DOI: 10.3390/app16157629 ISSN: 2076-3417

Optimum Cut-Off Points of Conventional and Novel Anthropometric Indices for Obesity Screening in Young Japanese Females: A Pilot Study

Mutiara Arsya Vidianinggar Wijanarko, Masaharu Kagawa

Background: Conventional anthropometric indices such as body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) are widely used for obesity screening; however, their accuracy may be limited in young Japanese women, who often exhibit higher percentage body fat (%BF) at lower BMI values. This pilot study examined the relationships between DXA-derived %BF and anthropometric indices and evaluated their ability to identify excess adiposity. Methods: A cross-sectional study was conducted among 78 Japanese female university students aged 18–28 years. Whole-body composition was assessed using dual-energy X-ray absorptiometry (DXA), and excess adiposity was defined as %BF ≥ 30%. Receiver operating characteristic analyses were performed to evaluate the discriminatory ability of anthropometric indices and identify exploratory optimal cut-off values. Results: Participants had a median BMI of 20.3 kg/m2 and a mean %BF of 32.3 ± 5.4%. Conventional BMI, WC, and WHtR thresholds showed very low sensitivity for detecting excess adiposity despite perfect specificity. ROC analyses identified substantially lower optimal cut-off values, yielding sensitivities of approximately 70–80%, specificities of 58–75%, and AUC values of 0.76–0.78. Among novel anthropometric indices, body roundness index (BRI) demonstrated the strongest discriminatory ability. Conclusions: Conventional anthropometric thresholds may underestimate DXA-defined excess adiposity in young Japanese female university students. This exploratory pilot study identified lower candidate cut-off values and suggested that BRI may serve as a useful adjunctive anthropometric index for identifying excess adiposity in this population. These findings should be interpreted cautiously and require validation in larger and more diverse populations before clinical application.

More from our Archive