Combined effects of long‑term air pollution exposures on adult active asthma: a quantile g-computation analysis

Abstract

Air pollution is a well‑established risk factor for the development of asthma, yet most studies examine pollutants individually, failing to capture the health effects of real‑world pollutant mixtures. Assessing long-term multipollutant exposure is essential for understanding asthma development. To estimate the overall effects of joint exposure to multiple air pollutants on active asthma in adulthood, among individuals free of active asthma at earlier assessments, using quantile g-computation (qgcomp). We analyzed 5,299 adults from the Respiratory Health in Northern Europe (RHINE) cohort who were asthma-free between 1990 and 2010. Active asthma was defined at the 2020 follow-up as asthma attacks and/or medication use in the past 12 months. Residential exposures to PM 2.5 , NO 2 , and O 3 were modelled for 1990, 2000, and 2010. All nine exposure-timepoint combinations were included in a single qgcomp model, adjusted for age, sex, BMI, smoking, education, and study center. In 2020, 312 participants (5.9%) had active asthma. A simultaneous one-quartile increase across all nine pollutant timepoint components was associated with higher odds of active asthma (OR 2.24, 95% CI 1.33–3.78). NO 2 and O 3 received the largest and most stable positive weights within the mixture model, particularly at the 2000 exposure wave. Sensitivity analyses showed consistent positive associations for 1990 and 2000 exposure mixtures, while estimates for 2010 were attenuated. Long-term exposure to multiple air pollutants in adulthood was associated with higher odds of active asthma by the 2020 assessment. Quantile g-computation is a valuable framework for assessing environmental mixtures and supports the need for multipollutant approaches in prevention.