Epidemiol Health.  2023;45(1):e2023001. 10.4178/epih.e2023001.

Long-term association of pericardial adipose tissue with incident diabetes and prediabetes: the Coronary Artery Risk Development in Young Adults Study

Affiliations
  • 1Department of Public Health, Baylor University, Waco, TX, USA
  • 2Department of Exercise Science, Syracuse University, Syracuse, NY, USA
  • 3Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
  • 4Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
  • 5Department of Health and Human Physiology, Department of Epidemiology, University of Iowa, Iowa City, IA, USA
  • 6Division of Epidemiology and Community Health, University of Minnesota, Twin Cities, MN, USA
  • 7Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA

Abstract


OBJECTIVES
We examined whether pericardial adipose tissue (PAT) is predictive of prediabetes and type 2 diabetes over time.
METHODS
In total, 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 the new onset of prediabetes/diabetes was examined 5 years, 10 years, and 15 years after the PAT measurements. Multivariable Cox regression models were used to examine the association between the tertile of PAT and incident prediabetes/diabetes up to 15 years later. 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 area under the receiver operating characteristic curve (AUC).
RESULTS
The highest tertile of PAT was associated with a 1.56 times (95% confidence interval [CI], 1.03 to 2.34) 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 AUCs of WC, BMI, WHtR, and PAT for predicting diabetes were not significantly different, whereas the AUC of WC for predicting prediabetes was higher than that of PAT.
CONCLUSIONS
PAT may be a significant predictor of hyperglycemia, but this association might depend on the effect of BMI or WC. Additional work is warranted to examine whether novel adiposity indicators can suggest advanced and optimal information to supplement the established diagnosis for prediabetes/diabetes.

Keyword

Adipose tissue; Obesity; Prediabetes; Diabetes
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