key: cord-0721579-65ys2w1h authors: Huang, Ying; Heflin, Colleen M.; Validova, Asiya title: Material Hardship, Perceived Stress, and Health in Early Adulthood date: 2020-09-17 journal: Ann Epidemiol DOI: 10.1016/j.annepidem.2020.08.017 sha: 4c2503b6599fa20cd76f2284d37c9a18a0d67f14 doc_id: 721579 cord_uid: 65ys2w1h OBJECTIVE: We examined the associations between material hardship and health outcomes in early adulthood, and the extent to which these associations are mediated by perceived stress. METHODS: We used Wave I & IV of the National Longitudinal Study of Adolescent Health (Add Health), a nationally representative survey of young adults aged 18 to 34 years old (N=13,313). Multivariate logistic regression and decomposition methods were used to evaluate the associations between types and depth of material hardship (food, bill-paying and health resource hardship) and health outcomes (self-rated health, depression, sleep problems, and suicidal thoughts) in early adulthood, and the extent to which these associations were mediated by perceived stress. RESULTS: The adjusted odds of fair or poor health status, depression, sleep problems, and suicidal thoughts were higher among individuals with material hardship than counterparts without. A considerable proportion of the association between material hardship and health outcomes was attributable to perceived stress. CONCLUSIONS: Material hardship is associated with adverse health outcomes in early adulthood, and these relationships are robust after accounting for various sociodemographic characteristics and family background. Perceived stress accounted for a sizable portion of the effects of material hardship on health. PUBLIC HEALTH IMPLICATIONS: Efforts to promote health equity in young adults should focus on material hardship and associated stressful conditions. experienced severe housing hardship, such as eviction and homelessness, suffer more health 48 problems than individuals without such housing hardship [25] [26] [27] . Finally, bill-paying hardship 49 occurs when individuals are unable to pay essential bills. The consequences of bill-paying 50 hardship can be severe, leading to utility interruption or shutoff, housing instability or eviction, 51 wage garnishment or bankruptcy [28] . Each of these forms of material hardship are experienced 52 as significant stressful events and are adversely associated with health outcomes, particularly 53 mental health [29] [30] [31] [32] . 54 Psychosocial stress has emerged as a leading mechanism linking material hardship and 55 poor health. The stress process model proposed by Pearlin [33, 34] posits that social 56 characteristics including those surrounding socioeconomic status lead to stress exposures that 57 affect health and psychological well-being. The stress process framework specifically 58 hypothesizes that stressful life conditions can set in motion physiological responses to maintain 59 equilibrium within the body and that, under conditions of chronic stress, these responses may 60 contribute to cumulative indicators of increased physiological risk [33, 34] . Conditions 61 surrounding material hardship may influence health if they are conducive to stress. It is proposed 62 that individuals experiencing material hardship are more likely to experience both chronic and 63 acute stressors in their lives [35, 36] . Numerous studies have provided empirical support for the 64 idea that material hardship is associated with more reported life stress [37, 38] . In addition, when In the analyses, we used data from Add Health, a nationally representative study of 90 adolescents in grades 7 through 12 in 1994-1995 who were followed into adulthood over four 91 waves of data collection [48] . The first wave of data collection occurred during the 1994-1995 92 school year with 20,745 participants who were in 7th to 12th grade and consisted of an in-home 93 and in-school assessment (Wave I). A second wave of collection occurred the following year in [49] . Dependent variables. Four measures of health outcomes were assessed. Self-rated poor 106 health (SRH) was assessed at Wave IV using a single question ('In general, how would you rate 107 your health?'). Responses of poor and fair are grouped into poor health, and responses of good, 108 very good and excellent are categorized as good health. The use of SRH intends to capture a 109 holistic view of health among young adults; it is reported to measure the same construct among 110 different ethnicities of adolescents and young adults [50] . Depression was measured using 20 111 items of a slightly modified version of the Center for Epidemiological Studies Depression (CES-112 J o u r n a l P r e -p r o o f D) [51, 52] . A cutpoint of ≥22 for males and ≥24 for females was established to maximize the 113 sensitivity and specificity for detecting major depressive