eISSN: 24692794 FRCIJ
Forensic Research & Criminology International Journal
Research Article
Volume 1 Issue 5  2015
Somatometric Evaluation of Long Bones of the Upper Extremity: A Forensic Tool
Ekezie J^{1}*, Anibeze CIP^{2}, Uloneme GC^{3}, Anyanwu GE^{4}, Danborno SB^{5} and Iwuoha G^{6}
^{1}Department of Anatomy, Federal University of Technology, Nigeria
^{2}Department of Anatomy, Abia State University, Nigeria
^{3}Department of Anatomy, Imo State University Owerri, Nigeria
^{4}Department of Anatomy, University of Nigeria, Nigeria
^{5}Department of Anatomy, Amadu Bello University, Nigeria
^{6}Department of Public Health, Federal University of Technology, Nigeria
Received: September 27, 2015 Published: December 07, 2015
*Corresponding author: Ekezie J, Department of Anatomy, Federal University of Technology, PMB 1526 Owerri Nigeria, Tel: +234 806 5430037; Email:
Citation: Ekezie J, Anibeze CIP, Uloneme GC, Anyanwu GE, Danborno SB, Iwuoha G (2015) Somatometric Evalution of Long Bones of the Upper Extrimity: A Forensic Tool. Forensic Res Criminol Int J 1(5): 00029. DOI: 10.15406/frcij.2015.01.00029
Abstract
Somatometric techniques are important tools in forensic investigation as well as in studying biological variation. The present study investigated the long bones of the upper extremity to ascertain which one will be more appropriate to generate regression equations for prediction of BH. Four long bone lengths (HL UL, RL and CL) were evaluated subcutaneously. BH was taken using Anthropometer, while randomly HL, UL, RL and CL were measured on the right side of the body from a pull of 211 subjects using measuring tape.
The findings of the present study indicate that the correlation ‘r’ between BH and the right upper limb measurements were significant for HL, UL, RL, in the overall population; the highest correlation between the dependent variable BH and the independent variable (UL) in overall population was 0.82 (P< 0.0001). In the females the correlation was significant for HL UL, RL, and CL; the highest correlation was found in UL, r=0.71 (P< 0.0001) the least was indicated by CL, r =–0.25. In the males the study revealed positive significant correlation for HL UL, and RL, The highest correlation was seen in UL, r=0.71 (P< 0.0001) while the least was 0.26 (P=0.02) as seen in HL. This present study shows that the UL is a veritable dimension in the estimation of BH for the Igbos because the Pearson’s correlation coefficient ‘r’ obtained was the heights amongst that obtained for the other segments HL, RL and CL. Also the coefficient of determinant ‘R’ for testing model adequacy was highest for UL which had a lower SEE.
Keywords: Upper limb; body height; Forensic anthropology; Igbos
Abbreviations
BH: Body Height; HL: Humeral Length; RL: Radial Length; UL: Ulna Length; CL: Clavicle Length; F: Female; M: male; R: Multiple Correlation Coefficient Value; R^{2}: Percentage Contribution by the Explanatory Variable to the Variation in the Dependent Variable (BH); R^{2}adjusted: Compares the Regression Models Containing Different Number of Explanatory Variables (Upper Limbs Segments i.e. HL, RL, UL, and CL); SEE: Standard Error of Estimate (Predicts the Deviation of Estimated BH from the Actual BH)
Introduction
Somatometric techniques are employed in the measurement of the living body and cadaver and help in studying biological variations in humans. Such techniques are useful in forensic/anthropological investigations to estimate the chronological age and even stature of a given population or individual. The prediction of the dimension of one body segment from another or to relate the proportions of one body segment to another has also gained importance in various area of modern science. In growth and development, the relationships between body segments are used in the assessment of normal growth as well as in scientific syndromes [14].
