Kirsten Kelmelis

Grant Type

Dissertation Fieldwork Grant

Institutional Affiliation

Pennsylvania State U.

Grant number

Gr. 9604

Approve Date

April 13, 2018

Project Title

Kelmelis, Kirsten S., Pennsylvania State U., University Park, PA - To aid research on 'Modeling Variation in Well-Being in Urban and Rural Skeletal Samples from Medieval Denmark,' supervised by Dr. James Wood

Preliminary abstract: In paleodemography, urbanization has been viewed as detrimental to well-being for human populations, as the formation of urban centers led to unsanitary living conditions, food shortages, and infectious diseases. However, the reconstruction of past well-being is complicated by the practical constraints of poor preservation, lack of cultural context, and small sample size, as well as the theoretical challenges of heterogeneous frailty and selective mortality. This project will study osteological differences in well-being among urban and rural populations from northern Denmark using three representative skeletal samples in a maximum likelihood modeling framework to account for the important issues of heterogeneous frailty and selective mortality in death assemblages. Skeletal samples from Ole Worms Gade, Sejet, and Øm Kloster represent a regional sample of medieval-early modern (ca. 1050-1536 AD) preindustrial people near the city of Horsens that experienced different population densities and social settings, which I hypothesize will be observed in skeletal variations of lesions indicating frailty and selectivity within and across samples. As well-being can be remarkably diverse both within and across populations, I will use multiple skeletal markers of stress and non-specific infection that develop in childhood to disentangle individual and group level differences and assess how well-being interacts with infections that manifest on the skeleton in later years, such as leprosy, tuberculosis, treponematosis, and periodontal disease. As a study focused on past health, this project will contribute to a broader understanding of how individual well-being varies across time and space, and how those differences are related to population dynamics.