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RESEARCH PAPER
Beauty in Mind: The Effects of Physical Attractiveness
on Psychological Well-Being and Distress
Nabanita Datta Gupta
1
•Nancy L. Etcoff
2
•
Mads M. Jaeger
3,4
Springer Science+Business Media Dordrecht 2015
Abstract Attractive people enjoy many social and economic advantages. Most studies
find effects of attractiveness on happiness or life satisfaction, but based on traditional
cross-sectional approaches. We use a large longitudinal survey consisting of a sample of
male and female high school graduates from Wisconsin followed from their late teens to
their mid-1960s. The panel construction of the data and the fact that interviews of the
siblings of the respondents are available allow us to analyze the effects of physical
appearance on psychological well-being (human flourishing) and ill-being (distress and
depression) conditioning on unobserved individual heterogeneity via random effects. We
find a significant positive relationship between measures of physical attractiveness (greater
facial attractiveness at high school, and lower BMI and greater height in middle age) and a
measure of psychological well-being, and a significant negative relationship between
measures of physical attractiveness and distress/depression. These effects are slightly
smaller when we adjust for demographics and mental ability but, with the exception of
All authors have contributed equally to this work. Authors are listed in alphabetical order.
&Nabanita Datta Gupta
ndg@econ.au.dk
Nancy L. Etcoff
netcoff@mgh.harvard.edu
Mads M. Jaeger
mmj@soc.ku.dk; mme@sfi.dk
1
Department of Economics and Business Economics, Aarhus University,
Fuglesangs Alle
´4, 8210 A
˚rhus V, Denmark
2
Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School,
CNY 149, 13th St, Charlestown, MA 02138, USA
3
Department of Sociology, University of Copenhagen, Øster Farimagsgade 5,
Building 16, 1014 Copenhagen K, Denmark
4
The Danish National Centre for Social Research, Herluf Trolles Gade 11,
1052 Copenhagen K, Denmark
123
J Happiness Stud
DOI 10.1007/s10902-015-9644-6
height, remain significant. Our results suggest that attractiveness impacts psychological
well-being and depression directly as well as through its effects on other life outcomes.
Keywords Physical attractiveness Psychological well-being Distress Longitudinal
survey Random effects Sibling differences
1 Introduction
Beauty is rewarding and rewarded. Brain imaging studies reveal that brain reward path-
ways fire at the sight of attractive strangers’ faces (Aharon et al. 2001). Social psychol-
ogists have identified a ‘‘halo’’ effect of physical attractiveness leading to inferences that
the attractive are more competent, confident, and socially skilled than the unattractive
(Eagly et al. 1991; Hatfield and Sprecher 1986; Langlois et al. 2000; Feingold 1992). In
labor markets, a ‘‘beauty premium’’ and ‘‘plainness penalty’’ is seen: attractive individuals
are more likely to be hired, promoted, and to earn higher salaries than unattractive indi-
viduals (Hamermesh and Biddle 1994; Hosada et al. 2003). Attractive people are more
likely to win arguments, persuade others to change their opinions, and be offered assis-
tance. Compared with unattractive adults, they have more dating and more sexual expe-
rience [reviewed in Etcoff (1999)]. One would have to assume that attractive people are
happier than other people. Afforded so many social and economic advantages, they must
be happier.
Very few studies have adequately tested this assumption, and fewer have offered evi-
dence that supports it. In a study of college students, Diener et al. (1995) found that facial
attractiveness had marginal effects on overall happiness and life satisfaction. Looking
within sub-domains, they found a small but significant effect on satisfaction with romantic
life, but no effect on satisfaction with any of the other 33 sub-domains measured. A study
of female fashion models found that they had slightly lower well-being and greater per-
sonality maladjustments than non-models matched for age and ethnicity, a result that may
not be generalizable to the general population of attractive women (Meyer et al. 2007).