The relationship between specific body dimensions is also important in the identification of criminals and victims. In conditions where the available evidences are skeletal remains [56], or complete body part/ fragmented parts, Anthropologists/Forensic Scientist are continually putting forward means to evaluate and estimate sex, age, height and race, ( the big four of Forensic Anthropology). In some places, there are times when complete body parts (either upper or lower extremities) are deposited along the road by unknown persons.. Such deposited body parts are either carted away by animals or crushed into pieces by moving vehicles. A time, the culprits and the person whose body were mutilated were never identified.
This study tries to evaluate the length of the long bones of the right upper extremity, subcutaneously, in other to generate possible regression formula for BH estimation of the study population (Igbo). This is because the identification of a person is important in the living as well as in the dead. In the living it is required in civil matters and criminal issues. In the dead it is important for proper dead body disposal and in unknown bodies [7].
The Igbo are a group of distinguished people who live in the Southeastern Nigeria. They are one of the three major ethnic groups in Nigeria [8]. They are seen in villages, towns and cities scattered over the Eastern part of Nigeria, South of the River Benue and East of River Niger, which is in the rain forest belt of the country [9] and also in the diaspora [10]. Igbos occupies an area of about 15,800 square mile (about 41,000 square kilometers) which is located between Latitude 5º and 7º North, and between 6º and 8º East of the Greenwich Meridian. They are bounded to the East by the lands of the Ibibio and the Cross River, to the South by the Ijaw speaking people, to the West by the Edo ethnic group and to the North by the Igala and the Idoma speaking people [1113].
Materials and Method
Participants were randomly selected from a pull of 211 persons [14] and attention was paid on the evaluation of the lengths of the long bones of the upper extremity after informed consents were given by the subjects.
Study location
This study was conducted in Imo State, Nigeria and it took eight (8) months to be completed.
Demographics
The following demographic information was collected: age, sex, and state of origin. This is very important in any Somatometric study because they help to establish variability within populations.
Exclusion criteria
Pregnant women and subjects with musculoskeletal disorder affecting body height and upper limb were excluded from this study.
Inclusion criteria
Only participants from the Igbo states who were apparently healthy were included in the study.
Anthropometrics
Body height (BH): This was measured to the nearest 0.1cm using an Anthropometer with subjects standing without shoes with the heels held together, toes apart, and the head held in the Frankfort plane [15].
Humeral length (HL): This the distance immediately below the acromioclavicular joint where the head of humerus is felt, to inferior part of the capitulum where the radius articulates with the humerus when the arm is abducted.
Ulna length (UL): The subject’s elbow was flexed to 90º with the fingers extended in the direction of the long axis of the forearm, and the distance between the most proximal point of the olecranon and the tip of the styloid process of the ulna was measured [16].
Radial length (RL): The distance measured in cm where the head of the radius articulate with the humerus (elbow joint) to the radial styloid process palpated in the anatomical snuff box.
Clavicular length (CL): The acromial end is palpated 23cm medial to the lateral border of the acromion, when the arm is alternately flexed and extended, then the length in cm is measured from the sternal end to the acromioclavicular joint.
The long bones of the upper extremity were accessed subcutaneously [17] and measurement were taken using tape placed at the landmarks described above.
Stastical Analysis
The data analysis was carried out using statistical package for social sciences (SPSS 17.0 software). In summarizing the data, the Minimum, Maximum, Mean and Standard deviations were estimated and presented. A comparison of difference of variable in females and males was also carried out. To test the relationship between BH and dimensions of long bones of the upper extremity, Pearson correlation was performed. The prediction function was derived through linear regression for each of the measurement with BH for the overall population, males and females separately. Finally the predicted/estimated values of BH were compared with that of observed/actual value.
Results
The general Somatometric characteristics of the study population are shown in Table 1. The descriptive statistics for both the females and males samples is shown in Table 2. We can see the standard deviation, the mean, and the maximum and minimum values of the Somatometric variables. All the Somatometric dimensions measured directly showed statistically significant differences between females and males, p<0.0001 with females having a lower mean value than males (Table 3).

