The association between fine particulate matter and acute lower respiratory infections in Yancheng City, China

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Abstract
Due to the rapid economic development and acceleration of industrialization, most cities in China are experiencing severe air pollution. Exposure to fine particulate matter (PM2.5) has been associated with acute lower respiratory tract infection (ALRI). To estimate associations between short-term exposure to PM2.5 and ALRI hospitalization in Yancheng City, China. This was a 6-year time-series study from 2014 to 2019. Data on hospitalization were collected from four high-ranked general hospitals, including for community-acquired pneumonia (CAP), acute exacerbation of chronic bronchitis (AECB), acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and acute exacerbation of bronchiectasis (AEB), and the sum was termed total ALRIs. We obtained pollutant exposure data from five fixed monitoring stations. The association between PM2.5 and ALRI hospitalization was estimated using the generalized linear model with quasi-Poisson regression. Two-pollutant models were applied to test the robustness of the observed correlations. Subgroup analyses included sex, age, and season. During the study period, a total of 43,283 cases of total ALRIs were recorded. The average annual mean PM2.5 concentration was 45.4 ± 32.3 μg/m3. A 10-μg/m3 increase in PM2.5 concentration (lag 0) was significantly associated with increases in hospitalizations for total ALRIs (at 0.73%; 95% CI: 0.40%, 1.06%), in CAP (at 0.80%; 95% CI: 0.02%, 1.57%), in for AECOPD (1.08%; 95% CI: 0.38%, 1.78%), and AECB (0.67%; 95% CI: 0.23%, 1.11%). The estimated effects for total ALRIs and AECB were relatively robust with adjustment for other air pollutants. Associations between PM2.5 and total ALRIs were stronger in females, in the elderly, and in the cold season. PM2.5 exposure was significantly associated with ALRI morbidity, and females and older people were more susceptible to PM2.5 air pollution, especially in the cold season.

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