O R I G I NA L A RT I C L E
doi:10.1111/j.1558-5646.2011.01546.x
HERITABILITY OF PREFERENCES FOR MULTIPLE
CUES OF MATE QUALITY IN HUMANS
Brendan P. Zietsch,1,2,3 Karin J. H. Verweij,3,1 and Andrea V. Burri4
1
School of Psychology, University of Queensland, St. Lucia 4067, Brisbane, Queensland, Australia
2
3
E-mail: [email protected]
Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Herston 4006, Brisbane, Queensland,
Australia
4
Department of Twin Research and Genetic Epidemiology, St. Thomas’ Hospital, King’s College, London
Received February 16, 2011
Accepted November 27, 2011
Human mate preferences have received a great deal of attention in recent decades because of their centrality to sexual selection,
which is thought to play a substantial role in human evolution. Most of this attention has been on universal aspects of mate preferences, but variation between individuals is less understood. In particular, the relative contribution of genetic and environmental
influences to variation in mate preferences is key to sexual selection models but has barely been investigated in humans, and
results have been mixed in other species. Here, we used data from over 4000 mostly female twins who ranked the importance
of 13 key traits in a potential partner. We used the classical twin design to partition variation in these preferences into that due
to genes, family environment, and residual factors. In women, there was significant variability in the broad-sense heritability of
individual trait preferences, with physical attractiveness the most heritable (29%) and housekeeping ability the least (5%). Over
all the trait preferences combined, broad-sense heritabilities were highly significant in women and marginally significant in men,
accounting for 20% and 19% of the variation, respectively; family environmental influences were much smaller. Heritability was a
little higher in reproductive aged than in nonreproductive aged women, but the difference was not significant.
KEY WORDS:
Heritability, indirect benefits, mate choice, multiple ornaments, sexual selection, twin study.
Sexual selection has helped shape the human mind and body, and
will continue to influence the nature of our species into the future
(Darwin 1859; Miller 2000). It is therefore crucial to understand
how sexual selection operates in humans, and investigating mate
preferences is central to this goal. Although there has been much
research on species- and sex-typical aspects of human mate preferences (Buss 1989; Gangestad and Scheyd 2005; Li and Kenrick
2006; Donohoe et al. 2009; Singh et al. 2010), there has been less
focus on the substantial variation between individuals. In particular, the extent to which genetic and environmental factors underlie
variation in mate preferences is of central importance to the operation of sexual selection (Jennions and Petrie 1997; Widemo
and Saether 1999; Chenoweth and Blows 2006; Chenoweth
and McGuigan 2010), but this has barely been investigated in
humans.
1
C 2012 The Author(s).
Evolution
In a number of nonhuman species, there is evidence for genetic variation in mate preferences (for reviews, see Bakker and
Pomiankowski 1995; Jennions and Petrie 1997), and a handful
of studies (in insects, fish, and birds) have attempted to formally quantify this genetic variation (Collins and Carde 1989;
Gray and Cade 1999; Jang and Greenfield 2000; Brooks and
Endler 2001; Iyengar et al. 2002; Hall et al. 2004; Simmons 2004;
Delcourt et al. 2010; see Schielzeth et al. 2010 for a review). These
studies have mostly yielded quite low heritability estimates, but
results are inconsistent—many did not detect statistically significant genetic effects, and given the large range of the heritability
estimates (0–51%) and often small sample sizes, it is unclear to
what extent the inconsistency in results is due to sampling error,
different methodologies, different species, or the different types
of preferences that were measured.
B . P. Z I E T S C H E T A L .
Only one study has attempted to quantify genetic influences
on human mate preferences, and this looked at preference for only
one trait (altruism) in a relatively small sample of identical and
nonidentical female twins (N = 177 pairs; Phillips et al. 2010),
yielding a heritability estimate of 57%. However, a wide variety
of traits contribute to sexual attractiveness, each of which may indicate different aspects of mate quality (Candolin 2003) and may
vary in their relative importance depending on individual differences (DeBruine et al. 2010b) and ecological conditions (Lee
and Zietsch 2011); heritability may differ considerably between
traits. Individual differences in the relative importance placed on
different cues of mate quality have hardly been investigated in
any species—it is not known if there is a genetic basis to any such
variation.
Also, it is difficult to know what heritability to expect in human mate preferences because humans are a pair-bonding species,
unlike the species in most previous studies. In pair-bonding
species, individuals’ mate preferences will not necessarily correspond to their realized mate “choices,” because of supply and
demand constraints in the mating market (Postma et al. 2006;
Courtiol et al. 2010). Independent investigations of mate choice
for ornament size in a pair-bonding bird species (collared flycatchers) yielded very low heritability estimates of less than 5%
(Qvarnstrom et al. 2006; Hegyi et al. 2010). Consistent with this, a
recent study (Zietsch et al. 2011) looking at the partners of a large
sample of identical and nonidentical twins indicated similarly low
(approximately 5%) heritability of mate choice across a range of
key traits (age, height, BMI, education, income, social attitudes,
religiosity, various personality traits). Genetic variation in unconstrained preferences in pair-bonding zebra finches was also low
(approximately 10%) and nonsignificant (Schielzeth et al. 2010).
