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Diabetes incidence and long-term exposure to air pollution: a cohort study. Zorana Jovanovic Andersen 14.09.2011 ISEE. Diabetes. Diabetes epidemic , cased in large part by obesity epidemic and physical inactivity
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Diabetes incidence and long-termexposure to air pollution: a cohortstudy Zorana Jovanovic Andersen 14.09.2011 ISEE
Diabetes • Diabetes epidemic, cased in large part by obesityepidemic and physicalinactivity • Metabolicdisease, highbloodsugar, type-2, insulin resistance • In USA
Background: Diabetes & Air Pollution • Diabetes established modifier of a link between air pollution andCVD (inflammation, endothelial dysfunction, prothrombotic changes, altered heart rate variability) • Biological mechanismprolonged exposure to air pollution involves inflammation in adipose tissue, increased blood glucose levels, insulin resistance, glucose intolerance in mice • Short-term exposure to elevated air pollution linked to increased risk of diabetes mortality and hospitalization
Aim of thisstudy • We studied the association between traffic-related air pollution levels at the residence and the risk for diabetes in an elderly Danish cohort, and tested for an effect modification by lifestyle, education, and co-morbid conditions.
Methods - Cohort • Danish Diet, Cancer and Health cohort • 57 053 subjects, Copenhagen and Aarhus • Interviewed in 1993-1997 (baseline) • Age 50-65 years • Linkage to Central Population Registry and Danish Address Database - residential address history (1971) • Linkage to Danish National Diabetes Register (1995) for assessment of health outcome
Danish Diabetes Register • The NDR was established by linking existing nationwide administrative records in the Danish healthcare system
Danish Diabetes Register • Results of blood glucose measurements are not included • 50-60% of the patients > 1 inclusion criterion • Not possible to distinguish type 1 and type 2 diabetes • Due to different dates of initiation of the underlying registers and accumulation of prevalent cases, only incidence values after 1 January 1995 were found to be reliable • Incidence of diabetes was defined as the earliest record in the diabetes register occurring after 1 January 1995, between baseline (1993-1997) and 27 June 2006.
Methods – Air Pollution Exposure • AirGIS dispersion model, sum of: 1) regionalbackground, 2) urbanbackground, & 3) streetlevelcontribution • Input for AirGIS model • Street/building geometry • Street network and traffic data • Meteorology Traffic counts, emission factors, density, speed, types, variation patterns over time GIS Mapsbuildingheight, streetwidth, opensector
Methods – Air Pollution Exposure • AirGIS Model output: • Annual mean NO2 /NOx concentrations at individual address Flow and dispersion inside a street canyon
Methods – Statistical Model • Cox proportional hazards model, left truncation at age at baseline, and right censoring at age at hospital admission for ACS, death, emigration, or 27 June 2006 • NO2 /NOx ,time-dependent variables, the estimates per IQR • Confounders: smoking (status, intensity, duration, ETS), occupational exposures, BMI, educational level, fruit consumption • Effect modification: interaction term, Wald-test • Spline (rcs) in R, for dose-repsonse curve
Results • Exclusions: • 571 cancer before baseline • 962 missing address or geocode • 1 341 missing address • 1 147 self-reported diabetes at baseline • 173 diabetes record in the NDR before baseline • 6 with diabetes between baseline and 01.01.1995 • 1 035 missing covariates Original Cohort Final Study Population ”All Diabetes” 7.8% diabetes originallyincluded in NDR Incidence rate: 8 per1 000 person-years Exclusion of 1163 included solely due to blood glucose measurements 5.5% diabetes ‘strict definition’ Incidence rate: 5.7 per 1 000 person-years ”Confirmed Diabetes”
Results: Main Analysis Model WITHOUT waist-to-hip ratio: 1.05 (1.02-1.10) Model WITHOUT BMI and waist-to-hip ratio: 1.08 (1.04-1.12)
Conclusions • The risk for diabetes was weakly positively associated with increasing mean levels of traffic-related air pollution at the residence • The risk was highest in non-smokers and physically active people, those with a-priori low risk