Stature Estimation Methods Research Articles

An investigation of the relationship between long bone measurements and stature: Implications for estimating skeletal stature in subadults.

The present study introduces new regression formulae that address several challenges of current subadult stature estimation methods by 1) using a large, contemporary, cross-sectional sample of subadult skeletal remains; 2) generating regression models using both lengths and breadths; 3) utilizing both linear and nonlinear regression models to accommodate the nonlinear shape of long bone growth; and 4) providing usable prediction intervals for estimating stature. Eighteen long bone measurements, stature, and age were collected from computed tomography images for a sample of individuals (n = 990) between birth and 20 years from the United States. The bivariate relationship between long bone measurements and stature was modeled using linear and nonlinear methods on an 80% training sample and evaluated on a 20% testing sample. Equations were generated using pooled-sex samples. Goodness of fit was evaluated using Kolmogorov-Smirnov tests and mean absolute deviation (MAD). Accuracy and precision were quantified using percent testing accuracy and Bland-Altman plots. In total, 38 stature estimation equations were created and evaluated, all achieving testing accuracies greater than 90%. Nonlinear models generated better fits compared to linear counterparts and generally produced smaller MAD (3.65 - 15.90cm). Length models generally performed better than breadth models, and a mixture of linear and nonlinear methods resulted in highest testing accuracies. Model performance was not biased by sex, age, or measurement type. A freely available, online graphical user interface is provided for immediate use of the models by practitioners in forensic anthropology and will be expanded to include bioarchaeological contexts in the future.

Comparison of Regression Analysis and Mathematical Methods for Stature Estimation from the Upper Limb Measurements of the Modern South Indian Population

This study aimed to establish reliable mathematical and regression analysis (RA) methods for estimating stature using upper limb (UL) anthropometric parameters in the modern South Indian (MSI) population. This study was conducted on a sample size (117 men and 97 women) from the MSI population. Dead bodies within 3 hours of death were included in this study, as the study outcome is meant to apply to the dead and dismembered UL parts. Mathematical and linear RA methods were used to derive multiplication factors (MFs) and regression equations (REs) for the estimation of stature from UL measurements (arm length [AL], forearm length, palm length, and middle finger length [MFL]) and assess their prediction accuracy. A statistically significant correlation was found between UL measurements and stature, indicating their potential use for stature estimation. Both genders showed a statistically significant positive relationship between UL measurements and stature. Both MF and RA methods exhibited reasonable goodness of fit, albeit the RA method yielded a closer estimate of the actual stature than the former. The derived RE showed reasonable goodness of fit and precision in both genders, as evidenced by high R2 values and low standard errors. The RA and MF methods slightly over- and under-estimated the actual stature, respectively. The MFL and AL showed the strongest and weakest relationship with the stature. Both methods have practical significance though the precision is higher with RA methods. The MF method is simpler, as it is independent of statistical resources, while the RA method may be more useful in cases where there is a large amount of variation in the data. The outcome of this study has significant implications for the forensic and anthropology fields. The derived RE and MF provide a reliable framework for estimating stature from anthropometric measurements of dismembered UL remnants. This information can be valuable in forensic investigations, unidentified remains cases and archaeological studies.

New More Generic and Inclusive Regression Formulae for the Estimation of Stature from Long Bone Lengths in Children

Existing child stature estimation methods have a number of disadvantages. This paper addresses some of these limitations by developing regression-based stature estimation formulae that are more generic and inclusive. A sample of 142 individuals under 12 years of age from the Hamann—Todd Human Osteological Collection and the New Mexico Decedent Images Database were used to generate five least squares linear regression formulae to estimate stature from the diaphyseal length of long bones. All models showed excellent fits to the data (R2 close to or at 0.98), and internal validation confirmed the stability and accuracy of model parameters. External validation was performed using a sample of 14 individuals from the Lisbon Collection and the Victoria Institute of Forensic Medicine. Overall, the humerus provides the most accurate estimate of stature, but the femur and tibia showed the greatest coverage. These formulae can be used in a variety of contexts and are not dependent on group affiliation, including sex.