While meta-analyses suggest that attractive adults have slightly better mental health and
less social anxiety than unattractive adults (Feingold 1992; Langlois et al. 2000), a study of
1100 female twins found no relations between physical attractiveness and three separate
measures of depression (McGovern et al. 1996). Reviewing the evidence on happiness and
attractiveness, one researcher concluded that the ‘‘bottom line is that good looking people
aren’t any happier’’ (Lyubomirsky 2007). To date, most of the findings on attractiveness
mirror a slew of other findings in well-being research that demonstrate that life circum-
stances explain little of the variance in happiness (Lyubomirsky et al. 2005).
A few studies have looked at specific ‘‘objective’’ body measurements associated with
norms of attractiveness such as height and weight and their relation to happiness or
depression. Deaton and Arora (2009) found that the taller are happier but the results are
almost entirely explained by the association between height and both income and educa-
tion. Barry et al. (2008) have shown that the risk of major depression significantly
increases with BMI even when controlling for other risk factors, particularly for women.
In this study, we use the Wisconsin Longitudinal Study to test whether attractiveness is
significantly linked to psychological well-being and distress/depression across the lifespan.
We use the WLS for three reasons: it includes multiple sources of measurement of physical
N. D. Gupta et al.
123
attributes including observer ratings of facial attractiveness and self-reports of weight and
height; it includes standardized measures of well-being and of depression; and it has
detailed demographic information on respondents from their late teens until their mid-
1960s. This long observational period allows us to analyze the effect of physical attrac-
tiveness on well-being and distress while taking into account mediators of well-being and
ill-being such as marriage, divorce, unemployment and any unobserved individual
heterogeneity. Finally, interviews of the siblings of the WLS respondents provide a way of
accounting for unobserved family background effects common to siblings from the same
family.
2 Materials and Methods
The Wisconsin Longitudinal Survey (WLS) is a long-term study of a broadly represen-
tative sample of 10,137 white, non-Hispanic American men and women who graduated
from Wisconsin high-schools in 1957 (Wisconsin Longitudinal Study, 1957–2011).
Interviews with either the respondents or their parents were conducted six times over a
period of more than 50 years (in 1957, 1964, 1975, 1992–1993, 2003–2005 and 2011) and,
for a subsample of the WLS respondents, four times with a randomly selected sibling (in
1977, 1993–1994, 2004–2007 and 2011).
2.1 Attractiveness Measures
The high-school yearbook pictures of 8434 WLS participants were rated for attractiveness in
2008 by judges recruited from the Madison senior scholars program. Twelve judges (six men
and six women, mean age 78.5) rated each photograph on an 11-point rating scale from ‘‘not
at all’’ to ‘‘extremely’’ attractive. The reliability of the facial attractiveness ratings (Cron-
bach’s alpha) is .87 (Hauser 2009). We use the normed average rating across the 12 judges.
Our measure of BMI is based on self-reports obtained in 1992–1993 and 2003–2005 when
subjects were approximately 54 and 65 years old. Finally, we include height in inches.
2.2 Psychological Well-being Measures
Wisconsin Longitudinal Survey respondents and the subsample of siblings were assessed
using the Ryff six-factor model of well-being (RPWB; Ryff 1989; Ryff and Keyes 1995),
theoretically derived dimensions of well-being focusing on the extent to which respondents
endorse high levels of autonomy, environmental mastery, personal growth, positive rela-
tions with others, purpose in life and self-acceptance. The WLS respondents received a
shortened version of the RPWB based on 42 (1993) and 31 items (2004). Psychological
well-being applied in the paper is an aggregate scale of standardized scores on four of these
measures: personal growth, purpose in life, self-acceptance and environmental mastery.
while Ryff and Keyes (1995) suggest that a six factor structure is the best fit to the data, not
all studies agree. Following Springer et al. (2006), we combined the four highly redundant
subscales into one index of positive mental health. The other dimensions will be examined
separately in future work. Our measure of psychological distress/depression is the Center
for Epidemiologic Studies Psychological Distress/Depression Scale (CES-D) a common
screening test of depressive feelings and behaviors during the past week (Radloff 1977). It
consists of 20 items, standardized to have zero mean and unit standard deviation (SD).
