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symmetry - Journal of've Psychology 1994 Vol I08 No 3...

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Unformatted text preview: Journal of 've Psychology 1994. Vol. I08. No. 3. 233-242 Copyri I994 the American Ps I eat Association. Inc. El! by m 08' 07354036915111: Human (Homo sapiens) Facial Attractiveness and Sexual Selection: The Role of Symmetry and Averageness Karl Grammar and Randy Thornhill We hypothesized from the parasite theory of sexual selection that men (Homo sapiens) would prefer averageness and symmetry in women’s faces. that women would prefer averageness and symmetry in men‘s faces, and that women would prefer largeness (not averageness) of the secondary sexual traits of men’s faces. We generated computer images of men‘s and women‘s faces and of composites of the faces of each sex, and then had men and women rate opposite-sex faces for 4 variables (attractive. dominant. sexy. and healthy). Symmetry. averageness. and the sizes of facial features were measured on the computerized faces. The hypotheses were supported. with the exception of the hypothesized effects of averageness of female and male faces on attractiveness ratings. This is the first study to show that facial symmetry has a positive influence on facial attractiveness ratings. Although adult facial attractiveness ratings are replicable, even cross-culturally (see reviews and discussions in Jones & Hill, 1993, and Langlois & Roggman. 1990), there has been considerable controversy around attempts to identify in research the facial features that actually cause faces to be judged attractive or unattractive. As discussed by Langlois and Roggman, studies of individual facial features (e.g., nose size) often have yielded inconsistent results between studies. Faces created by combining individual faces into composites have been shown to be more attractive than the individual faces, which is felt to be a preference for average facial features (Langlois & Roggman, 1990; Symons. 1979). Averageness of faces can be calculated metrically or constructed photogrammetrically. Galton (1879) con- structed composites of individual pictures with the photo- graphic method of simply projecting them one over the other on a negative. According to Galton, this method “enables us to obtain with mechanical precision as general- ized picture; one that represents no man in particular, but portrays an imaginary figure possessing the average features of any given group of man" (1879, p. 341). Indeed. Treu (1914) had the impression that these composites are “sin- gularly beautiful" (p. 441). However, as Alley and Cunning- ham (1991; see also Benson & Perrett, 1991) pointed out. composites are also more symmetrical and rather free of Karl Grannner, Ludwig Boltzmann Institute for Urban Ethology, Vienna. Austria; Randy Thornhill, Department of Biology. Uni- versity of New Mexico. We thank Klaus Atzwanger, John Dittami, Steve Gangestad, Joy Ingram, Km't McKean, and Don Symons for helpful comments on the research. Randy 'l‘homhill thanks Klaus Atzwanger and John Dinami for their hospitality in Vienna. Anne Rice‘s help with the preparation of the article is appreciated. Correspondence concerning this article should be addressed to Karl Grammer, Ludwig Boltzmann Institute for Urban Ethology, Althanstrasse 14, A-1090 Vienna, Austria or to Randy 'I‘hornhili, Department of Biology, University of New Mexico. Albuquerque, New Mexico 87131—1091. Electronic mail may be sent to [email protected] 233 facial blemishes, and therefore one of these traits, rather than averageness per se. may be the cause of the enhanced attractiveness of composites. In addition, Alley and Cun- ningham emphasize that there is considerable evidence (e.g., Keating, 1985) that the most sexually attractive rnale faces are those that show extremes, not averageness. in certain features (e.g., wide jaw), felt to be perceived as dominance indicators. Our study of the cross-sex attractive» ness ratings of faces of both sexes attempts to clarify adult facial beauty by examining the roles of facial symmetry and averageness and their interaction with individual dimen- sions of the face. We use the theoretical framework of sexual selection. The prominent theory of sexual selection is the parasite theory, which proposes that sexual selection favors these traits that advertise resistance to parasites. both microparasites. such as bacteria and viruses, and macroparasites, such as nema- todes and protozoa (Hamilton & Zuk, 1982). There is con- siderable evidence that parasite-resistant organisms win in competition for mates. both in intrasexual competition (usu- ally males competing for females) and in being chosen by the opposite sex and that secondary sexual traits advertise parasite resistance (see partial reviews in Hausfater & Thornhill, 1990, and Zuk, 1992). According to the parasite theory of sexual selection, mate choice decisions include medical examinations of potential mates, and parasite- resistant organisms are preferred because they produce ge- netically resistant offspring or provide better parental care to the offspring. Thus. the parasite theory proposes that beauty of bodily form is perceived as a cue to high parasite resistance by animals in choosing mates. ' Secondary sexual characters are evolved outcomes of sexual selection. There is a link between parasite resistance and secondary sexual traits because sex hormones, eSpe- cially testosterone, lower immunocompetence (Folstad & Karler, 1992; Wedekind. 