key: cord-0847796-l18vrwtz
authors: Piyathilake, Chandrika J.; Badiga, Suguna; Chappell, Ashley R.; Johanning, Gary L.; Jolly, Pauline E.
title: The dataset for the assessment of the inflammatory potential of the overall diet consumed by women of childbearing age
date: 2021-06-21
journal: Data Brief
DOI: 10.1016/j.dib.2021.107238
sha: b6f5b89e2983b9e3a6de8000d3c8c301d6e1dedb
doc_id: 847796
cord_uid: l18vrwtz

The data presented in this article is related to the research article titled “Racial differences in dietary choices and their relationship to inflammatory potential in childbearing age women at risk for exposure to COVID-19”. This data article provides details of dietary intake data from 509 women (African American, n = 327 and Caucasian American, n = 182) who are residents of Birmingham, AL. All women were characterized for demographic and lifestyle factors and indicators of excess body weight (EBW) that are likely to influence overall dietary habits. Dietary intake data was collected by administering the modified version of the NCI validated Block food frequency questionnaire (98.2-isoflav version) that includes 110 food items of the original version (98.2 version) and an additional 24 phytochemical rich food items. The data article describes our approach to derive the dietary inflammatory score using a validated empirical dietary inflammatory index based on the frequency and the amount of consumption of each food item with minor modifications. This data will allow researchers to understand the composition of a Southern-style diet consumed by women of childbearing age and its relationship to inflammatory potential, EBW, dietary guidelines, dietary reference intakes or diet quality indices.

The data presented in this article is related to the research article titled "Racial differences in dietary choices and their relationship to inflammatory potential in childbearing age women at risk for exposure to COVID-19". This data article provides details of dietary intake data from 509 women (African American, n = 327 and Caucasian American, n = 182) who are residents of Birmingham, AL. All women were characterized for demographic and lifestyle factors and indicators of excess body weight (EBW) that are likely to influence overall dietary habits. Dietary intake data was collected by administering the modified version of the NCI validated Block food frequency questionnaire (98.2-isoflav version) that includes 110 food items of the original version (98.2 version) and an additional 24 phytochemical rich food items. The data article describes our approach to derive the dietary inflammatory score using a validated empirical dietary inflammatory index based on the frequency and the amount of consumption of each food item with minor modifications. This data will allow researchers to understand the composition of a Southern-style diet consumed by women of childbearing age and its relationship to inflammatory potential, EBW, dietary guidelines, dietary reference intakes or diet quality indices. Table   Subject Health and Medical Sciences -Nutrition Specific subject area

The dataset for the assessment of the inflammatory score of the diet of women of childbearing age Type of data Tables-3 Figure- 1 How data were acquired Dietary data was obtained by administering NCI validated food frequency questionnaire (Block 98.2-isoflavon) Data format Raw, Analysed Parameters for data collection Data was obtained from women age 19-50 years Description of data collection Information regarding demographics and lifestyle factors was obtained by administering a risk factor questionnaire. Height, weight and waist circumference were measured using standard procedures. BMI was computed using weight and height measurements. % body fat was measured using a TANITA bioelectrical impedance equipment. Dietary intake data that reflected

The dataset deposited consists of demographic information, lifestyle factors and dietary intake data obtained from 509 women of aged 19-50 years who are residents of Birmingham, AL. Demographic data consists of age, race, level of education and indicators of excess body weight (EBW), namely, BMI, percentage of body fat and waist circumference and health insurance information. Lifestyle data variables include parity, level of physical activity (minutes/week) and current smoking status (yes/no). The distribution of demographic and lifestyle data of the population are presented in Table 1 . A majority of the women are African American (64%), have excess body weight (~60% based on BMI, % body fat or WC), completed high school education or higher education (79%), engaged in less than 150 min of moderate physical activity (80%), non-smokers (67%) and 67% with parity ≥ 1 at the time the data collection. 50% of the women paid their medical care on their own while 50% had coverage through health maintenance organization (HMO), Medicaid or other government assistance.

To obtain dietary intake data, we administered the Block food frequency questionnaire 98.2isoflavon version, which contains 110 food items of the original questionnaire (98.2) and an additional 24 phytochemical containing food items. The Block associates merged those additional 24 food items shown in Fig. 1 with the 98.2 version to create the 98.2-isoflavon version.

