International Journal of Anatomy Radiology and Surgery (Mar 2024)

Estimation of Stature among Healthcare Workers using Arm Span, Biacromial Breadth, and Forearm Length Dimensions: A Cross-sectional Study

  • Richa Bhatnagar,
  • Garima Sharma,
  • Rohit Sharma,
  • Vishal Kalia,
  • Vipul Parmar,
  • Manoj Kumar Gandhi

DOI
https://doi.org/10.7860/IJARS/2024/66612.2978
Journal volume & issue
Vol. 13, no. 02
pp. 17 – 21

Abstract

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Introduction: Stature is one of the most commonly used anthropometric dimensions for identification purposes in forensic investigations and for assessing the development and growth of individuals. It is well-known that various anatomical anthropometric parameters can accurately estimate stature. Aim: To estimate stature among healthcare workers in Himachal Pradesh using linear regression equations based on percutaneous anthropometric parameters of the upper limbs and trunk. Materials and Methods: This cross-sectional study was conducted on healthcare workers at Dr. Rajendra Prasad Government Medical College, Kangra, Tanda, Himachal Pradesh for a one year (September 2021-August 2022) duration. The study included 360 healthy healthcare workers from the Himachal Pradesh population, 180 females and 180 males, aged 21 years and above. Stature, arm span, Biacromial Breadth (BAB), and forearm length dimensions were measured for each subject. Statistical analysis was done using Microsoft Excel and Epi-Info version 7.1 software. The Pearson Correlation Coefficient was used to determine the correlation between stature and different anatomical anthropometric parameters. Linear regression equations were developed to estimate stature, with significance set at p-value ≤0.001. Results: The mean age of the study population was 41.33±28.91 years. The descriptive anthropometric parameters measured in the study were as follows: stature 162.4±6.85 and 149.4±7.15, arm span 165.67±7.5 and 150.31±8.33, right forearm length 26.68±1.33 and 24.36±1.59, left forearm length 26.47±1.30 and 24.30±1.55, BAB 34.11±2.16 and 31.74±2.32, respectively for males and females. Conclusion: The regression equations derived from this study can be valuable for estimating stature in situations where accurate stature measurements are not feasible.

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