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Both ambient fine particulate matter (PM2.5) and aging are important urban concerns. However, the associations between PM2.5 constituents and the acceleration of aging (AA) remain unclear. We included 16,051 adults (aged 25–80 years) with 19,252 medical observations in Taiwan during 2008−2017. 2-year average PM2.5 and its five major constituents were assessed using a two-stage machine learning model at a resolution of 1 km2. AA was determined by the difference between the Klemera–Doubal biological age and chronological age. A linear mixed model (LMM) with inverse probability weights was used to examine the associations between AA and air pollution. In a semi-randomized study design, we applied a post-matching LMM to assess the impacts of changes in air pollution exposure on AA. Each interquartile range increase in ambient PM2.5, SO4-2, NO3–, NH4+, organic matters (OM), and black carbon (BC) was associated with a 0.20 (95 %confidence interval [CI]: 0.17–0.24), 0.19 (0.15–0.23), 0.14 (0.11–0.18), 0.21 (0.17–0.24), 0.22 (0.19–0.26) and 0.25 (0.21–0.28) year increase in AA, respectively. BC was generally associated with the greatest increase in AA as compared to other constituents. We did not find evident thresholds in their concentration–response associations. Participants exposed to increased levels of PM2.5, SO4-2, NO3–, NH4+, OM, and BC experienced an increase in AA of 0.11 (−0.07–0.29), 0.20 (0.02–0.39), 0.15 (−0.02–0.33), 0.12 (−0.07–0.31), 0.24 (0.07–0.41), and 0.30 (0.07–0.52) years, respectively, compared to those exposed to decreased/unchanged levels. Long-term exposure to ambient PM2.5 and its constituents may accelerate biological aging among Chinese adults. Exposed to increased levels may further aggregate the aging process. This study suggests that reducing exposure to air pollution is beneficial, even for residents within moderately-to-highly polluted regions, such as Taiwan. Rigorous regulation of PM2.5 and its constituents may prevent the acceleration of biological age. |
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