Interactions between long-term ambient particle exposures and lifestyle on the prevalence of hypertension and diabetes: insight from a large community-based survey
IntroductionEvidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by...
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| Published in: | Journal of epidemiology and community health (1979) Vol. 77; no. 7; pp. 440 - 446 |
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| Language: | English |
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| Abstract | IntroductionEvidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles.MethodsThis was a large population-based survey during 2019–2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise.ResultsA total of 82 345 residents were included in the final analyses. For each 1 μg/m3 increase in PM2.5, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM2.5 and the combined condition was greatest in the group with 4–8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2–3 and those with 0–1 unhealthy lifestyle (P interaction=0.026). Similar results and trends were observed in PM10 and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable.ConclusionLong-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions. |
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| AbstractList | Evidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles.
This was a large population-based survey during 2019-2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise.
A total of 82 345 residents were included in the final analyses. For each 1 μg/m
increase in PM
, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM
and the combined condition was greatest in the group with 4-8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2-3 and those with 0-1 unhealthy lifestyle (P
=0.026). Similar results and trends were observed in PM
and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable.
Long-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions. IntroductionEvidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles.MethodsThis was a large population-based survey during 2019–2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise.ResultsA total of 82 345 residents were included in the final analyses. For each 1 μg/m3 increase in PM2.5, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM2.5 and the combined condition was greatest in the group with 4–8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2–3 and those with 0–1 unhealthy lifestyle (P interaction=0.026). Similar results and trends were observed in PM10 and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable.ConclusionLong-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions. Evidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles.INTRODUCTIONEvidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles.This was a large population-based survey during 2019-2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise.METHODSThis was a large population-based survey during 2019-2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise.A total of 82 345 residents were included in the final analyses. For each 1 μg/m3 increase in PM2.5, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM2.5 and the combined condition was greatest in the group with 4-8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2-3 and those with 0-1 unhealthy lifestyle (P interaction=0.026). Similar results and trends were observed in PM10 and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable.RESULTSA total of 82 345 residents were included in the final analyses. For each 1 μg/m3 increase in PM2.5, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM2.5 and the combined condition was greatest in the group with 4-8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2-3 and those with 0-1 unhealthy lifestyle (P interaction=0.026). Similar results and trends were observed in PM10 and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable.Long-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions.CONCLUSIONLong-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions. |
| Author | Zhang, Yuqin Xiao, Jianpeng Deng, Xinlei Cai, Huanle Chen, Shirui Du, Zhicheng Lin, Ziqiang Wang, Xinran Wang, Ying Wu, Wenjing Lin, Shao Zhang, Wangjian Hao, Yuantao Hopke, Philip K Rich, David Q Ju, Xu Lawrence, Wayne R Qu, Yanji Gu, Jing Lin, Xiao |
| AuthorAffiliation | 7 Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangzhou, Guangdong, China 3 Institute for a Sustainable Environment, Clarkson University, Potsdam, New York, USA 8 Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China 2 Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA 4 Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA 5 Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, New York, USA 9 Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China 6 Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China 1 School of Public Health/Sun Yat-sen Global Health Inst |
| AuthorAffiliation_xml | – name: 1 School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – name: 4 Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA – name: 6 Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China – name: 8 Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China – name: 9 Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China – name: 7 Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangzhou, Guangdong, China – name: 2 Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA – name: 5 Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, New York, USA – name: 3 Institute for a Sustainable Environment, Clarkson University, Potsdam, New York, USA |
| Author_xml | – sequence: 1 givenname: Huanle surname: Cai fullname: Cai, Huanle organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 2 givenname: Zhicheng surname: Du fullname: Du, Zhicheng organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 3 givenname: Xiao surname: Lin fullname: Lin, Xiao organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 4 givenname: Wayne R surname: Lawrence fullname: Lawrence, Wayne R organization: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA – sequence: 5 givenname: Philip K surname: Hopke fullname: Hopke, Philip K organization: Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA – sequence: 6 givenname: David Q surname: Rich fullname: Rich, David Q organization: Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA – sequence: 7 givenname: Shao surname: Lin fullname: Lin, Shao organization: Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, New York, USA – sequence: 8 givenname: Jianpeng surname: Xiao fullname: Xiao, Jianpeng organization: Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China – sequence: 9 givenname: Xinlei surname: Deng fullname: Deng, Xinlei organization: Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, New York, USA – sequence: 10 givenname: Yanji orcidid: 0000-0003-1766-6338 surname: Qu fullname: Qu, Yanji organization: Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangzhou, Guangdong, China – sequence: 11 givenname: Ziqiang surname: Lin fullname: Lin, Ziqiang organization: Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China – sequence: 12 givenname: Xinran surname: Wang fullname: Wang, Xinran organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 13 givenname: Xu surname: Ju fullname: Ju, Xu organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 14 givenname: Shirui surname: Chen fullname: Chen, Shirui organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 15 givenname: Yuqin surname: Zhang fullname: Zhang, Yuqin organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 16 givenname: Wenjing surname: Wu fullname: Wu, Wenjing organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 17 givenname: Ying surname: Wang fullname: Wang, Ying organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 18 givenname: Jing surname: Gu fullname: Gu, Jing organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China – sequence: 19 givenname: Yuantao orcidid: 0000-0001-8024-5312 surname: Hao fullname: Hao, Yuantao email: haoyt@bjmu.edu.cn organization: Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China – sequence: 20 givenname: Wangjian orcidid: 0000-0001-9655-6385 surname: Zhang fullname: Zhang, Wangjian email: zhangwj227@mail.sysu.edu.cn organization: School of Public Health/Sun Yat-sen Global Health Institute/Center for Health Information Research, Sun Yat-Sen University, Guangzhou, Guangdong, China |
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| CitedBy_id | crossref_primary_10_1093_ije_dyae112 crossref_primary_10_1265_ehpm_24_00159 crossref_primary_10_1016_j_apr_2025_102665 crossref_primary_10_1016_j_envres_2025_120885 crossref_primary_10_1038_s41612_025_00953_w |
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| Snippet | IntroductionEvidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly... Evidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined... |
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| SubjectTerms | Air Pollutants - analysis Air pollution Air Pollution - analysis Alcohol China - epidemiology Comorbidity Diabetes Diabetes mellitus Diabetes Mellitus - epidemiology Diet Disease Drinking behavior Environmental Exposure - analysis Environmental health Health facilities health impact assessment Humans Hypertension Hypertension - epidemiology Life Style Lifestyles Mortality Original research Particulate matter Particulate Matter - adverse effects Particulate Matter - analysis Prevalence Public health Sleep Smoking Surveys Surveys and Questionnaires Variables |
| Title | Interactions between long-term ambient particle exposures and lifestyle on the prevalence of hypertension and diabetes: insight from a large community-based survey |
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