Sex Estimation of the Human Skeleton: History, Methods, and Emerging Techniques

Sex Estimation of the Human Skeleton is a comprehensive work on the theory, methods, and current issues for sexing human skeletal remains. This work provides practitioners a starting point for research and practice on sex estimation to assist with the identification and analysis of human remains. It contains a collection of the latest scientific research, using metric and morphological methods, and contains case studies, where relevant, to highlight methodological application to real cases. This volume presents a truly comprehensive representation of the current state of sex estimation while also detailing the history and how we got to this point.

Divided into three main sections, this reference text first provides an introduction to the book and to sex estimation overall, including a history, practitioner preferences, and a deeper understanding of biological sex. The second section addresses the main methodological areas used to estimate sex, including metric and morphological methods, statistical applications, and software. Each chapter topic provides a review of older techniques and emphasizes the latest research and methodological improvements. Chapters are written by practicing physical anthropologists and also include their latest research on the topics, as well as relevant case studies. The third section addresses current considerations and future directions for sex estimation in forensic and bioarchaeological contexts, including DNA, secular change, and medical imaging Sex Estimation of the Human Skeleton is a one-of-a-kind resource for those involved in estimating the sex of human skeletal remains.

• Provides the first comprehensive text reference on sex estimation, with historical perspectives and current best practices
• Contains real case studies to underscore key estimation concepts
• Demonstrates the changing role of technology in sex estimation

• Language: English
• Publisher: Academic Press
• Release date: May 30, 2020
• ISBN: 9780128157688

Book preview

Introduction to sex estimation and this volume

Alexandra R. Klales, Forensic Anthropology Program, Department of Sociology and Anthropology,Washburn University, Topeka, KS, United States

Abstract

The goal of this book is put sex estimation on equal footing with the other biological profile parameters that have been extensively explored and consolidated in the last 10 years (cf., Pilloud & Hefner’s 2016 Biological Distance Analyses: Forensic and Bioarchaeological Perspectives, or Latham et al.’s 2010 Age Estimation of the Human Skeleton). While several works have touched on sex estimation and done an excellent job of summarizing it within larger edited volumes (e.g., Cabo et al., 2012; Garvin, 2012; Moore, 2013), relegating it to a single chapter or two limits our complete and full understanding of sex estimation. This chapter begins with a brief introduction to sex estimation, moves to appropriate terminology, and then ends with a summary of the book goals and format. The goal of this volume is to present a truly comprehensive representation of the current state of sex estimation while also detailing the history and how we got to this point.

Keywords

Sex estimation; Biological profile; Osteobiography; Sex determination; Morphoscopic

Brief introduction to sex estimation

The biological profile or osteobiography consists of estimating an unknown individual’s ancestry, sex, age, and stature based on their skeletal form. The purpose of estimating these demographic variables varies between bioarchaeology, forensic anthropology, and paleoanthropology (see Chapter 3 of this volume). Nevertheless, sex estimation is generally the second step in biological profile estimation and one of the most important, as many of the methods for stature and age estimation are sex-specific. While a crucial step of the biological profile, sex estimation cannot be performed until after the assessment of general age (adult vs. subadult) and estimation of ancestry. General age impacts which features and skeletal regions can or cannot be used (see Chapter 14 of this volume), and populations vary considerably in the levels of sexual dimorphism (see Chapter 17 of this volume). Sex estimation lacks some of the inherent difficulties found with the other profile parameters because the outcome is limited to only two options: male or female. However, despite having fewer options or answers, sex estimation remains one of the more difficult aspects of biological profile assessment, especially with incomplete, fragmentary, and subadult remains or in populations with lower levels of sexual dimorphism.

