10. Expoloring Age - Transition Analysis as a Tool for Detecting the Elderly

Maaranen, Nina; Buckberry, Jo

doi:10.31265/ams-skrifter.v0i26.215

Cited by 6 publications

(10 citation statements)

References 75 publications

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“…When looked at separately, the pubic symphysis generally produces the best estimates followed by the sacroiliac joint, with the cranial sutures finishing a distant third, similar to what another validation study found (Maaranen & Buckberry, 2018).…”

Section: Prior Distributionssupporting

confidence: 75%

Paleodemography: From archaeology and skeletal age estimation to life in the past

Boldsen

Milner

Ousley

2021

American Journal of Biological Anthropology

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Much of paleodemography, an interdisciplinary field with strong ties to archaeology, among other disciplines, is oriented toward clarifying the life experiences of past people and why they changed over time. We focus on how human skeletons contribute to our understanding of preindustrial demographic regimes, including when changes took place that led to the world as we know it today. Problems with existing paleodemographic practices are highlighted, as are promising directions for future work. The latter requires both better age estimates and innovative methods to handle data appropriately. Age‐at‐death estimates for adult skeletons are a particular problem, especially for adults over 50 years that undoubtedly are mistakenly underrepresented in published studies of archaeological skeletons. Better age estimates for the entirety of the lifespan are essential to generate realistic distributions of age at death. There are currently encouraging signs that after about a half‐century of intensive, and sometimes contentious, research, paleodemography is poised to contribute much to understandings of evolutionary processes, the structure of past populations, and human‐disease interaction, among other topics.

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Section: Prior Distributionssupporting

confidence: 75%

Paleodemography: From archaeology and skeletal age estimation to life in the past

Boldsen

Milner

Ousley

2021

American Journal of Biological Anthropology

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“…Although TA is a statistical step forward, its age estimates still fall short of what is needed for forensic and archaeological applications, particularly for individuals between 45 and 75 years of age (Milner & Boldsen, 2012c). Despite the method's correction for correlated traits, applications of the method have found lower accuracy (i.e., percentage of individuals falling into estimates ranges that contain their true age) than what would be expected given the use of 95% prediction intervals (Getz, 2017;Jooste et al, 2016;Maaranen & Buckberry, 2018). This finding indicates that the ad hoc correction for trait correlations is not entirely successful.…”

Section: Boldsen Et Al (2002) Methods Performancementioning

confidence: 99%

“…Encouragingly, several studies evaluating TA have found that the commonly held assumption that variation in adult age indicators increases throughout adulthood may be unjustified. Although skeletal variation increases between 45 and 75 years of age, it appears to decrease after this time, as reflected in a narrowing of predicted age intervals (Getz, 2017;Jooste et al, 2016;Maaranen & Buckberry, 2018;Milner & Boldsen, 2012c)4. Additionally, there appears to be acceptably low inter-observer error in most trait scores (Fojas et al, 2018;Jooste et al, 2016), which indicates that results can be reliably compared among observers.…”

Section: Boldsen Et Al (2002) Methods Performancementioning

confidence: 99%

“…The output of the method is individualized age-at-death estimates for each skeleton based on the features available, their character states, and user-selected information (i.e., sex, ancestry1, and prior distribution). Since its publication, the method has gained in popularity and has demonstrated its utility in modern (Fojas, Kim, Minsky-Rowland, & Algee-Hewitt, 2018;Getz, 2017;Jooste, L'Abbe, Pretorius, & Steyn, 2016;Milner & Boldsen, 2012c), as well as historical and archaeological contexts (Boldsen, 2007;Bullock, Márquez, Hernández, & Ruíz, 2013;DeWitte, 2010;Getz, 2017;Maaranen & Buckberry, 2018;Wilson, 2014;Wittwer-Backofenet al, 2008).…”

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confidence: 99%

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The use of transition analysis in skeletal age estimation

