Sex estimation from cranial morphological traits: Use of the methods across American Indians, modern North Americans, and ancient Egyptians.

This paper focuses on estimating sex by visual assessment of human cranial morphology. Practitioners in the field report variation in sexual dimorphism across populations. This study evaluates again the general hypothesis that populations vary in their pattern of sexual dimorphism. Specifically, the study tests the degree of expression of four cranial morphological traits (glabella, supraorbital margins, nuchal crest, and mastoid process) across three samples from different time periods and which vary in sociocultural transitions: 1) modern Americans of rural and urban areas spanning the last 186 years; 2) Dynastic Egyptians; and 3) Averbuch American Indians, spanning approximately 1255 CE to 1425 CE, from the southeastern United States. These three populations were specifically chosen for sampling as they represent distinct temporal and groups of varied ancestral composition. Crania from these samples were scored 1-5, with 1 being consistent with expected female morphology. The estimated sex was compared to either documented sex (when available) or discriminant functions derived from craniometrics. Freeman-Fisher-Halton tests examined sample differences, within sexes, affecting the visual assessment method. Post hoc tests were applied to pinpoint where the differences lie between the samples. The findings of this study support the hypothesis that the method does not estimate the sex of crania from all populations in the same manner, indicating that populations display differing patterns of sexual dimorphism. However, understanding these patterns and adjusting for how the method is applied will lead to reliable assessments. A relative frequency table and graphs of distributions are provided for practitioners who can use the information to make successful assessments of sex.

Horizontal hepatitis B virus transmission through non-sexual close contact in Turkish chronic hepatitis B patients living outside of Turkey.

BACKGROUND AND AIMS: Hepatitis B virus (HBV) infection is a global threat and with the growing cultural diversity in Western Europe, knowledge on routes of infection in order to decrease HBV spreading is essential. This study assessed the risk of horizontal transmission through non-sexual close contact in the chronic hepatitis B (CHB) population in Maastricht (the Netherlands) and Genk (Belgium), with a main focus on the differences between ethnic groups. METHODS: In this multicenter retrospective study, 166 CHB patients, who were still under follow-up between December 2009 to December 2014, were recruited from the Hepatology Outpatient Departments of two hospitals, one in Maastricht and one in Genk. Ethnicity (defined as country of origin (COO)) and routes of transmission were collected from all patients. RESULTS: The CHB population in Maastricht and Genk consisted of 98 and 68 patients, respectively. In Maastricht, 31% were of Dutch and 16% of Chinese origin. In Genk, mainly Belgian (15%) and Turkish (50%) patients were included. The percentage of horizontal transmission in the total study cohort was 9%. Moreover, the COO groups Dutch/Belgian (n=40), Turkish (n=38) and Chinese (n=18) differed in the number of cases infected by horizontal transmission (4%, 30% and 6%, p=0.030). CONCLUSION: Although the prevalence of horizontal transmission in the total study cohort is low, non-sexual close contact may play a role in the migrant population, particularly the Turkish. This should be an important public health target with respect to the prevention of HBV spreading.

Estimating stature in fossil hominids: which regression model and reference sample to use?

coResearchers have long appreciated the significant relationship between body size and an animal's overall adaptive strategy and life history. However, much more emphasis has been placed on interpreting body size than on the actual calculation of it. One measure of size that is especially important for human evolutionary studies is stature. Despite a long history of investigation, stature estimation remains plagued by two methodological problems: (1) the choice of the statistical estimator, and (2) the choice of the reference population from which to derive the parameters. This work addresses both of these problems in estimating stature for fossil hominids, with special reference to A.L. 288-1 (Australopithecus afarensis) and WT 15000 (Homo erectus). Three reference samples of known stature with maximum humerus and femur lengths are used in this study: a large (n=2209) human sample from North America, a smaller sample of modern human pygmies (n=19) from Africa, and a sample of wild-collected African great apes (n=85). Five regression techniques are used to estimate stature in the fossil hominids using both univariate and multivariate parameters derived from the reference samples: classical calibration, inverse calibration, major axis, reduced major axis and the zero-intercept ratio model. We also explore a new diagnostic to test extrapolation and allometric differences with multivariate data, and we calculate 95% confidence intervals to examine the range of variation in estimates for A.L. 288-1, WT 15000 and the new Bouri hominid (contemporary with [corrected] Australopithecus garhi). Results frequently vary depending on whether the data are univariate or multivariate. Unique limb proportions and fragmented remains complicate the choice of estimator. We are usually left in the end with the classical calibrator as the best choice. It is the maximum likelihood estimator that performs best overall, especially in scenarios where extrapolation occurs away from the mean of the reference sample. The new diagnostic appears to be a quick and efficient way to determine at the outset whether extrapolation exists in size and/or shape of the long bones between the reference sample and the target specimen.