Beauty in Mind: The Effects of Physical Attractiveness on…
123
We control for sex (female), years of completed schooling, retirement status, marital status,
total household income in quintiles, homeownership, mental ability,
1
and objective health (a
scale measuring the total number of illnesses that the respondent has ever experienced).
2.3 Analysis
We use two analysis samples. In the main sample we include the 8434 WLS respondents with
a valid facial attractiveness rating. This sample consists of 4416 women and 4018 men.
Respondents in this sample are observed twice (in 1993 and 2004). In the secondary sample,
which we use for supplementary within-family analysis, we include WLS respondents for
whom there is also information on a randomly selected sibling (i.e., a subsample of the main
WLS sample). This sample includes sibling respondents with valid information on BMI (3183
observations) and height (3255 observations). The WLS respondent and sibling respondent in
the secondary sample are both observed twice (in 1993 and 2004).
We exploit the availability of repeated observations of the well-being and distress/de-
pression variables in 1993 and 2004 to address potential confounding from unobserved
heterogeneity. Specifically, we estimate random effects (RE) models that control for unob-
served individual characteristics that affect well-being and distress/depression. The RE model
is a panel data model that uses repeated observations of the dependent and independent
variables to control for the fact that some individuals for reasons unobserved by the researcher
may be more prone to mental distress than others. One example of an unobserved factor could
be genetic susceptibility to depression—a recent meta-analysis finds that individuals with the
short variant of the serotonin transporter gene 5-HTTLPR have a higher tendency to expe-
rience depression after stressful incidents (Karg et al. 2011). The RE approach thus enables us
to provide more robust estimates of the association between physical attractiveness and well-
being and distress/depression than a traditional cross-sectional approach.
As a robustness check, we also run ‘‘sibling-differenced’’ RE models in which we use
the secondary sample and calculate differences across siblings from the same family in
both the dependent and the independent variables. The idea behind this approach is that, in
addition to controlling for individual unobserved heterogeneity, we use the sibling-dif-
ferenced variables to also control for family-level unobserved characteristics that affect
physical attractiveness and well-being (such as common upbringing or genes). Since mixed
(brother–sister) pairs can differ substantially in height and BMI, we standardize these
variables within sexes i.e., transform them to Z-scores. In this way, all pairs of siblings can
be included in the estimation. Facial attractiveness is only available for the main WLS
respondent, however, which means that we cannot include this variable in the sibling-
differences models.
3 Results
3.1 Findings
Table 1presents descriptive statistics from our main and secondary WLS samples pooled
over the two observation periods (1993 and 2004). Psychological well-being and depres-
sion measures, facial attractiveness, BMI and height (standardized within sexes) are
1
Our proxy for mental ability is respondents’ scores on the Henmon-Nelson test of mental ability when
they were approximately 18 years old.
N. D. Gupta et al.
123
centered on zero. Mean BMI in the main sample is 27.3, in the overweight category. Mean
height is 67.4 inches (women 64.7 inches, men 70.6 inches). 51.6 % of the WLS sample is
female. Individuals on average have 13.4 years of schooling. More than 80 % of the
respondents are married. On average, measured mental ability is 100.5. The distributions of
the dependent and independent variables are very similar in the main and secondary
sample.
Table 2uses the main WLS sample in a random effects regression of well-being and ill-
being on physical attractiveness. Separate regressions are run for each of the measures:
psychological well-being and distress/depression. Two specifications are shown: column 1,
physical attractiveness only, and column 2, adjusted for demographic variables and mental
ability.
