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The Unequal Benefits of Upward Mobility Lauren Gaydosh , Kathleen

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The Unequal Benefits of Upward Mobility Lauren Gaydosh , Kathleen The Unequal Benefits of Upward Mobility Lauren Gaydosh1, Kathleen Mullan Harris1, Kristen Schorpp1, Sara McLanahan2, Edith Chen3, and Greg Miller3 Background The socioeconomic gradient in health in the United States is persistent, and increasing over time.1–5 Individuals in the top 1% of the income distribution can expect to live 10-15 years longer than those in the bottom 1%.4 Individuals with a college degree can also expect to outlive their less educated counterparts by about a decade.5 However, higher socioeconomic status (SES) is not uniformly beneficial for all individuals; there is evidence that the education payoff is not as steep for minority groups compared to non-Hispanic whites,5,6 and may in some cases actually be associated with worse health.7 Furthermore, it is not only achieved SES in adulthood that shapes health; childhood SES is strongly predictive of childhood health and endures across the life course.8,9 There is emerging evidence that the interaction between childhood and adult SES may actually have important implications for health. In a set of papers by Brody, Chen, Miller and colleagues, the authors document a pattern that they refer to as “skin-deep resilience”, wherein rural African Americans from severely disadvantaged backgrounds who manage to achieve upward mobility demonstrate lower rates of psychosocial problems, but poorer physiological health compared to African Americans from similar backgrounds who remain disadvantaged.7,10,11 Two studies suggest that this relationship may exist in other populations and subgroups beyond rural African Americans. Research from the Dunedin birth cohort in New 1 Carolina Population Center, University of North Carolina at Chapel Hill 2 Office of Population Research, Princeton University 3 Department of Psychology, Northwestern University DRAFT – PLEASE DO NOT CITE OR CIRCULATE - 1 Zealand finds that upwardly mobile individuals have similar or worse health compared to stably low status individuals.12 A study among American adults documents a greater prevalence of chronic conditions among individuals with some college education compared to those with only a high school education, but this study did not explore the role of upward mobility.13 In this project we examine the health consequences of individual trajectories of upward socioeconomic mobility in a nationally representative sample of American adults. Upward mobility may be associated with multiple stressors that could have health consequences. First, the sustained level of effort, self-control, and single-mindedness required to achieve upward mobility from a highly disadvantaged setting may be stressful and physiologically taxing.7,10,11 In African Americans, such high-effort coping strategies have been referred to as “John Henryism”.14 There is mixed evidence as to how sustained vigilance relates to health outcomes, with variation by physiological and psychological outcomes,15–17 as well as by gender.18 Second, when individuals from disadvantaged backgrounds achieve upward mobility, it is likely that the higher SES environment in which they find themselves differs greatly from their social environment of origin.19,20 Such incongruence may lead to feelings of isolation, and experiences of discrimination.15,21–23 Upward mobility may also weaken or sever social ties, leading to a lack of social support, which is predictive of poor health.24,25 Third, both sustained effort and social isolation may lead to greater levels of perceived stress, which has been demonstrated to affect health.26,27 Upwardly mobile individuals may also feel that their achieved position is tenuous,28,29 and perceived stress may reflect perceptions of threat. Finally, stress associated with upward mobility may lead to unhealthy coping behaviors that vary by gender.30,31 Indeed, Jackson and colleagues find that the coping behaviors (smoking, drinking, poor diet) employed by black individuals may serve to buffer against psychological disorders DRAFT – PLEASE DO NOT CITE OR CIRCULATE - 2 while creating physiological health costs.32 These findings underscore the need to examine physiological, psychological, and cognitive health separately. We investigate the health consequences of upward mobility using nationally representative integrated demographic, social, contextual and biological data. We hypothesize that upward mobility is physiologically taxing, resulting in poorer physiological health. We extend this research by examining other race/ethnic groups that have not been included in prior research.7,10,15 To our knowledge, ours is the first study to test “skin-deep resilience” in a nationally representative, racially and ethnically diverse