A study on the short-term impact of fine particulate matter pollution on the incidence of cardiovascular diseases in Beijing, China

Ma, Yanhui; Yang, Sixu; Yu, Zhiang; Jiao, Haoran; Zhang, Yifan; Ma, Bingji

doi:10.1016/j.atmosenv.2019.116889

Cited by 23 publications

(9 citation statements)

References 40 publications

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“…The increase of the concentration of PM2.5, correlated with the risk of CCD in people over 65 years old, and the study also found that under the influence of PM2.5, the maximum lag effect appeared earlier in people over 65 years old. Similar to the results of this study, Ma Yuxia et al studied the relationship between PM2.5 and CVD in Beijing and found that the lag effect was the shortest in the 60-75-year-old subgroup [41]. Compared with young people, elderly people have poorer physical fitness and more basic diseases, so people over 65 years old are more likely to be affected by the environment, and the maximum lag effect appears faster.…”

Section: Discussionsupporting

confidence: 85%

“…In terms of the maximum lag effect in this study, NO2 was the most harmful pollutant, and the estimated value of the effect of outpatient visits in males was generally greater than that in females. Ma Yuxia et al's study [41] on the relationship between PM2.5 and CVD in Beijing found that there are more women than men with ischemic heart disease or hypertension caused by the increase of PM2.5 concentration. However, the incidence of arrhythmia in men was usually higher than that in women.…”

Section: Discussionmentioning

confidence: 99%

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Air Pollution and Outpatient Visits for Cardiovascular and Cerebrovascular Diseases: A Time-Series Analysis in Luoyang, China

Guo

Wang

Wei

et al. 2021

Preprint

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Background: Previous studies have shown that air pollution has a great impact on cardiovascular and cerebrovascular diseases (CCD), but there is a lack of research on low and medium pollution areas. This study was the first time to explore the effects of air pollutants on the outpatient visits of CCD in Luoyang, which is located in low and medium pollution areas.Methods: In this study, the Generalized Additive Model (GAM) was used to establish a single pollutant model, a multi-pollutant model and stratified modes of age, sex and season to evaluate the effects of PM2.5, PM10, SO2, NO2, CO and O3 on the outpatient visits of CCD within a week.Results: The results of single pollutant model showed that PM2.5, PM10, SO2, NO2, CO and O3 all had significant effects on the outpatient visits of CCD with a lag effect, interquartile range (IQR) increased in their concentration, the outpatient visits with CCD increased by 2.8%(95%CI:1.7%-4.0%), 3.0%(95%CI:1.8%-4.1%), -4.2% (95%CI: -5.5%- -2.9%), 20.5%(95%CI:18.2%-22.7%), 10.4%(95%CI:8.8%-12.1%), 2.3%(95%CI:0.8%-3.9%). The multi-pollutant model showed that there may be complex interactions among pollutants. The results of stratified model showed that there was no significant difference in the effects of different pollutants on different genders and ages, and the results of seasonal stratification showed that PM2.5, PM10, SO2 and CO had a greater influence on the outpatient visits of CCD in spring and summer, while NO2 and O3 had a greater influence on the outpatient visits of CCD in autumn and winter.Conclusion: The results showed that air pollutants significantly affected the outpatient visits of CCD, among which NO2 had the greatest influence, and seasonal effects and the combined effects of various pollutants should be considered in the prevention of CCD.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Air Pollution and Outpatient Visits for Cardiovascular and Cerebrovascular Diseases: A Time-Series Analysis in Luoyang, China

Guo

Wang

Wei

et al. 2021

Preprint

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“…O 3 was only positively correlated with the risk of CCD in people over 65 years old, and for PM 2.5 , the maximum lag effect appeared earlier in people over 65 years old. Similar to the results of this study, Ma Yuxia et al studied the relationship between PM 2.5 and CVD in Beijing and found that the lag effect was the shortest in the 60-75-year-old subgroup (Ma et al, 2019). Compared with young people, elderly people have worse physical fitness and more underlying diseases, so people over 65 years old are more likely to be affected by the environment, and thus the maximum lag effect appears faster.…”

Section: Discussionsupporting

confidence: 85%

“…In terms of the maximum lag effect in this study, NO 2 was the most harmful pollutant, and the estimated value of its effect on outpatient visits by men was generally greater than that for women. Ma Yuxia et al's study (Ma et al, 2019) on the relationship between PM 2.5 and CVD in Beijing found that there were more women than men with ischaemic heart disease or hypertension caused by the increase in PM 2.5 concentration. However, the incidence of arrhythmia in men was usually higher than that in women.…”

