Evaluation of Stature Estimation from the Database for Forensic Anthropology

Trotter and Gleser's (1958) equations outperform Trotter and Gleser's (1952) equations in stature estimation of the US White males

Trotter and Gleser presented two sets of stature estimation equations for the US White males in their 1952 and 1958 studies. Following Trotter's suggestion favouring the 1952 equations simply due to the smaller standard errors, the 1958 equations have been seldom used and have gone without additional systematic validation tests. This study aims to assess the performance of the Trotter and Gleser 1952, Trotter and Gleser 1958, and FORDISC equations for the White males in a quantitative and systematic way, particularly when applied to the WWII and Korean War casualties. In sum, 27 equations (7 from the 1952 study, 10 from the 1958 study, and 10 from FORDISC) were applied to the osteometric data of 240 accounted-for White male casualties of the WWII and Korean War. Then, the bias, accuracy, and Bayes factor for each set of stature estimates were calculated. The results show that, overall, Trotter and Gleser's 1958 equations outperform the 1952 and FORDISC equations in terms of all three measures. Particularly, the equations with higher Bayes factors produced stature estimates where distributions were closer to that of the reported statures than those with lower Bayes factors. When considering Bayes factors, the best performing equation was the "Radius" equation from the 1958 study (BF = 15.34) followed by the "Humerus+Radius" equation from FORDISC (BF = 14.42) and the "Fibula" equation from the 1958 study (BF = 13.82). The results of this study will provide researchers and practitioners applying the Trotter and Gleser stature estimation method with a practical guide for equation selection.

Key Points

The performance of three stature estimation methods was compared quantitatively.Trotter and Gleser's (1952, 1958) and FORDISC White male equations were included.Overall, Trotter and Gleser's 1958 method outperformed the other methods.This study provides a practical guide for stature estimation equation selection.

Stature estimation by semi-automatic measurements of 3D CT images of the femur

Stature estimation is one of the most basic and important methods of personal identification. The long bones of the limbs provide the most accurate stature estimation, with the femur being one of the most useful. In all the previously reported methods of stature estimation using computed tomography (CT) images of the femur, laborious manual measurement was necessary. A semi-automatic bone measuring method can simplify this process, so we firstly reported a stature estimation process using semi-automatic bone measurement software equipped with artificial intelligence. Multiple measurements of femurs of adult Japanese cadavers were performed using automatic three-dimensional reconstructed CT images of femurs. After manually setting four points on the femur, an automatic measurement was acquired. The relationships between stature and five femoral measurements, with acceptable intraobserver and interobserver errors, were analyzed with single regression analysis using the standard error of the estimate (SEE) and the coefficient of determination (R²). The maximum length of the femur (MLF) provided the lowest SEE and the highest R²; the SEE and R² in all cadavers, males and females, respectively, were 3.913 cm (R² = 0.842), 3.664 cm (R² = 0.705), and 3.456 cm (R² = 0.686) for MLF on the right femur, and 3.837 cm (R² = 0.848), 3.667 cm (R² = 0.705), and 3.384 cm (R² = 0.699) for MLF on the left femur. These results were non-inferior to those of previous reports regarding stature estimation using the MLF. Stature estimation with this simple and time-saving method would be useful in forensic medical practice.

Estimating Adult Stature Using Metatarsal Length in the Korean Population: A Cadaveric Study

This study aims to propose a regression equation for estimating stature in the Korean population using metatarsal bones from cadavers and to validate the appropriateness of the Korean-specific equation by comparing it to equations from other populations. A total of 81 adult formalin-fixed cadavers (51 males and 30 females) were evaluated. The first and second metatarsal bones' physiological and maximal lengths were measured, and the cadaveric stature of the subjects was determined as the distance from the vertex to the plantar face of the heel. In all measurements, the correlation coefficient between real stature and metatarsal length was statistically significant (p < 0.001). Additionally, both sexes showed a correlation between stature and metatarsal bone length. For unknown sex, M1 (first metatarsal maximal length) showed the strongest association between stature and metatarsal length. The following is the appropriate regression equation: 1172.4913 + 7.3275M1 (R = 0.703). The current equation demonstrated a statistically significant appropriateness for the Korean population when compared to equations for other populations (p < 0.001). In conclusion, we proposed a Korean-specific regression equation for estimating stature using metatarsal length, and this formula may be more appropriate and useful in forensic science for the Korean population.

