Estimation of stature from the upper limb measurements of Sudanese adults

Prediction of Body Height Using Hand Length and Hand Breadth in Pharmacy and Nursing Students at Misrake Ghion College, Northeast Ethiopia: An Anthropometry Study

Objectives

To predict body height using hand length and hand breadth in pharmacy and nursing students at Misrake Ghion College, Northeast Ethiopia.

Methods

A cross-sectional prospective study was conducted from October 15 to January 20, 2021. The study was carried out on 316 students (160 males and 156 females). The study participants were from the Amhara ethnic groups, with the age range of 18 to 25 years. Body height, hand length, and hand breath were measured and analyzed using SPSS version 23. The strength of association was evaluated using correlation analysis. The significance level was set at p < 0.05. A paired sample t test was performed. Regression equations were derived using simple and multiple linear regression analysis.

Results

Hand length and hand breadth had a positive significant correlation with body height in both male and females. In both males and females, left hand length had a strong significant correlation (males r = 0.768, females r = 0.670), followed by right hand length (males r = 0.711, females r = 0.626). Regarding hand length, right hand breadth (males r = 0.671, female r = 0.438) and left hand length (males r = 0.504, females r = 0.525). There was a significant bilateral difference in hand length and hand breadth on its right and left sides (p < 0.05). Simple and multiple regression equations were formulated for each sex.

Conclusion

In both males and females, body height can be estimated from hand length and breadth using simple or multiple regression equations.

Simple linear regression approach for evaluating models to estimate stature based on upper limb dimensions of adult Bangladeshi males

Background

The stature of a living human reflects the nutritional, genetic, and disease patterns of individual experiences. This study adopted a simple linear regression method and R2 values to identify the preferred model for stature estimation based on the lengths of the arm, radius, ulna, and hand; breadth of the hand; and circumference of the wrist of the adult Bangladeshi male population. This cross-sectional study was performed in the Anatomy Department of Sir Salimullah Medical College, Dhaka, from January 2009 to June 2011. One hundred right-handed adult Muslim Bangladeshi males aged 25 to 45 years participated in the study.

Results

The regression model using right and left ulnar length explained 63% of the measured stature with the least standard error of the estimate (0.435 and 0.436), the model using left and right arm length explained 60%, the model using left and right radius length explained 51%, and the model using left- and right-hand length explained 44% of the measured stature. However, the models using left and right handbreadth and wrist circumference explained only 11 to 13% of the measured stature with a higher standard error of the estimate (6.66 to 6.73). For 25- to 45-year-old Bangladeshi Muslim males, the ulnar length of both sides was the best predictor of stature.

Conclusions

Linear regression equations in estimating stature effectively may encourage its application in future studies addressing different age groups, sexes, nutritional statuses, religions, and ethnicities of Bangladesh.

Stature estimation for Saudi men based on different combinations of upper limb part dimensions

Estimating stature based on body/limb parts can help define the characteristics of unidentified bodies. The most studied upper limb part is the hand, although few studies have examined whether stature can be estimated using fingers plus other hand dimensions. Moreover, there is paucity in anthropometric studies that determined whether bilateral whole limb parts (e.g., arms, forearms, and hands) are related to stature among the living subjects.This prospective cross-sectional study aimed to evaluate the relationship between different upper limb measurements and the stature of Saudi men. Furthermore, I assessed whether upper limb asymmetry was present, and developed regression models to estimate stature based on different available measurements. Stature and 13 upper limb parameters were measured for 100 right-handed Saudi men who were 18 to 24 years old.All measurements were positively correlated with stature (P < .001), and the best single predictor was the bilateral ulnar length. Asymmetry was more pronounced in the hand measurements. A multiparameter model provided reasonable predictive accuracy (±3.77-5.68 cm) and was more accurate than single-parameter models. Inclusion of the right-side fingers improved the model's accuracy.This study developed potential models for estimating stature during the identification of bodies of Saudi men.

Stature estimation from handprint measurements: an application to the medicolegal investigation

Background

The estimation of the stature of human beings is a major part of medicolegal investigation when only body parts are found. The study aimed to estimate the stature from different handprint measurements in a Bangladeshi population using statistical considerations. A sample of 200 young Bangladeshi adults (100 men and 100 women) with no physical disabilities participated in this study. Stature and seven anthropometric measurements were measured using standard anthropometric measurements. The bilateral asymmetry was tested using the independent t test. The Pearson’s correlation coefficient (R) between the stature and different handprint measurements was calculated. Consequently, the simple and multiple linear regression models were developed to estimate the stature from the handprint measurements.

Results

The bilateral asymmetry was statistically not significant (p > 0.05) in right and left handprints. Sex difference significantly (p < 0.05) influences the relationship between stature and handprint measurements. A positive and strong coefficient of correlation (R) value presents between stature and the handprint measurements. The right 2^nd digit length in men (R = + 0.709, R² = 0.502, SEE = ± 44.141 mm) and the right handprint length in women (R = + 0.552, R² = 0.305, SEE = ± 49.074 mm) were the most reliable estimator of stature. However, when data were combined for both sexes, the right handprint length was identified as the most reliable estimator of stature with higher values of R (+ 0.777) and R² (0.603), and a lower value of SEE (± 55.520). Multiple regression equation showed greater reliability than linear regression equations in stature estimation from handprint measurements in Bangladeshi population.

