Sabine Schipf1, Till Ittermann1, Teresa Tamayo2, Rolf Holle3, Michaela Schunk3, Werner Maier3, Christine Meisinger4, Barbara Thorand4, Alexander Kluttig5, Karin Halina Greiser6, Klaus Berger7, Grit Müller7, Susanne Moebus8, Uta Slomiany8, Andrea Icks9, Wolfgang Rathmann2, Henry Völzke10. 1. Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. 2. Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University, Düsseldorf, Germany. 3. Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Neuherberg, Germany. 4. Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Institute of Epidemiology II, Neuherberg, Germany German Center for Diabetes Research (DZD), Neuherberg, Germany. 5. Institute of Medical Epidemiology, Biostatistics and Informatics, Martin-Luther-University Halle-Wittenberg, Halle(Saale), Germany. 6. Institute of Medical Epidemiology, Biostatistics and Informatics, Martin-Luther-University Halle-Wittenberg, Halle(Saale), Germany Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany. 7. Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany. 8. Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Germany. 9. Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University, Düsseldorf, Germany Department of Public Health, Faculty of Medicine, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany. 10. Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany German Center of Cardiovascular Research, Greifswald, Germany.
Abstract
BACKGROUND: Population-based data are paramount to investigate the long-term course of diabetes, for planning in healthcare and to evaluate the cost-effectiveness of primary prevention. We analysed regional differences in the incidence of self-reported type 2 diabetes mellitus in Germany. METHODS: Data of participants (baseline age 45-74 years) from five regional population-based studies conducted between 1997 and 2010 were included (mean follow-up 2.2-7.1 years). The incidence of self-reported type 2 diabetes mellitus at follow-up was compared. The incidence rates per 1000 person-years (95% CI) and the cumulative incidence (95% CI) from regional studies were directly standardised to the German population (31 December 2007) and weighted by inverse probability weights for losses to follow-up. RESULTS: Of 8787 participants, 521 (5.9%) developed type 2 diabetes mellitus corresponding to an incidence rate of 11.8/1000 person-years (95% CI 10.8 to 12.9). The regional incidence was highest in the East and lowest in the South of Germany with 16.9 (95% CI 13.3 to 21.8) vs 9.3 (95% CI 7.4 to 11.1)/1000 person-years, respectively. The incidence increased with age and was higher in men than in women. CONCLUSIONS: The incidence of self-reported type 2 diabetes mellitus shows regional differences within Germany. Prevention measures need to consider sex-specific differences and probably can be more efficiently introduced toward those regions in need. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
BACKGROUND: Population-based data are paramount to investigate the long-term course of diabetes, for planning in healthcare and to evaluate the cost-effectiveness of primary prevention. We analysed regional differences in the incidence of self-reported type 2 diabetes mellitus in Germany. METHODS: Data of participants (baseline age 45-74 years) from five regional population-based studies conducted between 1997 and 2010 were included (mean follow-up 2.2-7.1 years). The incidence of self-reported type 2 diabetes mellitus at follow-up was compared. The incidence rates per 1000 person-years (95% CI) and the cumulative incidence (95% CI) from regional studies were directly standardised to the German population (31 December 2007) and weighted by inverse probability weights for losses to follow-up. RESULTS: Of 8787 participants, 521 (5.9%) developed type 2 diabetes mellitus corresponding to an incidence rate of 11.8/1000 person-years (95% CI 10.8 to 12.9). The regional incidence was highest in the East and lowest in the South of Germany with 16.9 (95% CI 13.3 to 21.8) vs 9.3 (95% CI 7.4 to 11.1)/1000 person-years, respectively. The incidence increased with age and was higher in men than in women. CONCLUSIONS: The incidence of self-reported type 2 diabetes mellitus shows regional differences within Germany. Prevention measures need to consider sex-specific differences and probably can be more efficiently introduced toward those regions in need. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Entities:
Keywords:
Cohort studies; Epidemiological methods; Epidemiology of diabetes; GEOGRAPHY
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