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  • The Internet Journal of Biological Anthropology
  • Volume 4
  • Number 1

Original Article

Face Shape Differences in Selected Indigenous Peoples’ Groups in Mindanao, Philippines

C Demayo, M Torres, P Olvis, N Manlegro

Keywords

discriminant analysis, fluctuating asymmetry, geometric morphometrics, indigenous groups, non-metric multidimensional scaling

Citation

C Demayo, M Torres, P Olvis, N Manlegro. Face Shape Differences in Selected Indigenous Peoples’ Groups in Mindanao, Philippines. The Internet Journal of Biological Anthropology. 2009 Volume 4 Number 1.

Abstract

The face shape of individuals belonging to seven different indigenous groups (IG) from Mindanao was studied using geometric morphometric analysis. A total of 496 images of the face (217 males and 279 females) were obtained from the Bagobo, Bilaan, Higaunon, Kalagan, Maranao, Subanen and Talaandig groups. Forty three manually defined landmarks done in triplicates generated relative warp scores which were subjected to different statistical tools in order to compare face shapes and to examine relatedness between IGs. Non-metric multidimensional scaling and discriminant analysis showed significant variation between IGs however, patterns of clustering were different in male and female populations. Procrustes ANOVA showed that sides, individual, and interaction in all IGs of both populations had P-values of <0.000, which is indicative of the presence of asymmetry, distinctness of the face shape each individual, and a significant variation among IGs in both male and female populations. The interaction of sides and individual p-value showed high fluctuating asymmetry (FA) for all IGs regardless of gender. This may be attributed to the intermarriage practices between individuals of same IG which are still applicable to some groups nowadays. In conclusion, each IG possesses distinct face shape but individuals belonging to each group have high degree of variation.

 

Introduction

Face analysis had been quite important in studies of distinguishing pure and mixed races1 and in health-related fields 2-6. The human face can provide demographic information, such as gender and ethnicity7. Even though genetic differences among human groups are relatively small, these differences nevertheless can be used to situate many individuals within broad, geographically based groupings8. Many argued that each race has different gene pools and different subgroups may exhibit different behaviors, peculiarities, and anthropometric characteristics 9-19 thus, it is important to explore other tools in studying morphological traits that can be used to differentiate human groups especially the face. In the past, facial anthropometry has been successfully utilized for forensic purposes 18, 20-22.

Analysis of the face is important especially for facial recognition, historical research, investigations, telecommunications or even games. Facial data is commonly obtained by direct anthropometric measurements23. Landmarks have been used in qualifying cranial variation23-26 like measuring and comparing linear, angular and surface contours and proportions in people. For many years 47 landmark points were identified to describe the face23,25-26. With the advances in computational biology and image analysis, several other methods have evolved to detect faces and find the facial features correctly27. Some of these methods include knowledge based 28, invariant feature29, template matching32-33 and appearance based34-37. The new method of ‘geometric morphometrics’ (GM), an adaptation of multivariate statistics and graphics to the study of phenotypic variation, has proved to be useful for the detection of form changes and is very useful in understanding shape variations in living organisms thus was used in this study. In this method, the relative locations of a set of individually identified points or “landmarks” are identified as biometric variables, the ‘shape coordinates’, that can then be regressed one by one on the factors that cause them or the features of the systems they are presumed to affect. The methodological approaches of GM make use of two-dimensional or three-dimensional coordinate data to describe size and shape at the same time38-42. The statistical properties of GM have been proven superior to those of distance-based or angle-based methods43-45 and the supply graphics are far more legible and interpretable to the applied biologist, the tools of GM was therefore used in describing group differences in selected group of indigenous peoples (IP’s) groups in the Philippines.

The Philippines is a mountainous archipelago that comprises 7,100 islands grouped into three regions: Luzon, Visayas, and Mindanao. It is a home to a very diverse collection of indigenous ethnic minorities 46 although the Filipino people in general are basically of Malay stock47. Approximately 10 to 15 percent of the country’s population of 96 million is comprised of different indigenous groups48. Indigenous peoples are defined as the descendants of the original inhabitants of the archipelago who retained their own customs, traditions and life ways despite colonization49. Of all the Philippine islands, Mindanao has the largest concentration of indigenous peoples, reaching to about 61 percent of the total indigenous peoples population in the country49-50. The introduction of a different cultural system led to the disintegration of indigenous society49. However, the indigenous groups in general still have a rather traditional way of living51 including endogamous marriages thus are fit to be the subject of anthropometric investigations.

The study aims to compare face shape among and within the seven selected indigenous groups in Mindanao and to examine the extent of variation exhibited among these populations using geometric morphometric analysis. It is hoped that the comparison of face shape among and within the seven indigenous groups will provide information as to the degree of relatedness and differences among these groups. The study focuses only in examining the extent of difference and similarities of face shape of individuals belonging to the seven selected indigenous groups in Mindanao, Philippines. The groups included in this study are the Bagobo, Bilaan, Higaunon, Kalagan, Maranao, Subanen, and Talaandig.

