12 Years of Exercise Data Shows Physical Activity Slows Biological Aging by Over a Year

Epigenetic aging clocks — tools that measure biological age through DNA methylation patterns — are among the most promising biomarkers for predicting health outcomes and disease risk in aging populations. While prior research has suggested exercise may slow epigenetic aging, most studies have been cross-sectional or relied on short-term interventions. This study from the University of Michigan addresses that gap using 12 years of longitudinal physical activity data from the Health and Retirement Study (HRS), one of the largest and most representative cohorts of older Americans.

The study enrolled 3,873 participants from the HRS Venous Blood Study, all of whom had leukocyte DNA methylation assessed in 2016 using the Infinium Methylation EPIC BeadChip. Three second-generation epigenetic clocks were used: GrimAge acceleration (GrimAA), PhenoAge acceleration (PhenoAA), and DunedinPACE. These clocks were chosen for their superior ability to capture biological aging variability compared to first-generation tools. Physical activity was self-reported biennially from 2004 to 2016, with participants classified as 'active' if they engaged in vigorous activity at least weekly or moderate activity more than once weekly.

In cross-sectional analysis for 2016, 58% of participants were classified as physically active. After adjusting for age, sex, race/ethnicity, education, total wealth, and smoking status, active participants had significantly lower epigenetic age acceleration: −1.26 years for GrimAA (95% CI: −1.59 to −0.93), −1.70 years for PhenoAA (95% CI: −2.26 to −1.15), and −0.05 years per chronological year for DunedinPACE (95% CI: −0.06 to −0.04). These associations attenuated only slightly after further adjustment for BMI, mobility limitations, and chronic disease, indicating that the relationship is not simply mediated by body composition or illness burden.

Importantly, the researchers applied a Structured Life-Course Modelling Approach (SLCMA) — a novel statistical method that simultaneously evaluates wave-specific and cumulative physical activity exposures to determine which timing pattern best predicts EAA. This approach identified both accumulated physical activity over the full follow-up period and the most recent 2016 measurement as the two strongest predictors of epigenetic age acceleration across all three clocks. This dual finding suggests that both long-term consistency and current activity independently matter for biological aging.

The study also uncovered meaningful effect modification by social factors. Males showed significantly stronger associations between physical activity and DunedinPACE compared to females (P-interaction = 0.04). Notably, Hispanic participants showed a paradoxical positive association between physical activity and GrimAA compared to non-Hispanic Whites (P-interaction = 0.009), a finding the authors suggest warrants further investigation and may reflect unmeasured socioeconomic or cultural factors. These heterogeneities underscore that the benefits of physical activity on epigenetic aging may not be uniformly distributed across demographic groups, with implications for targeted public health interventions.