Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c
NCD Risk Factor Collaboration (NCD-RisC). (2023). Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c. Nature Medicine, 29, 2885-2901. https://doi.org/10.1038/s41591-023-02610-2
Julkaistu sarjassa
Nature MedicinePäivämäärä
2023Tekijänoikeudet
© The Author(s) 2023
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.
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Julkaisija
Springer NatureISSN Hae Julkaisufoorumista
1078-8956Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/194641303
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Lisätietoja rahoituksesta
This study was funded by the UK Medical Research Council (grant number MR/V034057/1 to M.E.), the UK Research and Innovation (Research England Policy Support Fund to M.E.) and the US Centers for Disease Control and Prevention (to E.W.G.). B. Zhou is supported by a fellowship from the Abdul Latif Jameel Institute for Disease and Emergency Analytics, funded by a donation from Community Jameel, at Imperial College London. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. For the purpose of open access, the author has applied a Creative Commons Attribution license to the Author Accepted Manuscript version arising from this submission. ...Lisenssi
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