Methodology

Image Acquisition and Processing

We recruited a total of 496 male and female members of the different indigenous peoples’ groups to participate in this study. Front view images of the face with neutral expression, closed mouth and without deformations were captured using a digital camera. These images were particularly sampled from both male and female individuals belonging to the seven selected indigenous groups, namely the Bagobo, Bilaan, Higaunon, Kalagan, Maranao, Subanen, and Talaandig. Table 1 summarizes the number of samples gathered from each group and specifies the exact sampling regions within the island of Mindanao.

Figure 1
Table 1. Number of image samples acquired from the seven indigenous groups and their respective sampling sites

Forty three (43) anatomical landmarks were defined in each image in regions that characterize the morphological difference in the human face structure. The manual input of landmarks was done in triplicates and the Cartesian coordinate scores of these landmarks were recorded using the tpsDig 2.10 program43. The landmark locations in the face are illustrated in Figure 1 below and the details are summarized in Table 3. Each landmark was classified into type I landmark, a point that occurs at joins of tissues or bones, or type II landmark, a point defined by local properties such as maximal curvatures.

Figure 2
Figure 1. Location of anatomical landmarks of the face.

Figure 3
Table 2. Anatomical landmarks of the face

Geometric Morphometric Analysis

In order to compare face shape, standard procedures of geometric morphometrics were applied to the samples. These include Procrustes superimposition and thin-plate spline interpolation which eliminate scale, position and orientation biases and create maximal fit of homologous landmarks.

Variables describing shape variation in the datasets based on 2D coordinates were calculated and relative warp scores were then obtained using tpsRelw 1.4544. The scores were used to generate the XY plot of the relative warps in a Procrustes coordinate using the paleontological statistics software (PAST)52. This process gives picture to the distribution of the individuals of the entire population, which was further visualized in the deformation grid in order to explain shape patterns as we move along axes.

A consensus configuration of the face shape was also generated using tpsSpline45. The same program was used to produce the mean shapes of each indigenous group which were warped consorting to the consensus configuration. This aids in the visualization of variation of each group relative to the entire population.

Statistical Analyses

The relative warp scores generated were subjected to various statistical tools in order to further analyze the face shape of the indigenous groups. But first, scores of the images were symmetrized by getting the average shape of the left and right sides of each image using the superimposition method. SPSS 13.053 was the software used for this procedure.

The process of symmetrization eliminates asymmetry biases, thus eliminating environmental factor as variable that determines face shape other than the developmental or genetic component. In this way, indigenous groups can be compared to each other without having to face the problem in difference of environmental factors.

The symmetrized data were subjected to non-metric multidimensional scaling (NMDS), a method for visualizing dissimilarity in data. It measures similarity or dissimilarity of each data instead looking at its characteristic54. The distances were computed in Euclidean similarity measure and the stress value which determines the significance of variation between groups was obtained using the Shepard plot. This technique determines if the variation in each indigenous group is significant, particularly a stress value below 0.05.

The data also underwent cluster analysis in order to further sort the groups into clusters that could explain which indigenous groups are most closely related to each other. A Bootstrap value of 50 or greater denotes significant grouping. Cluster analysis specifically, is just an exploratory data analysis that sorts different objects into groups in a way that the degree of association is maximal55, that is why NMDS was applied first to determine the presence of significant variation between the pre-determined before sorting them out into the most related indigenous groups.

Procrustes ANOVA

Procrustes ANOVA was used to study left-right variation in the face shape. The deviations of the configurations from the consensus are broken down according to the main effects of individuals, sides (for object symmetry), and individuals-by-side interaction.

The main effect of individuals represents the inter-individual variation, that is, variation present within an indigenous group. Sides on the other hand, represent the asymmetric variation called directional asymmetry (DA), that is, one side is systematically different from the other one. The individuals-by-side interaction quantifies the asymmetric variation within individuals called fluctuating asymmetry (FA), small random differences between the left and right sides in bilateral traits56.

Discriminant Analysis

This technique was used to determine which variables discriminate between the indigenous groups in male and female populations57. The purpose of employing discriminant analysis is to see the relatedness among indigenous groups by basing the percentage of original group cases which are correctly classified. If a significant number of individuals are correctly classified to a group, the classification table will yield a high percentage of correct estimate which is 70 percent or higher58.

Results and Discussion

Canonical variate analysis showed significant differences between the indigenous Peoples’ groups (Fig. 2). The Procrustes ANOVA results show extremely significant asymmetric variation within each group although not all individuals exhibit face asymmetry (Table 3). While variability existed within each group as revealed by procrustes ANOVA, minimal overlapping of scores among indigenous groups was observed, indicating differences in face shapes between groups.

