The effects of ethnicity and age on sex-specific thresholds for the accumulation of visceral adipose tissue in adults
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Higher visceral adipose tissue (VAT) is associated with higher levels of cardiometabolic risks factors. Bosch et al. (1) identified sex-specific total body fat percent thresholds above which VAT increased significantly in a population that was 70% White and 21% Black and ranged in age from 19-47 years. These thresholds were strongly correlated to increased cardiometabolic risk factors. The purposes of this study were to confirm Bosch et al. (1) and examine the effects of ethnicity on the percent body fat threshold in a wider age range. First, data were obtained from Black and White females (n=800) and males (n= 673), 19-47 years of age to identify sex-specific body fat thresholds. Second, an expanded analysis, included data from 1,756 females and 1,455 males, 18-75 years of age who were Asian (18.1%), Black (6.7%), Hispanic (19.8%) and White (55.4%). Piecewise regression was used to identify sex-specific thresholds in the Bosch replication. In the expanded data analysis, it was used to identify sex and ethnicity specific thresholds, whereas the expanded analysis examined sex and ethnicity specific thresholds. Results demonstrated, the threshold for females and males was 36.2% and 25.8%, respectively. The expanded analysis showed that ethnicity affected the percent fat threshold, particularly for Asian females. For females, the thresholds were 28.9% for Asian, 32.1% for Hispanic, 34.2% for White, and 35.6% for Black. For males the thresholds were 22.9% for White, 24.0% for Black, 24.3% for Hispanic, and 25.3% for Asian. While statistical comparison between the two studies and amongst the ethnicities could not be done, this study largely confirms the Bosch et al (1) thresholds. In addition, it shows that the Asian female threshold is lower, but thresholds among the other ethnicities are similar. This research is important because replication of studies with a different sample helps confirm or contradict previous findings and adding other variables, such as ethnicity, helps further explain why differences may occur.