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Long-term Association of Pericardial Adipose Tissue with Incident Diabetes and Prediabetes: the Coronary Artery Risk Development in Young Adults Study
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Minsuk Oh, Wonhee Cho, Dong Hoon Lee, Kara M. Whitaker, Pamela J. Schreiner, James G. Terry, Joon Young Kim
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Epidemiol Health. 2022;e2023001. Published online December 3, 2022
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DOI: https://doi.org/10.4178/epih.e2023001
[Accepted]
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Abstract
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Abstract
OBJECTIVES We examined if pericardial adipose tissue (PAT) is predictive of prediabetes and type 2 diabetes over time.
METHODS A total of 2,570 adults without prediabetes/diabetes from the Coronary Artery Risk Development in Young Adults Study were followed up over 15 years. PAT volume was measured by computed-tomography scans and new onset of prediabetes/diabetes was examined 5, 10, and 15 years after the PAT measurement. Multivariable Cox regression models were used to examine the association between tertile of PAT and up to 15 years later incident prediabetes/diabetes. The predictive ability of PAT (vs. waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR)) for prediabetes/diabetes was examined by comparing the receiver operating characteristics curve (ROC)-area under the curve (AUC).
RESULTS The highest tertile of PAT was associated with 1.56 (95% CI 1.03, 2.34) times higher rate of diabetes than the lowest tertile; however, no association was found between the highest tertile of PAT and prediabetes in the fully adjusted models, including additional adjustment for BMI or WC. In the fully adjusted models, the ROC-AUC of WC, BMI, WHtR, and PAT in predicting diabetes were not significantly different, whereas the ROC-AUC of WC in predicting prediabetes were higher than that of PAT.
CONCLUSIONS PAT may be a significant predictor of hyperglycemia, but this association may be dependent on the effect of BMI or WC. Additional work is warranted to examine if novel adiposity indicators can suggest advanced and optimal information to the established diagnosis for prediabetes/diabetes.
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Summary
Korean summary
Key Message
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