Technical note: a blind test of mandibular ramus flexure as a morphologic indicator of sexual dimorphism in the human skeleton.

Loth and Henneberg (1996, Am. J. Phys. Anthropol. 99:473-487) identified a single morphological feature of the mandible, the presence or absence of a distinct flexure or angulation of the posterior margin of the mandibular ramus at the level of the occlusal plane, which appears to be an extraordinarily accurate predictor of sex. Using only this feature, Loth and Henneberg were able to predict sex with 94% accuracy in a large sample of mandibles. In this article, we report the results of a blind test of mandibular ramus flexure as a predictor of sex. In our blind test, only 62.5% of the mandibles were correctly sexed, and virtually identical results were obtained when the same sample of mandibles was examined by a second observer. Overall, our results demonstrate that: 1) the association between ramus flexure and sex is weak; 2) the predictive accuracy of Loth and Henneberg's method is better than chance for only one sex, males; and 3) the method is based on a trait that cannot be reliably or consistently identified.

Use of ordinal categorical variables in skeletal assessment of sex from the cranium.

In anthropological studies, visual indicators of sex are traditionally scored on an ordinal categorical scale. Logistic and probit regression models are commonly used statistical tools for the analysis of ordinal categorical data. These models provide unbiased estimates of the posterior probabilities of sex conditional on observed indicators, but they do so only under certain conditions. We suggest a more general method for sexing using a multivariate cumulative probit model and examine both single indicator and multivariate indicator models on a sample of 138 crania from a Late Mississippian site in middle Tennessee. The crania were scored for five common sex indicators: superciliary arch form, chin form, size of mastoid process, shape of the supraorbital margin, and nuchal cresting. Independent assessment of sex for each individual is based on pubic indicators. The traditional logistic regressions are cumbersome because of limitations imposed by missing data. The logistic regression correctly classified 66/74 males and 46/64 females, with an overall correct classification of 81%. The cumulative probit model classified 64/74 males correctly and 51/64 females correctly for an overall correct classification rate of 83%. Finally, we apply parameters estimated from the logit and probit models to find posterior probabilities of sex assignment for 296 additional crania for which pubic indicators were absent or ambiguous.

Estimation of African ape body length from femur length.

The estimation from long bone lengths of stature in humans or body size in apes has a deep history in physical anthropology. To date, we can enumerate at least five different statistical methods for making such estimations. These methods are: (1) the regression of body length on long bone length (inverse calibration), (2) regression of long bone length on body length followed by solving for body length (classical calibration), (3) major axis regression of body length on long bone length, (4) reduced major axis regression of body length on long bone length, and (5) use of a long bone/body length ratio. We examine some of the statistical properties of these estimators using a large sample of humans (n = 2053) to derive the estimators, and applying them to smaller samples of Pan troglodytes (n = 42), Pan paniscus (n = 8), and Gorilla gorilla (n = 35). Based on the root mean-squared error (RMSE), the reduced major axis is the preferred estimator for body length in the combined Pan sample. However, inverse calibration is the best estimator for body length in gorillas based on the RMSE. Many estimators grossly underestimate body length in the apes. Differences in allometries between humans and great apes are obvious, but it is important to show the assumptions necessary in estimating body size from fossil remains, especially when isolated long bones are recovered and the global allometry is consequently unknown.

Stature estimation and calibration: Bayesian and maximum likelihood perspectives in physical anthropology.

Many applied problems in physical anthropology involve estimation of an unobservable quantity (such as age at death or stature) from quantities that are observable. Two of the more disparate subdisciplines of our discipline, paleoanthropology and forensic anthropology, routinely make use of various estimation methods on a case-by-case basis. We discuss the rationales for making estimations on isolated cases, taking stature estimation from femoral and humerus lengths as an example. We show that the entirety of our discussion can be placed within the context of calibration problems, where a large calibration sample is used to estimate an unobservable quantity for a single skeleton. Taking a calibration approach to the problem highlights the essentially Bayesian versus maximum likelihood nature of the question of stature estimation. On the basis of both theoretical arguments and practical examples, we show that inverse calibration (regression of stature on bone length) is generally preferred when the stature distribution for a reference sample forms a reasonable prior, while classical calibration (regression of bone length on stature followed by solving for stature) is preferred when there is reason to suspect that the estimated stature will be an extrapolation beyond the useful limits of the reference sample statures. The choice between these two approaches amounts to the decision to use either a Bayesian or a maximum likelihood method.