Ambient particulate matter (PM) pollution has been linked to elevated mortality, especially from cardiovascular diseases. However, evidence on the effects of particulate matter pollution on cardiovascular mortality is still limited in Lanzhou, China. This research aimed to examine the associations of daily mean concentrations of ambient air pollutants (PM2.5, PMC, and PM10) and cardiovascular mortality due to overall and cause-specific diseases in Lanzhou. Data representing daily cardiovascular mortality rates, meteorological factors (daily average temperature, daily average humidity, and atmospheric pressure), and air pollutants (PM2.5, PM10, SO2, NO2) were collected from January 1, 2014, to December 31, 2017, in Lanzhou. A quasi-Poisson regression model combined with a distributed lag non-linear model (DLNM) was used to estimate the associations. Stratified analyses were also performed by different cause-specific diseases, including cerebrovascular disease (CD), ischemic heart disease (IHD), heart rhythm disturbances (HRD), and heart failure (HF). The results showed that elevated concentration of PM2.5, PMC, and PM10 had different effects on mortality of different cardiovascular diseases. Only cerebrovascular disease showed a significant positive association with elevated PM2.5. Positive associations were identified between PMC and daily mortality rates from total cardiovascular diseases, cerebrovascular diseases, and ischemic heart diseases. Besides, increased concentration of PM10 was correlated with increased death of cerebrovascular diseases and ischemic heart diseases. For cerebrovascular disease, each 10 μg/m3 increase in PM2.5 at lag4 was associated with increments of 1.22% (95% CI 0.11–2.35%). The largest significant effects for PMC on cardiovascular diseases and ischemic heart diseases were both observed at lag0, and a 10 μg/m3 increment in concentration of PMC was associated with 0.47% (95% CI 0.06–0.88%) and 0.85% (95% CI 0.18–1.52%) increases in cardiovascular mortality and ischemic heart diseases. In addition, it exhibited a lag effect on cerebrovascular mortality as well, which was most significant at lag6d, and an increase of 10 μg/m3 in PMC was associated with a 0.76% (95% CI 0.16–1.37%) increase in cerebrovascular mortality. The estimates of percentage change in daily mortality rates per 10 μg/m3 increase in PM10 were 0.52% (95% CI 0.05–1.02%) for cerebrovascular disease at lag6 and 0.53% (95% CI 0.01–1.05%) for ischemic heart disease at lag0, respectively. Our study suggests that elevated concentration of atmospheric PM (PM2.5, PMC, and PM10) in Lanzhou is associated with increased mortality of cardiovascular diseases and that the health effect of elevated concentration of PM2.5 is more significant than that of PMC and PM10.
相似文献The global prevalence of gestational diabetes mellitus (GDM) is increasing annually, and previous research reports on the relationship between exposure to air pollutants and GDM are not completely consistent. We investigated the association between air pollutant exposure and GDM in pregnant women in a retrospective cohort study in Guangzhou. We found that in the first trimester, exposure to PM2.5 and CO showed a significant association with GDM. In the second trimester, exposure to PM10 was significantly associated with GDM. In the third trimester, exposure to PM2.5, PM10, NO2, SO2, and CO at IQR4 (odds ratio [OR]?=?1.271, 95% confidence interval [CI]: 1.179–1.370; OR?=?1.283, 95% CI: 1.191–1.383; OR?=?1.230, 95% CI: 1.145–1.322; OR?=?1.408, 95% CI: 1.303–1.522; OR?=?1.150, 95% CI: 1.067–1.240, respectively) compared with IQR1 was positively associated with GDM. However, exposure to NO2 was negatively associated with GDM in the first and second trimesters, and O3 was negatively associated with GDM in the second and third trimesters. We found that the correlation between air pollutants and GDM in different trimesters of pregnancy was not completely consistent in this retrospective cohort study. During pregnancy, there may be an interaction between air pollutant exposure and other factors, such as pregnant women’s age, occupation, anemia status, pregnancy-induced hypertension status, and pregnancy season.
相似文献The COVID-19 pandemic has a close relationship with local environmental conditions. This study explores the effects of climate characteristics and air pollution on COVID-19 in Isfahan province, Iran. A number of COVID-19 positive cases, main air pollutants, air quality index (AQI), and climatic variables were received from March 1, 2020, to January 19, 2021. Moreover, CO, NO2, and O3 tropospheric levels were collected using Sentinel-5P satellite data. The spatial distribution of variables was estimated by the ordinary Kriging and inverse weighted distance (IDW) models. A generalized linear model (GLM) was used to analyze the relationship between environmental variables and COVID-19. The seasonal trend of nitrogen dioxide (NO2), wind speed, solar energy, and rainfall like COVID-19 was upward in spring and summer. The high and low temperatures increased from April to August. All variables had a spatial autocorrelation and clustered pattern except AQI. Furthermore, COVID-19 showed a significant association with month, climate, solar energy, and NO2. Suitable policy implications are recommended to be performed for improving people’s healthcare and control of the COVID-19 pandemic. This study could survey the local spread of COVID-19, with consideration of the effect of environmental variables, and provides helpful information to health ministry decisions for mitigating harmful effects of environmental change. By means of the proposed approach, probably the COVID-19 spread can be recognized by knowing the regional climate in major cities. The present study also finds that COVID-19 may have an effect on climatic condition and air pollutants.
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