Department of Anthropology (UGC Centre of Advanced Study), Panjab University, Sector-14, Chandigarh, India.
Department of Anthropology, Panjab University, Chandigarh, India.
Acta Biomed. 2021 Jul 1;92(3):e2021225. doi: 10.23750/abm.v92i3.10274.
Estimation of age, stature, sex, and ancestry contributes to the establishment of the biological profile of the deceased in forensic examinations. Assessment of the body weight aids in the approximation of the overall body size of the individual which may help in the forensic identification process. In clinical examinations, body weight assessment assumes importance in cases where body weight measurement is a challenging task due to illness and body deformity.
The present research was conducted to estimate the body weight from the percutaneous width of the bones and joints with the help of prediction equations.
The study was carried out on 344 adults (172 Females and 172 Males) aged between 18 and 25 years from the Himachal Pradesh State of North India. Eleven anthropometric measurements including height vertex, mid-arm circumference, humerus bicondylar width, transverse chest breadth, sagittal chest breadth, bi-iliac breadth, handbreadth, femur bicondylar breadth, ankle breadth, foot breadth, and body weight were taken on each individual. The sex differences were evaluated by using independent student t-test and Mann-Whitney U test and the correlation between the body weight and the anthropometric variables was investigated by using both Karl Pearson's correlation coefficient and Spearman's rank correlation coefficient depending upon the normality of the data. Regression models for the estimation of body weight were calculated. Further, a validation study was carried out to check the accuracy and utility of the derived regression models by calculating the mean absolute percent prediction error (MAPPE).
Significant sex differences were observed among all the anthropometric variables. The transverse chest breadth and mid-arm circumference were strongly correlated with the body weight, whereas, a good correlation was also observed in other measurements except for the ankle breadth. The SEE (Standard error of estimate) of the derived linear regression models was compared, and it was found that multiple linear regression models show better accuracy than simple linear regression models. The MAPPE was found to be less in the case of multiple linear regression models than the linear ones.
The present investigation concludes that regression models can be used in the estimation of body weight from the percutaneous measurements and joint widths with reasonable accuracy in an Indian population.
在法医检查中，估计年龄、身高、性别和种族有助于建立死者的生物学特征。体重评估有助于估计个体的总体体型，这有助于法医鉴定过程。在临床检查中，当由于疾病和身体畸形导致体重测量变得具有挑战性时，体重评估就显得尤为重要。
本研究旨在通过预测方程从骨骼和关节的皮测宽度来估计体重。
本研究对来自印度北部喜马偕尔邦的 344 名年龄在 18 至 25 岁的成年人（172 名女性和 172 名男性）进行了研究。对每个人进行了 11 项人体测量，包括身高顶点、上臂围、肱骨双髁宽度、胸廓横径、胸廓矢状径、双髂宽、手握宽、股骨双髁宽、踝宽、足宽和体重。使用独立学生 t 检验和曼-惠特尼 U 检验评估性别差异，并根据数据的正态性使用卡尔·皮尔逊相关系数和斯皮尔曼秩相关系数研究体重与人体测量变量之间的相关性。计算了用于估计体重的回归模型。进一步进行了验证研究，通过计算平均绝对百分比预测误差（MAPPE）来检查得出的回归模型的准确性和实用性。
所有人体测量变量均观察到显著的性别差异。胸廓横径和上臂围与体重密切相关，而其他测量值也存在较好的相关性，除了踝宽。比较了得出的线性回归模型的 SEE（估计标准误差），发现多元线性回归模型比简单线性回归模型具有更高的准确性。MAPPE 在多元线性回归模型中比线性模型小。
本研究表明，回归模型可用于从皮测测量和关节宽度估计印度人群的体重，具有合理的准确性。
