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A Genetic Component to National Differences in Happiness

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A Genetic Component to National Differences in Happiness

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National differences in subjective well-being (SWB) have been attributed to socioeconomic, climatic, and genetic factors. We focus on one particular facet of SWB—happiness or positive affect—measured by the nationally representative World Values Survey (WVS). We find that national percentages of very happy people across the three latest WVS waves (2000–2004, 2005–2009, 2010–2014) are consistently and highly correlated with national prevalence of the rs324420 A allele in the FAAH gene, involved in the hydrolysis of anandamide, a substance that reportedly enhances sensory pleasure and helps reduce pain. Climatic differences are also significantly associated with national differences in happiness, whereas economic wealth, recent economic growth, rule of law, pathogen prevalence, and the distribution of short versus long alleles in the serotonin transporter gene SLC6A4 are not significant predictors of national happiness.
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1 23
Journal of Happiness Studies
An Interdisciplinary Forum on
Subjective Well-Being
ISSN 1389-4978
J Happiness Stud
DOI 10.1007/s10902-015-9712-y
A Genetic Component to National
Differences in Happiness
Michael Minkov & Michael Harris Bond
1 23
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RESEARCH PAPER
A Genetic Component to National Differences
in Happiness
Michael Minkov
1
Michael Harris Bond
2
Springer Science+Business Media Dordrecht 2016
Abstract National differences in subjective well-being (SWB) have been attributed to
socioeconomic, climatic, and genetic factors. We focus on one particular facet of SWB—
happiness or positive affect—measured by the nationally representative World Values
Survey (WVS). We find that national percentages of very happy people across the three
latest WVS waves (2000–2004, 2005–2009, 2010–2014) are consistently and highly cor-
related with national prevalence of the rs324420 A allele in the FAAH gene, involved in
the hydrolysis of anandamide, a substance that reportedly enhances sensory pleasure and
helps reduce pain. Climatic differences are also significantly associated with national
differences in happiness, whereas economic wealth, recent economic growth, rule of law,
pathogen prevalence, and the distribution of short versus long alleles in the serotonin
transporter gene SLC6A4 are not significant predictors of national happiness.
Keywords Genes Happiness Positive affect Climate National wealth
1 Introduction
A number of recently published studies have shown associations between measures of
national culture and national prevalence of specific genetic polymorphisms (e.g., Chiao and
Blizinsky 2010; Fischer 2013; Kong 2014; Minkov et al. 2015; Minkov and Bond 2015;
Mrazek et al. 2013; Way and Lieberman 2010, etc.). Although all these studies are
&Michael Minkov
michaelminkov@yahoo.com
Michael Harris Bond
ssmhb@polyu.edu.hk
1
Varna University of Management, ul. Tsarigradsko Shose 149 B, 1784 Sofia, Bulgaria
2
Department of Management and Marketing, Faculty of Business, Hong Kong Polytechnic
University, Kowloon, Hong Kong, SAR, China
123
J Happiness Stud
DOI 10.1007/s10902-015-9712-y
Author's personal copy
characterized by various limitations, some of which are very serious (Eisenberg and Hayes
2011; Minkov et al. 2015), the search of genetic components of national culture is
becoming a promising research field, as the data base of available markers grows.
National culture is closely related to aggregate national personality traits (Hofstede and
McCrae 2004). A decade ago, Allik and McCrae (2004) expressed the opinion that genetic
differences between nations may account for national differences in aggregated personality
traits. This hypothesis has never been tested in depth. However, some preliminary findings
suggest that Allik and McCrae may be right. Minkov et al. (2015) have reported an
association between a national genetic index and aggregate national neuroticism. Since
neuroticism is associated with subjective well-being (SWB), this suggests that national
differences in SWB may have a genetic component.
In this article we focus on a particular facet of SWB—happiness or positive affect—and
test the hypothesis that national measures of that facet have a genetic component that
remains statistically significant after controlling for other plausible predictors.
It is well-known that national measures of happiness are not perfectly stable. A
stable factor, such as a nation’s genetic profile, cannot explain on its own any fluctuations
in any measure. At best, it can explain only the stable element in the observed national
differences in happiness. The object of our study is precisely to explain that stable element.
