Inverse probability weighted distributed lag effects of short-term exposure to PM2.5 and ozone on CVD hospitalizations in New England Medicare participants - Exploring the causal effects

Qiu, Xinye; Wei, Yaguang; Wang, Yan; Di, Qian; Sofer, Tamar; Awad, Yara Abu; Schwartz, Joel

doi:10.1016/j.envres.2019.109095

Cited by 44 publications

(33 citation statements)

References 37 publications

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“…Similar results were also observed in other continents [8,29]. In New England, a study found that the highest harmful effects of PM 2.5 exposure were at lag0~5, for each 10 μg/m 3 increment associated with an increase of 4.31%, 3.95% and 2.56% percentage change in the hospital admission rate for myocardial infarction, congestive heart failure and ischemic stroke respectively [8]. Another study in Denmark found the highest ultra ne particles-associated risks for stroke at lag0~4 [29].…”

Section: Discussionsupporting

confidence: 92%

“…In the present investigation, we found that moving average lag model usually had higher estimates than that of single-day exposure, with the greatest effects observed at lag0~2. Similar results were also observed in other continents [8,29]. In New England, a study found that the highest harmful effects of PM 2.5 exposure were at lag0~5, for each 10 μg/m 3 increment associated with an increase of 4.31%, 3.95% and 2.56% percentage change in the hospital admission rate for myocardial infarction, congestive heart failure and ischemic stroke respectively [8].…”

Section: Discussionsupporting

confidence: 65%

“…Previous studies have provided strong evidence of the harm effect of PM 2.5 on cardiorespiratory diseases [5,6]. Although several large-scale studies, conducted in western developed countries [7,8], have examined the associations between air pollution and cardiorespiratory hospital admissions. These results may not be applicable to developing countries due to local climate conditions, PM chemical components and population susceptibility.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Ambient Fine Particulate (PM2.5) on Hospital Admissions for Respiratory and Cardiovascular Diseases in Wuhan, China

Ren

Liu

et al. 2020

Preprint

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Background: The positive associations between ambient PM2.5 and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM2.5 based on an entire population of megalopolis. In addition, due to the lack of accurate methods of assessing individual PM2.5 exposure, further studies are still necessary to be launched in China.Methods: The study was conducted in Wuhan, a megacity in central China with about 10.8929 million population. Daily hospital admission records, from October 2016 to December 2018, were obtained from Wuhan Information center of Health and Family Planning, which administrates all the hospitals in Wuhan. The daily air pollution concentration and weather variable in Wuhan during the study period were collected. We developed Land use regression model (LUR) to assess individual PM2.5 exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposures to PM2.5. We also conducted stratification analyses by age, sex and season.Results: A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 for total cardiovascular diseases and 159,365 for total respiratory diseases. We found short-term PM2.5 exposure was associated with increased risk of cardiorespiratory hospital admission in Wuhan. Per 10 μg/m3 increase of PM2.5 at lag0~2 days was associated with 1.23% (95%CI: 1.01–1.45%) and 1.95% (95%CI: 1.63–2.27%) elevated risk of admission from cardiovascular and respiratory diseases respectively. The elderly were at higher PM-induced risks. The associations appeared to be more evident in the cold season than in the warm season.Conclusions: This study contributed evidence to support the short-term effects of PM2.5 on cardiorespiratory hospital admission, which may be helpful for air pollution control and disease prevention in Wuhan.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionsupporting

confidence: 65%

Section: Introductionmentioning

confidence: 99%

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Effect of Ambient Fine Particulate (PM2.5) on Hospital Admissions for Respiratory and Cardiovascular Diseases in Wuhan, China

Ren

Liu

et al. 2020

Preprint

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“…Organisation and Indian Council of Medical Research (Report, 2020). Following the same, moving average approach was applied to determine the cumulative lag effect of air pollutants and their association with meteorological factors (Kim et al, 2019;Qiu et al, 2020;Rojas-roa and Rodríguezvillamizar, 2019;Zhang et al, 2020;Zhu et al, 2018Zhu et al, , 2019. So, Generalised additive model (GAM) with Gaussian distribution was utilised to connect the infected rate due to COVID-19 and air pollutants or meteorological parameters (Chuang et al, 2011;Gao et al, 2019;Ravindra et al, 2019;Sun et al, 2015;Tong et al, 2018;Yoon, 2019;Zhang and Batterman, 2010).…”

Section: Discussionmentioning

confidence: 99%

Significance between Air pollutants, Meteorological Factors and COVID-19 Infections: Probable Evidences in India

Sahoo

2020

Preprint

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SARS-CoV-2 (Coronavirus) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors and the daily reported infection cases caused by novel coronavirus in India. The daily positive infected cases, air pollution and meteorological factors in 288 districts were collected from January 30, 2020 to April 23, 2020 in India. Speraman’s correlation and generalised additive model were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2 and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS and WD) with COVID-19 infected cases. The study indicated that a 10 µg/m3 increase during (Lag0-14) in PM2.5, PM10 and NO2 was resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01) and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of COVID 19 infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19 infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19 infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there is significant relationship between air pollutants and meteorological factors with COVID-19 infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.

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“…However, there is an incubation period of 5 to 14 days to show the symptoms of COVID-19 infections as reported by the World Health Organisation and Indian Council of Medical Research (Report 2020 ). Following the same, moving average approach was applied to determine the cumulative lag effect of air pollutants and their association with meteorological factors (Kim et al 2019 ; Qiu et al 2020 ; Rojas-roa and Rodríguez-villamizar 2019 ; Zhang et al 2019b ; Zhang et al 2020 ; Zhu et al 2018 , 2019 ). Focusing on previous studies and findings, generalized additive model (GAM) with Gaussian distribution was utilized to connect the infected rate due to COVID-19 and air pollutants or meteorological parameters (Chuang et al 2011 ; Gao et al 2019 ; Ravindra et al 2019 ; Sun et al 2015 ; Tong et al 2018 ; Yoon 2019 ; Zhang and Batterman 2010 ).…”

Section: Materials and Methodologymentioning

confidence: 99%

Significance between air pollutants, meteorological factors, and COVID-19 infections: probable evidences in India

Sahoo

2021

Environ Sci Pollut Res

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Graphical abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman’s correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM 2.5 , PM 10 , NO 2 , and SO 2 ) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 μg/m 3 increase during (Lag0-14) in PM 2.5 , PM 10 , and NO 2 resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO 2 and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO 2 and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.

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Inverse probability weighted distributed lag effects of short-term exposure to PM2.5 and ozone on CVD hospitalizations in New England Medicare participants - Exploring the causal effects

Cited by 44 publications

References 37 publications

Effect of Ambient Fine Particulate (PM2.5) on Hospital Admissions for Respiratory and Cardiovascular Diseases in Wuhan, China

Effect of Ambient Fine Particulate (PM2.5) on Hospital Admissions for Respiratory and Cardiovascular Diseases in Wuhan, China

Significance between Air pollutants, Meteorological Factors and COVID-19 Infections: Probable Evidences in India

Significance between air pollutants, meteorological factors, and COVID-19 infections: probable evidences in India

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