John Albanese

A Metric Method for Sex Determination Using the Proximal Femur and Fragmentary Hipbone

Abstract:  The pubic bone is considered one of the best sources of information for determining sex using skeletal remains, but can be easily damaged postmortem. This problem has led to the development of nonpelvic methods for cases when the pubic bone is too damaged for analysis. We approached this problem from a different perspective. In this article, we present an approach using new measurements and angles of the proximal femur to recreate the variation in the pubic bone. With a sample from the Terry Collection (n > 300), we use these new variables along with other traditional measurements of the femur and hipbone to develop two logistic regression equations (femur and fragmentary hipbone, and femur only) that are not population specific. Tests on an independent sample (Grant Collection; n = 37–40) with a different pattern of sexual dimorphism resulted in an allocation accuracy of 95–97% with minimal difference by sex.

A Method for Estimating Sex Using the Clavicle, Humerus, Radius, and Ulna

Sex estimation from skeletal remains can be an important part of preliminary identification. The best source of information for estimating sex is the pelvis but it is not always available for analysis. For these cases, a probabilistic sex estimation method is presented using combinations of standard and alternative measurements of the clavicle, humerus, radius, and ulna. Various equations are developed that are not population specific and that are applicable in various recovery scenarios. The equations were tested using four independent samples (n > 370), including a forensic sample. Allocation accuracies vary by test sample and equation and are consistently good (87.4–97.5%) except for a sample of very small males that show the extreme effects of poverty and mortality bias. For many of the cases where allocation was incorrect, the probabilistic approach indicated that no confidence should be placed in the incorrect allocation and the unknown should be classified as sex indeterminate.

Is It Possible to Escape Racial Typology in Forensic Identification

This chapter provides a review of metric and morphological methods for determining ancestry from skeletal forensic cases, as well as a comparative look at emerging genetic “origins”-determination methods. The authors address two major issues with respect to these methods. Are the methods consistent with observable patterns of human biological variation and with the apportioning of variation in skeletal reference samples used to represent population groups? Do the methods have any utility for positive identification of unknowns? In addition, the authors provide examples of the patterns of variation in cranial measurements, infracranial measurements, and morphological characters as observed in skeletal reference samples to illustrate some of the limitations of the underlying assumptions of “race”-determination methods.

Latent Evidence Detection using a Combination of Near Infrared and High Dynamic Range Photography: An Example Using Bloodstains

Abstract:  In this paper, we use bloodstains to illustrate an approach for identifying latent evidence on dark cloth using near infrared (NIR) photography combined with high dynamic range (HDR) photography techniques. NIR photography alone has been used to capture latent evidence that cannot be seen in normal ambient light. HDR techniques combine multiple bracketed photographs of the same image to increase the dynamic range of the photograph which can provide greater contrast. Using NIR photography alone, we were able to detect a bloodstain up to a 1/16 dilution, an improvement over previous studies. Combining NIR photography with the HDR process resulted in a noticeable increase in visibility up to 1/16 dilution when compared to NIR photographs alone. At 1/32 dilution, we were able to detect bloodstains that were not visible using NIR alone. NIR is a useful tool for imaging latent evidence, and combining NIR with HDR consistently provides better results over NIR alone.

The relationship between cadaver, living and forensic stature: A review of current knowledge and a test using a sample of adult Portuguese males

The use of cadaver length and forensic stature as a proxy for living standing height has not been scrutinized in detail. In this paper we present a brief review of the current knowledge on the relationship between cadaver, living and forensic stature; assess the magnitude and nature of the differences between these three measures of stature; and investigate the potential impact of these differences in forensic contexts. The study uses a sample of 84 males who were autopsied in 2008 at the National Institute of Legal Medicine and Forensic Sciences (Porto, Portugal), where stature data were collected from three different sources: cadaver stature was obtained from the corpse prior to autopsy, living stature was obtained from military conscription records and forensic stature was obtained from national citizenship identification card records. Descriptive statistics, ANOVA and linear regression are used to analyze the data. The results show that cadaver stature is the highest measure, followed by forensic and by living stature, and the difference between cadaver and living stature is greater than expected (4.3cm). Results also show considerable individual variation in the differences between the three measures of stature and that differences decrease with stature, although only slightly. This study has shown that the difference between cadaver and living stature is greater than previously thought and suggests that previously reported correction factors are a minimum rather than a mean correction. Forensic stature is likely to be incorrectly estimated and can jeopardize identification if methods estimate living rather than forensic stature.

