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 Table of Contents  
Year : 2019  |  Volume : 5  |  Issue : 1  |  Page : 24-28

Determination of sex from the tibia in a contemporary Sri Lankan population

1 Division of Anatomy, Department of Basic Sciences, Faculty of Dental Sciences, University of Peradeniya, Peradeniya, Sri Lanka
2 Department of Forensic Medicine, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka
3 Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka

Date of Web Publication28-Mar-2019

Correspondence Address:
Dr. Amal Nishantha Vadysinghe
Department of Forensic Medicine, Faculty of Medicine, University of Peradeniya, Peradeniya 20400
Sri Lanka
Prof. Deepthi Nanayakkara
Division of Anatomy, Department of Basic Sciences, Faculty of Dental Sciences, University of Peradeniya 20400
Sri Lanka
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jfsm.jfsm_56_18

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Determination of sex from the tibial dimensions has been attempted before in different populations. The formulae developed to determine sex of one population are not appropriate to be applied to another. Seven standard variables including the maximum length of tibia, proximal epiphyseal breadth, distal epiphyseal breadth, minimum circumference of shaft, anteroposterior diameter at nutrient foramen, transverse diameter at the nutrient foramen (TDNF), and circumference at the nutrient foramen obtained from 81 adult tibiae (56 male and 25 female) were analyzed to investigate the sexual dimorphism in the tibial dimensions to establish sex estimating formulae from the tibia in a contemporary Sri Lankan population. Results confirmed the existence of sexual dimorphism of the tibia. Discriminant functions obtained resulted in the classification accuracies ranging from 61.9% to 80.2%. The most dimorphic single parameter in males was the TDNF providing an accuracy of 92.9%, while in females, the minimum circumference of shaft provided an accuracy of 70.4%. The best multivariate equation utilizing two tibial dimensions resulted in an accuracy of 80.2% after cross-validation. We envisage that sex estimating formulae established in this study for a contemporary Sri Lankan population will contribute toward the biological profiling and identification of unknown skeletal remains.

Keywords: Discriminant function analysis, forensic anthropology, sex determination, Sri Lankans, tibia

How to cite this article:
Nanayakkara D, Vadysinghe AN, Nawarathna LS, Sampath H. Determination of sex from the tibia in a contemporary Sri Lankan population. J Forensic Sci Med 2019;5:24-8

How to cite this URL:
Nanayakkara D, Vadysinghe AN, Nawarathna LS, Sampath H. Determination of sex from the tibia in a contemporary Sri Lankan population. J Forensic Sci Med [serial online] 2019 [cited 2023 Feb 8];5:24-8. Available from: https://www.jfsmonline.com/text.asp?2019/5/1/24/255133

  Introduction Top

Reconstructing the biological profile, which includes sex, age, race-ethnicity, and stature estimation, is an important task when unknown skeletal remains are recovered. Sex determination is one of the first and basic steps in assessing the biological profile because the ability to determine whether the skeletal elements belong to a male or female individual immediately narrows down the pool of potential identities.[1]

In this context, the pelvis and skull, in particular, have been considered the most useful structures for determining sex as they exhibit the most sexual dimorphic features. When the pelvis and skull are either fragmented or absent, postcranial bones, especially the long bones are usually used for sex determination.[2],[3],[4] In addition, Spradley and Jantz[4] shown that several postcranial elements can outperform skull dimensions in their accuracy to determine sex.

Previous studies have demonstrated that the populations vary considerably from each other in size and proportion as a result of genetic and environmental factors affecting skeletal growth.[5],[6] These differences are known to affect the metric assessment of sex. Further, a constant revision of the sex estimation standards is necessary to cope with secular changes.[7] It is therefore imperative that population-specific standards for sex determination are developed for people born in certain time periods.

