Background: Exposures to both ambient fine particulate matter (PM
2.5) and extreme weather conditions have been associated with cardiovascular disease (CVD) deaths in numerous epidemiologic studies. However, evidence on the associations with CVD deaths for interaction effects between PM
2.5 and weather conditions is still limited. This study aimed to investigate associations of exposures to PM
2.5 and weather conditions with cardiovascular mortality, and further to investigate the synergistic or antagonistic effects of ambient air pollutants and synoptic weather types (SWTs).
Methods: Information on daily CVD deaths, air pollution, and meteorological conditions between 1 January 2012 and 31 December 2014 was obtained in Shanghai, China. Generalized additive models were used to assess the associations of daily PM
2.5 concentrations and meteorological factors with CVD deaths. A 15-day lag analysis was conducted using a polynomial distributed lag model to access the lag patterns for associations with PM
2.5.
Results: During the study period, the total number of CVD deaths in Shanghai was 59,486, with a daily mean of 54.3 deaths. The average daily PM
2.5 concentration was 55.0 µg/m
3. Each 10 µg/m
3 increase in PM
2.5 concentration was associated with a 1.26% (95% confidence interval (CI): 0.40%, 2.12%) increase in CVD mortality. No SWT was statistically significantly associated with CVD deaths. For the interaction between PM
2.5 and SWT, statistically significant interactions were found between PM
2.5 and cold weather, with risk for PM
2.5 in cold dry SWT decreasing by 1.47% (95% CI: 0.54%, 2.39%), and in cold humid SWT the risk decreased by 1.45% (95% CI: 0.52%, 2.36%). In the lag effect analysis, statistically significant positive associations were found for PM
2.5 in the 1–3 lag days, while no statistically significant effects were found for other lag day periods.
Conclusions: Exposure to PM
2.5 was associated with short-term increased risk of cardiovascular deaths with some lag effects, while the cold weather may have an antagonistic effect with PM
2.5. However, the ecological study design limited the possibility to identify a causal relationship, so prospective studies with individual level data are warranted.
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