Literature DB >> 18000887

Testing the quality of nonadult Bayesian dental age assessment methods to juvenile skeletal remains: the Lisbon collection children and secular trend effects.

Yann Heuzé1, Hugo F V Cardoso.   

Abstract

Age estimation of nonadult skeletons from archaeological or forensic contexts has relied heavily on modern schedules of dental formation developed on samples of children of affluent populations. Although genetic factors have been considered to have had the greatest influence on population differences in dental development, increased interest has been placed on the role of environmental influences, such as differences in socioeconomic status and secular trends. This study evaluates the quality (i.e., accuracy and reliability) of two Bayesian dental age estimation methods to a sample of identified child skeletons from the Lisbon collection (20th century Portugal). The two Bayesian methods are developed on a reference sample of modern children from France, Ivory Coast, Iran, and Morocco. The test sample from Lisbon, compared to the reference sample, is separated by over 50 years of secular trends and comprises a lower socioeconomic segment. The two Bayesian methods show that the Lisbon children are consistently 1-year behind in dental age compared to the modern children of the reference sample. Environmental factors largely explain the differences between dental and chronological age in historic samples of nonadults. 2007 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  2008        PMID: 18000887     DOI: 10.1002/ajpa.20741

Source DB:  PubMed          Journal:  Am J Phys Anthropol        ISSN: 0002-9483            Impact factor:   2.868


  2 in total

1.  Iron deficiency anemia, population health and frailty in a modern Portuguese skeletal sample.

Authors:  Samantha M Hens; Kanya Godde; Kristin M Macak
Journal:  PLoS One       Date:  2019-03-07       Impact factor: 3.240

2.  Temporal mapping of the closure of the anterior fontanelle and contiguous sutures using computed tomography, in silico models of modern infants.

Authors:  Nicolene Lottering; Clair L Alston; Mark D Barry; Donna M MacGregor; Laura S Gregory
Journal:  J Anat       Date:  2020-04-13       Impact factor: 2.921

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.