Combined health effects of air pollutant mixtures on respiratory mortality using BKMR in Hangzhou, China.

Abstract

Previous research on respiratory system mortality primarily focused on understanding their combined effects and have neglected the fact that air pollution mixtures are interrelated. This study used Bayesian kernel machine regression (BKMR) to analyze the relationship between air pollutant mixtures and respiratory mortality in Hangzhou, China from 2014 to 2018. The results showed a significant association between pollutant mixtures and respiratory system mortality primarily driven by PM_2.5 and SO₂. The joint exposure of air pollutants was positively correlated with respiratory system mortality at lag 01 and lag 02 days. The estimated joint effects of log-transformed mixture air pollution exposure on log-transformed respiratory system mortality increased from -0.02 (95% CI: -0.08-0.02) and -0.01 (95% CI: -0.05-0.04) at the 25th percentile to 0.06 (95% CI: 0.01-0.12) and 0.04 (95% CI: -0.001, 0.09) at the 75th percentile. Additionally, there was evidence of an interaction between O₃ and PM₁₀. This study confirms that exposure to multiple pollutants is a significant public health problem facing the Hangzhou population given the compounded effect proven with regression analysis, while furthermore, the control of PM_2.5 and SO₂ also represents a serious concern.Implications: Evidence indicates interactions between O₃ and PM₁₀. This study demonstrates that exposure to multiple pollutants exerts combined effects on the public health of the Hangzhou population, highlighting the importance of controlling PM_2.5 and SO₂.