If unconstrained mate preferences are this low in humans, it would
contrast with other human psychological and behavioral traits, the
vast majority of which have been shown to have moderate-to-high
heritability (Turkheimer 2000; Bouchard and McGue 2003).
Genetic and environmental effects on mate preferences are
difficult to quantify (Chenoweth and Blows 2006), but such research in humans has some practical advantages over corresponding research in other species. First, we can simply ask men and
women what they prefer in a partner, greatly simplifying the
acquisition of preference data. Studies have shown correspondence between self-reported mate preferences and those revealed
by implicit testing (Wood and Brumbaugh 2009). Second, the
availability of large samples of identical (monozygotic; MZ) and
nonidentical (dizygotic; DZ) twins allows natural genetic experiments using the classical twin design (Posthuma et al. 2003). This
design partitions variance in a trait into that due to genetic, family
environmental, and residual factors.
Here, we quantify the relative influence of genes and environment on variation in self-reported mate preferences using a
2
EVOLUTION 2012
community sample of over 4000 mostly female twin individuals.
We use the same methodology for assessing mate preferences
as in Buss’ seminal cross-cultural work (Buss 1989), in which
13 traits are ranked as to their importance in a potential partner.
We account for age effects, analyze male and female preferences
separately, and estimate the genetic and environmental influences
on preferences for the 13 traits individually as well as for data
combined over all the traits. This is the first study to quantify
genetic influences on a range of human mate preferences, and
the first in any species to test for genetic variation in the relative
importance placed on different cues of mate quality.
Methods
PARTICIPANTS
We use data from 4625 twin individuals from the U.K. Adult
Twin Registry (TwinsUK). The TwinsUK is a cohort of unselected volunteer Caucasian twins that started in 1993 (Spector
and Williams 2006). Note that the cohort consists of predominantly females (90%) and same-sex pairs, because initial research
focused on diseases with higher prevalence in women than in
men (e.g., osteoporosis and osteoarthritis). All volunteers in the
registry were recruited through successive national media campaigns in the United Kingdom and Ireland and from other twin
registers, including the Aberdeen Twin Registry and the Institute
of Psychiatry Adult Registry. The TwinsUK population has been
compared for a number of diseases, traits, socio-demographic
and environmental factors to an age-matched U.K. population,
and a singleton population cohort from Northeast London and
was found to be no different in terms of social class, lifestyle
characteristics, and disease prevalence (Andrew et al. 2001). The
only significant difference found was for weight, where MZ twins
were slightly lighter and showed smaller variance compared with
DZ twins and singletons. Numerous epidemiologic studies using the TwinsUK cohort have further demonstrated the comparability of MZ and DZ twins for a variety of traits (e.g., sexual
orientation, sexual dysfunction, number of partners, emotional
intelligence, anxiety) (Cherkas et al. 2004; Burri et al. in press;
Burri and Spector in press) therefore making a systematic bias
unlikely.
Of these 4625 twins, 39 were excluded from further analysis because they were adopted (N = 17), of unknown zygosity (N = 12), part of a triplet or quadruplet (N = 2),
or regular siblings of a twin pair (N = 8). The remaining 4586 twin individuals ranging in age from 19 to 83 included 4045 females (mean age ± standard deviation [SD] =
51.1 ± 12.7) and 541 males (mean age ± SD = 49.2 ± 14.0).
Approximately half (49.1%) of these twins were identical (MZ)
and half (50.9%) nonidentical (DZ). The sample consisted of
1763 full pairs and 1060 single twins, the latter group retained
H E R I TA B I L I T Y O F H U M A N M AT E P R E F E R E N C E S
to increase precision of the means. There were only 16 opposite sex pairs, too few for stable correlation estimates, so these
were treated as single twins. Sixty-four percent of participants
were married, but mate preferences differed little depending on
marital status after controlling for age. Homosexual participants
were not identified, but as self-identified homosexuals only account for approximately 1% and 3% of the female and male
populations, respectively (Kirk et al. 2000), any differences in
the variance components of their preferences would not substantively affect the results. Zygosity of the twins was determined
based on standardized questions about physical similarity that
have over 95% accuracy when judged against genotyping, and
when uncertain zygosity was checked by genotyping (Peeters
et al. 1998). Further details about the sample, data collection,
and zygosity determination can be found elsewhere (Spector and
Williams 2006). The data used in this project are available through
http://www.twinsuk.ac.uk/collaborations.html.
MEASURES
In 2002, participants completed a Lifestyle questionnaire including a measure of long-term mate preferences: “Below are
listed a set of characteristics that might be present in a potential mate or marriage partner. Please rank them on their desirability when you are/were considering a long-term relationship.”
There were 13 traits (see Table 1), so participants were to assign each characteristic a different score ranging from 1 (most
important characteristic for potential mate) to 13 (least important characteristic for potential mate). This measure was developed and validated by Buss and Barnes (1986) and later administered across 37 cultures by Buss (1989) to test evolutionary
hypotheses.
