The accurate estimation of age at death of human skeletal remains is an important aspect of many disciplines including archaeology, palaeopathology and medicine. The aim of this project was to investigate five aspects of the endocranial surface of the skull, mid-parietal thickness, hyperostosis frontalis interna (HFI), cranial suture fusion, vascular grooves and arachnoid granulations and to evaluate their relationship with age. Four samples (total 697 skeletons) were used: (1) A modern post-mortem population; (2) an early 20th century American anthropological collection; (3) A 17th-19th century French/English archaeological sample; (4) An English 10th-19th century archaeological sample. Three of these samples were of known age at death. Direct measurement, recording and X-ray techniques were used to evaluate the relationship between specific bone changes and age. A measurable, but weak relationship with age was observed in skull mid-parietal thickness, HIF, rate of endocranial and ectocranial suture fusion and the cross sectional profile of meningeal vessel grooves. A new technique for the diagnosis of HFI was proposed, based on standard x-ray score. Use of this method on the four samples showed that HFI is not increasing in prevalence with modernity, as previously thought. A strong relationship was observed between arachnoid granulation pit counts and age. A new method for estimating age at death was proposed and tested on two populations of known age. This new method was as accurate in estimating age at death as two of the most popular techniques currently in use. The method has less bias in ageing, can be applied to both sexes with equal accuracy and has no maximum age cut-off point.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:498048 |
| Date | January 1997 |
| Creators | Barber, Geraldine Anne |
| Publisher | University of Bristol |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1983/e21cfbf9-d22e-4b08-ad7f-d771a5c97c5b |
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