1.1 Previously Reported Predictors of National Differences in Subjective
Well-Being
There is a vast array of studies explaining national differences in SWB. Although a variety
of different predictors has been proposed, the available evidence suggests some conver-
gence in the results. Analyses of large-scale studies of SWB, such as the nationally rep-
resentative World Values Survey (WVS; www.wordlvaluessurvey.com), are quite
unequivocal. Minkov’s (2009) analysis of WVS data from representative populations in 97
countries led to the conclusion that the strongest predictor of national differences in SWB
are average differences in life control or freedom of choice endorsed by that nation’s
population, i.e., the feeling that one controls one’s life and can live it as one wishes.
Interesting as this finding may be, it is circular as it does not explain what accounts for
national differences in perceived freedom of choice.
Inglehart et al. (2008) report the same finding: the main predictor of happiness differ-
ences across nations is the feeling of freedom of choice. These authors go a step further in
their analysis. They find that, at the national level, this sense of freedom is a function of
national economic development, democratization, and increasing social tolerance. This
suggests that the distal predictors of national differences in happiness are two strongly
correlated variables: national wealth and the rule of law. However, this argument cannot
explain why the highest percentages of very happy people in the WVS are consistently
found in northern Latin America and West Africa (Nigeria and Ghana). These regions rank
low in national wealth and economic growth. They may have free elections, but they are
characterized by little effective rule of law, since they have the highest murder and robbery
rates in the world as well as high levels of corruption (Minkov 2011).
Other studies report a similar association between national wealth and happiness. Based
on such findings, Jorm and Ryan (2014) concluded that economic growth in poor countries
will improve global subjective well-being even though higher-income countries need to
focus on other determinants of well-being. Di Tella et al. (2003) found that movements in
reported well-being are associated with movements in gross national domestic product.
The statistical correlations that these studies report across a large number of nations may be
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significant, but the mystery of the high happiness levels in northern Latin America and
West Africa remains.
An alternative explanation is provided by van de Vliert (2009). This author recognizes
the association between national wealth and SWB, but analyzes climatic factors as well,
such as harshness of summers and harshness of winters. From the perspective of this
theory, people from poor societies in geographic areas that do not have excessive climatic
variation are likely to be happier than people in poor societies with excessive climates. Van
de Vliert’s theory thus may be able to explain the happiness paradox of Latin America and
West Africa. However, his explanation of the relatively high happiness of Scandinavians is
less convincing. In his view, people in rich countries need a cold climate to be happy,
because it provides much-needed stimulation for productive activity. In an affluent society,
people cannot be happy without dealing with some challenge. This hypothesis is yet to be
proven.
If climatic factors are associated with subjective well-being, it is plausible that pathogen
prevalence (Murray and Schaller 2010) will also be correlated with it, as pathogen
prevalence is related to climate. Inglehart et al. (2013) launched the idea that parasite
(pathogen) prevalence may account for cultural and economic factors that ultimately affect
happiness.
Recently, Proto and Oswald (2014) offered a genetic explanation. In their view, ‘‘na-
tional happiness’’ (the term used in the title of their publication) has a genetic component.
Happier nations have a lower prevalence of a specific genetic polymorphism: short alleles
in the 5-HTTLPR variable number tandem repeat (VNTR) of the serotonin transporter
gene. Individual-level studies have associated that polymorphism with negative affect and
depressiveness.
At this point, we must dwell on the confusing terminology used in various studies of
SWB. This construct is defined as ‘‘a person’s evaluative reaction to his or her life—either
in terms of life satisfaction (cognitive evaluations) or affect (ongoing emotional reac-
tions)’’ (Diener and Diener 1995, p. 653). These two facets of SWB have also been defined
as ‘‘cognitive’’ (or ‘‘evaluations of one’s life according to subjectively determined stan-
dards’’) and ‘‘hedonic balance’’ (or ‘‘the balance between pleasant affect and unpleasant
affect’’) (Schimmack et al. 2002, p. 582). Unfortunately, many published studies do not
distinguish clearly between these two facets of SWB.
The WVS regularly fields two items that address SWB. One of these (item v10 in the
more recent WVS waves) asks the respondents, ‘‘Taking all things together, would you say
you are’. The possible answers are: ‘‘very happy’’, ‘‘rather happy’’, ‘‘not very happy’’,
and ‘‘not at all happy’’. Another question (item v23 in the latest WVS wave) asks, ‘‘All
things considered, how satisfied are you with your life as a whole these days? Using this
card on which 1 means you are ‘completely dissatisfied’ and 10 means you are ‘completely
satisfied’ where would you put your satisfaction with your life as a whole?’
