Exposome

The environmental chemical exposome and health insurance: Examining associations and effect modification of epigenetic aging in a representative sample of United States adults

Cross-sectional study of 2,315 peoplePopulations
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Abstract

Environmental exposures are contributors to morbidity and mortality, yet the potential protective role of health insurance in mitigating these effects remains underexplored. We used data from the 1999-2000 and 2001-2002 cycles of the National Health and Nutrition Examination Survey (NHANES) to examine whether health insurance status is associated with the chemical exposome and whether being insured modifies relationships of environmental exposures with epigenetic aging biomarkers of morbidity and mortality (GrimAge2 and DunedinPoAm). Among 2315 adults aged 50 - 84 years, we evaluated 64 chemical exposures. In covariate, socioeconomic status-adjusted models, being insured compared to being uninsured was marginally associated with 0.21-SD lower blood lead levels (95% CI: -0.39, -0.04, P = 0.03) and 0.29-SD higher PCB180 levels (95% CI: 0.003, 0.57, P = 0.048). In leukocyte- and covariate-adjusted models, insurance attenuated the relationship of lead with GrimAge2 (Insured: β = 0.08-years, 95% CI: -0.08, 0.24; Uninsured β = 0.65-years, 95% CI: 0.11, 1.20; P interaction = 0.04) and DunedinPoAm (Insured: β = 0.001, 95% CI: -0.002, 0.003; Uninsured β = 0.01, 95% CI 0.0001, 0.02; P interaction = 0.047). Similar trends were also observed for cadmium, cotinine, and PCB180 but not statistically different between insurance categories. These findings suggest that health insurance may serve as a protective factor against the biological aging impacts of certain environmental exposures, possibly through improved access to exposure monitoring and preventive/therapeutic care. While not a substitute for environmental policy or exposure remediation, insurance may represent a small, complementary, and more immediately actionable tool to help reduce harm. However, given the small magnitude of model estimates, results should be interpreted with caution regarding their practical significance.