Section: Discussionmentioning

confidence: 99%

Air pollution and outpatient visits for cardiovascular and cerebrovascular diseases: A time‐series analysis in Luoyang, China

Guo

Wang

Wei

et al. 2021

Meteorological Applications

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Previous studies have shown that air pollutants have a significant impact on cardiovascular and cerebrovascular diseases (CCD), but these studies have focused more on provincial capitals or large cities. This study was the first time to explore the effects of air pollutants on CCD in Luoyang. In this study, the generalized additive model (GAM) was used to establish a single-pollutant model, a multi-pollutant model and stratified modes of age, sex and season to evaluate the effects of PM 2.5 , PM 10 , SO 2 , NO 2 , CO and O 3 on outpatient visits for CCD within a week. The results of the single-pollutant model showed that PM 2.5 , PM 10 , SO 2 , NO 2 , CO and O 3 all had significant effects on the outpatient visits for CCD with a lag effect. The multi-pollutant model showed that there might be complex interactions among pollutants. The results of the stratified model showed that there was no significant difference in the effects of different pollutants on different genders and ages, and the results of seasonal stratification showed that PM 2.5 , PM 10 , SO 2 and CO had a greater influence on the outpatient visits for CCD in spring and summer, while NO 2 and O 3 had a greater influence on the outpatient visits for CCD in winter and summer, respectively.The results showed that air pollutants significantly affected outpatient visits for CCD, among which NO 2 had the greatest influence, and seasonal effects and the combined effects of various pollutants should be considered in strategies for the prevention of CCD.

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“…Therefore, it was not possible to use spatial interpolation or pollution data from the nearest air quality monitoring station to reflect the exposure level of the hospital population. After consulting the relevant literature [8,21,22], the values from the above three urban stations were averaged to calculate one daily concentration value for PM 2.5. PM 10 , SO 2 , and NO 2 , and the corresponding air pollutant concentration values were set as the average pollutant exposure levels of urban residents according to the recommended methods.…”

Section: Data Collectionmentioning

confidence: 99%

Acute effects of fine particulate matter (PM2.5) on hospital admissions for cardiovascular diseases in Lanzhou, China: a time-series study

Yang

Chu

et al. 2022

Environ Sci Eur

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Background Up until now, evidence pertaining to the short-term effects of fine particulate matter (PM2.5) in cardiovascular diseases (CVD) is scarce in China. In this study, we aim to estimate the association between short-term exposure to PM2.5 and hospitalizations for total and cause-specific CVD in Lanzhou of China. Methods Daily counts of cardiovascular admissions were obtained from three large general hospitals in Lanzhou, China between 2014 and 2019. Air quality and meteorological data were obtained from the monitoring stations nearest to the admitting hospitals. We utilized Quasi-Poisson time-series regressions with distributed lag nonlinear models (DLNM) to assess the association between PM2.5 and CVD admitted in the three general hospitals. A stratified analysis was also conducted for age, sex, and disease subcategories. Results PM2.5 was positively correlated with daily admissions for total or other cause-specific CVD under different lag patterns. For every 10 μg/m3 increase in the PM2.5 concentration, the relative risk of daily admissions for total CVD, ischemic heart disease (IHD), heart rhythm disturbances (HRD), heart failure (HF), and cerebrovascular disease (CD) was: 1.011 [95% confidence interval (CI), 1.001–1.020] in lag01; 1.020 (95% CI 1.004–1.036) in lag07; 1.013 (95% CI 1.001–1.026) in lag7; 1.018 (95% CI 1.005–1.038) in lag1; and 1.007 (95% CI 1.001–1.018) in lag1. Both low and high temperatures increased the risk of cardiovascular hospitalization. No differences were found after stratification by gender and age. We found an almost linear relationship between the exposure to PM2.5 and cause-specific CVD admissions with no threshold effect. Males as well as the elderly, aged ≥ 65 years, were more vulnerable to PM 2.5 exposure. Conclusions Our results have demonstrated that PM2.5 has adverse impacts on cardiovascular hospitalizations in Lanzhou, especially on IHD.

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A study on the short-term impact of fine particulate matter pollution on the incidence of cardiovascular diseases in Beijing, China

Cited by 23 publications

References 40 publications

Air Pollution and Outpatient Visits for Cardiovascular and Cerebrovascular Diseases: A Time-Series Analysis in Luoyang, China

Air Pollution and Outpatient Visits for Cardiovascular and Cerebrovascular Diseases: A Time-Series Analysis in Luoyang, China

Air pollution and outpatient visits for cardiovascular and cerebrovascular diseases: A time‐series analysis in Luoyang, China

Acute effects of fine particulate matter (PM2.5) on hospital admissions for cardiovascular diseases in Lanzhou, China: a time-series study

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