The dietary intake data deposited is in the form of Microsoft Excel spreadsheets at the following site: Mendeley Data-Dietary Data . The Excel sheet 1 provides information on the frequency and the amount of food items consumed, daily intakes of macro and micronutrients, phytochemicals, dietary fibre, servings of food groups (vegetables, fruits, grains, dairy, meat/beans, dairy and fat/sugar/sweets) and health indices (glycaemic index, glycaemic load and healthy eating index). The frequency of consumption of food items is presented as the following codes; 1 = never, 2 = a few times per year, 3 = once per month, 4 = 2-3 times per month, 5 = once per week, 6 = 2 times per week, 7 = 3-4times per week, 8 = 5-6 times per week, 9 = every day. To be consistent, we have converted the frequency of consumption of food items to per week. As shown in Excel sheet 1 , the amount of food consumed is coded as 1, 2, 3, 4 referring to the serving sizes from small to large and M referring to missing data. Excel sheet 2 provides the codes based on the number of servings from 1-4 or missing data as "M" for each food item or a group of similar items. Excel sheet 3 provides the data dictionary for demographic and lifestyle variables, indicators of EBW, and food items provided in the excel sheet 1.

All food items were grouped into two categories based on their inflammatory potential as either anti-inflammatory foods (75 food items) or pro-inflammatory foods (55 food items) based on published reports of knowledge about their effects on overall diet-related inflammation score or inflammatory biomarkers [1] [2] [3] [4] [5] [6] [7] [8] [9] and further grouped based on their similarityfurther subdivided into various food groups as shown in Table 2 . The scoring of the food items based on the frequency and the amount of consumption of the food item(s) per week is presented in Table 3 .

The data was collected from 509 reproductive age women who are residents of Birmingham, AL. A risk factor questionnaire was administered to obtain information regarding demographics and lifestyle factors. Height, weight and waist were measured using standard procedures. BMI was computed using the weight and height measurements (kg/m 2 ). Percentage body fat was measured using the TANITA bioelectrical impedance equipment.

Self-administered dietary intake data was gathered using the modified version of the validated Block food frequency questionnaire (FFQ) 98.2-isoflavon that contain 134 food items (110 food items of the original version + 24 phytochemical rich food items added). The study staff was available to provide guidance and clarity on questions and to check the completeness of answering questions. The questionnaire included information on the portion sizes of food items consumed and their frequency. Each participant was provided with portion size pictures to aid in choosing the accurate portion size. Information obtained from the FFQ data was processed by the Nutriquest (Mason City, IA 50401) using a database developed and updated from the USDA Nutrient Database for Reference standards. The data file provided by the Nutriquest included information on the estimates of the amount and the frequency of each food item as wells as daily nutrient intakes of 40 nutrients of interest to the current study.

Dietary data summarized was used to calculate the DIS using a similar method as described by Kannauchi et al [10] to derive the empirical dietary inflammatory index (eDII), an index based on the frequency and the amount of consumption of foods. Unlike in this previous method, we scored individual food items rather than food groups in order to obtain a more comprehensive score. Briefly, we grouped the food items consumed by each study participant as pro-inflammatory or anti-inflammatory based on published reports of knowledge about their effects on overall diet-related inflammation score or inflammatory biomarkers. [1] [2] [3] [4] [5] [6] [7] [8] [9] The food items grouped as anti-inflammatory ( n = 75) or pro-inflammatory ( n = 55); respectively and were further grouped based on their similarity. We computed the weekly consumption of each food item using the frequency and quantity information reported by the participants. We then categorized the consumption of each food item into three groups of consumption level as high, moderate or low based on frequency and amount consumed per week and provided a score depending on whether the item was pro-inflammatory ( + 2, + 1 or 0) or anti-inflammatory ( −2, −1 or 0). The inflammatory scores of all items were then added to create the overall DIS for each study participant. For example, if the study participant had a score of −30 for the consumption of anti-inflammatory foods and a score of + 35 for the consumption of pro-inflammatory foods, then the overall DIS for that participant is + 5. 

The data collection was conducted according to the Declaration of Helsinki and was approved by the University of Alabama at Birmingham Institutional Review Board, protocol number IRB-040126002.

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Dietary red and processed meat intake and markers of adiposity and inflammation: the multiethnic cohort study

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Effect of dietary sugar intake on biomarkers of subclinical inflammation: a systematic review and meta-analysis of intervention studies

A novel dietary inflammatory index reflecting for inflammatory ageing: technical note

This work was supported by R01 105448 (National Cancer Institute) and T37-MD001448 (Minority Health Research Training grant, National Institute on Minority Health and Health Disparities)

Supplementary material associated with this article can be found in the online version at doi: 10.1016/j.dib.2021.107238 .

The authors have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.