Effects of fine particulate matter and its chemical constituents on influenza-like illness in Guangzhou, China.

BACKGROUND

Although the link between fine particulate matter (PM) and influenza-like illness (ILI) is well established, the effect of the chemical constituents of PM on ILI remains unclear. This study aims to explore this effect in Guangzhou, China.

METHODS

Daily data on ILI cases, PM levels, and specific PM constituents (black carbon [BC], chlorine [Cl], ammonia [NH], nitrate [NO], and sulfate [SO]) in Guangzhou, China, were collected for the period of 2014-2019. Additionally, data on gaseous pollutants and meteorological conditions were obtained. By using quasi-Poisson regression models, the association between exposure to PM and its constituents and ILI risk was estimated. Stratified subgroup analyses were performed by gender, age, and season to explore in depth the effects of these factors on disease risk.

RESULTS

Single-pollutant modeling results showed that an increase of one interquartile range (IQR) in Cl, SO, PM, NH, BC, and NO corresponded to relative risks of ILI of 1.046 (95 % CI: 1.004, 1.090) (lag03), 1.098 (95 % CI: 1.058, 1.139) (lag01), 1.091 (95 % CI: 1.054, 1.130) (lag02), 1.093 (95 % CI: 1.049, 1.138) (lag02), 1.111 (95 % CI: 1.074, 1.150) (lag03), and 1.103 (95 % CI: 1.061, 1.146) (lag03), respectively. Notably, the association between ILI and BC remained significant even after adjusting for PM mass. Subgroup analyses indicated that individuals aged 5-14 and 15-24 years may exhibit higher sensitivity to BC and Cl exposure than other individuals. Furthermore, stronger associations were observed during the cold season than during the warm season.

CONCLUSIONS

Results showed that the mass and constituents of PM were significantly correlated with ILI. Specifically, the carbonaceous fractions of PM were found to have a pronounced effect on ILI. These findings underscore the importance of implementing effective measures to reduce the emission of specific sources of PM constituents to mitigate the risk of ILI. Nevertheless, limitations such as potential exposure misclassification and regional constraints should be considered.