Abstract

Objective PM2.5, 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. Methods Mortality 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. Results From 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. Conclusions In 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.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call