Stature estimation using foot dimensions via 3D scanning in Taiwanese male adults

In forensic identification, the use of foot dimensions to predict stature is a requisite. For Taiwanese male stature prediction, available information about stature estimation using foot dimensions is still lacking. Therefore, the primary purpose of this study was to establish Taiwanese adult male stature prediction models for various foot dimensions. A total of 2,072 male 3D foot models were collected and the subjects' ages ranged from 18 to 59 years old. Thirteen foot dimensions for each foot were utilized in this study. Bilateral differences were tested using pairedt-tests. Stature predictions based on different foot dimensions were conducted using simple linear and stepwise regression methods. The results showed significant bilateral differences in the majority of the selected foot dimensions (p < 0.001). Foot length had the highest positive correlation with stature in the right and left foot. Using length-related dimensions generated better prediction accuracy (0.356 < R² < 0.533, 4.193 < SEE < 4.928), whereas the worst accuracy was observed with angle-related dimensions (0.001 < R² < 0.023; 6.072 < SEE < 6.137) when employing a single foot dimension to estimate Taiwanese male stature. Stepwise regression analysis results indicated that the coefficient of determination was improved to 0.590 and 0.593 by applying five and six foot parameters to predict stature, respectively. The findings of the present study suggest that these stature estimation equations can be applied to predict Taiwanese male stature in the forensic science field.

Missing Value Imputation in Stature Estimation by Learning Algorithms Using Anthropometric Data: A Comparative Study

Estimating stature is essential in the process of personal identification. Because it is difficult to find human remains intact at crime scenes and disaster sites, for instance, methods are needed for estimating stature based on different body parts. For instance, the upper and lower limbs may vary depending on ancestry and sex, and it is of great importance to design adequate methodology for incorporating these in estimating stature. In addition, it is necessary to use machine learning rather than simple linear regression to improve the accuracy of stature estimation. In this study, the accuracy of statures estimated based on anthropometric data was compared using three imputation methods. In addition, by comparing the accuracy among linear and nonlinear classification methods, the best method was derived for estimating stature based on anthropometric data. For both sexes, multiple imputation was superior when the missing data ratio was low, and mean imputation performed well when the ratio was high. The support vector machine recorded the highest accuracy in all ratios of missing data. The findings of this study showed appropriate imputation methods for estimating stature with missing anthropometric data. In particular, the machine learning algorithms can be effectively used for estimating stature in humans.

Updated lower limb stature estimation equations for a South African population group

One of the main steps in the identification of an unknown person, from their skeletal remains, is the estimation of stature. Measurements of intact long bones of the upper and lower extremities are widely used for this purpose because of the high correlation that exists between these bones and stature. In 1987, Lundy and Feldesman presented regression equations for stature estimation for the black South African population group based on measurements of bones from the Raymond A. Dart Collection of Human Skeletons. Local anthropologists have questioned the validity of these equations. Living stature measurement and magnetic resonance imaging scanograms of 58 adult volunteers (28 males and 30 females) representing the modern black South African population group were obtained. Physiological length of the femur (FEPL) and physiological length of the tibia (TPL) were measured on each scanogram and substituted into appropriate equations of Lundy and Feldesman (S Afr J Sci. 1987;83:54–55) to obtain total skeletal height (TSHL&F). Measured total skeletal height (TSHMeas) for each subject from scanograms was compared with TSHL&F. Both FEPL and TPL presented with significantly high positive correlations with TSHMeas. A comparison between TSHL&F and TSHMeas using a paired t-test, showed a statistically significant difference – an indication of non-validity of Lundy and Feldesman’s equations. New regression equations for estimation of living stature were formulated separately for male and female subjects. The standard error of estimate was low, which compared well with those reported for other studies that used long limb bones. Significance: • Statistically significant differences were observed between measured and estimated skeletal height, thus confirming non-validity of Lundy and Fieldsman’s (1987) equations for lower limb bones. • New regression equations for living stature estimation were formulated for femur and tibia lengths, and the low standard error of estimates of equations compared well to results from other studies.

