Journal of Evolutionary Psychology, 2012, 163–175
DOI: 10.1556/JEP.10.2012.4.1
1789–2082 © 2012 Akadémiai Kiadó, Budapest
THE MYTH OF HIDDEN OVULATION:
SHAPE AND TEXTURE CHANGES IN THE FACE
DURING THE MENSTRUAL CYCLE
E. OBERZAUCHER
1,
, S. KATINA DR.2
, S. SCHMEHL MAG.3
,
I. HOLZLEITNER MAG.4
, I. MEHU-BLANTAR MAG.5,*
1
University of Vienna Vienna
Abstract. In recent years, evidence has been gathered indicating increased attractiveness of female
faces at the point of ovulation. In this paper, we asked what changes in facial appearance occur
during menstrual cycle that lead to this shift in attractiveness. We analysed facial photographs
of 20 young women with a normal cycle. We found evidence for textural changes, as well as
shape changes that might account for the ovulatory peak in attractiveness. Generally, facial shape
at ovulation is perceived as more attractive–and ovulating women are perceived as more attractive
the closer their face shape is to the “ovulation shape”. These findings support the hypothesis that
attractive signals might be rooted in signals of fertility.
Keywords. ovulation, facial attractiveness, symmetry, geometric morphometric methodology
INTRODUCTION
The fact that human females do not appear to show any visible signs of ovulation –
unlike other primates–has led to the development of a rich theoretical body of work
attempting to explain this phenomenon in terms of evolutionary constraints.
Has hidden oestrus evolved to trick males into forming a pair bond (ALEXANDER
and NOONAN 1979)? Following this line of reasoning, males unaware of females’
fertility would remain bonded to ensure impregnation and paternity; a female
providing clues to her ovulation might risk losing male investment (TRIVERS
1972). Or, quite the opposite, has hidden oestrous arisen to increase paternal insecurity
to allow females to “escape the negative consequences of being pawns in marriage
games” (GRAY and WOLFE 1983)? Once monogamy is established, an optional
female strategy would be to copulate outside their long-term relationships,
thus obtaining superior genes for their offspring while ensuring paternal investment
by her long-term partner (BELLIS and BAKER 1991). Indeed, increased extra-pair
copulations coincide with an increase in females’ self-reported arousal to sexual
*
Address for correspondence: 1
E. OBERZAUCHER, University of Vienna Vienna, AUSTRIA,
E-mail: elisabeth.oberzaucher@univie.ac.at. 2
S. KATINA DR., Department of Anthropology and
Department of Mathematics and Statistics, Faculty of Science, Masaryk University, Brno, Czech
Republic, E-mail: stanislav.katina@gmail.com 3
S. SCHMEHL MAG., University of Vienna, Department
of Anthropology, E-mail: susanne.schmehl@univie.ac.at. 4
I. HOLZLEITNER MAG., University
of Vienna, Dept. of Anthropology, E-mail: iris.holzleitner@univie.ac.at. 5
I. MEHUBLANTAR
MAG., University of Vienna, Dept. of Anthropology, E-mail: womme@gmx.at
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stimuli (LUSCHEN and PIERCE 1972), peaks in sexual receptivity (ADAMS, GOLD
and BURT 1978), and an increased amount of attraction to, and fantasies about, men
who are not their primary partners. Yet another hypothesis speculates that signals of
oestrus might have been reduced to counter infanticide by increased paternal uncertainty
(HRDY 1981). Unfortunately, these theories cannot be tested empirically.
In recent years, evidence has accumulated indicating that women’s mate preferences
change during ovulation (ROBERTS et al., 2004). In this context, the term
hormone-mediated adaptive design has been introduced: In their fertile phase,
women prefer more masculine features than in their non-fertile phase (JOHNSTON et
al., 2001). In addition, male body odour smells most intense and least unpleasant to
women at ovulation (DOTY et al., 1975; SINGH and BRONSTAD 2001).
