Abstract
This paper seeks to provide a stabilised (i.e. less vulnerable to differences in sex
representation) equation for estimating maternal mortality for biased skeletal samples. The stabilised equation is developed and tested on the United Nations (2017) data used to develop the original method (McFadden and Oxenham, 2019), and is applied to 16 bioarchaeological samples from mainland Southeast Asia. First order correlations and basic descriptive statistics were applied to the data. The stabilised equation was comparable in accuracy to the original equation. When applied to bioarchaeological samples, it proved to be advantageous where the sex ratio differed by more than 0.15 in either direction (i.e. more females or more males). The stabilised equation is an improvement over the original equation for samples that exhibit sex-bias that is randomly distributed by age. This method extends the potential applications of the maternal mortality estimator.
representation) equation for estimating maternal mortality for biased skeletal samples. The stabilised equation is developed and tested on the United Nations (2017) data used to develop the original method (McFadden and Oxenham, 2019), and is applied to 16 bioarchaeological samples from mainland Southeast Asia. First order correlations and basic descriptive statistics were applied to the data. The stabilised equation was comparable in accuracy to the original equation. When applied to bioarchaeological samples, it proved to be advantageous where the sex ratio differed by more than 0.15 in either direction (i.e. more females or more males). The stabilised equation is an improvement over the original equation for samples that exhibit sex-bias that is randomly distributed by age. This method extends the potential applications of the maternal mortality estimator.
Original language | English |
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Pages (from-to) | 113-117 |
Number of pages | 5 |
Journal | Anthropological Science |
Volume | 128 |
Issue number | 3 |
Early online date | 4 Aug 2020 |
DOIs | |
Publication status | Published - 4 Aug 2020 |
Keywords
- sample bias
- fertility
- maternal mortality
- childbirth
- pregnancy