Abstract
The attributable burden is codetermined by the exposure level and nontarget characteristics. However, the conventional method of health impact assessment based on preestablished exposure-response functions includes only a few well-known characteristics and thus is insufficient to capture the comprehensive variation. We aimed to develop a method to fuse health impact assessment with epidemiological analysis and to identify factors driving baseline risk. The method was applied to identify the factors underlying the change in the number of fine particulate matter (PM(2.5)) related deaths in China between 2000 and 2010. During the study period, the number of PM(2.5)-related deaths across mainland China increased by 0.62 (95% CI: 0.57, 0.69) million, with 0.65 (95% CI: 0.47, 0.91) million, 0.55 (95% CI: 0.39, 0.79) million, and 0.11 (95% CI: 0.06, 0.18) million deaths being associated with increased PM(2.5) exposure, population aging, and growth in population size, respectively. However, economic growth, urbanization, improvement of welfare services, and improvement of hospital services resulted in 0.25 (95% CI: 0.15, 0.40) million, 0.16 (95% CI: 0.10, 0.27) million, 0.16 (95% CI: 0.09, 0.26) million, and 0.09 (95% CI: 0.05, 0.15) million fewer deaths, respectively. Results indicated that increased exposure was the major driver of the change in the number of PM(2.5)-related deaths, and economic growth was the main driver of increased resilience to air pollution.