Estimating Height and Sex from Shoulder Width and Arm Length

Estimating Height and Sex from Shoulder Width and Arm Length | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Estimating Height and Sex from Shoulder Width and Arm Length Muazzez Elçin Özkan, Yasemin Balcı, Ümit Ünüvar Göçeoğlu, Barış Ethem Süzek, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8642816/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Identification is important in forensic medical applications. In events with or without mortality, determining the height and sex of individuals is also a part of identification. In this study, it was aimed to develop methods for estimating height and sex from shoulder width and arm length. Materials and Methods One hundred and fifty volunteers were included in the study. In addition to the demographic data of the participants, height, bilateral arm lengths and shoulder width measurements were recorded in the data collection form. Data were evaluated with SPSS statistical program. Correlation and regression analyses were performed. Whether there was a significant difference between the means of the right and left side measurements was tested with the t test. Results Seventy-five (50%) of the participants were female, 75 (50%) were male, and mean age was 26.3 years ± 5.8. The Aegean Region was the region where the majority of the participants lived the longest, both in the place of birth and in the process of completing their bone development. The measurement with the strongest correlation with height is the arm span measurement when the sex is known or unknown, the correlation coefficient between the left side arm length measurements and the height is higher than that of the right, and therefore, if both side measurement results are available, only left side measurements can be measured. It was evaluated that it would be appropriate to use it in estimating the length of the shoulder, the correlation between shoulder width and sex was the strongest, and the formula used together with the left arm length and shoulder width gave the highest rate of correct (89.3%) results. Conclusion It was determined that the strongest correlation with height was the model in which left arm length and shoulder width measurements were used together (R = 0.887). Accordingly, height estimation formula, if sex is unknown, is as such: Height = 51.95+(1.61 x left arm length + 0.589 x shoulder width) (SEE:4.35), and in cases where the sex is known, it is Height = 63.49+(1.49 x left arm length + 0.50 x shoulder width) (SEE:3.89) form males and Height = 79.75+(1.48 x left arm length) (SEE:4.58) for females. Forensic Anthropology Arm Length Shoulder Width Height Estimation Sex Estimation 1. INTRODUCTION Apart from criminal deaths in which the remains are dismembered, burned, or have become impossible to identify postmortem, the remains are generally not in one piece in events where mass deaths occur like in natural disasters such as plane, sea, train accidents, earthquake, tsunami, fire events in crowded buildings, and mass graves after wars ( 1 – 4 ). Determination of sex and height in dismembered remains is the basic and most important part of identification ( 2 ). Making an estimation of sex and height by anthropometric measurements made from unidentified body parts and revealing morphological features are parts of identification. DNA analyses that give definitive results in sex determination are very costly and take a long time to get results. In situations encountered in the ordinary course of life, more practical, low-cost, reliable sex determination methods are needed. Studies have been carried out using the length of hand and arm for identification on mutilated and unidentified remains ( 5 – 10 ). Since the measurement results to be obtained from anthropometric measurements are affected by factors such as the historical period and geographical region of the population where the measurement is made, the social origin of the population, the total number of individuals measured and the way the measurements are made, the measurements need to be restructured and reformulated in accordance with the era. The measurement values of different societies belonging to the same historical period may differ. Again, the anthropometric values of a society in different historical periods may vary ( 11 ). In this study, it was aimed to create formulas for estimating height and sex from shoulder width and arm length. It is assumed that the study will contribute to the creation of a database specific to the Turkish society in the Aegean Region of Türkiye. 2. MATERIALS AND METHODS Ethics Committee Approval dated 13.03.2020 and numbered 37 of Muğla Sıtkı Koçman University Human Research Ethics Committee was received for the research. In the research, a tape measure, electronic height and weight scale, data collection forms, and informed consent forms were used. The study was carried out in the laboratory room of Muğla Sıtkı Koçman University Faculty of Medicine, Department of Forensic Medicine. In the study, the number of samples was determined in the 85–95% confidence interval based on the population of Muğla province, which constitutes the population, with equal sex distribution. The sample size was calculated using the 'Sample Size Calculator' program. According to the calculation, it was determined that 150 participants would be sufficient. Informed consent was obtained from 150 participants who agreed to participate in the study on a voluntary basis. Those with congenital or acquired problems that would make it difficult to make healthy measurements on their shoulders and arms were not included in the study. Written informed consent was obtained from all participants prior to enrollment. Each volunteer was individually informed about the purpose and procedures of the study, the voluntary nature of participation, and the right to withdraw at any time without any consequences. Ethical approval for this study was obtained from the Muğla Sıtkı Koçman University Human Research Ethics Committee (Protocol No: 200008; Decision No: 37; dated 13 March 2020). The study was conducted in accordance with the principles of the Declaration of Helsinki and the provisions of the Turkish Personal Data Protection Law (Law No. 6698). Participants' age, sex, place of birth, place of residence for the longest time, measured height, weight, both arm length and shoulder width measurements were recorded in a data collection form. 2.1. Measurements By means of a tape measure, the distance from the acromion protrusion to the processus styloideus radii on the wrist was measured for arm length measurement, and for shoulder width measurement, the distance between the acromion protrusion on both sides was taken. The arm span measurement included in the study was not taken separately from the participants during the measurement; it was obtained by summing the two sides arm length and shoulder width measurements taken from the participants. The arm span measurement is also referred to as the stroke length measurement. 2.2. Statistical analyses Dependent variables of the study were height and sex; independent variables were shoulder width and arm lengths. Correlation and regression analyses were performed by evaluating all the data obtained through SPSS statistical program. 2.2.1. Stature estimation Means and standard deviations of the measured values are presented. The paired samples t test was used to test whether there was a significant difference between the means of the right and left side measurements. The relation between the measurements taken and height was evaluated by Pearson Correlation Analysis. Formulas were created with Linear Regression Analysis in order to calculate the estimated height. 2.2.2. Sex estimation Measurement values taken for sex determination were evaluated with Spearman Correlation Analysis. Sex estimation formulas were created with Logistic Regression Analysis. Kolmogorov Smirnov test was used in terms of whether each measurement was in normal distribution according to sex, Parametric Independent Sample T Test was used for those with normal distribution, and Nonparametric Mann-Whitney U Test was used for those without normal distribution. In variables in which the difference between the mean according as per sex was significant, sex estimation formulas were created according to the 0.5 cut-off value determined performing Binary Logistic Regression Analysis. The value obtained as a result of applying the formulas was evaluated as female if the cut-off value was greater than 0.5 and male if it was smaller. 3. RESULTS A total of 150 volunteers, 75 (50%) females and 75 (50%) males, were included in the study. Mean age of the participants was 26.3 years (SD: 5.8), with the youngest participant 20 years old and the oldest 57 years old. Although there were participants from every region, the birthplace of 45.3% of the participants was the Aegean region, and 18.0% of them were from the Mediterranean region. The regions where the participants lived the longest and completed their bone development were the Aegean region with 52.7% and the Mediterranean region with 17.3%. Minimum, maximum, mean values and 95% confidence interval of all measurements obtained from the participants are presented in Table 1 . Table 1 Descriptive statistics of measurements obtained from participants MALES FEMALES Mean ± SD Min-Max %95 confidence interval Mean ± SD Min-Max %95 confidence interval Right arm length(cm) 60.25 ± 3.21 51.50–68.00 59.51–60.99 54.67 ± 2.79 48.00–60.00 54.03–55.31 Left arm length(cm) 59.99 ± 3.24 50.50–67.00 59.25–60.74 54.24 ± 2.72 47.00-60.50 53.61–54.86 Shoulder width(cm) 42.30 ± 2.49 37.50–49.00 41.73–42.87 36.61 ± 2.86 31.00-46.50 35.95–37.27 When arm span measurements were evaluated, the mean was 162.55 ± 7.00 in males and 145.51 ± 7.11 in females, and it was seen that the mean of height measurements was 12.23 cm higher than the mean of arm span measurement. Bilateral arm lengths and shoulder widths were found to have a normal distribution in males and females with the applied normality test (Kolmogorov Smirnov; p > 0.05). 3.1. Stature estimation The correlations between all lengths and heights obtained from the participants were evaluated and given in Table 2 . Table 2 Correlation of measured lengths with height Measured lengths Correlation Coefficient (r) Gender unknown (n:150) Male (n:75) Female (n:75) Right Left Right Left Right Left Arm length Sig.(2-tailed) .853 .866 .752 .775 .652 .664 .000 .000 .000 .000 .000 .000 Shoulder width Sig.(2-tailed) .684 .255 .350 .000 .027 .002 Arm span Sig.(2-tailed) .883 .000 .795 .000 .652 .000 Paired samples t test was used to test whether there was a significant difference between the means of the right and left side measurements. As well as having detected a very strong correlation (r:.987, p:000) between right and left arm lengths, a statistically significant difference was also found between the measurement averages (n:150, t: 6.270, p: .000). It was observed that the measurement with the strongest correlation with height was the arm span measurement when the sex was known or unknown. The correlation coefficient between the arm length measurements on the left side and the height was higher than the right side. A strong and statistically significant correlation was found between shoulder width and right (r:.607, p:.000) and left (r:.612, p:.000) arm length. The correlations with height and R² values of the models developed using all measurements are given in Table 3 . Table 3 Models developed using all measurements R R² Adjusted R² Std. Error of the Estimate (SEE) Left Arm Length + Shoulder width 0.887 0.787 0.784 4.348 Right Arm Length + Shoulder width 0.878 0.771 0.768 4.509 Left Arm Length 0.866 0.749 0.747 4.702 Right Arm Length 0.853 0.727 0.726 4.902 Shoulder width 0.684 0.468 0.464 6.851 Arm Span 0.883 0.780 0.778 4.407 According to the models created in the regression analysis of the study group, it was observed that the strongest correlation with height was the model in which left arm length and shoulder width measurements were used together (R = 0.887) and 78.4% (SEE:4.348) of the changes in the height measurement of all individuals in the universe, in which 150 individuals were taken as a sample in the study group, could be explained by this model according to the corrected R² value result. Height estimation formulas of the developed models are given in Table 4 . If the sex is unknown, height estimation formula in the 1st model with the strongest correlation is as Height = 51.95+(1.61 x left arm length + 0.589 x shoulder width) (SEE:4.35). Height estimation models developed in cases where the sex is known are given in Table 5 . In cases where the sex is known and according to the 1st model with the strongest correlation in males, the formula is as: Height = 63.49+(1.49 x left arm length + 0.50 x shoulder width) (SEE:3.89), and for women, it is as: Height = 79.75+(1.48 x left arm length) (SEE:4.58). Table 6 shows the comparison of arm length