We find that greater facial attractiveness, lower BMI and greater height are associated
with higher psychological well-being and lower depression. These effects are slightly
smaller when we adjust for demographics and ability but, with the exception of height,
Table 1 Descriptive statistics
Sample WLS respondents WLS respondents and siblings
Mean SD N Mean SD N
Psychological well-being scale
a
31.409 5.102 13,571 31.487 5.036 6295
Depression (modified CES-D)
a
15.289 15.018 13,465 14.929 14.536 6235
Physical attractiveness
Facial attractiveness
a
.013 1.257 16,868 – – –
Body mass index
a
27.295 4.740 12,783 27.123 4.588 5641
Height in inches
b
67.410 3.856 13,576 67.425 3.827 6510
Sex (female)
c
51.6 20,634 51.0 17,556
Years of schooling 13.389 2.419 19,224 13.455 2.186 10,668
Dummy for retired
c
41.4 15,171 38.9 8637
Married
c
80.3 16,183 81.6 9195
Never married
c
4.0 16,183 3.9 9195
Widowed
c
4.8 16,183 4.4 9195
Divorced
c
10.0 16,183 9.4 9195
No. illnesses 1.440 1.586 13,618 1.371 1.568 6421
Total family income, quintiles 5.496 2.872 15,671 5.696 2.819 8154
Homeowner
c
91.0 15,466 91.4 7947
Mental ability 100.459 14.915 20,634 100.845 14.815 13,238
Brother pairs
c
– – – 23.8 17,556
Sister pairs
c
– – – 25.7 17,556
Means/percentages, standard deviations (SD) and number of observations
Descriptive statistics are for the pooled (1993 and 2004) waves
a
Variable is standardized in the empirical analyses
b
Variable is standardized within genders in the empirical analyses
c
Percentages. The sample ‘‘WLS respondents’’ includes all WLS respondents with a valid observation of
facial attractiveness. The sample ‘‘WLS respondents and siblings’’ includes all WLS respondents for whom
the WLS also includes information on a randomly selected sibling. Descriptive statistics for this sample is
for the WLS and sibling respondent
Beauty in Mind: The Effects of Physical Attractiveness on…
123
remain statistically significant. Furthermore, the effects of physical attractiveness on
psychological well-being and depression are roughly comparable. A 1 SD increase in facial
attractiveness is linked with an increase in psychological well-being of .069 and .055 SDs
after adjusting for demographics and ability.
2
A 1 SD increase in adolescent BMI implies a
Table 2 Random effects regressions of psychological well-being outcomes
Model Psychological well-being
a
Depression
1212
Facial attractiveness .069
(.012)***
.055
(.012)***
-.057
(.012)***
-.038
(.012)**
Body mass index -.098
(.011)***
-.074
(.011)***
.071
(.011)***
.057
(.011)***
Height in inches .031
(.012)**
.017
(.012)
-.020
(.012)
-.009
(.012)
Sex (=female) .165
(.024)***
.097
(.024)***
Years of schooling .046
(.006)***
-.002
(.006)
Dummy for retired (ref. working) .076
(.016)***
-.108
(.017)***
Never married (ref. married) -.237
(.060)***
.132
(.059)*
Widowed -.100
(.044)*
.419
(.046)***
Divorced -.017
(.037)
.081
(.037)*
No. illnesses -.040
(.006)***
.086
(.006)***
Total family income, quintiles .031
(.004)***
-.016
(.004)***
Homeowner .091
(.036)*
-.146
(.037)***
Mental ability .001
(.001)
-.005
(.001)***
Proportion of variance within-individual .616 .593 .556 .522
R
2
(between-individual) .022 .082 .014 .101
Number of observations 9552 9552 9505 9505
Parameter estimates with standard errors in parenthesis. WLS respondents sample
*** p\.001; ** p\.01; * p\.05
a
Aggregate scale of scores on personal growth ?purpose in life ?self-acceptance ?environmental
mastery. Model 1 for each outcome includes the physical attractiveness variables while Model 2 includes the
physical attractiveness and the control variables. No significant interactions between sex and the physical
attractiveness variables
2
Some research suggests that the effects of physical attractiveness on well-being need not be linear (Tove
´e
et al. 2006; Courtiol et al. 2010). For example, taller men and women of average height are considered more
attractive than short men and tall/short women. We tested for nonlinear effects of physical attractiveness by
including square terms for all physical attractiveness variables. We found little evidence of non-linear
effects, however.
