Long-term residential exposure to source-specific particulate matter and incidence of diabetes mellitus — A cohort study in northern Sweden
Sommar, Johan N. ; Segersson, David ; Flanagan, Erin LU
and Oudin, Anna
LU
(2023)
In Environmental Research
217.
- Abstract
Diabetes mellitus (DM) incidence have been assessed in connection with air pollution exposure in several studies; however, few have investigated associations with source-specific local emissions. This study aims to estimate the risk of DM incidence associated with source-specific air pollution in a Swedish cohort with relatively low exposure. Individuals in the Västerbotten intervention programme cohort were followed until either a DM diagnosis or initiation of treatment with glucose-lowering medication occurred. Dispersion models with high spatial resolution were used to estimate annual mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10 μm (PM10) and ≤2.5 μm (PM2.5) at individual... (More)
Diabetes mellitus (DM) incidence have been assessed in connection with air pollution exposure in several studies; however, few have investigated associations with source-specific local emissions. This study aims to estimate the risk of DM incidence associated with source-specific air pollution in a Swedish cohort with relatively low exposure. Individuals in the Västerbotten intervention programme cohort were followed until either a DM diagnosis or initiation of treatment with glucose-lowering medication occurred. Dispersion models with high spatial resolution were used to estimate annual mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10 μm (PM10) and ≤2.5 μm (PM2.5) at individual addresses. Hazard ratios were estimated using Cox regression models in relation to moving averages 1–5 years preceding the outcome. During the study period, 1479 incident cases of DM were observed during 261,703 person-years of follow-up. Increased incidence of DM was observed in association with PM10 (4% [95% CI: -54–137%] per 10 μg/m3), PM10-traffic (2% [95% CI: -6–11%] per 1 μg/m3) and PM2.5-exhaust (11% [95% CI: -39–103%] per 1 μg/m3). A negative association was found for both PM2.5 (-18% [95% CI: -99–66%] per 5 μg/m3), but only in the 2nd exposure tertile (-10% [95% CI: -25–9%] compared to the first tertile), and PM2.5-woodburning (-30% [95% CI: -49–4%] per 1 μg/m3). In two-pollutant models including PM2.5-woodburning, there was an 11% [95% CI: -11–38%], 6% [95% CI: -16–34%], 13% [95% CI: -7–36%] and 17% [95% CI: 4–41%] higher risk in the 3rd tertile of PM10, PM2.5, PM10-traffic and PM2.5-exhaust, respectively, compared to the 1st. Although the results lacked in precision they are generally in line with the current evidence detailing particulate matter air pollution from traffic as an environmental risk factor for DM.
(Less)
- author
- Sommar, Johan N.
; Segersson, David
; Flanagan, Erin
LU
and Oudin, Anna
LU
- organization
- publishing date
- 2023-01-15
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Air pollution, Cohort, Diabetes mellitus, Exhaust, Particulate matter, Traffic emissions
- in
- Environmental Research
- volume
- 217
- article number
- 114833
- publisher
- Elsevier
- external identifiers
-
- scopus:85145580527
- pmid:36402182
- ISSN
- 0013-9351
- DOI
- 10.1016/j.envres.2022.114833
- language
- English
- LU publication?
- yes
- id
- 48c4ba53-a212-480b-9164-750885555352
- date added to LUP
- 2023-02-09 15:49:04
- date last changed
- 2024-06-25 15:21:23
@article{48c4ba53-a212-480b-9164-750885555352,
abstract = {{<p>Diabetes mellitus (DM) incidence have been assessed in connection with air pollution exposure in several studies; however, few have investigated associations with source-specific local emissions. This study aims to estimate the risk of DM incidence associated with source-specific air pollution in a Swedish cohort with relatively low exposure. Individuals in the Västerbotten intervention programme cohort were followed until either a DM diagnosis or initiation of treatment with glucose-lowering medication occurred. Dispersion models with high spatial resolution were used to estimate annual mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10 μm (PM<sub>10</sub>) and ≤2.5 μm (PM<sub>2.5</sub>) at individual addresses. Hazard ratios were estimated using Cox regression models in relation to moving averages 1–5 years preceding the outcome. During the study period, 1479 incident cases of DM were observed during 261,703 person-years of follow-up. Increased incidence of DM was observed in association with PM<sub>10</sub> (4% [95% CI: -54–137%] per 10 μg/m<sup>3</sup>), PM<sub>10</sub>-traffic (2% [95% CI: -6–11%] per 1 μg/m<sup>3</sup>) and PM<sub>2.5</sub>-exhaust (11% [95% CI: -39–103%] per 1 μg/m<sup>3</sup>). A negative association was found for both PM<sub>2.5</sub> (-18% [95% CI: -99–66%] per 5 μg/m<sup>3</sup>), but only in the 2nd exposure tertile (-10% [95% CI: -25–9%] compared to the first tertile), and PM<sub>2.5</sub>-woodburning (-30% [95% CI: -49–4%] per 1 μg/m<sup>3</sup>). In two-pollutant models including PM<sub>2.5</sub>-woodburning, there was an 11% [95% CI: -11–38%], 6% [95% CI: -16–34%], 13% [95% CI: -7–36%] and 17% [95% CI: 4–41%] higher risk in the 3rd tertile of PM<sub>10</sub>, PM<sub>2.5</sub>, PM<sub>10</sub>-traffic and PM<sub>2.5</sub>-exhaust, respectively, compared to the 1st. Although the results lacked in precision they are generally in line with the current evidence detailing particulate matter air pollution from traffic as an environmental risk factor for DM.</p>}},
author = {{Sommar, Johan N. and Segersson, David and Flanagan, Erin and Oudin, Anna}},
issn = {{0013-9351}},
keywords = {{Air pollution; Cohort; Diabetes mellitus; Exhaust; Particulate matter; Traffic emissions}},
language = {{eng}},
month = {{01}},
publisher = {{Elsevier}},
series = {{Environmental Research}},
title = {{Long-term residential exposure to source-specific particulate matter and incidence of diabetes mellitus — A cohort study in northern Sweden}},
url = {{http://dx.doi.org/10.1016/j.envres.2022.114833}},
doi = {{10.1016/j.envres.2022.114833}},
volume = {{217}},
year = {{2023}},
}