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Personality and well-being 1
Running Head: PERSONALITY AND WELL-BEING
Happiness is a Personal(ity) Thing: The Genetics of Personality and Well-being in a
Representative Sample
Alexander Weiss and Timothy C. Bates
University of Edinburgh
Michelle Luciano
Queensland Institute of Medical Research
Personality and well-being 2
Abstract
While happiness has a genetic component it has been unclear what might explain these
heritable differences. Here we use a population sample of 973 twin-pairs to test the
hypothesis that heritable differences in subjective wellbeing are entirely accounted for by
genetic architecture of the five-factor model personality domains. Results supported a model
in which wellbeing was accounted for by unique genetic influences on extraversion,
neuroticism, and conscientiousness, and by a genetic “covitality” factor influencing all five
major personality domains in the direction of low N, and high extraversion, openness to
experience, agreeableness, and conscientiousness, as well as elevated wellbeing.
Personality and well-being 3
Happiness is a personal(ity) thing: The Genetics of Personality and Well-being in a
Representative Sample
The fact that personality dimensions, especially Neuroticism and Extraversion,
explain a substantial amount of subjective well-being is well-known. To date there are several
explanations offered, though none so far has considered the possibility that common genes
explain variance in personality and subjective well-being. In the present study we used a
large representative twin sample to test whether the latent genetic effects explaining the
individual differences in the Five-Factor Model (FFM) of personality also account for
individual differences in subjective well-being.
A considerable body of work has focussed on the construct of subjective well-being,
operationalized in reliable measures of positive and negative moods and global satisfaction
(Diener, Suh, Lucas, & Smith, 1999). Researchers have found that subjective well-being was
largely independent of environmental and socio-economic differences, and showed high
levels of within-person stability across measurement times (Lykken & Tellegen, 1996) and
high heritability (Lykken & Tellegen, 1996; Nes, Røysamb, Tambs, Harris, & ReichbornKjennerud, 2006). Other studies indicated that subjective well-being was strongly linked to
the FFM, especially Neuroticism, Conscientiousness, and Extraversion (DeNeve & Cooper,
1998). In addition, Agreeableness and Openness to Experience also appear to play roles in
some elements of happiness and unhappiness (McCrae & Costa, 1991).
Given that subjective well-being variance is mostly stable and not the result of
environmental or demographic factors prompted some to suggest that individuals have
biologically-based, stable well-being “set points” (Lykken & Tellegen, 1996). This
hypothesis is supported by behavior genetic studies which have found that genetic effects
explain approximately 50% of variance in subjective well-being, with evidence for both
additive (Nes et al., 2006) and non-additive (gene × gene interaction) genetic effects (Lykken
Personality and well-being 4
& Tellegen, 1996). These behavior genetic studies also did not find evidence for significant
common environmental effects, i.e. all of the familial similarity between siblings within
families appears to be genetic in origin. In fact, these studies found that environmental
impacts on subjective well-being consist of non-familial environmental effects. These
findings are supported by non-behavior genetic research showing that finding or losing a job
(Lucas, Clark, Georgellis, & Diener, 2004) and change in marital status (Lucas, Clark,
Georgellis, & Diener, 2003) can affect subjective well-being.
Like subjective well-being, the domains of the FFM are also mostly stable in
adulthood (see, e.g., Roberts, Walton, & Viechtbauer, 2006) and heritable (Bouchard &
Loehlin, 2001). Moreover, numerous studies have shown that personality traits, especially
Extraversion and Neuroticism, account for approximately half of the variance in subjective
well-being (DeNeve & Cooper, 1998). Previously offered explanations for these correlations
include direct effects, such as the relationship of Extraversion and Neuroticism to reward and
punishment, respectively (Cantor & Sanderson, 1999; Carver & Scheier, 1990; Carver &
White, 1994) as well as indirect or instrumental effects, where trait differences act to alter the
experiences an individual encounters (McCrae & Costa, 1991).
One explanation for the correlation between personality and subjective well-being is
that, as with Neuroticism and depression (Kendler, Gardner, Gatz, & Pedersen, 2007;
Kendler, Gatz, Gardner, & Pedersen, 2006) personality and well-being share genes in
common.
We tested a common genetic cause hypothesis in a large representative sample of
adult United States twins. Our hypothesis posits that the heritable component of subjective
well-being is entirely explained by the latent genetic architecture of the FFM. If supported,
this hypothesis provides important insights for theories of subjective well-being, suggesting
Personality and well-being 5
that the genetic and environmental models of subjective well-being may be framed in terms
of personality.
