Regression-based Prediction of Stature From Humeral and Femoral Segment Lengths Among Nigerian School Children

Abstract Background Accurate stature estimation is important in forensic anthropology, clinical practice, and anthropometric research when direct height measurement is impractical. Because anthropometric relationships vary across populations, population-specific prediction models are required. Objective To develop regression equations for estimating stature from humeral and femoral segment lengths among school-aged children in Southwestern Nigeria. Methods A cross-sectional study was conducted among 85 apparently healthy children aged 6–12 years attending Achievers University Primary School, Owo, Nigeria, comprising 44 males and 41 females. Standing height was measured using a stadiometer, while humeral and femoral segment lengths were obtained using standard anthropometric techniques. Pearson's correlation and multiple linear regression analyses were used to assess associations and develop sex-specific stature-prediction equations. Results Mean stature was 128.80 ± 8.15 cm in males and 130.10 ± 10.14 cm in females. Stature was significantly correlated with age, humeral length, and femoral segment length in both sexes (p < 0.001). Among males, age showed the strongest correlation with stature (r = 0.723), whereas femoral segment length showed the strongest correlation among females (r = 0.838). Regression models explained 75.4% of the variance in male stature (R² = 0.754) and 88.3% in female stature (R² = 0.883). Conclusion Age, humeral length, and femoral segment length are useful predictors of stature among Nigerian children aged 6–12 years. The developed sex-specific equations provide preliminary population-specific tools for stature estimation, with potential applications in forensic anthropology, clinical assessment, and anthropometric research. External validation in larger and geographically diverse Nigerian populations is recommended.