and shoulder width measurements and their standard deviations in similar studies conducted in different populations for height estimation. Table 4 Models developed using all measurements and height estimation formulas a Models Pearsons correlation (r) Unstandardized Coefficients Std. Error of the Estimate Sig. %95 Confidence Interval B Std. Error Lower Upper 1 Constant LAL SW 0.887 51.948 4.968 .000 42.130 61.766 1.610 0.108 4.348 .000 1.396 1.825 0.589 0.115 .000 0.361 0.816 2 Constant RAL SW 0.878 51.547 5.236 .000 41.200 61.895 1.580 0.113 4.509 .000 1.357 1.804 0.628 0.119 .000 0.394 0.863 3 Constant LAL 0.866 55.787 5.312 4.702 .000 45.290 66.283 1.950 0.093 .000 1.767 2.133 4 Constant RAL 0.853 55.443 5.636 4.902 .000 44.305 66.581 1.944 0.098 .000 1.751 2.137 5 Constant SW 0.684 102.627 5.688 6.851 .000 91.387 113.868 1.636 0.143 .000 1.352 1.919 6 Constant AS 0.883 52.146 5.039 4.407 .000 42.189 62.103 0.747 0.033 .000 0.682 0.811 Table 5 Height estimation models developed in cases where the sex is known b Models Pearsons correlation (r) Unstandardized Coefficients B Std.Error Std. Error of the Estimate Sig. %95 Confidence Interval Alt sınır Üst sınır Males 1 0.799 Consant 63.486 10.945 3.88586 .000 41.668 85.304 LAL 1.492 0.140 .000 1.213 1.771 SW 0.500 0.182 .008 0.137 0.863 2 0.775 Constant 82.813 8.742 4.05581 .000 65.392 100.235 LAL 1.522 0.145 .000 1.232 1.812 3 0.752 Constant 84.395 9.225 4.22806 .000 66.009 102.782 RAL 1.489 0.153 .000 1.185 1.794 4 0.255 Constant 146.511 12.279 6.19993 .000 122.038 170.984 SW 0.653 0.290 .027 0.076 1.231 5 0.795 Constant 56.617 10.521 3.89341 .000 35.648 77.585 AS 0.723 0.065 .000 0.594 0.852 Females 1 0.664 Consant 79.751 10.614 4.57984 .000 58.597 100.905 LAL 1.483 0.195 .000 1.093 1.872 2 0.652 Constant 82.519 10.574 4.64206 .000 61.446 103.592 RAL 1.420 0.193 .000 1.036 1.805 3 0.350 Constant 133.000 8.551 5.73835 .000 115.959 150.042 SW 0.742 0.233 .002 0.278 1.207 4 0.652 Constant 78.993 11.069 4.64494 .000 56.934 101.053 AS 0.558 0.076 .000 0.406 0.709 Table 6 Comparison of Similar Studies Conducted in Different Populations c Authors Population n Arm Length Shoulder width Stature Formula Mean SD Mean SD Shah et. al ( 43 ) Indian (Muslim group of Gujarat) M: 64 F: 16 77.00 4.516 8.4 4.4389 31.722 + 1.664 (AL) ± 6.6587 119.362 + 1.068 (SW) ± 8.8780 Shah et. al ( 43 ) Indian (Hindu group) M: 64 F: 16 78.00 4.567 9.2 2.4790 36.310 + 1.586 (AL) ± 4.5405 59.475 + 2.565 (SW) ± 5.7302 Tripti Shakya et. al ( 33 ) Nepalese population M: 75 F: 75 R: 39.54 L: 38.76 R:3.130 L:2.991 - - 2.051 (RUAL) + 52.853 0.707 (LUAL) + 52.853 M. Akhlaghi et al. ( 45 ) Iranian population M: 50 F: 50 34.9 2.5 - - M: 1.886 (UAL) + 107.334 F: 1.911 (UAL) + 98.099 Navid et al. ( 42 ) Iranian population M: 50 F: 50 M: 33.72 F: 30.12 M:2.30 F:2.29 - - 91.641 + 2.509 (UAL) ± 7.16 Airan et al. ( 46 ) Indian population M: 201 F: 199 R: 30.56 L: 30.44 R:2.07 L:2.07 - - M: 2.37 x (RUAL) + 92.95 ± 4.46 M: 2.39 x (LUAL) + 92.76 ± 4.52 F: 2.44 x (RUAL) + 82.88 ± 3.98 F: 2.36 x (LUAL) + 85.44 ± 4.06 N. Yeasmin et al. ( 47 ) Bangladeshi adult populations M: 150 F: 150 - - 39.76 3.609 95.20 + 1.564 (SW) ± 7.175 O. Celbis et al. ( 49 ) Turkish population M: 80 F: 47 RL M: 45 RL F: 217 UL M: 264 UL F: 236 RL M:11.5 RL F:11.9 UL M:12.3 UL F:12.0 - - M: 3.367 (RL) + 872.286 ± 47 M: 3.054 (UL) + 890.603 ± 48 F: 4.731 (RL) + 539.893 ± 35 F: 4.217 (UL) + 573.174 ± 43 D. Howley et al. ( 51 ) Australian population M: 35 F: 61 L: 25.17 R: 25.25 L: 1.859 R:1.868 - - 65.281 + 4.131 (LFAL) ± 4.028 65.282 + 4.1117 (RFAL) ± 4.008 Present work Turkish population M: 75 F: 75 R: 57.46 L: 57.12 R:4.105 L:4.153 39.45 3.912 55.44 + 1.94 (RAL) ± 4.90 55.79 + 1.95 (LAL) ± 4.70 102.63 + 1.64 (SW) ± 6.85 3.2. Sex estimation Measurement values taken for sex determination were evaluated with Spearman Correlation Analysis and are given in Table 7 . Table 7 Correlation of Measurements with Gender (Sperman) N Correlations with Gender Left Arm Length 150 0.729; p:0.000 Right Arm Length 150 0.710; p:0.000 Shoulder Width 150 0.758; p:0.000 Variances were homogeneous in terms of bilateral arm length and shoulder width measurements according to sex, and a statistically significant difference was found between the mean lengths (Independent t test, p:0.000). Sex estimation formulas obtained by Binary Logistic Regression Analysis from the measurements taken are given in Table 8 . Table 8 Sex estimation formulas d Formulas LAL + SW 49,042 + (LAL x -0.442 + SW x -0.600) RAL + SW 47,665 + (RAL x -0.408 + SW x -0.608) LAL 38,186 + (LAL x -0.669) RAL 36,733 + (RAL x -0.639) SW 33,157 + (SW x -0.839) The result of applying the formula for each measurement was as such: male if less than 0.5, and female if greater than 0.5. The percentages of correct prediction of sex by sex prediction formulas were determined and are given in Table 9 . Table 9 The accuracy values of gender prediction formulas in correctly predicting gender e The Percentages and Numbers of Correct Prediction Males (n:75) Females (n:75) Total Number of Individuals (n:150) n % n % n % LAL + SW 68 90.7 66 88.0 134 89.3 RAL + SW 67 89.3 64 85.3 131 87.3 LAL 65 86.7 65 86.7 130 86.7 RAL 67 89.3 59 78.7 126 84.0 SW 63 84.0 65 86.7 128 85.3 With the formula obtained from the right arm length, sex could be determined accurately at a rate of 84%; 59 of 75 females and 67 of 75 males were estimated correctly. With the formula obtained from the left arm length, sex could be determined correctly with a rate of 86.7%; 65 of 75 females and 65 of 75 males were estimated correctly. With the formula obtained from shoulder width, sex could be determined accurately at a rate of 85.3%; 65 of 75 females and 63 of 75 males were estimated correctly. The comparison of arm length, shoulder width measurements and standard deviations in similar studies conducted in different populations for sex determination, and the ratios of the formulas to accurately predict sex are given in Table 10 . Table 10 Comparison of gender prediction studies conducted in different populations f, g Authors Population n Arm Length Shoulder width Gender Formula % Accuracy Mean SD Mean SD Moore & Digangi ( 48 ) Colombian M: 84 F: 50 M; UAL:31.74 F; UAL:28.77 M:18 F:20.53 M:10.37 F:9.26 M:7.74 F:4.64 -20.8545 + 0.072(SH) + 0.106(SB) g 93.5 Shah et. Al ( 43 ) Indian (Muslim group of Gujarat) M: 64 F: 16 77.00 4.516 8.4 4.44 -9.552 + 0.290(SW) g -29.978 + 0.417(AL) g 78.8 86.3 Shah et. Al ( 43 ) Indian (Hindu group) M: 64 F: 16 78.00 4.567 9.2 2.48 -72.655 + 1.953(SW) g -34.232 + 0.469(AL) g 93.8 83.8 N. Yeasmin et al. ( 47 ) Bangladeshi adult population M: 150 F: 150 - - 39.76 3.61 −20.657 + 0.522(SW) g 78.6 D. Howley et al. ( 51 ) Australian population M: 35 F: 61 LFAL: 25.17 RFAL: 25.25 L: 1.859 R:1.868 - - - L: 86.3 R: 86.0 G. Mall et al. ( 50 ) German population M: 64 F: 79 M; UAL: 33.4 F; UAL: 30.7 M:1.58 F:1.59 - - 0.196 (UAL) + 1.962 (HHD) + 1.160 (HEW) -22.608 ≤0.30: female 93.15 Present work Turkish population M: 75 F: 75 R: 57.46 L: 57.12 R: 4.105 L: 4.153 39.45 3.912 38,186 + (L AL x -0.669) 36,733 + (R AL x -0.639) 33,157 + (SW x -0.839) 86.7 84.0 85.3 4. DISCUSSION Sex and height estimation is an essential part of identification. Identification process is necessary not only for the suspect, but also for the victim. In criminal cases, anthropometric measurements are used to determine the height and sex of the remains or body parts that are unrecognizably decomposed or dismembered. Especially in mass disasters, studies to determine sex and height within the framework of standards specific to previously established societies gain importance. In studies on the subject, it is emphasized that the results obtained are specific to the region and historical period ( 5 – 10 , 12 – 32 ). The determination and evaluation of all biological profile elements used in identification varies depending on sex. Therefore, correct identification of sex is the most important and first stage in identification ( 22 ). DNA analyses that give definitive results in sex determination are costly and take a long time to get results. Especially in cases where mass deaths occur, it is requested that the incident be clarified quickly so that the delivery process of the deceased to their relatives is not prolonged. Therefore, more practical, low-cost and reliable sex determination methods are needed. In the past centuries, many researchers conducted studies on estimating height and sex in different populations using various anthropometric measurements for identification. In some of these studies, the correlation of arm span and arm length with height was also emphasized ( 33 – 36 ). Anthropological studies for identification give results specific to the society and the time period in which the study is conducted. Researchers have suggested recalculating the estimation formulas at appropriate time intervals ( 13 – 15 , 37 – 39 ). The ages of 150 volunteering adult participants, 75 of whom were males and the remaining 75 females, were between the ages of 20–57 years. Therefore, the study reflects the anthropological measurements of 1965 and later. When the birthplace regions of the participants were examined, it was seen that there were participants from every region, and it was understood that they were mostly from the Aegean Region. Considering that besides the place of birth of the individuals, the geographical region and environment they are in during the developmental age may be more important, and the regions they were in during the period when their bone development was completed were also evaluated, and it was seen that the majority were from the Aegean Region. When the descriptive statistics of all measurements made in females and males were examined, it was determined that all measurements were higher in males than in females (Table 1 ). It was found that all measurements taken in the study showed a significant correlation with height (p < 0.05). In line with this information, it was determined that it is appropriate to evaluate all measurements in terms of identification (Table 2 ). The reason why the correlation coefficients with height and correlation coefficients of the measurements in cases where the sex is not known are higher than the correlation coefficients according to sex is considered to be due to higher standard deviation and therefore, wider estimation interval. In arm length measurements, a significant difference was found between the measurements of the right and left sides (p < 0.05), and the correlation coefficient between the measurements of the left side and the height was found to be higher than the right. As a result, it was considered that it would be appropriate to use only the left side measurements in the estimation of height if the measurement results of both sides are available. In a study investigating the relationship between arm span, arm length and tibia length with height in 416 people aged 15–18 in Ethiopia, arm span was taken as the sum of the measurements starting from the longest fingertip of one side to the hand, the arm, shoulder width and the other side to the distal arm, hand, longest finger, and it was shown that the correlation of arm span measurements with height was quite high. Correlation values have been shown to be R = 0.843 in males, R = 0.708 in females for arm span measurement, R = 0.806 in males, R = 0.635 in females for arm length, R = 0.738 in males and R = 0.611 in females for tibia length. It has been stated that the mean arm span measurement was 5.8 cm higher than the mean height ( 34 ). In other anthropological studies, it has been found that the mean arm span measurement was 8.3 cm higher in the black race and 3.3 cm higher in the white race than the average height ( 35 , 36 ). In this study, arm span measurements were not measured separately, and this measurement value was obtained from the sum of arm lengths of both sides and shoulder width measurements taken from the participants. When arm span measurements were evaluated, it was found that there was a strong correlation with height (R = 0.883), R = 0.795 in males and R = 0.652 in females, and the mean of height measurements was 12.23 cm higher than the mean of arm span measurement. The reason for the higher difference in arm span measurement from other studies was thought to be due to the difference in measurement points. In this study, hand and finger length were not included in arm span measurement. The correlation between arm length of both sides and height was higher in males than in females. Similar results have been shown in other studies ( 33 , 40 , 41 ). This is because males are thought to complete puberty an average of 2 years later than females, thus having additional time for bone development compared to females. In the study by Navid et al. ( 42 ), it has been shown that there was a correlation between upper arm length and height in all participants, and the correlation of upper arm length with height was significant in male cases, but no significant correlation was found in female