N 
Minimum 
Maximum 
Mean 
Std. Deviation 
AGE (years) 
211 
16.00 
45.00 
23.58 
4.95 
BH (cm) 
211 
149.00 
190.00 
167.55 
9.10 
RL 
203 
23.00 
33.50 
28.18 
2.08 
UL 
84 
25.00 
34.00 
29.06 
1.87 
HL 
202 
21.00 
39.00 
29.96 
3.35 
CL 
186 
8.60 
22.00 
14.62 
3.09 
Table 1: Descriptive Statistics of the Overall Population.
Variables 
Females 
Males 
N 
Minimum 
Maximum 
Mean 
Std. Deviation 
N 
Minimum 
Maximum 
Mean 
Std. Deviation 
AGE (years) 
123 
16.00 
45.00 
23.74 
5.36 
88 
18.00 
43.00 
23.35 
4.34 
BH (cm) 
123 
149.00 
190.00 
163.17 
7.64 
88 
156.00 
190.00 
173.66 
7.30 
RL 
120 
23.00 
31.00 
27.38 
1.59 
83 
24.00 
33.50 
29.35 
2.15 
UL 
52 
25.00 
31.00 
28.20 
1.44 
32 
26.00 
34.00 
30.44 
1.66 
HL 
120 
21.00 
38.00 
29.17 
2.94 
82 
23.00 
39.00 
31.13 
3.58 
CL 
112 
8.60 
21.00 
14.15 
2.72 
74 
9.00 
22.00 
15.32 
3.49 
Table 2: Descriptive Statistics of the Females and Females.
Variables
(cm) 
Paired Differences 
T 
Df 
Sig.
(2tailed) 


95% Confidence Interval of the Difference 

Mean 
Std. Deviation 
Std. Error Mean 
Lower 
Upper 
BH (F)BH (M) 
14.01 
3.77 
0.40 
14.81 
13.21 
34.85 
87 
0.000 
RL(F)RL(M) 
2.32 
2.05 
0.23 
2.77 
1.87 
10.21 
80 
0.000 
UL (F)UL(M) 
2.36 
2.06 
0.57 
3.60 
1.12 
4.14 
12 
0.001 
HL(F)HL(M) 
2.65 
4.20 
0.47 
3.59 
1.72 
5.66 
79 
0.000 
CL (F)–CL(M) 
0.84 
4.22 
0.52 
1.87 
0.19 
1.63 
66 
0.107 
Table 3: Comparison of Difference of Variable in Females and Males of Right Upper Extremity.
The correlation coefficient between BH and the right upper extremities dimensions (RL, UL, HL and LC) in the study population was found to be statistically significant and positive, indicating a strong relationship between BH and right upper extremity dimensions, but there was no significant correlation between BH and CL. The highest positive correlation was observed in UL, r= 0.822 while the least was observe in HL r=0.393 (Table 4). For the females, the least significant correlation was observed in the CL, r =0.245 while the highest value was obtained in UL r=0.713. In the male population, significant and positive correlation was recorded between BH and right upper extremity segments. The least significant correlation was observed in HL, r = 0.257 while the highest was observed in UL, r= 0.713 (Table 4).
Variables
(cm) 
Overall Population 
Female 


Males 
N 
Pearson Correlation 
Sig. (2tailed) 
N 
Pearson Correlation 
Sig. (2tailed) 
N 
Pearson Correlation 
Sig. (2tailed) 
RL 
203 
0.635** 
0.000 
120 
0.438** 
0.000 
83 
0.608** 
0.000 
UL 
84 
0.822** 
0.000 
52 
0.713** 
0.000 
32 
0.713** 
0.000 
HL 
202 
0.393** 
0.000 
120 
0.322** 
0.000 
82 
0.257* 
0.020 
CL 
186 
0.004 
0.953 
112 
0.245** 
0.009 
74 
0.038 
0.751 
Table 4: Pearson Correlation between BH with Right Upper Extremity Dimensions in the Overall Population.
**Correlation is Significant at the 0.01 Level (2tailed).
*Correlation is Significant at the 0.05 Level (2tailed).
