Prediction Of Stature Research Articles

Stature Prediction and Formulation of Regression Equation from Hand and Foot Anthropometry

Background: Estimation of stature is a key feature of personal identification. Evaluation of stature fromincomplete skeletal and decomposing human remains is particularly important in personal identification forforensic experts and anthropologists.Methods: The data was collected from 1000 asymptomatic, healthy adults (500 males and 500 females)belonging to border areas of Punjab region of age group ranged between 18-50 years.Results: The comparison of each parameter of the study shows that all parameters have higher valuesin males than in females. It is also observed that in males highest correlation is exhibited by Right footlength(r= .418) and in females it is exhibited by Left Foot Length (r= .354). The calculated linear regressionformulae show good reliability and applicability for stature estimation.Conclusion: In all parameters the foot length and hand length are better predictors of stature in both sex.Using regression formulae the height of subject can be easily determined and this will be used as researchtool in anthropological and medicolegal issues.

Stature Estimation of an Individual Using Nasal, Facial, and Palatal Height among Tamil Nadu Population.

Background:Stature estimation in human identification has a significant forensic importance. The stature correlates positively with bones or human body parts. Measurements of various body parts such as the arm, leg, feet, and finger can be used to estimate stature. This study is done to correlate the stature of person with facial, nasal, and palatal height among Tamil Nadu population.Aim and Objective:The aim and objective was to determine an individual's stature using facial, nasal, and palatal height and to find out the most reliable parameter to determine the stature of the person.Materials and Methods:Anthropometer, Vernier caliper, and palatometer were used for the analysis. The initial pilot study included 20 individuals. The representative study included 100 individuals of age 21–25 years. (Group 1 – males, Group 2 – females). Values of the three parameters (nasal, facial, and palatal) are calculated and related to that of the person's stature.Results:The quantitative data collected from the subjects are studied using (Pearson correlation) statistical analysis. The quantitative data availed from nasal height were found to be more reliable compared to the other two data in stature prediction. Correlation between stature and nasal height shows a significant positive correlation among the female group (2) with (P– value = 0.57).Conclusion:This study may play a significant role in case of human identification immediately after mass disasters and certain criminal investigations. Further studies with larger samples may produce more reliable values.

Stature Estimation from Anthropometry of Foot in Adults of Border Areas of Punjab

Background: Stature is one of the various parameters of identification of the individuality of a person. Estimation of stature from various measurements of the body is of value in medicolegal investigations as well as in anthropology. The foot measurements are important in forensic field as they can be used as body height predictors for an individual.The current study deals with developing a regression equation for stature estimation from foot breadth and foot length and to find out the correlation between stature, foot breadth and foot length. Methods: The data was collected from 500 asymptomatic, healthy adults (250 males & 250 females) belonging to border areas of Punjab region of age group ranged between 18-50 years.Results: The correlation between foot length and stature (r= 0.337) was more than foot breadth and stature (r= 0.046) indicating foot length to be a better predictor of stature. Linear regression equations were derived for estimation of stature from foot breadth and foot length.Conclusion: Both foot breadth and foot length showed positive correlation with stature as indicated by the regression coefficient. The results indicate that one can successfully estimate staure from different foot dimensions. The calculated regression formulae show good reliability and applicability of estimate which would be useful for Anthropologists and Forensic Medicine experts.

Prediction of Stature in Males of Tamil Population from Measurements of Percutaneous Tibial Length

Forensic experts are often in confrontation with the challenging task of determination of stature along withrace, age etc. for the purpose of establishing the identity of the deceased individual in those circumstanceswhere only skeletal remains, mutilated or dismembered body parts, extremely decomposed body parts etc.are provided by investigating authorities. In the current study, a genuine attempt has been made to arriveat the population specific regression equation for stature prediction from the percutaneous length of Tibia.The subjects chosen for this study include 120 adult males belonging to Tamil population falling withinthe age range of 21 to 30 years. Stature and percutaneous lengths of right and left Tibia from each subjectwere precisely recorded following standard protocols using appropriate instruments and analysis of thedata collected was done applying Pearson correlation through SPSS software version 26 to arrive at theregression equations for stature assessment based on percutaneous right and left Tibial lengths respectively.By comparing the regression formulae obtained from the present study with those derived from variouspopulation specific studies done on Indian population, our regression equations found to be distinctive toTamil population and therefore can be authentically applied for calculation of stature of deceased frompercutaneous Tibial length in males of Tamil population whenever skeletal remains are available.