cases. Although the correlation between shoulder width and height was strong (R = 0.684), it was found that both sides had a lower correlation than arm length measurements; however, there was a strong and statistically significant correlation between shoulder width and arm length measurements. In the study of Shakya et al. ( 33 ) with 150 people in Nepal, it has been established that there was a strong correlation between arm length and height, right arm length had a stronger correlation with height (R = 0.911), and left arm length (R = 0.895) in males and right arm length (R = 0.779) in females had higher correlation with height, and when R² values were examined, it was shown that height could be determined 80.1% from left arm length in males and 60.6% from right arm length in females. In a study conducted in India, Muslim and Hindu groups have been evaluated separately, and it has been found that the correlation of arm length with height was higher than shoulder width in both groups. Correlation with height in the Muslim group has been detected as R = 0.751 for arm length, R² value 56.4%, R = 0.473 for shoulder width, R² value 22.4%, and in the Hindu group, it has been found as R = 0.849 for arm length, R² value 72.1% for shoulder width, R = 0.745 for shoulder width, R² value 55.5% ( 43 ). “R value” is the correlation coefficient. “R² value” expresses how much of the change in the dependent variable (height) can be explained by the independent variables (measurements taken) so that the estimated height can be calculated in the study group. Therefore, "R² value" is a statistical measure of how well the regression estimates converge to the actual data points. When multiple regression analysis was applied in the measurements taken in the study, it was observed that the correlation between the height of the model in which left arm length and shoulder width were used together was the highest (R = 0.887). According to the R² value, it was observed that the model in which left arm length and shoulder width measurements were used could explain the heights of 78.4% (SEE:4.348) of all individuals in the study group from which 150 individuals were taken as a sample. The standard error of estimation (SEE) is a good parameter to evaluate the accuracy of linear regression equations. Since the standard estimation error was relatively low in the model obtained, it was considered appropriate to use it in estimating height. The models created in the regression analysis made from the measurements taken in the study are given in Table 4 . Although the height estimation models for each variable/measurement are included in the table, when arm length of both sides and shoulder width measurements are available, it was considered appropriate to use the 1st model in which left arm length and shoulder width measurements were taken since both the correlation is strong and it would be more practical to use unilateral measurements in practice, In multiple regression analysis (Table 5 ) performed for the cases where the sex is known, 5 models were created for males and 4 models for females. According to the 1st model with the strongest correlation in males, it was considered appropriate to use the formula created from the left arm length and shoulder width, and the formula created in the 1st model in which the left arm length was used for females. It was observed that a meaningful model could not be developed by using the left arm length and shoulder width together in females. In similar studies conducted in different populations for the determination of height (Table 6 ), it has been stated that the differences between the studied groups are affected by factors such as the historical period of the population in which the measurement is made, genetic factors, geographical region, social origin of the population, the total number of individuals measured and the way the measurements are made ( 33 , 42 , 43 , 45 , 46 , 47 , 49 , 51 ). Measurement values taken for sex determination were evaluated with Spearman Correlation Analysis, and it was seen that the measurement with the strongest correlation was shoulder width (R = 0.758), and the correlation of left arm length was stronger than the right (Table 7 ). When sex estimation formulas (Table 8 ) obtained by Binary Logistic Regression Analysis from the measurements taken were applied, the model that used the left arm length and shoulder width was the one with the highest rate of correctly predicting sex in all participants with 89.3%. In estimation formulas using a single measurement, it was evaluated that sex estimation made from the left arm length measurement was able to accurately determine sex in 86.7% of all participants (Table 9 ). In the study conducted by Duyar and Tacar, it has been determined that sex could be determined with an accuracy rate of 64.7%-86.5% from shoulder and hip width measurements ( 44 ). In a study conducted with 160 people in India, the measurement of shoulder width was 78.8% and arm length was 86.3% in the Guajarat Muslim group. In the Hindu group, it was shown that 93.8% of the shoulder width and 83.8% of the arm length could detect sex correctly, and it was emphasized that the results would be different according to the population in which the study was conducted ( 43 ). Similar studies have been conducted using upper extremity length and shoulder width measurements in different populations for sex determination (Table 10 ). It has been determined that the rate of correct determination of sex is higher in formulas developed using more than one measurement location ( 48 , 50 ). 5. CONCLUSION New technological developments such as DNA studies, facial reconstruction, and radiological examinations are used in the identification of unknown remains in forensic medical practices. However, in mass disasters such as natural disasters, transportation accidents, war, terror and bomb attacks, metric and morphological studies gain importance for identification of fragmented or disintegrated corpses. The database, which consists of the measures that emerged as a result of the study, is capable of supporting different Forensic Medicine studies in the long run. It is thought that the findings obtained from arm length and shoulder width measurements and regression formulas will contribute to the application in crime scene investigations, can be used in determining height and sex, thus contributing to the identification process. ABBREVIATIONS AL, Arm Length AS, Arm Span DNA, Deoxyribonucleic acid HEW, Humerus Epicondylar Width HHD, Humerus Head Diameter LAL, Left Arm Length LFAL, Left Forearm Length LUAL, Left Upper Arm Length RAL, Right Arm Length RFAL, Right Forearm Length RL, Radial Length RUAL, Right Upper Arm Length SB, Scapula Breadth SD, Standard Deviation SEE, Standard Error of the Estimate SH, Scapula Height SPSS, Statistical Package for the Social Sciences SW, Shoulder Width UAL, Upper Arm Length UL, Ulnar Length Declarations Ethics approval and consent to participate Ethical approval for this study was obtained from the Muğla Sıtkı Koçman University Human Research Ethics Committee (Protocol No: 200008; Decision No: 37; dated 13 March 2020). Written informed consent was obtained from all participants prior to enrollment. The study was conducted in accordance with the principles of the Declaration of Helsinki and the provisions of the Turkish Personal Data Protection Law (Law No. 6698). Consent for publication Not applicable. No identifiable individual-level data are presented in this manuscript. Funding Not applicable. Author Contribution Conducting the literature review and project preparation: MEÖ, YB, BES ; Supervision: YB, BES ; Materials: MEÖ ; Data Collection and Processing: MEÖ, BY; Transferring the data to a statistical program and conducting statistical analysis: MEÖ, YB; Literature Search and Interpretation and discussion of the findings, and manuscript writing: MEÖ, YB, UUG. Data Availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Due to ethical and privacy considerations, the data are not publicly available. References Açıkgöz N, Hancı İH (2002) Adli Biyoloji. Adli Tıp ve Adli Bilimler. İç: Hancı İH, editör. Ankara: Seçkin Yayıncılık San ve Tic AŞ; s.577–598 Açıkgöz N, Hancı İH (2002) Adli Hemogenetik. Adli Tıp ve Adli Bilimler. İç: Hancı İH, editör. Ankara: Seçkin Yayıncılık San ve Tic AŞ; s.598–613 Açıkgöz N, Hancı İH (2002) Adli Mikrobiyoloji. Adli Tıp ve Adli Bilimler. İç: Hancı İH, editör. Seçkin Yayıncılık San ve Tic AŞ, Ankara. s.613 Açıkgöz N, Hancı İH (2002) Kılların Adli Tıptaki Önemi. Adli Tıp ve Adli Bilimler. İç: Hancı İH, editör. Seçkin Yayıncılık San ve Tic AŞ, Ankara. .s.617 – 30 Sanlı SG, Kızılkanat ED, Boyan N, Özşahin ET et al (2005) Stature estimation based on hand lenght and foot lenght. Clin Anat 18(8):589–596 Abdel-Malek AK, Ahmed AM, Saharkawi SA, Hamid NM (1990) Prediction of stature from hand measurements. Forensic Sci Int 46(3):181–187 Jasuja OP, Singh G (2004) Estimation of stature from hand and phalange lenght. JIAFM 26(3):ISSN0971–0973 Saxena SK (1984) A study of correlation and estimation of stature from hand lenght, hand breadth and sole lenght. Anthrop Anz 42(4):271–276 Cheng JC, Leung SS, Chiu BS, Tse PW et al (1998) Can we predict body height from segmental bone length measurements? A study of 3647 children. J Pediatr Orthop 18(3):387–393 İris M, Celbis O (2003) Türk toplumunda humerus uzunluğundan boy tahmini. Adli Bilimler Dergisi 2(4):9–15 Boldsen JL (1990) Body Proportions, population structure and height prediction. Adli Tıp Dergisi 6:157–165 Gordon CC, Buikstra JE (1992) Linear models for the prediction of stature from foot and boot dimensions. J Forensic Sci 37(3):771–782 Jasuja OP, Singh J, Jain M (1991) Estimation of stature from foot and shoe measurements by multiplication factors: a revised attempt. Forensic Sci Int 50(2):203–215 Ashizawa K, Kumakura C, Kusumoto A, Narasaki S (1997) Relative foot size and shape to general body size in Javanese, Filipinas and Japanese with special reference to habitual footwear types. Ann Hum Biol 24(2):117–129 Robbins LM (1986) Estimating height and weight from size of footprints. J Forensic Sci 31(1):143–152 Tomassoni D, Traini E, Amenta F (2014) Gender and age related differences in foot morphology. Maturitas 79(4):421–427 Fessler DMT, Haley KJ, Lal RD (2005) Sexuel dimorphism in foot lenght proportionate to stature. Ann Hum Biol 32(1):44–59 Sahni D, Sanjeev, Sharma P, Harjeet et al (2010) Estimation of stature from facial measurements in northwest indians. Leg Med 12:23–27 Agnihorti KA, Kachhwaha S, Googoolye K, Allock A (2011) Estimation of stature from cephalo-facial dimensions by regression analysis in indo-maurition population. J Forensic Leg Med 18:167–172 Giles E, Vallandigham PH (1991) Height estimation from foot and shoeprint lenght. J Forensic Sci 36(4):1134–1151 Narles VL, Miller JS (2004) Making tracks: the forensic analysis of footprints and footwear impressions. Anat Record (Part B:New Anat) 279B:9–15 Zeybek FG (2011) Ayak antropometrik ölçümlerinin cinsiyet tespiti ve boy tahmini açısından değerlendirilmesi. Doctoral Dissertation. DEÜ Sağlık Bilimleri Enstitüsü, İzmir Wunderlich RE, Cavanagh PR (2001) Gender differences in adult foot shape:implication for shoe desing. Med Sci Sports Exerc 33(4):605–611 Rich J, Dean DE, Cheung YY (2003) Forensic implications of the foot anda ankle. J Foot Ankle Surg 42(4):221–225 Jasuja OP, Harbhajan S, Anupama K (1997) Estimation of stature from stride length while walking fast. Forensic Sci Int 86:181–186 Thomas JL, Kunkel MW, Lopez R, Sparks D (2006) Radiographic values of the adult foot in a standardized population. J Foot Ankle Surg 45(1):3–12 Dogan A, Uslu M, Aydınoğlu A, Harman M et al (2007) Morphometric study of the human metatarsals and phalanges. Clin Anat 20(2):209–214 Jasuja OP, Manjula (1993) Estimation of stature from footstep lenght. Forensic Sci Int 61(1):1–5 Singh TS, Phookan MN (1993) Stature and footsize in four thai communties of assam, india. Anthrop Anz 51(4):349–355 Krishan K, Sharma A (2007) Estimation of stature from dimension of hand and feet in north indian population. J Forensic Leg Med 14(6):327–332 Agnihotri AK, Purwar B, Googoolye K, Agnihotri S et al (2007) Estimation of stature by foot lenght. J Forensic Leg Med 14(5):279–283 Vernon W (2006) The development and practice of forensic podiatry. J Clin Forensic Med 13:284–287 Shakya T, Mishr D, Pandey P (2021) Estimation of Stature from Upper Arm Length. Int J Health Sci Res 11(5):23–29 Mulu A, Sisay B (2021) Estimation of Stature from Arm Span, Arm Length and Tibial Length among Adolescents of Aged 15–18 in Addis Ababa Ethiopia. Ethiop J Health Sci. ;31(5) Mohanty SP, Babu SS, Nair NS (2001) The use of arm span as a predictor of height: A study of South Indian women. J Orthop Surg 9(1):19–23 Steele MF, Chenier TC (1990 Nov-Dec) Arm-span, height, and age in black and white women. Ann Hum Biol 17(6):533–541 Giles E, Vallandigham PH (1991) Height Estimation From Foot And Shoeprint Length. J Forensic Sci 