Long-term air pollution exposure and self-reported morbidity: A longitudinal analysis from the Thai cohort study (TCS)
Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollu...
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Published in | Environmental research Vol. 192; p. 110330 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier Inc
01.01.2021
Elsevier |
Subjects | |
Online Access | Get full text |
ISSN | 0013-9351 1096-0953 1096-0953 |
DOI | 10.1016/j.envres.2020.110330 |
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Abstract | Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand.
This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005–2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO.
After controlling for potential confounders, we found that an IQR increase in PM10 was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO2 was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O3 and NO2.
Long-term exposure to air pollution, especially for PM10 and SO2 was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population.
•Evidence on health effects of long-term air pollution exposure are still limited in Southeast Asia.•SO2 was associated with an increased risks of self-reported high blood pressure, high blood cholesterol, and diabetes.•Increase of PM10 was also associated with the incidences of high blood pressure and high blood cholesterol.•The effects were observed even at the level below the National Standard Limit.•This study suggests air pollution increases cardiovascular disease risk factors for younger population. |
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AbstractList | •
Evidence on health effects of long-term air pollution exposure are still limited in Southeast Asia.
•
SO
2
was associated with an increased risks of self-reported high blood pressure, high blood cholesterol, and diabetes.
•
Increase of PM
10
was also associated with the incidences of high blood pressure and high blood cholesterol.
•
The effects were observed even at the level below the National Standard Limit.
•
This study suggests air pollution increases cardiovascular disease risk factors for younger population. Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand. This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005–2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO. After controlling for potential confounders, we found that an IQR increase in PM10 was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO2 was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O3 and NO2. Long-term exposure to air pollution, especially for PM10 and SO2 was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population. •Evidence on health effects of long-term air pollution exposure are still limited in Southeast Asia.•SO2 was associated with an increased risks of self-reported high blood pressure, high blood cholesterol, and diabetes.•Increase of PM10 was also associated with the incidences of high blood pressure and high blood cholesterol.•The effects were observed even at the level below the National Standard Limit.•This study suggests air pollution increases cardiovascular disease risk factors for younger population. Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand.BACKGROUNDSeveral studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand.This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005-2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO.METHODSThis longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005-2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO.After controlling for potential confounders, we found that an IQR increase in PM10 was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO2 was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O3 and NO2.RESULTSAfter controlling for potential confounders, we found that an IQR increase in PM10 was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO2 was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O3 and NO2.Long-term exposure to air pollution, especially for PM10 and SO2 was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population.CONCLUSIONSLong-term exposure to air pollution, especially for PM10 and SO2 was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population. Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand. This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM ), sulfur dioxide (SO ), nitrogen dioxide (NO ), ozone (O ), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005-2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM , O , NO , SO , and CO. After controlling for potential confounders, we found that an IQR increase in PM was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O and NO . Long-term exposure to air pollution, especially for PM and SO was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population. Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand.This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005–2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM₁₀, O₃, NO₂, SO₂, and CO.After controlling for potential confounders, we found that an IQR increase in PM₁₀ was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO₂ was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O₃ and NO₂.Long-term exposure to air pollution, especially for PM₁₀ and SO₂ was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population. |