The Constant, Regression coefficient and Variation explained (R^{2}) derived for each of the right upper extremity measurements with BH are shown in Table 5 for the overall population and Table 6 for females and males. The values indicate that the constant for the HL was higher than that for RL, and UL, the regression coefficients were highly significant indicating that they are contributing for the prediction of BH. The variation explained (R^{2}x100) showed that it ranges from 15.4% to 67.6 % in the overall population. The best prediction power is observed in UL in the study population. For the females the variation explained ranged from 5.9% to 50.9%, with the UL having the best predict power while the least goes for the CL. In the males, the variation explained ranged from 6.6% to 50.9%, with the UL having the highest prediction power while the HL contributed the least to the variation explained.
Variables 
Constant 
Regression Coefficient 
R^{2} 
p value 
RL 
89.121 
2.780 
0.404 
0.000 
UL 
61.105 
3.604 
0.676 
0.000 
HL 
135.845 
1.052 
0.154 
0.000 
Table 5: Constant, Regression Coefficient and Variation Explained (R^{2}) of Right Upper Extremity Variables with BH (Dependent) Variables in Overall Population.
Variables 
Females 
Males 
Constant 
Regression
Coefficient 
R^{2} 
p value 
Constant 
Regression
Coefficient 
R^{2} 
p value 
RL 
104.976 
2.126 
0.192 
0.000 
114.451 
2.018 
0.369 
0.000 
UL 
86.283 
2.662 
0.509 
0.000 
85.334 
2.882 
0.509 
0.000 
HL 
138.551 
0.844 
0.104 
0.000 
157.930 
0.500 
0.066 
0.020 
CL 
173.228 
 0.70 
0.060 
0.009 




Table 6: Constant, Regression Coefficient and Variation Explained (R^{2}) of Right Upper Extremity Variables with BH (Dependent) Variables in Females and Males.
The Regression coefficient for the CL was not significant in the overall population as well as in the males but was significant in the females. This means that the CL did not contribute to the variation explained in the overall population and males but contributed to that of the females, i.e. R^{2} X 100 equals 6%. Tables 7 and 8 represent the values for R^{2}, Adjusted R^{2}, and SEE of the right upper extremities variables in the overall population, females and males respectively. The best simple linear regression model was developed using UL and this has the highest values for the coefficient of determination R^{2} as 0.676, R^{2}_{Adjusted} as 0.672 and multiple correlation coefficient R as 0.822 in the overall population.
Variables 
R 
R^{2} 
Adjusted R^{2} 
SEE 
RL 
0.635 
0.404 
0.401 
7.032 
UL 
0.822 
0.676 
0.672 
4.693 
HL 
0.393 
0.154 
0.150 
8.277 
Table 7: R^{2}, Adjusted R^{2}, and SEE of Right Upper Extremities Variables in Overall Population.
Variables 
Females 
Males 
R 
R^{2} 
Adjusted R^{2} 
SEE 
R 
R^{2} 
Adjusted R^{2} 
SEE 
RL 
0.438 
0.192 
0.185 
6.964 
0.608 
0.369 
0.361 
5.701 
UL 
0.713 
0.509 
0.499 
3.799 
0.713 
0.509 
0.492 
4.778 
HL 
0.322 
0.104 
0.096 
7.334 
0.257 
0.066 
0.054 
6.779 
CL 
0.245 
0.060 
0.052 
7.572 




Table 8: R^{2}, Adjusted R^{2}, and SEE of Right Upper Extremities Variables in Females and Males.
In the females, the best simple linear regression model was developed using UL and this has highest values for the coefficient of determination R^{2} as 0.509, R^{2}_{Adjusted} as 0.499 and multiple correlation coefficient R as 0.713 with a 3.7993 SEE. In the males, the best simple linear regression model was developed using UL and this has highest values for the coefficient of determination R^{2} as 0.509, R^{2} Adjusted as 0.492 and multiple correlation coefficient R as 0.713 with a 4.7782 SEE.