sample. Understanding the health risks associated with upward mobility will provide a more nuanced understanding of the relationship between SES and health. Documenting the health consequences of social mobility in early adulthood provides a foundation from which to understand different aging trajectories for those from disadvantaged backgrounds that begin during the transition to adulthood. Furthermore, documenting and explaining the physiological health costs associated with upward mobility can inform the development of interventions to reduce stress and avoid the presumptive biological costs associated with upward mobility, thereby encouraging healthy aging. Data and Methods Data - We rely on data from the National Longitudinal Study of Adolescent to Adult Health (Add Health). Add Health is an ongoing national longitudinal study of the social, behavioral, and biological linkages in health and developmental trajectories from early adolescence into adulthood. The data are representative of American adolescents in grades 7-12 in 1994-1995. The initial sample included 20,745 adolescents aged 12-20; since the start of the study, DRAFT – PLEASE DO NOT CITE OR CIRCULATE - 3 participants have been interviewed in home at four data collection waves. At Wave IV in 2008- 2009, respondents were aged 24-32 (n=15,701, 80.3% response rate) and asked to participate in biological specimen collection (over 95% provided specimens, almost 15,000). These data are particularly well-suited to address the specific aims described here, as they include detailed family, contextual, health and biological measures. Furthermore, the Add Health sample is diverse, with an oversample of particular ethnicities/races enabling an exploration of heterogeneity of the influence of upward mobility. Finally, the physiological biomarkers of health risk examined here are predictive of health before disease is manifest, permitting a window for potential aging interventions. Childhood Disadvantage – To measure childhood disadvantage, we construct a count of 27 binary indicators that capture cumulative exposure to household, school, and neighborhood disadvantage over childhood and/or during adolescence (Wave I). Household disadvantage indicators include a binary indicator of cumulative family instability across childhood and adolescence, low parent education (less than high school), the bottom quartile of household income, household welfare receipt in the past month, parent unemployment, and parent-reported difficulty paying bills. Neighborhood disadvantage indicators were taken from the 1990 U.S. Census to best approximate neighborhood conditions during Wave I of the Add Health study. Neighborhood disadvantage measures include the tract-level proportion of households receiving welfare, proportion of unemployed adults, proportion of households below poverty line, proportion of adults with less than a high school education, proportion female headed households, proportion black residents, proportion vacant homes, and the county-level infant mortality rate and violent DRAFT – PLEASE DO NOT CITE OR CIRCULATE - 4 crime rate. Each item was recoded so those residing in neighborhoods at the top quartile of the distribution were coded as disadvantaged. Parental reports of neighborhood conditions or problems were also included in the index, including parent-reported problems with neighborhood litter, neighborhood drug use, and desire to move away from the neighborhood. Finally, indicators of school disadvantage at Wave I included school-level aggregated measures of the proportion of households receiving welfare, the proportion of unemployed parents, the proportion of single-parent households, and the proportion of parents with less than a high school education. All items were recoded as binary indicators, with the top quartile coded as disadvantaged. School disadvantage was also captured using Wave I school administrator reports of grade retention, the school dropout rate, class sizes, the proportion teachers with a Master’s degree, and daily school attendance. Consistent with other items in the index, school administrator items were recoded as binary indicators, with the top quartile of grade retention, dropout rate, and class size coded as disadvantaged, and the bottom quartile of teachers with an MA and daily school attendance coded as disadvantaged. We sum all of the indicators to create a score ranging from 0 to 25 with a mean of 5.7. We standardize the score, so that the coefficients associated with the disadvantage index can be interpreted as the change in health risk associated with a one standard deviation increase in disadvantage. Adult Achievement - We measure adult achievement with an indicator for whether the respondent has completed any college education by Wave IV (age 25-34). DRAFT – PLEASE DO NOT CITE OR CIRCULATE - 5 Adult Health Outcomes
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