36(4):1134–1151 Singh TS, Phookan MN (1993) Stature and footsize in four Thai communities of Assam, India. Anthropol Anz. :349–355 Qamra SR, Deodhar SD, Jit I (1986) A metric study feet of north-west Indians and its relationship to body height and weight. Int J Physiol Anthropol Hum Gen 12:131–138 Nandi ME, Olabiyi OA, Ibeabuchi NM, Okubike EA, Iheaza EC (2018) Stature Reconstruction from Percutaneous Anthropometry of Long Bones of Upper Extremity of Nigerians in the University of Lagos. Arab J Forensic Sci Forensic Med 1(7):869–880 Arif M, Rasool SH, Chaudhary MK, Shakeel Z (2018) Estimation of stature; upper arm length a reliable predictor of stature. Prof Med J 25(11):1696–1700 Navid S, Mokhtari T, Alizamir T, Arabkheradmand A, Hassanzadeh G (2014) Determination of Stature from Upper Arm Length in Medical Students. Anat Sci 11(3):135–140 Shah T, Patel M, Nath S, Menon SK (2015) A model for construction of height and sex from shoulder width, arm length and foot length by regression method. J Forensic Sci Criminol 3(1):102 Duyar İ, Tacar O (1998) Antropometrik boyutlarda gözlenen cinsiyet farklılıklarının diskriminant analizi kullanılarak incelenmesi. Morfoloji Dergisi 6(1):10–14 Akhlaghi M, Hajibeygi M, Zamani N, Moradi B (2012) Estimation of stature from upper limb anthropometry in Iranian population. J Forensic Leg Med 19(5):280–284 Airan N, Dwivedi AK, Das AR, Mishra SK (2016) Estimation of stature from length of arm in adult population of Garhwal region of Uttarakhand, India. Int J Biomedical Res 7(12):842–846 Yeasmin N, Asadujjaman M, Islam MR, Hasan MR (2022) Stature and sex estimation from shoulder breadth, shoulder height, popliteal height, and knee height measurements in a Bangladeshi population. Forensic Sci International: Rep 5:100258 Moore MK, DiGangi EA, Ruíz FPN, Davila OJH, Medina CS (2016) Metric sex estimation from the postcranial skeleton for the Colombian population. Forensic Sci Int 262:286–e1 Celbis O, Agritmas H (2006) Estimation of stature and determination of sex from radial and ulnar lengths in a Turkish corpse sample. Forensic Sci Int 158(2–3):135–139 Mall G, Hubig M, Büttner A, Kuznik J, Penning R, Graw M (2001) Sex determination and estimation of stature from the long bones of the arm. Forensic Sci Int 117:23–30 Howley D, Howley P, Oxenham MF (2018) Estimation of sex and stature using anthropometry of the upper extremity in an Australian population. Forensic Sci Int 287:220e1–220e10 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8642816","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585261731,"identity":"c3f051c2-caef-48d1-ac00-410fb2942f5e","order_by":0,"name":"Muazzez Elçin Özkan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIie3RsQrCMBCA4ZSDcwl2bVHfodDFyeKjSNcOgpMIKnTo6OpLuN6sBHTpAxQ6aO0LKCLoZiLasekomH84MvSjF8KYyfSLtRjbsq2jjtZJDt7WEqgIgKcINiEKqRO+/6UlNkAhxml/tElW++k9GnSRQXHOaogboyfWmTOiVGDeo1Auhr4f1RBPcCb4RZIsxNwlkIRjp44EFTmWOHFpoSceKKIWywCtKwk9cYS8C08dn9LQ71h04Aiau9hJXN74ft6jw664PmkW2K24KOvIt+FSDrkk+7xUgwI1rEfDr00mk+m/egGTa0cbLWTgXQAAAABJRU5ErkJggg==","orcid":"","institution":"Ministry of Health Cigli Education and Research Hospital","correspondingAuthor":true,"prefix":"","firstName":"Muazzez","middleName":"Elçin","lastName":"Özkan","suffix":""},{"id":585261733,"identity":"253f22c1-b944-4106-a6ad-d25022bcf153","order_by":1,"name":"Yasemin Balcı","email":"","orcid":"","institution":"Mugla Sıtkı Kocman University","correspondingAuthor":false,"prefix":"","firstName":"Yasemin","middleName":"","lastName":"Balcı","suffix":""},{"id":585261736,"identity":"ab6d25ec-3173-42f7-a3b1-897b9c90a992","order_by":2,"name":"Ümit Ünüvar Göçeoğlu","email":"","orcid":"","institution":"Mugla Sıtkı Kocman University","correspondingAuthor":false,"prefix":"","firstName":"Ümit","middleName":"Ünüvar","lastName":"Göçeoğlu","suffix":""},{"id":585261740,"identity":"a562c692-f9b7-4094-b759-2416235d6da6","order_by":3,"name":"Barış Ethem Süzek","email":"","orcid":"","institution":"Mugla Sıtkı Kocman University","correspondingAuthor":false,"prefix":"","firstName":"Barış","middleName":"Ethem","lastName":"Süzek","suffix":""},{"id":585261742,"identity":"f6991d63-9c6e-4f34-ae1f-cec736c63047","order_by":4,"name":"Betül Yürürdurmaz","email":"","orcid":"","institution":"Elazıg Fethi Sekin City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Betül","middleName":"","lastName":"Yürürdurmaz","suffix":""}],"badges":[],"createdAt":"2026-01-19 20:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8642816/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8642816/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104399722,"identity":"ac36d706-9ba0-4079-82bf-010f47a21d51","added_by":"auto","created_at":"2026-03-11 12:07:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1197701,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8642816/v1/0a8e9c20-b080-4c77-918c-d9ab2b53d5c7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEstimating Height and Sex from Shoulder Width and Arm Length\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eApart from criminal deaths in which the remains are dismembered, burned, or have become impossible to identify postmortem, the remains are generally not in one piece in events where mass deaths occur like in natural disasters such as plane, sea, train accidents, earthquake, tsunami, fire events in crowded buildings, and mass graves after wars (\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Determination of sex and height in dismembered remains is the basic and most important part of identification (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Making an estimation of sex and height by anthropometric measurements made from unidentified body parts and revealing morphological features are parts of identification. DNA analyses that give definitive results in sex determination are very costly and take a long time to get results. In situations encountered in the ordinary course of life, more practical, low-cost, reliable sex determination methods are needed.\u003c/p\u003e \u003cp\u003eStudies have been carried out using the length of hand and arm for identification on mutilated and unidentified remains (\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Since the measurement results to be obtained from anthropometric measurements are affected by factors such as the historical period and geographical region of the population where the measurement is made, the social origin of the population, the total number of individuals measured and the way the measurements are made, the measurements need to be restructured and reformulated in accordance with the era. The measurement values of different societies belonging to the same historical period may differ. Again, the anthropometric values of a society in different historical periods may vary (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, it was aimed to create formulas for estimating height and sex from shoulder width and arm length. It is assumed that the study will contribute to the creation of a database specific to the Turkish society in the Aegean Region of T\u0026uuml;rkiye.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cp\u003e Ethics Committee Approval dated 13.03.2020 and numbered 37 of Muğla Sıtkı Ko\u0026ccedil;man University Human Research Ethics Committee was received for the research.\u003c/p\u003e \u003cp\u003eIn the research, a tape measure, electronic height and weight scale, data collection forms, and informed consent forms were used. The study was carried out in the laboratory room of Muğla Sıtkı Ko\u0026ccedil;man University Faculty of Medicine, Department of Forensic Medicine.\u003c/p\u003e \u003cp\u003eIn the study, the number of samples was determined in the 85\u0026ndash;95% confidence interval based on the population of Muğla province, which constitutes the population, with equal sex distribution. The sample size was calculated using the 'Sample Size Calculator' program. According to the calculation, it was determined that 150 participants would be sufficient.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eInformed consent\u003c/strong\u003e \u003cp\u003ewas obtained from 150 participants who agreed to participate in the study on a voluntary basis. Those with congenital or acquired problems that would make it difficult to make healthy measurements on their shoulders and arms were not included in the study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e Written informed consent was obtained from all participants prior to enrollment. Each volunteer was individually informed about the purpose and procedures of the study, the voluntary nature of participation, and the right to withdraw at any time without any consequences. Ethical approval for this study was obtained from the Muğla Sıtkı Ko\u0026ccedil;man University Human Research Ethics Committee (Protocol No: 200008; Decision No: 37; dated 13 March 2020). The study was conducted in accordance with the principles of the Declaration of Helsinki and the provisions of the Turkish Personal Data Protection Law (Law No. 6698).\u003c/p\u003e \u003cp\u003eParticipants' age, sex, place of birth, place of residence for the longest time, measured height, weight, both arm length and shoulder width measurements were recorded in a data collection form.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Measurements\u003c/h2\u003e \u003cp\u003eBy means of a tape measure, the distance from the acromion protrusion to the processus styloideus radii on the wrist was measured for arm length measurement, and for shoulder width measurement, the distance between the acromion protrusion on both sides was taken. The arm span measurement included in the study was not taken separately from the participants during the measurement; it was obtained by summing the two sides arm length and shoulder width measurements taken from the participants. The arm span measurement is also referred to as the stroke length measurement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Statistical analyses\u003c/h2\u003e \u003cp\u003eDependent variables of the study were height and sex; independent variables were shoulder width and arm lengths. Correlation and regression analyses were performed by evaluating all the data obtained through SPSS statistical program.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Stature estimation\u003c/h2\u003e \u003cp\u003eMeans and standard deviations of the measured values are presented. The paired samples t test was used to test whether there was a significant difference between the means of the right and left side measurements. The relation between the measurements taken and height was evaluated by Pearson Correlation Analysis. Formulas were created with Linear Regression Analysis in order to calculate the estimated height.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Sex estimation\u003c/h2\u003e \u003cp\u003eMeasurement values taken for sex determination were evaluated with Spearman Correlation Analysis. Sex estimation formulas were created with Logistic Regression Analysis.\u003c/p\u003e \u003cp\u003eKolmogorov Smirnov test was used in terms of whether each measurement was in normal distribution according to sex, Parametric Independent Sample T Test was used for those with normal distribution, and Nonparametric Mann-Whitney U Test was used for those without normal distribution. In variables in which the difference between the mean according as per sex was significant, sex estimation formulas were created according to the 0.5 cut-off value determined performing Binary Logistic Regression Analysis. The value obtained as a result of applying the formulas was evaluated as female if the cut-off value was greater than 0.5 and male if it was smaller.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eA total of 150 volunteers, 75 (50%) females and 75 (50%) males, were included in the study. Mean age of the participants was 26.3 years (SD: 5.8), with the youngest participant 20 years old and the oldest 57 years old. Although there were participants from every region, the birthplace of 45.3% of the participants was the Aegean region, and 18.0% of them were from the Mediterranean region. The regions where the participants lived the longest and completed their bone development were the Aegean region with 52.7% and the Mediterranean region with 17.3%. Minimum, maximum, mean values and 95% confidence interval of all measurements obtained from the participants are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of measurements obtained from participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eMALES\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eFEMALES\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%95 confidence interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%95 confidence interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight arm length(cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e60.25\u0026thinsp;\u0026plusmn;\u0026thinsp;3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.50\u0026ndash;68.