide, lead, and carbon disulfide on the auditory threshold of workers from several different industries and found deficits in the 4000-8000 Hz range. Similarly, Balzano (1952) studied 16 workers who had been exposed to lead fumes or dust for several years, or who showed clinical symptoms of lead poisoning, and found no deficit in hearing low tones (below 512 Hz), mild deficit 131 (B-3) in the middle tones (512, 1024, and 2044 Hz), and large deficits in the high tones (above 2044 Hz). The same hearing losses were evident irrespective of whether the tone was promulgated via air or via bone conduction, suggesting that the effects of lead on hearing are central rather than peripheral. Koch and Serra (1962) found that 12 workers exposed to tetraethyl lead experienced im- pairment but possessed normal audiograms below 2000 Hz. On the other hand, Atchabarov, Moshdevich, and Pyataev (1967) found that 15% of a sample of 41 leaded workers had deficits at the low and high frequency ranges with good sound perception at the medium frequencies. Hearing deficiencies which have been reported are often based on relatively few workers and the conditions under which hearing tests are made are seldom presented. Although there is some con- trol for aging--most studies have employed subjects less than 50 years old (Balzano, 1952; Atchabarov, et al., 1967; Valcie and Manojlovic, 1971)--other possible causes of hearing loss are generally not evaluated. Neither is hearing capacity prior to lead exposure reported. With the variability in frequencies effected, the relatively low proportion of lead poisoned workers showing any effect, and the lack of desirable controls, it is difficult to know the extent to which lead poisoning is respon- sible for those losses which are reported. Neuromuscular functions Muscle impairment is one of the classical signs of severe lead intoxication (Atchabarov, Aldanazarov, Nikulicheva, Romakhov, & Sabdenova, 1955; Sbertoli, 1963; Goodman §& Gilman, 1965). Im- pairment has been reported most commonly in four groups of muscles: (1) the extensors of the wrist and fingers (radial nerve); (2) the extensors of the toes and foot (peroneal nerve); (3) the small muscles of the hand; and (4) the deltoid, biceps, brachialis anticus and long supinator (Goodman & Gilman, 1965, p. 727). Early signs of neuromuscular dysfunction include muscle weakness (Hay, 1950; Klopp, 1955; Atchabarov, et al., 1955; Campbell, et al., 1970; Car- lin § Ferrandiz, 1956), easy fatigue (Magnus, 1964; Goodman &§ Gilman, 1965), tremor (Ravasini, 1961; Simpson, Seaton, § Adams, 1964), and lack of muscular coordination (Hay, 1950; Ravasini, 1961; Perlstein & Attala, 1966). The observed weakness generally occurs after mus- cular exertion and on the preferred side (Goodman § Gilman, 1965). If intoxication is substantial, paralysis may result (Katsunuma § Negishi, 1962; Sbertoli, 1963). Neurological effects have been measured indirectly in tasks that require rapid motor responses. Reaction times of lead intoxicated workers have been compared to those of non-exposed workers by vari- ous Soviet and Eastern European scientists (Jacobsen § Seiter, 1972). Since most of the available information concerning these studies has been provided by the Kettering Abstracts, details of the tests are not reported herein. However, suffice it to say that increased reaction times have been reported in leaded workers in response to spoken words or other auditory stimuli (Cupcea, Raucher, Derevenco, 132 (B-4) Deleanu, Pop, §& Gross, 1954; Boyadzhiev, Stoev, & Petkov, 1962), to visual stimuli (Boyadzhiev, et al., 1962), and to electrical stimuli (Cupcea, et al., 1954; Timofeev, Spivak, & Deinichenko, 1955). Motor reflexes have been shown to be slowed in leaded workers (Rubino, et al., 1965; Timofeev, et al., 1955; Boyadzhiev, et al., 1962). Rubino, et al. (1965) developed a method of measuring the patellar reflex which consisted of a stimulator (small hammer), surface electrodes, and an electromyograph. Normal latency of 25 control subjects was about 114 msec. while latency of the 18 lead poisoned subjects was approximately 133 msec. with values as high as 167 msec. These authors and others (Sessa, Ferrari, & Colucci, 1965; Hausmanowa-Petrusewicz, Emeryk, Sobkowica, Wasoxica, & Tur, 1962) recommend using EMG's (electromyograms) as early detectors of lead intoxication since motor reflex delays occur prior to cir- culatory effects (Sessa, et al., 1965; Cupcea, et al., 1954). Recordings of nerve conduction rates have been made on the lateral popliteal nerve of the leg. This procedure usually involves stimulating either the knee or the ankle and recording the muscle action potential through surface electrodes over the extensor digitoren brevis. It is generally agreed that the maximal fre- quency and amplitude of response is the same in leaded as well as non-leaded subjects (Rubino, et al., 1965; Sessa, et al., 1965; Catton, Harrison, Fullerton, & Kazantis, 1970; Fullerton & Harri- son, 1969). However, the amplitude of the volley from knee sti- mulation, expressed as a proportion of the amplitude of ankle sti- mulation, does differ significantly for the two groups. Catton, et al. (1970) reported that the difference for controls was 94.5% whereas the ratio for leaded subjects was 85.1%. In a recent study by Seppalainen and Hernberg (1972), subclinical nerve damage was detected in lead workers with no other clinical neurological symptoms, They found that the conduction velocities in the ulnar and median nerve were significantly lower for the lead workers than they were for the control group. In summary, it is clear that lead intoxication, particularly at high levels, may result in various neuromuscular dysfunctions; the consequences of such dysfunctions will be to detrimentally affect the performance of tasks involving motor responses. Psychological Functions Subjective, personality, social behavior.--Psychological re- sponses to lead poisoning cover a wide range and are subject to large individual differences. Probably the most common psycho- logical manifestation of lead poisoning cited in the literature is irritability and uncooperativeness of the patient (Goodman & Gilman, 1965; Lane, 1965, Byers, 1959; N.A.S., 1972). Other behavioral characteristics which are cited include hostility, hyperactivity, moodiness, depression, delirium, and occasionally mania or psy- chosis (Byers &§ Lord, 1943; Eisler §& Bartousek, 1960; Freed, 1963; Lane, 1965; Goodman & Gilman, 1965). Unfortunately, the literature dealing with adult behavior resulting from lead intoxication tends to simply list the clinical characteristics with no description of the overt behavior (e.g., Freed, 1963). Considering that many lead 133 (B-5) intoxicated patients suffer from headaches, insomnia, colic, con- stipation, and other medical symptoms, it is perhaps not too sur- prising that they exhibit abnormal emotions and personality traits. The data which are most obviously lacking are those which would de- fine the relation between the extent of these behaviors and the body burden of lead. BEHAVIORAL MONITORING OF LEAD EFFECTS The diagnosis of lead poisoning and the monitoring of lead-ex- posed workers requires the integration of several types of information since no single medical symptom or biological test is definitive, For example, colic, anorexia, headache, and muscular discomfort of the abdominal syndrome may also indicate acute appendicitis, renal colic, duodenal ulcer, gastric ulcer, acute gastroenteritis, acute prophyria, heat exhaustion, or intestinal parasitic infestation (Zavon, 1964). Similarly, peripheral neuritis, weakness, or paralysis of the muscular system may be caused by infection, malnutrition, metabolic disease (diabetes), or arsenic (Zavon, 1964). The cen- tral neurological syndromes are similar to any intercranial pres- sures such as from infections of the meninges or brain, neoplasms (tumors), tuberculoma, syphilitic infection, or uremia (Zavon, 1964). Even "lead line," a black ring on the gums once frequently reported, is not specific to lead and may be caused by infectious gingivitis, normal pigmentation of dark-skinned races, bismuth, or other metals forming a black sulfide, or dental discoloration due to poor hygiene (Zavon, 1964), Because of this non-specificity of both biological data and medical symptomatology, the diagnosis of lead intoxication requires the analysis of a large body of data. Several authors (Zavon, 1964; Johnstone, 1964; N.A.S., 1972) recommend the evaluation of at least three types of information: medical symptoms, biological data, and patient history. Although this approach is highly desirable, the essential problem of detecting functional changes at low levels of intoxication is not this easily resolved. The demonstrated non- specificity of lead effects, especially at low levels, is a con- siderable concern for researchers dealing with functional disorders. It is therefore necessary to develop direct behavioral measures which are sensitive to functional alterations over a wide range of intoxication levels, While it should not be assumed that observed functional disorders are caused solely by lead absorption, even in individuals with considerable exposure to lead, it is important to relate the functional (and behavioral) measures to the various in- dices of body burden of lead, and consider these indices in con- junction with the subjects' exposure history, biological history, and medical symptoms. The development and use of behavioral or functional methods for detecting acute and chronic exposures to chemical and physical agents at the workplace have recently become primary concerns of researchers in the field of occupational safety and health (Cohen and Margolis, 1973). In the development of behavioral methods, it 134 (R-6) is important not only to relate the overt behavioral change to a specific biochemical change in the body, but also to be able to relate these variables to the physiological changes and to the exposure conditions under which a specific dysfunction occurs. While this study does relate the behavioral or functional changes to changes in the biochemistry of the body, relating these vari- ables to physiological changes and specific exposure levels is beyond the scope of the present project. The emphasis of the study, therefore, is to maximize the gain in terms of the relative para- meters of the neurotoxic effects of exposure to lead and of the stress-sensitive behavioral performance measures. 135 (B-7) APPENDIX C DESCRIPTION OF TASKS EMPLOYED IN THE COMPREHENSIVE BEHAVIORAL TEST BATTERY Prepared by John D. Repko, Ph.D., Kenneth Hunt, Karl E. Rothrock, and John M. Lyddan A total of 12 testing instruments was selected for use in the "Evaluation of the Behavioral Functions of Workers Exposed to Lead," supported by H.E.W. Contract No. HSM 99-72-123; in addition, a compre- hensive personal-data questionnaire was employed, but is not described in this appendix. These instruments were selected for inclusion in the multifactor test battery on the basis of their usefulness in measuring certain aspects of behavior which might be expected to change as a result of increases in the body burden of lead. A comprehensive review of the literature dealing with the behavioral and biologic effects of lead provided a list of symptoms which might be expected to occur in cases of lead exposure. Tasks which logically should be sensitive to such symptomalogical changes were then selected for use in the test battery. The core of the test battery consisted of five tasks from the multiple-task performance battery (MTPB) currently employed by the Performance Research Laboratory in its studies of the effects of various stresses on work behavior (see Alluisi, 1969; Alluisi § Chiles, 1967; Chiles, Alluisi, § Adams, 1968; Morgan & Alluisi, 1972). These tasks provide measurements of watchkeeping, vigilance, and attentive functions, sensory-perceptual functions, memory functions, and time-sharing functions. They were selected originally to meet certain criteria of validity, sensitivity, engineering feasibility, reliability, flexibility, work-load variability, trainability, and control data availability (cf. Alluisi & Fulkerson, 1964, pp. 5-6); a complete description of the historical development of the MIPB tasks as they have been employed in a synthetic-work situation are given in Appendix D. For the purpose of the current research project, the use of the MIPB was modified so that reliable measurements could be obtained during a l-hour period of testing. In addition to the psychological functions assessed by use of the MIPB tasks, other psychological, sensory, and psychomotor functions were assessed by the use of tests of the following performances: (a) visual acuity, (b) auditory acuity, (e) muscular strength, endurance, and recovery, (d) tremor, (e) immediate recall (memory), (f) mood or affect, and (g) eye-hand coordination. MULTIPLE-TASK PERFORMANCE BATTERY (MTPB) A modification of the electromechanical version of the MIPB (used with permission under U.S. Army Contract No. DA-49-193-MD-2567) was employed as the core of the comprehensive behavioral test battery. The performance panels, programming, and scoring apparatus and the experimenters' control consoles have been discussed in previous reports (cf. Adams, 1958; Alluisi, 1969; Chiles, et al., 1968; Morgan § Alluisi, 1972). The tasks, as defined for use in this study, are essentially identical to those employed previously in investigations of the effects of alcohol and altitude on behavior and 137 (C-1) in the selection of air traffic controller trainees (cf. Chiles & Jennings, 1970; Jennings, Chiles, § West, 1972). The tasks of the modified MTPB were employed to assess performance in terms of four principle psychological functions (Adams § Chiles, 1960; 1961; Alluisi, Chiles, Hall, & Hawkes, 1963; Alluisi § Fulkerson, 1964; Alluisi, Hall, & Chiles, 1962); these functions (with the name of the specific task given in parentheses) are (1) watchkeeping, vigilance, and attentive functions (warning-lights, blinking-lights, and probability monitoring), (2) sensory-perceptual functions (target identification), (3) memory functions, both short- and long-term (arithmetic computations), and (4) time-sharing functions (all tasks). In the modified version of the MTPB, workers were required to time- share the various tasks. Specifically, the worker was responsible all of the time for the three watchkeeping tasks (warning-lights, blinking-lights, and probability monitoring), but only part of the time for each of the other tasks (target identification and arithmetic computations). Thus, the relative demands on performance during a l-hr period are varied from low to medium to high depending on whether the watchkeeping tasks are presented alone or with one of the other tasks. The basic 1-hr task program is shown in Table C-1. As indicated, there were 5 min of preliminary instructions about the tasks of the MTPB, followed by 25 min of performance testing. During the first 25 min of testing, there were 5 min of low-demand performance (monitoring tasks only) and 20 min of medium-demand performance (monitoring and target identification). This sequence of testing was then repeated for a second 25 min in which the arithmetic computations task was used in place of the target identification task so as to provide for 20 min of high-demand performance. Table C-1 Basic 1-Hour Task-Performance Schedule 5-Minute Interval in Each 1-Hour Period Performance Task 13 2 4 5 6 7 2 310 101 Blinking-Lights Monitoring X X X X X X X X X X Warning-Lights Monitoring 2 X X X X XZ X X X X X Oo Oo od or Probability Monitoring 5 X X X X XH XX X X X g a Target Identification > X X X X § 5 5 Arithmetic Computations = = X X X X eo + BOE mS Level of Demand ET SSE gM SD =o = 22222 SE 2 ¥£ = 138 (C-2) PROBABILITY MONITORING TARGET CODE-LOCK IDENTIFICATION A \ SOLVING 7 x \ 7 X \ Z—1 5 \Q =X x XX XX © ® &- J 1 1 1 << = ~® ®®e ®] = ’ RR 2 ® | = 3[7[+[0[9[-[3]5] fii L \ ll 7 ] E \ ZZ = | WARNING-LIGHTS \__ arithmetic 47 BLINKING-LIGHTS MONITORING COMPUTATION MONITORING Figure C-1. Schematic diagram of the front view of a MIPB operator panel. Tasks of the MIPB.--The MTPB tasks were displayed on each of five identical operator panels (one for each member of a 5-man worker group) similar to the one shown schematically in Figure C-1. The tasks, as modified for use in the current research, are described in the following paragraphs. Three passive or watchkeeping tasks were employed to assess the worker's performance of watchkeeping, vigilance, and attentive functions; these are identified as the blinking-lights, warning-lights, and probability montitoring tasks. The first of these tasks is presented by a pair of warning-lights, one green and one red, located on the extreme left of the panel. The task requires that the worker respond to the relatively frequent lighting of a red light or the unlighting of a green light. Located on the extreme right of the panel is a pair of vertically arranged amber lights which flash alternately at an over-all rate of two 139 (C-3) flashes per second. This task, blinking-lights monitoring, requires that the subject respond to a relatively frequent arrest of this alternation of the two amber lights by pressing the button underneath the two lights. The third passive task, probability monitoring, presents a task which is more complex than the former two. It is displayed along the top of the operator's panel and consists of four semi-circular scales, each with a pointer which normally rests at zero. The critical signal is an introduction of a bias which shifts one of the pointers by approximately 20 scale units (1/5 of the scale) to the right or to the left. The task requires the worker to detect this critical signal or bias and press the appropriate button under the meter in question. Critical signals are presented at an over-all rate of 72 signals per hour for each of these watchkeeping tasks. Inter-signal intervals were scheduled randomly and independently for each task. The active tasks consist of the target identification and arithmetic computations tasks. The target identification task (TID) is presented to the worker by a 4-in square array of 36 close-butted lights which form a 6 by 6 matrix used to present the "metric histoforms'" employed in the TID task. Each TID problem consists of two metric histoforms which are presented sequentially for 5 and 2 sec, respectively. The worker is required to report whether the sequentially presented metric histoforms are the same or different. His answer is indicated by pressing an appropriate push button located to the left of the TID display. Knowledge of results is provided by a blue indicator light which is illuminated above the correct response button just prior to the presentation of the next problem. The task is force-paced at a rate of two problems per min, An amber light on each panel provided a 30-sec warning or "ready" signal prior to the beginning of the first problem. The second active task, arithmetic computations (MATH), requires that a worker add two, 2-digit numbers and then subtract from that sum a third 2-digit number. The answer is indicated by manipulation of four decade thumb switches immediately to the right of the numerical indicators, and a push button just to the left and slightly above the switches, If the answer is correct, a blue indicator light is 1it as the problem is removed and prior to the presentation of the next problem. The task is force- paced at a rate of three problems per min during the task presentation. The beginning of this task presentation is also signaled by an amber light which is lighted 30 sec prior to the first problem. Performance Measures of the MTPB The modified MTPB provides 36 non-independent measures of general performance. Of these, 10 measures represent the over-all individual performances of the workers during the entire time that a particular task was presented (with and without the presentation of the other tasks) during the 1-hr test period. These measures, therefore, are regarded as the primary individual-performance measures obtained from the five tasks of the MTPB; the behavioral measures are listed in Table C-2, The information given in Table C-2 shows that separate measures of latency (mean response time) were provided by each of the three watchkeeping tasks, i.e., red and green warning-lights, blinking-lights, and probability 140 (C-4) monitoring. In addition, the probability monitoring task provided measures of accuracy and false responding as well. The accuracy measure of this task represents the percentage of correct detections of the total number of biases (or signals) presented; the false re- sponding measure represents the total number of false responses made during the entire presentation time of the task. For each of the Table C-2 Over-all Performance Measures of the MIPB Performance Behavioral Statistical Task Measure Measure Warning-Lights (Red) (1) Speed Mean Response Time Warning-Lights (Green) (2) Speed Mean Response Time Blinking-Lights (3) Speed Mean Response Time Probability Monitoring (4) Speed Mean Response Time (5) Correct Detections Percent Correct (6) False Responding Total False Responses Target Identification (7) Accuracy Percent Correct (8) Attempted Percent Attempted Arithmetic Computations (9) Accuracy Percent Correct (10) Attempted Percent Attempted active tasks, target identification and arithmetic computations, measures of accuracy and the solutions attempted were provided. For each of these measures, the percentages are based on the total number of pro- blems presented for each task respectively. In addition to the over-all individual-performance measures, 18 additional behavioral measures represent the performance of the workers during different levels of work load provided by the addition of other tasks. That is to say, the performances on each of the watchkeeping tasks during low-demand performance (i.e., watchkeeping alone) as well as during medium- and high-demand performances (i.e., watchkeeping with target identification and with arithmetic computations) were determined. Therefore, for each of the behavioral measures derived from the watch- keeping tasks listed in Table C-2 there are an additional three measures, depending upon whether the task was performed alone, with TID, or with MATH. For the convenience of the reader, these measures are listed in Table C-3. 