N. D. Gupta et al.
123
.074 SD fall in well-being adjusting for controls, and a .057 SDs rise in depression
adjusting for controls. Height has a positive effect on psychological well-being, but this
effect is no longer statistically significant after adjusting for controls, which was also found
by Deaton and Arora (2009). The effect of physical attractiveness is comparable to that of
other correlates of psychological well-being and depression. For example, the effect on
psychological well-being of a 1 SD increase in facial attractiveness is similar to the effect
of moving up one quartile in the distribution of family income and, moreover, equivalent to
about one-third of the gender difference in well-being.
The effects of the demographic variables on well-being and depression concur with the
literature (Frey and Stutzer 2002). For example, we find a positive association between
family income and well-being and a negative association between these measures and
depression (see e.g. Diener and Biswas-Diener 2002; Diaz-Serrano 2009). Being female is
associated with significantly higher well-being and a greater tendency towards depression,
a paradox resolved by noting that studies find while gender accounts for less than 1 % of
the variance in happiness, 13 % is accounted for by sex differences in affect intensity, with
women reporting greater intensities of both positive and negative emotions (Fujita et al.
1991).
3
Relative to married individuals, those never married or widowed score lower on
well-being and higher on depression. Poor health goes together with reduced individual
well-being. Finally, a greater proportion of the variation in psychological well-being arises
within individuals than between individuals (thus, suggesting over-time persistence in
psychological well-being).
In Table 3, we use the secondary sample consisting of WLS respondents and their
siblings in a robustness analysis to control for unobserved family-specific factors. In our
RE models BMI effects (now based on adult BMI) on psychological well-being and
depression get stronger after we difference out common family-level factors. A 1 SD
increase in BMI is associated with a decrease in psychological well-being of .111 SDs
adjusting for controls and an increase in the depression score of .091 SDs. Height in this
model is, throughout, statistically insignificant. Overall, the results from the within-family
RE models are similar to those presented above.
4
4 Discussion
Our results have a number of implications. We find that physical attractiveness can be
associated with a statistically significant influence on self-reported well-being and
depression/distress in a large sample of WLS adults. Even when we account for education,
marriage, widowhood, divorce, illnesses and income, all known correlates of subjective
well-being and depression, the effects remain statistically significant for two out of three
3
Interaction effects between gender and the physical attractiveness measures in the models in Table 2were
not significant.
4
We have run additional analyses using the multiple imputation methods (Graham 2009) implemented in
Stata to handle missing values on those of our explanatory variables that have the lowest number of
observations (BMI, height, and number of illnesses, see Table 1). We have run all the models presented in
Tables 2and 3using 20 imputations of missing values for these three variables (which means that we
increase the effective sample size by about 1000 in the models presented in Table 2and by about 700–800 in
the models presented in Table 3). The effects of the attractiveness and control variables in these models are
almost identical to the ones presented in Tables 2and 3, which suggests that there is no systematic pattern in
the missing values which influences our results (available on request).
Beauty in Mind: The Effects of Physical Attractiveness on…
123
measures of attractiveness (facial attractiveness and BMI) on well-being and on distress/
depression.
BMI exerts direct as well as indirect effects on well-being and depression that become
even stronger once we account for unobserved family-level characteristics. BMI may
impact well-being and depression through exposure to weight related stigma and dis-
crimination, internalization of stigma, and social disadvantage or ostracism. Muennig
(2008) suggests that the stress of being overweight or obese may even plausibly explain a
portion of the BMI-health associations.