Although the happiness item and the life satisfaction item are highly correlated at the
national level (Minkov 2009), they do not measure the same thing in all countries. Sim-
ilarly, at the individual level, their within-nation correlation also varies across nations from
high to only moderate. The happiness item seems to tap the hedonic element of SWB,
whereas the life satisfaction item elicits a cognitive appraisal. Evidence for this distinction
comes from sub-Saharan Africa. In a number of countries in that region, respondents
evidently dissociate happiness and life satisfaction, because these countries score high on
the former and low on the latter. Interviews that the first author of this article regularly
conducts with Nigerian students confirm this perceived dichotomy. Nigerians say that
happiness means being in a good mood, probably an innate personality trait. Life
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satisfaction, however, comes from an appraisal of one’s achievements. Thus, it is possible
to be in a good mood in a country like Nigeria, but it is hard to be satisfied with one’s life,
as one cannot achieve much in such a national culture.
If Proto and Oswald (2014) are right, and national differences in SWB do have a genetic
element, it should manifest itself in the hedonic component of SWB. We can expect
associations between a national genetic index and national differences in aggregate Big-
Five personality traits, or specific facets of such traits, such as positive affect, in accor-
dance with the argument of Allik and McCrae (2004). Genes may somehow be involved in
the cognitive element of SWB as well, yet we lack individual-level studies that suggest a
plausible mechanism. As for the hedonic element, we explain below why a genetic con-
tribution to its strength at both the individual and national levels is plausible.
1.2 Potential Genetic Contributors to Happiness
Serotonin is a chemical in the human brain that maintains mood balance. It has been found
to play a role in susceptibility to depression and suicide (Young 2007). The SLC6A4 gene
encodes the serotonin transporter protein (SERT or 5-HTT). The short (S) allelic variant of
the serotonin transporter-linked polymorphic region (5-HTTLPR) is associated with
reduced SERT availability and function compared with the long (L) form, as well as with
anxiety and neuroticism (Homberg and Lesch 2011). This pattern of relationships suggests
that Proto and Oswald’s (2014) hypothesis concerning the association between the
5-HTTLPR polymorphism and national differences in happiness is plausible. However,
those authors did not test that hypothesis appropriately, because they did not have sufficient
data concerning the worldwide prevalence of the S and L alleles. Working with a small and
globally unrepresentative sample of nations can result in erroneous conclusions about the
association between national differences in genes and personality or culture (Eisenberg and
Hayes 2011; Minkov et al. 2015).
Anandamide is a naturally occurring endogenous brain cannabinoid that has been shown
to enhance sensory pleasure (Mahler et al. 2007). It also plays an important role in pain
suppression (Walker et al. 1999). Anandamide is degraded by the enzyme fatty acid amide
hydrolase (FAAH; McKinney and Cravatt 2005), which suggests that inhibition of FAAH
may be an approach to anti-anxiety therapy (Kathuria et al. 2002). Mice that lack FAAH
display reduced pain sensation (Cravatt et al. 2001). Pharmacological blockade of FAAH
produces anxiolytic (anxiety-reducing) effects (Gaetani et al. 2003).
The FAAH gene encodes a protein that is responsible for the hydrolysis of anandamide
(National Center for Biotechnology Information 2015). It has a single nucleotide poly-
morphism (SNP) known as rs324420. The A allele of this SNP is associated with increased
anandamide signaling (Conzelmann et al. 2012), as well as reduced FAAH expression and
decreased anxiety (Dincheva et al. 2015). Similar conclusions were reached by Hariri et al.
(2009): the A allele was associated with reduced threat-related reactivity and increased
reward-related reactivity. Also, Conzelmann et al. (2012) found an association between the
A allele and reduced brain reactivity toward unpleasant faces as well as enhanced reactivity
towards reward.
Collectively, these findings suggest that A-allele carriers may be less prone to anxiety
and, consequently, report higher baseline happiness. Nations with a higher prevalence of
the A allele may thus have higher percentages of happy people. This hypothesis has never
been tested so far.
