A Bayesian Approach to Age‐at‐Death Estimation from Osteoarthritis of the Shoulder in Modern North Americans

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.

Reconsidering osteoarthritis as a skeletal indicator of age at death

“…In contrast with the expectation that the relationship between age and OA would be obscured by multiple other risk factors, age emerged from the GLM analyses as a consistent and significant predictor of OA in nearly all tested joints. This finding accords with recent research indicating strong age correlations for degenerative joint changes (Alves‐Cardoso & Assis, ; Brennaman et al, ; Falys & Prangle, ; Winburn, ) and highlighting the inextricable relationship between OA and skeletal age estimation (Calce et al, ). It thus seems valid—at least during the analysis of European‐American samples—for practitioners to refer to the herein‐presented age cut‐offs to supplement an age‐at‐death estimate informed by other skeletal indicators (see Table ; practitioners can also refer to descriptions in Table ).…”

“…Yet, while medical research on OA indicates that obesity (Coggon et al, ; Couchman, ; Felson et al, , ; Fransen et al, ; Mandl, ), vigorous physical activity (Allen et al, ; Cooper, McAlindon, Coggon, Egger, & Dieppe, ; Croft, Cooper, Wickham, & Coggon, ; Dahaghin, Tehrani‐Banihashemi, Faezi, Jamshidi, & Davatchi, ; Felson & Zhang, ; Fransen et al, ; Maetzel, Mäkelä, Hawker, & Bombardier, ), and trauma (Coggon et al, ; Couchman, ; Felson & Zhang, ; Neyret, Donell, DeJour, & DeJour, ; Solomon, ; Zhang, Glynn, & Felson, ) all contribute to the progression of the disease, researchers in multiple fields acknowledge that age is a particularly important systemic risk factor for the development of OA (Calce, Kurki, Weston, & Gould, ; Loeser, ; Mandl, ; Weiss & Jurmain, ). In line with this opinion, biological anthropologists have begun to explore the relevance of synovial joint degeneration for age estimation (Alves‐Cardoso & Assis, ; Brennaman, Love, Bethard, & Pokines, ; Calce, ; Calce, Kurki, Weston, & Gould, ; Winburn, ). Their findings indicate that the relationship between age and OA deserves to be reconsidered for the purposes of skeletal age estimation.…”

Status of Mandibular Third Molar Development as Evidence in Legal Age Threshold Cases

“…These values were obtained from probit regression in the R package “VGAM.” The estimated mean and standard deviation for age‐of‐attainment are 19.41 and 1.83 years, respectively. The probability value on a Lagrange multiplier test for normality of the attainment ages is p = 0.4342. This is a goodness‐of‐fit test indicating that there is a strong basis for arguing that the unobserved distribution of attainment ages is indeed normally distributed.…”

Validation of the Acetabulum As a Skeletal Indicator of Age at Death in Modern European‐Americans,

“…For the purposes of age estimation, this dichotomous distinction may be meaningless. Both metamorphic and degenerative skeletal changes are age correlated, and both should be incorporated into skeletal age‐estimation methods . A potential venue for this incorporation might be the multifactorial Bayesian age‐estimation methods that are currently gaining support among forensic anthropologists .…”