Source
Center for Cancer Prevention (CPO-Piemonte), Torino, Italy, Human Genetics Foundation (HuGeF), Torino, Italy, Department of Public Health and Clinical Medicine, Umea University, Sweden, Department of Environmental Medicine and Public Health, University of Padova, Italy, Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública-CIBERESP), Spain, Murcia Regional Health Authority, Murcia, Spain, Division of Human Nutrition, Section of Nutrition and Epidemiology, University of Wageningen, The Netherlands, Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute (ISPO), Florence, Italy, Navarre Public Health Institute, Pamplona, Spain, Public Health Department of Gipuzkoa, Basque Government, San Sebastián, Spain, Inserm (Institut National de la Santé et de la Recherche Médicale), Centre for Research in Epidemiology and Population Health (CESP), France, Paris-South University, Villejuif Cedex, France, Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands, Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, UK, MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK, Lund University Diabetes Center, Malmö, Sweden, Department of Public Health and Clinical Medicine, Umea University, Sweden, Harvard School of Public Health, Boston, MA, USA, School of Public Health, Imperial College London, London, UK, Social and Environmental Health Research, London School of Hygiene and Tropical Medicine, UK, Unit of Nutrition, Environment and Cancer, Catalan Institute of Oncology (ICO), Barcelona, Spain, Danish Cancer Society Research Center, Copenhagen, Denmark, Department of Epidemiology, German Institute of Human Nutrition, Bergholz-Rehbrücke, Germany, Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany, Department of Clinical Gerontology, Addenbrooke's Hospital, Cambridge, UK, Unit of Preventive Medicine and Public Health School of Medicine, Murcia, Spain, Department of Psychosocial Cancer Research, Institute of Cancer Epidemiology, Danish Cancer Society, Copenhagen, Denmark, Department of Epidemiology, School of Public Health, Aarhus University, Aaarhus, Denmark, Nutritional Epidemiology Unit, Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy, Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy, Asturias Health & Health Care Council, Oviedo, Spain, Dietary Exposure Assessment Group, International Agency for Research on Cancer, Lyon, France, Andalusian School of Public Health, Granada, Spain, National Institute for Public Health and the Environment, Centre for Prevention and Health Services Research, Bilthoven, The Netherlands, Cancer Registry and Histopathology Unit, Civile M.P. Arezzo Hospital, Ragusa, Italy, MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK, Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK and MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
Abstract
BACKGROUND:
Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases worldwide. In high-income countries, low socioeconomic status seems to be related to a high incidence of T2DM, but very little is known about the intermediate factors of this relationship.Method We performed a case-cohort study in eight Western European countries nested in the EPIC study (n = 340 234, 3.99 million person-years of follow-up). A random sub-cohort of 16 835 individuals and a total of 12 403 incident cases of T2DM were identified. Crude and multivariate-adjusted hazard ratios (HR) were estimated for each country and pooled across countries using meta-analytical methods. Age-, gender- and country-specific relative indices of inequality (RII) were used as the measure of educational level and RII tertiles were analysed.
RESULTS:
Compared with participants with a high educational level (RII tertile 1), participants with a low educational level (RII tertile 3) had a higher risk of T2DM [HR: 1.77, 95% confidence interval (CI): 1.69-1.85; P-trend < 0.01]. The HRs adjusted for physical activity, smoking status and propensity score according to macronutrient intake were very similar to the crude HR (adjusted HR: 1.67, 95% CI: 1.52-1.83 in men; HR: 1.88, 95% CI: 1.73-2.05 in women). The HRs were attenuated only when they were further adjusted for BMI (BMI-adjusted HR: 1.36, 95% CI: 1.23-1.51 in men; HR: 1.32, 95% CI: 1.20-1.45 in women).
CONCLUSION:
This study demonstrates the inequalities in the risk of T2DM in Western European countries, with an inverse relationship between educational level and risk of T2DM that is only partially explained by variations in BMI.