County-level variation in the long-term association between PM2.5 and lung cancer mortality in China

Abstract

IntroductionThe relative risk (RR) of long-term exposure to PM2.5 in lung cancer mortality (LCM) may vary spatially in China. However, previous studies applying global regression have been unable to capture such variation. We aimed to employ a geographically weighted Poisson regression (GWPR) to estimate the RRs of LCM among the elderly (≥65 years) related to long-term exposure to PM2.5 and the LCM attributable to PM2.5 at the county level in China. MethodsWe obtained annual LCM in the elderly between 2013 and 2015 from the National Death Surveillance. We linked annual mean concentrations of PM2.5 between 2000 and 2004 with LCM using GWPR model at 148 counties across mainland China, adjusting for smoking and socioeconomic covariates. We used county-specific GWPR models to estimate annual average LCM in the elderly between 2013 and 2015 attributable to PM2.5 exposure between 2000 and 2004. ResultsThe magnitude of the association between long-term exposure to PM2.5 and LCM varied with county. The median of county-specific RRs of LCM among elderly men and women was 1.52 (range: 0.90, 2.40) and 1.49 (range: 0.88, 2.56) for each 10 μg/m3 increment in PM2.5, respectively. The RRs were positively significant (P < 0.05) at 95% (140/148) of counties among both elderly men and women. 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. There were 99,967 and 54,457 lung cancer deaths among elderly men and women that could be attributed to PM2.5, with the attributable fractions of 31.4% and 33.8%, respectively. ConclusionsThe relative importance of long-term exposure to PM2.5 in LCM differed by county. The results could help the government design tailored and efficient interventions. More stringent PM2.5 control is urgently needed to reduce LCM in China.