Stature Estimation among Iraqis based on Anthropometrics of the Hands using Multivariable Regression

Sinan Subhi Farhan; Ahmed Al-Imam; Watheq Mohammed Al-Jewari

doi:10.54133/ajms.v4i.120

Authors

Sinan Subhi Farhan Department of Basic Sciences, Faculty of Pharmacy, Al-Rafidain University College, Baghdad, Baghdad 10052, Iraq https://orcid.org/0000-0003-4759-219X
Ahmed Al-Imam Alumni Ambassador, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AD, United Kingdom https://orcid.org/0000-0003-1846-9424
Watheq Mohammed Al-Jewari Department of Basic Sciences, Faculty of Pharmacy, Al-Rafidain University College, Baghdad, Iraq https://orcid.org/0000-0002-3667-6630

DOI:

https://doi.org/10.54133/ajms.v4i.120

Keywords:

Anthropometrics of hands, Morphometric studies, Forensic sciences, Arabs of the Middle East

Abstract

Background: Estimating stature is useful in forensics and personal identification. There are no established methods for estimating height among Iraqis in the literature. Objective: To forecast the stature of Iraqis based on the morphometric features of both hands. Methods: We recruited 101 students from Al-Rafidain University College, collected data on ethnicity, gender, weight, and height, and measured fourteen morphometric parameters for each hand, including hand length, palm length, hand breadth, maximum handbreadth, and finger length. To predict stature based on the above variables, the statistician used multivariable linear regression. Results: The sample consisted of males (48.5%) and females (51.5%) aged 18-23 years of Arabic (95%) and Kurdish (5%). We estimated the average weight (65.68±1.32) and height (169.5±21.13). Three prediction equations were developed. The whole sample (accuracy=74.8%, p<0.001) and the male cohort (65%, p<0.001) had significantly higher statistical accuracy than the females (47.2%, p<0.001). Within the overall sample, males assumed commonalities in parameters assigned to both hands, which primarily included the length of the right hand, right middle finger, left palm, and left little finger. Females' stature estimation, on the other hand, correlated to morphometric criteria strictly related to the left hand, such as hand length, palm, ring finger, and little finger. The findings corroborated neural network analysis and qualitative data from the ChatGPT big language model. Conclusion: We successfully developed multivariable prediction models critical to human identification for forensic purposes, such as catastrophic situations caused by disfiguring accidents, organized crime, and mass graves, all of which occurred often in Iraq during the last two decades. Experts in reconstructive hand surgery may be interested in our findings.

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Author Biography

Watheq Mohammed Al-Jewari, Department of Basic Sciences, Faculty of Pharmacy, Al-Rafidain University College, Baghdad, Iraq

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