Getz

2020

WIREs Forensic Science

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The ability to produce accurate and precise age-at-death estimates from adult skeletal remains is critical for both forensic and bioarchaeological analyses. Despite many decades of investigation, anthropologists are still heavily reliant on methods that fail to adequately capture biological variation in skeletal aging and produce estimates that are insufficient for most applications. The Transition analysis (TA) by Boldsen et al. (2002) refers to a broad category of statistical approaches used to generate probabilistic information from binary or ordinal reference data as well as a specific method, Transition Analysis (TA) (Boldsen et al. 2002), that combines components of the cranial sutures and pelvic joints. The TA method uses free software to generate age estimates from the available trait scores, a statistical correction for the use of correlated features, and information about population mortality structure. Variations of the transition analysis approach have also applied to data from traditional ageestimation methods, isolated areas of the skeleton, and many features distributed throughout the body. Investigations of TA and other transition analysisbased approaches on archaeological, historic, and modern remains have demonstrated significant improvements in our ability to document skeletal variation, produce estimates in the upper half of the adult lifespan, and investigate patterns of mortality in the past. Despite these improvements, several challenges remain, including wide age intervals and systematic age-estimation bias, particularly for individuals in the youngest and oldest portions of adulthood. Moving forward, component-based approaches capable of producing individualized, probabilistic estimates using new skeletal features and userfriendly software are needed.

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“…As TA2 was developed on American—the Terry—and Portuguese—the Coimbra—collections (Boldsen, Milner, Konigsberg, et al, 2002; Milner & Boldsen, 2012a), a series of validation studies have been performed to test broad population applicability. These have shown the method's suitability for the analysis of the United States (Fojas et al, 2018; Milner & Boldsen, 2012c; Simon & Hubbe, 2021), Colombian (Lopez‐Cerquera & Casallas, 2018), Finnish (Maaranen & Buckberry, 2018), and South African populations (Jooste et al, 2016) (Table 1), while its performance on Asian populations remains unknown.…”

Section: Introductionmentioning

confidence: 99%

Age‐at‐death patterns and transition analysis trends for three Asian populations: Implications for [paleo]demography

Kim

Algee‐Hewitt

2021

American Journal of Biological Anthropology

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Objectives Age‐at‐death estimation provides biological anthropologists with fundamental biographic information to help resolve various theoretical and practical questions about both individual expression and populational trends in present and past contexts. Particularly, researchers interested in reconstructing past populations' mortality profiles have favored using Boldsen and colleagues' Transition Analysis (TA2), as the method provides both methodological and statistical solutions for optimally treating traditional ordinal, categorical score data from multiple age indicators. In this article, we present an assessment of TA2 to better understand its age estimation patterns and trends when applied to a large‐scale, documented Asian skeletal sample. Materials and methods Specifically, this study examines the patterns of error and bias of TA2 when applied to three Asian populations. We assess cumulative effects of the age estimates in mortality reconstruction, and TA2's ability to accurately characterize the effects of covariates (e.g., sex, stature) that are linked to inequal social status and differential access to resources and known to further cause mortality disparities. Results The results show that age estimates of three age indicators (the pubic symphysis, auricular surface, and cranial sutures) combined with an informed prior produced the most accurate age estimates across all three Asian samples. Thus, the age composition of a target skeletal sample dictates the accuracy of TA2 estimates, and therefore demographic parameters. Discussion Although the exact parameter values may differ from the true values and a consistent underestimation of female age‐at‐death and survivorship is evident, TA2 recovers a realistic approximation of a mortality pattern by revealing (previously hidden) elderly individuals.

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10. Expoloring Age - Transition Analysis as a Tool for Detecting the Elderly

Cited by 6 publications

References 75 publications

Paleodemography: From archaeology and skeletal age estimation to life in the past

Paleodemography: From archaeology and skeletal age estimation to life in the past

The use of transition analysis in skeletal age estimation

Age‐at‐death patterns and transition analysis trends for three Asian populations: Implications for [paleo]demography

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