Air pollution, road traffic noise and lack of greenness and risk of type 2 diabetes: A multi-exposure prospective study covering Denmark. (December 2022)
- Record Type:
- Journal Article
- Title:
- Air pollution, road traffic noise and lack of greenness and risk of type 2 diabetes: A multi-exposure prospective study covering Denmark. (December 2022)
- Main Title:
- Air pollution, road traffic noise and lack of greenness and risk of type 2 diabetes: A multi-exposure prospective study covering Denmark
- Authors:
- Sørensen, Mette
Poulsen, Aslak H.
Hvidtfeldt, Ulla A.
Brandt, Jørgen
Frohn, Lise M.
Ketzel, Matthias
Christensen, Jesper H.
Im, Ulas
Khan, Jibran
Münzel, Thomas
Raaschou-Nielsen, Ole - Abstract:
- Highlights: Air pollution, traffic noise and lack of green space have been associated with diabetes in analyses mainly focusing on one or two environmental factors at a time. We aimed to investigate if air pollution, road traffic noise and green space are independent risk factors of type 2 diabetes. In a multi-pollutant analysis, ultrafine particles, NO2, noise at both most and least exposed façade and two proxies of lack of green space were all associated with higher risk of type 2 diabetes. The cumulative risk estimate of the multi-pollutant analysis was much higher than the risk estimate of any single pollutant. Abstract: Objective: Air pollution, road traffic noise and lack of greenness coexist in urban environments and have all been associated with type 2 diabetes. We aimed to investigate how these co-exposures were associated with type 2 diabetes in a multi-exposure perspective. Methods: We estimated 5-year residential mean exposure to fine particles (PM2.5 ), ultrafine particles (UFP), elemental carbon (EC), nitrogen dioxide (NO2 ) and road traffic noise at the most (LdenMax) and least (LdenMin) exposed facade for all persons aged > 50 years living in Denmark in 2005 to 2017. For each air pollutant, we estimated total concentrations and traffic contributions. Based on land use maps, we estimated proportion of green and non-green space within 150 and 1000 m of all residences. In total, 1.9 million persons were included and 128, 358 developed type 2 diabetes duringHighlights: Air pollution, traffic noise and lack of green space have been associated with diabetes in analyses mainly focusing on one or two environmental factors at a time. We aimed to investigate if air pollution, road traffic noise and green space are independent risk factors of type 2 diabetes. In a multi-pollutant analysis, ultrafine particles, NO2, noise at both most and least exposed façade and two proxies of lack of green space were all associated with higher risk of type 2 diabetes. The cumulative risk estimate of the multi-pollutant analysis was much higher than the risk estimate of any single pollutant. Abstract: Objective: Air pollution, road traffic noise and lack of greenness coexist in urban environments and have all been associated with type 2 diabetes. We aimed to investigate how these co-exposures were associated with type 2 diabetes in a multi-exposure perspective. Methods: We estimated 5-year residential mean exposure to fine particles (PM2.5 ), ultrafine particles (UFP), elemental carbon (EC), nitrogen dioxide (NO2 ) and road traffic noise at the most (LdenMax) and least (LdenMin) exposed facade for all persons aged > 50 years living in Denmark in 2005 to 2017. For each air pollutant, we estimated total concentrations and traffic contributions. Based on land use maps, we estimated proportion of green and non-green space within 150 and 1000 m of all residences. In total, 1.9 million persons were included and 128, 358 developed type 2 diabetes during follow-up. We performed analyses using Cox proportional hazards models, with adjustment for individual and neighborhood-level sociodemographic co-variates. Results: In single-pollutant models, all air pollutants, noise and lack of green space were associated with higher risk of diabetes. In two-, three- and four-pollutant analyses of the air pollutants, only UFP and NO2 remained associated with higher diabetes risk in all models. LdenMax, LdenMin and the two proxies of green space remained associated with diabetes in two-pollutant models of, respectively, noise and green space. In a multi-pollutant analysis, we found hazard ratios (95 % confidence intervals) per interquartile range of 1.021 (1.005; 1.038) for UFP, 1.012 (0.996; 1.028) for NO2, 1.022 (1.012; 1.033) for LdenMin, 1.013 (1.004; 1.022) for LdenMax, and 1.038 (1.031; 1.044) and 1.018 (1.010; 1.025) for lack of green space within, respectively, 150 m and 1000 m, and a cumulative risk index of 1.131 (1.113; 1.149). Conclusions: Air pollution, road traffic noise and lack of green space were independently associated with higher risk of type 2 diabetes. … (more)
- Is Part Of:
- Environment international. Volume 170(2023)
- Journal:
- Environment international
- Issue:
- Volume 170(2023)
- Issue Display:
- Volume 170, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 170
- Issue:
- 2023
- Issue Sort Value:
- 2023-0170-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-12
- Subjects:
- Air pollution -- Green space -- Multi-pollutant -- Road traffic noise -- Type 2 diabetes
CRI cumulative risk index -- EC Elemental carbon -- HR hazard ratios -- LdenMax Road traffic noise at the most exposed façade -- LdenMin Road traffic noise at the least exposed façade -- NonGreen1000m the proportion of areas within 1000 m not classified as recreational areas, forests and open nature areas -- NonGreen150m the proportion of areas within 150 m not classified as low built up, high built up, agricultural areas, recreational areas, forests and open nature areas -- PM2.5 Particulate matter with a diameter <2.5 µm -- SES Socioeconomic status -- UFP Ultrafine particles
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Environmental Monitoring -- Periodicals
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Hygiène du milieu -- Périodiques
Environnement -- Surveillance -- Périodiques
Environmental health
Environmental monitoring
Environmental protection
Periodicals
333.705 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01604120 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.envint.2022.107570 ↗
- Languages:
- English
- ISSNs:
- 0160-4120
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