141 (C-5) The remaining eight individual-performance measures were derived from the performances of the workers on the active tasks. Since performance on these tasks is somewhat more difficult than the performances on the watchkeeping tasks, the first half of their 20-minute presentation (see Table C-1) may represent acquisition or learning effects. In order to account for these possible effects measures were obtained separately during the first 10 minutes and during the second 10 minutes of the task Table C-3 Work-Load Measures of the Watchkeeping Tasks Performance Performance Behavioral Statistical Task Demand Level Measure Measure Warning-Lights Low (Alone) (11) Speed Mean Response Time (Red) Med. (w/TID) (12) Speed Mean Response Time High (w/MATH) (13) Speed Mean Response Time (Green) Low (Alone (14) Speed Mean Response Time Med. (w/TID) (15) Speed Mean Response Time High (w/MATH) (16) Speed Mean Response Time Blinking-Lights Low (Alone) (17) Speed Mean Response Time Med. (w/TID) (18) Speed Mean Response Time High (w/MATH) (19) Speed Mean Response Time Probability Low (Alone) (20) Speed Mean Response Time Monitoring Med. (w/TID) (21) Speed Mean Response Time High (w/MATH) (22) Speed Mean Response Time Low (Alone) (23) Correct Percent Correct Detections Med. (w/TID) (24) Correct Percent Correct Detections High (w/MATH) (25) Correct Percent Correct Detections Low (Alone) (26) False Total False Response Responding Med. (w/TID) (27) False Total False Response Responding High (w/MATH) (28) False Total False Response Responding presentation. From the worker's point of view, however, there was no break between the first and second 10-minute presentations. These eight behavioral measures are listed in Table C-4. 142 (C-6) Table C-4 Performance Measures of the Active Tasks Performance 10-Minute Behavioral Statistical Task Period Measure Measure Target First (29) Accuracy Percent Correct Identification Second (30) Accuracy Percent Correct First (31) Attempted Percent Attempted Second (32) Attempted Percent Attempted Arithmetic First (33) Accuracy Percent Correct Computations Second (34) Accuracy Percent Correct First (35) Attempted Percent Attempted Second (36) Attempted Percent Attempted VISUAL ACUITY TEST The near and far visual acuity of each worker was determined individually for both left and right eyes by means of a Bausch and Lomb Ortho-rater, Type 71-21-31. For each test, the test objects appeared on a single slide in 15 steps of progressive difficulty over a range equivalent to a Snellen rating of from 20/200 to 20/13. Prior to testing, each worker was shown a sample card on which the test object appeared; a reproduction of the test object shown on that card is presented in Figure C-2. The worker was told to identify the corner containing the large checkerboard pattern by saying TOP, BOTTOM, LEFT or RIGHT. While the experimenter was indicating the corners in which the pattern could appear, the sample card was rotated to the appropriate position. Since this is a test of absolute visual acuity, testing was per- formed without visual correction. After removing either glasses or contact lenses as appropriate, each worker placed his forehead against the headrest provided on the apparatus and was told to look into the machine at the slide containing the series of checkerboard patterns. The experimenter initially inserted slide F-4 (far acuity, right eye) and inquired about pattern 1. The following question was then asked: "In the large pattern at the top, the number 1 pattern, do you see in which corner the checkerboard pattern appears?" If a correct response were given by the worker, the experimenter in- quired about pattern 4, and then pattern 8. If pattern 4 were missed, patterns 2 and 3 were given. If pattern 8 were missed, patterns 5, 6, and 7 were examined. If pattern 8 were correctly identified, successive patterns from 9 through 15 were examined until two consecutive patterns were missed. 143 (C-7) The number of the last correct frame served as the score for the eye tested at the acuity index examined. This testing procedure was repeated with slides F-5 (far acuity, left eye), N-2 (near acuity, right eye), and N-3 (near acuity, left eye). The order of presentation of the slides was counterbalanced in order to control for effects due to practice. The average duration of this test was approximately 2 minutes. Measures of visual acuity.--As previously stated, the number of the last correct frame served as the measure of visual acuity for the eye tested at either near or far vision. The Snellen visual acuity equiva- lents of the Ortho-Rater acuity levels and the visual angle subtended by each of the successive patterns are given in Table C-5 (these data have been adopted from the Reference Manual of the Bausch & Lomb Optical Company, Rochester, New York). Each of the four visual acuity measures obtained by the Ortho-Rater is listed in Table C-6. Figure C-2. Sample visual acuity test object used by the Bausch & Lomb Ortho-Rater. 144 (C-8) Table C-5 Visual Acuity Equivalents of Ortho-Rater Acuity Levels* Test Pattern Visual Snellen Number Angle Visual Equivalent 1 10.0" 20/200 2 5.0! 20/100 3 3.33! 20/67 4 2.5! 20/50 5 2.0" 20/40 6 1.67! 20/33 7 1.43! 20/29 8 1.25" 20/25 9 1.11" 20/22 10 1.0 20/20 11 0.91" 20/18 12 0.83! 20/17 13 0.77? 20/15 14 0.71" 20/14 15 0.67" 20/13 *From Bausch § Lomb Reference Manual, p. 33. Table C-6 Behavioral Measures of the Visual Acuity Test Performance Test Behavioral Measure Statistical Measure Ortho-Rater (Far Vision) Ortho-Rater (Near Vision) (37) Right Visual Acuity (38) Left Visual Acuity (39) Right Visual Acuity (40) Left Visual Acuity Test Pattern Number Test Pattern Number Test Pattern Number Test Pattern Number 145 (C-9) AUDITORY ACUITY TEST Two indications of auditory acuity were determined individually for each worker tested. Initial threshold values were acquired by means of a Maico Audiometer, Model F-1, for both left and right ears at frequencies of 500, 1000, 2000, 4000, and 8000 Hz (the earphones were "Calibrated Audiometric Headset Noise Barriers,' Model M-7, which were fitted with Maico, Circumaural, Air Seal Cushions to attenuate the ambient noise levels of the testing situation). A single tone-decay test was then made on the ear in which, and using the frequency at which, the highest threshold value had been recorded. Threshold Test Each worker was seated initially with his back to the experimenter and given the following instructions: "This is a test of your hearing. I will present a series of tones to you. When you hear a tone, raise your hand. Now put on the head-phones with red ear- phone of the right ear and blue ear-phone on the left ear." The experimenter began by presenting a 40 dB impulse tone of either high (8000 Hz) or low (500 Hz) frequency to either the left or right ear (the order of testing was counterbalanced in order to control for practice effects). If the tone were heard, the dB setting was successively decreased by 10 units, until the tone was missed. It was then successively increased by 5 units, until the worker reported hearing the tone again, and then decreased by steps of 5 units until the tone was missed. The procedure was repeated until the subject responded positively at least twice at a minimal dB setting. The minimal setting was recorded as the threshold score for the examined frequency and the ear tested. If the 40 dB tone was not heard, the dB setting was successively increased by 20 units until the tone was heard. At this point, the dB setting was successively de- creased by 10 units, as before, until missed, and then increased and decreased by 5 units until a threshold value was achieved. This procedure was repeated for each frequency in the sequence and for both left and right ears. Tone-Decay Test After the auditory threshold values had been determined, the worker was read the following instructions in preparation for the tone-decay test: "Now I want you to raise your hand when you hear the tone. Then keep your hand up for as long as you hear that tone." The audiometer was set for the appropriate ear, dB reading, and frequency at which the highest dB value had been recorded in determining the thresholds. If equally high dB values occurred at more than one frequency for a single ear, the high frequency was used. If equally high values were recorded in both ears, the poorer ear (displaying relatively high dB values) was tested. A continuous tone was presented 146 (C-10) Table C-7 Behavioral Measures of the Auditory Acuity Tests Performance Behavioral Statistical Task Measure Measure Right Ear-Threshold Test 500 Hz (41) Auditory Threshold Decibel Value 1000 Hz (42) Auditory Threshold Decibel Value 2000 Hz (43) Auditory Threshold Decibel Value 4000 Hz (44) Auditory Threshold Decibel Value 8000 Hz (45) Auditory Threshold Decibel Value Left Ear-Threshold Test 500 Hz (46) Auditory Threshold Decibel Value 1000 Hz (47) Auditory Threshold Decibel Value 2000 Hz (48) Auditory Threshold Decibel Value 4000 Hz (49) Auditory Threshold Decibel Value 8000 Hz (50) Auditory Threshold Decibel Value Tone-Decay Test First Trial (51) Duration of Tone Time, in Seconds Second Trial (52) Duration of Tone Time, in Seconds until the worker lowered his hand. sec, this was recorded, and the test was concluded. If the tone had been heard for 60 If the tone had been heard for less than 60 sec, the duration was recorded, the dB level was raised by 5 units, and a second duration was recorded before concluding the test. tests was approximately 10 min. Measures of Auditory Acuity The average performance time for the two auditory Auditory threshold values were determined for each ear at frequencies of 500, 1000, 2000, 4000, and 8000 Hz. at each of these frequencies served as the measure of performance (each reading was adjusted, however, according to the specific calibration characteristics of the audiometer for each testing session). The actual decibel value obtained In addition, the tone-decay test provided a measure of the duration that the specific tone remained audible to the worker. Table C-7. These measures are summarized in MUSCULAR STRENGTH, ENDURANCE, AND RECOVERY, AND TREMOR TESTS These two tests were employed in conjunction with each other. They were performed by each worker in the following order: .tremor was tested in both right and left hands, then strength, endurance, and recovery (SER) was 147 (C-11) tested for the preferred hand only, and finally, an additional tremor test was performed with each hand. Both tasks were performed at a single testing station and as little time as possible elapsed between tasks. Although the two tasks were interrelated, they are discussed separately. Strength, Endurance, and Recovery During each SER testing session, each worker was measured in a standardized manner: a measurement of original maximum strength (S1) was obtained; exactly 1 min later, a measurement of endurance (E) was made at a load equal to 50% of the maximum strength. This was followed by a 1-min rest and a final maximum strength response (S2). The measurement procedure may be summarized as follows: Maximum One 50% Load One Maximum Strength------ Minute------ Endurance------ Minute------ Strength ($1) Rest (B) Rest (S72) Apparatus.--The apparatus for this task was a portable ergometric system which provided for a dynamic input from the worker and a dual output of information. This system is one of a series of similar devices used in the research of Dr. Lee S. Caldwell of the Experimental Psychology Division of the U.S. Army Medical Research Laboratory (AMRL), Fort Knox, Kentucky. The apparatus was designed and built by the AMRL personnel and loaned to the Performance Research Laboratory for use in the current research. A schematic diagram of the component parts of the apparatus is shown in Figure C-3. CHART RECORDER 1 DYNAMOME TER STRAIN : HANDLE AMPLIFIER POUNDAGE or == METER TT Figure C-3. Schematic diagram of the apparatus used in the tests of Strength, Endurance, and Recovery. 148 (C-12) The input portion of the apparatus was an isometric handle, positioned approximately at the height of and adjacent to the seated worker's knee. The handle was bolted to the vertical section of an inverted T-shaped piece of steel pipe, which was in turn affixed to a horizontal bar bolted to a 26-by-26 in section of gray-painted, 3/4- in plywood. A chair was placed on this wooden platform such that the handle was on the worker's preferred side. Both the height and the depth of the handle were adjustable; thus, all workers were able to grip the handle in the same relative position, regardless of worker height. Four strain gages mounted on the handle and wired as a Wheatstone bridge formed the balanced input circuit to a solid-state strain amplifier. When a force was applied to the handle, the bridge was thrown out of balance and a current directly proportional to the applied force was amplified and fed in parallel to both a display voltmeter, which had a scale marked in pounds and was visible to the worker, and a heat sensi- tive chart recorder, which provided a continuous record of the worker's output. The equipment was contained in its metal carrying case, and only this case and the meter were visible to the worker during the testing. Procedure.--The worker was seated in the chair so that the hand-grip dynamometer was on his preferred side. The hand-grip was adjusted at approximately the height of the worker's knee and at a depth such that his elbow would form a 90° angle during the SER trials. The importance of maintaining this position and a proper positioning of the hand on the hand-grip was explained to the worker. The general paradigm and instructions were given to each worker in the following manner: "This is going to be a test of your strength and endurance. I am going to ask you to use the handle at your side. Place your hand underneath the grip in this manner (demonstrate) and pull up on it like this (demonstrate). Keep your (right, left--non-preferred) arm down at your side and your feet on the floor during the pull. We will have three separate pulls during this trial. During the first pull I want to determine your maximum strength. I want you to pull as hard as you can for just long enough for me to get a readout on this chart--a couple of seconds. Try to reach your maximum as quickly as possible so that you don't waste your energy. Now wait until I start my recorder and tell you to begin, then pull as hard as you can until I tell you to stop. Okay? Ready (turn on recorder) . . . go." When it was determined that the worker had exerted his maximum strength pull (usually requiring 1-2 sec) he was instructed to relax, the recorder was turned off, and the experimenter began timing a 1- min interval. During the interval, it was necessary for the experi- menter to compute, from the chart record, the pounds of force exerted during the strength pull, enter this data on the score sheet, and compute and enter 50% of this amount for purposes of the next pull. During this time the worker was given the following instructions for the endurance pull: 149 (C-13) "The next pull will be an endurance-type pull. I want you to use the meter on the wall to your (right, left-- non-preferred side) and watch it while you pull, pulling this time only until the meter reads (the computed 50% value) pounds. Once you have the meter at (the computed 50% value) pounds, keep it there as long as you can. It will not be necessary to pull as fast as you did last time. Okay? Ready (once the l-minute interval is over; turn on recorder) . . . go." When the worker had exhausted his endurance and indicated this, he was again told to relax while the experimenter turned off the recorder and began timing a second 1-min interval. During this interval, the worker was informed that the third and last pull was to be a second maximum-strength pull, and his memory was refreshed as to the technique. When the end of the interval arrived, the second strength pull was handled as the first. The following instructions were given to the worker prior to this final strength pull: "The last pull will be just like the first one, a maximum strength pull--as hard as you can for a couple of seconds. Okay? Ready (once interval is over; turn on recorder) . . . go." After the worker had finished this pull, he was told to relax; this completed the series of SER tests. Measures of the SER test.--Many of the investigations conducted during recent years have employed isometric measures of strength (Hunsicker & Greey, 1957), and some have used a measure of muscular endurance obtained by use of the Relative-Load Technique. Caldwell and his co-workers (Caldwell, 1960,; 1962; 1963; 1964a; 1964b; 1964c; 1965; Caldwell § Smith, 1966; Lyddan, Caldwell, § Alluisi, 1971) have demonstrated both the utility of these measures and the high reliability of the endurance measures; the load-endurance functions obtained by Caldwell closely match those of the European investigators who developed the Relative-Load Technique (see Caldwell, 1963). The SER testing provided five separate measures of muscular output. These measures were defined as follows: original muscular strength (Si), measured as the force, in pounds, of the first strength pull; muscular endurance (E), measured as the duration, in seconds, of the endurance pull (the force of the endurance was derived by calculating 50% of Sp); and secondary strength (Sy), defined as the force, in pounds, of the second strength pull. Strength recovery (Rg) was based on the percentage of recovery from the first, Sj, to the second, Sp, strength pulls. A measure of impulse was also derived by multiplying the force of the endurance squeeze (i.e., 50% of S1) by the duration of that squeeze. A list of the SER measures is provided in Table C-8. Tremor The test of tremor is similar, if not identical, to the SAM Arm- Hand Steadiness Test produced by the Department of Psychology, AAF School of Aviation Medicine (see Melton, 1947, pp. 501-557). The basic 150 (C-14) Table C-8 Behavioral Measures of the SER Tests Performance Behavioral Statistical Test Measure Measure Original Strength (SJ (53) Muscular Force Number of Pounds Endurance (E) (54) Muscular Endurance Total Seconds Secondary Strength (S,) (55) Muscular Force Number of Pounds Strength Recovery (R) (56) Recovery Percent Recovery Impulse (I) (57) Impulse (Force X Pound-Seconds Duration) dimensions of the apparatus, including stylus and target, and the procedures in administering the test were adapted from Model CM103A4 of the SAM Arm-Hand Steadiness Test. Since this test of tremor was interrelated with the tests of strength, endurance, and recovery, its administration was performed according to the following paradigm: Pre-test of Tremor---- SER ----Post-test of Tremor (Preferred hand, (Preferred hand) (Preferred hand, Non- Non-preferred hand) preferred hand) Apparatus.