Regression Equation and Multiplication Factor for the Reconstruction of Stature by Femur Length

Authors

  • Raj Kumar Karki Kathmandu University School of Medical Sciences, Dhulikhel, Nepal
  • Pankaj Kumar Singh Kathmandu University School of Medical Sciences, Dhulikhel, Nepal
  • Abdul Sami Khan Kathmandu University School of Medical Sciences, Dhulikhel, Nepal
  • Sudeep Regmi Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

DOI:

https://doi.org/10.3126/jucms.v8i02.34265

Keywords:

Femur length, Multiplication Factor, Regression equation, Stature

Abstract

INTRODUCTION

Stature is the important parameter along with age, sex and race while identifying bodies. Stature has direct relationship with the skeletal dimensions most importantly with lower limbs. This study attempts to derive regression equation (RE) and multiplication factor (MF) from femur length (FL) which could be used for stature reconstruction.

MATERIAL AND METHODS

The study was conducted amongst the 160 students and staff of Dhulikhel Hospital, Nepal for the period of six months from February 2020 to July 2020. The sample was composed of 95 males and 65 females between the age of 18 - 40 years. The femoral length and height was measured in standard position using standard measuring instruments. Statistical analysis was done using SPSS 25.

 

RESULTS

The mean height and femur length of overall sample was 162.33 ±7.62 cm and 40.14 ±2.132 cm respectively, male surpassing the female dimensions. There was a strong correlation between femur length and stature (r = 0.723, 0.869 and 0.791 for males, females, and overall participants respectively). MF was derived as 4.084 ±0.139, 3.99 ±0.11, 4.047 ±0.135 and RE was derived as y = 75.51 + 2.13*FL ±4.06, y = 55.238 + 2.581*FL ±2.999, y = 48.791 + 2.829*FL ±4.672 for males, females and overall participants. Both methods were checked for accuracy and could successfully interpret the height (p>0.05).

CONCLUSION

The femoral length was found to be a reliable estimator of stature of an individual by using both RE and MF.

Downloads

Download data is not yet available.
Abstract
222
PDF
300

Author Biographies

Raj Kumar Karki, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

Department of Forensic Medicine and Toxicology, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

Pankaj Kumar Singh, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

Department of Forensic Medicine and Toxicology, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

Abdul Sami Khan, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

Department of Forensic Medicine and Toxicology, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

Sudeep Regmi, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

Department of Forensic Medicine and Toxicology,  Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

Downloads

Published

2020-12-31

How to Cite

Karki, R. K., Singh, P. K., Khan, A. S., & Regmi, S. (2020). Regression Equation and Multiplication Factor for the Reconstruction of Stature by Femur Length. Journal of Universal College of Medical Sciences, 8(02), 25–30. https://doi.org/10.3126/jucms.v8i02.34265

Issue

Vol. 8 No. 02 (2020)

Section

Original Articles

License

Authors have to give the following undertakings along with their article:

  1. I/we declare that this article is original and has not been submitted to another journal for publication.
  2. I/we declare that I/we surrender all the rights to the editor of the journal and if published will be the property of the journal and we will not publish it anywhere else, in full or part, without the permission of the Chief Editor.
  3. Institutional ethical and research committee clearance certificate from the institution where work/research was done, is required to be submitted.
  4. Articles in the Journal are Open Access articles published under the Creative Commons CC BY-NC License (https://creativecommons.org/licenses/by-nc/4.0/)
  5. This license permits use, distribution and reproduction in any medium, provided the original work is properly cited, and it is not used for commercial purposes.