ArticleNumber | 110330 |
Author | Strazdins, Lyndall Somsamai, Pathumvadee Puengson, Janya Vilainerun, Duangkae Honda, Akiko Tawatsupa, Benjawan Friel, Sharon Kelly, Matthew Pandee, Daoruang Ingviya, Thammasin Churewong, Chaiyun Tran, Tam Rimpeekool, Wimalin Sangrattanakul, Yodyiam Sleigh, Adrian Bain, Chris Dellora, Tarie Zhao, Jiaying Lim, Lynette Takano, Hirohisa Yiengprugsawan, Vasoontara Paoin, Kanawat Prapamontol, Tippawan Tangmunkongvorakul, Arunrat Phosri, Arthit Seposo, Xerxes Tesoro Caldwell, Bruce Khamman, Suwanee Pangsap, Suttinan Mark, Tanya McMichael, Anthony Dixon, Jane Hounthasarn, Suttanit Banwell, Cathy Chokhanapitak, Jaruwan Carmichael, Gordon Sripaiboonkij, Nintita Banks, Emily Jordan, Susan Buya, Suhaimee Somboonsook, Boonchai Berecki-Gisolf, Janneke McClure, Roderick Wimonwattanaphan, Wanee Ueda, Kayo Harley, David Seubsman, Sam-ang Kjellstrom, Tord |
Author_xml | – sequence: 1 givenname: Kanawat surname: Paoin fullname: Paoin, Kanawat organization: Department of Environmental Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Japan – sequence: 2 givenname: Kayo surname: Ueda fullname: Ueda, Kayo email: uedak@health.env.kyoto-u.ac.jp organization: Department of Environmental Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Japan – sequence: 3 givenname: Thammasin orcidid: 0000-0002-8894-3817 surname: Ingviya fullname: Ingviya, Thammasin organization: Department of Family and Preventive Medicine, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand – sequence: 4 givenname: Suhaimee orcidid: 0000-0002-3921-7819 surname: Buya fullname: Buya, Suhaimee organization: Medical Data Center for Research and Innovation, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand – sequence: 5 givenname: Arthit orcidid: 0000-0002-5541-867X surname: Phosri fullname: Phosri, Arthit organization: Department of Environmental Health Sciences, Faculty of Public Health, Mahidol University, Bangkok, Thailand – sequence: 6 givenname: Xerxes Tesoro orcidid: 0000-0003-0339-8213 surname: Seposo fullname: Seposo, Xerxes Tesoro organization: School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan – sequence: 7 givenname: Sam-ang surname: Seubsman fullname: Seubsman, Sam-ang organization: School of Human Ecology, Sukhothai Thammathirat Open University, Nonthaburi, Thailand – sequence: 8 givenname: Matthew orcidid: 0000-0001-7963-2139 surname: Kelly fullname: Kelly, Matthew organization: Department of Global Health, Research School of Population Health, Australian National University, Canberra, Australia – sequence: 9 givenname: Adrian surname: Sleigh fullname: Sleigh, Adrian organization: Department of Global Health, Research School of Population Health, Australian National University, Canberra, Australia – sequence: 10 givenname: Akiko orcidid: 0000-0002-7358-4372 surname: Honda fullname: Honda, Akiko organization: Department of Environmental Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Japan – sequence: 11 givenname: Hirohisa surname: Takano fullname: Takano, Hirohisa organization: Department of Environmental Engineering, Graduate School of Engineering, Kyoto University, Kyoto, Japan – sequence: 12 givenname: Jaruwan surname: Chokhanapitak fullname: Chokhanapitak, Jaruwan – sequence: 13 givenname: Chaiyun surname: Churewong fullname: Churewong, Chaiyun – sequence: 14 givenname: Suttanit surname: Hounthasarn fullname: Hounthasarn, Suttanit – sequence: 15 givenname: Suwanee surname: Khamman fullname: Khamman, Suwanee – sequence: 16 givenname: Daoruang surname: Pandee fullname: Pandee, Daoruang – sequence: 17 givenname: Suttinan surname: Pangsap fullname: Pangsap, Suttinan – sequence: 18 givenname: Tippawan surname: Prapamontol fullname: Prapamontol, Tippawan – sequence: 19 givenname: Janya surname: Puengson fullname: Puengson, Janya – sequence: 20 givenname: Wimalin surname: Rimpeekool fullname: Rimpeekool, Wimalin – sequence: 21 givenname: Yodyiam surname: Sangrattanakul fullname: Sangrattanakul, Yodyiam – sequence: 22 givenname: Sam-ang surname: Seubsman fullname: Seubsman, Sam-ang email: sam-ang.seu@stou.ac.th – sequence: 23 