Female behaviour changes, too: Walking style becomes more feminine
(GRAMMER et al., 2003), and women dress more ‘sexily’ during the fertile window
of their cycle (GRAMMER, RENNINGER and FISCHER 2004). Not only do women behave
differently, they are also perceived differently: Several recent studies show
that women are judged to be more attractive when in their fertile phase of the menstrual
cycle (ROBERTS et al., 2004; LAW SMITH et al., 2006).
The fact that women lack ostentatious sexual swellings does not imply that
women do not signal their fertility status. Both the sexual swellings in primates, as
well as the shifts in human behaviour and facial appearance during ovulation, apparently
make females more attractive to males. Thus, we think the term ‘concealed
ovulation’ to be inappropriate and misleading.
The fact that women are most attractive in the fertile window of their cycle
(ROBERTS et al., 2004; LAW SMITH et al., 2006) causes us to question whether we
have been approaching the whole topic from the wrong end: Traits associated with
attractiveness could well be perceived as attractive because they are signals of ovulation.
Instead of ovulation being hidden in humans, signals of ovulation might have
spread over the whole menstrual cycle. Thus, fertility signals may have become part
of overall attractiveness.
Female attractiveness is characterised by a number of aspects, such as reduced
fluctuating asymmetry, markers of hormone levels, skin coloration, and neoteny
markers. According to the parasite theory of sexual selection (HAMILTON and ZUK
1982), the absence of anomalies in ontogeny shows ‘developmental stability’: The
inability to cope with environmental and genetic perturbations is for example reflected
in elevated levels of fluctuating asymmetry (GANGESTAD, THORNHILL and
YEO 1994; GRAMMER and THORNHILL 1994; THORNHILL and MOLLER 1998), a
symmetric face presumably indicates high immune competence (THORNHILL and
GANGESTAD 1993). Preferences for averageness have been linked to heterozygosity,
which represents a larger buffer against pathogens.
In addition, immune competence is highly relevant because the steroid reproductive
hormones responsible for the development of attractive, secondary sexual
traits, may negatively affect immunological functions (FOLSTAD and KARTER
1992). Thus, markers developed with the help of high sex hormone levels may sig-
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nal the ability of the immune system to deal with the deteriorating effect of oestrogen
(SERVICE 1998). The display of handicaps such as hormone markers can signal
the ability to meet the costs imposed by this handicap. As another example, ZAHAVI
and ZAHAVI (1997) discuss red cheeks and lips. The red colouring is a result of peripheral
blood circulation below the skin, which cannot be kept up in a cold environment
or during times of illness.
Skin texture is also known to affect the attractiveness of faces, and it too seems
to signal fitness. ROBERTS et al., (2005) found skin homogeneity and attractiveness
to be positively associated with heterozygosity in MHC-genes. MATTS et al., (2007)
found that a different skin can make the same face look 20 years older. Skin darkens
in pregnancy, under the influence of hormonal contraception, which has been
taken to assume that paler skin–found to be attractive in previous studies–might be
an indicator of neoteny (FROST 1988).
JONES (1996) showed that female faces exhibiting certain–neotenous–facial
proportions–small lower face, lower jaw and nose, and large lips–are perceived as
more attractive. The strong association between youth and fecundity in adult females
supposedly led to the male preference for facial markers of high, age-related
fecundity. Women’s faces are attractive when they possess small lower facial features,
especially a gracile jaw, and large lips, which manifest under the influence of
oestrogen. These features may also be signals of nulliparous status (SYMONS 1995).
In the present study we address the question why ovulating women are perceived
as more attractive. Can increased attractiveness at ovulation be linked to
measurable parameters? And, are those parameters similar to those already known
to be positively linked to female attractiveness?
