A study on estimating body height from length of ulna of adult Nepalese population
DOI:
https://doi.org/10.3126/dmj.v7i1.86109Keywords:
Anthropometry, Sex Characteristics, Stature, UlnaAbstract
Introduction: Stature estimation plays a vital role in anthropological and forensic investigations, particularly in regions like Nepal with diverse ethnic populations. Among long bones, the ulna is frequently utilized due to the ease of palpation of its proximal and distal landmarks. However, limited research exists correlating ulna length and stature in the Nepalese population. So, the objective is to estimate body height from ulna length and assess its correlation with sex in adult Nepalese population.
Methods: A cross-sectional study was conducted at Kathmandu University School of Medical Sciences, involving 299 healthy students (107 males and 192 females). Height was measured using a stadiometer, while ulna length was recorded using a vernier caliper. Data were analyzed using SPSS v16.0. Independent and paired t-tests were employed to assess sex and side differences, while simple linear regression generated stature prediction equations.
Results: In overall population, ulna length showed a strong bilateral correlation with stature, conforming its reliability for height estimation. Males had significantly greater mean height (167.3 ± 12.1 cm) and ulna length (right: 26.7 ± 1.3 cm; left: 26.5 ± 1.3 cm) than females (height: 156.1 ± 6.2 cm; right: 24.5 ± 2.6 cm; left: 24.2 ± 1.3 cm). Statistically significant side asymmetry was observed, with the right ulna slightly longer in both sexes. Regression analysis revealed a stronger correlation between ulna length and height in females, especially with the left ulna (r = 0.732, R² = 0.536). In contrast, males showed weak correlations (right ulna: r = 0.216; left: r = 0.193).
Conclusion: Ulna length is correlated with height of a person, particularly the left ulna in females, is a reliable predictor of stature in the Nepalese population. The findings highlight the necessity of sex and population specific models for accurate stature estimation, especially in forensic and clinical contexts. Further research including broader geographic representation is recommended for enhanced applicability.