The association between periodontal disease and periosteal lesions in the St. Mary Graces cemetery, London, England A.D. 1350-1538

Abstract

Numerous studies have demonstrated significant associations between periodontal disease and many other diseases in living populations, and some studies have shown that individuals with periodontal disease are at elevated risks of mortality. Recent analysis of a medieval skeletal sample from London has also shown that periodontal disease was associated with increased risks of mortality in the past. This study examines whether periodontal disease is associated with periosteal lesions in a skeletal sample from the urban St. Mary Graces cemetery (n = 265) from medieval London. The results reveal a significant association between periodontal disease and periosteal lesions in the St. Mary Graces sample (i.e., individuals with periodontal disease were also likely to have periosteal lesions), and the association between the two is independent of age. The association between the two pathological conditions might reflect underlying reduced immune competence and thus heightened susceptibility to pathogens that cause periodontal disease or periosteal lesions, exposure to an environmental factor, or underlying heightened inflammatory responses.

Paleopathology

“…The sugar and starch content and stickiness and abrasiveness of foods influence caries formation, so cooking technologies complicate interpretation. A study from Medieval England (Dewitte and Bekvalac, 2011) reveals the same association with increased mortality that was discovered quite recently in modern people. These studies offer epidemiological insights that complement present-day research (Russell et al, 2013).…”

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

“…The average Δ age (16.44 years) was high enough to require thoughtful consideration when choosing an age estimation method and drawing conclusions based on those estimations. Bioarchaeologists often divide skeletal samples into age cohorts of 10–15 years (e.g., Lieverse, Weber, Ivanovich Bazaliiskiy, Ivanova Goriunova, & Aleksandrovich Savel'ev, , Berbesque & Doran, , Rojas‐Sepúlveda, Ardagna, & Dutour, , Šlaus, , Klaus, Larsen, & Tam, , Klaus & Tam, , Scott & Buckley, , Dabbs, , DeWitte & Bekvalac, , Novak & Šlaus, , DeWitte, , Woo & Sciulli, , Da‐Gloria & Larsen, , Griffin, , Marklein, Leahy, & Crews, , Krakowka, , Ostendorf Smith, Kurtenbach, & Vermaat, , Trautmann, Wißing, Díaz‐Zortia Bonilla, Bis‐Worch, & Bocherens, , Geber & Murphy, , Hubbe, Green, Cheverko, & Neves, , Milella, Betz, Knüsel, Larsen, & Dori, , Yaussy & DeWitte, ), and under these conditions, a difference of 16.44 years is enough to move an individual into a different category entirely. There is also considerable variation around the mean Δ age (standard deviation = 11.97), showing that comparing the two methods is not only a matter of correcting them by adding or subtracting a constant.…”

Frontiers in the bioarchaeology of stress and disease: Cross‐disciplinary perspectives from pathophysiology, human biology, and epidemiology

“…Bioarchaeology should begin a broader experimentation with these and other techniques in epidemiology, such as Bayesian methods, the conditional maximum likelihood estimator, logistic regression, or hierarchical log linear analyses (DeWitte and Bekvalac, 2011). There are many potential paths to measure prevalence.…”