Estimation of biological sex (see Chapter 4 of this volume) in skeletal biology is based on the premise that there are appreciable size and shape differences in the skeletal form of males and females within and between populations (i.e., sexual dimorphism). Humans are less sexually dimorphic than most of the other living primates, and secondary sex characteristics, which create the phenotypic differences between males and females, arise as a response to sexually dimorphic hormones (see Chapter 14 for a more detailed discussion). The degree of sexual dimorphism in any species is impacted by both extrinsic factors, like nutrition and stress, and intrinsic factors, such as hormone levels (see Moore, 2013 for a more detailed discussion). Essentially biological anthropologists are interpreting these sexually dimorphic features of the human skeleton. In any population, males will on average have more rugose or robust muscle attachment sites than females throughout the body. Females also exhibit appreciable differences in the form, positioning, and orientation of the pelvis related to the functional requirements of parturition and its effect on the bony pelvis (see Chapter 6 of this volume). These pelvic differences, in turn, result in male/female differences throughout the body, for example, in the carrying angle of the elbow and the Q-angle of the knee. In regard to size differences, males are, on average, anywhere from 8% to 10% larger (i.e., heavy, wider, or taller) than females (Rogers & Mukherjee, 1992); therefore, males will tend to have larger skeletal measurements in comparison to females, especially in long bone length and joint size. Despite these differences, there will always be overlap between the sexes as there will be larger females and smaller males in any population. Considerable variation also exists within and between populations, and this must be considered when estimating sex of an unknown individual (see Chapter 17 of this volume).

Current methods used to estimate sex consist of either (1) qualitative traits sometimes referred to as nonmetric, morphological, morphoscopic, macromorphoscopic, anthroscopic traits or (2) quantitative measures known as metrics (see below for a more detailed discussion of appropriate terminology). The former consist of visually examining a particular feature, skeletal region, or trait and determining if it is robust/gracile or, in some cases, present/absent. The assumption is that the more gracile expression will have a greater frequency in females, while the more robust expressions will be more typical of males. In cases of presence or absence, the trait is question is presumed to be found in one sex rather than the other. The combination of these traits can be compiled for a majority rule or decision table approach (e.g., Burns, 2006; Phenice, 1969; Rogers & Saunders, 1994), or more appropriately incorporated into an established method with statistical measures of probability (e.g., Klales, Ousley, & Vollner, 2012; Rennie, 2018; Walker, 2005, 2008). The latter approach focuses on sexually dimorphic size (breadth and length) differences between the sexes, which can be captured metrically. One could argue for the addition of a third category or subcategory of metric methods called geometric morphometrics, which examines the interplay and differences between shape and size from a metric perspective (see Chapter 13 of this volume).

There remains debate as to which data type (qualitative vs. quantitative) and which specific methods we should be using to estimate sex (Garvin, 2012). A survey of practicing biological anthropologists indicated that the vast majority prefer using both qualitative and quantitative approaches to estimate sex; however, when only one or the other is utilized, qualitative methods were preferred nearly 2:1 (see Chapter 2 of this volume for complete survey results). Recent works have documented a perceived shift to quantitative methods due to their seemingly more objective nature (Christensen, Passalacqua, & Bartelink, 2019; Dirkmaat, Cabo, Ousley, & Symes, 2008; Moore, 2013), but one could also argue that many metric approaches suffer from reliability issues due to the difficulty in defining or locating landmarks (e.g., Type 2 and Type 3). Further criticisms of metric approaches suggest that there is greater population specificity; they are time-consuming and require specialized equipment; and they necessitate greater training. Criticisms of standard qualitative methods (majority rule or presence/absence of traits) include greater subjectivity, reliance on experience, and a lack of statistical rigor (Bruzek, 2002; Klales et al., 2012), yet they are quick and easy to apply. Stewart (1979) once argued why waste time to measure traits that can be verified very quickly by the naked eye? (Moore, 2013, p. 92). Based on survey results, we can clearly see that skeletal biologists are using both qualitative and quantitative approaches, neither of which is without its own benefits and inherent limitations. Several studies have demonstrated the correlation between metrics and morphological trait expression and suggest there is no biological reason to favor either kind (e.g., Cheverud et al., 1979, p. 196; Kenyhercz, Fredette, Klales, & Dirkmaat, 2012). It, therefore, stands to reason that we should be using as many possible sources of information to make an accurate estimate of sex, and often the qualitative and quantitative data will coincide.