Using tibial fragments to reconstruct the total skeletal height of black South Africans

Stature is an important component of the biological profile of unknown skeletal remains and regression equations for estimating stature have been derived for a number of bones. However, bones are rarely recovered intact in both forensic and archaeological cases, and regression formulae for fragmentary remains have therefore been developed. These equations are, however, both sex- and population-specific, and while formulae exist for many populations, those using fragmentary tibiae do not exist for black South Africans. The aim of this study was therefore to establish regression equations for estimating total skeletal height (TSH), and thereby stature, from tibial fragments in a black South African population. A sample of 99 male and 99 female black South African skeletons were obtained from the Raymond A. Dart Collection of Human Skeletons and the TSH of each skeleton was calculated using the anatomical method. Eleven additional measurements representing tibial fragments were taken on each tibia, and both uni- and multivariate equations were established for estimating TSH from these fragments. All tibial variables were significantly, positively correlated with TSH, and equation correlations ranged between 0.41 and 0.91. The range of standard errors of estimate for the derived sex-specific (3.43-5.06 cm) and sex-pooled (3.44-5.94 cm) multivariate equations were slightly larger than those reported for intact tibiae in black (2.78-3.06 cm) and white (2.59-3.16 cm) South Africans. All uni- and multivariate-equations estimated TSH with moderate to high accuracy, which indicates that in the absence of intact tibiae, the equations presented in this study can be used to give accurate estimates of TSH, and thereby stature, for black South Africans.

Stature estimation from tibia percutaneous length: New equations derived from a Mediterranean population

Stature is a fundamental anthropometric character to trace the biological profile of a person. In some cases, when dismembered or mutilated bodies are discovered in a forensic context, it is essential to estimate stature from single districts of the body. Nevertheless, to date and worldwide, there are only few population-specific studies on stature estimation from leg length and none of them concerns modern populations in southern Europe. We attempted to fill this gap, focusing on the estimation of stature from the length of the tibia in a Mediterranean population (Italians). We carried out the current study on a sample of 374 Italian university students of both sexes (age range: 19.9-34.4). Both, actual stature and percutaneous length of tibia were measured and new equations were developed for stature estimation. We tested separate regression equations for each sex, as well as an equation for remains, whose sex is unknown. To assess their reliability, the equations were tested on a holdout sample of 30 individuals from the same population. Moreover, results of new specific linear regression equations were compared to others from the literature. We demonstrated that the newly proposed formulae (for males and combined sexes) and the ones by Olivier (for females) provided the most reliable estimations of stature for southern Europeans.

Discrepancies between reported and cadaveric body size measurements associated with a modern donated skeletal collection

Body mass and stature estimation methods used in biological anthropology require materials with known body size information. There are several types of body size data that can be associated with skeletal collections. However, discussion regarding the reliability and suitability of these types of information for anthropological research is scarce. This paper focuses on differences between reported and recorded cadaver weights and heights associated with a modern donated skeletal collection, similar to these commonly used in anthropological research. In addition, the study identifies factors that may influence these discrepancies. The results show statistically significant differences between reported and cadaver body size information. Generally, reported weights, statures and body mass indices (BMI) were greater compared to the cadaver information in this sample. However, potential effects on these discrepancies varied depending on sex and information type. Age was found to influence stature discrepancy in females, and donation type had an effect on the female weight discrepancy. The results also show that body size range (weight, stature and BMI) can contribute to these discrepancies. Even though the differences between reported and cadaver data may not be significant at the population level, the individual variation can cause misclassifications of individuals depending on the data used. This study encourages researchers using modern documented collections and their body size information to openly acknowledge the types of weight and stature data used and to discuss potential problems associated with them.

