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Accuracy and challenges in age estimation in adults: a scoping review of anthropological, dental, biochemical, and
J Rojas-Torres1,2,3, L Martínez-Durán4,5, J M de Anta6
1Programa de Doctorado en Ciencias, Mención Biología Celular y Molecular Aplicada, Universidad de La Frontera, 4811230, Temuco, Chile. javier.rojas@ufrontera.cl.
Abstract:
Age estimation is crucial in forensic sciences for victim identification, migration studies, and bioarchaeology. In subadults, it is based on maturational changes, while in adults, it relies on degenerative processes, reducing accuracy. Traditional methods, such as anthropological and dental approaches, are widely used, but recent advances in biochemical and molecular biology (BMB) have introduced epigenetic and biochemical analyses. Given the variability in biological aging, it is essential to evaluate and compare these methods for more precise and reproducible results. This article is a scoping review analyzing the accuracy of anthropological, dental, and BMB methods for estimating age in living individuals, cadavers, and adult skeletal remains. A scoping review following PRISMA-ScR guidelines was conducted in PubMed, Scopus, and WOS, covering studies from 2015 to 2024. Articles applying regression models for age estimation and reporting error metrics were included, while reviews and studies without precision data were excluded. Anthropological methods analyze degenerative changes in bone structures, such as the pubic symphysis and acetabulum, with error margins of 4-25 years. Forensic dentistry uses pulp-to-tooth ratios and secondary dentin deposition, yielding mean errors of 2.5-12.5 years. BMB methods, such as DNA methylation, telomere shortening, and aspartic acid racemization, offer accuracies of ± 3 to ± 10 years but require specialized equipment. Artificial intelligence enhances reproducibility, although standardization challenges remain. Age estimation in adults, particularly those over 40, remains challenging. Validating traditional methods, integrating AI, and applying multivariate molecular models can improve accuracy. A multidisciplinary approach is essential for forensic applications.
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