Which particular method to use varies considerably from case to case, and will likely vary based on different contexts (e.g., bioarchaeological vs. forensic). The first primary limitation for appropriate method selection will always be which bones/features are available for analysis. For example, Waldron (1987) suggests that only about two-thirds of remains recovered in archaeological contexts contain the pubic bone, thereby negating the ability to use the highly accurate methods associated with this particular skeletal region. Because of differential preservation, virtually every single bone has been assessed quantitatively, qualitatively, or both for its potential for sex estimation due to the incomplete nature of skeletal remains that are often encountered in forensic, bioarchaeological, and paleoanthropological contexts. A second limiting factor is resource availability: Do you have the equipment necessary to use a particular method (e.g., calipers, manuals, etc.)? Do you have access to a computer, software, or internet connection? Are their financial constraints (e.g., purchasing software, digitizer, dental calipers, etc.)? In a perfect world, these would not be limiting factors, but, in reality, not all practitioners and laboratories have equal access to the materials or resources required to utilize certain methods. Lastly, determinations of method appropriateness should include a critical evaluation of a method’s suitability for a specific population and to the tests of validity and reliability of the method. As Ousley always says, it is our responsibility to do good science (Klales et al., 2012, p. 106) of which Daubert reminds us in forensic settings, but which should also be the case in nonforensic contexts as well.

Terminology

Below is some clarification on the nuances of sex estimation terminology that are used throughout the chapters within this volume.

Sex assessment vs. sex determination vs. sex estimation

Sex assessment has been defined by Spradley and Jantz (2011, p. 290) as the use of morphological traits with no estimable error rates, classification rates, or any associated statistics. This has been the historic approach to both sex and ancestry estimation in bioarchaeological and forensic contexts, whereby features or the gestalt were used to subjectively produce a sex assessment. The use of assessment for sex estimation is quite problematic based on the aforementioned definition. We know today that this historical assessment approach is not only invalid and unreliable but also lacks the scientific rigor required of our methodology; therefore, we should be moving away from both the practice of assessment and the use of the term assessment to refer to sex estimation practices. Recognizing the problematic issues with this terminology, the American Academy of Forensic Sciences’ Academy Standards Board (ASB) Anthropology section recently (Fall 2019) corrected Standard 090 Standard for Sex Assessment in Forensic Anthropology, based on feedback from the public commencing from January 2019.

Sex determination, on the other hand, implies levels of confidence approaching 100% accuracy and implies that sex can be treated as a known criterion (Gibbon, Paximadis, Štrkalj, Ruff, & Penny, 2009). The term determination itself is defined as establishing something exactly (Oxford Dictionary). At present, the only employable method with which to determine biological/chromosomal sex with near 100% accuracy is through DNA analyses, and even this method is not without its own caveats and limitations, such as false negatives (see Chapter 21 of this volume). Articles as recent as 2018/19 in the Journal of Forensic Sciences; Forensic Science International; International Journal of Osteoarchaeology; and the American Journal of Physical Anthropology include research methods on sex that are termed sex determination, rather than sex estimation, using methods other than DNA. Furthermore, current government agencies, such as the Defense POW/MIA Accounting Agency (DPAA), use sex determination/assessment within their standard operating procedures (SOPs) and case reports when estimating sex from skeletal parameters, even in circumstances when DNA is not utilized. Using the term determination in our case reports or site reports infers a level of confidence that simply cannot be obtained using currently available metric and morphological estimates of sex; therefore, the use of this terminology should be restricted to DNA analyses alone as it could confuse law enforcement, jurors, judges, coroners, the general public, and other agencies to which our reports are issued. Moore (2013, p. 92) perfectly summarizes this sentiment with her statement until accuracy rates consistently reach 100% (which will likely never happen due to human variation), it is better to consider this endeavor estimation of sex.

