[Estimate of human visceral adipose area and abdominal subcutaneous adipose area in obese Chinese by simple anthropometric parameters].
OBJECTIVE
To explore the relationship of simple anthropometric parameters with abdominal subcutaneous adipose area (SA) with visceral adipose area (VA), and to generate equations predicting SA and VA by simple anthropometric parameters.


METHODS
SA and VA were measured with computed tomography (CT) in 309 human subjects (male 88, female 221). Weight (W), height (H), body mass index (BMI), waist circumference (WC), abdominal circumference (AC), hip circumference (HC) and waist to hip ratio (WHR) were also measured. Multiple stepwise regression analysis was used to generate equations for predicting SA and VA from age and simple anthropometric parameters of 259 subjects (80%, including 181 women and 78 men) randomly selected from the overall sample. These equations were then cross-validated in the remaining 50 subjects (20%, including 40 women and 10 men).


RESULTS
The best regression equations for male were developed for predicting SA and VA, and the explanatory variables included WC and age. In women, the equation for predicting SA included AC and BMI; the equation for predicting VA included WHR and W and age. In the cross-validation study, the differences between predicted and observed values of VA in men and women were -7.83% and -6.94%, respectively; the differences between predicted and observed values of SA in men and women were 8.01% and 0.69%, respectively. The goodness of fit between predicted and observed values is good.


CONCLUSIONS
The absolute amount of human VA and SA in obese Chinese can be predicted from anthropometric measurements.
Ran
Xingwu
X
Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu 610041, China.
Li
Xiaosong
X
Tong
Nanwei
N
Li
Qifu
Q
Tang
Baode
B
Li
Xiujun
X
D034841:Abdominal Cavity; D034861:Abdominal Wall; D000273:Adipose Tissue; D000293:Adolescent; D000328:Adult; D000368:Aged; D000886:Anthropometry; D015992:Body Mass Index; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000473:pathology*; D012044:Regression Analysis; D040521:Subcutaneous Tissue