Toggle Main Menu Toggle Search

Open Access padlockePrints

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

Lookup NU author(s): Professor Dame Louise Robinson, Dr Andrew KingstonORCiD, Kate Sheffer

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2023, The Author(s).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.


Publication metadata

Author(s): Zhou B, et al., NCD Risk Factor Collaboration (NCD-RisC), Robinson A, Kingston A, Sheffer K

Publication type: Article

Publication status: Published

Journal: Nature Medicine

Year: 2023

Volume: 29

Pages: 2885-2901

Online publication date: 09/11/2023

Acceptance date: 25/09/2023

Date deposited: 29/11/2023

ISSN (print): 1078-8956

ISSN (electronic): 1546-170X

Publisher: Nature Research

URL: https://doi.org/10.1038/s41591-023-02610-2

DOI: 10.1038/s41591-023-02610-2

Data Access Statement: Data used in this research are governed by data-sharing protocols of participating studies. Contact information for data providers can be obtained from www.ncdrisc.org and https://doi.org/10.5281/zenodo.8169145. The computer code for the log-binomial regression in this work is available at www.ncdrisc.org and https://doi.org/10.5281/zenodo.8169145.

PubMed id: 37946056


Altmetrics

Altmetrics provided by Altmetric


Funding

Funder referenceFunder name
Community Jameel
Medical Research Council
MR/V034057/1
UK Research and Innovation
US Centers for Disease Control and Prevention

Share