Health insurance and epigenetic aging: Trends in a United States adult population

Abstract

Background: Health insurance plays an important role in reducing morbidity and mortality. Still, there is limited data examining the relationships of health insurance with biomarkers of aging that reflect morbidity and mortality risk.

Methods: We conducted a cross-sectional study of United States adults using data from the National Health and Nutrition Examination Survey (NHANES) to examine the relationships of health insurance with seven DNA methylation-based biomarkers of aging (epigenetic age): HannumAge, HorvathAge, SkinBloodAge, PhenoAge, GrimAge2, DNAm Telomere Length, and DunedinPoAm.

Results: Our analyses included 2315 participants with available health insurance and epigenetic aging data (mean [sd] age, 65.1 [9.3] years). Compared to the uninsured, having health insurance was associated with a 2.25-year lower GrimAge2 (95 %CI: -3.49, -1.02, P = 0.001) and a slower DunedinPoAm pace of aging (β = -0.04, 95 %CI: -0.06, -0.02, P < 0.001) in basic demographic-adjusted models. GrimAge2 (β = -1.42, 95 %CI: -2.75, -0.09, P = 0.04) and DunedinPoAm (β = -0.03, 95 %CI: -0.06, -0.01, P = 0.02) relationships were attenuated after additional adjustments for general health, body mass index (BMI), education, occupation, and poverty-to-income ratio. Model estimates were larger if insurance plans were more comprehensive and included dental coverage and/or single service plans. When considering categories of insurance, similar trends were observed with private insurance and public insurance plans (i.e. Medicare, Medicaid/CHIP, and other government plans), although private insurance relationships were more often statistically significant.

Conclusion: Our findings suggest that epigenetic aging measures may be useful for examining the relationship between health insurance and population health, with potential implications for policy decisions.

Keywords: CHIP; DNA methylation age; Dental insurance; Medicaid; Medicare.

Fig. 1

Pearson Correlations (r) and Median Absolute Error (MAE) of Epigenetic Age with Chronological Age.Fig. 1 presents the chronological age and epigenetic age correlation coefficients and median absolute errors for the study sample (n = 2315) for Hannum DNAmAge [A], Horvath DNAmAge [B], SkinBloodAge [C], PhenoAge [D], GrimAge2 [E], DNAmTL [F], and DunedinPoAm [G]. Insured participants are shown in blue while uninsured participants are shown in red.