Because the omission of one or more trait rankings can affect
the other trait rankings, we excluded individuals from further
analysis when their summed rank scores deviated 10 or more
points from the “correct” score (i.e., 91; 1 + 2 +· · ·+ 13)—this
allowed for minor departures from the standard ordering scheme
(e.g., ranking traits as equally important) but eliminated more
serious departures that would compromise the integrity of the
scale. Along with the exclusion of those who did not complete the
item at all, this resulted in a reduction of sample size of 18.6%
(N = 855).
The rankings of each trait were analyzed as continuous variables. To attenuate the effects of outliers and skewed distribution,
outliers were winsorized (three SDs from the mean) and variables
were transformed (log, square root, or inverse, depending on the
degree of skewness) where necessary.
STATISTICAL ANALYSES
Data preparation was performed in PASW-Statistics 17.0. Statistical analyses employed full information maximum-likelihood
modeling procedures using the statistical package Mx (Neale et al.
2006), which accounts for the nonindependence of twins within
a pair. In maximum-likelihood modeling, the goodness-of-fit of a
model to the observed data is distributed as chi-square (χ2 ). By
testing the change in chi-square (χ2 ) against the change in degrees of freedom (df), we can test whether dropping or equating
specific model parameters (for example, the MZ and DZ twin pair
correlations) significantly worsens the model fit. In this way, we
can test hypotheses regarding those parameters.
We determined twin pair correlations per zygosity group
(MZ females, MZ males, DZ females, DZ males) for each trait,
and also equated (i.e., effectively averaged) twin pair correlations
over all traits in a multivariate model. We tested whether MZ twin
pairs were correlated significantly more strongly than DZ twin
pairs, which would demonstrate a genetic influence on individual
differences in mate preferences.
To quantify any genetic effect, the classical twin design was
used to partition variance in mate preferences into that due to
additive genetic (A), nonadditive genetic (D), shared (or family)
environmental (C), and residual (E) sources (Neale and Cardon
1992). Additive genetic variance is due to summed allelic effects
across multiple genes; because MZ twins share all of their alleles,
whereas DZ twins share on average only half of their segregating
alleles, A influences are correlated at 1.0 for MZ pairs, and 0.5 for
DZ pairs. Nonadditive genetic variance includes dominance (allelic interactions within genes) and epistasis (interaction between
multiple genes); D influences are modeled as correlating at 1.0
for MZ pairs, and 0.25 for DZ pairs (see Posthuma et al. 2003 for
more details). Shared environmental factors may include shared
home environment, parental style, and uterine environment; C influences are assumed to correlate at 1 for both MZ and DZ pairs.
Residual variance includes environmental factors not shared by
twin pairs (e.g., idiosyncratic experiences), stochastic biological
effects, and measurement error; E influences are correlated at zero
for both MZ and DZ twin pairs. In reality, observed MZ and DZ
twin correlations generally reflect a combination of A, C, D, and
E influences, and structural equation modeling determines the
combination that best matches the observed data (Posthuma et al.
2003).
Although the classical twin design above is a very standard
technique that has been used in countless behavioral genetic studies, it is important to note that when using only twins reared
together, certain parameter estimates can be subject to severe biases and imprecision depending on the true nature of influences
on the trait (see Keller and Coventry 2005; Keller et al. 2010 for
detailed treatments of this). First, it is not possible to estimate
C and D simultaneously, because C and D are negatively confounded: C influences increase and D influences decrease the DZ
correlation relative to the MZ correlation, and so if both effects are
EVOLUTION 2012
3
4
EVOLUTION 2012
1
2
3
4
5
6
7
8
9
10
11
12
13
Kind and understanding1
Easy going2
Intelligent3
Healthy3
Physically attractive3
Exciting personality3
Wants children4
Good earning capacity4
Creative and artistic5
Good housekeeper5
Good heredity5
University graduate6
Religious7
1.46
2.53
2.38
2.08
2.74
3.00
3.38
2.43
2.57
2.36
2.27
2.22
2.88
SD
2.12
6.28
5.65
4.24
7.32
8.15
11.45
5.81
6.59
5.57
4.95
4.92
8.01
VP
7
0
2
0
1
0
0
4
0
0
7
10
10
−0.06
0.15
−0.04
−0.15
0.16
0.31
0.01
−0.12
0.00
−0.01
−0.19
0.02
−0.18
7.98
5.79
20.75
20.96
20.75
23.14
6.42
6.08
22.51
22.13
19.07
4.02
6.25
N wins’ed Mean
r (age)
Transformed scale
3.00
2.57
5.65
4.85
6.46
6.56
3.38
2.43
5.63
5.38
5.55
2.83
3.64
SD
1
3
4
5
2
6
9
10
8
7
11
12
12
11.39
9.46
9.25
9.12
10.62
9.09
5.82
4.13
6.08
6.35
3.96
2.96
2.96
Rank Mean
2.11
2.51
2.32
2.16
2.25
2.73
2.99
2.21
2.37
2.67
2.32
1.84
3.02
SD
Raw scale
Females (N = 3285)
4.44
6.02
5.36
4.63
5.05
6.79
8.75
4.61
5.61
6.10
5.37
3.31
8.94
VP
−0.06
0.21
−0.01
−0.10
0.04
0.29
−0.14
0.23
0.00
−0.38
0.01
0.16
−0.14
70
10
13
31
0
0
0
0
0
4
34
66
93
6.17
5.83
21.08
21.49
17.36
21.22
5.82
4.12
24.16
24.58
19.03
3.96
6.47
r (age) N wins’ed Mean
Transformed scale
3.49
2.70
5.48
5.09
6.03
6.42
2.99
2.17
4.94
5.52
5.66
2.52
3.73
SD
<0.001
0.62
0.18
0.10
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
0.91
0.45
0.44
Sex diff
P-value
reflected and square root: 10 × ((14-score)0.5 ); 4 no transformation required; 5 square root: 10 × (score0.5 ); 6 log: 10 × (LG10(score)); 7 inverse: 10 × (1/score).V P , phenotypic variance after controlling for
(transformed scale) between males and females.