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

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 in Ancient Greece: population-specific equations and secular trends from 9000 BC to 900 AD

Stature is critical for our understanding of human morphology and evolution. This necessitates the development of accurate stature estimation methods. The aim of the present study is to generate population-specific equations for ancient Greece and to explore the diachronic stature trends over the last 10,000 years. In parallel, it introduces the Logarithmic Human Stature Index (LHSI) as a new tool for inter-population comparisons. We collected anthropometric data and reconstructed stature using the anatomical method from 77 males and 59 females from Greece (3rd c. BC–9th c. AD). We utilized this dataset to generate population-specific equations. We then applied the new formula to 775 individuals (10th millennium BC–9th c. AD) from Greece exploring stature secular trends. We tested the new equations to different populations of European origin (662 males and 498 females). Ordinary least square sets based on lower limbs provided the best estimations with the smaller errors. Male and female stature in ancient Greece in the last 10,000 years ranged from 159.7 to 170.6 cm and from 153.1 to 160.4 cm, respectively. We observed a decrease from the Mesolithic to the Neolithic period, a gradual increase from the Bronze Age to the Archaic/Classical periods, and a steady increase from the Roman period onwards. Stature secular trends in Greece are in accordance with historic, archaeological, and genomic data and similar to European patterns. LHSI is a valuable tool for anthropometric comparisons between reference series and thus can contribute to the choice of the optimal stature estimation formula.

Assessing the accuracy of the anatomical method for stature estimation in White South African males

ABSTRACT The anatomical method is considered the most accurate stature estimation method, however, research has concluded that the soft-tissue correction factors associated with this method may be sex- and population-specific. Therefore, this study aimed to evaluate the applicability of these soft-tissue correction factors for the estimation of stature in White South African males. Magnetic resonance imaging scans of 30 White South African male volunteers, between 21 and 59 years of age, were used to collect skeletal measurements of bones that contribute to total skeletal height. The soft-tissue correction factors within the literature were subsequently applied to estimate the living stature of each individual. Paired t-tests were used to compare the accuracies of these estimates of living stature to the measured heights of the participants. Living stature was significantly underestimated using the soft-tissue correction factors of Fully (1956; 6.14 cm), Raxter and colleagues (2006; 4.80 cm), and Brits and colleagues (2017; 0.96 cm), and significantly overestimated by Bidmos and Manger (2012; 9.65 cm). Cloete’s (2017) equation overestimated stature by 0.65 cm, however, this was not significant. These results suggest population-specific soft-tissue correction factors associated with stature estimation and, therefore, the newly derived stature estimation equations should be used to estimate stature of White South African males.

Methodological analysis of stature estimation from tibia osteometric data

ObjectivesStature is one of the characteristic elements of the biological profile, allowing the identification of human bone remains in a forensic context. Stature has a strong relationship of proportionality with the long bones of the lower limb. This study focuses on the biometric exploitation of the whole-bone tibia to estimate stature. The objective is to evaluate the performance of different stature estimation methods using various measurements. In addition, the use of age correction factors was studied in order to observe their influences. Materials and MethodsThe study was based on a sample of 91 tibias (43 males and 48 females) from the Belgian population for which 20 standard measurements were taken. A total of 28 regression equations from eight methods were used with or without the inclusion of two correction factors. The performance of the methods was evaluated by exploiting the estimation errors and the number of individuals included in the area of acceptability defined for the study. ResultsThe tibia measurements were reproducible. The most effective for stature estimation were bone lengths. The whole-bone methods developed in the 21st century was the most efficient, and the application of correction factors allowed for the improvement of the equations. Discussion and conclusionThe best performing method is Nikita et al. 2017, and the correction age best emphasizing stature estimation was 30 years. Equations for females provided the majority of the best results, followed by those for undetermined sex.

A comparison of the anatomical and the mathematical stature estimation methods on an ancient Greek population.