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.51\u0026ndash;60.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e54.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e48.00\u0026ndash;60.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e54.03\u0026ndash;55.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft arm length(cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e59.99\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.50\u0026ndash;67.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.25\u0026ndash;60.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e54.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47.00-60.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.61\u0026ndash;54.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShoulder width(cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e42.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.50\u0026ndash;49.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.73\u0026ndash;42.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e36.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31.00-46.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35.95\u0026ndash;37.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen arm span measurements were evaluated, the mean was 162.55\u0026thinsp;\u0026plusmn;\u0026thinsp;7.00 in males and 145.51\u0026thinsp;\u0026plusmn;\u0026thinsp;7.11 in females, and it was seen that the mean of height measurements was 12.23 cm higher than the mean of arm span measurement. Bilateral arm lengths and shoulder widths were found to have a normal distribution in males and females with the applied normality test (Kolmogorov Smirnov; p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Stature estimation\u003c/h2\u003e \u003cp\u003eThe correlations between all lengths and heights obtained from the participants were evaluated and given in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of measured lengths with height\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasured lengths\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eCorrelation Coefficient (r)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGender unknown\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n:150)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n:75)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n:75)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eLeft\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLeft\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eRight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eLeft\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eArm length\u003c/p\u003e \u003cp\u003eSig.(2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.664\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eShoulder width\u003c/p\u003e \u003cp\u003eSig.(2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArm span\u003c/p\u003e \u003cp\u003eSig.(2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.883\u003c/p\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.795\u003c/p\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.652\u003c/p\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePaired samples t test was used to test whether there was a significant difference between the means of the right and left side measurements. As well as having detected a very strong correlation (r:.987, p:000) between right and left arm lengths, a statistically significant difference was also found between the measurement averages (n:150, t: 6.270, p: .000). It was observed that the measurement with the strongest correlation with height was the arm span measurement when the sex was known or unknown. The correlation coefficient between the arm length measurements on the left side and the height was higher than the right side. A strong and statistically significant correlation was found between shoulder width and right (r:.607, p:.000) and left (r:.612, p:.000) arm length. The correlations with height and R\u0026sup2; values of the models developed using all measurements are given in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModels developed using all measurements\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted R\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStd. Error of the Estimate (SEE)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Arm Length\u0026thinsp;+\u0026thinsp;Shoulder width\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Arm Length\u0026thinsp;+\u0026thinsp;Shoulder width\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.509\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Arm Length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Arm Length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShoulder width\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.851\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArm Span\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to the models created in the regression analysis of the study group, it was observed that the strongest correlation with height was the model in which left arm length and shoulder width measurements were used together (R\u0026thinsp;=\u0026thinsp;0.887) and 78.4% (SEE:4.348) of the changes in the height measurement of all individuals in the universe, in which 150 individuals were taken as a sample in the study group, could be explained by this model according to the corrected R\u0026sup2; value result.\u003c/p\u003e \u003cp\u003eHeight estimation formulas of the developed models are given in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. If the sex is unknown, height estimation formula in the 1st model with the strongest correlation is as Height\u0026thinsp;=\u0026thinsp;51.95+(1.61 x left arm length\u0026thinsp;+\u0026thinsp;0.589 x shoulder width) (SEE:4.35).\u003c/p\u003e \u003cp\u003eHeight estimation models developed in cases where the sex is known are given in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. In cases where the sex is known and according to the 1st model with the strongest correlation in males, the formula is as: Height\u0026thinsp;=\u0026thinsp;63.49+(1.49 x left arm length\u0026thinsp;+\u0026thinsp;0.50 x shoulder width) (SEE:3.89), and for women, it is as: Height\u0026thinsp;=\u0026thinsp;79.75+(1.48 x left arm length) (SEE:4.58).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the comparison of arm length and shoulder width measurements and their standard deviations in similar studies conducted in different populations for height estimation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModels developed using all measurements and height estimation formulas \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eModels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePearsons correlation (r)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStd. Error of the Estimate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e%95 Confidence Interval\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003cp\u003eLAL\u003c/p\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e61.766\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003cp\u003eRAL\u003c/p\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e61.895\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.804\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003cp\u003eLAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e66.283\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003cp\u003eRAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e66.581\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e113.868\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.919\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003cp\u003eAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e62.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.811\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHeight estimation models developed in cases where the sex is known \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearsons correlation (r)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e \u003cp\u003eB Std.Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStd. Error of the Estimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e%95 Confidence Interval\u003c/p\u003e \u003cp\u003eAlt sınır \u0026Uuml;st sınır\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e \u003cp\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConsant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e3.88586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e41.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e85.304\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.771\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82.813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.05581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e65.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e100.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.812\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.22806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e66.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e102.782\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.794\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e146.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6.19993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e122.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e170.984\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.89341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e35.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e77.585\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConsant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.57984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e58.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e100.905\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.872\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.64206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e61.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e103.592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e133.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5.73835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e115.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e150.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4.64494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e56.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e101.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Similar Studies Conducted in Different Populations \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eArm Length\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eShoulder width\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStature Formula\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShah et. al (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndian (Muslim group of Gujarat)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 64\u003c/p\u003e \u003cp\u003eF: 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.4389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.722\u0026thinsp;+\u0026thinsp;1.664 (AL)\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6587\u003c/p\u003e \u003cp\u003e119.362\u0026thinsp;+\u0026thinsp;1.068 (SW)\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8780\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShah et. al (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndian (Hindu group)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 64\u003c/p\u003e \u003cp\u003eF: 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.4790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36.310\u0026thinsp;+\u0026thinsp;1.586 (AL)\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5405\u003c/p\u003e \u003cp\u003e59.475\u0026thinsp;+\u0026thinsp;2.565 (SW)\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTripti Shakya et. al (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNepalese population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 75\u003c/p\u003e \u003cp\u003eF: 75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR: 39.54\u003c/p\u003e \u003cp\u003eL: 38.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR:3.130\u003c/p\u003e \u003cp\u003eL:2.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.051 (RUAL)\u0026thinsp;+\u0026thinsp;52.853\u003c/p\u003e \u003cp\u003e0.707 (LUAL)\u0026thinsp;+\u0026thinsp;52.853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM. Akhlaghi et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIranian population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 50\u003c/p\u003e \u003cp\u003eF: 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM: 1.886 (UAL)\u0026thinsp;+\u0026thinsp;107.334\u003c/p\u003e \u003cp\u003eF: 1.911 (UAL)\u0026thinsp;+\u0026thinsp;98.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNavid et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIranian population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 50\u003c/p\u003e \u003cp\u003eF: 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM: 33.72\u003c/p\u003e \u003cp\u003eF: 30.