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Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

Zhou, B; Sheffer, KE; Bennett, JE; Gregg, EW; Danaei, G; Singleton, RK; Shaw, JE; Mishra, A; Lhoste, VPF; Carrillo-Larco, RM; et al. 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Zhang, Z-Y; Zholdin, B; Zimmet, P; Zitt, E; Zoghlami, N; Cisneros, JZ; Ezzati, M (2023) Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c. NATURE MEDICINE, 29 (11). pp. 2885-2901. ISSN 1078-8956 https://doi.org/10.1038/s41591-023-02610-2
SGUL Authors: Whincup, Peter Hynes

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Abstract

Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance.

Item Type: Article
Additional Information: Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2023
Keywords: 11 Medical and Health Sciences, Immunology
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: NATURE MEDICINE
ISSN: 1078-8956
Dates:
DateEvent
9 November 2023Published
25 September 2023Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
MR/V034057/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
Web of Science ID: WOS:001103103800003
URI: https://openaccess.sgul.ac.uk/id/eprint/116169
Publisher's version: https://doi.org/10.1038/s41591-023-02610-2

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