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2 Method
We used the nationally representative WVS (www.worldvaluesurvey.com) to calculate
average national percentages of respondents who reported that they were ‘‘very happy’’. In
the 2010–2014 WVS wave, these percentages range from 67.5 in Mexico to 5.3 in Egypt,
dwarfing the national differences in the percentages of respondents who have chosen any of
the other three response options. We know from empirical studies that positive affect and
negative affect are not two sides of the same coin; they appear to be independent
dimensions (Kuppens et al. 2006; Schimmack et al. 2002). In this study, we are interested
in national differences in happiness rather than unhappiness; that is, positive affect rather
than negative affect. Therefore, we analyze only the percentages of people who state
unambiguously that they are happy. Minkov (2013) shows that selection of ambiguous
positions on a four-point Likert scale, such as ‘‘somewhat’ or ‘‘rather’’, usually results
in poor predictive properties at the national level. This is so because selection of the
‘somewhat’’ or ‘‘rather’’ position on the WVS four-point Likert scale apparently denotes
uncertainty and ambiguity on the part of the respondent.
To minimize the effect of ephemeral situational factors (such as a sudden rise of
unemployment) and random measurement error, we averaged the data from the three latest
WVS waves: 2000–2004, 2005–2009, and 2010–2014. Table 1shows correlations between
the national percentages of very happy people in these three waves. The high correlations
suggest high stability in the observed national differences in happiness and justify the
averaging of the data into a single 2000–2014 national happiness index, reflecting per-
centages of people in nationally representative studies who regularly experience positive
affect.
To validate our happiness index, we used a measure by Kuppens et al. (2006): a national
positive affect index (component 1 in Table 1in that publication).
Since the number of WVS countries that are represented in all three waves from 2000 to
2014 is relatively small, we decided to include also those nations that are represented in at
least two waves during that period. We used the three-wave index as a dependent variable
and data from two waves at a time to predict scores on the three-wave index by means of
linear regressions. R square values exceeded .95, attesting to the high reliability of the
estimates.
To enlarge our index even more, we also calculated predicted scores for countries that
were studied only once by the WVS in 2000–2014. Although these regression models also
showed highly acceptable reliability (R
2
[.90), we took a conservative approach and
analyzed the resulting happiness index separately.
Table 1 Correlations between national percentages of World Values Survey respondents who report that
they are ‘‘very happy’’, WVS waves 2000–2004, 2005–2009, 2010–2014
Percentage very happy
2005–2009
Percentage very happy
2000–2004
Percentage very happy
2010–2014
.83* (n=36) .78* (n=24)
Percentage very happy
2005–2009
.80* (n=22)
* Correlation significant at the .001 level
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Table 2 Sources of rs324420 A allele estimates
Country Source
Algeria Estimate based on converging data for Algerian Mozabites (Berbers) in Kidd (2014) and
Palestinian Arabs in Kidd (2014)
Andorra Estimate based on converging data for Spain in De Luis et al. (2013) and French in Kidd
(2014)
Argentina Estimate based on data for Spain, assuming a small Amerindian admixture
Australia Estimate based on data for European Americans in Kidd (2014)
Austria Estimate based on Germany
Belarus Estimate based on Russia
Botswana Estimate based on data for southern African Bantu populations in Kidd (2014)
Brazil Estimate based on Spain, as well as data for West African Blacks in Kidd (2014), taking
into account Brazil’s racial composition
Bulgaria Estimate based on nearly converging data for Greece and Hungary
Burkina Faso Estimate based on data for West Africans in Kidd (2014)
Canada Estimate based on data for European Americans in Kidd (2014)
Cambodia Data for Khmers in Kidd (2014)
Chile Estimate based on Argentina
China Data for Han in Kidd (2014)
Colombia Estimate based on Spain, as well as data for Amerindians and West African Blacks in Kidd
(2014), taking into account Colombia’s racial composition
Cyprus Estimate based on Greece
Denmark Jensen et al. (2007)
Ecuador Estimate based on Spain, as well as data for Amerindians in Kidd (2014), taking into
account Ecuador’s racial composition
Egypt Estimate based on converging data for Algeria and Palestine
El Salvador Estimate based on Spain, as well as data for Amerindians in Kidd (2014), taking into
account El Salvador’s racial composition
Estonia Kidd (2014)
France Kidd (2014)
Germany Doehring et al. (2007)
Ghana Estimate based on data for West Africans in Kidd (2014)
Greece Marinos et al. (2014)
Hong Kong Data for Han in Kidd (2014)
Hungary Kidd (2014)
India Data for Indian and Pakistani ethnic groups in Kidd (2014). Despite the significant
divergence between the data for Dravidians in the south of India and the northern
populations, a median value is plausible for India as a whole
Indonesia Calculated from data for Malays (healthy controls) in Sim et al. (2013)
Ireland Kidd (2014)
Iraq Estimate based on data for Palestinians in Kidd (2014)
Italy Estimate based on data from Kidd (2014)
Japan Estimate based on data from Kidd (2014)
Jordan Estimate based on data for Palestinians in Kidd (2014)
Korea Kidd (2014)
Laos Kidd (2014)
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Although our study focuses on national differences in positive affect, not life appraisal,
we did consider the life satisfaction item (v23 in the 2010–2014 WVS). However, as we
demonstrate in the Sect. 3, it proved to be out of place in an analysis of the relationship
between genes and SWB at the national level.