Methods
Participants
The sample consisted of 973 twin-pairs from the MacArthur Foundation Survey of
Midlife Development in the United States (MIDUS). Sample recruitment was initially by
telephone. Approximately 50,000 households, representative of the population of the United
States were screened by telephone. Just under 15% of respondents reported having a twin in
the family, of whom 60% gave permission for the twins to be contacted as part of the MIDUS
recruitment process (Kendler, Thornton, Gilman, & Kessler, 2000; Kessler, Gilman,
Thornton, & Kendler, 2004). Zygosity was determined using self-report questions (eye and
hair color similarity, similarity in childhood indicated by misidentification) with > 90%
accuracy (Lykken, Bouchard, McGue, & Tellegen, 1990).
Inclusion criteria included being first degree relatives of the original contact or their
partner, currently aged between 25 and 74 years, living in the continental United States,
having home contact telephone, speaking English. The resultant twin sample consisted of 973
twin-pairs (365 MZ and 608 DZ) where at least one member of the pair had some personality
or subjective well-being data. Mean age was 44.9 (SD = 12.1). The number of each twin pair
type and their ages are shown in Table 1.
----------------------------------Insert Table 1 about here
----------------------------------Measures
Personality. The Midlife Development Inventory (MIDI), a self-administered 25-item
4-point Likert scale adjectival personality questionnaire (Lachman & Weaver, 1997) was
Personality and well-being 6
mailed to each participant. Adjectives were chosen from existing measures (e.g., Goldberg,
1990). We used the five previously defined scales (University of Wisconsin Institute of
Aging, 2004). Briefly, each personality scale was constructed by summing up the items
defining that dimension: Neuroticism was defined by moody, worrying, nervous, and
(reversed) calm; Extraversion was defined by outgoing, friendly, lively, active, and talkative;
Openness to Experience was defined by creative, imaginative, intelligent, curious, broadminded, sophisticated, and adventurous; Agreeableness was defined by helpful, caring, warm,
soft-hearted, and sympathetic; and Conscientiousness was defined by organized, responsible,
hardworking, and (reversed) careless.
Subjective well-being. We assessed subjective well-being using three questions from
the MIDUS sample that were similar to those used in other scales (see, e.g., Diener, Suh,
Lucas, & Smith, 1999). Questions were part of a telephone interview. The first question
asked how satisfied participants were with life at the present, the second asked how much
control subjects felt they had over their lives, and the third question asked how satisfied they
were with life overall. As with the personality questionnaire, each question could be
answered using a four-point Likert Scale with lower values indicating higher subjective wellbeing. For the purpose of the present study we reverse-coded and summed these items.
Analysis
A classical twin design, in which the resemblance of identical and non-identical twins
is compared, was used. Based on previous findings indicating the possibility of nonadditive
genetic effects and the lack of shared environmental effects (Lykken & Tellegen, 1996), we
used structural equation models to specify the covariance of identical twins as additive (A)
plus dominance (or non-additive) genes (D), and the covariance of non-identical twins as
0.5A plus 0.25D. Unique environmental (E) sources of variance are unshared between co-
Personality and well-being 7
twins so only contribute to trait variance. Parameter estimates for A, D and E were estimated
by maximum likelihood in Mx (Neale, Boker, Xie, & Maes, 1999).
Multivariate genetic modeling began from the approach of Cholesky decomposition
of additive genetic, dominance genetic, and unique environmental covariance between the
measures. This specifies as many factors as there are variables for each source of variance,
each factor having one loading less than the previous one. Reduced models (i.e., those with
fewer parameters) are favored if the likelihood ratio chi-square comparing the models is less
than the critical value (alpha = .05) of the chi-square distribution, indicating that there is no
significant difference between the saturated model and the reduced model.
Results
Table 2 shows the means and standard deviations for the personality domains and
subjective well-being and the MZ and DZ correlations. Monozygotic twin correlations were
substantially greater than dizygotic twin correlations, consistent with prior findings
suggesting a non-additive genetic component to subjective well-being and little evidence for
shared environmental effects (Lykken & Tellegen, 1996). We therefore included genetic
dominance rather than shared environmental effects in our base model.