--A dimensional drawing of the apparatus for this task is shown in Figure C-4. The test unit consisted of a 14 1/2-by-10-by-10 in board, painted gray, on which was mounted a 10-by-10-by-8 in gray metal contact box (BUD RADIO, CU 880). In approximately the center of the front of the contact box was the 'contact hole," which was 1/4 in in diameter. Also used was a probe, consisting of a 4 1/2 in long handle, 1/2 in in diameter, from which protruded a 4 1/2 in long, 1/8 in metal stylus. This equipment was connected to a pair of Hunter timers (Model 111-C) such that when they were turned on, one timer would time-out 30 sec and then automatically begin the second timer, which would time-out another 30 sec. When the stylus touched the side of the contact hole, a circuit was completed through a set of contacts on one of the Hunter timers (whichever one was operant at the time of the contact) to one of a pair of Sedeco impulse counters (Type TCeZ4E), each of which was enabled by one of the timers. Thus, the number of contacts made during the 1-min interval was separately recorded for each of two sequential 30-sec trials. A schematic drawing of the equipment involved in instrumenting this task is shown in Figure C-5. 151 (C-15) 1 t 8 1/2" Figure C-4. Dimensional drawing of the apparatus and probe (stylus) used in the test of tremor. Procedure. --The worker was seated in the chair and positioned with his preferred shoulder directly in front of the apparatus so that he had room to fully extend his preferred arm. He was shown the stylus and the grip to be used during the trial. The following instructions were then read to the worker: "This is going to be a kind of steadiness test. I'm going to ask you to grip this probe in this manner (demonstrate) and insert it in this hole (show location) about an inch or so and try to keep from hitting the sides of the hole as much as possible. Position yourself so that your shoulder is directly in front of the hole and so that you can fully extend your arm. We'll do your (right, left--preferred) hand first and then switch and do your other hand. The trial will take 1 minute per hand. Try to get as comfortable as possible so that you don't move during the trial. Okay? Now if you'll get ready, go ahead and place the tip of the probe into the hole, and when you're ready, I'll start the timers (affirmative response). Okay, begin." 152 (C-16) HUNTER TIMER IMPULSE COUNTER 1 = TEST x UNIT HUNTER oo TIMER IMPULSE COUNTER 2 = A J— —— os vous PROBE Figure C-5. Schematic diagram of the apparatus used in the tremor test. Once the worker appeared ready, the experimenter initiated the 1- min trial by starting the timers. At the 30-sec mark, the circuit automatically switched from one timer (and counter) to the other; the experimenter then recorded the number of hits for the first 30 sec and cleared that counter. At the end of 1 min the circuit automatically stopped, the number of hits for the second 30 sec were recorded and cleared from the second counter. The experimenter then turned off the timers and told the worker to prepare to repeat the trial using his non- preferred hand. Once the worker was positioned properly, the timers were started and the trial was repeated as before. At the end of these pre-test trials, the worker performed the SER tasks. Immediately upon the cessation of the SER tasks, the Tremor task was repeated in exactly the manner and order (preferred hand, non- preferred hand) in which it was performed before. At the end of the post-test trials, the Tremor task was considered concluded. (Note: During the trials it was necessary for the experimenter to closely 153 (C-17) monitor the counters to insure that the worker did not hold the tip of the stylus against the side of the hole; if this were attempted, the counter would "hang up'' halfway between two numbers and the worker was then reminded that he was to try to avoid touching the side of the hole during the trial. The worker's body position was also monitored to insure that it did not change during the course of a trial.) Measures of the Tremor test.--The behavioral measures derived from the tremor test represent the tremor or lack of muscular control of the arm and hand when the arm is extended at full length (Melton, 1947). The specific measure employed in assessing the degree of muscular control is the total number of times the stylus made contact with edge of the target hole. Since the workers were given two 30-sec test trials for both the preferred and non-preferred hands, a total of four measures were obtained during both the pre-test and post-test trials. Table C-9 provides a listing of the various trials and the measures derived therefrom. Table C-9 Behavioral Measures of the Tremor Test Performance Behavioral Statistical Task Measure Measure Pre-Test Trials Preferred Hand First 30-Seconds (58) Muscular Control Number of Hits Second 30-Seconds (59) Muscular Control Number of Hits Non-Preferred Hand First 30-Seconds (60) Muscular Control Number of Hits Second 30-Seconds (61) Muscular Control Number of Hits Post-Test Trials Preferred Hand First 30-Seconds (62) Muscular Control Number of Hits Second 30-Seconds (63) Muscular Control Number of Hits Non-Preferred Hand First 30-Seconds (64) Muscular Control Number of Hits Second 30-Seconds (65) Muscular Control Number of Hits 154 (C-18) DIGIT-SPAN TEST Each worker was individually instructed to listen to, and then repeat, a sequence of single-digit numbers read aloud by the experimenter. The experimenter began by reading a series (Trial 1) of three numbers. If the worker was able to correctly repeat the series, a sequence of four numbers was then presented. For every correct repetition of a series by the worker, a subsequent sequence was presented, in which the number of digits was increased by one unit to a maximum of nine digits. Whenever the worker answered incorrectly, a second series (Trial 2) was presented which contained the same number of digits as occurred in the previous (incorrect) trial. Any deviation from the sequence of digits presented by the experimenter was considered an incorrect response. If the second trial of a series were repeated correctly, the procedure continued, until two trials of a given series were missed. The average duration of the test was approximately 2 min. Table C-10 provides a listing of the number sequences employed in the digit-span test. Measures of the Digit-Span Test The score was the longest sequence of digits repeated without error in either trial. The measure for this test is given in Table C-11. MULTIPLE AFFECT ADJECTIVE CHECK LIST The Multiple Affect Adjective Check List (MAACL), developed by Zuckerman and Lubin (for references, see Zuckerman, 1960; Zuckerman, Lubin, Vogel, & Valerius, 1964) and published by Educational and Industrial Testing Service, San Diego, California, was employed in this study. It consists of a printed sheet on which appear a list of 132 adjectives. In performing the test, each worker was required to check those words or adjectives which describe how he felt at the time of testing. Although no time limit was given, the MAACL was usually completed within 5 min. The directions for performing the test were printed on the test and are as follows: "On this sheet you will find words which describe different kinds of moods and feelings. Mark an "X" in the boxes beside the words which describe how you feel now - today. Some of the words may sound alike, but we want you to check all the words that describe your feelings. Work rapidly." So Measures of the MAACL The MAACL is scored along two dimensions (positive and negative) for each of three affective states; i.e., anxiety, depression and hostility. The positive scores reflect the number of marked items that should have been avoided, whereas the negative scores indicate the number of unmarked items that should have been checked in each affect pool. These positive and negative scores are then combined (summed) to provide overall scores for anxiety, depression, and hostility. An index of general discomfort, or dysphoria was then computed by summing the three individual scores. High scores on the individual scales indicated greater degrees of anxiety, depression, hostility, or dysphoria, respectively. The four psychological measures obtained from the MAACL are summarized in Table C-12. 155 (C-19) Table C-10 Number Sequences Employed in the Digit-Span Test Number Series Trial 1 Trial 2 3 4-6-1 5-8-3 4 5-3-2-8 6-1-7-5 5 5-6-8-4-9 8-6-9-4-7 6 6-1-8-3-7-2 2-8-1-3-7-6 7 7-9-1-6-3-8-5 4-1-7-5-2-8-3 8 9-3-6-4-7-1-5-2 5-2-8-1-7-4-9-6 9 4-8-5-9-7-3-6-9-1 8-2-7-4-5-3-6-7-1 Table C-11 Behavioral Measure of the Digit-Span Test Performance Behavioral Statistical Task Measure Measure Digit-Span Test (66) Immediate Recall Sequence Number 156 (C-20) Table C-12 Behavioral Measures of the MAACL Performance Behavioral Statistical Task Measure Measure MAACL (67) Anxiety Sum of the Negative and Positive Scores (68) Depression Sum of the Negative and Positive Scores (69) Hostility Sum of the Negative and Positive Scores (70) Dysphoria Sum All Negative and All Positive EYE-HAND COORDINATION TASK The test of eye-hand coordination used in this study was employed originally by Poock (1967) at the University of Michigan. (Thus, it is referred to as the Michigan Eye-Hand Coordination Test.) Although Poock (1967) used the total time for completing the maze as a basis for predicting performance in small-part operations in industry, recent modifications of the scoring techniques have allowed for measurements of hole-to-hole times and hole-to-hole variability. These modifications have been employed by Chaffin and his co-workers at the University of Michigan in their studies of the behavioral effects of occupational exposure to low-levels of mercury (Chaffin, Dinman, Miller, Smith, § Zontine, 1973). The equipment made for this study by the Performance Research Laboratory was based on specifications of the Michigan Eye-Hand Coordination Test furnished by Dr. Donald Chaffin. Apparatus The apparatus for this task consisted of a hole plate, a sounding board, a microphone, a tape recorder, and a stylus. A schematic diagram of the components employed in this task is shown in Figure C-6. The hole plate was aluminum; it measured 8-by-8-by-1/8 in, contained 119 holes (each 1/8 in in diameter), and was painted white with a thin black line (1/16 in wide) which connected the holes. As shown in Figure A-7, the interconnecting lines formed a maze pattern which the workers were required to follow in performing this task. Switches (MICRO, Model L4) were mounted beneath the first and last holes so that when a stylus (A, B. Dick, No. 469) was inserted, a Standard Electric Timer (Model S-1) was started (first hole) and stopped (last hole), and a total time (to the [1 MICHIGAN EYE-HAND ROLY gr TESTING APPARATUS | rns SONY TAPE RECORDER MICROPHONE Figure C-6. Schematic diagram of the apparatus used in the test of Eye-Hand Coordination, nearest .01 sec) between the two holes was obtained. The plate containing the maze pattern was mounted in a sturdy wooden frame. Directly beneath the hole-plate was the sounding board--an aluminum plate 1/32 in thick and cut to fit the wooden frame. Attached to the aluminum sounding board was an Electro-Voice, Model 805 Contact Microphone, which formed the input into a Sony Audio Tape Recorder, Model TC-104. The recorded sound of the stylus striking the sounding board was later scored by use of a Digital Equipment Company PDP-12A Computer (see Appendix J for a full description of the scoring procedure). Procedure The worker was seated facing the apparatus. After determining which was the preferred hand, the experimenter turned the plate so that the starting-hole was in the correct position. The worker was then given the following instruction: "This is an eye~hand coordination task. I want you to grip this stylus about 2 in from the tip (hold stylus and demonstrate) and completely insert the tip of the stylus into each of these holes (indicate plate) while following the black line. Proceed as rapidly as possible without missing any of the holes. Do not rest your arm on the table or the apparatus while you are performing this task," 158 (€-22) STAI i LHD tN\D Figure C-7. Maze pattern utilized in the Michigan Eye-Hand Coordination Task (actual size). 159 (C-23) The worker was then asked to take the stylus in his preferred hand and prepare to begin, but to wait for the experimenter's signal before starting. and the experimenter said "GO!" Once the worker was ready, the tape recorder was turned on The worker's performance was monitored during the trial to insure that both the switches (beneath the first and last holes) were activated. At the end of the trial, the experimenter turned off the recorder, recorded the time required by the worker to complete the trial, and At this point, the plate was rotated so that the starting point would be on the side opposite to that used by cleared the running time counter. the preferred hand. The worker was then told to take the stylus in his non-preferred hand in preparation for the second trial, which was run in a manner identical to that of the first. After the time from this second trial was recorded, the eye-hand coordination test was concluded. Measures of the Eye-Hand Coordination Test The data obtained from the Michigan Eye-Hand Coordination Task yielded three primary measures of coordination between the muscles of the hand and arm and the visual system. Measures of the total times for completing the 119 hole maze were determined separately from the performance of both the preferred and non-preferred hands. In addition, measures of the mean hole-to-hole times as well as measures of hole-to- hole variability were obtained. in Table C-13. Table C-13 A summary of these measures is provided Behavioral Measures of the Eye-Hand Coordination Test (80) Response Variability Performance Behavioral Statistical Task Measure Measure Right Hand Michigan Eye-Hand Test (71) Total Responses Number of Hits (72) Speed Total Response Time (73) Speed Mean Inter-Hole Time (74) Response Variability Standard Deviation (75) Response Variability Standard Error of the Mean Left Hand Michigan Eye-Hand Test (76) Total Responses Number of Hits (77) Speed Total Response Time (78) Speed Mean Inter-Hole Time (79) Response Variability Standard Deviation Standard Error of the Time 160 (C-24) APPENDIX D RESEARCH METHODOLOGY OF THE SYNTHETIC-WORK TECHNIQUE Prepared by Ben B. Morgan, Jr. and Earl A. Alluisi A synthetic-work approach (Alluisi, 1967, 1969; Chiles, Alluisi, § Adams, 1968) has been developed to provide measurements of multiple-task performance obtained within the domain of work behavior. The basis for this approach is a laboratory work situation that is created by combining into a synthetic job six tasks that represent functions which man is called upon to perform in just about any job. No specific system has been simulated directly, but a generalized system has been devised in terms of the performance functions represented in many different systems. The data obtained from use of the synthetic-work approach, therefore, are applicable to a wide variety of specific systems that employ the same functions. These functions (and the tasks used in measuring their performance) are the (a) watchkeeping, vigilance, and attentive functions (warning- lights, blinking-lights, and probability monitoring), (b) memory functions, both short- and long-term (arithmetic computations), (e) sensory-perceptual functions (target identification), (d) procedural functions, including such things as interpersonal coordination, cooperation, and organization (code-lock solving), (e) communication functions, including the reception and transmission of information (not directly measured, but involved in all active tasks of the MIPB), (f) perceptual-motor functions (no direct measure), and (g) intellectual functions (no direct measure). Tasks designed to measure directly certain nonverbal-mediational aspects of intellectual functioning (cf. Alluisi § Coates, 1969; Alluisi §& Morgan, 1971; Coates § Alluisi, 1971; Morgan §& Alluisi, 1971), and a kind of decision-making behavior (cf. Rebbin, 1969) are under development. Some attempts have also been made to employ tracking tasks with the MIPB (e.g., Adams, Levine, §&§ Chiles, 1959; Chambers, Johnson, Van Velzer, & White, 1966; Jennings, Chiles, & West, 1972). Behavioral measures of five of these functions are obtained from the operator's performance in working at the six tasks, which are generally displayed at each of five identical work stations arranged as shown in Figure D-1; there is one work station for each member of a 5-man crew. Subjects are typically required to occupy these work stations for 8 hr per day, and to work at the MIPB tasks as they would any other job. SYNTHETIC-WORK METHODOLOGY Description of the MIPB Tasks Several similar multiple-task performance batteries have been used in the synthetic-work approach to the study of sustained performance. In the MTPB used at the University of Louisville, the tasks are displayed on each of five identical (approximately 12 in high and 20 in wide) instrument or MTPB-operator panels; the front view of one such panel 161 (D-1) Figure D-1. Schematic drawing of work-station area employed. is shown schematically in Figure D-2. Reference should be made to this figure in order to understand the task descriptions given below. Warning-lights monitoring.--One of the three watchkeeping tasks is presented with a pair of warning lights, one green and one red, located to the extreme left of the panel. The normal state for this task is for the green light to be lit and red light unlit. At random intervals of time, when a signal is presented, there is a change of state and the subject is then required to turn the green light on should it go off, or the red light off should it come on, by pressing a push button located immediately below the light in question. If the subject fails to respond within 2 min, the non-normal condition is corrected and he is scored with a maximum latency. The subject's latency in responding to each non-normal identification is recorded on a 0.1 sec timer, but prior to analysis it is transformed to a normalized speed score (cf. Alluisi, Thurmond, & Coates, 1967, Ap. D, p. 79). Blinking-lights monitoring.--On the extreme right of the panel there is a pair of vertically arranged amber lights that are employed to present a second watchkeeping task. Under normal conditions the two lights flash alternately at an over-all rate of two flashes per second. The critical signal is an arrest of this alternation in which either the top or the bottom light flashes at twice its usual rate. The duration of each flash, both in the normal and arrested condition, 162 (D-2) PROBABILITY MONITORING TARGET Tso LOCK IDENTIFICATION \ SOLVING 5000 © ®® ® al Te @®® ®O® XX KX 2 ® = 4]3]7,6/0/9/2[8)5] (#4 X | XI , J XxX T X /7— T F 5 3 ce 4 Z 3 = | WARNING-LIGHTS \ ARITHMETIC J BLINKING -LIGHTS _| MONITORING COMPUTATION MONITORING Figure D-2. Schematic diagram of the front view of an MIPB operator panel. Letters in circles represent indicator lights, A--amber, B--blue, G--green, and R--red; the smaller circles with crossing diagonals represent push buttons. is 0.25 sec. If the subject fails to respond within 2 min, the non- normal condition is corrected and he is scored with a maximum latency. This task has been recently added to the battery, and was initially used in BEID-1 (cf. Alluisi, et al., 1967, p. 58); there are prior research findings on which it is based (cf. Chinn & Alluisi, 1964; Smith, Warm, § Alluisi, 1966). The length of time during which the critical signal is present is recorded on a 0.l-sec timer, but prior to analysis this latency score is transformed to a normalized speed score (cf. Alluisi, et al., 1967, Ap. D, p. 79). Probability monitoring.--Four semicircular scales located along the upper portion of the panel are used to display the probability- monitoring task. A pointer on each scale is driven by a random program generator. The pointer settings are normally distributed with a mean of zero (12 o'clock position on the scale) and a known standard deviation. 163 (D-3) Introduction of a bias to the programming device causes the mean of the distribution on one of the four scales to shift by a specified amount (usually one standard deviation). This shift in the mean does not affect the variability of the pointer positions. When the subject detects a shift in the mean, he indicates this by pressing a push button under the meter in question--the left push button if he has detected a bias-to-the-left, and the right push button for a bias-to-the-right. Whenever the subject pushes any of the probability-monitoring push buttons, the pointer of the meter in question moves to and stabilizes at the mean of its current distribution (i.e., either zero, or biased right or left). If a bias is present, then a correct response by the subject causes the scale to be reset to a zero-bias condition. Data recorded are the number of bias signals presented, the number of bias signals detected correctly, the number of false responses, and the time required to detect each bias correctly. Data analyzed are the percentage of signals correctly detected, and a measure of the speed of detection (800 sec--the longest intersignal interval-- minus the mean detection time). Arithmetic computations.