Table 2 continued
Country Source
Malaysia Calculated from data for Chinese and Malays (healthy controls) in Sim et al. (2013), as well
as Dravidian populations in Sim et al. (2013), taking into consideration Malaysia’s ethnic
composition
Mexico Estimate based on Spain and data for Amerindians in Kidd (2014), taking into
consideration Mexico’s racial composition
Mongolia Kidd (2014)
Morocco Estimate based on Algeria
New Zealand Estimate based on data for European Americans in Kidd (2014)
Nigeria Estimate based on data for Hausa and Yoruba in Kidd (2014)
Norway Estimate based on Denmark
Pakistan Estimate based on data for Pakistani populations in Kidd (2014)
Palestine Kidd (2014)
Peru Estimate based on data for Quechua (Kidd 2014) and Spain, taking into account Peru’s
racial composition
Romania Estimate based on nearly converging data for Greece and Hungary
Russia Kidd (2014)
Rwanda Estimate based on data for southern African Bantu populations in Kidd (2014)
Singapore Calculated from data for Chinese and Malays (healthy controls) in Sim et al. (2013), as well
as Dravidian populations in Sim et al. (2013), and Han in Kidd (2014), taking into
account Singapore’s ethnic composition
South Africa Estimate based on data for southern African Bantu populations in Kidd (2014), assuming a
small, predominantly European admixture
Spain De Luis et al. (2013)
Sri Lanka Estimate based on data for South Indian populations in Kidd (2014)
Sweden Estimate based on Denmark
Switzerland Estimate based on Germany
Syria Estimate based on Palestine
Taiwan Data for Han in Kidd (2014)
Thailand Estimate based on data for Khmers in Kidd (2014)
Tunisia Estimate based on Algeria
Uganda Estimate based on data for southern African Bantu populations in Kidd (2014)
Ukraine Estimate based on data for Russians in Kidd (2014)
United
Kingdom
Estimate based on data for converging data for Irish and European Americans in Kidd
(2014)
Venezuela Estimate based on Spain, as well as data for Amerindians and West African Blacks in Kidd
(2014), taking into account Venezuela’s racial composition
Vietnam Estimate based on Laos
Yemen Estimate based on converging data for Palestinians and Yemenite Jews in Kidd (2014)
Zambia Estimate based on data for southern African Bantu populations in Kidd (2014)
Zimbabwe Estimate based on data for southern African Bantu populations in Kidd (2014)
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Table 3 Estimates of national prevalence of the rs324420 A allele and average percentage of respondents
‘very happy’’, world value survey waves 2000–2004, 2005–2009, 2010–2014
Prevalence of
rs324420 A
allele (%)
Average percentage ‘‘very
happy’’ 2000–2004,
2005–2009, 2010–2014,
with predictions from 2
waves
Average percentage ‘‘very
happy’’ 2000–2004,
2005–2009, 2010–2014,
with predictions from
2?1 waves
Albania NA NA 10.6
Algeria 12.0 17.5 17.5
Andorra 20.0 NA 27.9
Argentina 23.0 (estimate) 32.8 32.8
Armenia NA NA 30.5
Australia 23.0 (estimate) 34.6 34.6
Austria 20.0 (estimate) NA NA
Azerbaijan NA NA 37.0
Belarus 26.0 (estimate) NA 12.8
Botswana 20.0 NA NA
Brazil 25.3 (calculated) 33.8 33.8
Bulgaria 16.0 (estimate) NA 11.1
Burkina Faso 42.5 NA 24.0
Canada 23.0 (estimate) NA 45.0
Cambodia 09.0 NA NA
Chile 23.0 (estimate) 31.0 31.0
China 13.0 16.1 16.1
Colombia 35.0 (calculated) 50.7 50.7
Cyprus 18.2 (estimate) 32.3 32.3
Denmark 26.3 NA NA
Ecuador 35.0 (calculated) NA 53.2
Egypt 11.0 (estimate) 11.1 11.1
El Salvador 32.0 (estimate) NA NA
Estonia 32.0 NA 12.7
France 21.0 NA 35.4
