Background: The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM1 which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas.
Methods: A total of 580,757 participants in southern China were enrolled during 2009-2015 and followed up to 2020. The annual average concentration of PM1, PM2.5, and PM10 at 1 km2 spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels.
Results: 37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037-1.046), 1.031 (95 % CI: 1.028-1.033), and 1.029 (95 % CI: 1.027-1.031) per 1 μg/m3 increase in PM1, PM2.5, and PM10 concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM1, PM2.5, and PM10 tend to be higher in the low-exposure group than in the general population.
Conclusions: We provided comprehensive evidence for the potential causal links betweenlong-term PM exposureand all-cause mortality, and suggested stronger links for PM1compared to large particles and among certain vulnerable subgroups.
Keywords: All-cause mortality; Causal inference model; Long-term effect; Particulate matter.
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