--Three, 3-digit numbers are displayed along the lower central portion of the panel by means of nine, 1-digit numerical indicators. The operator is required to subtract the third 3-digit number from the sum of the first two. He indicates his answer by manipulation of four decade thumb switches immediately to the right of the indicators, and a push button just to the left and slightly above the switches. Depression of the push button will cause the response to be recorded automatically. If the answer is correct, a blue indicator light (immed- iatley above the numerical indicators, and just to the right of center) is 1it for a 1/2-sec interval as the problem is removed and just prior to the presentation of a new problem. Problems are presented at a rate of three per minute during the 30-min interval allocated to the performance of arithmetic computa- tions in each 2-hr work period. An amber indicator light (immediately above the numerical indicators, and just to he left of center) is lit 30 sec prior to the presentation of the first problem and it remains lit throughout the 30 min. Ten different random orders of a basic set of 570 problems are used--one order each day for the first 10 days of testing, then a simple replication of order 1 on Day 11, 2 on Day 12, etc. Each order is divided into six sections of 95 problems, from which are drawn the 90 problems presented during each 30-min period of arithmetic computations. Subjects are scored in terms of (a) the percentage of problems attempted and (b) the percentage of problems correctly answered. 164 (D-4) Target Identification.--In the center of each subject's panel there is a 4-in square array of 36 close-butted, square lights. These lights, which form a 6-by-6 matrix, are used to present the "metric histoforms' that are employed in the target-identification task. These are contoured figures consisting of lit and unlit elements that give the appearance of solid bar graphs. A finite set of 240 metric histoforms has been drawn at random from the 720 possible 36-element constrained figures (figures in which each of the six possible column heights appears once and only once). Each of these 240 figures is programmed to appear with its base at 6 o'clock (i.e., with columns rising) to represent a ''target' image. Another set of figures, drawn from the same basic set of 720, is used to represent ''choice' images. These latter figures are randomly positioned so that the base of a figure can occur at 12, 3, 6, or 9 o'clock. The task typically presented to the subject is as follows: There is a 5-sec display of the upright figure, or target image. This is followed by a 5-sec off period. Then there is a 2-sec display of a randomly positioned image (choice-A), a 2-sec off period, and a 2-sec display of a second randomly positioned image (choice-B). After a response period of 14 sec, the cycle is repeated with a new stored image and new sensed choice images. Each subject is required to respond by use of one of three push buttons (to the left, just below the display) to indicate whether in his judgment the first, second, or neither of the choice images was the same as the target image. The subject's response is indicated on his panel by the amber light above the push button; the appropriate light is 1it when he makes his response and remains lit until extin- guished when the problem is cycled and a new problem presented. When this is done, and just before a new problem appears, a blue knowledge- of-results indicator is lit for a 1/2-sec interval to inform the subject regarding the correct response to the problem. The basic set of 240 target images is programmed in a constant order on each of 10 different punched tapes, but the answer orders and the 'different' images on each of these tapes are random and dif- ferent within the restriction that in each case an equal number of the three responses is called for. Records are made of the total number of responses and the number of correct responses made by each subject. Data analyzed are the percentage of problems attempted and the percent- age of problems responded to correctly. Code-lock solving.--As presently constituted, the code-lock task is a group-performance task that principally involves procedural func- tions. The task requires the crew to discover the proper sequential order for depressing five push buttons--one for each of the five members of the crew. Three jewel indicator lights (red, amber, and green) and two push buttons (one a spare) are located on each of the five 165 (D-5) panels in the center-right portion between the target-identification and the blinking-lights displays. Illumination of the red light is the signal that a problem is present and unsolved. The amber light is illuminated when any subject depresses his push button, but with no indication as to which subject it was or whether it was just one or more than one who did so. The problem is solved only when each of the five push buttons has been depressed in the correct sequential order for the specific problem. Thus, the red light is extinguished when the correct first subject in the sequence depresses his push button, and it will remain extinguish- ed until an incorrect response is made. When such an erroneous re- sponse does occur, the red light is re-illuminated, and the programming apparatus is reset automatically to the beginning of the sequence. In order to recommence the search for a solution, the correct first sub- ject must depress his button first, then the correct second subject must depress his button, etc. When all five push buttons have been depressed in the correct order, the green light is illuminated as a signal that the problem has been solved. Following a between-problem pause of 30 sec, the green light goes off, the red light comes on, and the crew is presented with a replication of the problem previously solved. This requirement for a '"'second solution'" is included to increase the sensitivity of the task to performance decrements. Following the second solution and a between-problem pause of 30 sec, the green light goes off, the red light comes on, and the crew is presented with a new sequence or code to solve. Several measures of crew performance are employed: Records are made of the time required for code-lock solutions, the total number of responses made, and the number of errors (or programmer resettings). In addition, the data analyzed include the mean number of sequences solved per unit time--a measure that is linearly related to the relative information transmission rate per period, and equally weighted on the speed and accuracy factors that have been identified (cf. Alluisi, Chiles, Hall, § Hawkes, 1963, pp. 28-32). General.--The six tasks were selected to meet certain criteria of validity, sensitivity, engineering feasibility, reliability, flex- ibility, work-load variability, trainability, and control-data avail- ability (cf. Alluisi, 1967, 1969; Alluisi § Fulkerson, 1964, pp. 5-6; Chiles, et al., 1968). In addition, three of the tasks were selected initially on the basis of an analysis of individual operator requirements for long-range, long-endurance weapons systems (cf. Adams, 1958; Chiles, et ac., 1968). The three remaining tasks represent either modifications intended to improve the tasks already in use, or additions to extend the range of functions measured with the performance required by the battery. All of the tasks show very high reliabilities (see Alluisi, 1967; Alluisi, Hall, § Chiles, 1962; Chiles, et al., 1968), and have 166 (D-6) done so since their earliest use (Adams, et al., 1959). Several of the tasks have been described in previous reports: (a) arithmetic computations, probability monitoring, and warning-lights monitoring by Adams and Chiles (1960, pp. 4-6; 1961, Ap. III), (b) code-lock solving by Alluisi, Hall, and Chiles, (1962, pp. 5-6), (ec) target identification by Alluisi, et al., (1963, pp. 4-6), and (d) blinking- lights monitoring by Alluisi and Fulkerson (1964, p. 12). The tasks contained in the current MIPB are nearly identical to those employed in a prior version of the battery (see Alluisi, Chiles, § Hall, 1964, (Ap. I); the tasks were described prior to the construction of the equipment (Alluisi & Fulkerson, 1964, pp. 10-14) and after their use in previous studies of the behavioral effects of infectious diseases (Alluisi, et al., 1967, Ap. A; Coates, Thurmond, Morgan, & Alluisi, 1969, Ap. A; Morgan, Coates, & Rebbin, 1970, Ap. A; Thurmond, Alluisi, § Coates, 1968, Ap. A). A more recent description of the tasks has been provided by Morgan and Alluisi (1972). TASK SCHEDULE The six MIPB tasks are synthesized with the panel into a reasonably realistic work-like situation--a situation that requires the operator to be responsible for the time-sharing of functions at various levels of work load. The work is typically divided over a 2-hr performance period so that the operator is responsible all of the time for the three watchkeeping tasks, but only part of the time for the three active tasks: (a) arithmetic computations during 30 min of each 2 hr period, 15 min in combination with the watchkeeping tasks only, and 15 min with the group-performance procedural task of code-lock solving as well, (b) code-lock solving during half of each 2-hr period, 15 min with arithmetic computations and watchkeeping, 30 min with watchkeeping alone, and 15 min with watchkeeping and target identification, and (¢) target identification during 30 min, half as indicated (with watch- keeping and code-lock solving) and half with the watchkeeping tasks only. Thus, relative demands on performance are low, intermediate, or high, depending on whether the watchkeeping tasks are presented alone, with only one of the active tasks, or with two (or more) of them. The 2-hr performance schedule typically used is presented in Table D-1. When subjects are required to work for 8 hr a day, this schedule is repeated four times during the day. However, from the subject's point of view, there is no break between repetitions of the program from the start to the end of a period of testing since the three watchkeeping tasks (warning-lights, blinking-lights, and probabi- lity monitoring) are presented continuously at each work station. INITIAL RESEARCH PROGRAM The development of the synthetic-work technique and research use of the MTPB began in 1956 when the Aerospace Medical Research Laboratories, Wright-Patterson Air Force Base, Ohio, began a program of research on crew performance; much of the research was conducted under contract 167 (D-7) Table D-1 Basic 2-Hour Task-Performance Schedule 15-Minute Interval in Each 2-Hour Period Performance Task 1 > 3 7 T g = 3 Blinking-Lights Monitoring X X X X X X X X Warning-Lights Monitoring X X X X X X X X Probability Monitoring X X X X X X X X Arithmetic Computations X X Code-Lock Solving X X X X Target Identification X X Level of Demand Low Med. High Med. Med. High Med. Low at the Human Factors Research Laboratory of the Lockheed-Georgia Company, Marietta, Georgia. The plan was to conduct research on crew performance applicable to advanced systems of a general class, ''ten years in the future;' major emphasis was placed on operator performances of the functional aspects of mission-related tasks. A group of tasks was assembled, the performance panels, programming and scoring apparatus, experimenters' control consoles, and crew compartments were designed and constructed (see Adams, 1958), and an initial experiment was then conducted to answer certain technical questions concerning the tasks of the MTPB--questions such as those related to task reliability and intertask correlations (see Adams, et al., 1959). Among the variables investigated in later studies were the following: (a) the work-rest cycle (8 hr on-duty and 8-hr off, 6-hr on and 6 off, 4 on and 4 off, and 2 on and 2 off); (b) the work-rest ratio (1:1, 2:1, and 3:1) (e) the operator's work load; (d) the addition of group-performance tasks; (e) the total duration of the period of confinement in the crew compartment (4 hr, 4 days, and 12, 15, and 30 days): (f) the effects of 2 days of sleep loss on performance under two demanding work-rest schedules (4-2 and 4-4); (g) the elementary relations between the performance measures obtained and two biomedical measures (temperature and pulse rate); and (4) samples of subjects who represented different populations (college students, including ROTC and Air Force Academy cadets, operational B-52 crews, and Air Force Officers newly graduated from pilot training schools). The results of these studies have been reported in a series of Air Force technical reports (Adams § Chiles, 1960, 1961; Alluisi, et al., 1962, 1963, 1964. 168 (D-8) The conclusions reached on the basis of this decade of research on sustained performance, work-rest scheduling, and circadian rhythms in man, may be summarized as follows: (a) Man can probably follow a 4-4 work-rest schedule for very long periods without detriment to his performance. (b) For shorter periods of 2, or possibly 4 weeks a more demanding 4-2 work-rest schedule can be followed by selected men with reasonable maintenance of performance efficiency. (ec) In following the more demanding schedule, man uses up his performance reserves, and so is less able to meet the demands of emergency conditions such as those imposed by sleep loss. (d) The circadian rhythm that is evidenced in physiological measures may also be evidenced in the performance measures, depending on the information given to, and the motivation of, the subjects and depending also on the total work load; even where motivation is sufficiently high, the cycling may be demonstrated in the performances of overloaded operators. Finally, (e) the MIPB and methodology employed in the synthetic-work approach have yielded measures that are sensitive to the manipulation of both obvious and subtle experimental variables; continued use and refinement of both should lead to further advances in the general area of performance- assessment research (cf. Alluisi, 1969; Alluisi § Chiles, 1967; Chiles, et al., 1968; Morgan & Alluisi, 1972). RECENT RESEARCH FINDINGS A more recent series of investigations of sustained performance has been directed toward the assessment of the Behavioral Effects of Infectious Diseases (BEID). This research program consisted of two Control studies conducted at the Performance Research Laboratory of the University of Louisville, and six illness-related studies conducted at the U.S. Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, Maryland. Several of these studies have been summarized elsewhere (Alluisi, 1969) . In its entirety, the BEID research program consisted of the fol- lowing studies: (a) BEID-1 was a control study that provided comparison data for the remainder of the experiments. The BEID-1 subjects were uninfected, and they performed at levels essentially identical to those of subjects in previous MIPB experiments as well as the hospital-control subjects of subsequent BEID studies (Alluisi, Thurmond, §& Coates, 1971). (b) BEID-2 and BEID-3 were investigations of the effects of illness with Pasteurella tularensis (commonly termed "tularemia" or Rabbit fever) on sustained performance (Alluisi, et al., 1971; Thurmond, Alluisi, § Coates, 1971). (ec) BEID-4 and BEID-5 were investigations of the effects of illness with Phlebotomus fever (commonly called "Sandfly fever") on sustained performance and BEID-6 investigated the effects of Phlebotomus fever on both sustained performance and muscular output (Coates, Thurmond, Morgan, & Alluisi, 1972; Morgan, Coates, § Alluisi, 1973). (d) BEID-7 was an investigation of the effects of symptomatic treatment on the performance of subjects infected with Phlebotomus fever. (e) BEID-8, the latest study in the series, was designed to 169 (D-9) provide additional control data for BEID-7. It investigated the effects of treatment (identical to that given in BEID-7) on the performance of 10 uninfected subjects. The results of BEID-7 and BEID-8 have not yet been published. The two diseases involved in these studies are quite similar in terms of symptomatology, except for intensity, but they do differ in terms of etiology: Tularemia results from a bacterial infection, whereas the infectious agent in Sandfly fever is viral. Both infections produce fever, frontal and retro-orbital headache, photophobia, generalized malaise, arthralgia, and leukopenia. The conclusions reached from the findings of the BEID program may be summarized as follows: (a) In general, the average efficiency of performance on the MTPB dropped between 25 and 33% during the period of illness with tularemia. The average drop in performance efficiency was between 6 and 8% per 1°F rise in rectal temperature. (b) The results of studies involving the less-severe illness, Sandfly fever, indicate that average crew performance dropped between 18 and 25% during the period of illness with this disease. The average drop in performance in these studies ranged from 3 to 6% per 1°F rise in rectal temperature. (ec) With both diseases, the individual reactions to illness produced substantial individual differences in terms of performance decrements; subjects who were equally and fully ill (as judged clinically and measured biomedically) yielded performance decrements that ranged from essentially no decrement to one of 17 to 20% per degree rise in temperature. Current studies of these individual differences and their psychophysiological and biomedical correlates, as well as their personality, social, and subjective correlates, are continuing, but to date have produced no clearer understanding of their causes. (d) Symptomatic chemotherapy with aspirin and Darvon during illness with Phlebotomus fever appears to eliminate the otherwise expected perfor- mance decrements during the period of infection. (e) Aspirin and Darvon chemotherapy does not affect the performance of manual (non- infected) subjects, The results of the BEID research illustrate how the synthetic-work technique can be employed to assess the behavioral effects of a given stress, and then to evaluate various methods of enhancing performance that is impaired by that stress. These are currently being pursued in several lines of research which will not be reviewed here. Specifically, the synthetic-work technique has been employed in investigations of the (Morgan, Brown, & Alluisi, 1970) and noise (Repko, 1972). It is currently being employed to determine man's ability to recover from the effects of continuous work and sleep loss, and the interactive effects of the circadian rhythm (and other factors) on this capability, Continued use of this approach in the future will be designed to pro- and the changes in those capabilities which result from his exposure to various physical, chemical, temporal, and organismic stresses. 170 (D-10) APPENDIX E SUMMARY OF LABORATORY PROCEDURES EMPLOYED IN THE CLINICAL ANALYSES Prepared by John A. Nicholson, Ph.D. URINE COPROPORPHYRIN Determination of urine coproporphyrin levels was by the method of Schwartz et al. (1951). To a 5 ml pipetted sample of urine, collected in a container containing sufficient sodium carbonate to produce a urine pH of 6.5 - 8.5, was added 5 ml buffered acetic acid (4 vol glacial acetic acid to 1 vol of saturated aqueous sodium acetate), 75 ml ethyl acetate, and 20 ml distilled water. After vigorous shaking for 30 sec, the aqueous phase was discarded. The ethyl acetate was then washed twice with 20 ml portions of 1% aqueous sodium acetate, and once with 20 ml of freshly prepared 0.005% aqueous iodine. Urinary coproporphyrin was then extracted from the ethyl acetate by 4 extractions with 4 ml 1.5 N HCl. Coproporphyrin concentrations were determined on a Turner fluorometer using a Narrow pass excitation filter which peaked at 405 mu, coupled with a Corning UV filter (#5970). The emission used was a sharp cut filter, passing wavelengths longer than 595 mu. A stock solution of coproporphyrin was prepared by accurately weighing (micro balance) a sample of the tetramethyl ester of copropor- phyrin III (Calbiochem) which previously had been placed under vacuum in the presence of Pp0g for 2 days. To 5 ml aliquotes of urine containing a low level of coproporphyrin was added known amounts of coproporphyrin and the spiked samples extracted as described above. A standard curve was constructed from which the unknown concentrations were determined. Unknowns reading more than 90mg% were diluted with 1.5 N HC1 in order that they might be evaluated on the lower, more linear portion of the standard curve. The acidic coproporphyrin solutions were sealed in individual containers and stored in the dark under refrigeration. Periodic determination of these standards have shown them to be quite stable, thus indicating good instrumental stability over the same time interval. For this reason, coproporphyrin standards were not prepared during each series of unknown analyses, although the refrigerated standards were reanalyzed immediately prior to the analysis of each unknown series of samples. 