New Equations to Predict Body Fat in Asian-Chinese Adults Using Age, Height, Skinfold Thickness, and Waist Circumference

      Abstract

      Background

      Adiposity is an independent predictor of metabolic disease. However, highly accurate body fat assessment is not routinely done due to limited access to expensive and labor-intensive methods.

      Objective

      The aim of the study was to develop body fat prediction equations for Asian-Chinese adults using easily attainable anthropometric measurements.

      Design

      Prediction equations of body fat were developed using anthropometric and skinfold thickness measurements obtained from a cross-sectional study. These new equations were then validated using baseline data from an independent randomized controlled study.

      Participants/setting

      Healthy participants with no major diseases and not taking long-term medications were recruited in an ongoing cross-sectional study that began in June 2014 (n=439, 170 males, 269 females), as well as a randomized controlled trial (n=108, 58 males, 50 females) conducted from January 2013 to October 2014. Both the studies were conducted at Clinical Nutrition Research Center located in Singapore.

      Main outcome measures

      Data used to develop and validate equations were from two original studies that assessed body fat by dual-energy x-ray absorptiometry, age, waist circumference, height, and biceps and triceps skinfolds.

      Statistical analysis performed

      Sex-specific percent body fat prediction equations were developed using stepwise regression with Akaike Information Criterion on the cross-sectional data. The equations were then validated using data from the randomized controlled study and also compared against Asian-specific Davidson equations.

      Results

      The best body fat prediction model (R2=0.722, standard error of estimation=2.97 for females; R2=0.815, standard error of estimation=2.49 for males) for both sexes included biceps and triceps skinfolds, waist circumference, age, and height. The new equations developed resulted in modest discrepancies in body fat of 1.8%±2.7% in males (P<0.001) and 0.7%±3.1% in females (P=0.125; not significant) compared with the Asian-specific Davidson equations (−7.4%±3.2% [P<0.001] and −7.4%±2.7% [P<0.001], respectively).

      Conclusions

      Sex-specific equations to predict the percent body fat of Asian-Chinese adults with a higher degree of accuracy were developed. Ease of use in both field and clinical settings will be a major advantage.

      Keywords

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      Biography

      C. J. Henry is director, Clinical Nutrition Research Centre, Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR) and National University Health System, Singapore, and a professor, Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

      Biography

      S. D/O Ponnalagu is a statistician, Clinical Nutrition Research Centre, Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR) and National University Health System, Singapore.

      Biography

      X. Bi is a research fellow, Clinical Nutrition Research Centre, Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR) and National University Health System, Singapore.

      Biography

      S.-Y. Tan is a senior research fellow, Clinical Nutrition Research Centre, Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR) and National University Health System, Singapore.