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Effects of diabetes definition on global surveillance of diabetes prevalence and diagnosis: a pooled analysis of 96 population-based studies with 331,288 participants

By August 10, 2015September 24th, 2020No Comments

LINK TO RESEARCH
https://pubmed.ncbi.nlm.nih.gov/26109024/

PUBLICATION
The Lancet Diabetes & Endocrinology

AUTHORS
NCD Risk Factor Collaboration (NCD-RisC)

ABSTRACT
Background: Diabetes has been defined on the basis of different biomarkers, including
fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose
tolerance test (2hOGTT), and HbA1c. We assessed the effect of different
diagnostic definitions on both the population prevalence of diabetes and
the classification of previously undiagnosed individuals as having diabetes
versus not having diabetes in a pooled analysis of data from
population-based health examination surveys in different regions.
Methods: We used data from 96 population-based health examination surveys that had
measured at least two of the biomarkers used for defining diabetes.
Diabetes was defined using HbA1c (HbA1c ≥6·5% or history of diabetes
diagnosis or using insulin or oral hypoglycaemic drugs) compared with
either FPG only or FPG-or-2hOGTT definitions (FPG ≥7·0 mmol/L or 2hOGTT
≥11·1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic
drugs). We calculated diabetes prevalence, taking into account complex
survey design and survey sample weights. We compared the prevalences of
diabetes using different definitions graphically and by regression
analyses. We calculated sensitivity and specificity of diabetes diagnosis
based on HbA1c compared with diagnosis based on glucose among previously
undiagnosed individuals (ie, excluding those with history of diabetes or
using insulin or oral hypoglycaemic drugs). We calculated sensitivity and
specificity in each survey, and then pooled results using a random-effects
model. We assessed the sources of heterogeneity of sensitivity by
meta-regressions for study characteristics selected a priori.
Findings: Population prevalence of diabetes based on FPG-or-2hOGTT was correlated
with prevalence based on FPG alone (r=0·98), but was higher by 2-6
percentage points at different prevalence levels. Prevalence based on HbA1c
was lower than prevalence based on FPG in 42·8% of age-sex-survey groups
and higher in another 41·6%; in the other 15·6%, the two definitions
provided similar prevalence estimates. The variation across studies in the
relation between glucose-based and HbA1c-based prevalences was partly
related to participants’ age, followed by natural logarithm of per person
gross domestic product, the year of survey, mean BMI, and whether the
survey population was national, subnational, or from specific communities.
Diabetes defined as HbA1c 6·5% or more had a pooled sensitivity of 52·8%
(95% CI 51·3-54·3%) and a pooled specificity of 99·74% (99·71-99·78%)
compared with FPG 7·0 mmol/L or more for diagnosing previously undiagnosed
participants; sensitivity compared with diabetes defined based on
FPG-or-2hOGTT was 30·5% (28·7-32·3%). None of the preselected study-level
characteristics explained the heterogeneity in the sensitivity of HbA1c
versus FPG.
Interpretation: Different biomarkers and definitions for diabetes can provide different
estimates of population prevalence of diabetes, and differentially identify
people without previous diagnosis as having diabetes. Using an HbA1c-based
definition alone in health surveys will not identify a substantial
proportion of previously undiagnosed people who would be considered as
having diabetes using a glucose-based test.
Funding: Wellcome Trust, US National Institutes of Health.

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