Background Ambient fine particulate matter (PM2.5) pollution is currently a serious environmental problem in China, but evidence of health effects with higher resolution and spatial coverage is insufficient. Objective This study aims to provide a better overall understanding of long-term mortality effects of PM2.5 pollution in China and a county-level spatial map for estimating PM2.5 related premature deaths of the entire country. Method Using four sets of satellite-derived PM2.5 concentration data and the integrated exposure-response model which has been employed by the Global Burden of Disease (GBD) to estimate global mortality of ambient and household air pollution in 2010, we estimated PM2.5 related premature mortality for five endpoints across China in 2010. Result Premature deaths attributed to PM2.5 nationwide amounted to 1.27 million in total, and 119,167, 83,976, 390,266, 670,906 for adult chronic obstructive pulmonary disease, lung cancer, ischemic heart disease, and stroke, respectively; 3995 deaths for acute lower respiratory infections were estimated in children under the age of 5. About half of the premature deaths were from counties with annual average PM2.5 concentrations above 63.61 μg/m3, which cover 16.97% of the Chinese territory. These counties were largely located in the Beijing-Tianjin-Hebei region and the North China Plain. High population density and high pollution areas exhibited the highest health risks attributed to air pollution. On a per capita basis, the highest values were mostly located in heavily polluted industrial regions. Conclusion PM2.5-attributable health risk is closely associated with high population density and high levels of pollution in China. Further estimates using long-term historical exposure data and concentration-response (C-R) relationships should be completed in the future to investigate longer-term trends in the effects of PM2.5.
Studies worldwide have estimated the number of deaths attributable to long-term exposure to fine airborne particles (PM 2.5 ), but limited information is available on short-term exposure, particularly in China. In addition, most existing studies have assumed that short-term PM 2.5 -mortality associations were linear. For this reason, the use of linear exposure-response functions for calculating disease burden of short-term exposure to PM 2.5 in China may not be appropriate. There is an urgent need for a comprehensive, evidence-based assessment of the disease burden related to short-term PM 2.5 exposure in China. Here, we explored the non-linear association between short-term PM 2.5 exposure and all-cause mortality in 104 counties in China; estimated county-specific mortality burdens attributable to short-term PM 2.5 exposure for all counties in the country and analyzed spatial characteristics of the mortality burden due to short-term PM 2.5 exposure in China. The pooled PM 2.5 -mortality association was non-linear, with a reversed J-shape. We found an approximately linear increased risk of mortality from 0 to 62 μg/m 3 and decreased risk from 62 to 250 μg/m 3 . We estimated a total of 169,862 additional deaths from short-term PM 2.5 exposure throughout China in 2015. Models using linear exposure-response functions for the PM 2.5 -mortality association estimated 32,186 deaths attributable to PM 2.5 exposure, which is 5.3 times lower than estimates from the non-linear effect model. Short-term PM 2.5 exposure contributed greatly to the death burden in China, approximately one seventh of the estimates from the chronic effect. It is essential and crucial to incorporate short-term PM 2.5 -related mortality estimations when considering the disease burden attributable to PM 2.5 in developing countries such as China. Traditional linear effect models likely underestimated the mortality burden due to short-term exposure to PM 2.5 .
Although existing studies have linked high temperature to mortality in a small number of regions, less evidence is available on the variation in the associations between high temperature exposure and cause-specific mortality of multiple regions in China. Our study focused on the use of time series analysis to quantify the association between high temperature and different cause-specific mortalities for susceptible populations for 43 counties in China. Two-stage analyses adopting a distributed lag non-linear model (DLNM) and a meta-analysis allowed us to obtain county-specific estimates and national-scale pooled estimates of the nonlinear temperature-mortality relationship. We also considered different populations stratified by age and sex, causes of death, absolute and relative temperature patterns, and potential confounding from air pollutants. All of the observed cause-specific mortalities are significantly associated with higher temperature. The estimated effects of high temperature on mortality varied by spatial distribution and temperature patterns. Compared with the 90th percentile temperature, the overall relative risk (RR) at the 99th percentile temperature for non-accidental mortality is 1.105 (95%CI: 1.089, 1.122), for circulatory disease is 1.107 (95%CI: 1.081, 1.133), for respiratory disease is 1.095 (95%CI: 1.050, 1.142), for coronary heart disease is 1.073 (95%CI: 1.047, 1.099), for acute myocardial infarction is 1.072 (95%CI: 1.042, 1.104), and for stroke is 1.095 (95%CI: 1.052, 1.138). Based on our findings, we believe that heat-related health effect in China is a significant issue that requires more attention and allocation of existing resources.
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