Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023001%3A_____%2F23%3A00084432" target="_blank" >RIV/00023001:_____/23:00084432 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14310/23:00133735 RIV/00064190:_____/23:10001074
Result on the web
<a href="http://www.nature.com/articles/s41591-023-02610-2" target="_blank" >http://www.nature.com/articles/s41591-023-02610-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41591-023-02610-2" target="_blank" >10.1038/s41591-023-02610-2</a>
Alternative languages
Result language
angličtina
Original language name
Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c
Original language description
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).
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30202 - Endocrinology and metabolism (including diabetes, hormones)
Result continuities
Project
—
Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Nature medicine
ISSN
1078-8956
e-ISSN
1546-170X
Volume of the periodical
29
Issue of the periodical within the volume
November
Country of publishing house
US - UNITED STATES
Number of pages
33
Pages from-to
"2885–2901"
UT code for WoS article
001103103800003
EID of the result in the Scopus database
2-s2.0-85176735771