Conclusions

It was concluded that the estimation of stature from handprint measurements is possible and reliable. The findings of this study are very useful from the forensic and medicolegal point of view and can use to estimate the stature in Bangladeshi population.

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.

Estimation of Body Stature Using the Percutaneous Length of Ulna of an Individual

Objective To explore the association between the percutaneous length of ulna and height of that individual and to formulate a gender-specific formula. Methods This is a cross-sectional study conducted at the Nishtar Medical University, Multan from May 1 2019 to July 1 2019. Length of ulna and body height were measured for 100 participants, including an equal number of males and females. Means of age, length of ulna and body height were compared between both genders. Regression coefficient, Pearson correlation coefficient and constant were calculated and regression formulae were formed for calculating height from length of the ulna for males, females, and the whole study group, separately. Data analysis was done using Statistical Package for the Social Sciences; version 23 (SPSS Inc., Chicago, IL); p≤0.05 was considered statistically significant. Results Pearson correlation coefficient, regression coefficient, constant were statistically significant for males, females, and the whole study group (p<0.001). Regression equations that were devised after analyzing the data to estimate the stature from ulna length are as follows: for the whole study group: 42.830+4.671 (length of ulna); for males: 70.369+3.698 (length of ulna); for females: 18.562+5.617 (length of ulna). Conclusion The length of ulna provides a reliable and relatively accurate means for estimating an individual's height. Regression formulae devised will be of practical use for forensic scientists, anthropologists, archeologists, clinicians and anatomists for estimating the stature from the length of the ulna.

Stature estimation from foot anthropometric measurements in Bangladeshi population

BACKGROUND

Estimating human stature is a major concern to formulate a biological profile which provides effective data for forensic identification. This research was aimed to generate a formula for estimating stature from human foot anthropometry.

METHODS

This study was conducted in selected 150 male and 150 female subjects within the range of 18 to 60 years randomly. From each subject, stature and seven-foot measurements were taken by applying the standard technique. Stature was estimated from foot measurements by using linear and multiple regression equations.

RESULTS

The result showed that each foot measurement was significantly (p < 0.001) and positively correlated with stature. Bilateral difference among male and female was not significant (p < 0.05). Multiple regression models showed better accuracy in estimating stature than linear regression models.

CONCLUSION

In conclusion, it can be said that human stature can be successfully estimated by using foot measurements which can be applied in forensic investigation.

Estimation of sex and stature using anthropometry of the upper extremity in an Australian population

Stature and a further 8 anthropometric dimensions were recorded from the arms and hands of a sample of 96 staff and students from the Australian National University and The University of Newcastle, Australia. These dimensions were used to create simple and multiple logistic regression models for sex estimation and simple and multiple linear regression equations for stature estimation of a contemporary Australian population. Overall sex classification accuracies using the models created were comparable to similar studies. The stature estimation models achieved standard errors of estimates (SEE) which were comparable to and in many cases lower than those achieved in similar research. Generic, non sex-specific models achieved similar SEEs and R² values to the sex-specific models indicating stature may be accurately estimated when sex is unknown.

Height Prediction From Ulna Length of Critically Ill Patients

BACKGROUND

Ulna length (UL) has been used in mathematical formulas to predict the body height of healthy and sick individuals. However, the evaluation of its use with patients admitted to intensive care units (ICU) is scarce. The objective of this study was to develop a mathematical equation to estimate critically ill patients' height using the UL measure and to evaluate its agreement with measured standing height.

METHODS

This cross-sectional study was performed at the ICU of a tertiary hospital in Brazil. A total of 100 patients aged ≥18 years who had their body height measured before ICU admission were enrolled. The equation was developed through multiple linear regression, and its agreement was assessed through paired Student's t test and Bland-Altman plot.

RESULTS

The following formula was obtained: height in cm = 153.492 - (7.97 × sex [sex: male = 1, female = 2]) + (0.974 × UL [in cm]). The difference between means of measured height (MH) and height estimated from UL was not significant (166.26 ± 8.75 cm and 166.30 ± 5.29 cm, respectively, P = .96), and a significant correlation (r = 0.624, P < .001) was detected. In the Bland-Altman analysis, UL was in agreement with MH; however, there was a significant bias (P < .001) suggesting that it may be disproportional and dependent on the average's height value.

CONCLUSION

The mathematical equation for height estimation using UL developed in this study matched the MH of critically ill patients. However, we suggest more studies for its validation.

