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Müller, G.* ; Wellmann, J.* ; Hartwig, S.* ; Greiser, K.H.* ; Moebus, S.* ; Jöckel, K.-H.* ; Schipf, S.* ; Völzke, H.* ; Maier, W. ; Meisinger, C. ; Tamayo, T.* ; Rathmann, W.* ; Berger, K.*

Association of neighbourhood unemployment rate with incident type 2 diabetes mellitus in five German regions.

Diabetic Med. 32, 1017-1022 (2015)

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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.

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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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