disorder in young adults [53] . Sleep 114 problems was assessed by asking how often respondents had trouble falling and staying asleep 115 through the night in the last four weeks. Respondents could choose from the following categories: 116 never in the past four weeks, less than once a week, one or two times a week, three or four times 117 a week, and five or more times a week. In addition, respondents were asked whether there were 118 times when they snored or stopped breathing while sleeping. We used this information to create a young adults [54] [55] [56] , and these health issues are established predictors of morbidity and 125 mortality in later adulthood [57, 58] . (PSS) by Cohen and colleagues, consisting of four items, was used to measure respondents' 155 perceived stress [60] . During Wave IV interviews, respondents were asked how often in the past 156 30 days they (i) were unable to control important things in their lives, (ii) felt confident in their (reverse coded), and (iv) felt that difficulties were piling up so high that they were unable to 159 overcome them. The response set to these items ranged from 0 (never), 1 (almost never), 2 160 (sometimes), 3 (fairly often), to 4 (very often). Responses to the four items were summed 161 together to create the PSS, with higher values representing more perceived stress (α= .73). health outcomes in young adulthood [63, 64] , we further controlled for parental highest 180 educational attainment and family structure. The former was measured as a categorical variable ranging from less than high school to college or more. Family structure was a categorical 182 variable distinguishing two-parent household, single-parent household, and other types of 183 household. Parallel measures of adolescent self-rated poor health and depressive symptom scores 184 were also included as covariates in the analysis. All these family background information and 185 health covariates were taken from Wave I. Table 2 presented results of the logistic regression models that estimate health conditions Next, we introduced the proposed mediating variable-perceived stress-into the models 253 to potentially explain why individuals with material hardship have poorer health outcomes than 254 individuals without these hardships. Table 3 summarized the results from models with and 255 without perceived stress, which were referred to as direct and total effects of material hardship, 256 respectively. Captured by the term Δ (%) due to perceived stress in Table 3 , results suggest that Table 3 . On Our study had several limitations. First, our results pertain to health outcomes at young 303 adulthood. Thus, it is unclear how material hardship would be associated with morbidity and 304 mortality later in life, when such hardship could be more consequential. Second, the statistical 305 associations in this study were based on observational data that prevent causal conclusions. Although we controlled for a robust set of covariates, including income, it is possible that those 307 who experienced material hardship differ in unobserved ways from those who did not experience 308 material hardship. We subjected our main findings to sensitivity checks by replicating the 309 associations between material hardship and health outcomes by using propensity score matching 310 and inverse probability weighting; these are methods that are thought to be rigorous by reducing 311 the potential impact of selection bias. In all cases, the results were qualitatively similar to the 312 main findings. In addition, our falsification test suggests that prior health problems (measured as 313 poor self-rated health, depression, and sleep problems) have no statistically significant 314 association with concurrent material hardship. We present these sensitivity analysis results in 315 Appendix 1. Finally, although we found that the stress pathway is responsible for some of the 316 health effects of material hardship, we cannot preclude other plausible mechanisms through 317 which material hardship may influence health. For example, nutritional deficiencies may accompany food hardship, which in turn, leads to poor health outcomes. It is also plausible that 319 the bill-paying hardship exposes individuals to hazardous living conditions that bring harm to 320 physical and mental health. Future research may consider using longitudinal data to address 321 some of these limitations. It may also be fruitful to investigate other mechanisms through which Note: (1) Abbreviation: OR Odds Ratio. (2) * p<0.05, ** p<0.01, *** p<0.001 (two-tailed tests). (3) 95% confidence intervals in parentheses. All models controlled for covariates shown in Table 4 . The structure of material hardship in US households: An examination of the coherence behind common measures of well-being. 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