Setting the stage for medieval plague: Pre‐black death trends in survival and mortality

DeWitte, Sharon N.

doi:10.1002/ajpa.22806

Cited by 55 publications

(51 citation statements)

References 94 publications

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“…These results demonstrate the impact of method choice on survival curves, a finding that is significant given the increasing reliance on survival curves in bioarchaeological studies (e.g., Nagaoka & Hirata, , DeWitte, , DeWitte & Bekvalac, , DeWitte, , DeWitte & Yaussy , Betsinger & DeWitte, , Fojas, , Gamble, Boldsen, & Hoppa, , Mayus, , Plemons, Davenport, & Herrmann, , Weisensee, Shillinglaw, & Bereczki, ). In our study, the likelihood of survival beyond middle age was significantly reduced when traditional aging methods were used.…”

Section: Discussionmentioning

confidence: 63%

Aging methods and age‐at‐death distributions: Does transition analysis call for a re‐examination of bioarchaeological data?

Clark

Simon

Hübbe

2019

Intl J of Osteoarchaeology

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Age estimation of adult skeletal remains is notoriously difficult because the degenerative change of adult skeletons is far more variable across individuals, populations, and anatomical regions than the developmental changes that occur during growth. Additionally, age mimicry makes it difficult to discern between the true population age structure and the age structure produced as an artifact of the reference sample. Transition analysis is an age estimation method that was developed to improve the accuracy of age estimation, especially in older adults, by applying a stricter statistical framework based on multiple osteological age markers. Despite its availability since 2002, bioarchaeologists continue to rely heavily on traditional aging methods. However, since transition analysis has begun to gain popularity, it is necessary to identify how the choice of age estimation method affects interpretations about life in the past, especially when samples aged through transition analysis are compared to samples aged with traditional methods. This study evaluates the effect of aging methods on age‐at‐death distributions in a sample from the Late Archaic and Prehistoric periods in Northeast Ohio. Ninety‐three skeletons were aged using both traditional aging methods and transition analysis, and the results from both methods were compared. The two aging methods produced vastly different age‐at‐death distributions and significantly different survival curves. This study shows that bioarchaeologists should be wary of taking pre‐existing data at face value and should consider interpreting data using both traditional aging methods and transition analysis until the accuracy of transition analysis is more clearly established.

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Section: Discussionmentioning

confidence: 63%

Aging methods and age‐at‐death distributions: Does transition analysis call for a re‐examination of bioarchaeological data?

Clark

Simon

Hübbe

2019

Intl J of Osteoarchaeology

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“…Sex is often not determined for prepubescent skeletons, and thus many paleodemographic studies are missing these data for (sometimes substantial) portions of their samples (in some cases, where sex is an important component of the overall research design, subadults are totally excluded from sample selection because of the issues with sexing prepubescent individuals). Examples of this in AJPA include studies by Alesan, Malgosa, and Simó (), Brewis et al (), DeWitte (), Douglas, Pietrusewsky, and Ikehara‐Quebral (), Fernández‐Crespo and de‐la‐Rúa (), Margerison and Knüsel (), Nagaoka and Hirata (), Owsley and Bass (), Rathbun (), Redfern, DeWitte, Pearce, Hamlin, and Dinwiddy (), and Wilson (). The estimation of adult sex is most often based on sexually dimorphic features of the skeleton, such as components of the skull and pelvis, and on long bone, dental, or cranial measurements.…”

Section: Problems With Demographic Datamentioning

confidence: 99%

“…The general method of transition analysis can be applied to any skeletal features that exhibit regular patterns of change with age and is not dependent on the ADBOU software (e.g., see Godde & Hens, ; Konigsberg, Herrmann, Wescott, & Kimmerle, ). Several applications or evaluations of the performance of transition analysis and other Bayesian approaches to age or mortality profile estimation have been published in AJPA (e.g., Boldsen, ; Bullock, Márquez, Hernández, & Ruíz, ; DeWitte, ; DiGangi, Bethard, Kimmerle, & Konigsberg, ; Godde & Hens, ; Hughes‐Morey, ; Konigsberg & Frankenberg, ; Lottering, MacGregor, Meredith, Alston, & Gregory, ; Milner & Boldsen, ; Steadman, Adams, & Konigsberg, ; Stojanowski & Duncan, ; Storey, ; Usher & Christensen, ; Wilson, ; Wittwer‐Backofen et al, ).…”

