Abstract

BACKGROUND AND AIM: Neighborhood socioeconomic status (nSES) may affect human health through stress pathways, but few studies to date have investigated this hypothesis. We studied the association between nSES and multiple biomarkers of cellular aging and inflammation. METHODS: We used data from several nested case-control studies conducted within two US-based cohorts of men and women. Blood samples were collected for a subset of participants ten years after enrollment (1989/90 for NHS, 1996 for HPFS). Relative leukocyte telomere length (rLTL) was assayed using quantitative polymerase chain reaction. Inflammatory biomarkers (c-reactive protein (CRP), interleukin-6 (IL-6), soluble tumor necrosis factor receptor 2 (sTNFR-2)) were assessed. Nine census tract measures of income, home value, earnings from rent and dividends, education, and demographics in 1990 were assigned to each participant’s address (home for NHS, home or work for HPFS) at the time of blood draw. We z-scaled component measures, and then summed together to create a nSES score. Associations between nSES and log-transformed biomarkers were estimated using linear regression models adjusted for individual level demographics, disease history, and lifestyle factors. RESULTS:Participants with available biomarker data ranged from 9,481 (IL-6) to 15,400 (CRP). Women (57.4 years) were younger than men (62.5 years). Adjusted models revealed no association between nSES and rLTL in women (β for 1-unit increase in nSES z-score=0.001, 95% CI: -0.003, 0.005) or men (β=0.001, 95% CI: -0.001, 0.003). However, in women, higher nSES was associated with lower circulating levels of CRP (β=-0.008, 95% CI: -0.013, 0.002), IL-6 (β=-0.006, 95% CI: -0.010, 0.002), and sTNFR-2 (β=-0.002, 95% CI: -0.004, -0.0004). In men, nSES was not associated with CRP, but weaker inverse associations for IL-6 (β=-0.004, 95% CI: -0.010, 0.001) and sTNFR-2 (β=-0.004, 95% CI: -0.006, -0.0013) were observed. CONCLUSIONS:Findings suggest that inflammation, rather than cellular aging, may mediate stress-related consequences of nSES. KEYWORDS: Built environment, internal exposome, socio-economic factors, cancer and cancer-precursors, environmental epidemiology

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