Phenotypes of prediabetes and metabolic risk in Caucasian youths with overweight or obesity
Purpose To assess the prevalence of pre-diabetes phenotypes, i.e., impaired fasting glucose (IFG), impaired glucose tolerance (IGT), increased HbA1c (IA1c), and their association with metabolic profile and atherogenic lipid profile in youths with overweight/obesity (OW/OB). Methods This cross-sectio...
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Veröffentlicht in: | Journal of endocrinological investigation 2022-09, Vol.45 (9), p.1719-1727 |
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Sprache: | eng |
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Zusammenfassung: | Purpose
To assess the prevalence of pre-diabetes phenotypes, i.e., impaired fasting glucose (IFG), impaired glucose tolerance (IGT), increased HbA1c (IA1c), and their association with metabolic profile and atherogenic lipid profile in youths with overweight/obesity (OW/OB).
Methods
This cross-sectional study analyzed data of 1549 youths (5–18 years) with OW/OB followed in nine Italian centers between 2016 and 2020. Fasting and post-load measurements of glucose, insulin, and HbA1c were available. Insulin resistance (IR) was estimated by HOMA-IR and insulin sensitivity (IS) by reciprocal of fasting insulin. The atherogenic lipid profile was assessed by triglycerides-to-HDL ratio or cholesterol-to-HDL ratio. Insulinogenic index was available in 939 youths, in whom the disposition index was calculated.
Results
The prevalence of overall pre-diabetes, IFG, IGT and IA1c was 27.6%, 10.2%, 8% and 16.3%, respectively. Analyzing each isolated phenotype, IGT exhibited two- to three-fold higher odds ratio of family history of diabetes, and worse metabolic and atherogenic lipid profile vs normoglycemic youths; IFG was associated only with IR, while IA1c showed a metabolic and atherogenic lipid profile intermediate between IGT and IFG.
Conclusion
Prevalence of pre-diabetes was high and IA1c was the most prevalent phenotype in Italian youths with OW/OB. The IGT phenotype showed the worst metabolic and atherogenic lipid profile, followed by IA1c. More studies are needed to assess whether HbA1c may help improving the prediction of diabetes. |
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ISSN: | 1720-8386 0391-4097 1720-8386 |
DOI: | 10.1007/s40618-022-01809-3 |