Section: Potential Solutionsmentioning

confidence: 99%

Demographic anthropology

DeWitte

2018

American J Phys Anthropol

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K E Y W O R D S : enthnographic census, life tables, paleodemography, population models 1 | I N TR ODU C TI ON Demography is the study of population dynamics. The primary foci of demography are rates and levels of mortality, fertility, and migration and how these all interact to produce population growth (or decline), density, and age-and sex-structures; how these rates or levels vary across time and space and what produces such variation; and what consequences these have on other aspects of human (or nonhuman) existence. These demographic phenomena lie at the very heart of evolution. Natural selection occurs as a result of differential fertility and mortality within a population; gene flow occurs because of migration between populations; and the effects of genetic drift are dependent upon population size, which is an outcome of the interactions among mortality, fertility, and migration (Gage, DeWitte, & Wood, 2012).These demographic forces also affect, are affected by, and reflect many of the things that anthropologists find most interesting. For example, the age-sex structure of a population influences the population's ratio of consumers to producers and numbers of potential marriage partners, and thus places limits on such things as subsistence strategies and household structure. The age-sex structure of a population can also significantly influence economic relationships among families and communities, as cultures often have inheritance and habitation rules that depend on the sex and sometimes age of individuals, and thus are inherently influenced strongly by demographic structure. Population growth and density affect socio-political structures and shape disease ecologies, which can, in turn, affect demographic rates and drive biological and cultural adaptations. Sociocultural phenomena also have the potential to powerfully shape demography. For example, warfare can have short-and long-term effects on sex ratios or age structures (as in the case of the post-World War II baby boom). Sexselective infanticide and abortion, and withholding of resources or medical care from daughters because of cultural preferences for sons affects sex ratios. Economic policies and warfare influence patterns of migration. Ultimately, demography is relevant to all fields of anthropology, whether or not all anthropologists are interested in demography itself and its effects on other aspects of human life. Although, as can be seen in the pages of the American Journal of Physical Anthropology, numerous anthropologists over the last 100 years of the journal's existence have been explicitly interested in demography, and in demographic anthropology in particular. In contrast to national demography, which primarily focuses on large datasets (often derived from censuses) from European and other industrialized populations, demographic anthropology typically focuses on relatively small, nonindustrial populations from which data are collected as a part of ethnographic fieldwork. Demographic anthropology also examines the demography of populat...

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“…All age groups are represented within the cemetery population, and they are buried within the same short period of the plague epidemic. However, older individuals will be a cohort who experienced the Great Famine of 1315–1317, which killed as much as 10% or more of the population of England (Kershaw ) and was followed by the Great Bovine Pestilence (1319–1320), which caused decades‐long milk scarcities (Kershaw ; DeWitte and Slavin ): their diet and health at that period may have affected their likelihood to survive the later epidemic compared with younger individuals with a better‐nourished childhood (DeWitte ).…”

Section: Introductionmentioning

confidence: 99%

The Whole Tooth and Nothing but the Tooth: Or why Temporal Resolution of Bone Collagen May Be Unreliable

Beaumont

2020

Archaeometry

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The carbon (δ 13 C) and nitrogen (δ 15 N) isotope ratios of human bone collagen have been used extensively over the last 40 years to investigate the diet of past populations. It has become apparent that bone collagen can give an unreliable temporal dietary signature especially in juveniles. With higher temporal resolution sampling of collagen from tooth dentine, it is possible to identify short-term changes in diet previously invisible in bone. This paper discusses the inherent problems of using bone collagen for dietary studies and suggests better sample choices, which can make our interpretations more robust, using breastfeeding and weaning as an example.

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Setting the stage for medieval plague: Pre‐black death trends in survival and mortality

Abstract: Together, these results suggest that health in general was declining in the 13(th) century, and this might have led to high mortality during the Black Death. This highlights the importance of considering human context to understand disease in past and living human populations.

Cited by 55 publications

References 94 publications

Aging methods and age‐at‐death distributions: Does transition analysis call for a re‐examination of bioarchaeological data?

Aging methods and age‐at‐death distributions: Does transition analysis call for a re‐examination of bioarchaeological data?

Demographic anthropology

The Whole Tooth and Nothing but the Tooth: Or why Temporal Resolution of Bone Collagen May Be Unreliable

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