Estimation of Stature from Foot Dimensions

The purpose of this study is to establish reliability of estimating stature from the foot dimensions inSouth Indian population. Volunteers aged above 18 years were recruited for the study and measured usingstandard measuring using standardized measuring equipment. Anthropometric measurements taken includestature,foot length, foot breath, navicular height and malleolar heights. Correlations,regression formulaand linear regression equations derived for both male and female showed positive correlation coefficientbetween stature and foot dimensions. To conclude foot dimensions were correlated with stature and can bea better predictor of stature.

Relationship Between Pituitary Siderosis and Endocrinological Disorders in Pediatric Patients with Beta-Thalassemia.

IntroductionExcess iron accumulation occurs mainly in organs such as reticuloendothelial cells, the pituitary gland, and the pancreas in beta-thalassemia because of blood transfusions. In the present study, it was aimed to investigate the relationship between T2* values on magnetic resonance imaging (MRI) and clinically diagnosed pituitary endocrinological disorders in children with thalassemia major.MethodsThis study enrolled patients diagnosed with beta-thalassemia at pediatric hematology outpatient clinics. In the study, in addition to the medical history of the patients, routinely performed tests, including hemoglobin electrophoresis, routine biochemical tests, and tests for pubertal development (follicle-stimulating hormone (FSH), luteinizing hormone (LH), estradiol, testosterone, etc.), as well as iron deposition measured by hepatic MRI T2* (STAR) sequence, were retrospectively assessed. A total of 29 patients were enrolled.ResultsHypothyroidism was detected in 34.6% (9/26) of patients, short stature in 37% (10/27), and pubertal retardation in 50% (14/28) of the patients. There was no significant correlation between hypothyroidism and pituitary MRI T2* values. No significant correlation was found between laboratory parameters and pituitary MRI examination. Although the sensitivity of T2* levels could rise above 80%, their specificity remained low. This is one of the major limitations of the pituitary MR T2* study for the prediction of short stature. The best lower cut-off level of MR T2* to predict short stature was found 14.6 ms.ConclusionThe diagnostic specificity pituitary MR examination levels for short stature were detected as low. Thus, the clinical standardization and validation of pituitary MR T2* values examination are needed before clinical follow-up and multifaceted studies are needed.

Prediction of Gender and Stature by Footprint Analysis in Punjab Population, Pakistan

Prediction of Gender and Stature by Footprint Analysis in Punjab Population, Pakistan

Adult Body Height and Cardiometabolic Disease Risk: The China National Health Survey in Shaanxi.

ObjectivesBased on data from the China National Health Survey, we aimed to examine the association between body height and cardiometabolic disease (CMD) in a large adult population from Shaanxi province, and further to test whether this association was hinged upon other population characteristics.MethodsThis population-based study was conducted in 2014 in Shaanxi Province, China. Utilizing a multi-stage stratified cluster sampling method, total 5,905 adults with complete data were eligible for analysis, and 1,151 (19.5%) of them had CMD. Of 1,151 CMD patients, 895 (15.1%) had one disorder and 256 (4.4%) had ≥2 disorders.ResultsUsing the bi-directional stepwise method and all-subsets regression, five factors—age, body mass index, family histories of CMD, exercise, and height—constituted the optimal model when predicting CMD risk. Restricted cubic spline regression showed a reduced tendency towards CMD with the increase of body height, with per 10 cm increment in body height corresponding to 14% reduced risk. Ordinal Logistic regression supported the contribution of body height on both continuous and categorical scales to CMD risk before and after adjustment, yet this contribution was significantly confounded by exercise and education, especially by exercise, which can explain 65.4% of total impact. For example, short stature was associated with an increased risk of CMD after multivariable adjustment not including exercise and education (odds ratio, 95% confidence interval, P: 1.42, 1.21 to 1.66, <0.001), and tall stature was associated with a reduced risk (0.77, 0.64 to 0.92, 0.003).ConclusionsOur findings indicate short stature was a risk factor, yet tall stature was a protective factor for CMD in Chinese. Notably, the prediction of short and tall stature for CMD may be mediate in part by exercise.

