Correlates of pericardial adipose tissue volume using multidetector CT scanning in cardiac patients in China.

Int J Cardiol

Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, 100 Shizi Street Hongshan Rd, Nanjing, Jiangsu Province, China. Electronic address:

Published: October 2017

Background: Pericardial adipose tissue (PAT) is an emerging cardiovascular risk factor, yet much less is understood about PAT volume in Chinese adults, especially in relation to physical activity. The study explores associations between demographic and clinical variables and PAT volume, using multidetector computed tomography (MDCT) scanning in China. We also examined the relationship between PAT volume and coronary artery disease (CAD).

Methods: An observational, correlational study design was used. Chinese (n=163) attended a study visit and underwent MDCT scanning between September 2014 and December 2015.

Results: Participants were 48.5% male and had a mean age of 60.6 (SD 9.4) years. PAT volume was higher (p=0.001) in males than in females. PAT volume was correlated with age (r=0.388, p=0.001), systolic blood pressure (r=0.205, p=0.009), body mass index (r=0.466, p=0.001), high-density cholesterol (r=-0.282, p=0.001), low-density cholesterol (r=0.177, p=0.024), and triglycerides (r=0.248, p=0.001). Both moderate intensity physical activity energy consumption (r=-0.363, p=0.001) and total physical activity (r=-0.290, p=0.001) had inverse relationships with PAT volume. Total sedentary energy consumption was positively related to PAT volume (r=0.266, p=0.001). Multiple regression revealed that age, male gender, BMI, LDL-C and total physical activity energy consumption were significant predictors of PAT volume (R=0.465). The relationship between PAT volume and CAD was found to be significant in the adjusted models.

Conclusions: Age, male gender, BMI, LDL-C and total physical activity energy consumption were significant predictors of PAT volume, and PAT volume itself is a predictor of CAD.

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http://dx.doi.org/10.1016/j.ijcard.2017.06.114DOI Listing

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