Age Estimation Through Osteon Histomorphometry: Analysis of Femoral Cross-Sections from Historical Autopsy Samples

Background/Objectives: Age estimation is of fundamental importance in forensic investigations. When traditional methods based on gross bone morphology or morphometric analysis cannot be applied, forensic experts must rely on multidisciplinary approaches. Histomorphometry has consistently proven to be reliable in cases of highly fragmented or incomplete skeletal remains, particularly in older individuals. Building on the foundational study of Amprino and Bairati, this study evaluated the correlations between bone microstructural features in femoral cross-sections and the age and sex of individuals. Methods: The sample comprised 95 femoral mid-diaphyseal thin sections obtained from autopsy specimens housed at the Institute of Legal Medicine, University of Bari (Italy), representing both male and female individuals aged 18 to 92 years. The numbers and densities of primary, intact secondary, and fragmentary secondary osteons, together with osteon circularity and the mean osteonal area, were measured to investigate age-related variation. Statistical analyses included t-tests, Mann–Whitney tests, Spearman’s rank correlation, and General Linear Models (GLMs). Results: No significant differences in histomorphometric variables were observed between males and females. However, the number of intact secondary osteons and osteon population density increased with age, while the mean osteonal area and osteon circularity decreased with age. Although some variables displayed significant correlations with age, residual analysis indicated a lack of heterogeneity in variance, which limited the development of a robust predictive model. Conclusions: The findings highlight both the potential and the limitations of histomorphometry in forensic age estimation. While certain microstructural variables correlate with age, inter-individual variability reduces predictive accuracy. Further research is needed to refine models that account for biological and biomechanical variability, particularly in older adults.