The temporal increase in hip osteoarthritis supports the hypothesis that there was an increasing need for greater logistical mobility over time to procure key resources away from the village sites. Additionally, the lack of sex differences in osteoarthritis prevalence may suggest that females and males likely performed similar levels of activity during these periods.

ANCOVAs or Factorial ANOVAs that incorporate age as a covariate should be considered more often in studies that test different prevalences of age-related osteological markers among past populations.

No abstract

Although the Health Index remains a useful comparison statistic, re-evaluation of fragmentary skeletal remains demonstrates the need for caution when applying it to incomplete skeletal series.

Age-at-death estimation is influenced by biological and environmental factors. Physiological stress is intertwined with these factors, yet their impact on senescence and age estimation is unknown. Stature, linear enamel hypoplasia (LEH), and antemortem tooth loss (AMTL) in the Hamann–Todd Osteological Collection (n = 297) are used to understand whether physiological stress is related to age estimation inaccuracy using transition analysis (TA). Considering the low socioeconomic status of individuals in the collection, it was expected that many people experienced moderate to severe physiological stressors throughout their lives. Of the sample, 44.1% had at least one LEH, but analyses found no relationship between LEH incidence and TA error. There was no association between stature and TA error for males or females. However, females with at least one LEH had significantly shorter statures (t = 2.412, p = 0.009), but males did not exhibit the same pattern (t = 1.498, p = 0.068). Further, AMTL frequency and TA error were related (r = 0.276, p < 0.001). A partial correlation controlling for age-at-death yielded a correlation coefficient of 0.024 (p = 0.684), suggesting that this relationship is mostly explained by age-at-death. These data suggest that age estimation methods are not significantly affected by physiological stress in this sample, but further investigations are needed to understand how these variables relate to skeletal aging.

Sufficient evidence supports arguments that early life conditions can influence adult morbidity and mortality in the past and present. Critical periods in which individuals are more susceptible to stressors leading to long-term effects vary, but how often and to what degree these long-term effects occur is less certain. To evaluate skeletal stress markers that fully develop during different life history stages (i.e., childhood and adolescence) and explore their influence on adult morbidity and mortality, we constructed four growth trajectory categories to estimate the effect of developmental timing of stress indicators on adult mortality risk in skeletal samples from postmedieval London (n = 118 individuals). To construct these growth trajectory categories, linear enamel hypoplasia and tibial length were used as evidence of early life stress during childhood and extended into adolescence. Pairwise relationships between growth trajectory scores and variables such as age, sex, and cemetery were explored using Chi-square and Fisher's exact tests. Long-term effects were also evaluated using Factorial ANOVA as a multifactorial method to test correlations between categorical variables of early life stress and adult mortality risk. Results suggest there was no relationship between age-at-death and growth trajectory score, with the only significance in growth disruption score being between tibial stunting and age-atdeath in males. Socioeconomic status did not impact results of this study, with only two statistically significant relationships noted for one cemetery. Results comparing males and females also yielded no significant differences, indicating sex was not a significant covariate. Overall, this paper presents a model that can help investigate differences between various developmental origins frameworks and be built upon by future researchers using different stress indicators, datasets, and skeletal samples to investigate potential change through time in lived experiences and how that change through time impacts patterns of mortality risk.

Accurate and precise age‐at‐death estimation methods are critical when studying past lifeways. However, adult age‐at‐death estimation is often difficult because of diverse physiologies, preservation, and timing of biological processes in target and reference populations. These challenges can complicate the comparison of results between studies, which can also be impacted by the training and method preference of each bioarchaeologist. In this paper, we first compare the use of two types of age‐at‐death estimation methods, namely, traditional methods (e.g., pubic symphyseal aging) and Transition Analysis. Second, we build upon the work of Falys and Lewis (2011), who reported frequencies of adult age‐at‐death method use between 2000 and 2010, by reporting the frequency of use for traditional methods over the past 40 years with special attention on the last decade. We build further on their work by identifying trends in the minimum age at adulthood, adult age categories, geographic region of institutional affiliation of the first author, and the geographic region of sample origin and interpreting their possible implications on comparability of bioarchaeological literature. Our results show that Transition Analysis, institutional affiliation, and sample origin do not represent major sources of variation in bioarchaeological literature so far. In the case of Transition Analysis, this could result from its limited use thus far, while institutional affiliation and sample origin do not represent major sources of variation because of the relative lack of diversity in both variables. There was, however, substantial variation in the type of traditional method used, the minimum age at adulthood, and adult age categories, which could affect comparability between studies. Our study highlights the need for continued discussion about standardizing bioarchaeological age‐at‐death estimation while respecting the unique needs of diverse target samples.

Bioarcheologists have focused extensively over the past few decades on how to best investigate past activity, often concentrating on data collection protocols and more recently focusing on statistical approaches. Here, we complement ongoing studies focusing on emerging inequality during the Middle Period (AD 400-1000) in the San Pedro de Atacama oases (Chile) by investigating entheseal patterns among individuals (n = 210) interred in four cemeteries. This period represents a time of demographic expansion and the development of interregional networks and formalized social inequalities, all of which would have shaped the lived experiences of local inhabitants. The four cemeteries studied here allow investigations of potential differences between individuals living in a close geographic area: Solcor 3 and Casa Parroquial represent "elite" sites connected with the Tiwanaku state, the somewhat later site of Coyo 3 is associated with mining activities, and Quitor 6 Tardío represents individuals from relatively lower status. Using two complementary multifactorial tests, factorial ANOVA and ANCOVA, we identified differences in entheseal scores in several joints as a proxy for activity patterns among the cemeteries (left and right shoulders and wrists, and left elbow and hip; p < 0.05), with individuals from Casa Parroquial demonstrating lower entheseal scores in most joints. Results highlight how we can infer differences in entheseal patterns among individuals interred in cemeteries that were in close geographic proximity and in use over similar periods, highlighting possible differences in lived experiences in the sites categorized as "elite" as well as the effects of cemetery location, either within the core oases or outside them. Our analyses further suggest that ANCOVA and factorial ANOVA can identify more nuanced differences among the cemeteries while accounting for covariates in a single test, making them more robust inferential statistical approaches for this type of study.