Bayesian modeling predicts age and sex are not required for accurate stature estimation from femoral length

Despite the recognized flaws in applying traditional stature estimation equations such as those of Trotter and Gleser (1952) [5] to a contemporary population, there are currently no available alternatives for stature estimation in Australia that address these limitations. Post mortem computed tomography (PMCT) DICOM scans of the left and right femora were acquired from 76 Australian deceased individuals aged 17-76 years for metric analysis. Femoral bicondylar length, femoral epicondylar breadth and anterior-posterior (AP) diameter, medial-lateral (ML) diameter, circumference and cortical area at the femoral midshaft were measured on three-dimensional (3D) models to build statistical models for estimating stature. In addition, Australian individuals aged 16-63 years (n=111) were measured in standing and supine positions to aid in the adjustment of supine stature of deceased individuals utilized in this study to standing stature. The results of this preliminary evaluation strongly indicate that the optimal model for estimating stature includes bicondylar femoral length and epicondylar breadth, that the effect of sex as an independent variable is very low, and there is limited practical benefit in including age in the estimation of stature. Our study indicates that the Australian population sampled represents a small yet significant shift in stature from the original Trotter and Gleser sample. Additionally, in the case of fragmentary remains, it was found that epicondylar breadth and AP diameter had the highest probability of accurate stature estimation in the absence of bicondylar femoral length. As stature forms a significant component of a biological profile and therefore aids in the personal identification of human remains, it is important that forensic anthropologists utilize the most accurate methodologies available. Stature estimation of Australian individuals is therefore achieved with higher accuracy through utilizing the femoral equations proposed in this study.

Estimation of stature from hand and foot dimensions in a Korean population

The estimation of stature using foot and hand dimensions is essential in the process of personal identification. The shapes of feet and hands vary depending on races and gender, and it is of great importance to design an adequate equation in consideration of variances to estimate stature. This study is based on a total of 5,195 South Korean males and females, aged from 20 to 59 years. Body dimensions of stature, hand length, hand breadth, foot length, and foot breadth were measured according to standard anthropometric procedures. The independent t-test was performed in order to verify significant gender-induced differences and the results showed that there was significant difference between males and females for all the foot-hand dimensions (p<0.01). All dimensions showed a positive and statistically significant relation with stature in both genders (p<0.01). For both genders, the foot length showed highest correlation, whereas the hand breadth showed least correlation. The stepwise regression analysis was conducted, and the results showed that males had the highest prediction accuracy in the regression equation consisting of foot length and hand length (R²=0.532), whereas females had the highest accuracy in the regression model consisting of foot length and hand breadth (R²=0.437) The findings of this study indicated that hand and foot dimensions can be used to predict the stature of South Korean in the forensic science field.

Accuracy and Reliability of Total Body Mass Estimation Techniques from Stature and Bi-iliac Breadth in Non-Hispanic U.S. Whites from the Bass Donated Skeletal Collection

This paper tests the fidelity of a recent method that used the NHANES III dataset as a proxy to estimate total body mass from stature and bi-iliac breadth in U.S. White males and females. The bi-iliac breadths of 230 males and 152 females identified as non-Hispanic U.S. White from the Bass Donated Skeletal Collection were measured, and along with stature from predonor paperwork, total body mass estimates were calculated and then compared to body masses recorded on predonor paperwork. Male and female samples were subdivided by body mass index (BMI [kg/m² ]) categories established by the World Health Organization. Our results suggest that total body mass estimates can be accurately assessed provided that the individual is within 18.50 ≤ BMI ≤ 29.99 for White males and 18.50 ≤ BMI ≤ 24.99 for White females. Recommendations on how to report total body mass estimates are also presented.

