Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach

• Published in: PloS one 2017-11, Vol.12 (11), p.e0187933-e0187933
• Main Authors: Fang, Xin, Fang, Bo, Wang, Chunfang, Xia, Tian, Bottai, Matteo, Fang, Fang, Cao, Yang
• Format: Article
• Language: English
• Subjects: Accidents; Adolescent; Adult; Age Factors; Aged; Aged, 80 and over; Air Pollutants - analysis; Air Pollutants - toxicity; Air pollution; Algorithms; Bayes Theorem; Bayesian analysis; Biology and Life Sciences; Child; China - epidemiology; Demographics; Earth Sciences; Engineering and Technology; Environmental Monitoring; Environmental policy; Epidemiology; Extreme weather; Fatalities; Female; Health aspects; Humans; Influence; Male; Medicin och hälsovetenskap; Meteorological data; Middle Aged; Mortality; Outdoor air quality; Parameter estimation; Particle Size; Particulate matter; Particulate Matter - analysis; Particulate Matter - toxicity; Particulate pollutants; Particulates; Patient outcomes; People and Places; Physical Sciences; Sensitivity analysis; Statistical analysis; Studies; Weather; Weather conditions; Weather effects; Weather extremes; Weather types; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0187933

There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, China. Days with extreme weather conditions were identified. Six synoptic weather types (SWTs) were generated. The generalized additive model was set up to link the mortality with PM2.5 and weather conditions. Parameter estimation was based on Bayesian methods using both the Jeffreys' prior and an informative normal prior in a sensitivity analysis. We estimate the percent increase in non-accidental mortality per 10 μg/m3 increase in PM2.5 concentration and constructed corresponding 95% credible interval (CrI). In total, 336,379 non-accidental deaths occurred during the study period. Average daily deaths were 307. The results indicated that per 10 μg/m3 increase in daily average PM2.5 concentration alone corresponded to 0.26-0.35% increase in daily non-accidental mortality in Shanghai. Statistically significant positive associations between PM2.5 and mortality were found for favorable SWTs when considering the interaction between PM2.5 and SWTs. The greatest effect was found in hot dry SWT (percent increase = 1.28, 95% CrI: 0.72, 1.83), followed by warm humid SWT (percent increase = 0.64, 95% CrI: 0.15, 1.13). The effect of PM2.5 on non-accidental mortality differed under specific extreme weather conditions and SWTs. Environmental policies and actions should take into account the interrelationship between the two hazardous exposures.