The tibia, following the femur, is the second most robust bone in the human skeleton and therefore likely to resist taphonomic agents and remain preserved. Further, previous studies have shown that there is considerable sexual dimorphism in the tibia and indicate that it can be utilized to discriminate sex in a forensic context.[5],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17],[18],[19] The tibial length, circumference at the nutrient foramen level, and proximal and distal breadths have been identified as significantly sexually dimorphic areas of the tibia in the previous reports.[5],[8],[9],[10],[14]

Although studies have been conducted for the determination of sex using dimensions of the tibia in various populations, no such standards are available for the Sri Lankan population. Thus, to fulfill this deficit, the present study was undertaken with the aim of investigating the sexual dimorphism in dimensions of the tibia and to generate population-specific sex determination formulae using sexually dimorphic tibial measurements in the contemporary Sri Lankan population.

  Materials and Methods Top

The material for the present study consisted of 81 adult tibiae (56 males and 25 females) drawn from the skeletal collection available at the Department X (Name of the institution was removed due to double-blind review policy). In most cases, information on the year of birth, sex, age at death, and the cause of death was available as the skeletons were prepared from the cadavers utilized by the routine dissections of the undergraduate academic program. Any tibia either having cortical bone deterioration, severe degenerative changes, or signs of fracture during life was excluded from the study. Approval from the Institutional Ethical Committee was obtained before data acquisition (ERC/FDS/UOP/1/2017/04).

Seven standard measurements were obtained from each individual tibia adopting landmark definitions described in previous studies.[12],[17] Description of each measurement is as follows and [Figure 1] illustrates the measurements (A-G):
Figure 1: Measurements of the tibia. (A) maximum length of the tibia, (B) maximum proximal epiphyseal breadth, (C) maximum distal epiphyseal breadth, (D) minimum circumference of shaft, (E) transverse diameter at the nutrient foramen, (F) anteroposterior diameter at the nutrient foramen, and (G) circumference of the tibia at the nutrient foramen

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  1. Maximum length of the tibia (MLT) – the distance from superior articular surface of the lateral condyle of the tibia to the tip of the medial malleolus (A)
  2. Maximum proximal epiphyseal breadth – the maximum distance between the most laterally projecting points on the medial and lateral condyles of the proximal epiphysis (B)
  3. Maximum distal epiphyseal breadth – the maximum distance between the two most laterally projecting points on the medial malleolus and the lateral surface of the distal epiphysis inside the fibular notch (C)
  4. Minimum circumference of shaft (MCS) – wherever found (usually at the distal third of the bone) (D)
  5. Transverse diameter at the nutrient foramen (TDNF) – the straight line distance of the medial margin from the interosseous crest (E)
  6. Anteroposterior diameter at the nutrient foramen (APNF) – the distance between the anterior crest and the posterior surface at the level of the nutrient foramen (F)
  7. Circumference of the tibia at the nutrient foramen (CNF) – the circumference measured at the level of the nutrient foramen (G).

The maximum length and proximal and distal epiphysial breadths of the tibia were measured using an osteometric board. A flexible steel measuring tape was used to measure the circumference. A digital vernier caliper (Mitutoyo, Japan) was used to obtain the rest of the measurements to the nearest 0.01 mm. Before primary data collection, a test for repeatability was conducted using Lin's concordance correlation coefficient (CCC) of reproducibility.

For this purpose 10 tibiae were selected and the measurements were repeated. All measurements were recorded by a single investigator. The values of CCC obtained in the present study were within the internationally accepted range (0.900 and 1), indicating that the technique used for measurements in this study was satisfactory.

Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS, IBM, SPSS Statistics V 21.0, United States), version 21. The data were assessed for normality using Kolmogorov–Smirnov test. Descriptive statistics including the means and standard deviations were obtained for each dimension separately for each sex. The Student's t-tests were performed to ascertain whether significant differences existed between the mean values of each measurement of males and females. P value <0.05 was considered statistically significant.

Sexual dimorphism ratios were calculated to determine the level of differences between the sexes using the formula below:

Sexual dimorphism ratio = (Male mean) ×100/(Female mean).

Subsequently, the data were subjected to univariate and stepwise discriminant analysis. The measurements which showed a significant sex dimorphism were individually subjected to univariate discriminant analysis to test the efficiency in sex determination. The demarking points for the univariate discriminant analysis were then defined as the midpoints between the male and female means. The demarking point serves to discriminate those bones with measurements above the demarking point as likely male (i.e., males are larger than females) and any bone with measurements below the demarking point as likely female.