givenname: Boonchai surname: Somboonsook fullname: Somboonsook, Boonchai – sequence: 24 givenname: Nintita surname: Sripaiboonkij fullname: Sripaiboonkij, Nintita – sequence: 25 givenname: Pathumvadee surname: Somsamai fullname: Somsamai, Pathumvadee – sequence: 26 givenname: Benjawan surname: Tawatsupa fullname: Tawatsupa, Benjawan – sequence: 27 givenname: Arunrat surname: Tangmunkongvorakul fullname: Tangmunkongvorakul, Arunrat – sequence: 28 givenname: Duangkae surname: Vilainerun fullname: Vilainerun, Duangkae – sequence: 29 givenname: Wanee surname: Wimonwattanaphan fullname: Wimonwattanaphan, Wanee – sequence: 30 givenname: Chris surname: Bain fullname: Bain, Chris – sequence: 31 givenname: Emily surname: Banks fullname: Banks, Emily – sequence: 32 givenname: Cathy surname: Banwell fullname: Banwell, Cathy – sequence: 33 givenname: Janneke surname: Berecki-Gisolf fullname: Berecki-Gisolf, Janneke – sequence: 34 givenname: Bruce surname: Caldwell fullname: Caldwell, Bruce – sequence: 35 givenname: Gordon surname: Carmichael fullname: Carmichael, Gordon – sequence: 36 givenname: Tarie surname: Dellora fullname: Dellora, Tarie – sequence: 37 givenname: Jane surname: Dixon fullname: Dixon, Jane – sequence: 38 givenname: Sharon surname: Friel fullname: Friel, Sharon – sequence: 39 givenname: David surname: Harley fullname: Harley, David – sequence: 40 givenname: Susan surname: Jordan fullname: Jordan, Susan – sequence: 41 givenname: Matthew surname: Kelly fullname: Kelly, Matthew – sequence: 42 givenname: Tord surname: Kjellstrom fullname: Kjellstrom, Tord – sequence: 43 givenname: Lynette surname: Lim fullname: Lim, Lynette – sequence: 44 givenname: Roderick surname: McClure fullname: McClure, Roderick – sequence: 45 givenname: Anthony surname: McMichael fullname: McMichael, Anthony – sequence: 46 givenname: Tanya surname: Mark fullname: Mark, Tanya – sequence: 47 givenname: Adrian surname: Sleigh fullname: Sleigh, Adrian email: adrian.sleigh@anu.edu.au – sequence: 48 givenname: Lyndall surname: Strazdins fullname: Strazdins, Lyndall – sequence: 49 givenname: Tam surname: Tran fullname: Tran, Tam – sequence: 50 givenname: Vasoontara surname: Yiengprugsawan fullname: Yiengprugsawan, Vasoontara – sequence: 51 givenname: Jiaying surname: Zhao fullname: Zhao, Jiaying |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33068582$$D View this record in MEDLINE/PubMed |
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ContentType | Journal Article |
Contributor | Strazdins, Lyndall Somsamai, Pathumvadee Puengson, Janya Vilainerun, Duangkae Tawatsupa, Benjawan Friel, Sharon Pandee, Daoruang Kelly, Matthew Churewong, Chaiyun Tran, Tam Rimpeekool, Wimalin Sangrattanakul, Yodyiam Sleigh, Adrian Bain, Chris Dellora, Tarie Zhao, Jiaying Lim, Lynette Yiengprugsawan, Vasoontara Prapamontol, Tippawan Seubsman, Sam-Ang Tangmunkongvorakul, Arunrat Caldwell, Bruce Khamman, Suwanee Pangsap, Suttinan Mark, Tanya McMichael, Anthony Dixon, Jane Hounthasarn, Suttanit Banwell, Cathy Chokhanapitak, Jaruwan Carmichael, Gordon Sripaiboonkij, Nintita Banks, Emily Jordan, Susan Somboonsook, Boonchai Berecki-Gisolf, Janneke McClure, Roderick Wimonwattanaphan, Wanee Harley, David Kjellstrom, Tord |
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Copyright | 2020 The Authors Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved. 2020 The Authors 2020 |
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Keywords | High blood cholesterol Long-term air pollution exposure High blood pressure Diabetes Cardiovascular disease risk factors |
Language | English |
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Snippet | Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort... • Evidence on health effects of long-term air pollution exposure are still limited in Southeast Asia. • SO 2 was associated with an increased risks of... |
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SubjectTerms | air Air Pollutants - analysis Air Pollutants - toxicity air pollution Air Pollution - adverse effects blood carbon monoxide Cardiovascular disease risk factors China cholesterol chronic exposure Cohort Studies Diabetes Environmental Exposure - adverse effects Environmental Exposure - analysis High blood cholesterol High blood pressure Humans hypertension kriging Long-term air pollution exposure Longitudinal Studies Morbidity nitrogen dioxide Nitrogen Dioxide - analysis Nitrogen Dioxide - toxicity ozone Ozone - analysis Particulate Matter - analysis pollution control Self Report sulfur dioxide Thailand - epidemiology traffic weather |
Title | Long-term air pollution exposure and self-reported morbidity: A longitudinal analysis from the Thai cohort study (TCS) |
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