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM:2.30\u003c/p\u003e \u003cp\u003eF:2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91.641\u0026thinsp;+\u0026thinsp;2.509 (UAL)\u0026thinsp;\u0026plusmn;\u0026thinsp;7.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAiran et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndian population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 201\u003c/p\u003e \u003cp\u003eF: 199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR: 30.56\u003c/p\u003e \u003cp\u003eL: 30.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR:2.07\u003c/p\u003e \u003cp\u003eL:2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM: 2.37 x (RUAL)\u0026thinsp;+\u0026thinsp;92.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.46\u003c/p\u003e \u003cp\u003eM: 2.39 x (LUAL)\u0026thinsp;+\u0026thinsp;92.76\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003c/p\u003e \u003cp\u003eF: 2.44 x (RUAL)\u0026thinsp;+\u0026thinsp;82.88\u0026thinsp;\u0026plusmn;\u0026thinsp;3.98\u003c/p\u003e \u003cp\u003eF: 2.36 x (LUAL)\u0026thinsp;+\u0026thinsp;85.44\u0026thinsp;\u0026plusmn;\u0026thinsp;4.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN. Yeasmin et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBangladeshi adult populations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 150\u003c/p\u003e \u003cp\u003eF: 150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95.20\u0026thinsp;+\u0026thinsp;1.564 (SW)\u0026thinsp;\u0026plusmn;\u0026thinsp;7.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Celbis et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTurkish population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 80\u003c/p\u003e \u003cp\u003eF: 47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRL M: 45\u003c/p\u003e \u003cp\u003eRL F: 217\u003c/p\u003e \u003cp\u003eUL M: 264\u003c/p\u003e \u003cp\u003eUL F: 236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRL M:11.5\u003c/p\u003e \u003cp\u003eRL F:11.9\u003c/p\u003e \u003cp\u003eUL M:12.3\u003c/p\u003e \u003cp\u003eUL F:12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eM: 3.367 (RL)\u0026thinsp;+\u0026thinsp;872.286\u0026thinsp;\u0026plusmn;\u0026thinsp;47\u003c/p\u003e \u003cp\u003eM: 3.054 (UL)\u0026thinsp;+\u0026thinsp;890.603\u0026thinsp;\u0026plusmn;\u0026thinsp;48\u003c/p\u003e \u003cp\u003eF: 4.731 (RL)\u0026thinsp;+\u0026thinsp;539.893\u0026thinsp;\u0026plusmn;\u0026thinsp;35\u003c/p\u003e \u003cp\u003eF: 4.217 (UL)\u0026thinsp;+\u0026thinsp;573.174\u0026thinsp;\u0026plusmn;\u0026thinsp;43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD. Howley et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustralian population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 35\u003c/p\u003e \u003cp\u003eF: 61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eL: 25.17\u003c/p\u003e \u003cp\u003eR: 25.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eL: 1.859\u003c/p\u003e \u003cp\u003eR:1.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e65.281\u0026thinsp;+\u0026thinsp;4.131 (LFAL)\u0026thinsp;\u0026plusmn;\u0026thinsp;4.028 65.282\u0026thinsp;+\u0026thinsp;4.1117 (RFAL)\u0026thinsp;\u0026plusmn;\u0026thinsp;4.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent work\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTurkish population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 75\u003c/p\u003e \u003cp\u003eF: 75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR: 57.46\u003c/p\u003e \u003cp\u003eL: 57.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR:4.105\u003c/p\u003e \u003cp\u003eL:4.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55.44\u0026thinsp;+\u0026thinsp;1.94 (RAL)\u0026thinsp;\u0026plusmn;\u0026thinsp;4.90\u003c/p\u003e \u003cp\u003e55.79\u0026thinsp;+\u0026thinsp;1.95 (LAL)\u0026thinsp;\u0026plusmn;\u0026thinsp;4.70\u003c/p\u003e \u003cp\u003e102.63\u0026thinsp;+\u0026thinsp;1.64 (SW)\u0026thinsp;\u0026plusmn;\u0026thinsp;6.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Sex estimation\u003c/h2\u003e \u003cp\u003eMeasurement values taken for sex determination were evaluated with Spearman Correlation Analysis and are given in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of Measurements with Gender (Sperman)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorrelations with Gender\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft Arm Length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.729; p:0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight Arm Length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.710; p:0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShoulder Width\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.758; p:0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eVariances were homogeneous in terms of bilateral arm length and shoulder width measurements according to sex, and a statistically significant difference was found between the mean lengths (Independent t test, p:0.000).\u003c/p\u003e \u003cp\u003eSex estimation formulas obtained by Binary Logistic Regression Analysis from the measurements taken are given in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSex estimation formulas \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormulas\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAL\u0026thinsp;+\u0026thinsp;SW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49,042 + (LAL x -0.442\u0026thinsp;+\u0026thinsp;SW x -0.600)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAL\u0026thinsp;+\u0026thinsp;SW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47,665 + (RAL x -0.408\u0026thinsp;+\u0026thinsp;SW x -0.608)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38,186 + (LAL x -0.669)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36,733 + (RAL x -0.639)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33,157 + (SW x -0.839)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe result of applying the formula for each measurement was as such: male if less than 0.5, and female if greater than 0.5.\u003c/p\u003e \u003cp\u003eThe percentages of correct prediction of sex by sex prediction formulas were determined and are given in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe accuracy values of gender prediction formulas in correctly predicting gender \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eThe Percentages and Numbers of Correct Prediction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMales (n:75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eFemales (n:75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTotal Number of Individuals (n:150)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAL\u0026thinsp;+\u0026thinsp;SW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAL\u0026thinsp;+\u0026thinsp;SW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e87.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWith the formula obtained from the right arm length, sex could be determined accurately at a rate of 84%; 59 of 75 females and 67 of 75 males were estimated correctly. With the formula obtained from the left arm length, sex could be determined correctly with a rate of 86.7%; 65 of 75 females and 65 of 75 males were estimated correctly. With the formula obtained from shoulder width, sex could be determined accurately at a rate of 85.3%; 65 of 75 females and 63 of 75 males were estimated correctly.\u003c/p\u003e \u003cp\u003eThe comparison of arm length, shoulder width measurements and standard deviations in similar studies conducted in different populations for sex determination, and the ratios of the formulas to accurately predict sex are given in Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e10\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of gender prediction studies conducted in different populations \u003csup\u003ef, g\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eArm Length\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eShoulder width\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender Formula\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e% Accuracy\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoore \u0026amp; Digangi (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 84\u003c/p\u003e \u003cp\u003eF: 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM; UAL:31.74\u003c/p\u003e \u003cp\u003eF; UAL:28.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM:18 F:20.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eM:10.37 F:9.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eM:7.74 F:4.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-20.8545\u0026thinsp;+\u0026thinsp;0.072(SH)\u0026thinsp;+\u0026thinsp;0.106(SB)\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e93.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShah et. Al (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndian (Muslim group of Gujarat)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 64\u003c/p\u003e \u003cp\u003eF: 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-9.552\u0026thinsp;+\u0026thinsp;0.290(SW) \u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e-29.978\u0026thinsp;+\u0026thinsp;0.417(AL) \u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e78.8\u003c/p\u003e \u003cp\u003e86.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShah et. Al (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndian (Hindu group)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM: 64\u003c/p\u003e \u003cp\u003eF: 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-72.655\u0026thinsp;+\u0026thinsp;1.953(SW) \u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e-34.232\u0026thinsp;+\u0026thinsp;0.469(AL) \u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e93.8\u003c/p\u003e \u003cp\u003e83.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN. Yeasmin et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBangladeshi adult population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM:\u003c/p\u003e \u003cp\u003e150\u003c/p\u003e \u003cp\u003eF:\u003c/p\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026minus;20.657\u0026thinsp;+\u0026thinsp;0.522(SW) \u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e78.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD. Howley et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustralian population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM:\u003c/p\u003e \u003cp\u003e35\u003c/p\u003e \u003cp\u003eF:\u003c/p\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLFAL: 25.17\u003c/p\u003e \u003cp\u003eRFAL: 25.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eL: 1.859\u003c/p\u003e \u003cp\u003eR:1.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eL: 86.3\u003c/p\u003e \u003cp\u003eR: 86.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG. Mall et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGerman population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM:\u003c/p\u003e \u003cp\u003e64\u003c/p\u003e \u003cp\u003eF:\u003c/p\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM; UAL: 33.4\u003c/p\u003e \u003cp\u003eF; UAL: 30.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eM:1.58\u003c/p\u003e \u003cp\u003eF:1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.196 (UAL)\u0026thinsp;+\u0026thinsp;1.962 (HHD)\u0026thinsp;+\u0026thinsp;1.160 (HEW) -22.608\u003c/p\u003e \u003cp\u003e\u0026le;0.30: female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e93.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresent work\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTurkish population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM:\u003c/p\u003e \u003cp\u003e75\u003c/p\u003e \u003cp\u003eF:\u003c/p\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR: 57.46\u003c/p\u003e \u003cp\u003eL: 57.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR: 4.105\u003c/p\u003e \u003cp\u003eL: 4.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38,186 + (L AL x -0.669)\u003c/p\u003e \u003cp\u003e36,733 + (R AL x -0.639)\u003c/p\u003e \u003cp\u003e33,157 + (SW x -0.839)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e86.7\u003c/p\u003e \u003cp\u003e84.0\u003c/p\u003e \u003cp\u003e85.