Table 3 Within-family random effects regressions of psychological well-being outcomes
Model Psychological well-being
a
Depression
12 12
Facial attractiveness – – – –
Body mass index -.116
(.019)***
-.111
(.019)***
.098
(.019)***
.091
(.019)***
Height in inches .018
(.024)
.013
(.023)
-.004
(.023)
.002
(.022)
Sex (=female) -.038
(.045)
-.036
(.048)
Years of schooling .054
(.010)***
-.014
(.010)
Dummy for retired (ref. working) .012 (.034) .006
(.035)
Never married (ref. married) -.140
(.094)
.221
(.091)*
Widowed -.044
(.071)
.282
(.072)***
Divorced -.080
(.060)
.081
(.059)
No. illnesses -.029
(.009)***
.062
(.009)***
Total family income, quintiles .031
(.006)***
-.024
(.006)***
Homeowner .146
(.060)*
-.201
(.060)***
Mental ability .001
(.006)
-.005
(.001)***
Brother pairs -.013
(.065)
-.020
(.064)
Sister pairs .030
(.062)
.074
(.061)
Proportion of variance within-individual .586 .573 .508 .484
R
2
(between-individual) .015 .058 .012 .075
Number of observations 3595 3595 3540 3540
Parameter estimates with standard errors in parenthesis. WLS respondents and siblings sample
*** p\.001; ** p\.01; * p\.05
a
Aggregate scale of scores on personal growth ?purpose in life ?self-acceptance ?environmental
mastery. Model 1 for each outcome includes the physical attractiveness variables while Model 2 includes the
physical attractiveness and the control variables
N. D. Gupta et al.
123
In contrast to Diener et al. (1995) we found statistically significant effects of facial
attractiveness on well-being. Our study differed from theirs in a number of ways: we relied
on high school rather than college year book photographs, a much bigger sample, on older
raters, on different measurements of well-being, and on uncovering effects of physical
attractiveness on well-being and depression measures using panel rather than cross-sec-
tional methods.
Subjective well-being has been operationalized in two ways; as a hedonic state, cap-
tured by self-reports of positive affect, negative affect, and life satisfaction (used by Diener
et al. 1995) or as eudaimonia, a state of flourishing captured by self-reports of aspirations,
self-acceptance, growth, and control over life choices (WLS 1957–2005; Ryff 1989). The
two types of measures are correlated but distinct. It is possible that the difference in the
way we have operationalized well-being contributed meaningfully to our disparate results.
It may be that physical attractiveness is less associated with day-to-day moods than with
feelings of mastery and agency, states that are more affected by constraints on life choices
or aspirations, and that would be fully manifest by middle age.
Our subjective well-being measure focused on feelings of self-confidence, positive self-
regard and agency. Our results are consistent with previous studies that found attractive
people to be more socially at ease (Feingold 1992), more assertive (Jackson and Huston
1975) and more likely to think they are in control of their own lives (Anderson 1978). In an
experimental labor market Mobius and Rosenblat (2006) estimated that the confidence
channel alone accounted for up to 20 % of the beauty premium.
Given the social and economic advantages of perceived facial attractiveness when
young and body weight throughout life it is not surprising that these aspects of appearance
may play a role in the development of positive self-regard, self-confidence and agency.
Internalization or transmission of stereotypes can even lead to behaviors that are self-
fulfilling prophecies. For example, in one study men spoke with women on the telephone
whom they believed to be physically attractive or unattractive (always the same individual,
but the men were given photographs of either attractive or unattractive individuals).
Women who were perceived (unknown to them) to be physically attractive behaved in a
more sociable, outgoing, and warm manner than did those perceived to be unattractive
(Snyder et al. 1977). Interestingly judges rated the men as more outgoing, humorous,
confident, and socially adept when they spoke to the ‘‘attractive women’’. Social warmth
and confidence or its lack emerged as a reciprocal gesture.
5 Limitations
Minorities are not well-represented in the WLS database. Subjects were mainly of German,
English, Irish, Scandinavian, Polish, or Czech ancestry. There were only a small number of
African–American, Hispanic, or Asian subjects.
The WLS raters of facial attractiveness were on average 50 years older than the Diener
et al. (1995) raters. Older judges’ facial ratings tend to be higher than those for younger
adults perhaps because they think all young people are attractive or because they respond
more positively in general (Meland 2002; Ebner 2008). However, the WLS raters came
from roughly the same cohort as the participants and were more likely to rate the pho-
tographs in a way similar to peers at the time would have. They would also be better able to
recognize subtle differences in hair and grooming styles that would affect ratings.
Beauty in Mind: The Effects of Physical Attractiveness on…
123
One can ask whether something other than the attractiveness of facial features accounts
for our findings. It could be that happy people smile more or do more to enhance their
appearance, and that their photographs are rated as more attractive for these reasons.