Stature is a key concept in the study of human past since along with the biological information it provides overall trends about the standards of living. However, stature data on historic and prehistoric populations are still limited, especially for key temporospatial settings of antiquity such as ancient Greece. We collected osteometric data from 35 male and 33 female individuals (n = 68) from a Roman Period necropolis (146 BC-330 AD) in northern Greece and we applied the anatomical stature estimation method (Raxter et al. 2006). We compared this estimation with the results of 20 regression equations (both ordinary least squares and reduced major axis methods) and we examined the factors that affect their accuracy such as body proportions and the chronology and geography of reference series. For our analyses, we calculated the percent prediction error (%PE) produced by each regression equation for males and females separately. We introduced the total %PE to evaluate each equation's effectiveness on both sexes simultaneously. We calculated long bone ratios and the Euclidean distance between the Greek dataset and the reference series. According to the anatomical method, males from Northern Greece had a mean stature value of 168.2 cm ± 5.38 and females of 156.9 cm ± 5.27. The regression equations of Vercellotti et al. (2009) provided the best estimations in both sexes. Estimation errors (%PE) were not statistically different between the ordinary least squares and reduced major axis equations. The chronological affinity in body proportions between the target population and the reference series could provide significant evidence for the prediction of the optimal regression formulae. With this paper we provide the first osteometric dataset for the anatomical stature estimation method from ancient Greece and we suggest the most suitable regression equations for this key region of the ancient World.

Improving anatomical stature estimation method. The relationship between living stature and intervertebral disc thickness.

Anatomical stature estimation methods reconstruct stature for skeletal specimens by adding up the heights of skeletal elements contributing to stature. In addition, these estimations factor in a certain amount of soft tissue known as "soft tissue correction". Our study focuses on the relationship between living stature and one of the major soft tissue contributors to stature: the intervertebral disc thickness/height. The purpose of this study was to clarify whether intervertebral disc thickness is greater in tall individuals and whether there is a linear correlation between stature and intervertebral disc height. To conduct this study, we utilized a subsample of the Northern Finland Birth Cohort of 1966 (n = 12,058) with known stature. We measured vertebral heights and intervertebral disc heights from low back MRI examination performed at the age of 46 years (n = 200). All subjects were considered healthy with no spinal injuries or pathologies. Our results clearly indicate that stature and intervertebral disc height have positive, statistically significant association. According to our results it is advisable to take into account the individual's skeletal height when soft tissue corrections for anatomical stature estimations are performed. Further studies utilizing full body MRI are needed to produce more accurate soft tissue corrections.

Application of anthropometric measurements analysis for stature in human vertebral column: A systematic review

Abstract Identification of skeletal human remains as the biggest challenge in forensic anthropology. Human stature estimation is an important biological profile component during forensic anthropological investigation. This systematic review summarised the application of anthropometric measurements on human vertebral column for stature prediction in different population. An extensive literature search was done in PubMed, Science Direct and Google Scholar from 2009 to 2019. The inclusive criteria include English studies that used anthropometry method on human vertebral columns for prediction of stature during identification skeletal remains. During the literature search, 38 related articles were found, whereby 13 had met the inclusion criteria. Most study showed a positive correlation of various anthropometric measurements on human vertebra column for stature estimation in different populations. This evidence-based review revealed the usefulness of anthropometric measurements using human vertebra column as an alternative method other than long bones for identification of human remains among different populations. Further studies are needed to determine the best reliable methods for stature estimation among various anthropometric measurements with a more advanced meta-analysis of the results on human vertebra column.

Stature Estimation from Postmortem CT Femoral Maximum Length in Contemporary Danish Population.

