Interpreting error in the estimation of skeletal growth profiles from past populations: An example demonstrating skeletal growth in historic African American communities.

OBJECTIVES: The study of growth in the past is a critical component of bioarcheological analyses. However, our understanding of growth in the past is subject to a number of methodological challenges. This study aims to model the skeletal growth of past populations by considering the challenges associated with the data collection process and the challenges associated with the age estimation procedures. MATERIALS AND METHODS: We use skeletal remains from two historic African American cemeteries in the American South to model femoral diaphyseal length-for-age. We estimate the age of each individual using dental development techniques and present growth curves as both a product of the maximum likelihood (MLE) age estimate and the estimated posterior age distribution. Growth was compared against a reference sample from the University of Colorado Child Research Council Study. RESULTS: The results of our analyses showed that femoral diaphyseal length in two historic African American communities is small-for-estimated age as compared to a modern reference sample. However, the magnitude and characterization of this difference is variable when taking into account the broader posterior age distribution. DISCUSSION: Both samples may be small-for-age due to physiological stress associated with racism, inequality, and the compounding effects of early urbanization. However, the interpretation of growth in the past is muddled when considering the relationship between the study sample and the reference sample, when accounting for uncertainty in the age estimation procedure, and the error-inducing steps taken during the data collection process. Future interpretation of skeletal growth in the past must include a full account of the possible sources of error in order to present an accurate representation of growth.

Identifying migrant remains in South Texas: policy and practice.

In 2012, Texas surpassed Arizona in migrant deaths. The majority of deaths occurred in the Rio Grande Valley, specifically in Brooks County, Texas. Brooks County is one of the poorest in the state and was overwhelmed with deaths, without appropriate resources to follow the state laws pertaining to the investigation of unidentified human remains. Until 2013, most remains that were not immediately identified were buried without collecting DNA samples and the location of burials was not recorded. Our paper outlines the difficulties searching for these burials, the struggles of the families of the missing, and the collaborative approaches to facilitating identifications in South Texas. Community outreach combined with geophysical surveys guide which cemeteries are in need of exhumations. Once cemeteries are surveyed, archaeological methods are employed to exhume remains and document burials. Remains are taken to the Forensic Anthropology Center at Texas State for processing, analysis, and identification efforts. Undergraduate and graduate students clean remains and wash clothing and personal effects. After skeletal analysis, all information regarding the remains, including photographs of personal effects, are uploaded to the National Missing and Unidentified Persons System (NamUs) and a DNA sample is submitted to the University of North Texas for inclusion in the Combined DNA Index System (CODIS) DNA database. However, CODIS lacks DNA family reference samples from many families of the missing due to families living outside the US or because they do not feel comfortable providing a DNA sample in the presence of law enforcement. Therefore, it is necessary to work with non-governmental organizations who specialize in collecting missing persons reports and DNA samples from the families of the missing. Working collaboratively with multiple agencies, identification of migrant remains is possible.

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.

Refining Stable Oxygen and Hydrogen Isoscapes for the Identification of Human Remains in Mississippi.

Isoscape refinement is an essential component for accurately predicting region-of-origin in forensic investigations involving isotope analysis of unidentified human remains. Stable oxygen (δ18 O) and hydrogen (δ2 H) isotopes were measured from 57 tap water samples collected across Mississippi to model refined isoscapes for the state. A tap water conversion equation, δ18 Otw =1.64 δ18 Op-31.35, was developed for the southeastern USA to test the prediction accuracy of the δ18 Otw isoscape using individuals with known residential histories. A local Mississippi resident (USAFA-134) was assigned with 90% probability to the correct region-of-origin reported by the participant. Assignments for Georgia residents (USAFA-118 and USAFA-205) had variable results, predicting USAFA-118 from Mississippi and USAFA-205 as a nonlocal resident. Stable isotope values often overlap geographically and a multi-isotope approach should be used when narrowing region(s)-of-origin(s). This study demonstrates the utility of refining isoscapes and the importance of tissue calibration in prediction assignments of human remains.

Computerized reconstruction of fragmentary skeletal remains.