171 ( E-D URINE LEAD Urine lead determinations were performed by the method of Yeager et al. (1971). Urine specimens were collected in polypropylene containers which had previously been washed, rinsed with distilled water, washed with 1:1 nitric acid, rinsed several times with glass distilled/deionized water and air dried. All glassware used in this procedure was also first de-leaded as described under the '"blood-lead" procedure. Fifty ml urine, measured in a 50 ml graduated cylinder, was poured into a 125 ml separatory funnel, To this was added the following: I. 2 drops 0.1% phenol red 2, 10 ml 2 M ammonium citrate buffer (pH 8,5) 3. Ammonium hydroxide (dropwise, with shaking) until red color appeared, 4. 1 ml 10% NaCN 5. 1.0 ml freshly prepared 2% ammonium pyrrolidine dithiocarbamate (K&K) 6. 5.0 ml methyl isobutyl ketone (MIBK) After shaking vigorously for 30 sec., the aqueous phase was discarded and the remaining emulsion collected in a polypropylene tube which was capped and centrifuged for 5 min at 2000 rpm. The MIBK phase was then analyzed for lead by atomic absorption. Aqueous solutions containing 100 and 250mg/L of lead were also analyzed by the above method during each series of unknown analyses, analyzed before, during, and upon completion of the analysis of the unknown samples, URINE ALA Urine ALA levels were determined by the method of Davis and Andelman (1967). Disposable ion-exchange chromatographic columns, prepared for urine ALA determinations, were purchased from Bio Rad Laboratories, Richmond, California, The procedure we used consisted of that recommended by Bio Rad, which was only slightly modified from that developed by Davis and Andelman, 172 (E-2) Urine samples, collected in a container containing sufficient glacial acetic acid to produce a pH of 1-3, were stored under refrigera- tion prior to ALA analysis. Aqueous ALA standards were prepared each time a series of samples was analyzed, and the resulting standard curve used to determine the ALA concentrations of the unknowns, BLOOD LEAD Analysis of blood lead was performed according to the method of Hessel (1968). To eliminate possible lead contamination, all glassware was washed with soap and rinsed with distilled water. This was followed by overnight soaking in 1:1 nitric acid, rinsing 6 times with glass distilled/deionized water and drying in an oven. Polypropylene test tubes and caps were washed twice with soap, after which they were handled in a manner similar to that for the glassware. Blood samples were collected in a 10 ml heparinized, lead-free Vacutainer, After thorough mixing on a Vortex mixer, 5 ml of the sample was pipetted into a polypropylene test-tube (109 x 16 mm), To this was added 1 ml freshly prepared 2% aqueous ammonium pyrrolidine dithiocarbamate (APDC), 1 ml 5% aqueous Triton X, and 5 ml methyl isobutyl ketone (MIBK), with mixing between each addition. Aqueous lead standards were prepared by adding 100 ul of 70 and 40mg/ml lead standard to 5 ml glass distilled/ deionized water, thus obtaining final concentrations of 137 and 78.4mg% respectively. To these solutions were also added the other reagents referred to above. After capping the standards and unknowns, they were vigorously shaken for 1 min (manual). This was followed by centri- fugation for 5 min at 5000 rpm. The samples were analyzed by atomic absorption at the 2170 A lead line on an Instrumentation Laboratory Model 253 Atomic Absorption Emission Spectrophotometer with background correction. The instrument was initially calibrated using the 137mg% lead standard, followed by the 78.4mg% standard. Results from both standards and unknowns were obtained from a 10 second electronic integration of the signal pro- duced by each sample as it was aspirated into the flame. Only after instrumental stabilization had occurred to the extent that reproducible results (+ 2%) could be obtained from repetitive analyses of the stan- dards, were the unknowns analyzed for lead. The standards were also analyzed after approximately 10 unknown analyses; if any significant instrumental deviation had occurred subsequent to the previous analyses of the standards, the instrument was recalibrated and the appropriate unknowns reanalyzed for lead content. 173 (E-3 BLOOD ALA-D Blood ALA-D determinations were made as described by Bosignore et al. (1965) and as modified by Weissberg et al. (1971). Blood samples were collected in heparinized polypropylene test tubes (previously shown to be lead free), and were immediately frozen. Upon arrival at the laboratory, the samples were allowed to thaw, thoroughly mixed, and the ALA-D determinations performed. To a 10 ml lead-free Vacutainer, with the stopper removed, was added 0.5 ml blood, 5.0 ml glass distilled/deionized water, and 1.0 ml 1/15 M phosphate buffer (pH 6.8). After thorough mixing, the tube was restoppered under a nitrogen atmosphere. A 1.0 ml solution of 0.05 M ALA was then added from a plastic disposable syringe. The small amount of pressure developed by the addition of the ALA solution was relieved from the system by piercing the stopper with a syringe needle. The mixture was then incubated at 37°C for 1 hr with continuous agitation, after which the stopper was removed and the reaction quenched by adding 2.0 ml TCA-Hg solution (80 ml of 5% TCA plus 20 ml of 0.1 M HgClp). After thorough mixing the contents were centrifuged for 5 min at 4000 rpm, To 3.0 ml of the clear supernatant was added 3.0 ml of freshly prepared Ehrlich's reagent. After 3 min the optical density (ODgp) was determined at 553 mu on a Spectronic 20 Colorimeter, using an appropriately prepared blank. ALA-D activity was calculated as described by Weissberg (6): Units ALA-D = ODgp x 100 x 35,185 Hematocrit BLOOD HEMATOCRIT Blood hematocrits were routinely determined in duplicate using standard laboratory equipment (heparinized tubes, centrifuge, and reader). The average value of the duplicate analysis was reported for each unknown, 174 (E-4) APPENDIX F INDUSTRIAL AND PERSONAL HYGIENE PRACTICES Prepared By John D. Repko and Ben B. Morgan, Jr. Potential health hazards from industrial exposures to lead are created by the use of over one million tons of this metal each year. In a recent survey, the National Institute for Occupational Safety and Health recorded that workers in at least 110 occupations are exposed to lead during the conduct of their jobs (Jacobsen § Seiter, 1972). Recog- nizing these potential health problems, employers utilize various industrial- hygiene and engineering practices in order to protect employees from developing acute or chronic plumbism. In this regard, the purposes of this Appendix are to (a) provide data concerning the industrial hygiene practices of the three storage battery manufacturing companies which were involved in this study, and (b) relate these practices to the individual worker's personal hygiene history. INDUSTRIAL PRACTICES Information concerning the companies' hygiene practices was com- piled from responses to the Plant Questionnaire (see Appendix H, p. H-17 through H-19), and data concerning the workers' hygiene practices ‘were obtained from the Employee Questionnaire (see Appendix H, p. H-2 through H-4; relevant questions are numbers 9, 17, 18, 19, and 20). A summary of the responses to those items on the Plant Que tionnaire which deal with safety and health practices is presented in Table -1; only responses to those questions which were subject to numerical a vaso are included in this table. Also provided in the table is an indication of the percentage of workers in the experimental group who were affec -' hy a negative response to each question. It must be pointed out that the data of Table F-1 summarize the industrial hygiene practices in only three companies, that this represents a very small percentage of all storage-battery manufacturing companies (and a much smaller percentage of all lead-using companies in all industries), and therefore, that these findings must be generalized with extreme caution. Nevertheless, it is important to examine these data because of their relationship to the findings reported in the body of this report and because they do relate to the safety and health of approximately 300 workers exposed to inorganic lead at their worksite. It can be seen from these data that the companies involved in the study do provide general monitoring programs; however, companies differ with respect to the specific procedures followed. Specifically, all companies surveyed employ an industrial physician, all require medical examinations, all provide protective equipment, and all provide PbB or PbU examinations for their employees. Despite these commonalities, there are differences among the companies in the protocol involved in health monitoring. For example, two of the three companies require 175 (F-1) Table F-1 Summary of Responses to the Plant Questionnaire from Three Plants Utilizing Inorganic Lead Frequency of Response Percentage of Workers Question Area Yes No in Experimental Group Affected by Negative Response Does the company employ an 3 0 0.00 industrial physician? Does the company require medical 2 0 0.00 examinations for employees? a) Before employment. 2 1 39.87 b) Periodically during 1 2 60.13 employment. Does the company provide PbB 3 0 0.00 and/or urine examinations for employees? a) Workers are required to 1 2 74.68 transfer to another job or area of plant when PbB is greater than or equal to 80ug%. Does the company have a viable 2 1 39.87 program concerned with the reduction of air lead levels? Are lead levels in all work areas 2 1 39.85 measured periodically during the year? Does the company provide 3 0 0.00 protective equipment for employees in regular jobs? a) Respirators are available 3 0 0.00 at all times. b) Wearing of respirators is 2 1 34.81 enforced. : 176 (F-2) medical examination before employment, but only one requires medical exams periodically during employment. Therefore, only about 50%, of our sample of workers, received regular medical examinations during the course of employment. In order to have a medical monitoring program sensitive to the subtle and aggregate sequel of lead poisoning symptoms, medical monitoring must be extended to include all workers exposed to lead at their jobs. The common practice in the storage battery industry is to provide monthly clinical (PbB or PbU) tests to individuals in high-exposure areas and to provide semi-annual or quarterly tests to all other individuals in the plant. All of the companies visited require PbB or PbU examinations for all employees. The companies differ, however, with respect to frequency of such tests and the utilization of the data obtained from the tests. In some companies, specific data from tests are not always made available to the individual worker. It seems that management does not consider the individual worker to be capable of interpreting his own data. An individual may obtain his PbB (or other clinical data) only through his personal, family or company physician, and then only by request; individual data are not regularly sent to the individual or his personal physician, Clinical data are used by the industry to provide an index of the extent of exposure for a given individual. However, the precise nature of data utilization schemes is not standardized within the industry. Specifically, in two of three plants (representing approximately 75 per cent of the experimental group), workers are not required to transfer to another job or plant location when their respective PbB level is greater than or equal to 80ug%. The authors did note, however, that transfer usually occurred under certain other conditions; namely, when (a) PbB levels exceeded 90ug%, (b) the company or personal physician observed a sufficient number of medical symptoms to suggest that the worker was probably being deterimentally affected by lead, and (ec) the rate of increase in PbB was overly excessive. While these criteria might be used so as to protect the workers' safety and health, it was found that they were vaguely formulated, not formally standardized, and not universally followed. For example, the authors noted that individuals who possess a critical skill or who cannot be replaced in their specific job are allowed to continue under the same exposure conditions. Not infrequently the worker is told that his PbB is "high" or "excessive' and that he may transfer from his current job if he so desires. In such a case, the burden of decision is on the worker who generally lacks the requisite information to make a valid decision. Many times the worker will decide to remain in his present job rather than transfer because he feels that he will lose pay or, more importantly, lose his job entirely. Moreover, in situations where workers are transferred because of high PbB levels, it is the practice for such individuals to remain in a lower exposure job for a period of only about eight weeks. In many cases this period of time would not be sufficient for the PbB to recover to within normal ranges, even though it might be sufficient for an individual's PbB to drop below 80ug% (or whatever the particular criteria may be). The unfortunate problem with this procedure is that, upon returning to his regular job, the worker's PbB level also returns to excessive levels. 177 (F-3) It would appear that this chronic reabsorption of lead could be avoided by retaining the worker at lower airborne concentrations until PbB levels return to within normal limits. As discussed below, data of this study tend to document the fact that workers are not continually monitored or transferred automatically, even though PbB levels exceed 80ug%. In two of the plants where confirmatory PbB determinations were performed, the average PbB decreased insignificantly (¢ = 0.75, p > .10, df = 23; see Table 5, p. 21 of report) from the initial to the confirmatory tests, which were separated by as many as 88 days on the average. Table F-2 presents the PbB data, the dates of testing, the change in PbB, and the elapsed time between samples for the 25 workers who provided confirmatory samples. The inference from these data is that, for the average worker represented here, the exposure conditions did not change over the period of time between samples. Although the authors were not permitted access to company records concerning transfers and results of company-conducted PbB determinations, information compiled from other sources (conversations with workers) indicates that over 80% of these workers had continued in their current jobs between testing dates. It should be noted that the Employee Questionnaire asked for information concerning job titles (question 8) and the location of each worker's job within the plant (question 16). Although the authors attempted to identify specific jobs and examine them in terms of exposure conditions and PbB level, this proved to be an impossible task because of problems involved in interpreting obtained responses concerning job titles and locations and in obtaining from the companies data concerning each worker's job classification, plant location, and air-exposure levels. Although each of the companies reported that they monitored the levels of airborne lead at regular intervals, only two of the three plants employed what the authors consider to be viable airborne-lead reduction programs, and only two plants periodically measured airborne- lead levels in all work areas. In addition, although each of the three companies made respirators available to workers as an added safety measure aimed at reducing air-lead intake, only two of the companies required their workers to wear respirators. Only one of the companies required the wearing of respirators as a condition of employment; that is, continued employment was contingent upon adherence to the company's established procedures involving the use of respirators. No other company specifically enforced similar employment-contingency rules. PERSONAL PRACTICES The personal hygiene data from the Employee Questionnaire are tabulated in Tables F-3 through F-5. In analyzing these data, a non- parametric statistical test (Chi Square) was employed in order to obviate the need for certain assumptions concerning the forms of the sampling distributions of the data. The data presented in Table F-3 summarizes the results of the x? analyses for both PbB and ALA-D levels (four groups) as a function of each of the response categories dealing with the use of shower and respirators and with the incidence of worker accidents. The actual distributions of responses in the several response categories are given in Tables F-4 and F-5. 178 (F-4) Table F-2 Data of the Initial and Confirmatory Blood-Lead Determinations (N = 25) SUBJECT Initial Sample Confirmatory Sample PbB Elapsed CODE Date PbB Date PbB Change Time (Dys) 001 11/8/72 83 4/10/73 85 -8 154 401 11/9/72 82 4/9/73 62 -20 152 411 11/10/72 86 4/9/73 73 -13 151 811 11/10/72 80 4/9/73 59 -21 15] 421 11/10/72 81 4/9/73 81 0 151 471 11/14/72 91 4/9/73 86 -5 147 971 11/15/72 90 4/9/73 81 -9 146 681 11/15/72 93 4/9/73 63 -30 146 002 11/16/72 81 4/9/73 70 -11 145 102 7/26/73 243 9/21/73 251 +8 57 202 7/26/73 87 8/21/73 84 -3 57 702 7/26/73 95 9/20/73 96 +1 56 902 7/26/73 101 9/20/73 11 +10 56 012 7/26/73 85 9/20/73 23 +8 56 212 7/26/73 81 9/20/73 89 +8 56 312 7/26/73 101 9/21/73 106 +5 57 412 7/26/73 99 9/20/73 98 -1 56 512 7/26/73 99 8/21/73 106 +7 57 912 7/27/73 98 9/20/73 115 +17 55 222 7/27/73 86 9/21/73 98 +12 56 142 7/30/73 83 9/20/73 83 +10 52 842 7/31/73 125 9/18/73 100 -25 49 942 7/31/73 80 8/21/73 03 +13 52 852 8/1/73 89 9/31/73 105 +16 52 123 8/9/73 82 9/21/73 62 -20 43 MEAN TOTALS 96.44 94.40 -2.04 88.36 179 (E-5) Table F-3 Summary of x? Analyses for Three Personal Hygiene Questions as a Function of both PbB and ALA-D x2 Values QUESTION PbB ALA-D dar Shower 20.97* 7.38 3 Respirator 37.35% 5.08 6 Accident 0.11 3.45 3 * p < .001 It can be seen from the results of the analyses presented in Table F-3 that the distribution of '"Yes' and 'No'" responses to the question of whether the workers took showers was significant (p < .001) when workers were grouped according to PbB level. From the data in Table F-4, it can be seen that a relatively large percentage of responses occurred in the 40-80ug% group and that this distribution was in proportion to the totals in the response category. However, with respect to the percentages in the 80-120ug% group, a considerably higher percentage of workers responded that they did take showers (13.8%) as opposed to those who did not (3.6%). It is clear that these data do not support the contention that workers who do not take showers have higher blood-lead levels. In fact, although 18.4% of the total sample had PbB levels above 80pg%, and only 3.9% did not take showers. In terms of the responses as a function of ALA-D levels, there were no significant differences in the response distributions. From the data in Table F-5 it is quite clear that the percentage of responses across ALA-D groups was fairly evenly distributed. In comparing the distributions of response for both PbB and ALA-D, a clear difference in body burden emerges. Specifically, with respect to those workers who do not take showers, only 3.9% of the workers fall in the high PbB groups, whereas 19.1% fall in the two poorest ALA-D groups. The inference to be drawn from these data is that irrespective of PbB or ALA-D, showering does not seem to have an effect on body burden of lead. The distributions of the percentages of workers wearing respirators are given both as a function of PbB and of ALA-D (Tables F-4 and F-5). The pattern of responses to this item are similar to those obtained 180 (F-6) Table F-4 Summary of Percentages of Workers at each PbB Level for Three Personal Hygiene Questions PbB Level QUESTION RESPONSE TOTAL CATEGORY <40ug% 40-80pgh 80-120ug% >120ug% Shower YES 2.9 37.5 13.8 0.6 54.9 (N = 304) NO 6.9 34.2 3.6 0.3 45.1 TOTAL 9.9 73.7 17.4 1.0 100.0 Respirator <25% 8.9 53.3 7:9 0.3 70.5 (N = 302) 25-70% 0.0 8.3 6.6 0.7 15.6 >75% 1.0 10.3 2.6 0.0 13.9 TOTAL 9.9 71.9 17.2 1.0 100.0 Accident YES 3.3 21.9 5.5 0.3 31.0 (N = 306) NO 6.5 49.7 12.1 0.7 69.0 TOTAL 9.8 71.6 17.6 1.0 100.0 with the former question. Specifically, in terms of PbB levels, the distribution of responses was significantly different from the expected distribution (p < .001). The majority of workers (71.9%) fall between 40 and 80ug% of PbB and the greatest proportion of respondents (70.5) wear respirators less than 25% of the time. Moreover, in the two PbB groups greater than 80ug%, less than 3% of the total sample wore respirators greater than 75% of the time, while more than 15% of the workers in the sample wore respirators for lesser periods of time. This, along with the fact that 53.3% of the sample wore respirators less than 25% of the time and still had PbB levels below 80ug%, suggests that PbB levels are independent of the wearing of respirators. In terms of ALA-D levels, the distribution of responses is fairly evenly distributed. In cases where respirators are worn more than 75% of the time the propor- tion of workers in each ALA-D group does not differ significantly from the proportions in the two remaining response categories. These data suggest that although respirators may assist in lowering the intake of lead, they do not seem to have a significant effect on the body burden of lead; most workers possessed low PbB levels without wearing respirators. This is not to say that not wearing respirators reduces PbB. Rather, it suggests only that PbB levels are low even though respirators are not worn. Had this group worn respirators more, their PbB levels might have been even lower. 