Beyond additive effects: examining the combined impact of air pollutant interactions on pulmonary tuberculosis in China.

BACKGROUND

Various ambient air pollutants within a mixture may interact with each other and amplify or reduce the cumulative effects of individual air pollutants on health outcomes. However, health-related studies on the interactive effects of air pollutant mixtures remain limited. Additionally, the influence of greenness on health outcomes in the context of air pollutant mixtures has seldom been explored.

OBJECTIVE

To develop a joint analysis framework that focuses on the interactive effects among pollutants to evaluate the combined effects of ambient air pollutant mixtures on pulmonary tuberculosis (PTB) risks, taking into account greenness as a moderating factor.

METHODS

In this case-control study conducted in Lanxi, China, 1128 newly diagnosed PTB cases from 2019 to 2021 were matched with 2256 controls by sex and age. To evaluate exposure, the 24-month average values of particulate matter with aerodynamic diameters of ≤ 2.5 µm (PM2.5), sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and the Normalized Difference Vegetation Index before diagnosis or study entry were assessed using a high-resolution dataset. A quantile-based g-computation model was then used to estimate the additive and interactive effects of air pollutants on PTB risks and identify the moderating influence of greenness on these relationships.

RESULTS

Additive effect models showed that a one quartile increase in exposure to the air pollutant mixture was associated with elevated PTB risks (mixture odds ratio: 1.17, 95% confidence intervals: 1.07, 1.36), with NO2 contributing the most significant positive effect. Interactive effect models showed that incorporating interaction terms for O3 and other pollutants resulted in PTB risks that exceeded those estimated using the additive effects of various pollutants. Furthermore, areas with higher levels of greenness exhibited lower PTB risks associated with air pollutant mixture than areas with lower levels of greenness.

CONCLUSIONS

To reduce biases in air pollution control policies and maximize their health benefits, it is essential to assess both the additive and interactive effects when evaluating the health impacts of air pollutant mixtures. Furthermore, the influence of greenness should be considered in the context of these air pollutant mixtures.