Sex estimation from the percutaneous lengths of the femur and the ulna in a Ghanaian population using discriminant function analysis

Abstract Sex estimation models form a vital part in Forensic human identification but they are usually population-specific. This study aimed to develop and test sex estimation models for a Ghanaian population using percutaneous lengths of the femur (FL) and ulna (UL). The study was cross-sectional from June to July 2020, involving 99 adults (male: 52, females: 47), aged between 19 and 31 years. The lengths of the femur and ulna were measured using standard anthropometric techniques. All measurements were taken twice from the left side and then averaged. The sample was randomly divided into training (n = 60) and holdout (n = 39) samples before been analysed using discriminant function analysis (DFA). Cross-population studies were performed to test the reliability of the models. Males had longer femur and ulna than females (p < 0.001). Sex estimation accuracies from all the models ranged from 68.2% to 81.8% for males and 52.9% to 86.7% for females. The standardized mean difference (SMD: Cohen’s d) by sample type ranged from −0.19 to 3.08 (living samples), 0.19 to 4.73 (cadaveric samples) and 0.30 to 5.46 (skeletal samples). The SMD by population type were: Africa, excluding Mixed or White ethnicities (d= −0.02 to 3.08), Asia (d = 0.83 to 4.85) and Europe or the Americas (d = 0.30 to 3.38). When other population-specific models were tested on the holdout sample, the difference in the average sex estimation accuracy ranged from 0 to 25.6%. Sex estimation models from the lengths of the femur and ulna are specific to a the studied population and the type of sample used.