Spradley and Jantz (2011, p. 290) define sex estimation as the use of metric traits of the pelvis, skull, or any single bone or any combination of bones … because it provides an estimate in the form of an error rate or expected classification rate. Moore (2013) suggests the current consensus in sexing research focuses on metric methods, but I would argue that morphological methods are equally, if not more, popular (see Chapter 3 of this volume on practitioner preferences) due to their ease of use, broad applicability, and high agreement levels. Also, one could argue the modern morphological methods also include these estimates or statistical parameters (e.g., Klales, 2018; Klales et al., 2012; Walker, 2008) and, therefore, the term sex estimation should be expanded to include any estimation of sex with associated classification accuracy and error rates from skeletal parameters.

In the 21st century, we need to move away from using the term (and practice) of generating assessments and, instead, rely on estimates of sex (and other biological parameters) using valid and reliable methods (either morphological or metric). Our estimates should, in turn, include associated accuracy, probabilities, and error rates, and our methodological research at minimum should include these parameters, as well as tests of statistical assumptions (see Chapter 13 of this volume).

Nonmetric vs. morphological vs. qualitative methods vs. macromorphoscopic/morphoscopic

Colloquially, nonmetric simply means not based on a standard of measurement, which is perhaps where the confusion arises with the usage of this term in skeletal biology (Oxford Dictionary). This layperson’s definition simply means the assessment of anything that is not metric or measured as a continuous variable. However, in skeletal biology, nonmetric traits are often considered to be epigenetic (i.e., heritable) or quasi- or noncontinuous traits, which frequently vary by population group (Wilczak & Dudar, 2011) and, therefore, should be distinguished from the morphological skeletal variants used to estimate sex. A brief history of the term epigenetics suggests that its use to describe skeletal variants may also be problematic. Waddington (1968) originally defined the term as the branch of biology which studies the causal interactions between genes and their products which bring the phenotype into being. This definition has since been refined to the study of changes in gene function that are mitotically and/or meiotically heritable and that do not entail a change in DNA sequence (Wu & Morris, 2001). At present, the genetic mechanisms for many of the traits listed as nonmetric indicators of sex or ancestry are not well understood, and many of these traits may be less controlled by the epigenome and more so by environmental factors. The standardized skeletal documentation software Osteoware includes 62 nonmetric traits, some of which are likely not true nonmetric traits and are rather simple morphological traits (Wilczak & Dudar, 2011). Examples of true nonmetric skeletal traits include cranial ossicles, tori, septal apertures, third trochanters, and metopism. These traits have all been shown to exhibit a high heritability coefficient and are more strongly controlled by genetic, rather than environmental, factors (Sjøvold, 1984). While some of these traits tend to have higher frequencies in one sex or another, they are not typically utilized in a capacity for sex estimation.

Qualitative refers to describing the quality of something based on size, appearance, or value rather than on its quantity, while morphology is the form (size and shape) or structure of things (Oxford Dictionary). Morphological is most appropriate when we discuss sexually dimorphic skeletal features, because it is more broadly defined as form and structure and excludes measurable size differences and values. So, while we are using qualitative data, our methods are morphological. In the case of skeletal analyses, we are concerned with the internal anatomy of a person as reflected by the form of their skeletal features. Many of these features occur on a continuous gradation, for example, mastoid size or brow-ridge shape, which are often difficult to capture metrically. In some methods, these traits are scored on gradients from gracile to robust that can mimic quasicontinuous scoring found with nonmetric traits; however, they are not truly epigenetic, and these methods often group multiple features into a single scoring scale. For example, scoring the mental eminence in Walker (2008) requires assessment of tubercle presence/absence, width of the eminence, and projection of the chin (Lewis & Garvin, 2016). Likewise, in Klales et al. (2012), the ligamentous attachment orientation and angle are considered with overall bone shape for the evaluation of the ventral arc. In reality, multiple shape features are being grouped into scores based on overall morphology rather than scoring a single semicontinuous trait. Because of this, I would argue that we should be moving away from the use of the terms nonmetric or qualitative when we are referring to morphological traits used to differentiate the