Figure 4
Figure 2. Distribution of the indigenous peoples groups (A) female and (B) male along the first two canonical variate axes.

Figure 5
Table 3. Procrustes ANOVA results

The 43 manually defined landmarks in the 496 images from the Bagobo, Bilaan, Higaunon, Kalagan, Maranao, Subanen and Talaandig groups generated relative warps scores presented as scatter plot (Figure 3). RW1 shows a shift of face shape from a more pronounced forehead to a more pronounced jaw moving from left to right. Likewise, RW2 shows a shift of an elongated to a broader face shape going from top to bottom of the diagram.

Grids generated from the relative warp scores, showed the conformation of face shape of each group with respect to a consensus configuration (Fig. 3A, B, 4A, 5A). In the female population (Fig. 3A, 4A), the Bagobo females exhibit slimmer nasal area compared consensus shape. The Bilaan females show a wider jaw line, thinner lips and a horizontally compressed nose. The Higaunon females show a rounder face and wider set of eyes. The Kalagan females exhibit a more elongated face shape with prominent cheekbones. The Maranao females has broader face than when compared to the rest of the females. The Subanen females has the closest face configuration that of the consensus. The Talaandig females generally has broader forehead than their jaw line.

It is important to note here that the grids only show differences in traits which are visibly warped from the consensus. Thus, the application of non-metric multidimensional scaling and cluster analysis is important to provide a statistical basis in describing the degree of similarities and differences exhibited by the indigenous peoples’ groups. Fig 4B shows the minimum spanning tree of female groups generated in Euclidean distance by means of non-metric dimensional scaling. The stress value of 0.03476 indicates a significant level of variation among these groups. Cluster analysis (Fig. 4C) showed five significant groupings in the female population which are indicated by Bootstrap values greater than 50. Subanen, Bilaan, Kalagan, and Maranao groups are significantly different from the rest of the female population. The Higaunon, Bagobo, and Talaandig females have certain degree of similarities as shown by a low bootstrap value..

Figure 6
Figure 3. Relative warps of (A) female and (B) male populations obtained from the seven different indigenous groups

Figure 7
Figure 4. Comparison of face shape of the female population: (A) Mean shapes of the face of the different indigenous peoples groups derived from relative warp analysis; (B) Non-metric multidimensional scaling with stress value of 0.03476; (C) Dendogram based on Euclidian distances computed from relative warp scores.

For the males (Fig. 3A and B, 5B), the grouping patterns vary from that of the females. While significant variations exist among indigenous groups (i.e. stress value = 0.3476) (Fig. 5B), two major groupings can be observed - the Maranao-Bagobo-Bilaan cluster and Kalagan-Subanen-Higaunon-Talaandig cluster (Fig. 5C). The Maranao, Bagobo and Bilaan males showed more similarities in the face shape that are different from those of the Kalagan, Subanen, Higaunon and Talaandig male cluster. Based on the RW grids (Figs. 3A, 5A) specific differences can be observed among these indigenous peoples’ groups. The Higaunon males possess the thinnest lips. The Talaandig males exhibit the broadest face shape. The Bagobo, Bilaan and Subanen males more or less share similar configurations and also closely resemble the consensus configuration. The Kalagan shows a very distinct configuration, showing a prominent cheekbone.

Figure 8
Figure 5. Comparison of face shape of the female population: (A) Mean shapes of the face of the different indigenous peoples groups derived from relative warp analysis; (B) Non-metric multidimensional scaling with stress value of 0.03476; (C) Dendogram based on Euclidian distances computed from relative warp scores.

Discriminant analysis showed more than 90% of original group cases were correctly classified (Tables 4 and 5) indicating that the different indigenous peoples’ groups were distinctly different from each other. While many studies have applied various anthropometric methods in describing human populations19-26, results of this study showed that geometric morphometrics is as important in providing a quantitative description of the nature of face shapes and could be used to fingerprint distinct populations, race or ethnic groups.

Figure 9
Table 4. Reclassification of the female indigenous peoples groups.

94.4% of original grouped cases correctly classified

Figure 10
Table 5. Reclassification of the male indigenous peoples groups.

91.1% of original grouped cases correctly classified

Acknowledgements

We thank all of the men and women of the different indigenous peoples’ groups who participated in this study. Likewise, we would like to extend our heartfelt gratitude to the tribal leaders who facilitated the possible participation of the members in their communities. The technical assistance of Mr. Muhmin Michael Manting is also greatly appreciated.

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Author Information

Cesar G. Demayo
Professor of Biology, Department of Biological Sciences, MSU-Iligan Institute of Technology

Mark Anthony J. Torres
Assistant Professor of Biology, Department of Biological Sciences, MSU-Iligan Institute of Technology

Paul Rulete Olvis
Instructor, Natural Sciences and Mathematics Division, University of the Philippines Visayas Cebu College

Nadia Manlegro
Medical Student, College of Medicine, University of the Visayas

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