age, raw scale; r (age), correlation of the trait ranking (raw scale) with age, as obtained from SPSS; N wins’ed, Number of datapoints winsorized; Sex diff P-value, the significance of mean differences
3
Raw scale: untransformed, unwinsorized. Transformed scale: transformed and winsorized, where applicable. Transformations—1 reflect and inverse: 10 × (1/(14-score)); 2 reflect and log: 10 × (LG10(14-score));
12.27
9.53
9.38
9.37
9.28
8.21
6.42
6.08
5.38
5.19
3.95
3.14
2.96
Rank Mean
Raw scale
Males (N = 446)
Descriptive statistics for the 13 trait preferences.
Trait preferences
Table 1.
B . P. Z I E T S C H E T A L .
H E R I TA B I L I T Y O F H U M A N M AT E P R E F E R E N C E S
present they cancel each other out. The choice of modeling C or D
depends on the pattern of MZ and DZ correlations; C is estimated
if the DZ twin correlation is more than half the MZ twin correlation, and D is estimated if the DZ twin correlation is less than
half the MZ correlation—if C is modeled, its magnitude is underestimated to the extent that D is present, and vice versa if D is
modeled. Second, A and D are partially confounded because they
predict similar (but not identical) patterns of twin correlations.
As such, simultaneous A and D estimates are imprecise and their
relative magnitude can be biased down and up, respectively, to the
extent that there are multiloci epistatic effects. As such, separate
A, C, and D estimates should be treated with caution. However,
broad-sense heritability (i.e., A + D; the proportion of variance
in a trait accounted for by genetic factors) is quite robustly estimated with classical twin design using only twins reared together
(see Keller et al. 2010 for simulations demonstrating this), and
we therefore focus our interpretation mainly on this more reliable
estimate.
An assumption of the twin design is that trait-relevant environments are equally similar for MZ and DZ twins. Tests of this
assumption suggest it is valid for personality and sexual orientation (Loehlin 1992; Kendler et al. 2000), so it seems a reasonable
assumption for these mate preferences. Further details of the twin
design, including assumptions, can be found elsewhere (Neale
and Cardon 1992; Posthuma et al. 2003).
Age was modeled as a covariate, allowing us to determine
the direction and significance of age effects but partial them out
of genetic models. Because there is no reason to expect that the
sources of variation in mate preferences would be the same in men
and women, male and female variance components were modeled
separately.
Results
As a preliminary step, we tested the assumption that MZ and DZ
twins are comparable except for their level of genetic similarity—
inequality of means and variances of MZ and DZ twins could
suggest nonrandom sampling or sibling interaction effects that
could bias estimation of variance components (Carey 1992).
There were no substantive mean differences between MZ and
DZ twins for any trait preferences, with η2 < 0.003 for each
trait (i.e., zygosity accounted for less than 0.3% of the variance in each trait preference). Further, formal testing in Mx revealed no significant mean or variance differences between MZ
and DZ twins for trait preferences after correcting for the number of tests performed. As such, all preference means and variance were equated between MZ and DZ twins in subsequent
analyses.
Table 1 shows the descriptive statistics for the importance
of the 13 traits in a long-term partner. On average, both men
and women valued “kind and understanding” the most; “easy
going,” “intelligent,” “healthy,” and “physically attractive” were
also highly valued traits, but “good heredity,” “university graduate,” and “religious” were relatively unimportant. Some trait preferences showed significant mean sex differences, largely in line
with previous cross-cultural work (Buss 1989): compared with
men, women more strongly valued “kind and understanding,”
“wants children,” “good earning capacity,” whereas men more
strongly valued “physically attractive,” “good housekeeper,” “exciting personality,” and “creative and artistic.” Most trait preferences exhibited significant mean effects of age; increasing
in importance with age were “kind and understanding,” “religious,” “good housekeeper,” “good heredity,” “good earning capacity,” “intelligent,” and “healthy,” and decreasing in importance were “exciting personality” and “easy going.” Other trait
preferences showed age effects that were significantly different in males and females: “physical attractiveness” (decreased
with age in women, no effect in men); “earning capacity” and
“good heredity” (increased with age in women, decreased in
men); and “wants children” and “good housekeeper” (increased
with age in men, no effect in women). We could not distinguish
cohort effects from true age effects due to the cross-sectional
sample.