Can we refine body mass estimations based on femoral head breadth?

Femoral head breadth is widely used in body mass estimation in biological anthropology. Earlier research has demonstrated that reduced major axis (RMA) equations perform better than least squares (LS) equations. Although a simple RMA equation to estimate body size from femoral head breadth is sufficient in most cases, our experiments with male skeletons from European data (including late Pleistocene and Holocene skeletal samples) and the Forensic Anthropology Data Bank data (including the W. M. Bass Donated Skeletal Collection sample) show that including femoral length or anatomically estimated stature in an equation with femoral head breadth improves body mass estimation precision. More specifically, although directional bias related to body mass is not reduced within specific samples, the total estimation error range, directional bias related to stature, and temporal fluctuation in estimation error are markedly reduced. The overall body mass estimation precision of individuals representing different temporal periods and ancestry groups (e.g., African and European ancestry) is thus improved.

Regression equations for the estimation of stature and body mass using a Greek documented skeletal collection

Body size is an important variable in bioarchaeological and forensic studies, making the accurate calculation of stature and body mass imperative. Given that anatomical and morphometric approaches offer accurate results but require a particularly good preservation of the skeletal material, whereas mathematical and mechanical methods are more easily applicable but they are largely population-specific, the present paper uses a 'hybrid' approach in order to generate regression equations for the prediction of stature and body mass in a modern Greek sample. Specifically, anatomical and morphometric methods were used to calculate the stature and body mass of the individuals and regression equations using the Ordinary Least Squares and Reduced Major Axis methods were generated with long bone lengths and femoral head breadth as predictors. The obtained equations exhibit low random and directional error and perform better than existing equations designed using different samples from the United States, Europe, and the Balkans. Therefore, these equations are more appropriate for modern Greek material.

Temporal trends in craniometric estimates of admixture for a modern American sample

OBJECTIVES

Temporal trends in craniometric estimates of admixture are investigated for three U.S. populations in the FDB. Patterns of association between birth years and posterior probabilities of cluster membership are identified to assess how these proportions of admixture have changed over recent time. Demographic and genetic data correlates, patterns of morphological expression, and shifts in source populations are evaluated.

MATERIALS AND METHODS

Estimates of three-way admixture were obtained for 1,521 individuals of documented population, sex, and birth years that span the 20th century. Correlations were calculated between birth years and admixture proportions for members of each FDB population. Population and sex-specific admixture variation was further assessed by ANOVA and regression. Correlation analysis was used to identify, per population, which of the cranial measurements change in dimension under increased or decreased admixture.

RESULTS

Admixture proportions differ significantly by population and change over time. No sex differences are detected. Analysis of the relationship between admixture proportions and ILDs finds that admixture drives morphological change in areas of the cranium known to vary among populations. Results agree with prior work on secular change.

DISCUSSION

Findings reveal a progressive increase in White-European population admixture for the self-identified Black individuals, a recent demographic shift toward the increased representation of Hispanic individuals carrying greater Native American ancestry, and reduction in admixture for White individuals that suggest a loss of diversity over time. Changes in admixture produce tractable differences in morphological expression. Both sexes exhibit similar admixture proportions and self-identification patterns. Observed diachronic trends are corroborated by information on recent U.S. demographic change.