METHODS
20 females aged 19 to 31 (23.35 ± 3.15) were photographed every day at the same
time throughout an entire cycle after giving informed consent. Ovulation was detected
using ovulation kits. For this investigation we used the photo of the first day
of ovulation and a luteal picture from 14 days after ovulation.
In a two-alternative forced choice task, 15 men (aged 24.20 ± 4.57) and 10
women (aged 26.80 ± 4.49) decided between ovulatory and luteal images, which of
the images was better suited to the given items (attractive, healthy, sexy, sociable,
trustworthy, young, and likeable). OVULATORY and LUTEAL images were presented
simultaneously on a computer screen in random order.
The statistical analyses were performed in R software (R DEVELOPMENT,
CORE TEAM 2010). The results of hypotheses testing were considered as statistically
significant at p-value<0.05. All p-values were calculated by permutation
framework (number of permutations = 5000).
The odds that the face in ovulatory state was rated more positively for a particular
item was tested by a permutation Chi-square test. The null hypothesis is as
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follows: odds are less or equal than 1, where 1 means that ovulatory and luteal state
were chosen with the same probability.
We analysed the morphological changes using Geometric Morphometrics. On
the facial photographs, we measured Cartesian coordinates of 46 anthropological
landmarks and 26 semi-landmarks (6 on the upper and lower outline of each eyebrow,
7 on each half of the lower face, from the ear lobe to the turning point of left
and right chin, Table 1, Fig. 1).
Table 1. Definition of (semi)landmarks; left/right orientation – with respect to the observer.
*
excluded from the analysis
1*
Forehead right The right corner of the forehead, located in the hairline
2*
Trichion The mid point of the hairline
3*
Forehead left The left corner of the forehead, located in the hairline
4 Superciliare laterale right The most lateral point of the right eyebrow
5 Upper eyebrow right
6 Upper eyebrow right
7 Upper eyebrow right
Semilandmarks
8 Superciliare mediale right The most medial point of the right eyebrow
9 Lower eyebrow right
10 Lower eyebrow right
11 Lower eyebrow right
Semilandmarks
12 Superciliare mediale left The most medial point of the left eyebrow
13 Upper eyebrow left
14 Upper eyebrow left
15 Upper eyebrow left
Semilandmarks
16 Superciliare laterale left The most lateral point of the left eyebrow
17 Lower eyebrow left
18 Lower eyebrow left
19 Lower eyebrow left
Semilandmarks
20 Exocanthion right The outer corner of the right eye fissure where the eyelids meet
21 Iris top right
The highest point of the right iris; if not visible, point is located
on the approximated elongation of the circumference of the
pupil
22 Endocanthion right
The right inner corner of the right eye fissure where the eyelids
meet
23 Iris bottom right
The lowest point of the right iris; if not visible, point is located
on the approximated elongation of the circumference of the
pupil
24 Iris laterale right The most lateral point of the right iris
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Table 1. (Continue)
25 Pupil right The mid point of the right pupil
26 Iris mediale right The most medial point of the right iris
27 Endocanthion left The inner corner of the left eye fissure where the eyelids meet
28 Iris top left
The highest point of the left iris; if not visible, point is located
on the approximated elongation of the circumference of the
pupil
29 Exocanthion left The outer corner of the left eye fissure where the eyelids meet
30 Iris bottom left
The lowest point of the left iris; if not visible, point is located
on the approximated elongation of the circumference of the
pupil
31 Iris mediale left The most medial point of the left iris
32 Pupil left The mid point of the left pupil
33 Iris laterale left The most lateral point of the left iris
34 Alare origin right
The most inner point of the right ala of the nose; or elongation
of the nasolabial folds on right ala of the nose
35 Alare right The most lateral point on the right nasal ala
36
Columella apex (columella
breakpoint, nostril top
point) right
(The most anterior or) the highest point on the columella crest
at the apex of the right nostril
37 Subnasale
On the local midline of the junction formed by the lower border
of the nasal septum (the partition that divides the nostrils)