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"4. DISCUSSION","content":"\u003cp\u003eSex and height estimation is an essential part of identification. Identification process is necessary not only for the suspect, but also for the victim. In criminal cases, anthropometric measurements are used to determine the height and sex of the remains or body parts that are unrecognizably decomposed or dismembered. Especially in mass disasters, studies to determine sex and height within the framework of standards specific to previously established societies gain importance. In studies on the subject, it is emphasized that the results obtained are specific to the region and historical period (\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe determination and evaluation of all biological profile elements used in identification varies depending on sex. Therefore, correct identification of sex is the most important and first stage in identification (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). DNA analyses that give definitive results in sex determination are costly and take a long time to get results. Especially in cases where mass deaths occur, it is requested that the incident be clarified quickly so that the delivery process of the deceased to their relatives is not prolonged. Therefore, more practical, low-cost and reliable sex determination methods are needed.\u003c/p\u003e \u003cp\u003eIn the past centuries, many researchers conducted studies on estimating height and sex in different populations using various anthropometric measurements for identification. In some of these studies, the correlation of arm span and arm length with height was also emphasized (\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnthropological studies for identification give results specific to the society and the time period in which the study is conducted. Researchers have suggested recalculating the estimation formulas at appropriate time intervals (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). The ages of 150 volunteering adult participants, 75 of whom were males and the remaining 75 females, were between the ages of 20\u0026ndash;57 years. Therefore, the study reflects the anthropological measurements of 1965 and later.\u003c/p\u003e \u003cp\u003eWhen the birthplace regions of the participants were examined, it was seen that there were participants from every region, and it was understood that they were mostly from the Aegean Region. Considering that besides the place of birth of the individuals, the geographical region and environment they are in during the developmental age may be more important, and the regions they were in during the period when their bone development was completed were also evaluated, and it was seen that the majority were from the Aegean Region.\u003c/p\u003e \u003cp\u003eWhen the descriptive statistics of all measurements made in females and males were examined, it was determined that all measurements were higher in males than in females (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It was found that all measurements taken in the study showed a significant correlation with height (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In line with this information, it was determined that it is appropriate to evaluate all measurements in terms of identification (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The reason why the correlation coefficients with height and correlation coefficients of the measurements in cases where the sex is not known are higher than the correlation coefficients according to sex is considered to be due to higher standard deviation and therefore, wider estimation interval.\u003c/p\u003e \u003cp\u003eIn arm length measurements, a significant difference was found between the measurements of the right and left sides (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the correlation coefficient between the measurements of the left side and the height was found to be higher than the right. As a result, it was considered that it would be appropriate to use only the left side measurements in the estimation of height if the measurement results of both sides are available.\u003c/p\u003e \u003cp\u003eIn a study investigating the relationship between arm span, arm length and tibia length with height in 416 people aged 15\u0026ndash;18 in Ethiopia, arm span was taken as the sum of the measurements starting from the longest fingertip of one side to the hand, the arm, shoulder width and the other side to the distal arm, hand, longest finger, and it was shown that the correlation of arm span measurements with height was quite high. Correlation values have been shown to be R\u0026thinsp;=\u0026thinsp;0.843 in males, R\u0026thinsp;=\u0026thinsp;0.708 in females for arm span measurement, R\u0026thinsp;=\u0026thinsp;0.806 in males, R\u0026thinsp;=\u0026thinsp;0.635 in females for arm length, R\u0026thinsp;=\u0026thinsp;0.738 in males and R\u0026thinsp;=\u0026thinsp;0.611 in females for tibia length. It has been stated that the mean arm span measurement was 5.8 cm higher than the mean height (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In other anthropological studies, it has been found that the mean arm span measurement was 8.3 cm higher in the black race and 3.3 cm higher in the white race than the average height (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, arm span measurements were not measured separately, and this measurement value was obtained from the sum of arm lengths of both sides and shoulder width measurements taken from the participants. When arm span measurements were evaluated, it was found that there was a strong correlation with height (R\u0026thinsp;=\u0026thinsp;0.883), R\u0026thinsp;=\u0026thinsp;0.795 in males and R\u0026thinsp;=\u0026thinsp;0.652 in females, and the mean of height measurements was 12.23 cm higher than the mean of arm span measurement. The reason for the higher difference in arm span measurement from other studies was thought to be due to the difference in measurement points. In this study, hand and finger length were not included in arm span measurement.\u003c/p\u003e \u003cp\u003eThe correlation between arm length of both sides and height was higher in males than in females. Similar results have been shown in other studies (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). This is because males are thought to complete puberty an average of 2 years later than females, thus having additional time for bone development compared to females. In the study by Navid et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), it has been shown that there was a correlation between upper arm length and height in all participants, and the correlation of upper arm length with height was significant in male cases, but no significant correlation was found in female cases.\u003c/p\u003e \u003cp\u003eAlthough the correlation between shoulder width and height was strong (R\u0026thinsp;=\u0026thinsp;0.684), it was found that both sides had a lower correlation than arm length measurements; however, there was a strong and statistically significant correlation between shoulder width and arm length measurements. In the study of Shakya et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) with 150 people in Nepal, it has been established that there was a strong correlation between arm length and height, right arm length had a stronger correlation with height (R\u0026thinsp;=\u0026thinsp;0.911), and left arm length (R\u0026thinsp;=\u0026thinsp;0.895) in males and right arm length (R\u0026thinsp;=\u0026thinsp;0.779) in females had higher correlation with height, and when R\u0026sup2; values were examined, it was shown that height could be determined 80.1% from left arm length in males and 60.6% from right arm length in females. In a study conducted in India, Muslim and Hindu groups have been evaluated separately, and it has been found that the correlation of arm length with height was higher than shoulder width in both groups. Correlation with height in the Muslim group has been detected as R\u0026thinsp;=\u0026thinsp;0.751 for arm length, R\u0026sup2; value 56.4%, R\u0026thinsp;=\u0026thinsp;0.473 for shoulder width, R\u0026sup2; value 22.4%, and in the Hindu group, it has been found as R\u0026thinsp;=\u0026thinsp;0.849 for arm length, R\u0026sup2; value 72.1% for shoulder width, R\u0026thinsp;=\u0026thinsp;0.745 for shoulder width, R\u0026sup2; value 55.5% (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e\u0026ldquo;R value\u0026rdquo; is the correlation coefficient. \u0026ldquo;R\u0026sup2; value\u0026rdquo; expresses how much of the change in the dependent variable (height) can be explained by the independent variables (measurements taken) so that the estimated height can be calculated in the study group. Therefore, \"R\u0026sup2; value\" is a statistical measure of how well the regression estimates converge to the actual data points. When multiple regression analysis was applied in the measurements taken in the study, it was observed that the correlation between the height of the model in which left arm length and shoulder width were used together was the highest (R\u0026thinsp;=\u0026thinsp;0.887). According to the R\u0026sup2; value, it was observed that the model in which left arm length and shoulder width measurements were used could explain the heights of 78.4% (SEE:4.348) of all individuals in the study group from which 150 individuals were taken as a sample. The standard error of estimation (SEE) is a good parameter to evaluate the accuracy of linear regression equations. Since the standard estimation error was relatively low in the model obtained, it was considered appropriate to use it in estimating height.\u003c/p\u003e \u003cp\u003eThe models created in the regression analysis made from the measurements taken in the study are given in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Although the height estimation models for each variable/measurement are included in the table, when arm length of both sides and shoulder width measurements are available, it was considered appropriate to use the 1st model in which left arm length and shoulder width measurements were taken since both the correlation is strong and it would be more practical to use unilateral measurements in practice, In multiple regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) performed for the cases where the sex is known, 5 models were created for males and 4 models for females. According to the 1st model with the strongest correlation in males, it was considered appropriate to use the formula created from the left arm length and shoulder width, and the formula created in the 1st model in which the left arm length was used for females. It was observed that a meaningful model could not be developed by using the left arm length and shoulder width together in females.\u003c/p\u003e \u003cp\u003eIn similar studies conducted in different populations for the determination of height (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), it has been stated that the differences between the studied groups are affected by factors such as the historical period of the population in which the measurement is made, genetic factors, geographical region, social origin of the population, the total number of individuals measured and the way the measurements are made (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMeasurement values taken for sex determination were evaluated with Spearman Correlation Analysis, and it was seen that the measurement with the strongest correlation was shoulder width (R\u0026thinsp;=\u0026thinsp;0.758), and the correlation of left arm length was stronger than the right (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). When sex estimation formulas (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) obtained by Binary Logistic Regression Analysis from the measurements taken were applied, the model that used the left arm length and shoulder width was the one with the highest rate of correctly predicting sex in all participants with 89.3%. In estimation formulas using a single measurement, it was evaluated that sex estimation made from the left arm length measurement was able to accurately determine sex in 86.7% of all participants (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). In the study conducted by Duyar and Tacar, it has been determined that sex could be determined with an accuracy rate of 64.7%-86.5% from shoulder and hip width measurements (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). In a study conducted with 160 people in India, the measurement of shoulder width was 78.8% and arm length was 86.3% in the Guajarat Muslim group. In the Hindu group, it was shown that 93.8% of the shoulder width and 83.8% of the arm length could detect sex correctly, and it was emphasized that the results would be different according to the population in which the study was conducted (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilar studies have been conducted using upper extremity length and shoulder width measurements in different populations for sex determination (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e10\u003c/span\u003e). It has been determined that the rate of correct determination of sex is higher in formulas developed using more than one measurement location (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eNew technological developments such as DNA studies, facial reconstruction, and radiological examinations are used in the identification of unknown remains in forensic medical practices. However, in mass disasters such as natural disasters, transportation accidents, war, terror and bomb attacks, metric and morphological studies gain importance for identification of fragmented or disintegrated corpses.