Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study
BackgroundLong-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and mu...
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2022.1035415/full |
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| author | Amy Ronaldson Jorge Arias de la Torre Jorge Arias de la Torre Jorge Arias de la Torre Mark Ashworth Anna L. Hansell Anna L. Hansell Matthew Hotopf Matthew Hotopf Ian Mudway Ian Mudway Rob Stewart Rob Stewart Alex Dregan Ioannis Bakolis Ioannis Bakolis |
| author_facet | Amy Ronaldson Jorge Arias de la Torre Jorge Arias de la Torre Jorge Arias de la Torre Mark Ashworth Anna L. Hansell Anna L. Hansell Matthew Hotopf Matthew Hotopf Ian Mudway Ian Mudway Rob Stewart Rob Stewart Alex Dregan Ioannis Bakolis Ioannis Bakolis |
| author_sort | Amy Ronaldson |
| collection | DOAJ |
| description | BackgroundLong-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.MethodsMultimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM)2.5, PMcoarse, PM10, and nitrogen dioxide (NO2) concentrations (μg/m3–modeled to residential address) and multimorbidity status at the baseline assessment (2006–2010) in 364,144 people (mean age: 52.2 ± 8.1 years, 52.6% female). Air pollutants were categorized into quartiles to assess dose-response associations. Among those with multimorbidity (≥2 conditions; n = 156,395) we assessed associations between air pollutant exposure levels and multimorbidity severity and multimorbidity patterns, which were identified using exploratory factor analysis. Associations were explored using generalized linear models adjusted for sociodemographic, behavioral, and environmental indicators.ResultsHigher exposures to PM2.5, and NO2 were associated with multimorbidity status in a dose-dependent manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) [PM2.5: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO2: adjOR = 1.19 (95 % CI = 1.16, 1.23)]. We also observed dose-response associations between air pollutant exposures and multimorbidity severity scores. We identified 11 multimorbidity patterns. Air pollution was associated with several multimorbidity patterns with strongest associations (Q4 vs. Q1) observed for neurological (stroke, epilepsy, alcohol/substance dependency) [PM2.5: adjOR = 1.31 (95% CI = 1.14, 1.51); NO2: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM2.5: adjOR = 1.24 (95% CI = 1.16, 1.33); NO2: adjOR = 1.26 (95% CI = 1.15, 1.38)].ConclusionsThis cross-sectional study provides evidence that exposure to air pollution might be associated with having multimorbid, multi-organ conditions. Longitudinal studies are needed to further explore these associations. |
| first_indexed | 2024-04-11T07:48:02Z |
| format | Article |
| id | doaj.art-2221c0efbf5845ed90722fca88823b12 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-11T07:48:02Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj.art-2221c0efbf5845ed90722fca88823b122022-12-22T04:36:11ZengFrontiers Media S.A.Frontiers in Public Health2296-25652022-12-011010.3389/fpubh.2022.10354151035415Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional studyAmy Ronaldson0Jorge Arias de la Torre1Jorge Arias de la Torre2Jorge Arias de la Torre3Mark Ashworth4Anna L. Hansell5Anna L. Hansell6Matthew Hotopf7Matthew Hotopf8Ian Mudway9Ian Mudway10Rob Stewart11Rob Stewart12Alex Dregan13Ioannis Bakolis14Ioannis Bakolis15Centre for Implementation Science, Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United KingdomCentre for Implementation Science, Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United KingdomCIBER Epidemiology and Public Health (CIBERESP), Madrid, SpainInstitute of Biomedicine (IBIOMED), University of Leon, Leon, SpainSchool of Life Course and Population Sciences, King's College London, London, United KingdomCentre for Environmental Health and Sustainability, University of Leicester, Leicester, United KingdomNational Institute for Health and Care Research, Health Protection Research Unit (HPRU) in Environmental Exposures and Health at the University of Leicester, Leicester, United KingdomDepartment of Psychological Medicine, King's College London, IoPPN and South London and Maudsley NHS Foundation Trust, London, United KingdomSouth London and Maudsley NHS Foundation Trust, London, United KingdomNational Institute for Health and Care Research, Health Protection Unit in Environmental Exposures and Health, Imperial College London, London, United Kingdom0MRC Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College London, London, United KingdomDepartment of Psychological Medicine, King's College London, IoPPN and South London and Maudsley NHS Foundation Trust, London, United KingdomSouth London and Maudsley NHS Foundation Trust, London, United KingdomDepartment of Psychological Medicine, King's College London, IoPPN and South London and Maudsley NHS Foundation Trust, London, United KingdomCentre for Implementation Science, Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United Kingdom1Department of Biostatistics and Health Informatics, IoPPN, King's College London, London, United KingdomBackgroundLong-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.MethodsMultimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM)2.5, PMcoarse, PM10, and nitrogen dioxide (NO2) concentrations (μg/m3–modeled to residential address) and multimorbidity status at the baseline assessment (2006–2010) in 364,144 people (mean age: 52.2 ± 8.1 years, 52.6% female). Air pollutants were categorized into quartiles to assess dose-response associations. Among those with multimorbidity (≥2 conditions; n = 156,395) we assessed associations between air pollutant exposure levels and multimorbidity severity and multimorbidity patterns, which were identified using exploratory factor analysis. Associations were explored using generalized linear models adjusted for sociodemographic, behavioral, and environmental indicators.ResultsHigher exposures to PM2.5, and NO2 were associated with multimorbidity status in a dose-dependent manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) [PM2.5: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO2: adjOR = 1.19 (95 % CI = 1.16, 1.23)]. We also observed dose-response associations between air pollutant exposures and multimorbidity severity scores. We identified 11 multimorbidity patterns. Air pollution was associated with several multimorbidity patterns with strongest associations (Q4 vs. Q1) observed for neurological (stroke, epilepsy, alcohol/substance dependency) [PM2.5: adjOR = 1.31 (95% CI = 1.14, 1.51); NO2: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM2.5: adjOR = 1.24 (95% CI = 1.16, 1.33); NO2: adjOR = 1.26 (95% CI = 1.15, 1.38)].ConclusionsThis cross-sectional study provides evidence that exposure to air pollution might be associated with having multimorbid, multi-organ conditions. Longitudinal studies are needed to further explore these associations.https://www.frontiersin.org/articles/10.3389/fpubh.2022.1035415/fullair pollutionparticulate matternitrogen dioxidemultimorbidityhealth statusexploratory factor analysis |
| spellingShingle | Amy Ronaldson Jorge Arias de la Torre Jorge Arias de la Torre Jorge Arias de la Torre Mark Ashworth Anna L. Hansell Anna L. Hansell Matthew Hotopf Matthew Hotopf Ian Mudway Ian Mudway Rob Stewart Rob Stewart Alex Dregan Ioannis Bakolis Ioannis Bakolis Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study Frontiers in Public Health air pollution particulate matter nitrogen dioxide multimorbidity health status exploratory factor analysis |
| title | Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study |
| title_full | Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study |
| title_fullStr | Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study |
| title_full_unstemmed | Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study |
| title_short | Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study |
| title_sort | associations between air pollution and multimorbidity in the uk biobank a cross sectional study |
| topic | air pollution particulate matter nitrogen dioxide multimorbidity health status exploratory factor analysis |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2022.1035415/full |
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