Interactive associations of atmospheric humidity and air pollutants with self-reported chronic lung disease risk: Evidence from a nationwide population-based study in China.

Abstract

To evaluate the associations of multidimensional atmospheric humidity indicators and air pollution with self-reported chronic lung disease (CLD) among middle-aged and older adults in China.

Methods: Data from 16,204 adults aged ≥45 years from the 2011, 2013, and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Annual exposures to six air pollutants (CO, NO₂, O₃, PM₂.₅, PM₁。, SO₂) and six humidity indicators (RH, AVP, VPD, DPT, MR, SH) were estimated at 1-km resolution. Multivariable logistic regression and restricted cubic spline models were applied. Stratified and sensitivity analyses were conducted.

Results: Higher concentrations of CO, NO₂, O₃, PM₂.₅, and SO₂ were linearly associated with increased self-reported CLD risk, while PM₁。 showed an approximate U-shaped relationship. Each interquartile-range increase in air pollutant concentrations was associated with an 18-45% higher odds of self-reported CLD. AVP, VPD, DPT, MR, and SH were positively associated with self-reported CLD risk, whereas RH exhibited an inverted U-shaped pattern. Weighted quantile sum analyses showed significant positive associations for both air pollution and humidity mixtures. A significant interaction between RH and sex was observed. Sensitivity analyses across different lag structures confirmed that air pollutants and atmospheric humidity were consistently associated with self-reported CLD risk.

Conclusions: Long-term exposure to ambient air pollution and multidimensional humidity indicators was independently associated with higher self-reported CLD risk, highlighting the importance of considering meteorological factors in disease prevention.