Kanchan Tanuj, Krishan Kewal, Geriani Disha, Khan Iman Sajid
Department of Forensic Medicine, Kasturba Medical College, Mangalore, Manipal University, India.
Foot (Edinb). 2013 Dec;23(4):136-9. doi: 10.1016/j.foot.2013.10.015. Epub 2013 Nov 6.
Footprints give an estimate of the height of an individual using gender-dependent models derived for different population and ethnic groups. However, estimation of ethnicity, age and gender from a footprint may not always be possible in forensic case work.
The present study is done to develop models for stature (height) estimation from the width of footprints in the Indian population that are independent of the age and gender of individuals.
The present research was conducted on 100 young adults from different regions of India. Footprints were obtained from both feet using standard techniques. Stature, and metatarsophalangeal joint (MPJ) Width (distance across the widest part of the forefoot) and calcaneal (Calc) Width (distance across the widest section of the heel) were measured on 200 footprints. Regression models were derived for estimation of stature.
A positive correlation is observed between footprint measurements and stature. Regression models derived from the forefoot region give a more accurate estimate of stature than the heel region of the footprint. Multiple linear regression models gave more accurate estimates of stature than the single linear regression models.
Regression models derived in the study for Indian population may be valuable in establishing the stature of a footprint in practical scenario when the age and gender are unknown.
足迹可通过针对不同人群和种族群体推导的性别相关模型来估算个体身高。然而，在法医案件工作中，从足迹估算种族、年龄和性别并非总是可行的。
本研究旨在开发印度人群中基于足迹宽度估算身高的模型，该模型独立于个体的年龄和性别。
本研究对来自印度不同地区的100名年轻成年人进行。使用标准技术获取双脚的足迹。在200个足迹上测量身高、跖趾关节（MPJ）宽度（前脚掌最宽处的距离）和跟骨（Calc）宽度（足跟最宽处的距离）。推导用于估算身高的回归模型。
观察到足迹测量值与身高之间存在正相关。从前脚掌区域推导的回归模型比足迹的足跟区域能更准确地估算身高。多元线性回归模型比单一线性回归模型能更准确地估算身高。
本研究中为印度人群推导的回归模型在实际场景中，当年龄和性别未知时，对于确定足迹的身高可能具有重要价值。