The best simple equation developed for the overall population, females and males respectively are: BH _{overall population} = 61.105+3.604(UL), BH_{female} = 86.283+2.662(UL) and BH_{male} = 85.334 + 2.882(UL). BH could also be estimated using other dimension of the right upper extremity, the regression equations generated are also in Tables 810. The mean predicted value of BH through the regression function was similar to the mean observed value; however the minimum and maximum value indicated that there were differences in the predicted and observed value; the minimum predicted value overestimates the minimum observed value in the overall population, females and males while the maximum predicted value underestimates the maximum observed value in the overall population, females as well as in the males (Tables 11 &12).
Regression equation 
±SEE 
BH =89.121+2.780(RL) 
7.032 
BH =61.105+3.604(UL) 
4.693 
BH =135.845+1.052(HL) 
8.277 
Table 9: Regression Equations for Estimation of BH in the Overall Population Using Right Upper Extremity Measurements.
Regression equation (Female) 
±SEE 
Regression equation (Male) 
±SEE 
BH =104.976+2.126(RL) 
6.964 
BH =114.451+2.018(RL) 
5.701 
BH =86.283+2.662(UL) 
3.799 
BH =85.334+2.882(UL) 
4.778 
BH =138.551+0.844(HL) 
7.335 
BH =157.930+0.500(HL) 
6.778 
BH =173.228  0.70(CL) 
7.572 


Table 10: Regression Equations for Estimation of BH in Females Using Right Upper Extremity Measurements.

Minimum 
Maximum 
Mean 
Std. Deviation 
N 
Observed Value 
149.00 
190.00 
167.55 
9.10 
211 
RL 
153.06 
182.24 
167.46 
5.77 
203 
UL 
151.21 
183.64 
165.82 
6.74 
84 
HL 
157.93 
176.86 
167.36 
3.52 
202 
Table 11: Minimum, Maximum, Mean and Standard Deviations of the Predicted Values of BH by Regression Functions with Right Upper Extremity Variables in the Overall Population.
Variables 
Females 
Males 
Minimum 
Maximum 
Mean 
Std. Deviation 
N 
Minimum 
Maximum 
Mean 
Std. Deviation 
N 
Observed Value 
149.00 
190.00 
163.17 
7.64 
123 
156.00 
190.00 
173.66 
7.30 
88 
RL 
153.87 
170.87 
163.17 
3.38 
120 
162.8783 
182.05 
173.67 
4.34 
83 
UL 
152.84 
168.81 
161.37 
3.83 
52 
160.2648 
183.32 
173.06 
4.78 
32 
HL 
156.28 
170.63 
163.17 
2.48 
120 
169.4222 
177.42 
173.48 
1.79 
82 
CL 
158.50 
167.20 
163.30 
1.91 
112 





Table 12: Minimum, Maximum, Mean and Standard Deviations of the Predicted Values of BH by Regression Functions with Right Upper Extremity Variables in Females and Males.
Discussion
Close relationships exist between BH and dimensions of various body parts and the subsequent results are frequently applied in medicolegal investigation. In this study an attempt was made to establish BH using dimensions from long bones of the upper body extremity segments. Four right upper extremity measurements including BH of the subjects were measured. The prediction function was derived through linear regressions for each of the measurement with BH, for the overall population and for females and males separately. In this study, the mean BH and age for the population under study is 167.55 ± 9.00cm and 23.58 ± 4.95years respectively. While the minimum and maximum BH is 149.00 cm and 190.00 cm respectively. The mean BH and age for the female and male subjects are 163.17 ± 7.64cm, 23.74 ± 5.36 years and 173.66 ± 7.30cm and 23.35 ± 4.34 years respectively.
