Maciej Strak1, Nicole Janssen2, Rob Beelen2, Oliver Schmitz3, Ilonca Vaartjes4, Derek Karssenberg3, Carolien van den Brink2, Michiel L Bots4, Martin Dijst5, Bert Brunekreef6, Gerard Hoek7. 1. Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, Netherlands. Electronic address: m.m.strak@uu.nl. 2. National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands. 3. Global Geo and Health Data Centre, Utrecht University, Utrecht, The Netherlands; Department of Physical Geography, Faculty of Geosciences, Utrecht University, Netherlands. 4. Global Geo and Health Data Centre, Utrecht University, Utrecht, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands. 5. Global Geo and Health Data Centre, Utrecht University, Utrecht, The Netherlands; Department of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, Netherlands. 6. Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands. 7. Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, Netherlands.
Abstract
BACKGROUND: The evidence from observational epidemiological studies of a link between long-term air pollution exposure and diabetes prevalence and incidence is currently mixed. Some studies found the strongest associations of diabetes with fine particles, other studies with nitrogen dioxide and some studies found no associations. OBJECTIVES: Our aim was to investigate associations between long-term exposure to multiple air pollutants and diabetes prevalence in a large national survey in the Netherlands. METHODS: We performed a cross-sectional analysis using the 2012 Dutch national health survey to investigate the associations between the 2009 annual average concentrations of multiple air pollutants (PM10, PM2.5, PM10-2.5, PM2.5 absorbance, OPDTT, OPESR and NO2) and diabetes prevalence, among 289,703 adults. Air pollution exposure was assessed by land use regression models. Diabetes was defined based on a combined measure of self-reported physician diagnosis and medication prescription from an external database. Using logistic regression, we adjusted for potential confounders, including neighborhood- and individual socio-economic status and lifestyle-related risk factors such as smoking habits, alcohol consumption, physical activity and BMI. RESULTS: After adjustment for potential confounders, all pollutants (except PM2.5) were associated with diabetes prevalence. In two-pollutant models, NO2 and OPDTT remained associated with increased diabetes prevalence. For NO2 and OPDTT, single-pollutant ORs per interquartile range were 1.07 (95% CI: 1.05, 1.09) and 1.08 (95% CI: 1.05, 1.10), respectively. Stratified analysis showed no consistent effect modification by any of the included known diabetes risk factors. CONCLUSIONS: Long-term residential air pollution exposure was associated with diabetes prevalence in a large health survey in the Netherlands, strengthening the evidence of air pollution being an important diabetes risk factor. Most consistent associations were observed for NO2 and oxidative potential of PM2.5 measured by the DTT assay. The finding of an association with the oxidative potential of fine particles but not with PM2.5, suggests that particle composition may be important for a potential effect on diabetes.
BACKGROUND: The evidence from observational epidemiological studies of a link between long-term air pollution exposure and diabetes prevalence and incidence is currently mixed. Some studies found the strongest associations of diabetes with fine particles, other studies with nitrogen dioxide and some studies found no associations. OBJECTIVES: Our aim was to investigate associations between long-term exposure to multiple air pollutants and diabetes prevalence in a large national survey in the Netherlands. METHODS: We performed a cross-sectional analysis using the 2012 Dutch national health survey to investigate the associations between the 2009 annual average concentrations of multiple air pollutants (PM10, PM2.5, PM10-2.5, PM2.5 absorbance, OPDTT, OPESR and NO2) and diabetes prevalence, among 289,703 adults. Air pollution exposure was assessed by land use regression models. Diabetes was defined based on a combined measure of self-reported physician diagnosis and medication prescription from an external database. Using logistic regression, we adjusted for potential confounders, including neighborhood- and individual socio-economic status and lifestyle-related risk factors such as smoking habits, alcohol consumption, physical activity and BMI. RESULTS: After adjustment for potential confounders, all pollutants (except PM2.5) were associated with diabetes prevalence. In two-pollutant models, NO2 and OPDTT remained associated with increased diabetes prevalence. For NO2 and OPDTT, single-pollutant ORs per interquartile range were 1.07 (95% CI: 1.05, 1.09) and 1.08 (95% CI: 1.05, 1.10), respectively. Stratified analysis showed no consistent effect modification by any of the included known diabetes risk factors. CONCLUSIONS: Long-term residential air pollution exposure was associated with diabetes prevalence in a large health survey in the Netherlands, strengthening the evidence of air pollution being an important diabetes risk factor. Most consistent associations were observed for NO2 and oxidative potential of PM2.5 measured by the DTT assay. The finding of an association with the oxidative potential of fine particles but not with PM2.5, suggests that particle composition may be important for a potential effect on diabetes.
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