and the cutaneous portion of the upper lip
38
Columella apex (columella
breakpoint, nostril top
point) left
(The most anterior or) the highest point on the columella crest
at the apex of the left nostril
39 Alare left The most lateral point on the left nasal ala
40 Alare origin left
Most inner point of the left ala of the nose; or elongation of the
nasolabial folds on left ala of the nose
41 Cheilion right
The right corner of the mouth where the outer edges of the upper
and lower vermilions meet
42 Upper lip right
The point in the middle of Labiale superius (44) and right
Cheilion (41)
43 Crista philtri right
The point on the right crest of the philtrum, i.e. the vertical
groove in the median proportion of the upper lip, located on
the vermilion border
44 Labiale superius
The philtrum mid point, located on the vermilion border of the
upper lip
45 Crista philtri left
The point on the crest of the left philtrum, i.e. the vertical
groove in the median proportion of the upper lip, located on
the vermilion border
46 Upper lip left
The point in the middle between Labiale superius (44) and left
Cheilion (47)
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Table 1. (Continue)
47 Cheilion left
The left corner of the mouth where the outer edges of the upper
and lower vermilions meet
48 Lower lip left
The point in the middle between Labiale inferius (49) and left
Cheilion (47)
49 Labiale inferius The mid point of the vermilion border of the lower lip
50 Lower lip right
The point in the middle between Labiale inferius (49) and right
Cheilion (41)
51 Cleft right
The point between Stomion (52) and right Cheilion (41), exactly
on the right cleft between upper and lower lip
52 Stomion The mid point of the labial fissure
53 Cleft left
The point between Stomion (52) and left Cheilion (47), on the
left cleft between upper and lower lip
54 Zygion right The most lateral point on the right zygomatic arch
55 Otobasion inferius right
The lowest point of attachment of the right ear lobe to the
cheek, which determines the lower border of right ear insertion
56 Lower face right
57 Lower face right
58 Lower face right
59 Lower face right
60 Lower face right
61 Lower face right
62 Lower face right
Semilandmarks
63 Gnathion The turning point of the right and left side of the chin
64 Lower face left
65 Lower face left
66 Lower face left
67 Lower face left
68 Lower face left
69 Lower face left
70 Lower face left
Semilandmarks
71 Otobasion inferius left
The lowest point of attachment of the left ear lobe to the cheek,
which determines the lower border of left ear insertion
72 Zygion left The most lateral point on the left zygomatic arch
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Fig. 1. Design of the (semi)landmarks (left and middle; numbers correspond to Table 1) and
statistically significant (semi)landmarks (•: p-values < 0.05, not adjusted by any multiple post-hoc
correction, (semi)landmarkwise matched-pair Goodall F-test)
We calculated the Procrustes shape coordinates using a Generalized Procrustes
Analysis (BOOKSTEIN 1991). First, the centroid of each form was found, and its root
mean square distance to the (semi) landmarks computed; this is called centroid size
(CS). Second, the forms were re-scaled to CS = 1, the centroids superimposed, and
the forms rotated around the common centroid, until the sum of squared distances
between corresponding (semi) landmarks was a minimum over all such rotations.
This resulted in Procrustes shape coordinates. Equidistantly marked semi-landmarks
were slid with respect to reference curves using bending energy. Sliding was performed
iteratively on tangents, in a locally linear way, to get geometrically homologous
semi-landmarks on the curves.
Hypotheses about mean shape difference between ovulatory and luteal state
were tested by permutation matched-pair Goodall F-test and, additionally, for visualisation
purposes, by pointwise–(semi) landmarkwise–matched-pair Goodall Ftest,
where p-values were not adjusted by any multiple post-hoc correction. The aim
of pointwise statistical inference was only to visualize the statistical and biological
signal present in the data. Additionally we investigated fluctuating asymmetry in
both states (luteal and ovulatory) separately by permutation one-sample MardiaBookstein-Moreton
test (MARDIA, BOOKSTEIN and MORETON 2000). The level of
asymmetry was determined as the sum of squares of differences between original
and reflected forms.