In sexing the upper extremity parameters, all the variables were highly significant (P< 0.0001) in most cases except the CL. These values were higher in the males than in the females. This agrees with most biological measurements for example: osteometry [1819] Somatometry [8,14,2024]; Cephalometry/Cephalofacial [2529]. Distinct sexual dimorphisms have been reported in ulna measurements by many authors [3035], ours study also considered UL and noted distinct sexual dimorphisms [36]. In their study investigated the use of height to ulna ratio measurement (height/ulna) in the estimation of stature and observed sexual dimorphisms.
Estimation of stature and determination of sex from radial and ulnar bone lengths in Turkish corpses has been reported by [37]. The sample composed of 80 males and 47 females with an average age of 36 and 30 years respectively. Lengths measurements from the radius and ulna were obtained by exposing the epiphyseal ends in fashion similar to dry long bones. Discriminant function statistics indicated sex determination accuracy as high as 96% while regression analysis was used in stature estimation from the two bones. Conclusively, the authors noted that in the absence of pelvis, sex could be determined from long bones and cranium as they have high accuracy in sexing.
A number of authors have investigated stature estimation based on measurements of the ulna and other bones of upper limb [19,3840] and regression equations were generated; such generated equations must be population specific. [41], In their study estimated stature from upper extremity. The purpose of their study was to analyze the anthropometric relationships between dimensions of the upper extremity and BH. In their study of Turks residing in Istanbul, Turkey, 202 middle class males and 108 middle class females were sampled and variables such as hand length, forearm length and upper arm length were measured for analyses. They suggested that the estimation of a living stature could be made using the various dimensions of the upper limb while also stipulating that differences between populations must be considered before the application of their findings. This finding is in agreement with the present study because regression equations have been generated for the study population.
BH estimation based on UL in this study has SEE between 4.694.69 for the overall population, females and males while that of the other long bones (HL, RL and CL) of the upper extremity is between 5.708.28. This is however not similar to the standard errors of the estimations reported in several studies. For example, the standard errors of estimation from the formulae that [42] devised for several ethnic groups (whites, blacks, Mongoloids and Mexicans) based on humerus, radius, and ulna lengths were quite similar (approximately 44.8 cm). This may not be expected in our study due to ethnic variation and environmental factors.
In another study by [43], arm span was found to show the highest correlation with standing height. In the study, a cross sectional study was conducted to develop equations using several anthropometric measurements for estimating stature in Malaysian Elderly. The study used a total of 100 adults (aged 3049 years) and 100 elderly subjects (aged 60–86 years) from three major ethnic groups of Malays, Chinese and Indians. Anthropometric variables utilized were body weight, height, arm span, half arm span, demi span and knee height. Although our study did not measure upper extremity spans; however the highest correlation was observed s in UL and this may not agree with the finding of [43], because correlation between arm span and stature has been reported to vary in different ethnic groups [4445], The differential correlations may also arise due to different lengths of subsets of bones that constitute the arm span.
Mall G et al. [19] Investigated the determination of sex and estimation of stature from the long bones of the arm. The bones to be measured were prepared by mechanically removing soft tissues, tendons and ligaments. The study utilized a total of 143 individuals compromising of 64 males and 79 females who were sampled for variables including humeral length, vertical humeral head diameter, humeral epicondylar width, ulnar length, proximal ulnar width, distal ulnar width, radial length, radial head diameter, distal radial width. Their study revealed a significant difference between the means in males and females. Discriminant analysis had good results. Also the study showed that the linear regression analysis for correlation between bone lengths and stature led to unsatisfactory results with large 95% confidence intervals for the coefficient and high standard errors of estimate. The long bones in our study yielded satisfactory result with low SEE.
The estimation of stature is a very important step in developing biological profile for forensic identification [46,47]; because of this, the regression equations obtained in our study were checked for accuracy by comparing the estimated/predicted value of BH with the actual/observe BH. The results obtained were comparable.
Conclusion
This study has revealed that the UL in the overall population, females or males is the best upper extremity bone length that predicts the BH of the Igbos. Thus it is a veritable tool in forensic anthropology for estimation of BH and degree of sexual dimorphism.
Acknowledgment
The authors would like to thank the participants of this study for providing themselves for the measurements.
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