Background
The determination of living stature is a key component of personal identification of individuals. In this study, we developed predictive regression models and multiplication factors to reliably estimate living stature from foot length and breadth in adult Nigerian undergraduate students at the University of Lagos.
Materials and methods
The study sample comprised 400 subjects (200 males and 200 females) of Nigerian parentage, aged 18–36 years who volunteered and satisfied the inclusion criteria. Following institutional approval, anthropometric measurements of stature, foot length, and foot breadth were taken with a stadiometer, a large sliding caliper and a small sliding vernier caliper respectively according to the protocol recommended by the International Society for the Advancement of Kinanthropometry (ISAK). The data was analyzed for descriptive and inferential statistics using the SPSS statistical package version 20.
Results
Mean stature values of 176.44 ± 6.47 cm, 164.71 ± 6.70 cm, and 169.80 ± 8.79 cm were recorded for the males, females, and the pooled sample respectively. The mean values of the foot dimensions (right and left) in the males, females, and the pooled sample ranged from 9.49 ± 0.73 to 27.29 ± 1.30 cm. Independent t test exhibited statistically significant gender differences (P < 0.05) for all the parameters except age, with the males having consistently higher values than the females. Paired t test revealed the existence of bilateral asymmetry between right and left foot dimensions, except for the foot length in the males (P < 0.05). Significant positive correlation coefficients of stature with the foot length and breadth dimensions were found to range from 0.344 to 0.832 in the study. The multiplication factors computed for stature prediction from foot length and breadth ranged from 6.465 to 18.301 in the males, females, and the pooled sample.
Conclusion
This study has demonstrated that stature can be predicted from foot dimensions, with the foot length showing more accuracy and reliability than the foot breadth. The prediction models established from this study will be very useful in disaster victim identification from mutilated human remains in Nigeria.
; Olabiyi Olaleye Andrew 1 ; Nandi, Michael Ebe 1