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Estimating mortality burden attributable to short-term PM_2.5 exposure: A national observational study in China.

ABSTRACT: 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/m³ and decreased risk from 62 to 250 μg/m³. 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.

SUBMITTER: Li T

PROVIDER: S-EPMC6548716 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivePM2.5, which is a major contributor to air pollution, has large effects on lung cancer mortality. We want to analyse the long-term trends in lung cancer burden attributable to PM2.5 exposure and provide evidence that can be used for preventive measures and health resource planning.MethodsMortality data related to lung cancer were obtained from the Global Burden of Disease (GBD) 2019 project. A joinpoint regression analysis was used to assess the magnitude and direction of the trends in mortality from 1990 to 2019, and the age-period-cohort method was used to analyse the temporal trends in the mortality rate of lung cancer attributable to PM2.5 exposure by age, period, and cohort.ResultsFrom 1990 to 2019, the age-standardized mortality rate (ASMR) attributable to PM2.5 exposure trended slowly upwards, and the ASMR due to ambient PM2.5 exposure (APE) increased significantly, that due to household PM2.5 exposure (HPE) decreased. The longitudinal age curves show that the mortality rates due to PM2.5 exposure among younger individuals were low, and they significantly increased from their levels among those in the 45-49 age group to their levels among those in the over-85 age group. From 1990 to 2019, the period RRs due to APE increased, but those due to HPE decreased. Similar trends were observed in the cohort RRs. The overall net drift per year attributable to PM2.5 exposure was below 0. The local drift values increased with age and were above 0 for the over-80 age groups. The overall net drifts per year were above zero for APE and below zero for HPE. The corresponding results among males were higher than those among females.ConclusionsIn China, the type of air pollution responsible for lung cancer has changed from household air pollution to ambient air pollution. PM2.5 exposure is more harmful among males and older people. Ambient air pollution should be emphasized, and China should strengthen its implementation of effective public policies and other interventions.

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Estimating mortality burden attributable to short-term PM_2.5 exposure: A national observational study in China.

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OmicsDI is part of the ELIXIR infrastructure

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Dataset Information

Estimating mortality burden attributable to short-term PM2.5 exposure: A national observational study in China.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Estimating mortality burden attributable to short-term PM_2.5 exposure: A national observational study in China.