With a shape space matched-pair Principal Components Analysis (PCA, also
called relative warp analysis, RWA)–1) PCA in full shape space, 2) PCA in subspace
of global bending patterns, and 3) PCA in subspace of local bending patterns–
of the covariance matrix of approximate tangent Procrustes shape coordinates (centered
Procrustes shape coordinates, Procrustes fit coordinates), variability was decomposed
into orthogonal components and, subsequently, these components of
shape variation were examined (BOOKSTEIN 1991) and the main direction and size
of the shape changes between luteal and ovulatory state were identified. In the sub-
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space of the first two PCs, permutation one-sample test was used to test if PC scores
were significantly different from zero (if yes, we rejected the null hypothesis that
ovulatory and luteal faces do not differ in the particular PC subspace).
With a symmetrical two-block Partial Least Square Analysis (PLS) (BOOKSTEIN
1994; Sampson, STREISSGUTH, BARR and BOOKSTEIN 1989) we investigated
the correspondence between the set of centered Procrustes shape coordinates (block
1), and attraction variables and degree of fluctuating asymmetry (block 2). The multivariate
association between both blocks can be expressed by means of Pearson
product-moment correlation coefficient of singular warp (SW) scores.
Both PCA and PLS find low-dimensional linear combinations of highdimensional
measurements by adapting one single singular value decomposition of
common and cross-block covariance matrix, respectively. The biologically meaningful
signal was investigated in the first two principal components (PCs) and the
first SW.
The visualisation of shape change from source to target was done by Thin
Plate Spline (TPS) deformation grids (BOOKSTEIN 1991). The Procrustes mean
shape was chosen as a reference (source) form (Fig. 1). To quantify mean shape differences,
luteal and ovulatory mean shapes were chosen as targets. In both, PCA
and PLS, the matrix of scaled eigenvectors (PC loadings and singular vectors, resp.)
was used the same way. If necessary, TPS deformation grids were extrapolated
(magnified) in a particular direction to ease the visualisation.
The analysis of skin texture homogeneity was done with co-occurrence matrices
from a 50×50 pixels sized patch from the left cheek (HARALICK, SHANMUGAM
and DINSTEIN 1973). The co-occurrence matrix allows measuring the spatial interrelationships
of grey tones in a textural pattern and thus provides objective measurements
for skin texture. The colour characteristics in skin textures where calculated
in a HSV-colour space as an average over the whole patch. These procedures
have been employed successfully in previous studies (FINK, GRAMMER and MATTS
2006; GRAMMER and THORNHILL 1994; MATTS, FINK, GRAMMER and BURQUEST
2007).
Hypotheses about mean differences between ovulatory and luteal state in particular
texture variables were tested by permutation matched-pair Student’s t-test.
The null hypothesis was one-sided with the mean difference being less or equal to
zero.
Reliability of landmarks was calculated for both x- and y-coordinates simultaneously
as total variance (trace of covariance matrix of particular landmark). It reflects
intra- and inter-observer error scaled by sample total variance (n = 20). Median
intra-observer error was 3.60%, median inter-observer error 6.61%. Less reliable
were, not surprisingly, Type II and III landmarks (Bookstein, 1991), namely
forehead*
, trichion*
, superciliare, alare, alare origin, columella apex, iris mediale
and laterale, and gnathion (*
excluded from the analyses).
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RESULTS
Ovulatory faces were chosen significantly more often as being more attractive,
healthy, sexy, sociable, trustworthy, young, and likeable than luteal faces (Table 2).
