Stature estimation from lower limb anthropometry using linear regression analysis: A study on the Malaysian population - Bakar, Siti Noorain Abu; Alias, Aspalilah; Ibrahim, AbdelNasser; Abdullah, Nurliza; Judi, Hairuliza Mohamed; Swarhib, Mohamed; Das, Srijit; Nor, Faridah Mohd (Societa Editrice Universo, 2024)
Introduction. Stature is one of the characteristics that could be used to identify human, besides age, sex and racial affiliation. This is useful when the body found is either dismembered, mutilated or even decomposed, and helps in narrowing down the missing person's identity. Aim. The main aim of the present study was to construct regression functions for stature estimation by using lower limb bones in the Malaysian population. Materials and Methods. The sample comprised 87 adult individuals (81 males, 6 females) aged between 20 to 79 years. The parameters such as thigh length, lower leg length, leg length, foot length, foot height and foot breadth were measured. They were measured by a ruler and measuring tape. Statistical analysis involved independent t-test to analyse the difference between lower limbs in male and female. The Pearson's correlation test was used to analyse correlations between lower limb parameters and stature, and the linear regressions were used to form equations. The paired t-test was used to compare between actual stature and estimated stature by using the equations formed. Result. Using independent t-test, there was a significant difference (p < 0.05) in the measurement between males and females with regard to leg length, thigh length, lower leg length, foot length and foot breadth. The thigh length, leg length and foot length were observed to have strong correlations with stature with p= 0.75, p= 0.81 and p= 0.69, respectively. Linear regressions were formulated for stature estimation. Paired t-test showed no significant difference between actual stature and estimated stature. Conclusion. It is concluded that regression functions can be used to estimate stature to identify skeletal remains in the Malaysia population. Societ Editrice Universo (SEU).