1992). Whereas high titers of testosterone are necessary for the production of large sec- ondary sexual traits. there will necessarily be a positive correlation between development of secondary sexual 234 KARL GRAMMER AND RANDY THORNHILL traits and the quality of the immune system; only healthy organisms can afford the high testosterone handicap on the inunune system that is necessary for the production of elaborate sexual traits (Folstad & Karter, 1992). The hu- man face contains secondary sexual traits, that is, facial features that develop or increase in size at puberty under the influence of the sex hormones, androgens and estro- gens. Enlarged jaws, chins. and cheekbones in men are examples of facial secondary sexual traits that are influ- enced by testosterone (Enlow, 1990; Tanner, 1978), and Thomhill and Gangestad (1993) hypothesized that large- ness in these features are considered sexually attractive because of advertised innnunocompetence. Genetic diversity may be an important defense against parasites. both at the between-organisms level (i.e., the population level) and at the within-organisms level (see review in Thornlrill & Gangestad. 1993; see also Hamilton, 1982; Tooby, 1982). Within-organisms genetic diversity is dependent on individual genetic heterozygosity. For herita- ble traits that are continuously distributed, heterozygosity correlates positively with average trait expression (Soulé & Cuzin-Roudy, 1982). Facial attractiveness is continuously distributed and probably is heritable (see Thomhill & Gangestad, 1993). This implies that average values of facial features reflect high heterozygosity. Thus, Thornhill and Gangestad hypothesized that facial averageness is attractive because of its association with heterozygosity and thus parasite resistance. This hypothesized pattern may primarily apply to female faces. The intrasexual sexual competition component of sexual selection involving dominance and combat has worked more strongly on males than on females in human evolutionary history (Darwin, 1871; Symons, 19?9), and male faces have multiple. testosterone-facilitated secondary sexual traits (viz, adult male chin, cheekbones, brow ridge, and jaw) that are expected by the parasite theory to have evolved to signal health-related dominance by large- ness. Multiple male facial features in which dominance is signalled by enlarged features may take precedence over averageness in men’s facial attractiveness to women. Symmetry of bilaterally represented traits is positively correlated with heterozygosity in many animals, including humans (see review in Thornhill & Gangestad, 1993). Thus, facial symmetry, like facial averageness. may display un- derlying heterozygosity and parasite resistance (Thornhill & Gangestad, 1993). Also, body bilateral symmetry seems to reflect overall quality of development. especially the ability of an organism‘s developmental machinery to resist genetic perturbations and the numerous environmental pernirba- tions that occur during development (Leary & Allendorf, 1989; Parson, 1990, 1992; see review in Watson & Thorn- hill. 1994). which implies that a symmetrical face displays developmental homeostasis (Thomhill & Gangestad, 1993). The symmetry of bilateral secondary sexual characteristics is more sensitive to environmental perturbations during their development than is that of nonsexually selected bi- lateral traits (see review in Moller & Pomiankowski, 1993). This pattern of greater sensitivity of secondary sexual traits is seen in diverse animal taxa. including nonhuman primates (Manning & Chamberlain, 1993). Parasites have been shown to affect differentially the development of symmetry in organisms’ traits, and the symmetry of secondary sexual traits is most negatively influenced (Mallet, 1992; Mallet & Pomiankowski, 1993; Watson & Thornhill, 1994). Symme- try of facial secondary sexual traits may display irnrnuno— competence because the construction of such traits, espe- cially large ones, is expected to require more sex hormone (Thornhill & Gangestad, 1993). In this article we test the following hypotheses about facial attractiveness, which arise from these considerations: (a) Men prefer averageness and symmetry in women’s faces; (b) women prefer averageness and symmetry in men’s faces; and (c) women prefer extreme expression of the secondary sexual traits of men’s faces. Our approach uses computer techniques to measure composite and indi- vidual faces to assess the influence