The role of socioeconomic factors in Black-White health inequities across the life course: Point-in-time measures, long-term exposures, and differential health returns

Abstract

Research links Black-White health disparities to racial differences in socioeconomic status (SES), but understanding of the role of SES in racial health gaps has been restricted by reliance on static measures of health and socioeconomic well-being that mask the dynamic quality of these processes and ignore the racialized nature of the SES-health connection. Utilizing twenty-three years of longitudinal data from the Panel Study of Income Dynamics (1984-2007), this study uses multilevel growth curve models to examine how multiple dimensions of socioeconomic well-being—including long-term economic history and differential returns to SES—contribute to the life course patterning of Black-White health disparities across two critical markers of well-being: body mass index (N=9,057) and self-rated health (N=11,329). Findings indicate that long-term SES exerts a significant influence on both body mass index and self-rated health, net of point-in-time measures, and that Black-White health gaps are smallest in models that adjust for both long-term and current SES. I also find that Blacks and Whites receive differential health returns to increases in SES, which suggests that other factors—such as neighborhood segregation and exposure racial discrimination—may restrict Blacks from converting increases in SES into health improvements in the same way as Whites. Together, these processes contribute to the life course patterning of Black-White health gaps and raise concerns about previous misestimation of the role of SES in racial health disparities.

The social income inequality, social integration and health status of internal migrants in China

“…More social income inequality had a negative impact on self-reported health, perceived stress, subjective well-being, and mental health, even at the same level of socioeconomic integration. Findings from previous studies have suggested that socioeconomic factors were a primary driver of health inequities [ 58 ], in accordance with our results.…”

How do age and major risk factors for mortality interact over the life-course? Implications for health disparities research and public health policy

“…The “age-as-lever” has been given empirical support in mortality studies of various populations based on evidence that the hazard ratio associated with low SES or being a race/ethnic minority decline by age (de Mheen et al, 2001; Elo & Preston, 1996; Hoffmann, 2011; Lauderdale, 2001), but this finding is not universal (Dupre, 2007; Lynch, 2003). Studies of other health outcomes have also reached varying conclusions with some supporting cumulative disadvantage (Shuey & Willson, 2008; Willson, Shuey, & Elder, 2007), age-as-leveler (Boen, 2016; Brown, Richardson, Hargrove, & Thomas, 2016), or persistent inequality (Ferraro & Farmer, 1996), the latter of which reflects a constancy in the magnitude of the association across age.…”

Racial Disparities in COVID‐19 Mortality Among Essential Workers in the United States

“…We found that NH Blacks residing in the Midwest—specifically, Wisconsin, Kansas, Missouri, Michigan, and Illinois—have been the hardest hit by COVID‐19, with mortality rates ranging from nearly three to six times higher than those of NH Whites. While many Midwestern cities are often designated among the “best places to live” in America (Mishkin, Bhardwaj, Raimonde, & Wilt, 2019; US News & World Report, 2020), for NH Blacks they are among the worst places to call home due to well‐documented racial disparities in education, incarceration, employment, income, health, medical care, homeownership, voting access, wages, and numerous other socioeconomic factors (Boen, 2016; Council on Ethical and Judicial Affairs, 1990; Geruso, 2012; Stebbins & Comen, 2018; Williams & Jackson, 2005).…”