Research Article
Estimating age from adult occlusal wear: A modification of the miles method
Article first published online: 4 JUL 2012
DOI: 10.1002/ajpa.22106
Copyright © 2012 Wiley Periodicals, Inc.
Additional Information
How to Cite
Gilmore, C. C. and Grote, M. N. (2012), Estimating age from adult occlusal wear: A modification of the miles method. Am. J. Phys. Anthropol., 149: 181–192. doi: 10.1002/ajpa.22106
Publication History
- Issue published online: 14 SEP 2012
- Article first published online: 4 JUL 2012
- Manuscript Accepted: 22 MAY 2012
- Manuscript Received: 1 DEC 2011
Funded by
- L.S.B. Leakey Foundation
- Abstract
- Article
- References
- Cited By
Keywords:
- tooth wear;
- age estimation;
- hunter-gatherers
Abstract
The Miles method of age estimation relies on molar wear to estimate age and is widely used in bioarcheological contexts. However, because the method requires physical seriation and a sample of subadults to estimate wear rates it cannot be applied to many samples. Here, we modify the Miles method by scoring occlusal wear and estimating molar wear rates from adult wear gradients in 311 hunter-gatherers and provide formulae to estimate the error associated with each age estimate. A check of the modified method in a subsample (n = 22) shows that interval estimates overlap in all but one case with age categories estimated from traditional methods; this suggests that the modifications have not hampered the ability of the Miles method to estimate age even in heterogeneous samples. As expected, the error increases with age and in populations with smaller sample sizes. These modifications allow the Miles method to be applied to skeletal samples of adult crania that were previously only amenable to cranial suture age estimation, and importantly, provide a measure of uncertainty for each age estimate. Am J Phys Anthropol 149:181–192, 2012. © Wiley Periodicals, Inc.

1096-8644/asset/olbannerleft.gif?v=1&s=33f8ec505be287504f05fadcc3bcee886f62295e)
1096-8644/asset/olbannerright.gif?v=1&s=4305dbacc7e375e9300998894487b997b557e791)
