Stature estimation equations for modern American Indians in the American Southwest.

Stature estimation is a core component to the biological profile in forensic anthropology casework. Here we provide mathematical equations for estimating stature for contemporary American Indians (AI), which currently are lacking in forensic anthropology. Drawing on postmortem computed tomography data from the New Mexico Decedent Image Database we regressed cadaveric length on four long bone length measures of the tibia, femur, and humerus to produce 11 combinations of models. Separate regression models were calculated for the entire pooled sample, by sex, broad AI language groups, and age + sex subsamples and compared. Sex-specific models were statistically better than general models, which were more accurate than language group and age + sex models. Equations were created for general and sex-specific models. Application to an independent test sample demonstrates the equations are accurate for stature estimation with overestimates of less than 1 cm. The equations provide similar levels of precision to stature estimation programs like the FORDISC 3.0 module and other stature equations in the literature. We provide recommendations for equation use in casework based on our results. These equations are the first for estimating stature in contemporary AI. This paper demonstrates the appropriateness of these newly created stature equations for use in New Mexico and the surrounding region.

New Approaches to Juvenile Age Estimation in Forensics: Application of Transition Analysis via the Shackelford et al. Method to a Diverse Modern Subadult Sample.

Dental development is one of the most widely utilized and accurate methods available for estimating age in subadult skeletal remains. The timing of tooth growth and development is regulated by genetics and less affected by external factors, allowing reliable estimates of chronological age. Traditional methodology focuses on comparing tooth developmental scores to corresponding age charts. Using the Moorrees, Fanning, and Hunt (MFH) developmental scores, Shackelford and colleagues embed the dental development method in a statistical framework based on transition analysis. They generated numerical parameters underlining each "stage" and age-at-death distribution and applied them to fossil hominins and Neanderthals with limited application to modern humans. We use this same method on a subadult test sample (n = 201), representing modern individuals that may become part of the forensic record. We assess the probability coverage of the Shackelford et al. method derived from MFH standards as it applies to all available dentition. Results indicate promise: the age range at 90% and 95% confidence levels includes the chronological age of almost every individual tested. The maximum likelihood age estimates underestimate age by 0.5-2.5 years for individuals 0-15 years of age and by >2.5 years for individuals 16-18 years of age, as previously shown. In an attempt to refine the method, we adjusted the numerical parameters underlying the stages for developing teeth based on a combined modern reference sample (n = 1,964) and tested these revised parameters using the same test sample. The estimated ages from the modified method differ from the original Shackelford et al. methodology by underestimating age to a lesser degree. The modified method does include mean age-at-attainment values for earlier stages of several teeth, allowing for the calculation of narrower confidence intervals. While this study highlights areas of future research in refining dental developmental aging by transition analysis, it also demonstrates that the Shackelford et al. method is applicable and accurate when aging modern subadults in forensic work.

Intraobserver Error in Macromorphoscopic Trait Data,.

As part of a much larger investigation into the use of macromorphoscopic trait data by forensic anthropologists to estimate ancestry from unidentified skeletal remains, we conducted a fourteen-year (2002-2016) intraobserver error study. Motivated by the development of a large macromorphoscopic database-which will potentially utilize data collected in 2002-quantification of observer error, the impact of technological improvements in macromorphoscopic trait data collection and observer experience is necessary. To maximize comparisons between the two samples, ten macromorphoscopic traits were assessed. Results revealed three patterns of error relating to observer experience, the introduction of new technologies, and error inherent in the method. Overall, this study found the effect of error on macromorphoscopic trait analysis could be predicted and did not significantly impact their utility.