Harker and Keltner (2001) found that the display of a genuine smile in a college yearbook
photograph predicted well-being outcomes two and three decades later. However, previous
research using the WLS faces did not replicate that finding, (Freese et al. 2007) making
smiling unlikely to account for our findings.
Diener et al. (1995) suggested that part of the small relations they found between facial
attractiveness and subjective well-being may have been because happy people enhanced
their appearance more: effects were reduced when the subject’s usual cosmetics, hairstyles
and clothing were removed or covered. People higher in the personality traits of agree-
ableness and extroversion are judged more attractive than people lower in these qualities,
and crucially, the effect may be mediated by a ‘‘well-groomed appearance’’ (Meyer et al.
2007). Unfortunately this hypothesis cannot be addressed with this database.
Our effect sizes are small but comparable to those of demographic factors.
We acknowledge that well-being and depression are impacted more powerfully by
many other factors. One to be explored in a future paper is social relations beyond mar-
riage, divorce and widowhood (which were explored here). Research indicates that warm
and trusting social relationships are closely tied with subjective well-being (Diener and
Seligman 2002) but theorists question whether positive social relationships are a core
characteristic of eudaimonic well-being or a correlate of it (Waterman 2008). We will
analyze data from Ryff’s ‘‘personal relationships’’ factor along with WLS data on
friendships and relations with others throughout life to hone in on this question we suggest
that beauty may not be an advantage on this well-being factor, particularly in a person’s
relationships with members of the same sex. Several studies have found that others may
avoid, derogate or have negative biases toward attractive individuals of the same sex, male
or female (Agthe et al. 2011).
6 Conclusion
We suggest that attractiveness impacts well-being and depression in a number of ways,
both directly and indirectly. It confers social advantages, leads to conscious and uncon-
scious positive expectations of the attractive and negative stereotypes of the unattractive,
and it has effects on important life outcomes we looked at eudaimonic happiness, a concept
dating back to Aristotle, which philosophers describe as feeling of ‘‘being where one wants
to be, doing what one wants to do,’’ (Norton 1976, p. 216) and as a ‘‘centeredness in one’s
action, identity, strength of purpose and competence’’ (Waterman 2008, p. 236). We
suggest that greater societal action aimed at lowering appearance discrimination in the
workplace and elsewhere, combined with advocacy of programs to support enhanced body
satisfaction, and avoidance of messages that decrease body satisfaction would help to
increase subjective well-being for many.
To the long list of the factors associated with physical attractiveness, we must add two
others—positive mental well-being and (lower risk of) depression. Both have effects on
life outcomes making attractiveness an issue of importance and concern.
Acknowledgments We use data from the WLS of the University of Wisconsin-Madison. Since 1991, the
WLS has been supported by the National Institute on Aging (AG-9775 AG-21079 and AG-033285), with
additional support from the Vilas Estate Trust, the National Science Foundation, the Spencer Foundation,
N. D. Gupta et al.
123
and the Graduate School of the University of Wisconsin-Madison. A public use file of data is available from
the WLS, University of Wisconsin-Madison, 1180 Observatory Drive, Madison, Wisconsin 53706 and at
http://www.ssc.wisc.edu/wlsresearch/data/. We thank Danielle Barry and Lauren Haley for assistance.
Appendix
See Table 4.
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Table 4 Correlations between main variables
H54 H65 D54 D65 FA BMI54 BMI65
Happiness age 54 (H54)
Happiness age 65 (H65) .595
Depression age 54 (D54) -.575 -.409
Depression age 65 (D65) -.398 -.537 .529
Facial attractiveness (FA) .081 .060 -.065 -.043
BMI age 54 (BMI54) -.094 -.128 .070 .086 -.092
BMI age 65 (BMI65) -.072 -.128 .056 .089 -.083 .834
Height (H) .038 .039 -.019
ns
-.017
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.023
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-.057 -.023
ns
WLS respondents sample
All correlations significant at p\0.05 or better unless stated otherwise
ns
Not statistically significant
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