Stature estimation methods for Danish adult population have generally relied on Trotter and Gleser's and Boldsen's regression equations that are based on the skeletal remains of recent war dead American Whites, Terry Skeletal Collection, and Danish archaeological medieval skeletal materials, respectively. These equations are probably not suitable for stature estimation in contemporary Danish forensic cases. Furthermore, because postmortem computed tomography (PMCT) is now routinely performed at Danish forensic departments, equations based on PMCT, rather than measurements of defleshed bones, are needed. The aim of this study was to develop new equations for adult stature estimation based on PMCT femoral measurement. Maximum femoral length was measured on the PMCT images of 78 individuals (41 males and 37 females) aged 23-45years. The measurement accuracy was tested on dry bones, and all the measurements were included in the inter- and intra-observer analyses. Both analyses results demonstrated the reliability of the method and data. Comparison between the living stature of the individuals and the estimates based on the equations by Trotter and Gleser and Boldsen demonstrated the unreliability of the previous equations to some extent. New regression equations were then developed and validated on a different sample of 18 Danish forensic cases. Comparisons of all the equations indicated that both the sets of previous equations underestimated the stature in the new validation dataset. The new equations developed in this study provide a reliable alternative for stature estimation in modern Danish forensic cases.

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.

Ancestry estimation of three Mediterranean populations based on cranial metrics

The estimation of ancestry is an essential benchmark for positive identification of heavily decomposed bodies that are recovered in a variety of death and crime scenes. This is especially true when reconstructing the biological profile of the deceased as most methods for sex, age and stature estimation are population-specific. Ancestry estimation methods vary from traditional morphological assessment of cranial features and biometric quantification to computer-aided shape analysis and classification with specialised software. The current paper aims to explore population differences between three neighbouring countries (Greece, Cyprus and Turkey) that have been in constant interaction through conflicts and population movements from the ancient past to the present day, through cranial measurements.The sample consists of 160 dry crania of Greek origin, 137 dry crania of Greek-Cypriot of origin Cyprus and 380 CT scans from Turks individuals. Twelve measurements were taken in both dry and virtual skulls. Data were submitted to principal component analysis and discriminant function analysis. Intra- and inter-observer error as well as the measurement error between virtual and physical measurements were quantified using TEM, rTEM and R.Measurement error was very low in all cases. Classification accuracy for cross-validated data ranged from 74.1 to 97.9%. The highest accuracy was obtained for the Turks sample both in males and females. The results are in accordance with genetic data on the three populations.These results create great confidence in the application of the produced functions in forensic cases requiring ancestry estimation in Cyprus, specifically to unidentified individuals from the 1974 conflict. In addition, these standards can be applied in other forensic situations where ethnicity is an issue but the geographic area of origin is limited to the area encompassing Turkey, Cyprus and Greece.

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.

Radiographic evaluation of mandibular ramus for gender estimation: Retrospective study.

Background and Aims:Gender estimation is a very important part of a study in the field of anthropology and forensic sciences. In the skeleton, gender estimation is the first step of the identification process as subsequent methods for age and stature estimation are sex-dependent. Skeletal components such as the pelvis and skull are investigated for gender estimation and the mandible is a practical element to analyze sexual dimorphism in fragmented bones. The aim of the present study is to measure, compare, and evaluate various measurements of the mandibular ramus, observed in digital orthopantomographs and also to assess the usefulness of the mandibular ramus as an aid in gender estimation.Materials and Methods:A radiographic retrospective study was conducted using 80 digital orthopantomographs to measure, compare, and evaluate the measurements of the mandibular ramus such as maximum ramus breadth, maximum ramus height, and coronoid heightusing Planmeca ProMax® digital machine to assess the usefulness of mandibular measurements in gender estimation.Results:Descriptive statistics of various measurements and associated univariate F ratios for both the sexes were determined. Four variables were significant predictor in classifying a given sample (P < 0.001). The F-statistic values indicated that measurements expressing the greatest sexual dimorphism were noticed in the maximum ramus height.Conclusion:Mandibular ramus can be considered as a valuable tool in gender estimation and the most reliable measurements were obtained of linear objects in the horizontal plane by digital panoramic imaging.

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.