181 (F-7) Table F-5 Summary of Percentages of Workers at each ALA-D Level for Three Personal Hygiene Questions ALA-D Level QUESTION RESPONSE TOTAL CATEGORY >26 26-19 19-11 <11 Shower YES 15.8 12.5 11.2 15.5 54.9 (N = 304) NO 17.1 8.9 11.5 7.6 45.1 TOTAL 32.9 21.4 22.7 23.0 100.0 Respirator <25% 22.5 14.9 17.2 15.9 70.5 (N = 302) 25-75% 4.3 3.0 3.3 5.0 15.6 >75% 5.7 3.6 2:3 2.3 13.9 TOTAL 32.5 21.5 22.8 23.2 100.0 Accident YES 9.8 5.2 3.58 7.2 31.0 (N = 306) NO 23.2 16.0 13.7 16.0 69.0 TOTAL 33.0 21.2 22.5 23.2 100.0 Of the exposed workers in this study, 31% (see Tables F-4 and F-5) were involved in occupationally related accidents. Of this group, accidents occurred about equally across the four ALA-D groups. When grouped according to PbB the greatest proportion of accidents occurred in PbB groups greater than 40ug%. The data suggest that the occurrence of accidents may be independent of either PbB or ALA-D. This is not to say, however, that a total independence from body- burden was occurring; it may be that any body burden of lead, irrespec- tive of amount or clinical measure which is employed may contribute to the incidence of accidents. Moreover, accidents may also result from abnormal psychological states such as heightened anxiety, depression, or hostility, all of which were evidenced in this study (see Figure 31). Although data concerning the causes of accidents and the nature and extent of specific accidents are not available (due, in part, to lack of access to company records), it is quite clear that approximately one-third of this sample of lead-exposed workers were involved in occupationally related accidents during the course of their employment. CONCLUSIONS AND RECOMMENDATIONS From the data provided by the Plant and Employee Questionnaires and the observations noted by the authors during the conduct of their study, two general conclusions can be made; specifically, (1) industrial 182 (F-8) hygiene practices directed toward the improvement of worker safety and health are not formally standardized either between or within companies, and (2) the fact that the current data are equivocal with respect to whether showering and the use of respirators add a margin of safety, points up the importance of supplementing these practices with other standardized, monitoring procedures. Based on these two general conclusions, the current practices in the storage-battery manufacturing industry, and the assumption that formal, standardized industrial and personal hygiene practices are necessary and desired on the part of management in the storage-battery industry and the workers exposed to inorganic lead, the following recommendations are offered: 1. Each exposed worker should receive a full medical examination annually or semi-annually. 2. Each exposed worker should have monthly PbB and ALA-D determinations. 3. Prior to employment, each worker should have a full medical examination, PbB, and ALA-D tests. These latter clinical tests should then be used as a baseline or normal data for a given worker. 4. Workers should use respirators 100% of the time when airborne lead levels are excessive. 5. All workers should shower (and change clothes) before departure from work. 6. Continued employment should be contingent upon each worker's adherence to the proper use of respirators and post-shift showers. 7. Workers should automatically be transferred from their current exposure levels when PbB and ALA-D levels exceed criterion levels (see p. 64 for PbB and ALA-D standards). Such job transfers should involve no loss of pay or job rights to the worker. 8. After transfer a worker should remain in the lower- exposure job until PbB and ALA-D indices return to pre-exposure (i.e., pre-employment) levels. 9. An extensive and ongoing education program should be conducted to inform workers of the importance and meaning of PbB, ALA-D, and associated medical signs of lead poisoning; further, each worker should be informed individually of his or her own clinical findings. 183 (F-9) APPENDIX G EVALUATION OF HEALTH STATUS OF WORKERS EXPOSED TO INORGANIC LEAD Prepared by John D. Repko and John M. Lyddan In addition to environmental monitoring of airborne lead and the biological monitoring of the worker's body burden of lead, the immediate health status of a particular worker is often assessed by medical monitoring. Medical monitoring consists of a direct assessment of the effect of inorganic lead by assessing certain medical signs or symptoms without laboratory analysis and examination. The observed effects of acute and chronic lead poisoning from long-term exposure are well known. Kehoe (1972) classifies the signs and symptoms of lead poisoning into three general categories; namely, alimentary type, neuromuscular type, and lead encephalography. Various medical symptoms associated with each of these categories are summarized in Table G-1 (see Appendix A for a detailed description of each of these symptoms). In order to assess the medical status of workers in this study who were exposed to inorganic lead, data concerning medical signs and symptoms were compiled from the Employee Questionnaire (see Appendix H, p. H-2 through H-13). In compiling and analyzing these data, a non-parametric statistical test (Chi Square) was employed in order to obviate the need for certain assumptions concerning the forms of the sampling distribution of the data. The data presented in Tables G-2 through G-10 summarize the results of the x? analyses (and the appropriate percentage distribution of responses) for both PbB and ALA-D as a function of responses to specific questions from the Employee Questionnaire. Only those questions subject to numerical tabulation were included in the analyses. However, for purposes of this Appendix, only those questionnaire items which bore a significant relationship to either PbB or ALA-D are reported. MEDICAL SYMPTOMS Data indicative of the immediate health status of the workers exposed to inorganic lead were provided by Questions 22 and 23. Spe- cifically, these questions asked whether the worker (a) had any illness in the past 30 days, and (b) had taken any medicine in the past 24 hours. The results of the x? analyses for these questions are summa- rized in Table G-2. It can be seen from these data that the distribution of responses to the question of illness was significant (p < .05) when workers were grouped according to PbB level. It is also clear from the data in Table G-3 that 84.5% of the workers exposed to inorganic lead had no illness within the past 30 days, and the majority of workers responding 'NO'" had PbB levels between 40 and 80ug%; of the remaining 15.5% who were sick, 13.8% of the total sample had PbB levels greater than 40ug%. When the workers were grouped according to ALA-D levels, no significant pattern of response emerges. It is important to note, however, that 45% of the respondents had ALA-D levels of less than 19 units of activity. 185 (G-1) in Table G-1 Medical Symptoms Observed Three Categories of Lead Poisoning Alimentary Neuromuscular Encephalopathic Abdominal pain Anemia Anorexia Constipation Digestive disorders Loss of appetite Nausea Pallor of skin Liver problems of muscles of reflex Lowered muscle tone Pain in muscles & joints Paralysis Peripheral Neuritis Weakness "Wrist Drop" Atrophy Latency Degeneration of neurons Headache Intellectual disorders Reduced nerve-conduction velocity Loss of orientation Table G-2 Summary of x2 Analyses for PbB and ALA-D Questions Concerning Illness and Medication as a Function of both x2 Values’ Variable PbB ALA-D Illness 10.76%* Z.17 Medication 4.32 10 .68%* lf = 3; *+p < .05 186 (G-2) Summary of Percentages of Workers at Each PbB Level for Illness and Medication Questions Table G-3 PbB Level QUESTION RESPONSE TOTAL CATEGORY <40ugk% 40-801ug% 80-120ug% >120pg% Illness YES 1.6 12.3 0. 0.6 15.5 NO 8.5 59.2 16. 0.3 84.5 TOTAL 10.1 71.5 17. 1.0 100.0 Medication YES 3.5 14.9 2. 8.3 21.5 NO 6.6 56.6 14. 0.6 78.5 TOTAL 10.1 71.5 17. 0.9 100.0 Table G-4 Summary of Percentages of Workers at Each ALA-D Level for Illness and Medication Questions ALA-D Level QUESTION RESPONSE TOTAL CATEGORY >26 26-19 19-11 <11 Illness YES 3.8 4.1 3. 4.4 15.5 NO 29.7 17.4 19. 18.0 84.5 TOTAL 33.5 21.5 22. 22.5 100.0 Medication YES 9.8 5.7 Se 2.5 21.5 NO 23.7 15.8 19. 19.9 78.5 TOTAL 33.5 21.5 22. 22.5 100.0 187 (G-3) Concerning the question of medication, 78.5% had no medication within the previous 24 hour period before performance testing. In terms of PbB levels, the distribution of responses was not significant; the distribution, however, was significant (p < .05) in terms of ALA-D groupings. It can be seen from the data in Table G-4 that signifi- cance was attained because 9.8% of those taking medication and 23.7% of those not taking medication had normal ALA-D levels (that is, >26 units of activity). In general, it appears that most of the people with high PbB levels had not been sick recently; nor, in the case of ALA-D, had they taken any medication. Although the great majority of medical symptoms provided in the Employee Questionnaire did not show a significant pattern of responses as a function of either PbB or ALA-D, several questions did show significant relationship with at least one of the clinical measures. Those symptoms which were identified by the analyses included consti- pation (Question No. 24.11; see Appendix H), loss of orientation (24.22), liver problems (24.28), low blood (anemia) (24.29), peeling of skin (24.34), white lines around finger or toe nails (24.35), and taking of iron pills (37). A summary of the x2 analyses for these seven symptoms as a func- tion of both PbB and ALA-D is given in Table G-5. Although the majority of workers (>68%) responded that they did not exhibit one or more of these symptoms, the major proportion of those responding "YES'" in all symptom categories had PbB levels greater than 40ug% (see Table G-6) or ALA-D levels less than 26 units of activity (see Table G-7). With respect to this study group, the symptoms identified are characteristic of symptoms which have previously been associated with varying body-burden levels (see Appendix A; Repko, et al., in preparation) and categories of lead poisoning (see Table G-1; Kehoe, 1972). From these data it is evident that only a limited number of symptoms of lead poisoning are typically exhibited by workers exposed to inorganic lead on a daily basis. Moreover, where such symptoms are exhibited they are usually seen in a very small number of workers, and these workers occasionally have PbB levels within the "Acceptable" range, as low as between 40 and 80ug%. HEALTH HABITS During the conduct of this study the authors observed through conversation with workers and industrial health personnel that the worker's individual smoking, drinking, and drug habits are considered in the diagnosis and monitoring of lead poisoning. Quite often industrial health personnel attribute the elevation in PbB (or what- ever clinical measure is employed) and the existence of medical symptoms to excesses of one or more of these individual habits. In contrast to this general practice, the data of this study support the contention that these habits do not contribute to an elevation in PbB or a reduction in ALA-D. The summary of x2 analyses given in 188 (G-4) Table G-5 Summary of x? Analyses for Seven Symptoms as a Function of both PbB and ALA-D x2 SYMPTOM 1 1 PbB ALA-D Constipation 13.20%% 0.21 Loss of Orientation 15.58*%* 12.41%%* Liver Problems 0.63 10.00% Low Blood (Anemia) 8.82% 3.41 Peeling of Skin 9.41% 2.53 White Lines on Nails 5.05 8.05* Taking of Iron 9.97% 3.35 Yap = 3; #p < 05; **p < .01 Table G-8 shows that there was no significant pattern of responses to questions of whether or not a person smokes cigarettes or cigars (Questions 44 and 45), drinks alcoholic beverages (Question 63), or is taking drugs (Question 68). It can be seen from the data in Tables G-9 and G-10 that this lack of a significant relationship between these habits and the clinical measures occurred because the percentages of persons responding "YES" or "NO" in each PbB and ALA-D category were in the same proportion as the distribution of responses in the total sample. It should be pointed out that of the total sample of exposed workers 41.8% currently smoke, 33.9% drink alcoholic beverages, and 7.3% admit to the use of drugs of any kind, including No-Doze, sleeping pills, and tranquilizers as well as more commonly thought of drugs such as LSD, amphetamines, and marijuana. 189 (G-5) Table G-6 Summary of Percentages of Workers at Each PbB Level for Seven Medical Symptoms PbB Level QUESTION RESPONSE TOTAL CATEGORY <40ug% 40-80ug% 80-120ug% >120ng% Constipation YES 0.0 8.9 2:5 0.6 12.0 NO 10.1 62.7 14.9 0.3 88.0 TOTAL 10.1 71.5 17.4 0.9 100.0 Loss of YES 0.0 1.9 0.0 0.3 22 Orientation NO 10.1 69.6 17.4 0.6 97.8 TOTAL 10.1 71.5 17.4 0.9 100.0 Liver YES 0.0 1:3 0.3 0.0 1.6 Problems NO 10.1 70.3 17:1 0.9 98.4 TOTAL 10.1 71.5 17.4 0.9 100.0 Low Blood YES 0.6 3.5 0.0 0.3 4.4 (Anemia) NO 9.5 68.0 17.4 0.6 95.6 TOTAL 10.1 71.5 17.4 0.9 100.0 Peeling of YES 2.2 8.5 2.5 0.6 13.9 Skin NO 7.9 63.0 14.9 0.3 86.1 TOTAL 10.1 71.5 17.4 0.9 100.0 White Lines YES 1.6 5.1 1.6 0.3 8.5 on Nails NO 8.5 66.5 15.8 0.6 91.5 TOTAL 10.1 71.5 17.4 0.9 100.0 Taking of YES 2.2 24.1 4.1 0.9 31.3 Iron NO 7.9 47.5 13.3 0.0 68.7 TOTAL 10.1 71.5 17.4 0.9 100.0 190 (G-6) Table G-7 Summary of Percentages of Workers at Each ALA-D Level for Seven Medical Symptoms ALA-D Level QUESTION RESPONSE TOTAL CATEGORY >26 26-19 19-11 <11 Constipation YES 3.8 2.8 2.5 2+5 12.0 NO 29.7 17.8 19.9 19.6 88.0 TOTAL 33.5 21.5 22.5 22.5 100.0 Loss of YES 0.0 1.6 0.6 0.0 2 wl Orientation NO 33.5 19.9 21.8 22.5 97.8 TOTAL 33.5 21.5 22.5 22.5 100.0 Liver YES 0.3 0.0 0.0 1.3 1.6 Problems NO 33.2 21.5 22.5 21.2 98.4 TOTAL 33.5 21.5 22.5 22.5 100.0 Low Blood YES 1.9 0.6 1.6 0.3 4.4 (Anemia) NO 31.6 20.9 20.9 22.2 95.6 TOTAL 33.5 21.5 22.5 22.5 100.0 Peeling of YES 4.1 3.8 2.2 3.8 13.9 Skin NO 29.4 17.7 20.3 18.7 86.1 TOTAL 33.5 21.5 22.5 22.5 100.0 White Lines YES 1.9 3.5 0.9 2.2 8.5 on Nails NO 31.6 18.0 21.5 20.3 91.5 TOTAL 33.5 21.5 22.5 22.5 100.0 Taking of YES 10.4 8.2 7.3 5.4 31.3 Iron NO 23.1 13.3 15.2 17.1 68.7 TOTAL 33.5 21.5 22.5 22.5 100.0 191 (G-7) Table G-8 Summary of x2 Analyses for Three Personal Habits as a Function of both PbB and ALA-D x2 values! HABIT PbB ALA-D Smoking 2.72 5.25 Drugs 4.33 1.91 Drinking 7.76 1.66 lop = 3 Table G-9 Summary of Percentages of Workers at Each PbB Level as a Function of Three Personal Habits PbB Level HABIT RESPONSE TOTAL CATEGORY <40ung% 40-80ug% 80-120ug% >120ug% Smoking YES 5.1 30.0 6.7 0.0 41.8 NO 5.4 42.4 9.4 1.0 58.2 TOTAL 10.4 72.4 16.2 1.0 100.0 Drugs YES 0.9 5.4 0.6 0.3 7.3 NO 9.2 66.1 16.8 0.6 92.7 TOTAL 10.1 71.5 17.4 0.9 100.0 Drinking YES 4.7 25.3 3.8 0.0 33.9 NO 5.4 46.2 13.6 0.9 66.1 TOTAL 10.1 71.5 17.4 0.9 100.0 192 (G-8) Table G-10 Summary of Percentages of Workers at Each ALA-D Level as a Function of Three Personal Habits ALA-D Level HABIT RESPONSE TOTAL CATEGORY >26 26-19 19-11 <11 Smoking YES 16.2 10.1 7.4 8.1 41.8 NO 17.8 11.1 15.2 14.1 58.2 TOTAL 34.0 21.2 22.6 22.2 100.0 Drugs YES 2.5 A 0.9 1.6 7.3 NO 31.0 19.3 21.5 20.9 92.7 TOTAL 33.5 21.5 22.5 22.5 100.0 Drinking YES 11.7 8.2 7.6 6.3 33.9 NO 21.8 13.3 14.9 16.1 66.1 TOTAL 33.5 21.5 22.5 22.5 100.0 CONCLUSIONS AND RECOMMENDATIONS It is clear from the medical data compiled from the Employee Questionnaire that medical monitoring alone is insufficient to insure adequate workers' health. Data provided earlier in this report show that over 33% (Table 3, p. 25; N = 106) of the total exposed sample have PbB levels exceeding 70ug% and this is the PbB level at which some behavioral dysfunctions are initially evidenced (Table 15, p. 62). On this basis alone it would be expected that a similar proportion of workers would exhibit some pattern of medical symptoms associated with lead poisoning. Such a proportion of workers showing medical symptoms was not evidenced in the present data. It is therefore recommended that the evaluation and diagnosis of lead poisoning in workers exposed to inorganic lead specifically include and emphasize quantitative biological and behavioral measures as well as the more qualitative and subjective medical signs and symptoms. Such a recommendation is consistent with other authors (Zavon, 1964; Johnston, 1964; N.A.S., 1972) who have recommended that several sources of information, for example, medical symptoms, laboratory data, and patient history, are necessary to adequately diagnose lead poisoning. 193 (G-9) APPENDIX H OFFICIAL FORMS Prepared by John M. Lyddan Each of the forms requesting information from the workers participating in this study is included in this appendix. The employee questionnaire (pp. H-2 to H-13) was completed by each subject volunteer on the day prior to his scheduled testing. At the time of testing, each worker was required to read and sign the consent form (pp. H-14 to H-15); this form describes the purpose of the study, confidentiality of information, extent of testing, release of test results, and employee protection. Also at the time of testing, each worker was asked to read and sign (if they so desired) the form providing for the release of Company Medical Records and the release of Study Results to a designated physician (p. H-16); each subject was also asked to read the Assurance of Confidentiality statement (p. H-16) given by the Director of NIOSH. Finally, at each plant location, background information on each company's health and safety pro- gram was obtained (pp. H-17 to H-19). 195 (H-1) Form Approved 0.M.B. No. 68-5-72-049 Approval Expires 31 August 1973 DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE PUBLIC HEALTH SERVICE National Institute for Occupational Safety and Health Cincinnati, Ohio 45202 INORGANIC LEAD BEHAVIORAL EVALUATION STUDY CONDUCTED BY: Performance Research Laboratory University of Louisville Plant Code: SPONSORED BY: National Institute for Employee Code: Occupational Safety and Health CONTRACT NO: HSM 99-72-123 Date: EMPLOYEE QUESTIONNAIRE (To be completed by subject volunteer) Name (please print): (Last) (First) (Middle) Your Mailing Address: (Street) (City) (Zip) Your Personal Physician: (Last) (First) His Mailing Address (if known): (Street) (City) (Zip) Age: (years) 3. Height: (inches) Weight: (pounds) 5. Sex: M F Circle highest grade completed: 12345678 1234 1234 Pre-high school High School College Name of plant where you work: Job title: How long have you worked for this company: (years) NIOSH No. 16 (Cin.) 12-10-72 196 (H-2) Employee Code: eet 10. How long have you worked in your present job? (years) 11. For what other companies have you worked during the last 10 years? How long Name of Company Job Title (years) Years Worked From: 1) To: From: 2) To: From: 3) To: 12. Did you work with any of the following chemicals in the companies you listed under question 117 No YE8 Name of Company a) Metallic mercury { ) Cc ) b) Methyl mercury ( ) C ) ¢) Carbon disulfide ( ) C ) d) Methyl chloride C C ) e) Manganese (a C ) f) Arsenic () «C ) g) Thallium C) Cc ) h) Acrylamide «) Cc ) i) Trichloroethylane () Cc ) j) Methyl bromide C C ) k) Carbon monoxide C C ) 1) Others including solvents ( ) C or pesticides 13. Were any of the chemicals listed in question 12 used at all in the companies you worked for in the last 10 years? Chemical Name of Company a) b) c) 197 (H-3) Employee Code: NO YES 14. Did you work with lead or were you exposed to lead CH in the companies you listed under question 117? 15. Are you exposed to lead in your present job? Cc) (C ) 16. Describe the location within the plant of your present job 17. Do you shower at the plant when your shift is over? Cc) ) 18. About how much of your time on the job do you wear a respirator? (Circle closest answer) 0% 10% 25% 50% 75% 100% 19. Have you been involved in a work accident at this plant? ( ) ( ) a) If yes, when? (year) b) If yes, how many? c) If yes, causes: d) If yes, how many total days work did you lose? (days) 20. Have you been involved in a work accident at a previous ( ) ( ) employer's plant during the last 10 years? a) If yes, name of company b) If yes, how many c) If yes, causes d) If yes, extent and type of injuries e) If yes, how many total days of work did you lose? (days) 198 (H-4) Employee Code: 21. 