Social networks in diabetes epidemiology: The hidden layer between individuals and populations

Epidemiology
16:00HRS
20Apr2017
Location
Green and Blue Lecture Hall, UMCU
Speaker
Prof Daniel Witte

Daniel Rinse Witte, MD, PhD
Professor of Diabetes Epidemiology (Danish Diabetes Academy)

Short cv
Daniel started his career at the University of Utrecht, the Netherlands, where he studied medicine and completed a PhD in clinical epidemiology with a thesis focused on the non-invasive assessment of endothelial function in patients at high cardiovascular risk. He subsequently worked for 5 years as a post-doctoral clinical research fellow at the department of Epidemiology and Public Health, University College London, UK. His work there focused on screening models for type 2 diabetes and the analysis of risk factors for diabetes and its complications based on several large cohorts such as EURODIAB-Prospective Complications Study (Type 1 Diabetes) and the Whitehall II study (Type 2 Diabetes).

Between 2008 and 2012 Daniel was head of the diabetes epidemiology group at Steno Diabetes Center in Gentofte, Denmark. In this position he further developed his main research interests: the study of the pathophysiological mechanisms which determine the transition from normal glucose control via pre-diabetes to diabetes and the early stages of its complications at the level of large populations. He has a special focus on longitudinal trajectory analyses and analysis of clustering of diabetic complications. His work uses data from several large longitudinal studies, such as the Inter99 and ADDITION trials, the ADDITION-PRO and Whitehall II cohorts, as well as routine medical and population registers. Daniel has a strong interest in the use of routine registers to enrich cohort datasets with a view to studying the long-term consequences of dysglycaemia, diabetes risk and the clinical management of diabetes.

Between 2012 and 2014 Daniel was the Principal Investigator for the Luxembourg Cohort at the Luxembourg Institute of Health, Strassen, Luxembourg, tasked with the design and concept development for a national cohort in Luxembourg. In January 2015 he was appointed Professor of Diabetes Epidemiology at Aarhus University, Denmark; based on a grant from the Danish Diabetes Academy. He teaches at national and international courses at the post-graduate level and supervises several PhD students. Daniel is a member of the Danish Diabetes Academy and of the Steering Committees of the ADDITION-Denmark and ADDITION-Europe studies.

Abstract
Study designs and analysis approaches in epidemiology have traditionally focused on exposures and health outcomes of individuals assumed to be independent of each other, or of populations assumed to be composed of independent individuals. Social networks have generally been ignored but form an important intermediate layer connecting the individual and the population. New insights, methods and data structures now make it possible to study social network effects on the clustering and spread of chronic disease risk factors in unprecedented detail.

This lecture will first explore how the epidemiological/statistical assumption of independent observations has led chronic disease epidemiologists to develop a blind spot for social network phenomena. Examples of socially mediated spread of chronic diseases will be used to illustrate the potential epidemiological and public health impact of social networks, and to map out the current level of evidence in the field. Finally, preliminary results from analyses of the Danish Social Network Database will be presented, highlighting the possibilities for register-based analysis of social networks and health in Nordic countries.

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