Is the Obesity Paradox in Type 2 Diabetes Due to Artefacts of Biases? An Analysis of Pooled Cohort Data from the Heinz Nixdorf Recall Study and the Study of Health in Pomerania

Bernd Kowall,1 Andreas Stang,1,2 Raimund Erbel,3 Susanne Moebus,4 Astrid Petersmann,5 Antje Steveling,6 Karl-Heinz Jöckel,3 Henry Völzke7,8 1Center of Clinical Epidemiology, Institute for Medical Informatics, Biometry and Epidemiology, Medical Faculty, University Duisburg-Essen, Essen, Germany; 2School of Public Health, Department of Epidemiology, Boston University, Boston, MA 02118, USA; 3Institute for Medical Informatics, Biometry and Epidemiology, University Clinic Essen, University Duisburg-Essen, Essen, Germany; 4Center for Urban Epidemiology, Institute for Medical Informatics, Biometry and Epidemiology, University Clinic Essen, Essen, Germany; 5Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany; 6Department of Internal Medicine, University Medicine Greifswald, Greifswald, Germany; 7Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; 8German Center for Diabetes Research, Site Greifswald, Greifswald, GermanyCorrespondence: Bernd KowallCenter of Clinical Epidemiology, c/o Institute of Medical Informatics, Biometry and Epidemiology (IMIBE), Hufelandstraße 55, Essen 45147, GermanyTel +49-201-92239-295Fax +49-201-92239-333Email bernd.kowall@uk-essen.deAims/Hypothesis: There is controversy on whether an obesity paradox exists in type 2 diabetes, ie, that mortality is lowest in overweight or obesity. We examined the role of potential biases in the obesity paradox.Methods: From two regional population-based German cohort studies – the Heinz Nixdorf Recall Study and the Study of Health in Pomerania (baseline examinations 2000– 2003/1997– 2001) – 1187 persons with diabetes at baseline were included (mean age 62.6 years, 60.9% males). Diabetes was ascertained by self-report of physician’s diagnosis, antidiabetic medication, fasting/random glucose or haemoglobin A1c. Mortality data were assessed for up to 17.7 years. We used restricted cubic splines and Cox regression models to assess associations between body mass index (BMI) and mortality. Sensitivity analyses addressed, inter alia, exclusion of early death cases, of persons with cancer, kidney disease or with history of cardiovascular diseases, and of ever smokers. Furthermore, we examined the role of treatment bias and collider bias for the obesity paradox.Results: In spline models, mortality risk was lowest for BMI at about 31 kg/m2. Sensitivity analyses carried out one after another had hardly any impact on this result. In our cohort, persons with diabetes and BMI ≥ 30 kg/m2 did not have better treatment than non-obese patients, and we found that collider bias played only a minor role in the obesity paradox.Conclusion: In a cohort of 1187 persons with diabetes, mortality risk was lowest in persons with moderate obesity. We cannot explain this result by a variety of sensitivity analyses.Keywords: collider bias, diabetes, mortality, obesity paradox, overweight