The accuracy of the anatomical method for stature estimation in Black South African females

The anatomical method is considered the most accurate stature estimation method, but investigation has shown that it continuously underestimates stature. This underestimation is believed to be related to the use of universal soft tissue correction factors. Therefore, the aim of this study was to assess the accuracy of the soft tissue correction factors in a living population of Black South African females and to subsequently calculate a new soft tissue correction factor, specific for stature estimation in this population group. Thirty Black South African adult females voluntarily participated in this study and underwent a full body Magnetic Resonance Imaging (MRI) scan. Living stature was measured with a stadiometer and total skeletal height (TSH) was calculated from the MRI measurements. Stature was estimated from the TSH of each participant using Fully's (1956) [17], Raxter et al.'s (2006) [38] and Bidmos and Manger's (2012) [5] methods. Results indicated strong, statistically significant positive correlations between living and estimated statures, however, paired t-tests revealed that living stature was significantly underestimated using Fully's and Raxter et al.'s methods, while the method by Bidmos and Manger significantly overestimated stature. A lack of statistically significant correlations between soft tissue correction factors and the total skeletal height was found. Likewise, an absence of statistically significant correlations between age and the estimation error, with and without age adjustments were also observed. A new soft tissue correction factor, specific for stature estimation in Black South African females was calculated. The newly proposed regression equation presented improved stature estimation accuracies for this population group.

Metric Methods for the Biological Profile in Forensic Anthropology: Sex, Ancestry, and Stature

The biological profile, conducted by a forensic anthropologist, is necessary for severely decomposed or skeletonized remains. The biological profile consists of estimates of sex, age, ancestry, and stature. It is crucial to have a correct estimate of sex, as this designation will narrow down the search through missing persons reports by half (e.g., searching through NamUs). However, sex estimates can be population specific, necessitating accurate ancestry estimation. When estimates of age and stature are added, the search narrows further. If these estimates are incorrect, the unidentified human remains may never be identified. These biological profile components are estimated based on either metric or nonmetric methods (visual observation and recording of categorical data). While age is inherently nonmetric, stature is inherently metric. Estimates of sex and ancestry can take a metric or nonmetric approach. The purpose of this review article is to review metric methods in forensic anthropology (sex, ancestry, and stature), to provide general knowledge of why and how these metric methods work, and to highlight that estimates of sex, ancestry, and stature do not subscribe to a "one size fits all" model.

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.

Stature in 19th and early 20th century Copenhagen. A comparative study based on skeletal remains

Individual stature depends on multifactorial causes and is often used as a proxy for investigating the biological standard of living. While the majority of European studies on 19th and 20th century populations are based on conscript heights, stature derived from skeletal remains are scarce. For the first time in Denmark this study makes a comparison between skeletal stature and contemporary Danish conscript heights and investigates stature of males and females temporally and between socially distinct individuals and populations in 19th and early 20th century Copenhagen. A total of 357 individuals (181 males, 176 females) excavated at the Assistens cemetery in Copenhagen is analyzed. Two stature regression formulae (Trotter, 1970; Boldsen, 1990) are applied using femur measurements and evaluated compared to conscript heights. The results indicate that mean male stature using Boldsen follows a similar trend as the Danish conscript heights and that Trotter overestimate stature by ca. 6cm over Boldsen. At an inter population level statistically significant differences in male stature are observed between first and second half of the 19th century towards a slight stature decrease and larger variation while there are no significant changes observed in female stature. There are insignificant differences in stature between middle and high class individuals, but male stature differs statistically between cemeteries (p=0.000) representing middle/high class, paupers and navy employees, respectively. Female stature had no significant wealth gradient (p=0.516). This study provides new evidence of stature among males and females during the 19th century and suggests that males may have been more sensitive to changes in environmental living and nutrition than females.

Formulae for estimating skeletal height in modern South-East Asians

Estimating stature in human skeletal remains of Asian ancestry is problematic for forensic anthropologists due to the paucity and uncertain suitability of regression formulae. To address this issue, our study analyzed 64 individuals from a modern skeletal collection of South-East Asian origin and developed population-specific ordinary least squares regression formulae to estimate skeletal height from each of the long bones of the upper and lower limbs, as well as from trunk length. Results indicate that the most accurate estimates of skeletal height from a single bone (as measured by standard error of the estimate-SEE) are from tibial length in males (SEE = 2.40 cm) and from humeral length in females (SEE = 2.59 cm), followed by femoral length (SEE = 2.84 cm). When multiple elements are considered, the combination of femoral and tibial length yields the best estimates in both sexes as well as combined sex samples (male SEE = 2.40 cm; female SEE = 2.77 cm; combined sex SEE = 2.54 cm).