There were a few modest correlations between the different
trait preferences, ranging from –0.19 (“physically attractive” and
“kind and understanding”) to 0.32 (“intelligent” and “university
graduate”), but the average R2 was only 0.014 so we treated them
as independent traits in subsequent analyses.
Table 2 shows the twin pair correlations for mate preferences—for each trait separately and averaged over all traits. Of the
13 traits for both men and women, all but one (“kind and understanding” in males) showed higher MZ than DZ twin pair correlations, suggesting widespread genetic influences. In women,
twin pair correlations could not be equated across traits, indicating significant variability in the relative effect of genes and
environment between different trait preferences (P < 0.001). The
highest broad-sense heritability estimates (see Table 3) in women
were for “physically attractive” “exciting personality” “kind and
understanding” “good earning capacity” and “healthy” (all P <
0.001), while “good housekeeper” was the least heritable. Shared
environmental influences were significant for “intelligent” (P =
0.02) and “good housekeeper” (P = 0.02).
Male twin pair correlations could be equated across traits
without significant loss of model fit, indicating that the wide
variability across traits in twin pair correlation and heritability
estimates could be explained by error (due to the much smaller
male sample). Nevertheless, male preferences showed significant
genetic influences for “religious” (P = 0.002) and “good housekeeper” (P = 0.007). No shared environmental influences were
significant in males.
EVOLUTION 2012
5
0.02 (0.13) 0.21 (0.14) 0.09 (0.13) 0.12 (0.04−0.19)
0.15 (0.12) 0.25 (0.15) 0.02 (0.16) 0.09 (0.14) 0.03 (0.11) 0.22 (0.12) 0.13 (0.14) −0.19 (0.17) 0.10 (0.15)
0.25 (0.12)
EVOLUTION 2012
To estimate the overall genetic influence on mate preferences,
we fitted a multivariate genetic model in which we constrained
A, C, and E estimates to be equal across all 13 traits, separately
for males and females. This yielded overall heritabilities of 20%
(95% confidence interval [CI]: 14–26%) for women (P < 0.001)
and 19% (0–28%) for men (P = 0.05), and shared environmental
estimates of 5% in females and 3% in males, but it should be
recalled that shared environmental influences are underestimated
to the extent that nonadditive genetic effects are present. The
overall estimate of the familial effect (i.e., genetic plus family
environmental effects) was 25% (23–27%) and 22% (16–28%) in
women and men, respectively. In all traits, most of the variation
was residual (i.e., unexplained by genes or family environment).
Because of the very large age range of the sample, we also
tested whether there was any marked difference between the overall heritability of mate preferences in women of normal reproductive age (40 and under, when mate preferences are most consequential), and those over 40. Broad-sense heritability of the
reproductive age group was 25%, and a little lower for the over
40 group at 19%—this difference was not significant (P = 0.41).
The male sample was too small for a similar age comparison.
MZF, monozygotic female pairs; MZM, monozygotic male pairs; DZF, dizygotic female pairs; DZM, dizygotic male pairs.
0.17 (0.10) 0.26 (0.10) 0.36 (0.10) 0.21 (0.15−0.28)
0.31 (0.10)
0.23 (0.10) 0.42 (0.09) 0.06 (0.12) 0.14 (0.12) 0.24 (0.12) 0.34 (0.11) 0.16 (0.12) 0.00 (0.11)
0.20 (0.11)
0.13 (0.04) 0.23 (0.04) 0.22 (0.04) 0.15 (0.12−0.17)
0.23 (0.04)
0.13 (0.04) 0.28 (0.04) 0.06 (0.04) 0.10 (0.04) 0.05 (0.04) 0.14 (0.04) 0.09 (0.04) 0.16 (0.04)
0.08 (0.04)
0.17 (0.04) 0.31 (0.04) 0.29 (0.04) 0.24 (0.22−0.27)
0.25 (0.04)
0.20 (0.04) 0.36 (0.04) 0.20 (0.04) 0.30 (0.04) 0.25 (0.04) 0.20 (0.04) 0.24 (0.04) 0.22 (0.04)
Healthy
Intelligent
Kind
and
Easy
understanding going
0.24 (0.04)
Overall
(95%CI)
University
graduate
Religious
Good
Good
housekeeper heredity
Creative
and
artistic
Good
earning
capacity
Exciting
Wants
personality children
Physically
attractive
6
MZF (552
pairs)
DZF (537
pairs)
MZM (71
pairs)
DZM (51
pairs)
Table 2.
correlations across all traits in a multivariate model.
Twin pair correlations (and standard errors) for mate preferences for 13 traits. “Overall” correlations (and 95% confidence intervals [CIs]) are estimated by equating
B . P. Z I E T S C H E T A L .
Discussion
The results from this large twin study provide the first evidence
that a range of human mate preferences are heritable, and the
first evidence from any species that there is genetic variation in
the relative importance placed on different cues of mate quality.
