Equation-derived body fat percentage indicates metabolic abnormalities among normal-weight adults in a rural Chinese population.
OBJECTIVE
Obesity classification using body mass index (BMI) may miss subjects with elevated body fat percentage (BF%) and related metabolic risk factors. We aimed to evaluate whether BF% calculated by equations could provide more information about metabolic risks, in addition to BMI classification, in a cross-sectional rural Chinese population.


METHODS
A total of 2,990 men and women aged 18-80 years were included in this study. BF% was calculated using previously validated Chinese-specific equations. Metabolic syndrome was defined according to the updated National Cholesterol Education Program Panel III criteria for Asian Americans.


RESULTS
In total, 33.6% men and 32.9% women were overweight/obese according to BMI classification. Among those within the normal BMI range, 25.4% men and 54.7% women were indicated as overweight or obese given their elevated BF% (men: BF% ≥ 20%; women: BF% ≥ 30%). In both men and women, compared with those with normal BMI and BF% (NBB), subjects with normal BMI but elevated BF% (NBOB) were more likely to carry abnormal serum lipid profile and to have higher risks of metabolic syndrome. The multivariable adjusted odds ratios (95% confidence intervals) for metabolic syndrome were 5.45 (2.37-9.53, P < 0.001) and 5.65 (3.36-9.52, P < 0.001) for men and women, respectively. Moreover, the women with NBOB also showed higher blood pressure and serum uric acid than women with NBB.


CONCLUSIONS
Our study suggested that high BF% based on equations may indicate adverse metabolic profiles among rural Chinese adults with a normal BMI.
Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, People's Republic of China.
Xin
X
Liu
Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, People's Republic of China.
Yaling
Y
Zhao
Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, People's Republic of China.
Qiang
Q
Li
Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, People's Republic of China.
Shaonong
S
Dang
Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, People's Republic of China.|Nutrition and Food Safety Engineering Research Center of Shaanxi Province, Xi'an, Shaanxi, 710061, People's Republic of China.
Hong
H
Yan
D000273:Adipose Tissue / Q000378:metabolism*; D050154:Adiposity; D000328:Adult; D002681:China / Q000453:epidemiology; D005260:Female; D006801:Humans; D056865:Ideal Body Weight / Q000502:physiology*; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology* / Q000209:etiology; D008954:Models, Biological; D012424:Rural Population / Q000706:statistics & numerical data*; D055815:Young Adult