Stature determination from different body dimensions: a systematic review appraisal

Forensic anthropology is a special sub-field of biological anthropology (the study of human remains) that involves applying skeletal analysis and techniques in archaeology and forensic sciences to solving identity cases. Generally speaking forensic anthropology is the examination of human skeletal remains for law enforcement agencies to help with the recovery of human remains, determine the identity of unidentified human remains, interpret trauma, and estimate time since death. Through the established methods, a forensic anthropologist can aid law enforcement in establishing a profile of the unidentified remains. The profile includes sex, age, ancestry, height, length of time since death, and sometimes the evaluation of trauma observed on bones. In many cases after identity of an individual is made, the forensic anthropologist is called to testify in court regarding the identity of the remains and/or the trauma or wounds present on the remains. In the era of uncertainty of life and uplifment of criminal activities, there should be an enriched stock of scientific weapons for investigation and identification. In this context, the present review analysis initiated for the prediction of stature of an individual from different body parts that could enhance the procedures of identification as well as investigation.

Nutritional and socio-economic predictors of adult height in 152 world populations

Height is one of the most sensitive indicators of well-being because it combines the external influences of nutrition, economic wealth, health care, social equality, and other important socio-economic factors. The aim of this ecological study was to compare actual values of male and female height from 152 populations (except sub-Saharan Africa) with the mean supply of 47 food items from the FAOSTAT database (1995-2013) and mean values of seven socio-economic indicators (1995-2013). This comparison shows that economic wealth at the country level is only a mediocre correlate of physical growth because it is only loosely associated with the quality of nutrition and it does not reflect the social distribution of wealth. In a multiple regression model, the best predictors of stature are protein sources of the best and worst quality, and total fertility (which critically influences the amount of resources expended per child). In summary, these findings indicate that irrespective of crude economic statistics, the choice of specific nutrient sources and small family size are crucial factors determining the optimal physical development of children. Based on our data, we also believe that current international dietary recommendations regarding protein intake and protein quality would deserve serious re-evaluation.

Stature estimation in forensic examinations using regression analysis: A likelihood ratio perspective

For the identification of decomposed dead bodies and skeletal remains, estimation of stature is of utmost importance. In estimating stature from the percutaneous bone lengths or skeletal remains, regression analysis has been the method of choice. Technically, as the regression line is just the best fit to the data, the estimate of stature differs from the actual stature, and this difference is reported in terms of the root mean square error (RMSE). The estimate using regression analysis is probabilistic in nature and there is a confidence interval about the prediction. This interval is mostly not reported in various studies, neither are the probable errors in estimation. In the likelihood ratio approach, absolute “matching” or “identification” is not possible and therefore, only the quantitative strength of evidence (strength of association in the present context) is given.The sample for the present study comprised of 344 young adults (172 females and 172 males) residing in the Shimla city of Himachal Pradesh State of north India. The data have been generated from anthropometric measurements of seven percutaneous bone lengths besides stature. The present study reports the regression equations for stature estimation as traditionally calculated, but additionally, it signifies the determination of the confidence intervals of the regression line as well as the confidence intervals of the prediction of stature. The study also shows that for the likelihood ratio estimation, the regression analysis needs to be flipped, i.e. instead of using regression of stature versus bone length; the regression of bone length versus stature should be used.Practical application of finding the likelihood ratio of a recovered bone to be associated with two missing persons of known stature has also been discussed in the current study. This approach is further extended to a general scenario, where the likelihood of a person of known stature is evaluated with reference to any other person chosen at random from the relevant population. The likelihood ratios arrived at, have been found to be generally low, meaning that the strength of association of stature and percutaneous bone length is not very high, and combining likelihood ratios from different methods of personal identification may be needed.

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.