Participants ranked 13 traits according to their importance in a
potential partner—in both men and women, these trait rankings
were consistently more similar in identical than nonidentical twin
pairs, indicating genetic influences. Within-sex genetic modeling revealed significant variability in the heritability of the 13
trait preferences in women, with key traits (physical attractiveness, exciting personality, kindness, earning capacity, and health)
having the highest (and significant) heritabilities—these traits include purported indicators of genetic quality (physical attractiveness, health) and parental investment (kindness, earning capacity). When data were combined over all trait preferences, the
broad-sense heritability of mate preferences was estimated at 20%
(highly significant) and 19% (marginally significant) in women
and men, respectively. Shared environment significantly influenced women’s preferences for “intelligent” and “good housekeeper,” but overall shared (family) environment was estimated
to account for a nonsignificant 5% and 3% of variation in overall mate preferences in women and men, respectively—however,
these will be underestimates to the extent that nonadditive genetic
variation is present. The remainder of the within-sex variation
was residual, likely comprising unshared environmental influences and measurement error.
∗
E
C
A+D
D
A
0.00
(0.00–0.41)
0.23
(0.00–0.38)
0.77
(0.61–0.95)
0.76
(0.69–0.85)
0.00
(0.00–0.41)
–
Healthy
0.13
0.16
0.05
(0.00–0.28) (0.00–0.36) (0.00–0.26)
–
–
0.16
(0.00–0.28)
0.13
0.16
0.20∗∗∗
(0.00–0.28) (0.00–0.36) (0.13–0.28)
–
0.07
0.20∗
(0.00–0.21) (0.04–0.35)
0.80
0.64
0.80
(0.72–0.88) (0.57–0.71) (.72–0.88)
0.17
0.34
0.02
(0.00–0.40) (0.00–0.57) (0.00–0.26)
–
–
0.04
(0.00–0.28)
0.17
0.34
0.06
(0.00–0.40) (0.00–0.57) (0.00–0.28)
0.06
0.08
–
(0.00–0.34) (0.00–0.48)
0.77
0.58
0.94
(0.59–0.96) (0.43–0.79) (0.72–1.00)
Intelligent
0.00
(0.00–0.26)
0.25
(0.00–0.32)
0.25∗∗∗
(0.17–0.33)
–
Exciting
personality
Wants
children
Good
earning
capacity
0.14
0.13
(0.00–0.28) (0.00–0.29)
–
0.10
(0.00–0.31)
0.14
0.24∗∗∗
(0.00–0.28) (0.16–0.31)
0.07
–
(0.00–0.09)
0.70
0.75
0.80
0.76
(0.63–0.78) (0.68–0.83) (0.72–0.88) (0.69–0.83)
0.11
0.00
0.25
0.06
(0.00–0.35) (0.00–0.39) (0.00–0.52) (0.00–0.37)
–
0.23
–
–
(0.00–0.44)
0.11
0.24
0.25
0.06
(0.00–0.35) (0.00–0.45) (0.00–0.52) (0.00–0.37)
0.03
–
0.09
0.10
(0.00–0.30)
(0.00–0.42) (0.00–0.32)
0.86
0.77
0.66
0.84
(0.65–1.00) (0.74–0.83) (0.50–0.73) (0.63–1.00)
0.12
(0.00–0.28)
0.18
(0.00–0.37)
0.30∗∗∗
(0.22–0.37)
–
Physically
attractive
P < 0.05; ∗∗ P < 0.01; ∗∗∗ P < 0.001. NB: Estimates of E are not significance tested, because measurement error is always present.
Males
E
0.08
(0.00–0.29)
D
0.16
(0.00–0.31)
A + D 0.24∗∗∗
(0.15–0.31)
C
–
Females A
Kind and
Easy
understanding going
0.05
(0.00–0.27)
0.21∗
(0.03–0.30)
0.75
(0.67–0.81)
0.10
(0.00–0.47)
0.21
(0.00–0.49)
0.00
0.31∗∗
(0.00–0.18) (0.09–0.49)
0.00
–
(0.00–0.15)
1.00
0.69
(0.82–1.00) (0.51–0.91)
0.14
(0.00–0.35)
0.15
(0.00–0.29)
0.71
(0.65–0.76)
0.01
(0.00–0.50)
0.35
(0.00–0.53)
0.11
0.36∗∗
(0.00–0.44) (0.14–0.53)
0.15
–
(0.00–0.40)
0.83
0.74
0.64
(0.66–1.00) (0.56–0.93) (0.47–0.76)
0.17
(0.00–0.37)
0.14
(0.00–0.28)
0.69
(0.62–0.72)
0.11
(0.00–0.44)
–
0.07
(0.00–0.25)
0.10
(0.00–0.21)
0.83
(0.75–0.90)
0.00
(0.00–0.32)
0.17
(0.00–0.34)
0.17
(0.00–0.35)
–
Religious
0.12
(0.00–0.30)
0.10
(0.00–0.24)
0.78
(0.70–0.85)
0.00
(0.00–0.18)
–
University
graduate
0.07
0.17
0.14
(0.00–0.25) (0.00–0.37) (0.00–0.35)
–
–
–
Good
Good
housekeeper heredity
0.12
0.05
(0.00–0.30) (0.00–0.27)
–
–
Creative
and artistic
Estimates (and 95% CIs) of the proportion of variance in mate preferences accounted for by additive genetic (A), nonadditive genetic (D), shared environmental (C), and
residual (E) influences. A + D represents broad-sense heritability (in bold).
