Lung cancer mortality associated with PM2.5 in China: a national study based on county level

Abstract

Background: The relative risk (RR) of PM2.5 in lung cancer mortality (LCM) may vary spatially in China. However, previous studies applying global regression model have been unable to capture such variation. The research aimed to employ a geographically weighted Poisson regression (GWPR) model to estimate the county-specific RRs of LCM among the elderly (≥65 years) related to PM2.5 and predict LCM in China.Methods: We obtained LCM data between 2013 and 2015 from the Chinese National Death Surveillance. We linked annual mean concentrations of PM2.5 between 2000 and 2004 with LCM using GWPR model at the county level, after adjusting for smoking and socioeconomic covariates. County-specific coefficients from GWPR were used to predict LCM under different scenarios of PM2.5 concentration according to the WHO Air Quality Guidelines. Results: The magnitude of the association between PM2.5 and LCM varied with county. The medians of county-specific RRs of LCM among elderly men and women were 1.52 (range: 0.90, 2.40) and 1.49 (range: 0.88, 2.56) for each 10μg/m3 increment in PM2.5, respectively. Higher RRs of PM2.5 among elderly men were located at Southwest and South China, and higher RRs among elderly women were located at Northwest, Southwest, and South China. Our research estimated that around 411,201 (men: 269,389; women: 141,812) LCM among the elderly would be avoided in 2034, if PM2.5 concentration met the WHO guideline (10μg/m3). Conclusions: The relative importance of PM2.5 in LCM differed by county. The results could help the government design tailored and efficient interventions. Stringent PM2.5 control is urgently needed to reduce LCM in China.