STATURE ESTIMATION FROM HAND ANTHROPOMETRIC MEASUREMENTS IN PORT HARCOURT

ABSTRACT Stature estimation is essential in forensic, anthropological, and clinical contexts. This study developed regression models to predict stature from hand dimensions among adults in Port Harcourt, Nigeria. A total of 400 participants (168 males, 232 females) aged 18–50 years were measured for hand length, hand breadth, and stature using standard anthropometric protocols. Pearson correlation and linear regression analyses were performed to derive sex-specific predictive models. Hand length showed strong positive correlations with stature (r = 0.78, p < 0.001 in males; r = 0.72, p < 0.001 in females), while hand breadth also correlated positively (r = 0.65 in males; r = 0.61 in females). Univariate regression equations for stature estimation were H = 65.32 + 2.15 × Hand Length for males and H = 60.14 + 2.01 × Hand Length for females. Multivariate models incorporating hand breadth slightly improved predictive accuracy compared with univariate models (males: R² = 0.65; females: R² = 0.58). These findings indicate that hand measurements can reliably estimate stature in this population, with applications in forensic identification, clinical assessment, and ergonomic design.