22. 23, 24. Were you hospitalized in the last 2 years? If yes, a) cause of hospitalization b) date hospitalized c) how long in hospital d) have you completely recovered? Any illness in past 30 days? If yes, a) type of illness b) how long sick c) medicines taken, if known Did you take any medicine in past 24 hours? (including aspirin or other non-prescription medicines) a) b) Give name of medicine: Amount taken per day (days) Have you experienced any of the following within the last 6 months: 1) 2) 3) 4) 5) 6) 7) 8) 9) 10) Weight loss (exclude dieting)? Night sweating? Tire easily during the day? Lose temper easily? Noticeable change in your personality? Nightmares? Poor memory? Loss of consciousness? Trouble with arithmetic? Difficulty reading? 199 (H-5) NO ) ) ) ) ( ( ( ( YES Employee Code: 11) 12) 13) 14) 15) 16) 17) 18) 19) 20) 21) 22) 23) 24) 25) 26) 27) 28) 29) 30) 31) 32) 33) Constipation? Diarrhea? Difficulty finding the right words to express what you want to say? Feel depressed? Blush easily? Have trouble concentrating? Pain in lower back? Soreness in muscles and joints? Taste of metal in the mouth? Convulsions? Twitches in hands, arms or legs? Loss of orientation? Dizziness? Kidney problem? Legs or feet swell up? Dark brown urine? Yellow jaundice? Liver problem (hepatitis, cirrhosis)? Low blood (anemia)? Broken bone? If yes, which bone (where in body)? Arthritis? If yes, where in body? Notice your heart beating fast? Difficulty hearing what others say? 200 H-6) Employee Code: 25. 26. 27. 28. 29, 30. 31. 32. 33. 34, 35. 36. 34) Peeling of skin on palms of hands or soles of feet? If yes, how long? 35) White lines across the finger or toe nails? Have you ever had a tremor (shakiness) of: 1) hands? 2) lips? 3) face? 4) arms? 5) legs? 6) tongue? 7) whole body? Do you presently have any tremor? Which ones (list by above number)? Has your handwriting become shakier? Have you developed any difficulty in talking? Do you have any numbness of your tongue or lips? Do you have any numbness of your arms or legs? Do you feel unsteady when you walk? Have you ever had any disease of the nervous system (e.g., meningitis, neuritis, etc.)? Exclude nervousness. Do you get frequent headaches? Have you ever been treated for loss of consciousness? Have you ever been pale? 201 (H-7) NO — ( ) YES Employee Code: 37. 38. 39. 40, 41. 42, 43, a4, 45, 46, 47. 48, 49, Have you taken iron tonics or iron pills? Do you ever feel light-headed or dizzy? Do you wear glasses or contact lenses? Do you have frequent itching or watering of your eyes? Has your eyesight worsened recently? Do you think you have normal hearing? Have you ever smoked cigarettes, cigars, or a pipe regularly? Started smoking: (year) Quit smoking: (year) Circle how many cigarettes per day you smoked: a) less than 5 b) 1/2 pack c) 1 pack d) 1 1/2 packs e) 2 or more packs. Have you ever been allergic to anything? Item Type of Reaction 1) 2) 3) Do you sleep well? Have you noticed any weakness in your feet or hands? 202 (H-8) NO (J) ( CJ) ( CJ) CJ) ( CJ) { ¥ « CJ) CJ) ( CJ) ( Cc) Employee Code: 50. Does your health prevent you from doing anything you used to do? Activity Explain a) b) c) 51. Have you ever had any head injury? a) If yes, when? (year) b) Type of injury? c) If you have not completely recovered, what is still wrong with you? 52, Copy the following drawing in the bracket provided: i { \ : / | ‘ Lo. 53. Which hand did you use to copy the above drawing? (Circle Answer) Right Left 54. Which of the following reflects your attitude towards meals? 1) They are a necessary evil 2) They are nothing exciting 3) No particular feeling to them 4) Sort of enjoy them 5) Thoroughly enjoy them 55. Do you take vitamin supplements? 203 (H-9) ] Employee Code: 56. 57. 58. 59. 60. 61. 62, Is your appetite 1) Very good? 2) Good? 3) Average? 4) Poor? 5) Very poor? Are you on a special diet? Brief description: Weight Watchers Other Approximately how long does it take you to go to sleep at night? 1) 15 mins or less 2) 15-30 mins 3) 30-60 mins 4) Longer than an hour When do you feel you are most alert? 1) 1-5 am 2) 6-10 am 3) 11 am-3 pm 4) 4-8 pm 5) 9-12 pm How often do you wake up while sleeping? 1) Don't wake up until time to get up 2) 1-2 times 3) 3-4 times 4) More than 4 Do you know why you wake up during your sleep? If yes, why (for example, neighbor slams doors at 3 am every night)? How do you feel when you get up? 1) Completely rested 2) Somewhat rested 3) Tired 4) Very drowsy 204 H-10) ( ) YES Employee Code: 63. During a "typical" week, how much of the following do you drink? 1) Beer: a) None b) 1 or 2 glasses c) 3-6 glasses d) 7-12 glasses e) more than 12 glasses 2) Wine: a) None b) 1 or 2 glasses c) 3-6 glasses d) 7-12 glasses e) more than 12 glasses 3) Other alcoholic beverage: a) None b) 1 or 2 glasses c) 3-6 glasses d) 7-12 glasses e) more than 12 glasses 64. When do you normally drink your favorite alcoholic beverage? 1) Before work 2) After work 3) Weekends 4) With meals 5) Other (please indicate) 65. When was the last time you had an alcoholic beverage? 1) Within 6 hours 2) 6-12 hours 3) 12-24 hours 4) 1-5 days 5) More than 5 days 66. How long have you been drinking the amount indicated in question 637 1) Less than 1 month 2) 2-6 months 3) 7-12 months 4) 1-3 years 5) 4 or more years 205 {H-11) Employee Code: 67. Have you ever sampled or drunk moonshine (white lite'nin', etc.)? If yes, 1) how much? 2) when was the last time? 68. During the past 3 months, have you taken any of the following: (This will be held in strictest confidence; no "authorities'" will be notified) 1) Dexedrine? 2) Benzedrine (an amphetamine)? 3) "Speed"? 4) Marijuana? 5) LSD? 6) No Doze? 7) Sleeping pills (such as Compoze, Sleepeze, etc.)? 8) "Downers" (such as tuinal, redbirds, etc.)? ON INNA PNG ( 69. Please indicate how you feel about each of the following statements by checking the appropriate answer (check only one answer for each question): a) It is difficult to make suggestions or complaints to my supervisor (or foreman). Strongly agree Agree No opinion Disagree Strongly disagree b) I know pretty well how my supervisor feels about my work. Strongly agree Agree No opinion Disagree Strongly disagree ¢) I would recommend working here to a friend. Strongly agree Agree No opinion Disagree Strongly disagree 206 (H-12) NN PN PN NAN NON Nd Nd Employee Code: d) I would leave in a minute if I could get a similar job elsewhere. Strongly agree Agree No opinion Disagree Strongly disagree e) Sometimes I feel my job is of little importance here. Strongly agree Agree No opinion Disagree Strongly disagree f) Promotion possibilities are good in my department. Strongly agree Agree No opinion Disagree Strongly disagree g) Management is pretty good about listening to my complaints. Strongly agree Agree No opinion Disagree Strongly disagree h) My job is no more hazardous than jobs at other factories. Strongly agree Agree No opinion Disagree Strongly disagree 70. If there is anything we did not cover regarding your work, your health, and physical condition that you think is important, please comment below in your own words. Comment: (Signature of Employee) Date: 207 (H-13) DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE PUBLIC HEALTH SERVICE National Institute for Occupational Safety and Health Cincinnati, Ohio 45202 INORGANIC LEAD BEHAVIORAL EVALUATION STUDY EMPLOYEE CONSENT FORM CONDUCTED BY: Performance Research Laboratory Plant Code: University of Louisville SPONSORED BY: National Institute for Employee Code: Occupational Safety and Health CONTRACT NO: HSM 99-72-123 Date: CONSENT I hereby voluntarily agree to participate in the Inorganic Lead Behavioral Evaluation Study which is being conducted by the University of Louisville and sponsored by the National Institute for Occupational Safety and Health. The study has been discussed with me and I understand: A. Purpose of study and confidentiality of information: (1) This study is meant to evaluate the possible behavioral effects of long-term, low-level exposure to airborne lead, and (2) all information collected will be kept in strict confidence; B. Questionnaire and study tests: (1) A questionnaire must be answered, (2) the study tests are not hazardous to my health and pose a minimum of discomfort, (3) samples, such as blood, urine, hair will be be required for monitoring purposes and for special clinical tests, (4) tests will be given to measure attentive, sensory- perceptual, cognitive, psychomotor functions, and muscular strength and stability, and (5) a psychological test will be given to measure my present mood or subjective feelings; C. Medical records and release of test results: (1) My medical records will be required and separate written consent for release of records will be requested, and (2) I may request, by separate written consent (attached), a report of my test results or any significant behavioral findings from this study be sent to physicians of my choice; 208 (H-14) D. Employment protection and withdrawal from study: (1) My participation in this study or my tests results will not be used in any way to jeopardize my employment, and (2) I may withdraw from the study at any time. (Signature of Volunteer) Date: 209 (H-15) INORGANIC LEAD BEHAVIORAL EVALUATION STUDY Contract HSM 99-72-123 AUTHORIZATION FOR RELEASE OF INFORMATION Medical Records: I hereby authorize the Company to release to the University of Louisville such of my medical records on file in my Company Medical Record as are requested by the University. (Signature of Volunteer) Date: Lead Behavioral Study Results: I hereby request that the University of Louisville inform the following named physicians of my test results or of any significant behavioral findings from this lead study. (1) My personal physician: (2) Company physician: Dr. Dr. Street: Street: City: City: (3) Union physician: Dr. Street: City: (Signature of Volunteer) Date: ASSURANCE OF CONFIDENTIALITY The National Institute for Occupational Safety and Health hereby gives its assurance that your identity and your relationship to all information reported by you or derived from your participation in the Inorganic Lead Behavioral Study will be kept confidential in accordance with Public Health Service Regulations (42 CFR, Part I) and will not be disclosed without your written consent. Marcus M. Key, M.D. Assistant Surgeon General, PHS Director National Institute for Occupational Safety and Health 210 (H-16) DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE PUBLIC HEALTH SERVICE National Institute for Occupational Safety and Health Cincinnati, Ohio 45202 INORGANIC LEAD BEHAVIORAL EVALUATION STUDY CONDUCTED BY: Performance Research Laboratory Plant Code: University of Louisville SPONSORED BY: National Institute for Employee Code: Occupational Safety and Health CONTRACT NO: HSM 99-72-123 Date: PLANT QUESTIONNAIRE (To be completed by study interviewer) 1. Name of Plant: 2. What is chief product or service of this company ? 3. How many employees comprise the total work force at this plant? 4. Of this number how many are normally in the plant work areas as opposed to the office or outside areas? 5. Of those in the work area, what approximate percentage is male? NO YES 6. Does this company employ an industrial physician? CH) 1) At plant location? Cc) CC) 2) At corporate headquarters? Cc) CC ) 3) On a consulting basis? Cc) 4) Other (specify): 211 (H-17) 10. Does company require medical examinations for employees? 1) Before employee is hired? 2) Periodically during employment? 3) If yes, how often ? Does company provide protective equipment for employees in hazardous jobs? 1) Are respirators available at all times? 2) Is the wearing of respirators enforced? 3) What exhaust equipment is in use? Does company provide periodic lead blood and/or urine examination for employees? 1) If yes, at what body burden of lead is worker reassigned to another job? Blood: ug/g Urine: ug/liter Are any of the following materials used and/or found in the work area? 1) Carbon disulfide 2) Methyl chloride 3) Manganese 4) Arsenic 5) Thallium 6) Acrylamide 7) Lead (inorganic) 8) Lead (organic) 9) Trichloroethylene 10) Methyl bromide 11) Carbon monoxide 12) Methyl mercury 13) Metallic mercury 11. Identify other metals, solvents, or pesticides that may be found at the job-site which were not mentioned in above question: 1) 2) 3) 4) 5) 6) 212 (H-18) PS ONAN ATNATNTS ENN ATN NNN dd YY YY PS PN ANATN LNA ONTOS ed YY YY NY 12. 13. 14. 15. 16. 17. Does company have a program concerned with the Cc) ) reduction of air lead levels? Are lead levels in the work area measured Cc) () periodically during the year? Cc) C) 1) If yes, how often? Who dispenses the respirators to the employees? (circle appropriate answer([s]) 1) safety engineer 2) industrial hygienist 3) physician 4) nurse 5) other (specify): Does this company employ a safety engineer? Cc) () 1) At plant location? Cc) () 2) At corporate headquarters? Cc) () 3) On a consulting basis? Cc) () 4) Other (specify): Have any workers been reassigned to other jobs Cc) ) because of high body burden lead levels during the last 5 years? 1) If yes, how many? Who contributed information for completing this questionnaire? 1) 2) 3) 4) (Signature of Interviewer) Date: 213 (H-19) APPENDIX I SCHEDULES OF BEHAVIORAL TESTING Prepared by John M. Lyddan The agenda and schedules employed in "The Behavioral Effects of Occupational Exposure to Lead," conducted by the Performance Research Laboratory at the University of Louisville, are presented on the following pages. Included in tabular format are the dates for travel and the set-up and take-down of equipment at each location (Table I-1) and the specific daily schedules of testing at each location (Tables I-2 through I-6). The experimental personnel who aided in the collection of data included the following: The head of the research team was Dr. John D. Repko. He was assisted by Messrs. John M. Lyddan, Karl E. Rothrock, Donald L. Corson, Kenneth Hunt, and Mrs. Regina Hunt, R.N. In addition to his data collection duties, Mr. Karl E. Rothrock was on call for equipment emergencies throughout the study. Similarly, Mrs. Regina Hunt, R.N. was also in charge of the bleeding and supervised the collection of biomedical samples. The members of the research team rotated work assignments in order to equally distribute work loads and undesirable work times. 215 (1-1) General Schedule TABLE I-1 Date Location Activity 5 Oct. 1972 1E Meeting with Company Officials 16 Oct. 1972 1E Travel 16 Oct. 1972 1E Set-up Equipment 18-31 Oct. 1972 1E Testing 1 Nov. 1972 iE Take-down Equipment 1 Nov. 1972 1E Travel 23 Oct. 1972 2E Meeting with Company Officials 1 Nov. 1972 2B Travel 2 Nov. 1972 2E Set-up Equipment 8-16 Nov. 1972 2E Testing 17 Nov. 1972 2E Take-down Equipment 17 Nov. 1972 2E Travel 20 Jan. 1973 3E Meeting with Union Officials 24-25 July 1973 3E Travel 26 July 1973 3E Set-up Equipment 26 July-8 Aug. 1973 3E Testing 9 Aug. 1973 3E Take-down Equipment 10-11 Aug. 1973 3E Travel 7 Sept. 1973 3C Meeting with Union Officials 12-13 Sept. 1973 3C Travel 14 Sept. 1973 3C Set-up Equipment 16-21 Sept. 1973 3C Testing 23 Sept. 1973 3C Take-down Equipment 24-25 Sept. 1973 3C Travel 4 Oct. 1973 1C Meeting with Union Officials 11 Oct. 1973 1C Travel 11 Oct. 1973 1C Set-up Equipment 15-17 Oct. 1973 1c Testing 18 Oct, 1973 1c Take-down Equipment 24 Oct. 1973 1C Travel 24 Oct. 1973 1C Set-up Equipment 29 Oct.-2 Nov. 1973 1C Testing 6 Nov. 1973 1C Take-down Equipment 6 Nov. 1973 1C Travel 216 (1-2) TABLE I-2 Schedule of Testing, Location 1 E Date Time of Testing (Hours) Number Tested 10 Oct. 1972 1530 5 23 Oct, 1972 0730, 1430, 2300 13 24 Oct. 1972 1300, 1530 9 25 Oct. 1972 0730, 1300, 1530, 2330 19 26 Oct, 1972 1300, 1530 10 27 Oct. 1972 1300, 1530, 2330 10 28 Oct. 1972 1530 4 30 Oct. 1972 1430 5 31 Oct. 1972 1300 5 Total 80 TABLE I-3 Schedule of Testing, Location 2 E Date Time of Testing (Hours) Number Tested 8 Nov. 1972 0530, 1630 10 9 Nov, 1972 0530, 1630 10 10 Nov. 1972 0800, 1330, 1600 14 11 Nov. 1972 0830, 1200, 1500 12 12 Nov, 1972 0830, 1200, 1500 14 13 Nov, 1972 0530, 1330, 1630 14 14 Nov. 1972 0530, 1330, 1630 14 15 Nov. 1972 0530, 1330, 1630 13 16 Nov. 1972 1630, 1930 9 Total 110 217 (¥-3) TABLE I-4 Schedule of Testing, Location 3 E Date Time of Testing (Hours) Number Tested 26 July 1973 1215, 1545, 1800, 2015 15 27 July 1973 1215, 1545, 2015 8 28 July 1973 0900, 1200, 1545 9 29 July 1973 0900, 1545 4 30 July 1973 1200, 1745 9 31 July 1973 1200, 1745 6 1 Aug. 1973 0900, 1200, 1745 11 2 Aug. 1973 0900, 1200, 1745 13 3 Aug. 1973 0900, 1645 3 5 Aug. 1973 0900, 1200, 1545, 1800 14 6 Aug. 1973 1545 5 7 Aug. 1973 1745, 2400 10 8 Aug. 1973 1530, 1830 9 9 Aug. 1973 1200, 1530, 1830 10 Total 126 TABLE I-5 Schedule of Testing, Location 3 C Date Time of Testing (Hours) Number Tested 16 Sept. 1973 1600 5 17 Sept. 1973 1630, 1900 6 18 Sept. 1973 1600, 1900 8 19 Sept. 1973 1230, 1600 10 20 Sept. 1973 0800, 1600, 1900 12 21 Sept. 1973 0030, 1600 8 Total 49 218 (1-4) TABLE I-6 Schedule of Testing, Location 1 C Date Time of Testing (Hours) Number Tested 31 Oct. 1972 1700 5 15 Oct. 1973 0800, 1600 9 16 Oct. 1973 0800, 1600 9 17 Oct. 1973 1600 4 29 Oct. 1973 1600 4 30 Oct. 1973 1600 5 31 Oct, 1973 0800, 1200, 1600 10 1 Nov. 1973 0900, 1200, 1600 12 2 Nov. 1973 0900, 1600 5 Total 63 219 (1-5) APPENDIX J PROCEDURE FOR SCORING THE MICHIGAN EYE-HAND COORDINATION DATA Prepared by Karl E. Rothrock and John M. Lyddan APPARATUS During data collection, the responses to the eye-hand coordination task were recorded on magnetic tape with the use of a Sony Tape Recorder, Model No. TC-104, For purposes of scoring the data, the output of the tape recorder was fed into a Tektronic 114 Pulse Generator whose output was then relayed into Channel 3 of the real-time clock (KW-12A) of a Digital Equipment Corporation, PDP-12A Computer. Simultaneously, the output from the tape recorder was also fed through a Bogen CHB-35A Audio Amplifier into a speaker which allowed the operator to monitor the worker's recorded performance during scoring. A schematic diagram of the apparatus used in the scoring process is shown in Figure J-1. BOGEN AMPLIFIER SPEAKER - PDP-12A COMPUTER SONY SUNY } TEKTRONIX TAPE RECORDER PULSE GENERATOR [—1 = ~====-=-- CHANNEL 3 “4 — REAL-TIME CLOCK = “T= INPUT £L — TELETYPE (OUTPUT) = Figure J-1. Block diagram of the apparatus and equipment employed in scoring the eye-hand coordination data. 221 (J-1) SCORING PROCEDURE The procedure developed for use in scoring data obtained with the eye-hand coordination task was relatively complex and required that a number of rather arbitrary decisions be made by the scorer. A detailed description of this procedure for a typical worker's data is given below. Threshold Selection For each set of data, the scorer's first task was to adjust the volume of the tape recorder to a satisfactory "threshold" level. This was accompanied by listening to the audio tape recording of the worker's performance and by adjusting the playback volume until the pulse generator was always triggered by a "hit," but not by noise. The red light of the pulse generator was used as a visual reference for this purpose. Once the operator was satisfied with the threshold selection, he began the actual scoring of the data. It should be noted that the process of threshold selection represented a problem of considerable complexity and frustration. In many instances the noise (or a hit on top of the hole plate) was as loud as a real hit on the sounding plate. Therefore, it was extremely difficult to adjust the threshold properly. Scoring of Data The DIAL-MS system was loaded into the core area of the ppP-12AL, This system was then used to load the assembly language scoring program in the following manner: the LF key was typed on the teletype, followed by LO EYEHND, # and the RET key. Once tape motion had ceased, the I/Q PRESET and the START 2@ keys were toggles in order. This caused the program to begin running and to wait for input from the tape recorder to begin timing the hole-to-hole intervals. Scoring of the data began when the tape recorder, which had been positioned at the precise beginning of the worker's run, was started. Although the scoring was done automatically, it was necessary for the operator to monitor the procedure in order to listen for the occurrence of any double hits or missed responses which were not scored properly by the machine (because of an improper volume or threshold setting on the recorder). This also allowed him to halt the program (by means of a console switch) at the precise ending of the worker's run and then to shut off the tape recorder. At this point, the operator advanced the program to location 42¢@g (arbitrarily specified for this program) by setting the Left Switches to 420g and hitting the START LSW key. This enabled the program to print out, in octal (BASE 8) form, the number of hits scored, any time overflows, and the hole-to-hole times. Once the printout was completed, the The proper tapes were mounted on Units @ and 1, and both tape drives were set to WRITE ENABLE and REMOTE. The Left Switches were set to @#7@¢lg and the Right Switches to 73@@g, then the I/0 PRESET, DO, and START 2¢ console keys were toggled, in order. 