Standardized disease-related measures in diabetes research: Results from a global consensus process

Meena Daivadanam¹Kristi Sidney Annerstedt²Rajesh Vedanthan³Louise Maple-Brown^4,5Gary Parker⁶Maia Ingram⁷Gina Agarwal⁸Josefien Van Olmen⁹Renae Kirkham⁴Kirsten Bobrow¹⁰Francisco Gonzalez-Salazar¹¹Fanny Monnet^12,9*

• ¹Global health and migration unit, Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
• ²Department of Global Public Health, Karolinska Institutet (KI), Stockholm, Stockholm, Sweden
• ³Department of Population Health, Grossman School of Medicine, New York University, New York, United States
• ⁴Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia
• ⁵Endocrinology Department, Royal Darwin Hospital, Darwin, Australia
• ⁶Global Alliance for Chronic Diseases, London, United Kingdom
• ⁷Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, United States
• ⁸Department of Family Medicine, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
• ⁹Primary and Interdisciplinary Care Antwerp (ELIZA), Department of Family Medicine and Population Health, University of Antwerp, Antwerp, Antwerp, Belgium
• ¹⁰Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, Western Cape, South Africa
• ¹¹Division of Health Sciences, University of Monterrey, Monterrey, Mexico
• ¹²Center for Population, Family and Health, Department of Sociology, University of Antwerp, Antwerp, Belgium

BackgroundA lack of disease-related consensus measures for type 2 diabetes interventions is a barrier to the comparison of interventions across a variety of contexts, as well as to implementation and scale-up. The purpose of this study was to use an expert consensus approach to select disease-related measures for type 2 diabetes in order to facilitate cross-contextual research, as well as the implementation and scaling-up of initiatives.MethodsThe study was conducted using a two-phased cross-sectional design consisting of an online survey among research experts in 17 diabetes projects working in a global context, followed by an online modified Delphi panel comprised of reviewers with domain-specific expertise from different income settings who were not survey participants.Results Out of a total of 153 measures from 11 domains assessed, 49 measures were classified as core, 58 as optional and 46 excluded. The domains and measures spanned several categories including demographics, medical history, medication adherence, health behaviours, anthropometric measures, biochemical measures, and quality-of-life-related issues.ConclusionsThe core dataset of selected measures in type 2 diabetes may provide a standardized approach for determining which data should be collected, and can facilitate transnational comparisons between or within implementation projects to advance global diabetes research.