Analyzing entheseal changes in commingled human remains from Mesolithic and Neolithic periods in Portugal.

  • Published In: International Journal of Osteoarchaeology, 2024, v. 34, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Mazza, Bárbara; Silva, Ana María 3 of 3

Abstract

The analysis of entheseal changes requires knowing the biological profile of the sample analyzed, given that, mainly, the sex and age of the individuals influence the prevalence and degrees of the entheseal features. However, the bioarcheological record of several past populations presents isolated and commingled human bone remains, which constrains the estimation of such data. In this work, we propose to analyze the entheseal changes with the Coimbra method in a sample composed mainly of commingled human bone remains and, to a lesser extent, of semi‐complete individuals. For this purpose, we analyzed 312 bone elements from the upper and lower limbs of Late Mesolithic (Muge complex) and Late Neolithic/Chalcolithic archeological sites from Portugal. The results support previous information that individuals older than 40 present higher entheseal changes. In addition, body size has a low effect on entheseal changes and bone's biomechanical properties are positively correlated with some entheseal features. Some entheseal traits show higher prevalence during the Mesolithic, but there is mainly an increase in entheseal changes during the Neolithic. Although these differences could be due to different biological profiles between both samples, differences in lifestyle may also have contributed to the results. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Osteoarchaeology. 2024/01, Vol. 34, Issue 1, p1
  • Document Type:Article
  • Subject Area:Anthropology
  • Publication Date:2024
  • ISSN:1047-482X
  • DOI:10.1002/oa.3273
  • Accession Number:175520708
  • Copyright Statement:Copyright of International Journal of Osteoarchaeology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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