MODELS FOR ESTIMATING AGE AND SEX FROM VARIABLES OF THE PROXIMAL FEMUR IN A GHANAIAN POPULATION

Abstract

Age and sex estimation models from the proximal femur are population-specific due to genetic and environmental variabilities. Extrapolating a femur-based age or sex estimating model from one population to another will be problematic. Proximal femur-specific age and sex estimation models are limited in Ghana. The study aimed to estimate the age and sex of an adult Ghanaian population using osteometric measurements from the proximal femur. The study was cross-sectional from January to June 2019 at the Korle-Bu Teaching Hospital (KBTH). There were 125 (male=51, female=74) participants, aged from 31 to 82 years. The head diameter-left (HDL), neck diameter-left (NDL), neck-shaft angle-left (NSAL) and the Hip axis length-left (HALL) were measured twice using a standardized radiographic technique. Discriminant and logistic regression models were formulated for sex estimation while linear regression models were formulated for age estimation and these models were then tested for reliability. Males had longer HDL and NDL than females (P < 0.050). The average sex estimation accuracy in the discriminant analysis ranged from 58.4% to 64.0% (in the original sample) and 56.8% to 62.4% (in the cross-validation sample) while in the logistic regression analysis it ranged from 58.4% to 64.0%. The HDL was better than the NDL in sex attribution but only marginal. The multivariate model (HDL+NDL) marginally improved sex estimation accuracy (64.0%) over the univariate models for HDL (61.6%) and NDL (60.0%). In general, females were better classified than males. There was no significant difference between the chronological age and the estimated age of males using HALL although the confidence interval (95%CI) was wider than expected [Bias: 1.133 (95%CI: − 25.280 to 27.540). The femoral head and neck diameters or their combination are poor attributors of sex on average. Also, male adult age estimation using HALL is less precise. The use of these models in the Ghanaian population is not advised