Stepwise discriminant function analyses were conducted with the selected measurements as independent variables to discriminate between the sexes. The average of the functions at group centroids within each discriminant formula created a sectioning point between males and females.

  Results Top

The results of the Kolmogorov–Smirnov test confirmed that the data were distributed normally (P > 0.05). Descriptive statistics including the means and standard deviations generated for all variables of the tibia separately for males and females are presented in [Table 1]. The mean values of the measurements were higher in males than those of females in all cases. The results of the Student's t-test which are also presented in [Table 1] demonstrate highly significant differences between the measurements of sexes (P < 0.05–0.001) except the CNF for which the difference was statistically not significant (P > 0.05).
Table 1: Descriptive statistics of tibial dimensions (mm) in males and females

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[Table 2] presents the sexual dimorphism ratios, demarking points (points separating males from females), univariate F-ratios, and their corresponding significance levels. The index of dimorphism was always > 100 indicating that males, as expected, have greater tibial dimensions. The highest value of the index was seen in the APNF which showed a difference of 13.44%, while the lowest value was recorded for the CNF of the tibia (5.29%).
Table 2: Demarking points, sex dimorphism (%) and univariate statistics of tibial dimensions (mm)

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The most dimorphic single parameter on the basis of univariate discriminant function analysis for males was the TDNF providing an accuracy of 92.9% (after cross-validation) and for females the MCS with an accuracy of 70.4% [Table 3]. The overall cross-validated percent correct classifications for the tibial dimensions range from 61.9% to 73.8%. When a single variable is used, sex can be determined by comparing the dimension of the specimen with the corresponding demarking point (the average of the means for each sex). A higher value indicates a male and lower value indicates a female.
Table 3: Classification accuracy (%) for individual variables

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The results of the stepwise discriminant function analysis are shown in [Table 4]. Of the seven variables entered into the function, only two variables, the MLT and MCS, were selected for the analysis. The Wilks' lambda shows the percentage contribution of each measurement and determines the order of variables to enter the function. The Wilks' lambda ranges between 0 and 1; values close to 0 indicate that the group means are different and values close to 1 indicate that the group means are similar. The significance of the change in Wilks' lambda is measured with an F-test; if the F-value is greater than the critical value, the variable is kept in the model. [Table 4] also presents the unstandardized discriminant function coefficients and the sectioning points (the average of the male and female centroids). The best multivariate equation for the present sample utilizing MLT and MCS yielded an accuracy rate of 80.2% (male – 76% and female – 82.1%) after cross-validation.
Table 4: Summary of step-wise discriminant function analysis, unstandardized discriminant function coefficients and sectioning points

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Discriminant function score can be calculated by multiplying each variable with its unstandardized coefficient and adding them together along with the constant. A score greater than the sectioning point indicates the individual to be considered as a male, while a score lower than the sectioning point indicates a female. Further, the discriminant score is from the sectioning point, greater the reliability.

  Discussion Top

As part of the formulation of a biological profile, the determination of sex constitutes an important component that provides useful data toward narrowing the pool of potentially matching identities. Recent literature has demonstrated that metric analysis of long bones of the lower limb has considerable promise for the accurate determination of sex.[3],[5],[6],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17],[18],[19],[20],[21] On that basis, the present study was undertaken to seek the sex predicting potential of the tibia in a contemporary Sri Lankan population as tibiae have not before been analyzed in the Sri Lankan population for this purpose.

The findings of the current study clearly reaffirm the marked sexual dimorphism exhibited by the tibia as observed by previous investigators.[8],[9],[10],[11],[12],[13],[14],[15],[16],[17] Differences between male and female mean values for all variables with the exception of CNF obtained statistical significance at a P < 0.05–0.001 with male measurements being greater. Sexual dimorphism of the human skeleton is a vital biological attribute that can aid in the positive identification of unknown human remains in forensic investigations.

