Effect of short-term exposure to air pollution on hospital admission for cardiovascular disease : A time-series study in Xiangyang, China
Copyright © 2024 Elsevier B.V. All rights reserved..
BACKGROUND: Data on the relationship between short-term exposure to air pollution and cardiovascular diseases (CVDs) and the potential modifying factors are limited and inconsistent.
OBJECTIVE: To explore the relationship between short-term exposure to air pollution and CVD risk, and potential modification effect factors.
METHOD: A time series study was conducted on 52,991 hospital admissions for CVD from 2015 to 2019 in Xiangyang City, China. Air pollution data from four national fixed monitoring stations were collected to estimate exposure level in Xiangyang City. A quasi-Poisson generalized additive model incorporating a distributed lag nonlinear model was applied to evaluate the association between air pollution and CVD risk. The potential modification effect of sex, age, and season on the above associations was also evaluated.
RESULTS: CVD risk was positively associated with air pollution. Peak associations in single lag day structures were observed for particulate matter ≤10 μm in aerodynamic (PM10; RR: 1.040, 95 % CI: 0.996-1.087), PM2.5 (1.025, 1.004-1.045), nitrogen dioxide (NO2; 1.074, 1.039-1.111), and sulfur dioxide (SO2; 1.079, 1.019-1.141) at Lag 0 and ozone (O3; 1.018, 1.004-1.031) at Lag 4. In cumulative lag day structures, the highest RRs were 1.225 (1.079,1.392) for PM10 at Lag 06, 1.054 (1.013, 1.098) for PM2.5 at Lag 03, 1.200 (1.119, 1.287) for NO2 at Lag 04, and 1.135 (1.025, 1.257) for SO2 at Lag 02. Moreover, the association between air pollution and CVD risk was modified by sex and age (P < 0.05). Females and individuals aged ≤65 years were more vulnerable to NO2 and had a higher CVD risk.
CONCLUSION: Short-term exposure to air pollution was positively associated with CVD risk. Moreover, sex and age could modify the effect of air pollution on CVD risk. Females and individuals aged ≤65 years had a higher NO2 exposure-induced CVD risk.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:918 |
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| Enthalten in: |
The Science of the total environment - 918(2024) vom: 25. Feb., Seite 170735 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Liu, Yangwenhao [VerfasserIn] |
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| Links: |
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| Themen: |
Air Pollutants |
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| Anmerkungen: |
Date Completed 22.02.2024 Date Revised 22.02.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.scitotenv.2024.170735 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM368146855 |
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| 100 | 1 | |a Liu, Yangwenhao |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Effect of short-term exposure to air pollution on hospital admission for cardiovascular disease |b A time-series study in Xiangyang, China |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
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| 500 | |a Date Completed 22.02.2024 | ||
| 500 | |a Date Revised 22.02.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2024 Elsevier B.V. All rights reserved. | ||
| 520 | |a BACKGROUND: Data on the relationship between short-term exposure to air pollution and cardiovascular diseases (CVDs) and the potential modifying factors are limited and inconsistent | ||
| 520 | |a OBJECTIVE: To explore the relationship between short-term exposure to air pollution and CVD risk, and potential modification effect factors | ||
| 520 | |a METHOD: A time series study was conducted on 52,991 hospital admissions for CVD from 2015 to 2019 in Xiangyang City, China. Air pollution data from four national fixed monitoring stations were collected to estimate exposure level in Xiangyang City. A quasi-Poisson generalized additive model incorporating a distributed lag nonlinear model was applied to evaluate the association between air pollution and CVD risk. The potential modification effect of sex, age, and season on the above associations was also evaluated | ||
| 520 | |a RESULTS: CVD risk was positively associated with air pollution. Peak associations in single lag day structures were observed for particulate matter ≤10 μm in aerodynamic (PM10; RR: 1.040, 95 % CI: 0.996-1.087), PM2.5 (1.025, 1.004-1.045), nitrogen dioxide (NO2; 1.074, 1.039-1.111), and sulfur dioxide (SO2; 1.079, 1.019-1.141) at Lag 0 and ozone (O3; 1.018, 1.004-1.031) at Lag 4. In cumulative lag day structures, the highest RRs were 1.225 (1.079,1.392) for PM10 at Lag 06, 1.054 (1.013, 1.098) for PM2.5 at Lag 03, 1.200 (1.119, 1.287) for NO2 at Lag 04, and 1.135 (1.025, 1.257) for SO2 at Lag 02. Moreover, the association between air pollution and CVD risk was modified by sex and age (P < 0.05). Females and individuals aged ≤65 years were more vulnerable to NO2 and had a higher CVD risk | ||
| 520 | |a CONCLUSION: Short-term exposure to air pollution was positively associated with CVD risk. Moreover, sex and age could modify the effect of air pollution on CVD risk. Females and individuals aged ≤65 years had a higher NO2 exposure-induced CVD risk | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Air pollution | |
| 650 | 4 | |a Cardiovascular disease | |
| 650 | 4 | |a Distributed lag nonlinear model | |
| 650 | 4 | |a Hospital admission | |
| 650 | 4 | |a Time-series analysis | |
| 650 | 7 | |a Air Pollutants |2 NLM | |
| 650 | 7 | |a Nitrogen Dioxide |2 NLM | |
| 650 | 7 | |a S7G510RUBH |2 NLM | |
| 650 | 7 | |a Particulate Matter |2 NLM | |
| 700 | 1 | |a Guo, Meng |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Junxiang |e verfasserin |4 aut | |
| 700 | 1 | |a Gong, Yongxiang |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Chunrong |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Xiaodong |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Juming |e verfasserin |4 aut | |
| 700 | 1 | |a Ju, Changyu |e verfasserin |4 aut | |
| 700 | 1 | |a Ba, Yue |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Guoyu |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Xiaolin |e verfasserin |4 aut | |
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