Application of the anatomical method to estimate the maximum adult stature and the age-at-death stature

This study focuses on the age adjustment of statures estimated with the anatomical method. The research material includes 127 individuals from the Terry Collection. The cadaveric stature (CSTA)-skeletal height (SKH) ratios indicate that stature loss with age commences before SKH reduction. Testing three equations to estimate CSTA at the age at death and CSTA corrected to maximum stature from SKH indicates that the age correction of stature should reflect the pattern of age-related stature loss to minimize estimation error. An equation that includes a continuous and linear age correction through the entire adult age range [Eq. (1)] results in curvilinear stature estimation error. This curvilinear stature estimation error can be largely avoided by applying a second linear equation [Eq. (2)] to only individuals older than 40 years. Our third equation [Eq. (3)], based on younger individuals who have not lost stature, can be used to estimate maximum stature. This equation can also be applied to individuals of unknown or highly uncertain age, because it provides reasonably accurate estimates until about 60/70 years at least for males.

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.

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation.

Estimation of stature from hand and handprint dimensions in a Western Australian population

As part of the formulation of a biological profile, the estimation of stature is an important element that provides useful data towards narrowing the pool of potentially matching identities. Recent literature has demonstrated that anthropometry of the hand has considerable promise for the accurate estimation of stature; although the technique has only been tested in a relatively limited range of populations. The aim of the present study, therefore, is to assess the reliability and accuracy of using anthropometric hand measurements for the estimation of stature in a contemporary Western Australian population; we also evaluate whether stature can be accurately estimated from the measurement of handprints. The study sample comprises 91 male and 110 female adult individuals. Following the measurement of stature, seven measurements are taken on each hand and its corresponding print. To establish the reliability of acquiring these measurements, a precision study was performed prior to primary data collection. Measurements data are analysed using basic univariate statistics and simple and multiple regression analyses. Our results show that the degree of measurement error and reliability are well within accepted standards. Stature prediction accuracy using hand and handprint measurements ranges from ±4.74 to 6.53cm, which is comparable to established skeletal standards for the hand. This study provides new forensic standards for the estimation of stature in a Western Australian population and also demonstrates that the measurement and analysis of handprints affords a novel source of profiling data that is statistically quantified.

Stature estimation from long bone lengths in a Thai population

The estimation of stature is a very important step in developing a biological profile for forensic identification. However, little previous work has been done on stature estimation among modern Thai people, despite a growing number of forensic cases in Thailand in recent years. The current study was carried out on a sample of 200 skeletons from a northern Thai population (132 males and 68 females), ranging in age from 19 to 94 years. The maximum lengths of six long bones (humerus, radius, ulna, femur, tibia and fibula) were measured and stature reconstruction formulae generated using linear regression. These equations were then tested on a holdout sample of 15 females and 15 males. Results reveal that the three lower limb bones are the most accurate estimators of stature among the males, with the fibula equation producing the lowest standard error of the estimate (SE=4.89cm), followed by the femur (SE=5.06cm). Results for females were mixed. The femur produced the lowest standard error among the females (SE=5.21cm), followed by the radius (SE=5.63cm). However, when tested against the holdout sample (n=30), the femur equations were considerably more accurate, with a mean absolute error of 3.5cm and a median absolute error of 2.4cm. Females exhibited a higher standard error of the estimate than reported in many previous studies. This higher error may be the result of a recent secular trend in stature affecting the females of our sample somewhat more than the males.