When the measurements which showed a significant sex dimorphism in this study were subjected to multiple univariate and multivariate discriminant analysis to test the efficiency in sex estimation, the results revealed that the prediction accuracies for determination of sex using the tibial measurements ranged from 61.9% to 80.2% in the Sri Lankan population. Further, the results revealed that on the basis of univariate discriminant function analysis, the most dimorphic single parameter for sexing male individuals was the TDNF providing an accuracy of 92.9%, whereas in females, the MCS was the best single parameter with an accuracy of 70.4%. These findings of the study clearly demonstrate the forensic utility of the tibia as a predictor of sex.

In the present Sri Lankan skeletal sample, sex classification accuracy rates were higher in males (ranging from 62.5% to 92.9%) for all tibial measurements with the exception of MCS for which the females exhibited a higher accuracy rate. This is consistent with many previous studies[8],[14],[17] where higher accuracy rates have been observed in males than in females. Conversely, studies done in the South African whites,[16] prehispanic inhabitants of Canary Islands,[11] and Irish medieval skeletal sample[18] demonstrated higher accuracy rates in females. Females in the current study showed a wider variation in many variables, resulting in lower accuracies. Differences in accuracy rates between the sexes can result from a number of factors including variation in sample size and intrasex variability.[12]

In the stepwise analysis, the best sex determining formula for the present sample which utilized a combination of variables (MLT and MCS) achieved an overall cross-validated group classification rate of 80.2%. This accuracy rate is comparable with those established for an Indian (82.8%),[17] an Anatolian (73.5%–88.7%),[14] a South African African (79%–82%),[22] and a Cretan (69%–83%)[23] population. Relatively higher accuracy rates ranging from 84.4% to 91.1% and 80% to 89% have been observed in a contemporary Croatian sample[21] and a modern Japanese sample,[5] respectively. In these studies, different combinations of tibial measurements have been used to generate sex estimating formulae expressing varying levels of sex predicting accuracies. This implies that variables suited most for identifying sex vary in different population groups demonstrating the population-specific nature of sexual dimorphism. In the present study, population specificity was displayed in terms of the variables exhibiting the greatest degree of sexual dimorphism as well as the ranges of sex predicting accuracy.

A noteworthy observation of this study is that the MLT was found to be a useful sex predictor providing an accuracy rate of 78.6%. Moreover, the MLT was one of the variables that were selected by the stepwise procedure. While this finding is consistent with that of a Cretan sample,[23] it disagrees with the other studies[8],[11],[14] where breadth and circumference measurements are reported as better indicators of sex than length measurements.

In addition, one cannot ignore the importance of single osteometric variables, which may contribute to quick separation of bones which are dismembered, fragmentary, and commingled, as in mass fatalities. For this purpose, the demarking points were calculated for all tibial measurements in this study [Table 2]. The sex of a bone can be classified by measuring a particular variable and comparing it with the corresponding demarking point that has been determined in this study. Further, from a practical standpoint, the results of this study can be utilized to provide means of sex assessment in situations when the available bone is in fragmentary condition or when the sexually dimorphic major bones are missing or when more common multivariate sexing criteria are absent due to incomplete preservation, circumstances that commonly arise as in mass disasters.

  Conclusion Top

The results of the present study clearly reaffirm that tibia is sexually dimorphic. Further, they demonstrate that sexual dimorphism vary between populations, thus confirming that population-specific standards are required to ensure accurate results in sex determination. The study provides sex-specific reference values for tibial dimensions as well as univariate and multivariate discriminant functions, sectioning points, and associated classification rates for the estimation of sex in the contemporary Sri Lankan population. The formula to determine the discriminant score derived using the optimal combination tibial measurements enables sexing of unidentified skeletal remains with reasonable accuracy (80.2%). The standards established in this study can be used to determine sex of contemporary Sri Lankans in conjunction with other sexing evidence available in profiling unidentified remains, especially when the remains are fragmentary or poorly preserved. It is noteworthy that even though males showed significantly larger tibial dimension than females, sex prediction rates achieved for each of these variables are somewhat lower than those obtained by other investigators on other population groups. A major limitation of this study was the smaller sample size, especially for the females.


We acknowledge Dr. Ruwanthi Manawarathna with gratitude for compiling records.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

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  [Figure 1]

  [Table 1], [Table 2], [Table 3], [Table 4]


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