\u003c/p\u003e \u003cp\u003eThe database, which consists of the measures that emerged as a result of the study, is capable of supporting different Forensic Medicine studies in the long run. It is thought that the findings obtained from arm length and shoulder width measurements and regression formulas will contribute to the application in crime scene investigations, can be used in determining height and sex, thus contributing to the identification process.\u003c/p\u003e"},{"header":"ABBREVIATIONS","content":"\u003cp\u003eAL, Arm Length\u003c/p\u003e\u003cp\u003eAS, Arm Span\u003c/p\u003e\u003cp\u003eDNA, Deoxyribonucleic acid\u003c/p\u003e\u003cp\u003eHEW, Humerus Epicondylar Width\u003c/p\u003e\u003cp\u003eHHD, Humerus Head Diameter\u003c/p\u003e\u003cp\u003eLAL, Left Arm Length\u003c/p\u003e\u003cp\u003eLFAL, Left Forearm Length\u003c/p\u003e\u003cp\u003eLUAL, Left Upper Arm Length\u003c/p\u003e\u003cp\u003eRAL, Right Arm Length\u003c/p\u003e\u003cp\u003eRFAL, Right Forearm Length\u003c/p\u003e\u003cp\u003eRL, Radial Length\u003c/p\u003e\u003cp\u003eRUAL, Right Upper Arm Length\u003c/p\u003e\u003cp\u003eSB, Scapula Breadth\u003c/p\u003e\u003cp\u003eSD, Standard Deviation\u003c/p\u003e\u003cp\u003eSEE, Standard Error of the Estimate\u003c/p\u003e\u003cp\u003eSH, Scapula Height\u003c/p\u003e\u003cp\u003eSPSS, Statistical Package for the Social Sciences\u003c/p\u003e\u003cp\u003eSW, Shoulder Width\u003c/p\u003e\u003cp\u003eUAL, Upper Arm Length\u003c/p\u003e\u003cp\u003eUL, Ulnar Length\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eEthical approval for this study was obtained from the Muğla Sıtkı Koçman University Human Research Ethics Committee (Protocol No: 200008; Decision No: 37; dated 13 March 2020). Written informed consent was obtained from all participants prior to enrollment. The study was conducted in accordance with the principles of the Declaration of Helsinki and the provisions of the Turkish Personal Data Protection Law (Law No. 6698).\u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eNot applicable. No identifiable individual-level data are presented in this manuscript.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConducting the literature review and project preparation: MEÖ, YB, BES ; Supervision: YB, BES ; Materials: MEÖ ; Data Collection and Processing: MEÖ, BY; Transferring the data to a statistical program and conducting statistical analysis: MEÖ, YB; Literature Search and Interpretation and discussion of the findings, and manuscript writing: MEÖ, YB, UUG.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request. Due to ethical and privacy considerations, the data are not publicly available.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eA\u0026ccedil;ıkg\u0026ouml;z N, Hancı İH (2002) Adli Biyoloji. Adli Tıp ve Adli Bilimler. İ\u0026ccedil;: Hancı İH, edit\u0026ouml;r. Ankara: Se\u0026ccedil;kin Yayıncılık San ve Tic AŞ; s.577\u0026ndash;598\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eA\u0026ccedil;ıkg\u0026ouml;z N, Hancı İH (2002) Adli Hemogenetik. Adli Tıp ve Adli Bilimler. İ\u0026ccedil;: Hancı İH, edit\u0026ouml;r. Ankara: Se\u0026ccedil;kin Yayıncılık San ve Tic AŞ; s.598\u0026ndash;613\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eA\u0026ccedil;ıkg\u0026ouml;z N, Hancı İH (2002) Adli Mikrobiyoloji. Adli Tıp ve Adli Bilimler. İ\u0026ccedil;: Hancı İH, edit\u0026ouml;r. 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J Forensic Leg Med 18:167\u0026ndash;172\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiles E, Vallandigham PH (1991) Height estimation from foot and shoeprint lenght. J Forensic Sci 36(4):1134\u0026ndash;1151\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNarles VL, Miller JS (2004) Making tracks: the forensic analysis of footprints and footwear impressions. Anat Record (Part B:New Anat) 279B:9\u0026ndash;15\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeybek FG (2011) Ayak antropometrik \u0026ouml;l\u0026ccedil;\u0026uuml;mlerinin cinsiyet tespiti ve boy tahmini a\u0026ccedil;ısından değerlendirilmesi. Doctoral Dissertation. DE\u0026Uuml; Sağlık Bilimleri Enstit\u0026uuml;s\u0026uuml;, İzmir\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWunderlich RE, Cavanagh PR (2001) Gender differences in adult foot shape:implication for shoe desing. Med Sci Sports Exerc 33(4):605\u0026ndash;611\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRich J, Dean DE, Cheung YY (2003) Forensic implications of the foot anda ankle. J Foot Ankle Surg 42(4):221\u0026ndash;225\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJasuja OP, Harbhajan S, Anupama K (1997) Estimation of stature from stride length while walking fast. Forensic Sci Int 86:181\u0026ndash;186\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThomas JL, Kunkel MW, Lopez R, Sparks D (2006) Radiographic values of the adult foot in a standardized population. J Foot Ankle Surg 45(1):3\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDogan A, Uslu M, Aydınoğlu A, Harman M et al (2007) Morphometric study of the human metatarsals and phalanges. Clin Anat 20(2):209\u0026ndash;214\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJasuja OP, Manjula (1993) Estimation of stature from footstep lenght. 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Int J Health Sci Res 11(5):23\u0026ndash;29\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMulu A, Sisay B (2021) Estimation of Stature from Arm Span, Arm Length and Tibial Length among Adolescents of Aged 15\u0026ndash;18 in Addis Ababa Ethiopia. Ethiop J Health Sci. ;31(5)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohanty SP, Babu SS, Nair NS (2001) The use of arm span as a predictor of height: A study of South Indian women. J Orthop Surg 9(1):19\u0026ndash;23\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSteele MF, Chenier TC (1990 Nov-Dec) Arm-span, height, and age in black and white women. Ann Hum Biol 17(6):533\u0026ndash;541\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiles E, Vallandigham PH (1991) Height Estimation From Foot And Shoeprint Length. J Forensic Sci 36(4):1134\u0026ndash;1151\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh TS, Phookan MN (1993) Stature and footsize in four Thai communities of Assam, India. Anthropol Anz. :349\u0026ndash;355\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQamra SR, Deodhar SD, Jit I (1986) A metric study feet of north-west Indians and its relationship to body height and weight. Int J Physiol Anthropol Hum Gen 12:131\u0026ndash;138\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNandi ME, Olabiyi OA, Ibeabuchi NM, Okubike EA, Iheaza EC (2018) Stature Reconstruction from Percutaneous Anthropometry of Long Bones of Upper Extremity of Nigerians in the University of Lagos. Arab J Forensic Sci Forensic Med 1(7):869\u0026ndash;880\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArif M, Rasool SH, Chaudhary MK, Shakeel Z (2018) Estimation of stature; upper arm length a reliable predictor of stature. Prof Med J 25(11):1696\u0026ndash;1700\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavid S, Mokhtari T, Alizamir T, Arabkheradmand A, Hassanzadeh G (2014) Determination of Stature from Upper Arm Length in Medical Students. Anat Sci 11(3):135\u0026ndash;140\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah T, Patel M, Nath S, Menon SK (2015) A model for construction of height and sex from shoulder width, arm length and foot length by regression method. J Forensic Sci Criminol 3(1):102\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuyar İ, Tacar O (1998) Antropometrik boyutlarda g\u0026ouml;zlenen cinsiyet farklılıklarının diskriminant analizi kullanılarak incelenmesi. Morfoloji Dergisi 6(1):10\u0026ndash;14\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkhlaghi M, Hajibeygi M, Zamani N, Moradi B (2012) Estimation of stature from upper limb anthropometry in Iranian population. J Forensic Leg Med 19(5):280\u0026ndash;284\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAiran N, Dwivedi AK, Das AR, Mishra SK (2016) Estimation of stature from length of arm in adult population of Garhwal region of Uttarakhand, India. Int J Biomedical Res 7(12):842\u0026ndash;846\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYeasmin N, Asadujjaman M, Islam MR, Hasan MR (2022) Stature and sex estimation from shoulder breadth, shoulder height, popliteal height, and knee height measurements in a Bangladeshi population. Forensic Sci International: Rep 5:100258\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoore MK, DiGangi EA, Ru\u0026iacute;z FPN, Davila OJH, Medina CS (2016) Metric sex estimation from the postcranial skeleton for the Colombian population. Forensic Sci Int 262:286\u0026ndash;e1\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCelbis O, Agritmas H (2006) Estimation of stature and determination of sex from radial and ulnar lengths in a Turkish corpse sample. Forensic Sci Int 158(2\u0026ndash;3):135\u0026ndash;139\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMall G, Hubig M, B\u0026uuml;ttner A, Kuznik J, Penning R, Graw M (2001) Sex determination and estimation of stature from the long bones of the arm. Forensic Sci Int 117:23\u0026ndash;30\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHowley D, Howley P, Oxenham MF (2018) Estimation of sex and stature using anthropometry of the upper extremity in an Australian population. Forensic Sci Int 287:220e1\u0026ndash;220e10\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Forensic Anthropology, Arm Length, Shoulder Width, Height Estimation, Sex Estimation","lastPublishedDoi":"10.21203/rs.3.rs-8642816/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8642816/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eIdentification is important in forensic medical applications. In events with or without mortality, determining the height and sex of individuals is also a part of identification. In this study, it was aimed to develop methods for estimating height and sex from shoulder width and arm length.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003eOne hundred and fifty volunteers were included in the study. In addition to the demographic data of the participants, height, bilateral arm lengths and shoulder width measurements were recorded in the data collection form. Data were evaluated with SPSS statistical program. Correlation and regression analyses were performed. Whether there was a significant difference between the means of the right and left side measurements was tested with the t test.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSeventy-five (50%) of the participants were female, 75 (50%) were male, and mean age was 26.3 years\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8. The Aegean Region was the region where the majority of the participants lived the longest, both in the place of birth and in the process of completing their bone development. The measurement with the strongest correlation with height is the arm span measurement when the sex is known or unknown, the correlation coefficient between the left side arm length measurements and the height is higher than that of the right, and therefore, if both side measurement results are available, only left side measurements can be measured. It was evaluated that it would be appropriate to use it in estimating the length of the shoulder, the correlation between shoulder width and sex was the strongest, and the formula used together with the left arm length and shoulder width gave the highest rate of correct (89.3%) results.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIt was determined that the strongest correlation with height was the model in which left arm length and shoulder width measurements were used together (R\u0026thinsp;=\u0026thinsp;0.887). Accordingly, height estimation formula, if sex is unknown, is as such: Height\u0026thinsp;=\u0026thinsp;51.95+(1.61 x left arm length\u0026thinsp;+\u0026thinsp;0.589 x shoulder width) (SEE:4.35), and in cases where the sex is known, it is Height\u0026thinsp;=\u0026thinsp;63.49+(1.49 x left arm length\u0026thinsp;+\u0026thinsp;0.50 x shoulder width) (SEE:3.89) form males and Height\u0026thinsp;=\u0026thinsp;79.75+(1.48 x left arm length) (SEE:4.58) for females.\u003c/p\u003e","manuscriptTitle":"Estimating Height and Sex from Shoulder Width and Arm Length","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-05 08:27:34","doi":"10.21203/rs.3.rs-8642816/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"27ea61aa-8629-4595-bd72-28f85deaf4f6","owner":[],"postedDate":"February 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-01T07:24:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-05 08:27:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8642816","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8642816","identity":"rs-8642816","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}