Table 3.
H E R I TA B I L I T Y O F H U M A N M AT E P R E F E R E N C E S
EVOLUTION 2012
7
B . P. Z I E T S C H E T A L .
Our estimate of about 20% heritability in men and women fits
with the generally low heritabilities found for mate preferences in
other species (Collins and Carde 1989; Gray and Cade 1999; Jang
and Greenfield 2000; Brooks and Endler 2001; Iyengar et al. 2002;
Hall et al. 2004; Simmons 2004; Schielzeth et al. 2010), but our
study is one of the few in which the estimate is significantly different from zero. We had more statistical power than many animal
studies because of our large sample and multiple preference measures. This is important, because significant heritability demonstrates that mate preferences are partly under genetic control, a
critical assumption of most theoretical models of mate choice and
sexual selection (e.g., runaway, fitness indicators, sensory bias
[Fisher 1930; Zahavi 1975; Ryan 1998])—further, the idea that
mate preferences genetically vary in populations (and genetically
covary with preferred traits themselves) is central to certain models (e.g., runaway [Fisher 1930]). Establishing significant genetic
control of mate preferences therefore helps validate models of
mate choice and sexual selection, and more precisely quantifying the genetic variation helps improve the models (Widemo and
Saether 1999). Importantly, we found for the first time that there
is genetic variation in the relative importance placed on different
cues of mate quality, which is key to developing models of sexual
selection that take into account the use of multiple cues (Candolin
2003).
Quantifying the heritability of unconstrained mate preferences in addition to that of realized mate choices (see Zietsch et al.
2011) is also of considerable importance (Postma et al. 2006), especially in pair-bonding species. Zietsch et al. (2011) showed
that realized mate choices display very low heritability (approximately 5% for both sexes averaged over numerous traits)—much
lower than for unconstrained preferences as found in the present
study (approximately 20% for both sexes averaged over numerous traits). Although mate choices will relate to preferences, the
relationship may be multifactorial and indirect, especially under
mutual mate choice as is the case in humans. An individual’s
realized mate choice depends not only on the individual’s preferences, but also on the ability of the individual to obtain a mate
that matches those preferences. This in turn depends on a multitude of factors that influence supply and demand dynamics in
the mating market. These may include the number of mates from
which the individual could choose; the distribution of preferences
and preferred traits among those potential mates; and the number
of same-sex competitors and the distribution of their preferences
and traits. These and other variables in the mating environment
may explain why we find much higher proportion of environmental variation (i.e., lower heritability) in realized pair-bond mate
choice (Zietsch et al. 2011) than in unconstrained mate preferences (present results).
This has implications for testing models of sexual selection, which make predictions about genetic (co)variation in mate
8
EVOLUTION 2012
preferences (Fisher 1930; Zahavi 1975). Although the “process”
of sexual selection operates through realized mate choices, the
direct “products” of sexual selection are characteristics of the
individual (including mate preferences but also signaling traits,
etc.), which in turn influence mate choices along with the multitude of external factors described above. As such, it would
be most powerful to investigate the direct products of sexual
selection (e.g., mate preferences) to test predictions from different models of selection (i.e., to determine which model(s)
were most likely to have generated current phenotypes)—this
is especially the case given that we show that unconstrained
preferences are much more heritable than realized choices, because greater heritability affords more power to detect genetic
(co)variation, all else being equal. Of course, an integrated understanding of the operation and outcomes of sexual selection
requires the study of both preferences and realized choices, and
especially how mate preferences and other traits affect realized
choices.
Although mate preferences are considerably more heritable
than realized mate choices (see Zietsch et al. 2011), it is interesting
that mate preferences seem still to be less heritable than most other
human behavioral characteristics. Human personality traits tend
to be estimated at 30–60% heritability (Johnson et al. 2008), and
intelligence, mental disorders, and drug and alcohol use tend to
have heritabilities in this range or higher (Bouchard and McGue
2003; Deary et al. 2006; Levinson 2006; Agrawal and Lynskey
2008; Verweij et al. 2010).
The lower heritability of mate preferences could be partly
due to our measure of mate preferences, which might contain
more measurement error (thus a lower proportion of genetic variation) than the highly developed personality and intelligence tests.
On the other hand, mental disorders and drug and alcohol use
are often measured crudely and scored dichotomously, yet still
yield high heritability estimates. Another possible explanation for
low heritability of mate preferences is that mate preferences may
be less stable within individuals than other traits; for example,
women’s mate preferences are known to vary across their ovulatory cycle (Gangestad et al. 2007). Also, ranked mate preferences
change according to environmental cues of pathogen prevalence
and resource scarcity (Lee and Zietsch 2011), and could also be
influenced by past relationship experiences—further, these environmental influences may interact with genetic predispositions.