What can glove impression evidence reveal about assailants? A pilot study

Impressions and marks are expected components of any crime scene. There is nothing more disappointing for fingerprint experts than finding glove marks at a crime scene. The forensic expert’s primary task in such cases is to compare the characteristic features of glove impressions with the characteristics of a suspect. The aim of the present study was to determine whether additional information could be obtained from glove prints. Specifically, whether they could be used to help to predict the sex and stature of a suspect was investigated, as was the potential for ascertaining additional information in cases where such prints were recovered from diverse objects with different diameters. Male and female participants wore latex gloves, and after ink was applied to the gloves they grasped objects of different diameters (2, 4, 6 and 8 cm). Impressions of gloved flat hands were also obtained. Phalangeal and finger lengths were measured digitally via software. Sex and stature were successfully estimated based on impressions derived from gloved flat hands and from prints on various grasped objects. A regression equation was developed for stature prediction, and a discriminant equation was developed for sex prediction.

Prediction of Stature Based on Foot Length In Medical Students of Birat Medical College &amp; Teaching Hospital, Morang, Nepal

Introduction: Stature is one of the most important anatomical parameters for personal identification. Estimation of stature by measuring different parts of the body is valuable in medico legal investigations as well as in anthropology.&#x0D; Objectives: The objective of this study was to find correlation between stature and foot length and developing a regression equation for stature estimation from foot length among medical students of Birat Medical College &amp; Teaching Hospital, Morang, Nepal.&#x0D; Methodology: This is cross sectional study conducted at Department of Anatomy of Birat Medical College &amp; Teaching Hospital, Morang, Nepal from 15 March 2019 to 15 June 2019. Two hundred (100 male and 100 female) medical students were enrolled in the study. Stature and foot length were measured using standard instruments. The collected data was entered into Microsoft excel and analyzed by using SPSS.&#x0D; Results: The mean stature in male was 165.4 cm with SD of 8.46 cm, in female the mean stature was 156.5 cm and with SD 6.56 cm. The mean foot length in male was 25.84 cm with SD of 1.73 cm, in female mean foot length was 23.35 cm with SD 1.30 cm. This gender wise difference in mean stature and foot length between males and females was statistically significant (p&lt;0.001). There was significant positive correlation between stature and foot length (r = 0.534, P &lt; 0.001) for male and (r=0.675, P &lt; 0.001) for female. Regression equations were derived for estimation of stature from measurement of foot length in both sexes.&#x0D; Conclusion: This research found significant positive correlation between stature and foot length in both sexes. Regression equation was also derived which help to predict the stature by knowing the foot length in medico legal cases.

Update on the predictability of tall stature from DNA markers in Europeans

Predicting adult height from DNA has important implications in forensic DNA phenotyping. In 2014, we introduced a prediction model consisting of 180 height-associated SNPs based on data from 10,361 Northwestern Europeans enriched with tall individuals (770 > 1.88 standard deviation), which yielded a mid-ranged accuracy (AUC = 0.75 for binary prediction of tall stature and R2 = 0.12 for quantitative prediction of adult height). Here, we provide an update on DNA-based height predictability considering an enlarged list of subsequently-published height-associated SNPs using data from the same set of 10,361 Europeans. A prediction model based on the full set of 689 SNPs showed an improved accuracy relative to previous models for both tall stature (AUC = 0.79) and quantitative height (R2 = 0.21). A feature selection analysis revealed a subset of 412 most informative SNPs while the corresponding prediction model retained most of the accuracy (AUC = 0.76 and R2 = 0.19) achieved with the full model. Over all, our study empirically exemplifies that the accuracy for predicting human appearance phenotypes with very complex underlying genetic architectures, such as adult height, can be improved by increasing the number of phenotype-associated DNA variants. Our work also demonstrates that a careful sub-selection allows for a considerable reduction of the number of DNA predictors that achieve similar prediction accuracy as provided by the full set. This is forensically relevant due to restrictions in the number of SNPs simultaneously analyzable with forensically suitable DNA technologies in the current days of targeted massively parallel sequencing in forensic genetics.