Testing for bivariate normality using the “%P” function in Mx (z < -3.5 or > 3.5)
identified 8 outliers, which were removed from further analyses. We also controlled for
gender and age as males had significantly lower levels of Neuroticism, Agreeableness, and
Conscientiousness and older individuals had lower levels of Neuroticism and Openness but
higher levels of Agreeableness and subjective well-being (see Table 3).
----------------------------------Insert Tables 2, 3, and 4 about here
-----------------------------------
Personality and well-being 8
The hypothesized model specified that all genetic influences on subjective well-being
originated from a general genetic factor and genetic factors for the five personality domains.
This model therefore posited general latent additive and dominance genetic effects
underlying variance in all five personality domains and subjective well-being as well as
specific additive genetic and dominance effects for the five personality domains, which also
had the opportunity to explain variance in subjective well-being (see Figure 1). The fit of this
model was assessed using the chi-square and AIC criteria. Table 4 shows the fit statistics for
each model. There was no significant loss of fit between this model and the saturated model.
----------------------------------Insert Figure 1 about here
----------------------------------The hypothesised model was then further reduced by removing genetic paths from the
Agreeableness and Openness factors to Subjective well-being, as these were non-significant.
Finally, we tested whether dominance effects were significant; eliminating dominance effects
did not significantly reduce model fit. Thus, the final model included a general additive
genetic factor that contributed to variance in all five personality domains and subjective wellbeing, as well as specific genetic factors influencing each personality domain, and paths from
the independent genetic influences on Neuroticism, Extraversion, and Conscientiousness to
subjective well-being (see Figure 2). The corresponding E or unique-environment effects
were modelled as a Cholesky decomposition, and are presented in Table 5.
----------------------------------Insert Figure 2 and Table 5 about here
-----------------------------------
Personality and well-being 9
Discussion
The genetic structure of subjective well-being can be modelled adequately without
reference to genetic influences specific to subjective well-being. The model also indicated
that the observed correlations between subjective well-being and the FFM domains have a
genetic component, and that subjective well-being reflects differences in low Neuroticism,
high Extraversion, and, to a lesser extent, high Conscientiousness. Our findings cast previous
findings that showed a relationship between personality domains and subjective well-being
(McCrae & Costa, 1991) in a new light by showing that a common genetic cause underlies
variation in these important constructs. Moreover, our findings extend previous behavior
genetic findings on personality and subjective well-being (Bouchard & Loehlin, 2001;
Lykken & Tellegen, 1996; Nes et al., 2006) and depression (Kendler et al., 2007; Kendler et
al., 2006) by showing that a large part of the genetic architecture underlying individual
differences in happiness, is provided by the genetic structure of the FFM.
In this sample it was possible to drop the dominance effects without significantly
reducing fit. While this is not consistent with the findings of Lykken & Tellegen (1996) it is
consistent with other findings (Nes et al., 2006). One reason for the disparate findings of
dominance effects on well-being is that classical twin designs have low power to detect
dominance effects (Neale & Cardon, 1992). Thus an extended twin design or larger sample
would be needed to definitively address the question of whether dominance variance or
something like DZ sibling-contrast effects (Eaves & Silberg, 2005) are responsible for the
substantially higher MZ twin correlations in subjective well-being.
Finally, all models required a general latent genetic factor for all the five personality
domains and subjective well-being. This may reflect either a general factor such as lifehistory strategy (Figueredo, Vasquez, Brumbach, Sefcek, Kirsner, & Jacobs, 2005), but may
also reflect presentation bias or some other method factor. Future twin studies of personality
Personality and well-being 10
and subjective well-being that incorporate multiple methods (see, e.g. Riemann, Angleitner,
& Strelau, 1997) may clarify this issue.
In conclusion, the present study supports the presence of a general genetic factor,
possibly reflecting covitality (Weiss, King, & Enns, 2002), and additional effects of
personality on subjective well-being. Just as significant insights into physical and mental
illness have flowed from studies relating illness to normal variation in personality and from
research on the causes of co-morbidity (see, e.g., Deary, Wright, Harris, Whalley, & Starr,
2004), further research on the general and specific influences on subjective well-being may
lead to major advances in the understanding of happiness and other constructs of interest to
positive psychology.
Personality and well-being 11
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Personality and well-being 14
Author Note
Alexander Weiss, Department of Psychology, School of Philosophy, Psychology, and
the Language Sciences, The University of Edinburgh; Timothy C. Bates, Department of
Psychology, School of Philosophy, Psychology, and the Language Sciences, The University
of Edinburgh; Michelle Luciano, Queensland Institute of Medical Research.