An alternative approach for estimating stature from long bones that is not population- or group-specific.

An accurate and precise estimate of stature can be very useful in the analysis of human remains in forensic cases. A problem with many stature estimation methods is that an unknown individual must first be assigned to a specific group before a method can be applied. Group membership has been defined by sex, age, year of birth, race, ancestry, continental origin, nationality or a combination of these criteria. Univariate and multivariate sex-specific and generic equations are presented here that do not require an unknown individual to be assigned to a group before stature is estimated. The equations were developed using linear regression with a sample (n=244) from the Terry Collection and tested using independent samples from the Forensic Anthropology Databank (n=136) and the Lisbon Collection (n=85). Tests with these independent samples show that (1) the femur provides the best univariate results; (2) the best multivariate equation includes the humerus, femur and tibia lengths; (3) a generic equation that does not require an unknown to first be assigned to a given category provides the best results most often; (4) a population-specific equation does not provide better results for estimating stature; (5) sex-specific equations can provide slightly better results in some cases; however, estimating the wrong sex can have a negative impact on precision and accuracy. With these equations, stature can be estimated independently of age at death, sex or group membership.

Do century-specific equations provide better estimates of stature? A test of the 19-20th century boundary for the stature estimation feature in Fordisc 3.0

A sample (n=28) from the Terry Collection was selected to include only White males who were born and had their entire growth and development period before 1900 to assess the effects year of birth have on accuracy and precision when estimating stature. Using the computer application Fordisc 3.0, stature was estimated using the humerus, radius, femur, and tibia equations developed from White males born in the 19th Century and the 20th Century. The 19th Century White male equations did not consistently provide the most precise and accurate estimates of stature. The 20th Century equations provide results that were as good as or slightly better than the 19th Century equations for the humerus, radius and femur. The 20th Century equations provided notably better results for the tibia. There is a great deal of evidence that there are clear positive secular changes in most of North America in the last 100-125 years, but the division commonly advocated in a forensic context at the year 1900 has no positive effect on accuracy or precision when estimating stature.

Do group-specific equations provide the best estimates of stature?

An estimate of stature can be used by a forensic anthropologist with the preliminary identification of an unknown individual when human skeletal remains are recovered. Fordisc is a computer application that can be used to estimate stature; like many other methods it requires the user to assign an unknown individual to a specific group defined by sex, race/ancestry, and century of birth before an equation is applied. The assumption is that a group-specific equation controls for group differences and should provide the best results most often. In this paper we assess the utility and benefits of using group-specific equations to estimate stature using Fordisc. Using the maximum length of the humerus and the maximum length of the femur from individuals with documented stature, we address the question: Do sex-, race/ancestry- and century-specific stature equations provide the best results when estimating stature? The data for our sample of 19th Century White males (n=28) were entered into Fordisc and stature was estimated using 22 different equation options for a total of 616 trials: 19th and 20th Century Black males, 19th and 20th Century Black females, 19th and 20th Century White females, 19th and 20th Century White males, 19th and 20th Century any, and 20th Century Hispanic males. The equations were assessed for utility in any one case (how many times the estimated range bracketed the documented stature) and in aggregate using 1-way ANOVA and other approaches. This group-specific equation that should have provided the best results was outperformed by several other equations for both the femur and humerus. These results suggest that group-specific equations do not provide better results for estimating stature while at the same time are more difficult to apply because an unknown must be allocated to a given group before stature can be estimated.

Estimating Biological Characteristics With Virtual Laser Data

Laser scanning technology is increasingly being used in forensic anthropological research to obtain virtual data for archival purposes and post hoc measurement collection. This research compared the measurement accuracy of two laser scanners—the FARO Focus3D 330X and the FARO Freestyle3D—against traditionally obtained (i.e., by hand) control data (N = 454). Skeletal data were collected to address a novel question: the ability of laser scanning technology to produce measurements useful for biological characteristic estimation, such as sex and stature. Results indicate that both devices produced measurements very similar to control (c. 3‐mm average absolute error), but also illuminate a tendency to under‐measure. Despite these findings, the virtual data produced sex and stature estimates that varied little from control‐produced estimates, signifying the usefulness of virtual data for preliminary biological identification when the skeletal elements are no longer available for physical analysis.