Table 2. Frequencies of ovulatory face picture being chosen in the forced choice task
item
absolute
frequency
relative frequency in % ±
sd
Chi-square
stat
p-value
attractive 288 57.60 ± 2.21 11.25 < 0.001
healthy 306 61.20 ± 2.18 24.64 < 0.001
sexy 301 60.20 ± 2.19 20.40 < 0.001
sociable 273 54.60 ± 2.23 4.05 0.022
trustworthy 275 55.00 ± 2.22 4.80 0.014
young 293 58.60 ± 2.20 14.45 < 0.001
likeable 282 56.40 ± 2.22 7.94 0.002
Ovulatory and luteal faces were significantly different in PC2 of full shape
space (p = 0.002), and in PC1 and PC2 of local bending patterns (p = 0.001 and p =
0.032, resp.). In all PCs (see Fig. 2), the lower face is more robust in the luteal
phase, the nose is broader, and the eyebrows are more pronounced; in the ovulatory
phase, the lips are fuller and the whole face is more gracile (Fig. 2).
Fig. 2. TPS deformation grids; PCA in full shape space (first column; PC2, explained
variance 12.17%); PCA for global bending patterns (second column; PC1, 47.16%), and PCA for
local bending patterns (last two columns; PC1 and PC2, 14.46% and 12.24%, resp.)
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Shape corresponds to attractiveness ratings in more or less the same direction:
Among ovulatory faces, those which have the least deviation from the average ovulatory
face are perceived as most attractive, whereas those whose shape is similar to
the average luteal face are perceived as least attractive (Fig. 3).
Fig. 3. TPS deformation grids of PLS in SW1 (ovulatory faces only, explained variance
54.84%, Pearson product-moment correlation coefficient of attractiveness ratings and shape
coordinates = 0.622, calculated based on SW1 scores)
Ovulatory faces were not significantly asymmetric (p = 0.4), while luteal faces
were strongly asymmetric (p < 0.0001).
Ovulatory skin had significantly lower hue (it is redder), lower contrast, and
increased homogeneity compared to luteal skin (Table 3).
Table 3. Results of the texture analysis
item mean ovulatory ± sd mean luteal ± sd t-stat p-value
homogeneity 0.257 ± 0.028 0.243 ± 0.025 2.936 0.008
correlation 7.020×1011
± 2.520×1011
8.13×1011
± 2.210×1011
–2.097 0.050
hue 0.026 ± 0.059 0.029 ± 0.050 –2.875 0.010
DISCUSSION
Our findings confirm earlier studies insofar as facial pictures of ovulatory women
were chosen significantly more often as being more attractive, healthy, sexy, sociable,
trustworthy, young, and likeable than luteal faces. We could identify the shape
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changes that occur between the luteal and ovulatory state. The lower face is more
robust in the luteal phase, the nose is broader, and the eyebrows are more pronounced.
This corresponds to what have been described as masculine features in the
literature (ROBERTS et al., 2004). In the ovulatory phase the lips are fuller and the
whole face is less robust. Fuller lips and a fragile lower face have been previously
associated with youthfulness and high levels of oestrogen (GRAMMER et al., 2003;
SYMONS 1995). The increased redness of the face is probably due to higher peripheral
blood circulation.
While we took all measures to ensure that the faces were photographed in exactly
frontal position, any two-dimensional approach is vulnerable to tilting effects.
Part of the shape changes we find might be due to changes in head pose, i.e. the
luteal faces might be tilted back more. In order to rule out this possibility, we will
collect 3D data as a next step, which is not affected by head pose.
The findings of our study support the idea that some characteristics of what we
perceive as an attractive female face are actually synonymous to signals of ovulation.
Thus, the notion of hidden ovulation has to be challenged: First, as there are
detectable changes in the appearance of the female face at the point of ovulation, it
can not be considered hidden. Second, the signal value of those characteristics has
to be reinvestigated: What we perceive as being attractive might just signal ovulation,
conveying no information beyond the hormonal state.
ACKNOWLEDGMENT
Statistical analyses were supported by VEGA grant Nr. 2/0038/12 to SK.
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