G Müller1, J Wellmann1, S Hartwig2, K H Greiser2,3, S Moebus4, K-H Jöckel4, S Schipf5, H Völzke5,6, W Maier7, C Meisinger8, T Tamayo9, W Rathmann9, K Berger1. 1. Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany. 2. Institute of Medical Epidemiology, Biostatistics and Informatics, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany. 3. Division of Cancer Epidemiology, German Cancer Research Centre (DKFZ), Heidelberg, Germany. 4. Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany. 5. Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. 6. German Centre of Cardiovascular Research, Site Greifswald, Germany. 7. Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Health Economics and Health Care Management, Neuherberg, Germany. 8. Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany. 9. Institute of Biometrics and Epidemiology, German Diabetes Centre, Leibniz Centre for Diabetes Research at Heinrich-Heine-University, Düsseldorf, Germany.
Abstract
AIM: To analyse the association of neighbourhood unemployment with incident self-reported physician-diagnosed Type 2 diabetes in a population aged 45-74 years from five German regions. METHODS: Study participants were linked via their addresses at baseline to particular neighbourhoods. Individual-level data from five population-based studies were pooled and combined with contextual data on neighbourhood unemployment. Type 2 diabetes was assessed according to a self-reported physician diagnosis of diabetes. We estimated proportional hazard models (Weibull distribution) in order to obtain hazard ratios and 95% CIs of Type 2 diabetes mellitus, taking into account interval-censoring and clustering. RESULTS: We included 7250 participants residing in 228 inner city neighbourhoods in five German regions in our analysis. The incidence rate was 12.6 per 1000 person-years (95% CI 11.4-13.8). The risk of Type 2 diabetes mellitus was higher in men [hazard ratio 1.79 (95% CI 1.47-2.18)] than in women and higher in people with a low education level [hazard ratio 1.55 (95% CI 1.18-2.02)] than in those with a high education level. Independently of individual-level characteristics, we found a higher risk of Type 2 diabetes mellitus in neighbourhoods with high levels of unemployment [quintile 5; hazard ratio 1.72 (95% CI 1.23-2.42)] than in neighbourhoods with low unemployment (quintile 1). CONCLUSIONS: Low education level and high neighbourhood unemployment were independently associated with an elevated risk of Type 2 diabetes mellitus. Studies examining the impact of the residential environment on Type 2 diabetes mellitus will provide knowledge that is essential for the identification of high-risk populations.
AIM: To analyse the association of neighbourhood unemployment with incident self-reported physician-diagnosed Type 2 diabetes in a population aged 45-74 years from five German regions. METHODS: Study participants were linked via their addresses at baseline to particular neighbourhoods. Individual-level data from five population-based studies were pooled and combined with contextual data on neighbourhood unemployment. Type 2 diabetes was assessed according to a self-reported physician diagnosis of diabetes. We estimated proportional hazard models (Weibull distribution) in order to obtain hazard ratios and 95% CIs of Type 2 diabetes mellitus, taking into account interval-censoring and clustering. RESULTS: We included 7250 participants residing in 228 inner city neighbourhoods in five German regions in our analysis. The incidence rate was 12.6 per 1000 person-years (95% CI 11.4-13.8). The risk of Type 2 diabetes mellitus was higher in men [hazard ratio 1.79 (95% CI 1.47-2.18)] than in women and higher in people with a low education level [hazard ratio 1.55 (95% CI 1.18-2.02)] than in those with a high education level. Independently of individual-level characteristics, we found a higher risk of Type 2 diabetes mellitus in neighbourhoods with high levels of unemployment [quintile 5; hazard ratio 1.72 (95% CI 1.23-2.42)] than in neighbourhoods with low unemployment (quintile 1). CONCLUSIONS: Low education level and high neighbourhood unemployment were independently associated with an elevated risk of Type 2 diabetes mellitus. Studies examining the impact of the residential environment on Type 2 diabetes mellitus will provide knowledge that is essential for the identification of high-risk populations.
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