Research Article
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Estimation of stature from the lengths of ulna and tibia: a cadaveric study based on group-specific regression equations

Year 2012, Volume: 3 Issue: 1, 1 - 9, 01.11.2012

Abstract

Prediction of stature in forensic medicine and anthropology is one of the most important tools
in forensic identification. This study is aimed at generating group–specific stature equations
that produce the most accurate results. The study was conducted on 140 cadavers (78 males,
62 females) of ages ranging from 18 to 50 years. Ulna and tibia lengths of the cadavers, as
well as body height, were measured using two different methods. Values of ulna and tibia
were classified into three groups; long ulna/tibia, medium ulna/tibia, and short ulna/tibia, by
using 15th and 85th percentile values as cut-off points, and then least square regression equations were generated for each group. The results of these bone length sensitive formulae are
compared with the results obtained using the classical general formula. Comparisons highlight that group-specific formulae give more accurate results than those of general the formula
making them better suited to estimation of stature versus than the general formula in forensic
cases.

References

  • Agnihotri AK, Kachhwaha S, Jowaheer V, Singh AP. (2009) Estimating stature from percutaneous length of tibia and ulna in Indo-Mauritian population. Forensic Sci Int 187:109.e1−109.e3.
Year 2012, Volume: 3 Issue: 1, 1 - 9, 01.11.2012

Abstract

References

  • Agnihotri AK, Kachhwaha S, Jowaheer V, Singh AP. (2009) Estimating stature from percutaneous length of tibia and ulna in Indo-Mauritian population. Forensic Sci Int 187:109.e1−109.e3.
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Details

Primary Language English
Journal Section Research Articles
Authors

Osman Özgür Sargın This is me

İzzet Duyar

Sema Demirçin This is me

Publication Date November 1, 2012
Published in Issue Year 2012 Volume: 3 Issue: 1

Cite

Vancouver Sargın OÖ, Duyar İ, Demirçin S. Estimation of stature from the lengths of ulna and tibia: a cadaveric study based on group-specific regression equations. Euras J Anthropol. 2012;3(1):1-9.