of averageness, symme- try, and facial dimensions in facial attractiveness judgments. Method Rating Study The raters of computerized faces were 52 female and 44 male college students (Homo sapiens) from a German university. The digitized facial pictures were presented to each subject individu- ally by an interactive computer program. Order effects of presen- tation were controlled by presenting faces to raters in a randomized order. In a first run the program showed all pictlues to each subject sequentially. In a second not the subject rated each picture for 11 adjectives on a rating scale from 1 (least) to 3' (most). The adjectives and their accompanying rating scales were displayed randomly with each picture at the bottom of the computer screen. The subjects were allowed to view pictures as long as they wished. For this study only 4 of the 11 adjectives were used: attractive. dominant, sexy. and healthy. The subjects were trained interac» tively by the computer before making ratings until they were able to solve the rating task. Generation of Individual Test Photographs The photographed subjects were different persons from the raters. Each subject (16 women, age M 1 SD = 26.6 years 1 4.0, and 16 men, age M : SD = 25.3 years i 3.8) was seated upright in a chair with a light source on each side of the face in order to prevent shading. We carefully positioned each subject so that all were looking directly into the camera without any tilt of the head. Distance to the camera was constant. The picture was taken with a high-resolution video camera and digitized on a computer. The picture size was 600 X 570 pixels with a resolution of 72 pixels! 2.54 cm. Faces were standardized in size on a video screen by cross-hairs that marked the horizontal midline of the mouth, the horizontal midline of the inner and outer eye corners, and two vertical lines at the center of the pupil. Faces were adjusted to fit in the cross«hairs with the zoom lens of the video-camera (Figure 1; also see Langlois & Roggman, 1990). Generation of Composites The 16 pictures of each sex were randomly paired. and a blended gray value was calculated for the corresponding pixels of each pair. For this calculation the arithmetic drawing mode blend FACIAL ATTRACTWENESS: SYMMETRY AND AVERAGENESS 235 Figure I. Pictorial of technique used to standardize facial size. of ColorQuickDraw (part of System 7, Apple Computers, Coper- tino, CA) was used. Blend applies the following formula to the two source pixels in a eight-bit drawing environment: New Pixel = Source 1 X Weight *2- 65536 + Source 2 X (l — Weight + 65536) (1} In an eight-bit drawing environment, there are 256 gray values and the weight of each photo was set to 50%. The gray value of the blended pixel corresponds to the arithmetic mean of the gray values of the original pair of pixels. Because the composites created by this technique appear blurred. the original photos were also blurred by randomly introducing pixels. Finally, the gray values of the composites were equalized and adapted in brightness and contrast to the original photos. This procedure presumably controls for the strong effect of skin texture on attractiveness ratings (Benson & Perrett, 1991). This was an important control in our study because we were trying to examine the effect of other factors, especially symmetry, in attractiveness. For each sex this generated eight composites. each constituted from two originals of each sex (Figure 2). By combining these composites randomly in pairs, we created additional composites. The final test set of photographs for each sex consisted of 16 individual faces, 4 pictures combining the faces of four persons. 2 pictures combining eight faces. and one picture combining all 16 individual photos (Figure 3). Thus, the test set had 23 pictures for each sex. Facial Measurements Measurement points. The facial measurements were done on the computer screen with IMAGE 1.41 (shareware. National In- stitute of Mental Health. Bethesda, MD) at 76% of the original photo. This program measures and saves the coordinates of a selected pixel. We used 13 points, which were defined by distinct morphological structures of the face and thus could be identified reliably (Figure 4). The reliability of these points was examined by two methods. First, one of us placed the points on several faces three different times; point locations did not differ by more than one pixel. Second. a person unfamiliar with the research‘s hypoth- eses placed the points on each of 113 faces. and this was repeated by one of us without knowledge of the points placed by the naive assistant. The point locations had very high reliability: The zero- order correlation between the facial symmetries calculated from the points of the two raters was .80 (p < .0001). Points used included the outermost (P1 and P2) and the innermost eye corners (P3 and P4). The points for measuring the cheekbones (PS and P6) were defined as the leftmost and rightmost pixels of the face on a horizontal