Intraindividual variation, environmental variance, and gene-byenvironment interaction all contribute to variation that is unexplained by genes, hence lowering the heritability. On the other
hand, the low or absent family environmental influence on mate
preferences is in line with many other adult psychological traits
(e.g., personality, intelligence, psychopathology; Bouchard and
McGue 2003), although the possible underestimation of shared
environment estimates should be kept in mind.
H E R I TA B I L I T Y O F H U M A N M AT E P R E F E R E N C E S
Another possible reason for low heritability is selection,
which is expected to deplete genetic variation in traits affecting
fitness (Fisher 1930). Considering the centrality of mate preferences to sexual selection and their potential to confer direct
(genetic) and/or indirect (investment) benefits to offspring, selection is likely to be a factor. This raises the question of why any
genetic variation is maintained; this question applies to practically
all fitness-related quantitative traits (Mitchell-Olds et al. 2007),
but there are some factors that may specifically apply to mate
preferences. For example, the observation that mate preferences
vary across geographical regions (DeBruine et al. 2010a) suggests
that there may be environmental heterogeneity in selection pressures, which can in some circumstances maintain variation (i.e.,
balancing selection; Turelli and Barton 2004). On the other hand,
if mate choices map only weakly onto mate preferences, selection
on the latter may be weak; given that mate preferences are likely to
depend on many genes (i.e., a large mutational target area), mutational variance is likely to be substantial (i.e., mutation–selection
balance; Zhang and Hill 2005; Whitlock and Agrawal 2009).
It should also be noted that mate preferences might depend on
other heritable traits, creating indirect (or “reactive”) heritability
in mate preferences. Given the tendency for humans to mate with
individuals similar to themselves (Price and Vandenberg 1980;
Martin et al. 1986; Feingold 1988; Watson et al. 2004; Koenig et al.
2009; Zietsch et al. 2011) with regard to many traits (e.g., physical
attractiveness), reactive heritability in mate preferences seems
likely. For example, physically less-attractive individuals tend to
place less importance on physical attractiveness in a partner (Todd
et al. 2007)—physical attractiveness is heritable (McGovern et al.
1996), and so this would cause heritable variation in preference for
physical attractiveness even in the absence of genetic influences
acting directly on the preference itself. Mate preferences are also
likely to relate to personality characteristics, but as there is little
assortative mating on most personality traits (McCrae et al. 2008;
Zietsch et al. 2011), it is less clear what pattern of association
to expect. More research is needed on how mate preferences
depend on other characteristics (e.g., mate value, personality) of
the holder.
In addition to the aforementioned shortcomings of our measurement of mate preferences, there are other limitations to this
study. First, there are further limitations of the measure. One important limitation is that the ranking system prevents the valid
estimation of coefficients of additive and nonadditive genetic
variance (Houle 1992), because this requires ratio-scale measures (i.e., measures with a meaningful zero-point) (Hansen et al.
2011). These absolute statistics can be compared across different traits and species and can be more evolutionarily informative
than heritability (Hansen et al. 2011)—future studies should aim
to use ratio-scale measures of human mate preferences. Another
problem with the ranking system is that it does not measure the
direction of preferences regarding various traits, only the traits’
relative importance. While it is safe to assume that a partner is
always preferred to be healthy, the same cannot be said for the
partner being religious or a university graduate. Further, the measure only assessed preferences for 13 traits, leaving out many
traits of known importance (e.g., masculinity/femininity, body
size). It also gives no indication of how selective (or choosy) an
individual is when assessing mates—two individuals who rank
traits in the same order of relative importance might differ greatly
in the absolute importance of the traits when considering whether
to pursue or accept a mate. Further still, we only measured preferences in a long-term partner, whereas humans are known to
commonly engage in short-term as well as long-term mating.
More broadly, self-report measures are potentially subject to inaccuracies (e.g., limited awareness of own preferences) or biases
(e.g., social desirability), so future work should assess revealed
or implicit preferences. The fact that the sample was primarily
female meant less precision of male heritability estimates and no
ability to investigate potentially interesting cross-sex correlations
(i.e., between opposite-sex twins). Finally, despite the advantages
of the twin design, the lack of additional data from partners and
other relatives of twins precludes more complete characterization
of the sources of variance (see Keller et al. 2009, 2010).
Given these limitations, there is clearly much more work to
be done to fully understand the genetic and environmental variation in human mate preferences and what they reveal about our
evolution. Nevertheless, this study represents an important first
step—it demonstrates significant heritable within-sex variation in
mate preferences for multiple cues, and gives an idea of the relative magnitude of genetic and environmental influences. Further
investigation of the sources of variation within-sex will be an important complement to the mass of existing and ongoing research
on species- and sex-typical aspects of mate preferences.
ACKNOWLEDGMENTS
We would like to thank the twins for their voluntary contribution to this
research project. We would also like to thank the staff of the Twin Research
Unit (KCL) for their help and support in undertaking this project. The
Wellcome Trust provides core support for Department of Twin Research.
BPZ is supported by a UQ Postdoctoral Fellowship. KJHV is supported
by an ANZ Trustees Ph.D. scholarship in Medical Research.
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Associate Editor: R. Bonduriansky
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