Prediction of Stature from Metacarpal Length and Hand Length: A Digital Radiographic Study

Prediction of Stature from Metacarpal Length and Hand Length: A Digital Radiographic Study

A Study of Determination of Stature in Hyderabad Population from External Ear Morphometry

Introduction: Many studies have been conducted on the estimation of stature from different body parts like hands, trunk, vertebrae, extremities and foot. Since, all these parts of the body and also bones are not always available for forensic examination. It becomes now necessary to make use of other parts of the body like head &amp; face region. Determination of stature is considered an important parameter in medico-legal and forensic examinations.Objective: this study was carried out to investigate the possibility of estimating stature from external ear morphometry in a sample of Hyderabad population.Method: This study was carried out on 300 persons (180 males and 120 females). Besides stature, eight measurements were obtained from both ears of each participant using manual vernier caliper. Data were analyzed by SPSS version 16.Results: There was a strong significant positive correlation between all measurements and stature. A linear equation model for prediction of stature from given external ear dimension was generated. By simple linear regression analysis, the most accurate predictable variable of stature from both ears in males was ear length (R² = 0.728 in right ear and R² = 0.815 in left ear). While in females; right ear width (R² = 0.655) and left conchal width (R² = 0.791) are the most accurate variables that can predict stature.Conclusion: it is concluded that external ear morphometry can be used as an additional tool in the estimation of stature in Hyderabad population.

Stature estimation from the combination of clavicle, scapula, and sternum from 3D-VRT images in Chinese population.

The objective of the present study was to generate multiple regression models for stature estimation on the basis the combination of the clavicle, scapula and sternum derived from 3D-VRT images in Chinese population. The study sample comprised 363 individuals from China, including 159 females and 204 males, with documented ages between 19 and 82 years. Separate multiple linear regression equations for estimating stature on the basis of the measurements from the clavicle, scapula and sternum were then devised for males and females. For assessing the correlation between the stature and measurements of the clavicle, scapula and sternum, the Pearson's correlation coefficient was calculated and its significance was tested by Students t test. Finally, the multiple regression equations calculated from the measurements of the clavicle, scapula and sternum in relation to stature for each sex were established in the present study. The accuracy of stature prediction ranged from 4.777 to 5.313 cm for male and from 4.388 to 4.658 cm for female. In conclusion, the present results provide indications that the combination of the clavicle, scapula and sternum should be used as alternatives for stature estimation, and the multiple equations presented for stature estimation seem to be a more accurate than the equations from single bone.

Estimation of stature from radiographically determined lower limb bone length in modern Chinese

To develop population - specific stature prediction equations from measurements of the lower limb bone in a contemporary Chinese. 303 individuals of Han group in Western China, including 201 females and 102 males were collected. The study sample was randomly divided into two subgroups. A calibration sample, which consisted of 171 females and 87 males, was used to develop the regression formula. A validation sample comprising the remaining 30 female and 15 male individuals was then used to test the predictive accuracy of the established formula. The regression equations were developed from intact bones and fragments of the femur, tibia and fibula, the maximum lengths of femur, tibia, and fibula were highly correlated with the stature. The maximum length of femur provide the most accurate result with the prediction accuracy of 3.84 cm for unknown sex, 4.00 cm in the male group, 3.45 cm in the female group, 3.61 cm in the group with age no more than 45, 3.45 cm in the group with age above 45. Moreover, the multiple regression equations were developed, and they portray a more accurate stature in instances in which the femur, tibia and fibula are available. This paper provides indications that the femur, tibia and fibula are important bones for stature estimation and they could be effectively used in forensic cases.

A comparative study on the statistical modelling for the estimation of stature in Korean adults using hand measurements.

In forensic research, stature is an important indicator in the identification of humans. There are numerous methods for estimating stature, and their goal is to determine the optimal variables for delivering the most accurate predictions. The purpose of this study is to compare the predictive algorithms for stature based on various hand dimensions. The selected hand variables can be separated into four categories-length, breadth, wrist, and thickness-and 18 variables were eventually selected in this research. The hand dimension data were analyzed by descriptive statistics. In the Korean population, there were significant differences found within genders in terms of hands and stature. Two predictive algorithms, regression and artificial neural network, were compared on the basis of their coefficient of determination (R2) and root mean square error (RMSE). In the single linear regression, hand length (R2 = .386) and palm length (R2 = .349) were found to be the most relevant variables in stature prediction for males. For females, hand length (R2 = .286) and inner grip circumference (R2 = .261) scored the highest R2. In the multiple linear regression, an R2 of .659 was obtained for both males and females, with an RMSE of 5.38 cm. In the artificial neural network, the value of R2 was .05, along with an RMSE of 5.17 cm. Overall, this study proposes the artificial neural networks as an improved predictive algorithm for stature, and hand length and inner grip circumference were found to be the most relevant variables to predict stature.