AUTHOR=Daivadanam Meena , Annerstedt Kristi Sidney , Vedanthan Rajesh , Maple-Brown Louise , Parker Gary , Ingram Maia , Agarwal Gina , van Olmen Josefien , Kirkham Renae , Bobrow Kirsten , Gonzalez-Salazar Francisco , Monnet Fanny ,  GACD Diabetes Data Standardization Working Group , Berggreen-Clausen Aravinda , Mavrogianni Christina , Guwatudde David , Kapoor Deksha , Fottrell Edward , Cornejo Elsa , De Man Jeroen , Lazo-Porras Maria , Silva Ninha , Zhang Puhong , Iotova Violeta , Tao Xuanchen 

TITLE=Standardized disease-related measures in diabetes research: results from a global consensus process

JOURNAL=Frontiers in Public Health

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1580416

DOI=10.3389/fpubh.2025.1580416

ISSN=2296-2565

ABSTRACT=BackgroundA lack of disease-related consensus measures for type 2 diabetes interventions is a barrier to comparing interventions across various contexts, as well as to implementation and scale-up. This study aimed to use an expert consensus approach to select disease-related measures for type 2 diabetes 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.ResultsOut of 153 measures from 11 domains assessed, 49 were classified as core, 58 as optional, and 46 were excluded. The domains and measures spanned several categories, including demographics, medical history, medication adherence, health behaviors, anthropometric measures, biochemical measures, and quality-of-life-related issues.ConclusionThe core dataset of selected measures in type 2 diabetes may provide a standardized approach for determining which data should be collected. This can facilitate transnational comparisons between or within implementation projects to advance global diabetes research.