Acknowledgements???
Correspondence concerning this article should be addressed to Alexander Weiss,
Department of Psychology, School of Philosophy, Psychology, and the Language Sciences,
The University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, United Kingdom. Email: [email protected].
Personality and well-being 15
Table 1
Mean Age for Each Twin-pair Type
Zygosity
MZ
DZ
Type
Count
Age (SD)
Count
Age (SD)
Male1
171
44.5 (11.5)
136
44.2 (12.5)
Female2
194
43.5 (12.2)
213
45.9 (12.4)
259
45.8 (11.9)
Opposite Sex3
Note. 1Same-sex male pairs, 2Same-sex female pairs, 3Opposite-sex pairs
Personality and well-being 16
Table 1
Means and Standard Deviations of the Five Personality Domains and Subjective Well-being and their Correlations by Zygozity.
Monozygotic
Dimension
MTI
Neuroticism
Dizygotic
SDT1
M T2
SD T2
rT1,T2
3.51
.45
3.52
.48
.27
Extraversion
2.25
.72
2.23
.66
Openness
2.99
.52
3.00
Agreeableness
3.20
.58
Conscientiousness
3.43
.45
Subjective well-being
10.92
MTI
SDT1
M T2
SD T2
rT1,T2
3.52
.47
3.54
.47
.12
.44
2.22
.65
2.28
.66
.19
.51
.30
2.94
.52
2.97
.55
.12
3.24
.54
.39
3.22
.54
3.23
.57
.16
3.47
.42
.35
3.43
.43
3.44
.42
.13
1.49 10.91
1.43
1.37 10.86
1.44
.09
.30 10.92
Note. MT1 = Twin 1 mean; MT2 = Twin 2 mean; SDT1 = Twin 1 standard deviation; SDT2 = Twin 2 standard deviation, rT1,T2 = twin correlation.
Personality and well-being 17
Table 3
Modelled Gender and Age Effects
Male Deviation from Female Mean bage
Neuroticism
-.11
-.008
Extraversion ns
ns
O
ns
-.004
A
-.24
.002
C
-.10
ns
WB
ns
.005
Note. ns = p > .05.
Personality and well-being 18
Table 4
AIC and χ2 Fit Statistics for Hypothesised model, and Reduced Models of Personality Domains and Subjective Well-being.
Model
-2LL
df
² (df)
p
AIC
Saturated ADE Model
13040.402
10343
Hypothesized Model
13046.094
10353
5.69 (10)
0.84
-14.31
Drop Additive Genetic Oaths from Openness and
13047.878
10357
7.48 (14)
0.91
-20.52
13067.877
10371
27.47 (28)
0.49
-28.52
Agreeableness to SWB
Drop All Dominance effects
Note. -2LL = -2 log-likelihood; ² (df) = calculated on change in -2LL and change in df between nested models; AIC = Akaike’s Information
Criterion.
Personality and well-being 19
Table 5
Cholesky Decomposition of Unique variance– Standardised Path Coefficients
Factor
Factor
1
2
3
4
5
1
-.73
2
.05
.78
3
.12
.36
.64
4
.02
.44
.11
.75
5
.19
.11
.13
.11
.69
6
.20
.12
.04
.09
.06
6
.84
Personality and well-being 20
Figure Captions
Figure 1. Hypothesised model in which genetic effects on measured subjective well-being are
accounted for by a general covitality factor (AG) common to all traits, and by influences from
the latent genetic effects of the five personality domains (AN, AE, AO, AA, AC).
Figure 2. Final reduced model with standardized path coefficients. Values in parentheses are
95% confidence intervals.
Personality and well-being 21
Figure 1
AG
N
E
O
AN
AE
AO
A
AA
C
AC
W
Personality and well-being 22
Figure 2
AG
.15
(.02, .23)
-.29
(-.21, -.38)
.55
(.43, .65)
N
AN
E
O
-.62
(-.54, -.68)
.30
(.15, .41)
.23
(.13, 33)
.37
.30
(.18, .38)
A
.49
(.41, .55)
.32
(.21, .41)
C
AO
W
.58
(.50, .64)
.37
(.26. .44)
(.27, .45)
AE
.45
(.37, .53)
AA
.09
(.02, .18)
AC