A Bayesian Approach to Age‐at‐Death Estimation from Osteoarthritis of the Shoulder in Modern North Americans. Issue 3 (8th December 2016)

• Record Type: Journal Article
• Authors: Brennaman, Ashley L.; Love, Kim R.; Bethard, Jonathan D.; Pokines, James T.
• Is Part Of: Journal of forensic sciences. Volume 62:Issue 3(2017)
• Page Start: 573
• Page End: 584
• Publication Date: 2016-12-08
• Subjects: forensic science -- forensic anthropology -- age estimation -- shoulder -- degenerative joint disease -- transition analysis -- Bayesian statistics; Medical jurisprudence -- Periodicals; Forensic sciences -- Periodicals; Forensic Medicine -- Periodicals; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; 363.2505
• DOI: 10.1111/1556-4029.13327
• Languages: English
• ISSNs: 0022-1198

Abstract

Abstract: Osteoarthritis (OA) is a marker of degeneration within the skeleton, frequently associated with age. This study quantifies the correlation between OA and age‐at‐death and investigates the utility of shoulder OA as a forensic age indicator using a modern North American sample of 206 individuals. Lipping, surface porosity, osteophyte formation, eburnation, and percentage of joint surface affected were recorded on an ordinal scale and summed to create composite scores that were assigned a specific phase. Spearman's correlation indicated a positive relationship between each composite score and age (right shoulder = 0.752; left shoulder = 0.734). Transition analysis revealed a tendency toward earlier degeneration of the right shoulder. Bayesian statistics generated phase‐related age estimates based on highest posterior density regions. Best age estimates were into the seventh decade at the 90th and 50th percentile. The proposed method supplements traditional techniques by providing age estimates beyond a homogenous 50+ age cohort.