Stature estimation in a contemporary Japanese population based on clavicular measurements using multidetector computed tomography

The aims of this study was to assess the correlation between stature and clavicular measurements in a contemporary Japanese population using three-dimensional (3D) computed tomographic (CT) images, and to establish regression equations for predicting stature. A total of 249 cadavers (131 males, 118 females) underwent postmortem CT scanning and subsequent forensic autopsy between October 2011 and May 2016 in our department. Four clavicular variables (linear distances between the superior margins of the left and right sternal facets to the anterior points of the left and right acromial ends and between the superior margins of the left and right sternal facets to the left and right conoid tubercles) were measured using 3D CT reconstructed images that extracted only bone data. The correlations between stature and each of the clavicular measurements were assessed with Pearson product-moment correlation coefficients. These clavicular measurements correlated significantly with stature in both sexes. The lowest standard error of estimation value in all, male, and female subjects was 3.62cm (r²=0.836), 3.55cm (r²=0.566), and 3.43cm (r²=0.663), respectively. In conclusion, clavicular measurements obtained from 3D CT images may be useful for stature estimation of Japanese individuals, particularly in cases where better predictors, such as long bones, are not available.

Estimation of stature by using the dimensions of the right hand and right foot in Han Chinese adults

The Han Chinese people are the main ethnic group in China and the largest ethnic group in the world. The dimensions of the hands and feet have been successfully used for the estimation of stature. A total of 26,927 healthy adult subjects, comprising 13,221 men and 13,706 women, were recruited. The survey samples were chosen through random cluster sampling. The mean values were significantly higher in men than those in women for all measurements (P<0.001). All the measurements showed a statistically significant correlation with stature (P<0.01). The combination of the right hand length and the right foot length was the best predictor of stature because it had the lowest standard error of estimate. The use of multiple regression equations yielded better results than did the use of linear regression equations. The accuracy of stature prediction ranged from ±4.81 to ±6.39 cm. The present study was of great importance with regards to improving the physical anthropology database of ethnic groups in China.

Anthropometric correlations between parts of the upper and lower limb: models for personal identification in a Sudanese population

PURPOSE

Identification of a deceased individual is an essential component of medicolegal practice. However, personal identification based on commingled limbs or parts of limbs, necessary in investigations of mass disasters or some crimes, is a difficult task. Limb measurements have been utilized in the development of biological parameters for personal identification, but the possibility to estimate the dimensions of parts of limbs other than hands and feet has not been assessed. The present study proposes an approach to estimate the dimensions of various parts of limbs based on other limb measurements.

METHODS

The study included 320 Sudanese adults, with equal representation of men and women. Nine limb dimensions were measured (five based on the upper limb, four based on the lower limb), and extensive statistical analysis of the distribution of values was performed.

RESULTS

The results showed that all of the measured dimensions were sexually dimorphic and that there was a significant positive correlation between the dimensions of various parts of limbs. Regression models (direct and stepwise) were developed to estimate the dimensions of parts of limbs based on measurements pertaining to one or more other parts of limbs.

CONCLUSIONS

The study revealed that the dimensions of parts of the upper and lower limb can be estimated from one another. These findings can be used in medicolegal practice and extended to constructive surgery, orthopedics, and prosthesis design for lost limbs.

A study of correlations within the dimensions of lower limb parts for personal identification in a Sudanese population

The presence of an isolated limb or limb parts from different individuals presents a major challenge for medicolegal investigators in establishing identification in cases of wars, mass disasters, and criminal assaults because different populations have different sizes and proportions. The measurement of lower limb dimensions showed a high success rate in establishing individual identity in terms of sex and stature in various populations. However, there is a paucity of data concerning the correlation within the lower limb parts. This study aims to assess the existence of relationships within lower limb parts and to develop regression formulae to reconstruct limb parts from one another. The tibial length, bimalleolar breadth, foot length, and foot breadth of 376 right-handed Sudanese adults were measured. The results showed that all variables were significantly larger in males than in females. A significant positive correlation (P < 0.001) was found within the lower limb parts. Sex-specific linear equations and multiple regression equations were developed to reconstruct the lower limb parts in the presence of single dimension or multiple dimensions from the same limb. The use of multiple regression equations provided a better reconstruction than simple regression equations. These results are significant in forensics and orthopedic reconstructive surgery.

A study of the anthropometric correlations between upper limb measurements for personal identification in Sudanese population

The presence of multiple isolated commingled fleshed limbs or limb parts generates a significant challenge for forensic investigators in wars, mass disasters, and criminal assaults in the process of identification. Although upper limb measurements have been used to establish individual identity in terms of sex and stature with high success, there is a scarcity of data concerning the correlations within upper limb parts. Hence, this study aims to assess the relationships within upper limb parts and develop regression formulae to reconstruct the parts from one another. The study participants were 376 Sudanese adults (187 males and 189 females). The results of this study indicated significant sexual dimorphism for all variables. The results indicated a significant correlation within the upper limb parts. Linear and multiple regression equations were developed to reconstruct the upper limb parts in the presence of a single or multiple dimension(s) from the identical limb. Multiple regression equations generated better reconstructions than simple equations. These results are significant in forensics and orthopedic reconstructive surgery.