Health effect of multiple air pollutant mixture on sarcopenia among middle-aged and older adults in China.

BACKGROUND

As the global aging process accelerates, the health challenges posed by sarcopenia among middle-aged and older adults are becoming increasingly prominent. However, the available evidence on the adverse effects of air pollution on sarcopenia is limited, particularly in the Western Pacific region. This study aimed to explore relationships of multiple air pollutants with sarcopenia and related biomarkers using the nationally representative database.

METHODS

Totally, 6585 participants aged over 45 years were enrolled from the China Health and Retirement Longitudinal Study (CHARLS) in 2011 and 3443 of them were followed up until 2015. Air pollutants were estimated from high-resolution satellite-based spatial-temporal models. In the cross-sectional analysis, we used generalized linear regression, unconditional logistic regression analytical and restricted cubic spline (RCS) methods to assess the single-exposure and non-linear effects of multiple air pollutants on sarcopenia and related surrogate biomarkers (serum creatinine and cystatin C). Several popular mixture analysis techniques such as Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and quantile-based g-computation (Qgcomp) were further used to examinate the combined effects of multiple air pollutants. Logistic regression was used to further analyze the longitudinal association between air pollution and sarcopenia.

RESULTS

Each interquartile range increase in PM2.5, PM10 and NO2 was significantly associated with an increased risk of sarcopenia, with adjusted odds ratios (aORs) of 1.09 [95 % confidence interval (CI): 1.01, 1.20], 1.24 (95 % CI: 1.14, 1.35) and 1.18 (95 % CI: 1.08, 1.28), respectively. Our findings also showed that five air pollutants were significantly associated with the sarcopenia index. In addition, employing a mixture analysis approach, we confirmed significant combined effects of air pollution mixtures on sarcopenia risk and associated biomarkers, with PM10 and PM2.5 identified as major contributors to the combined effect. The results of the exposure-response (E-R) relationships, subgroup analysis, longitudinal analysis and sensitivity analysis all showed the unfavorable impact of air pollution on sarcopenia risk and related vulnerable populations.

CONCLUSIONS

Single-exposure and co-exposure to multiple air pollutants were positively associated with sarcopenia among middle-aged and older adults in China. Our study provided new evidence that air pollution mixture was significantly associated with sarcopenia related biomarkers.