line beneath the eyes. A comparable definition was made for the points for measuring the nose: P? and P8 describe the leftmost and rightmost point of the nose in the lower nose region. law width (P9 and P10) was measured as face width at the y coordinate of the mouth corners (P11 and P12). A final point was the chin boss (P13), or the lowest point of the chin curvature. In persons with a W-shaped chin boss, the middle point was used. Calculation of asymtry. We only dealt with horizontal asymmetry in this study. Facial asymmetry was calculated in two ways. Overall facial asymmetry (FA) was based on the sum of all possible nonredundant differences between the midpoints of six horizontal lines between the following pairs of points: Pl-PZ. P344. PS-Po, PT-PS, P9—P10, and P11-P12. These six lines were designated D1. D2. D3, D4, D5, and D6. respectively (Figure 5). The midpoint of each line was calculated with the formula. ([Left Point - Right Point] + 2) + Right Point. On a perfectly symmetrical face. all midpoints lie on the same vertical line. and the sum of all possible nonredundant midpoint differences is zero. The second measure of facial symmetry. which we call central facial asymmetry (CFA), focuses on the differences between mid- points of adjacent lines. especially in the center of the face. CFA corresponds to the sum of the differences of the midpoints of the lines D1 and D2, D2 and D3. D3 and D4, D4 and D5. and D5 and D6. In our analysis we assume for simplicity that facial symmetry deviations are linear rather than nonlinear. Calculation of averageness. Averageness of a face was deter- mined in the following way. First, the mean lengths of each of the lines D1 through D6 were calculated for the 16 normal photos of each sex. Averageness of the vertical dimension for each sex was Figure 2. A two-face composite (center), with the original photographs on either side. 236 KARL GRAMMER AND RANDY THORNHILL Figure 3. Sixteen-face composites of each sex. calculated by the distance between P13 and the midpoint of DI and the distance between P13 and the midpoint of D5. Then the absolute differences between these means for each sex and the length of each of the same lines in each individual face of the same sex were summed. Calculation of metric facial dimensions. The sizes of nine facial features were calculated: distance between outer eye corners (DI). distance between inner eye corners (D2). mean eye size ([P3 — Pl + P2 — P4] + 2), nose width (D4), facial width at cheekbones (D3). mouth width (D5). and jaw width (D6). In addition. we calculated average cheekbone prominence. (P6 - P5 + P6 - P10) + 2. Cheekbones are more prominent when values are positive than when they are negative. Finally. lower face proportions describe the relation between face length and jaw width. Midpoint DI - Pl3 + Do. A high value indicates a long face with a narrow jaw; a low value indicates a face with a wide jaw. Statistical Tests All statistical significance levels reported in this study are two~tailed. All ratings and means of ratings for the faces follow normal distributions. The .05 level is the critical level for statistical significance. Results Composites Versus Nomafs: Attractiveness The mean ratings of composites versus normal faces of each sex by opposite-sex raters were compared with t tests (Table 1). Female composites were judged significantly more attractive and sexier than normal photos. Also. female composites were judged significantly less dominant than normal female faces. There was not a significant difference in the health ratings of female composite versus normal faces. but female composites were rated healthier ( p = .10). Normal male faces were rated as significantly healthier, sexier, and more dominant than composite male faces; the same pattern is seen for the adjective attractive. and this just missed statistical significance (p = .06). Thus, making Figure 4. The landmark points used for facial measurements. FACIAL ATTRACT IVENESS: SYMMETRY AND AVERAGENESS 237 Figure 5. The lines used for facial measurements. composites from individual female faces yielded pictures that were more attractive than the originals, but the reverse was the case for male photos. It is possible that normal faces of males were rated more positively because they more frequently contained more extreme values in facial features. Indeed, male composites were rated as less dominant. The ages of normal subjects and the mean attractiveness ratings of their faces showed statistically insignificant cor- relations in each sex (16 females. r = .l3, p > .5, and 16 males, r = .22. p > .05). Composites Versus Normals: Averageness and Symmetry As pointed out by Alley and Cunningham (1991), in comparison with normal photos, composites are more aver- age in facial features but also show higher values in other traits. such as symmetry and smoothness of complexion (also Benson 8!. Perrett, l991). Thus. we measured metric averageness...
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