Development of an Easy-to-Use Visual Aid for the Prediction of Body Fat Based on Waist Circumference and Height in Asian Chinese Adults

Abstract Background Adiposity is a major risk factor for metabolic and cardiovascular diseases. Initial prediction equations to estimate adiposity are complex, requiring skinfold measurements that cannot be obtained conveniently by the general population. Objective To develop simplified prediction equations to estimate body fat percentage (%BF) in Asian Chinese adults, evaluate the validity of the simplified %BF prediction equations, compare the simplified %BF prediction equations with an existing equation, and create visual charts to enable easy assessment of adiposity by the general public. Design Simplified prediction equations were developed and evaluated for validity using anthropometric measurements obtained from a cross-sectional study. Participants and setting Healthy participants with no major diseases and not taking long-term medications were recruited in a cross-sectional study conducted at Clinical Nutrition Research Centre, Singapore, between June 2014 and October 2017. A total of 439 participants were used for model building (269 women and 170 men) and another 107 participants were used for evaluating validity (62 women and 45 men). Main outcome measures Simplified but acceptable prediction models and generation of user-friendly charts. Statistical analyses performed Simplified sex-specific %BF prediction equations were developed using stepwise regression and the model-building dataset. The best models were selected using the Akaike information criterion. The models were further simplified and their performance was compared using the validation dataset before choosing the final prediction equations. Results The final selected models for women and men included waist circumference and height with nonsignificant prediction bias in %BF of 0.84%±3.94% ( P =0.098, Cohen's d z =0.21) and –0.98%±3.65% ( P =0.079, Cohen's d z =0.27), respectively. The final equations were split into three height categories from which the sex-specific prediction charts were generated. Conclusions The sex-specific prediction charts provide a good visual guide for estimating %BF using height and waist circumference values that are easy to obtain by the general public.