Development of Stature Prediction Models from Anthropometric Measurements among Indigenous Adults of Imo State, Nigeria

Abstract

Background: Accurate stature estimation is essential in forensic anthropology, human identification, ergonomics, and clinical practice, particularly when direct measurement is impossible. Objective: This study investigated the relationship between stature and selected sitting anthropometric measurements and developed population-specific regression models for indigenous adults of Imo State, Nigeria. Methods: A cross-sectional study was conducted among 150 apparently healthy indigenous adults aged 18–40 years. Stature, sitting height, sitting eye height, sitting shoulder height, sitting popliteal height, and sitting knee height were measured using standardised anthropometric techniques. Descriptive statistics, independent-samples t-tests, Cohen's d, and multiple linear regression analyses were performed, with statistical significance set at p < 0.05. Results: Significant sex differences were observed in stature and all anthropometric variables (p < 0.001). Sitting knee height was the strongest predictor of stature in the combined, male, and female models. The regression models explained 81.2%, 81.3%, and 70.0% of the variation in stature among all participants, males, and females, respectively. Conclusion: This study provides the first population-specific stature prediction models for indigenous adults of Imo State, demonstrating that sitting knee height is the most reliable predictor of stature. The developed equations offer valuable tools for forensic anthropology, medico-legal investigations, ergonomics, and clinical practice when direct stature measurement is not feasible.