From toe to head: Use of robust regression methods in stature estimation based on foot remains

Stature estimation is a standard procedure in the fields of forensic and biological anthropology, bio-archaeology and paleoanthropology, in order to gain biological insights into the individuals/populations studied. The most accurate stature estimation method is based on anatomical reconstruction (i.e., the Fully method), followed by type I regression equations (e.g., ordinary least squares – OLS) based on long bones, preferably from the lower limb. In some cases, due to the fragmentary nature of the osseous material recovered, stature estimates have to rely on other elements, such as foot remains. In this study, we explore stature estimation based on different foot bones: the talus, calcaneus, and metatarsals 1–4 in Afro- and Euroamericans of both sexes. The approach undertaken in this study is novel for two reasons. First, individual estimates for each bone are provided, and tarsals and metatarsals are combined in order to obtain more accurate estimates. Second, robust statistical methods based on type I regression equations are used, namely least trimmed squares (LTS). Our results show that the best individual bones for estimating stature are the first and second metatarsal and both the talus and the calcaneus. The combination of a tarsal and a metatarsal bone slightly improves the accuracy of the stature estimate.

CHALLENGES IN APPROACHES TO SKELETAL STATURE ESTIMATION: AN EXAMPLE FROM PREHISTORIC EASTERN MISSISSIPPI AND WESTERN ALABAMA

Although stature is used widely as a bioarchaeological health indicator, its determination and subsequent interpretation are not always straightforward. A study of 77 individuals from eight prehistoric populations from the Tennessee-Tombigbee Waterway illustrates this issue. Application of three common stature estimation formulae to five Middle/Late Woodland and four Mississippian groups strongly suggests that use of partial versus whole bone, choice of element, and stature estimation method can create disparate patterns in health interpretation, not only for the direction of differences but particularly regarding the degree of differences among groups.

Methods for estimating missing human skeletal element osteometric dimensions employed in the revised fully technique for estimating stature

One of the greatest limitations to the application of the revised Fully anatomical stature estimation method is the inability to measure some of the skeletal elements required in its calculation. These element dimensions cannot be obtained due to taphonomic factors, incomplete excavation, or disease processes, and result in missing data. This study examines methods of imputing these missing dimensions using observable Fully measurements from the skeleton and the accuracy of incorporating these missing element estimations into anatomical stature reconstruction. These are further assessed against stature estimations obtained from mathematical regression formulae for the lower limb bones (femur and tibia). Two thousand seven hundred and seventeen North and South American indigenous skeletons were measured, and subsets of these with observable Fully dimensions were used to simulate missing elements and create estimation methods and equations. Comparisons were made directly between anatomically reconstructed statures and mathematically derived statures, as well as with anatomically derived statures with imputed missing dimensions. These analyses demonstrate that, while mathematical stature estimations are more accurate, anatomical statures incorporating missing dimensions are not appreciably less accurate and are more precise. The anatomical stature estimation method using imputed missing dimensions is supported. Missing element estimation, however, is limited to the vertebral column (only when lumbar vertebrae are present) and to talocalcaneal height (only when femora and tibiae are present). Crania, entire vertebral columns, and femoral or tibial lengths cannot be reliably estimated. Further discussion of the applicability of these methods is discussed.

Technical note: A re‐evaluation of stature estimation from skeletal length in the grave

Several methods for stature estimation have been proposed over the years. Among these methods is anatomical reconstruction, regression based on long bone lengths, and measuring skeletal vertex - talus length in the grave for individuals buried in a supine position. Recent studies have dealt with the applicability of skeletal length in the grave (Petersen: Int J Osteoarchaeol 15 (2005) 106-114) and anatomical reconstruction (Raxter et al.: Am J Phys Anthropol 130 (2006) 374-384). The results from the latter study calls into question the results of the former study. Therefore an investigation of the potential bias of using skeletal length in the grave as an estimate of living stature has been performed. Twenty Medieval Danish skeletons were measured both in situ and in the laboratory, and the anatomically reconstructed stature (Raxter et al.: Am J Phys Anthropol 130 (2006) 374-384) was compared with the skeletal length in the grave. The results show that 2.5 cm should be added to skeletal length in the grave in order to obtain an unbiased estimate ofliving stature.