A Bayesian Approach to Age‐at‐Death Estimation from Osteoarthritis of the Shoulder in Modern North Americans |
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| Authors: | Ashley L. Brennaman M.S. Kim R. Love Ph.D. Jonathan D. Bethard Ph.D. James T. Pokines Ph.D. |
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| Affiliation: | 1. Department of Anthropology, University of Wisconsin Milwaukee, Milwaukee, WI;2. Owner and Lead Consultant, K. R. Love Quantitative Consulting and Collaboration, Athens, GA;3. Department of Anthropology, University of South Florida, Tampa, FL;4. Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA |
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| 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. |
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| Keywords: | forensic science forensic anthropology age estimation shoulder degenerative joint disease transition analysis Bayesian statistics |
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