TY - JOUR
T1 - Estimating mortality burden attributable to short-term PM
2.5
exposure
T2 - A national observational study in China
AU - Li, Tiantian
AU - Guo, Yuming
AU - Liu, Yang
AU - Wang, Jiaonan
AU - Wang, Qing
AU - Sun, Zhiying
AU - He, Mike Z.
AU - Shi, Xiaoming
PY - 2019/4/1
Y1 - 2019/4/1
N2 -
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
.
AB -
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
.
KW - Mortality burden
KW - Non-linear
KW - PM
KW - Short-term
UR - http://www.scopus.com/inward/record.url?scp=85060945063&partnerID=8YFLogxK
U2 - 10.1016/j.envint.2019.01.073
DO - 10.1016/j.envint.2019.01.073
M3 - Article
C2 - 30731374
AN - SCOPUS:85060945063
SN - 0160-4120
SP - 245
EP - 251
JO - Environment International
JF - Environment International
ER -