This research presents a new software, "Fragmento", for accurate analyses of fragmentary human skeletal remains and facilitation of three-dimensional (3D) fragmentary matching and full bone reconstruction. The framework utilizes the power of statistical bone atlases to create 3D templates for bone matching and to interpolate missing anatomy for full bone reconstruction. Developed tool has enhanced features allowing the user to visualize, review and scale all scanned skeletal remains within a 3D statistical template, merging accepted registered elements to provide a fully reconstructed bone. A three stage validation was performed on Fragmento: Stages I and II used simulated fragmentary data which was compared to full bones with an error less than 3mm; Stage III compared output from geographic information system (GIS) software with comparable results. This validation process demonstrates the robustness and utility of Fragmento as tool for 3D fragmentary bone matching and full bone reconstruction.

Evaluation of stature estimation from the database for forensic anthropology.

Trotter and Gleser's (1-3) stature equations, conventionally used to estimate stature, are not appropriate to use in the modern forensic context. In this study, stature is assessed with a modern (birth years after 1944) American sample (N = 242) derived from the National Institute of Justice Database for Forensic Anthropology in the United States and the Forensic Anthropology Databank. New stature formulae have been calculated using forensic stature (FSTAT) and a combined dataset of forensic, cadaver, and measured statures referred to as Any Stature (ASTAT). The new FSTAT-based equations had an improved accuracy in Blacks with little improvement over Ousley's (4) equations for Whites. ASTAT-based equations performed equal to those of FSTAT equations and may be more appropriate, because they reflect both the variation in reported statures and in cadaver statures. It is essential to use not only equations based on forensic statures, but also equations based on modern samples.

Estimation of living stature from selected anthropometric (soft tissue) measurements: applications for forensic anthropology.

Estimation of living stature has obvious utility in the identification process. Typically, anthropologists estimate stature from the measurement of long bone length. This type of analysis is traditionally conducted on skeletonized or badly decomposed remains, so collection of the necessary bone measurements is relatively simple. As the role of anthropologists expands into medical examiner offices and mass fatality incidents, the analysis of fleshed bodies and body parts is a more common scenario. For stature estimation in these types of cases (e.g., analysis of body portions recovered from an aircraft crash site or from intentional dismemberment), the presence of soft tissue on the human remains would usually necessitate dissection to expose skeletal elements to derive metric data for stature estimation. In order to circumvent this step, this paper provides various formulae that allow for standard anthropometric (i.e., soft tissue) measurements to be used in place of skeletal measurements. Data were compiled from several anthropometric studies (National Health and Nutrition Examination Survey [NHANES] and U.S. Army Anthropometric Survey [ANSUR]) and numerous regression models are presented. Results are compared between skeletal measurements and the anthropometric measurements from each study. It was found that the ANSUR models are similar to the skeletal models, while the NHANES models exhibit weaker correlation coefficients and higher standard errors. Overall, this study finds that stature estimates derived from anthropometric data provide good results and remove the necessity for dissection when working with fleshed body portions.

Estimation and evidence in forensic anthropology: age-at-death.

A great deal has previously been written about the use of skeletal morphological changes in estimating ages-at-death. This article looks in particular at the pubic symphysis, as it was historically one of the first regions to be described in the literature on age estimation. Despite the lengthy history, the value of the pubic symphysis in estimating ages and in providing evidence for putative identifications remains unclear. This lack of clarity primarily stems from the fact that rather ad hoc statistical methods have been applied in previous studies. This article presents a statistical analysis of a large data set (n = 1766) of pubic symphyseal scores from multiple contexts, including anatomical collections, war dead, and victims of genocide. The emphasis is in finding statistical methods that will have the correct "coverage.""Coverage" means that if a method has a stated coverage of 50%, then approximately 50% of the individuals in a particular pubic symphyseal stage should have ages that are between the stated age limits, and that approximately 25% should be below the bottom age limit and 25% above the top age limit. In a number of applications it is shown that if an appropriate prior age-at-death distribution is used, then "transition analysis" will provide accurate "coverages," while percentile methods, range methods, and means (+/-standard deviations) will not. Even in cases where there are significant differences in the mean ages-to-transition between populations, the effects on the stated age limits for particular "coverages" are minimal. As a consequence, more emphasis needs to be placed on collecting data on age changes in large samples, rather than focusing on the possibility of inter-population variation in rates of aging.