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. 2015 Jun;56(2):199-224.
doi: 10.1177/0022146515582100. Epub 2015 Apr 30.

Race-Ethnicity, Poverty, Urban Stressors, and Telomere Length in a Detroit Community-based Sample

Arline T Geronimus  1 , Jay A Pearson  2 , Erin Linnenbringer  3 , Amy J Schulz  4 , Angela G Reyes  5 , Elissa S Epel  6 , Jue Lin  6 , Elizabeth H Blackburn  6
Affiliations

Race-Ethnicity, Poverty, Urban Stressors, and Telomere Length in a Detroit Community-based Sample

Arline T Geronimus et al. J Health Soc Behav. 2015 Jun.

Abstract

Residents of distressed urban areas suffer early aging-related disease and excess mortality. Using a community-based participatory research approach in a collaboration between social researchers and cellular biologists, we collected a unique data set of 239 black, white, or Mexican adults from a stratified, multistage probability sample of three Detroit neighborhoods. We drew venous blood and measured telomere length (TL), an indicator of stress-mediated biological aging, linking respondents' TL to their community survey responses. We regressed TL on socioeconomic, psychosocial, neighborhood, and behavioral stressors, hypothesizing and finding an interaction between poverty and racial-ethnic group. Poor whites had shorter TL than nonpoor whites; poor and nonpoor blacks had equivalent TL; and poor Mexicans had longer TL than nonpoor Mexicans. Findings suggest unobserved heterogeneity bias is an important threat to the validity of estimates of TL differences by race-ethnicity. They point to health impacts of social identity as contingent, the products of structurally rooted biopsychosocial processes.

Keywords: Latinos; aging; blacks; health disparities; neighborhood; poverty; stressors; telomeres; urban; whites.

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Figures

Figure 1
Figure 1
Predicted telomere length for 45-year-old participants adjusting for race/ethnicity (left), and also stratifying by poverty status (center; right)
Figure 2
Figure 2
Predicted telomere length differences among the poor compared to the non-poor within each race/ethnicity group, in Model 2 and Model 8 Notes: Model 2 controls for age and sex; Model 8 adjusts for all measured covariates.
See this image and copyright information in PMC

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