Stature Estimation from the Anthropometric Measurements of Footprint in Iban Ethnics of East Malaysia by Regression Analysis

A person's stature is an identifying characteristic that is often used in forensic investigation. Footprint is the one of the valuable physical evidence encountered in the crime scenes and examination of barefoot impressions is important especially in developing countries like India, Malaysia where majority of the rural population like to walk barefooted because of socio-economic and climatic reasons. Foot impressions are still found at crime scenes, since offenders often tend to remove their footwear either to avoid noise or to gain better grip in climbing walls, etc., while entering or exiting. Most of the foot/foot print studies were conducted on mixed population. The researchers have cautioned that the people from different races and regions of a country bear different morphological features depending upon their geographical distribution and primary racial characteristics and hence a single formula cannot represent all parts of that country or world. The present study aims to estimate stature from bilateral footprints collected from 320 (160 males, 160 females) consenting adult Ibans, an indigenous group residing in Sarawak state, east Malaysia. Informed consent and Human Ethical Approval were obtained. The height of the individuals and footprints were collected following the standard procedure. The data obtained were analyzed with PASW 20 computer software and derived regression formulae to estimate stature from footprint lengths of Iban ethnics. The result of the investigation revealed that all footprint lengths exhibit statistically positive significant correlation with stature (p< 0.001). Correlation coefficient (R) values are found to be higher in the pooled sample (0.861–0.887) when compared with males (0.753–0.789) and females (0.728–0.790). The regression formulae derived for the pooled sample can be used to estimate stature when the sex of the footprint remains unknown, as in real crime scenarios.

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