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

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.

Associations between short-term exposure to fine particulate matter and acute exacerbation of asthma in Yancheng, China.

Scarce evidence existed on the association between short-term exposure to fine particulate matter (PM2.5) and asthma in China. In this study, we aimed to explore the relationship of PM2.5 with acute asthma exacerbation in a coastal city of China. Cases of acute asthma exacerbation were identified from hospital outpatient visits in Yancheng, China, from 2015 to 2018. We utilized the generalized additive model linked by a quasi-Poisson distribution to assess the association between PM2.5 and daily acute asthma exacerbation. Different lag structures were built, and we conducted stratification analyses by gender, age, and season. Two-pollutant models were fitted, and concentration-response (C-R) curves were pooled. A total of 3,520 cases of acute asthma exacerbation were recorded, with a daily average of 3. We observed positive and significant associations of PM2.5 on lag 1, 2, lag 02, and lag 03 day. For each 10-µg/m3 increase in PM2.5 (lag 02), the associated increment in asthma was 3.15% (95% CI: 0.99%, 5.31%). The association remained after adjusting for gaseous co-pollutants. We observed significant PM2.5-asthma associations in males, patients ≤64 years, and during cold seasons. The C-R curves were positive and almost linear for total and strata-specific associations. In conclusion, this study provided robust evidence on the association of PM2.5 with acute asthma exacerbation, which may benefit future prevention strategy and policy making.

Association of fine particulate matter on acute exacerbation of chronic obstructive pulmonary disease in Yancheng, China.

BACKGROUND: Epidemiological evidence on the association between short-term exposure to fine particulate matter (PM2.5) air pollution and acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is limited in China. OBJECTIVES: To explore the associations between PM2.5 and AECOPD in Yancheng, China from 2015 to 2017. METHODS: In this time-series study, we used a generalized linear model with quasi-Poisson regression to investigate the association between PM2.5 and AECOPD admitted in two major hospitals in Yancheng. We tested the robustness of the associations using two-pollutant models and examined the potential effect modification by age, gender and season via stratification analyses. Lastly, we fitted the concentration-response curves. RESULTS: We identified a total of 4761 AECOPD inpatients during the study period. The average daily-mean PM2.5 concentration was 45.2 µg/m3. Each 10 µg/m3 increase in PM2.5 concentration on the concurrent day of the onset of AECOPD was associated with a 1.05% (95% confidence interval: 0.14%, 1.96%) increase in AECOPD. The association was robust to the adjustment of ozone, but not to sulfur dioxide, nitrogen dioxide, and carbon monoxide. The association was larger in females, elderly patients, and was restricted within the cold season, but all between-group differences were insignificant. The concentration-response relationship curves were generally linear but flatted at concentrations over 40 µg/m3. CONCLUSIONS: This study demonstrated a higher risk of AECOPD associated with present-day PM2.5 exposure in a Chinese city. We further provided important information on lag patterns, susceptible subgroups, sensitive seasons, as well as the characteristics of the concentration-response relationship curves.

Association between ambient particulate matter air pollution and ST-elevation myocardial infarction: A case-crossover study in a Chinese city.

BACKGROUND: Abundant epidemiological studies have revealed that short-term exposure to ambient air pollution increased the incidence of ischemic heart diseases. However, few investigations have explored the association between air pollution and ST-elevation myocardial infarction (STEMI), one major subtype of such events. METHODS: We conducted a time-stratified case-crossover study in two major hospitals of Yancheng, a city in East China, from January 2015 to February 2018. We used conditional logistic regression models to explore the association between hourly concentrations of air pollutants and STEMI hospitalizations. We explored potential effect modification in susceptible subgroups by age, gender, smoking status, and comorbidities. Two-pollutant models were fitted to test the robustness of the association. RESULTS: We identified a total of 347 STEMI patients. In single-pollutant models, each 10 µg/m3 increase in concentrations of fine and inhalable particulate matter (PM) (lag 13-24 h) was associated with increments of 5.27% [95% confidence interval (CI): 1.09%, 9.46%] and 3.86% (95%CI: 0.83%, 6.88%) in STEMI hospitalizations, respectively. We observed slightly larger associations of STEMI hospitalization with PM in patients who were older than 65, female, non-smoker, and with comorbidities (hypertension, diabetes or hyperlipidemia). The associations were generally robust to adjustment of criteria gaseous pollutants except for carbon monoxide. CONCLUSION: This is the first study in China that suggested acute exposure to elevated PM concentrations may trigger STEMI. Patients with cardiometabolic comorbidities were slightly more susceptible to air pollution.

Acute effects of ambient temperature and particulate air pollution on fractional exhaled nitric oxide: A panel study among diabetic patients in Shanghai, China.

BACKGROUND: Epidemiological studies have shown the associations of ambient temperature and particulate matter (PM) air pollution with respiratory morbidity and mortality. However, the underlying mechanisms have not been well characterized. The aim of this study is to investigate the associations of temperature and fine and coarse PM with fractional exhaled nitric oxide (FeNO), a well-established biomarker of respiratory inflammation. METHODS: We conducted a longitudinal panel study involving six repeated FeNO tests among 33 type 2 diabetes mellitus patients from April to June 2013 in Shanghai, China. Hourly temperature and PM concentrations were obtained from a nearby fixed-site monitoring station. We then explored the associations between temperature, PM, and FeNO using linear mixed-effect models incorporated with distributed lag nonlinear models for the lagged and nonlinear associations. The interactions between temperature and PM were evaluated using stratification analyses. RESULTS: We found that both low and high temperature, as well as increased fine and coarse PM, were significantly associated with FeNO. The cumulative relative risk of FeNO was 1.75% (95% confidence interval [CI], 1.04-2.94) comparing 15 °C to the referent temperature (24 °C) over lags 0-9 days. A 10 µg/m3 increase in fine and coarse PM concentrations were associated with 1.18% (95% CI, 0.18-2.20) and 1.85% (95% CI, 0.62-3.09) FeNO in lag 0-1 days, respectively. PM had stronger effects on cool days than on warm days. CONCLUSIONS: This study suggested low ambient temperature, fine PM, and coarse PM might elevate the levels of respiratory inflammation. Our findings may help understand the epidemiological evidence linking temperature, particulate air pollution, and respiratory health.