222 (3-2) operator was required to decide whether or not to save the data from this scoring run for later analysis. Although this decision was somewhat arbitrary, it was made on the basis of the number of hits detected (approximately 117) and whether or not any of the inter-hole times were shorter (indicating that the threshold had been too low and that the bounce of the probe, or other noise, had been scored as a double hit) or longer (indicating that the threshold was too high and that a real hit had not been detected) than could be expected logically. If approx- imately 117 inter-hole times had been measured and the data were accepted, they were saved on magnetic tape by setting the Right Switches to @¢@¢gdg and pressing CONT on the console to continue the program. Once the tape motion ceased, or if the run were deemed unacceptable and not saved on magnetic tape at all, the operator inititated a second scoring of the same set of data. This was done by rewinding the tape recorder and positioning it, as before, at the beginning of the subject's data, toggling the I/0 PRESET and START 2{ keys on the console, and starting the recorder. When the scoring and printing of the second run was completed, the operator again made a decision whether or not to save the scores. If the decision were affirmative, the data were saved on magnetic tape by pressing CONT as before, with @@@@g in the Right Switches if the first run had not been saved but with P@@2g in the Right Switches if the first run had been saved (these switches serve to tell the program which tape blocks to use for storing the data). If either of the two scoring runs were discarded, the operator was forced to return to the start of the subject's data, score it again, and, if necessary, again and again, until two acceptable runs had been saved on magnetic tape. Once this point in the procedure had been reached, the operator determined by an examination of the data whether or not the two runs were similar (i.e., they had an identical number of hits). If they had different numbers of hits, it was necessary to initiate another run on this data, which, when completed, was saved in either tape block @@@gg or tape block @@@2g, depending upon which of the two previously saved runs it was to replace. When the output from two similar runs had been obtained, the operator hit the CONT key in order to automatically restart the DIAL-MS system. Summarization of Data The next step in the procedure was to obtain an average of the two sets of data that had been saved. The FOCAL-12 monitor was brought into core for this purpose by typing the LF key, LO F12, # and the RET key. When an asterisk was printed on the teletype, indicating that FOCAL-12 was ready to accept commands, the program was loaded by typing L L, $EYEHND, @# and the RET key. Once loaded (as indicated by the appearance of another asterisk), the operator started this program by typing G and the RET key. He advanced the teletype paper to a new page using the LF key and responded to the program's requests for information which appeared on the PDP-12A's CRT screen. When these requests were answered (by typing in the worker's number, the hand used, and the block desired for magnetic tape storage), the program computed an arithmetic mean of the two similar sets of data. These mean hole-to-hole times were then summed to obtain a total time which was divided by the number 223 (J-3) of hits detected to obtain an overall mean inter-hole time; all these data were then printed on the teletype. Once the printout was completed, the operator advanced the teletype paper again so that the printout could be saved. This action completed the scoring of the data for one hand of the worker. The operator then restarted the DIAL-MS system and scored the data for the other hand of this worker in an identical manner. The entire procedure was then repeated for each worker's data. DOCUMENTATION OF MACHINE LANGUAGE PROGRAM Scoring Program The first section of the program (octal locations 4@2@-4101; see Table J-1, at the end of appendix, for the machine language listing of the scoring program) is used to retrieve the eye-hand data from the audio tape recorder and relay it into the computer via Channel 3 of the real-time clock. The routine '"START'" readies the real-time clock to accept input into Channel 3. When the first pulse of data is detected on Channel 3, the real-time clock starts counting at 1¢@¢ Hz. The data are retrieved and the hole-to-hole times are measured by the routine called '"NEXT,'" which accomplishes the following: (1) Waits the required time established in subroutine ''DELAY," (2) Accepts input from Channel 3 of the clock, (3) Measures the time between events on Channel 3 to the nearest millisecond and stores this time in core, (4) Prints an "H" on the teletype for each event (or "hit') detected on Channel 3, and (5) Repeats steps 1, 2, 3, and 4 above until the operator physically halts the machine (by depressing the halt console switch) at the end of a subject's data. The manual halt is necessary because the tape recorder is not under computer control. Subroutine 'DELAY'" delays checking the clock for 2¢ msec for each negative value of the variable DELCNT. For example, if DELCNT equals -5, then the delay will be 1¢¢ msec. This delay is provided in order to avoid measuring two "hits" for a single hole which might be caused by probe bounce. The value of DELCNT must be adjusted depending upon the closeness of double hits for a given subject (delays ranging from 140 to 240 msec were used in the procedure described above). The KW-12A real-time clock counts from @¢@@ to 4¢95 (decimal); with the next count it sets an overflow flip-flop and starts counting upward from @@@@ again. Routine "OVRFLO'" tallys the number of times the overflow 224 (J-4) flip-flop is set between events on Channel 3. Each overflow represents a time of 4.096 sec, which is an unusually long inter-hole time. The overflow count also serves as a flag to the operator that a very long inter-hole time has occurred; he must then decide whether to keep or discard this inordinately long time. In either case the correction is made (by adding 4.096 sec to the time or deleting the time for the data) in the FOCAL-12 summary program. During the initial run of this section of the program, the operator must adjust the threshold of the input signal so that an "H" is printed once and only once for each real event, After proper adjustment of the threshold level the operator executes this section of the program again to get a ''good" run. When the operator is satisfied with the subject's data he physically halts the machine (see step 5 in the description of the "NEXT" routine), then restarts the program at location 420¢ (octal). The section of the program in locations 420@-4346 (octal) will print the octal equivalent of each hole-to-hole time as shown in Figure J-2. It will then convert these octal times into floating point format and halt, The first part of this section (42¢0-4215) sets pointers to ready routine "GETNUM" for printing the octal hole-to-hole times. Routine "GETNUM" separates each octal digit of all the hole-to-hole times and adds the ASCII constant necessary for printing on the teletype. It then prints the octal equivalent of the hole-to-hole times on the tele- type (see Fig J-2). These actions are accomplished by routine "GETNUM" through the execution of the following subroutines: (1) ASCII, (2) CRLF, (3) TYPE, and (4) SPACE. Subroutine "ASCII" adds 26f (octal) to each digit of each hole-to- hole time for printing on the teletype. Subroutine 'CRLF'" types a carriage return and linefeed after a complete line of hole-to-hole times has been printed. It also sets the counter LNCNT to the number of hole- to-hole times (14 octal) to be printed on a line. Subroutine "TYPE" prints each digit on the teletype, Subroutine "SPACE" types two spaces between each hole-to-hole time on a line. Finally, routine "CONT" (octal locations 4310-4346) converts the octal hole-to-hole times to floating point format and stores these floating point data in core and halts, If the operator is satisfied with the obtained data, he transfers these floating point data onto two blocks of magnetic tape (Unit @) by depressing the continue console switch. Before depressing the continue switch, the operator must set the right switches to the first block number of the two blocks to be used in the transfer. If block numbers other than blocks @# and 1 and blocks 2 and 3 are used, the FOCAL-12 summarization programs will have to be changed to account for this, Once the data is transferred onto tape, the program automatically returns to the DIAL-MS system to facilitate loading of the FOCAL-12 summarization program, 225 (J-5) HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH HH HHH HHH KHHHHHHHHHHH HH HH HH HH HHH HH HH HHH HHH a165 oa60 1026 1021 0631 0604 0657 0633 0644 0645 0626 0562 8572 0568 0614 @534 1374 0664 0562 0645 0661 0610 1272 1000 0660 0725 0650 0715 0647 1404 0762 08646 0623 0731 O716 0651 0725 @711 0641 08545 0705 0564 0673 0564 0541 0637 0664 0632 @515 0605 0610 0550 0683 07780 0523 0515 0540 0522 0541 0514 A511 8514 ©8555 1211 0@572 0702 0644 0572 ©0532 0616 ©8547 0533 1213 0744 0614 0747 0565 A524 2650 0672 0542 0531 0602 0736 1023 0771 0762 0766 0624 0623 0577 0635 0546 0536 0517 0600 B640 0612 0465 0602 0576 0518 ©0537 0543 1125 0687 0501 @463 8570 0506 ©8500 0510 0446 0376 0421 0430 08377 0367 0403 Figure J-2, Output of the scoring program. The series of "H's" represents each of the hits detected for this particular set of data. Below the "H's" are the octal equivalents of each hole-to-hole time. The first octal number in the series (indicated by ''A") represents the total number of hits detected, and the second (indicated by "B") represents the total number of hole-to-hole times greater than 4.096 sec. 226 (J-6 Routine "WRITE" transfers that floating point data into the two specified blocks of magnetic tape (Unit @). The section of program in octal locations 40@2-4@@#5 and 2@2@-2(¢33 is used to restart the DIAL-MS system after the magnetic tape transfer. In order to further reduce the data, the operator must load and execute the FOCAL-12 summarization programs described in the following sections. Summarization Programs The purposes of the FOCAL-12 sections of the program are two-fold: first, to facilitate the printing of the data in decimal form and second, to perform calculations which are, at best, clumsy in Assembly Language. Although there are two separate programs, they may be conceptualized as a unit, being linked together by program command and separated only due to the exigencies of a limited core area. The first of the two programs, $EYEHND is listed in Table J-2. It opens two files--one on Unit @#, block @#, from which the data are obtained (F1) and one on Unit 1, on which the data are to be written (F3). It then initiates a dialogue with the experimenter (via the VR14 LINCscope display) in order to obtain the subject number, the hand used, and the tape block number on which to store the data. This information is then typed out (via the ASR-35 teletype) as a heading for the data. Also typed out is the number of holes detected, obtained from file F1. This program then saves the subject number, the hand used, and the number of holes detected as part of file F1 on Unit @#. Both files are then closed and the second program called into core. The second program, $EYEDAT, is listed in Table J-3. It begins by opening the two previously used files (F1 and F3) and one other, F2. It then creates an array which is used to hold the average (arithmetic mean) of the two runs of data obtained in the assembly language portion of this system (saved in blocks @#, 1, 2, and 3 of Unit @# and accessed as files F1 and F2, respectively). It then saves this array of data as file F3 on Unit 1. Once saved, it outputs the data by setting up two loops, one to keep track of the total number of scores printed, the other to keep track of the number printed per line. Once the data aare printed out, the program uses the previously computed array of scores to obtain both the sum and the mean of these scores; the sum being then printed out as "Total Time'" and the mean time as ''Mean,' the former in sec and the latter in msec. At this point, its work being done, the program closes all three files and halts. The output from these summarization programs is provided in Figure J-3. 227 (J-7) Table J-1 Machine Language Listing of Program Used to Score Eye-Hand Coordination Data 2000 0081 0802 2003 2004 20085 2006 2007 2010 2011 9212 P0813 2014 015 016 a1? 2020 09221 2022 0023 2024 0025 8026 027 0039 2031 2032 0833 2034 00835 PA36 0037 0040 0041 0042 2043 0044 2045 8046 2047 2050 0051 2052 2053 8054 2055 0056 0020 4021 4022 4023 4024 4025 4026 4027 4030 4031 4032 4033 4034 4035 4036 40317 4040 4041 4342 4043 4044 4045 4046 4047 4050 4051 4052 4053 4054 4055 4056 4057 4060 4061 4062 4063 4064 2002 7300 6133 6132 1021 6132 6135 7200 1022 6134 7200 6046 1825 6131 5235 6132 6135 7200 3436 1036 3010 4270 6135 7200 6131 5259 6136 3044 6135 90209 7650 5300 1044 3410 1024 6041 5263 *20 /THIS PROGRAM IS FOR INPUT OF EYE=HAND /CORD, DATA INTO CHANNEL 3 OF THE REAL /TIME CLOCK, IT YIELDS INDIVIDUAL HOLE=- /TO-HOLE TIMES & PRINTS THESE HOLE=-TO- /TIMES AND HALTS.SET RSW TO APPROPRIATE /BLOCK NUMBER, HIT CONTINUE AND THESE /DATA WILL BE CHANGED INTO FLOATING /POINT NUMBERS AND STORED ON UNIT a, PDP PMODE START, CLA CLL CLAB /@ BUFFER=-PRESET CLLR /@ CLOCK CONTROL REG. TAD X0100 CLLR /f CLOCK COUNTER CLSA /8 CLOCK STATUS CLA TAD KO103 /LOAD CLOCK ENABLE CLEN /FOR CHAN.,3 & FLAG CLA TLS /DUMMY TLS TAD K4300 /CONST.:1008HZ, MODE 3 CLSK /SKIP ON CLOCK FLAG JMP .=1 CLLR /SET CCR: 10@0HZ, MODE 3 CLSA /@ CLOCK STATUS CLA DCA I OVRCNT/CLEAR LOC. 6081 TAD OVRCNT/RESET STOR! FOR EACH DCA STOR! /SUBJECT NEXT, JMS DELAY CLSA /@ CLOCK STATUS CLA CLSX /SKIP ON CLOCK FLAG JMP o=1 CLBA /BUFFER PRESET T0 AC DCA STOR /STORE COUNT TEMP, CLSA /CLOCK STATUS TO AC AND K2 /MASX CLOCK STATUS SNA CLA /WHAT CAUSED OVERFLO? JMP OVRFLO/CLOCK COUNT OVERFLO TAD STOR /EVENT ON CHANNEL 3 DCA 1 STORI TAD KO31@ /CONSTANT FOR H TSF /SKIP ON TTY FLAG JMP ,-1 228 (J-8) Table J-1 (continued) Machine Language Listing of Program Used to Score Eye-Hand Coordination Data 00517 2060 2061 2062 P9063 0064 2065 20866 0067 0070 208171 2072 8973 2074 20875 2076 2877 2100 2171 81022 2103 0104 2105 8106 107 0110 e111 L112 2113 2114 2113 2116 a117 2120 121 g122 2123 2124 2125 2126 9127 2130 2131 2132 2133 4065 4066 4067 4070 4071 49172 4073 40174 4075 4076 401717 4100 4101 4200 4201 4202 4203 4204 4205 4206 4207 A210 4211 4212 A213 4214 4215 A216 4217 4220 422] 4222 4223 4224 A225 4226 4227 6046 7200 5245 2000 1034 3035 2033 5273 2035 5273 5670 2436 5245 7300 1036 1041 1010 3427 18023 3410 4262 1427 1020 7041 3061 1826 3010 1410 3056 1256 2050 7006 7006 4257 A272 1056 2047 TLS /PRINT H ON TTY CLA JMP NEXT / / DELAY, © TAD XDELAY DCA DELCNT 1Ssz DELAY! /28 MS, DELAY JMP o=1 1SZ DELCNT /DELAY 1S 20 TIMES JMP ,-3 /VALUE OF DELCNT IN JMP I DELAY/MILLISECONDS. / / OVRFLO, ISZ 1 OVRCNT/NO. OF TIMES CLOCK JMP NEXT /COUNTER OVERFLOWS, / / / *4200 CLA CLL TAD OVRCNT /COUNT NO, OF HITS CIA /7& STORE IN LOCATION TAD STORI /6008 DCA I X6000 TAD X@177 /END WORD FOR EACH DCA 1 STORI /SUBJECTS DATA, JMS CRLF TAD 1 K6200 /NO, OF WORDS TAD K2 CIA DCA WDCNT TAD K5777 /ST.ADDRESS IN CORE DCA STOR! GETNUM, TAD I STORI DCA TEMP 1aD TEMP AND P700@8/MASK FOR BITS 2,1&2, RTL /BITS 0,1&2 INTO BITS RTL /9,10¢&11, JMS ASCII/ADD ASCII CONSTANT JMS TYPE/TYPE NO.ON TELETYPE, TAD TEMP AND P3700/MASK FOR BITS 3,445, 229 (J-9) Table J-1 (continued) Machine Language Listing of Program Used to Score Eye-Hand Coordination Data 2134 2135 2136 21317 2140 g1al 2142 2143 2144 2145 2146 2147 2158 2151 2152 0153 2154 2155 2156 2157 2160 2161 0162 2163 2164 2165 2166 2167 2179 2171 2172 2173 2174 2175 2176 2177 8200 9201 p202 2203 0204 P205 2206 22017 2210 2211 4230 4231 4232 4233 4234 4235 4236 42317 4240 4241 4242 4243 4244 4245 4246 4247 4250 4251 4252 4253 4254 4255 4256 4257 4260 4261 4262 4263 4264 4265 4266 4267 4270 42171 4272 4273 4274 4275 4276 421717 4300 1012 7012 7912 4257 4272 1056 2046 1012 7010 4257 4272 1856 2045 4257 4272 20517 5253 4262 5254 4300 2061 5216 5310 2000 1054 5657 0020 1031 3057 1852 4272 1051 4272 5662 2000 6041 5273 6046 7300 5672 2000 RTR RTR RTR JMS JMS TAD AND RTR RAR JMS JMS TAD AND JMS JMS Isz JMP JMS JMP JMS Isz JMP JMP ASCll, © TAD JMP CRLF, @ TAD DCA TAD JMS TAD JMS JMP / TYPE, 2 ISF JMP TLS CLA JMP / SPACE, © /BITS 3,445 INTO BITS /9,10¢&11, ASCII/ADD ASCII CONSTANT. TYPE/TYPE NO. ON TELETYPE. TEMP P2@ 79 /MASK FOR BITS 6,748, /BITS 6,748 INTO BITS /9,10&11, ASCII/ADD ASCII CONSTANT. TYPE/TYPE NO. ON TELETYPE. TEMP PP@B7/MASK FOR BITS 9,10411, ASCII1/ADD ASCII CONSTANT TYPE/TYPE NO, ON TELETYPE. LNCNT/14 WORDS ON A LINE? +3 /NO, CRLF/YES. +2 SPACE WDCNT/ALL OF DATA PRINTED? GETNUM/NO. GET MORE DATA, CONT/YES. CHANGE TO FP, pP26@ I ASCII Mia LNCNT P215 TYPE P212 TYPE I CRLF CLL } TYPE 230 (J-10) Table J-1 (continued) Machine Language Listing of Program Used to Score Eye-Hand Coordination Data 212 2391 1855 TAD PN2 213 4302 3069 DCA NUMSPC 2214 4303 1053 TAD P24¢ 2215 4304 4272 JM5 TYPE 0216 4305 2060 ISZ NUMSPC 202117 4306 5303 JMP ,-3 p220 4387 5720 JMP 1 SPACE 0221 / 9222 / 0223 / p224 / 8225 4319 1026 CONT, TAD K5777 /START OF DATA #226 4311 3019 DCA STORI B2217 4312 10390 TAD K6777 /SET STOR2 TO 6777 023¢ 4313 3011 DCA STOR2 2231 4314 1831 FPOINT, TAD Ml4 /SET ROTATE= -14 0232 4315 3043 DCA ROTATE 2233 4316 1410 TAD 1 STOR1/GET DATA WORD 2234 4317 3044 DCA STOR 2235 4320 1044 TAD STOR 0236 4321 1032 TAD MOL 77 2237 4322 7650 SNA CLA /END OF DATA? 0240 4323 53417 JMP WRITE/YES. WRITE DATA, 0241 4324 7100 CLL /NO, 9242 4323 1044 TAD STOR 2243 4326 7004 RAL /COUNT NO. OF BINARY p244 4327 7430 SZL /DIGITS IN DATA WORD 2245 4330 5334 JMP EXPONT/& CHANGE TO FLOATING 2746 4331 2043 ISZ ROTATE/POINT FORMAT, 0247 4332 5326 JMP ,-4 2250 4333 5340 JMP EXPO /EXPONENT=Q? 9251 4334 7019 EXPONT, RAR 2252 335 3044 DCA STOR /SAVE ROTATED DATA 2253 A336 1043 TAD ROTATE 8254 4337 T7041 CIA 9255 4342 3411 EXPO, DCA 1 STOR2/STORE EXPONENT 9256 4341 1044 MTISSA, TAD STOR 2257 £34: 1019 RAR /LEFT JUSTIFY DATA 9260 4343 3411 DCA I STOR2/STORE MSP OF DATA 2261 A344 7010 RAR /LINXK TO BIT a, 9262 4345 3411 DCA 1 STOR2/STORE LSP OF DATA 02263 4346 5314 JMP FPOINT/GET ANOTHER NUMBER? 0264 / 0265 / 8266 4347 6141 WRITE, LINC 02617 LMODE 2210 0350 ©0900 HLT /MORE DATA? 02171 2351 0516 RSW /YES, BLOCK NO, FOR DATA e272 0352 4367 STC BLOCK 231 (J-11) Table J-1 (continued) Machine Language Listing of Program Used to Score Eye-Hand Coordination Data 22173 8353 1020 LDA I 2274 2354 1775 1775 /=2(10 BIT INDEXING) 92173 8355 4010 STC BLKCNT/SET BLKCNT=-2. 22176 8356 2405 ADD L 7000 9277 8357 4406 STC WRST 2300 9360 2406 AGAIN, ADD WRST 2301 2361 0023 TMA /LOAD TAPE MEMORY ADDRESS 8302 2362 1020 LDA I 2303 8363 0020 2020 /EXT. ADDRESS MODE 0304 2364 0001] AXO 2305 P3655 0011 CLR 2306 B366 0704 WRC /WRITE ON UNIT 2 2307 9367 0020 BLOCK, 0000 2310 2370 2367 ADD BLOCK 2311 8371 2403 ADD LX1 /ADD ONE TO.BLOCK. 2312 2372 A367 STC BLOCK 2313 2373 2405 ADD L7000/INCREASE TAPE MEMORY 2314 0374 2404 ADD L377 /ADDRESS BY 377. 8315 0375 4406 STC WRST 2316 8376 0230 XSX 1 BLXCNT/TWO BLOCKS WRITTEN? 2317 2377 6360 JMP AGAIN/NO, 2320 0400 ©0001 AXO /YES, 2321 2401 0000 HLT /RESTART DIAL? 2322 0402 6002 JMP 2 2323 / 8324 0403 0@00! LXI, } 2325 2404 0377 L377, 377 8326 240% 7000 L7000, 70200 2327 2406 000 WRST, 0 0330 / 2331 PMODE P332 *2020 8333 LMODE 2334 0020 1020 LDA 1 /SET UP STARTING ADDRESS 8335 2021 4000 4000 /FOR BLK, 300 OF DIAL 2336 0022 0023 TMA /LOAD TAPE MEMORY ADDRESS 23317 2023 10209 LDA 1 8340 P0924 0020 2020 p341 P0025 0081 AXO /EXT.ADDRESS MODE P5342 2026 0700 RDC /READ IN BLOCK 300 2343 2027 0300 83009 P5344 2030 @all CLR 2345 8931 0001 AXO /CLEAR EXT, OPS, BUFFER 2346 Po32 0602 LIF 2 2347 2033 6029 JMP 20 2350 / 232 (I-12) Table J-1 (continued) Machine Language Listing of Program Used to Score Eye-Hand Coordination Data 2351 / 8552 PMODE 2353 *4002 2354 LMODE 2355 Ovi A1B| RCG /BEGIN TO RESTART DIAL 2356 AA2Y S30: 6301 8357 2804 G61 LIF | 2560 BGS 60: JMP 20 2361 / 0362 / 2363 PMODE 2364 x10 2365 0210 , / xd. ot Dudley G. Anderson Chief, Chilchood Lead Poisoning Control Branch 239 (K-1) Y¢ U.S. GOVERNMENT PRINTING OFFICE: 1975-657-603/5549 Region No. 5-11 U.C. BERKELEY LIBRARIES C029223540