Definitions of Metabolic Health and Risk of Future Type 2 Diabetes in BMI Categories: A Systematic Review and Network Meta-analysis.
OBJECTIVE
Various definitions of metabolic health have been proposed to explain differences in the risk of type 2 diabetes within BMI categories. The goal of this study was to assess their predictive relevance.


METHODS
We performed systematic searches of MEDLINE records for prospective cohort studies of type 2 diabetes risk in categories of BMI and metabolic health. In a two-stage meta-analysis, relative risks (RRs) specific to each BMI category were derived by network meta-analysis and the resulting RRs of each study were pooled using random-effects models. Hierarchical summary receiver operating characteristic curves were used to assess predictive performance.


RESULTS
In a meta-analysis of 140,845 participants and 5,963 incident cases of type 2 diabetes from 14 cohort studies, classification as metabolically unhealthy was associated with higher RR of diabetes in all BMI categories (lean RR compared with healthy individuals 4.0 [95% CI 3.0-5.1], overweight 3.4 [2.8-4.3], and obese 2.5 [2.1-3.0]). Metabolically healthy obese individuals had a high absolute risk of type 2 diabetes (10-year cumulative incidence 3.1% [95% CI 2.6-3.5]). Current binary definitions of metabolic health had high specificity (pooled estimate 0.88 [95% CI 0.84-0.91]) but low sensitivity (0.40 [0.31-0.49]) in lean individuals and satisfactory sensitivity (0.81 [0.76-0.86]) but low specificity (0.42 [0.35-0.49]) in obese individuals. However, positive (<3.3 in all BMI categories) and negative (>0.4) likelihood ratios were consistent with insignificant to small improvements in prediction.


CONCLUSIONS
Although individuals classified as metabolically unhealthy have a higher RR of type 2 diabetes compared with individuals classified as healthy in all BMI categories, current binary definitions of metabolic health have limited relevance to the prediction of future type 2 diabetes.
MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, U.K.
Luca A
LA
Lotta
MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, U.K. Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Ali
A
Abbasi
MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, U.K.
Stephen J
SJ
Sharp
Genetics, GlaxoSmithKline Research and Development, Stevenage, U.K.
Anna-Stina
AS
Sahlqvist
Genetics, GlaxoSmithKline, King of Prussia, PA.
Dawn
D
Waterworth
Cardiovascular and Metabolic Diseases Research Unit, Pfizer Worldwide Research and Development, Cambridge, MA.
Julia M
JM
Brosnan
MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, U.K.
Robert A
RA
Scott
MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, U.K.
Claudia
C
Langenberg
MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, U.K. nick.wareham@mrc-epid.cam.ac.uk.
Nicholas J
NJ
Wareham
D015992:Body Mass Index; D001835:Body Weight; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology*; D006801:Humans; D009765:Obesity / Q000453:epidemiology; D050177:Overweight / Q000453:epidemiology; D011379:Prognosis; D012306:Risk