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Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c
Authors
Carlos Aguilar Salinas
Noor Ani Ahmad
+37 more
Ranjit Mohan Anjana
James Bennett
Rodrigo Carrillo-Larco
Melanie Cowan
Goodarz Danaei
Kairat Davletov
Majid Ezzati
Farshad Farzadfar
Cilcerio González-Villalpando
Edward Gregg
Rachel Heap
Giuseppina Imperatore
Andre Pascal Kengne
Young-Ho Khang
Hyeon Chang Kim
Tiina Laatikainen
Avula Laxmaiah
Victor Lhoste
Yuan Lu
Jean Claude Mbanya
Anu Mishra
Chris Paciorek
Meda Pavkov
Nowell Phelps
Ambady Ramachandran
Archie Rayner
Leanne Riley
Stefan Savin
Jonathan Shaw
Kate Sheffer
Rosie Singleton
Gretchen Stevens
Stephen Vander Hoorn
KM Venkat Narayan
Alisha Wade
Tomasz Zdrojewski
Bin Zhou
Publication date
1 January 2023
Publisher
Nature Research
Doi
Cite
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. © 2023, The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Fadi Charchar" is provided in this record*
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Spiral - Imperial College Digital Repository
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oai:spiral.imperial.ac.uk:1004...
Last time updated on 19/10/2023
Federation ResearchOnline
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vital:19129
Last time updated on 31/05/2024