Studies worldwide have estimated the number of deaths attributable to long-term exposure to fine airborne particles (PM2.5), but limited information is available on short-term exposure, particularly in China. In addition, most existing studies have assumed that short-term PM2.5-mortality associations were linear. For this reason, the use of linear exposure-response functions for calculating disease burden of short-term exposure to PM2.5 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 PM2.5 exposure in China. Here, we explored the non-linear association between short-term PM2.5 exposure and all-cause mortality in 104 counties in China; estimated county-specific mortality burdens attributable to short-term PM2.5 exposure for all counties in the country and analyzed spatial characteristics of the mortality burden due to short-term PM2.5 exposure in China. The pooled PM2.5-mortality association was non-linear, with a reversed J-shape. We found an approximately linear increased risk of mortality from 0 to 62 μg/m3 and decreased risk from 62 to 250 μg/m3. We estimated a total of 169,862 additional deaths from short-term PM2.5 exposure throughout China in 2015. Models using linear exposure-response functions for the PM2.5-mortality association estimated 32,186 deaths attributable to PM2.5 exposure, which is 5.3 times lower than estimates from the non-linear effect model. Short-term PM2.5 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 PM2.5-related mortality estimations when considering the disease burden attributable to PM2.5 in developing countries such as China. Traditional linear effect models likely underestimated the mortality burden due to short-term exposure to PM2.5.
Keywords: mortality burden, non-linear, PM2.5, short-ter
