SEASONAL PATTERN OF THE ACUTE MORTALITY EFFECTS OF AIR POLLUTION

Abstract:

Several studies have been published on seasonal variation of acute mortality effects of air pollution and the reported findings are inconsistent. The purpose of the study is to examine seasonal pattern of the associations between daily mortality and daily mean concentrations of particulate matter ≤ 10 μm (PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2) using four years of data (2001-2004) in Wuhan, China. Four distinct seasons occur in Wuhan, where approximately 4.5 million residents live in the city core area of 201 km2. Air pollution levels are higher and pollution ranges are wider than most cities. We use the statistical model of quasi-likelihood estimation within the context of the Generalized Additive Models (natural spline models in R) to model the natural logarithm of the expected daily death counts as a function of the predictor variables. The estimates of the interaction between season and pollution were obtained from the main effects and pollutant season interaction models. We found the interactions between three pollutants and cause-specific mortality were statistically significant (p < 0.05). The strongest effects occurred consistently in winters for all natural, cardiovascular, stroke, and respiratory mortality. Every 10-g/m3 increase in PM10 daily concentration at lag 0-1 day was associated with an increase in all natural mortality of 0.69% (95% CI: 0.44% - 0.94%), 0.34% (95% CI: 0.00-0.69%), 0.45% (95% CI: -0.13%-1.04%), and -0.21% (95% CI:-0.54%-0.12%) for winter, spring, summer, and fall, respectively. The results show clear seasonal pattern of the positive association between daily pollutants’ concentrations and daily mortality and the strongest effects modification occurred in winters.