Germany 20.0 22.2 22.2
Ghana 42.5 48.6 48.6
Greece 18.2 NA NA
Hong Kong 13.0 15.8 15.8
Hungary 14.0 NA NA
India 20.0 (calculated) 30.8 30.8
Indonesia 17.0 (estimate) 23.2 23.2
Iran NA NA 20.0
Iraq 11.0 (estimate) 10.0 10.0
Ireland 23.0 NA NA
Israel NA NA 28.8
Italy 12 (estimate) NA 18.5
Japan 20.0 (estimate) 29.8 29.8
Jordan 11.0 (estimate) 20.9 20.9
Kazakhstan NA NA 30.5
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Table 3 continued
Prevalence of
rs324420 A
allele (%)
Average percentage ‘‘very
happy’’ 2000–2004,
2005–2009, 2010–2014,
with predictions from 2
waves
Average percentage ‘‘very
happy’’ 2000–2004,
2005–2009, 2010–2014,
with predictions from
2?1 waves
Korea 16.7 13.2 13.2
Kuwait NA NA 39.2
Kyrgyzstan NA NA 29.2
Lebanon NA NA 19.1
Laos 28.0 NA NA
Libya NA NA 36.6
Malaysia 16.0 (calculated) 45.2 45.2
Mali NA NA 38.2
Mexico 46.0 (estimate) 60.8 60.8
Moldova NA 7.6 7.6
Mongolia 10.0 NA NA
Morocco 11.0 22.6 22.6
Netherlands NA 35.7 35.7
New Zealand 23.0 (estimate) 35.0 35.0
Nigeria 42.5 59.8 59.8
Norway 26.3 (estimate) NA NA
Pakistan 24.0 (calculated) 34.2 34.2
Palestine 11.0 NA 12.5
Peru 37.0 (calculated) 34.1 34.1
Philippines NA 44.4 44.4
Poland NA 22.0 22.0
Puerto Rico NA NA 55.4
Republic of Macedonia NA NA 20.0
Romania 16.0 (estimate) 11.3 11.3
Russia 26.0 13.4 13.4
Rwanda 18.0 26.4 26.4
Saudi Arabia NA NA 45.3
Serbia NA 10.7 10.7
Singapore 13.0 (calculated) 34.5 34.5
Slovenia NA NA 19.0
South Africa 20.0 (calculated) 41.8 41.8
Spain 20.0 16.4 16.4
Sri Lanka 12.0 NA NA
Sweden 26.3 (estimate) 39.9 39.9
Switzerland 20.0 (estimate) NA 40.0
Syria 11.0 (estimate) NA NA
Taiwan 13.0 24.4 24.4
Tanzania NA NA 57.3
Thailand 9.0 (estimate) 38.8 38.8
Trinidad NA NA 50.4
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Latest data concerning the national prevalence of 5-HTTLPR polymorphisms in the
serotonin gene, plus additional estimates, are available from Table 1in Minkov et al.
(2015). We adopted their expanded index, based on their estimate that the prevalence of
the S allele is about 44 % in the Arab countries and about 70 % in Indonesia and the
Philippines.
Our main source for rs324420 allele frequencies was Kidd (2014). This is an allele
frequency database maintained by Yale University population geneticist Kenneth Kidd,
and supported by the US National Science Foundation. The rs324420 table is available at
http://alfred.med.yale.edu/alfred/SiteTable1A_working.asp?siteuid=SI379351C. We expan-
ded Kidd’s data with data from peer-reviewed journals. Table 1provides details.
As Kidd’s (2014) data are for ethnic groups, not nations, we had to make estimates for
multi-racial nations, such as those of the Americas. Estimates of the ethnic or racial
composition of these countries are provided by the Central Intelligence Agency (2012). We
made estimates of the prevalence of the A allele in each main ethnicity in the Americas
based on data for Amerindians, West Africans, and US Afro-Americans from Kidd (2014).
Our estimates of the prevalence of the A allele in Whites in Latin Americas was the
prevalence of that allele in Spaniards (De Luis et al. 2013). Although Latin America has
descendants of other European groups as well, the Spanish estimate is plausible, as it seems
to be a European average.
Thus, our estimates of the prevalence of the A allele in the main ethnic and racial groups
in the American nations are as follows: Amerindians—47 %, Whites—20 %, Blacks
outside the US—42.5 % (the same as in Nigerians). We made the assumption that those
categorized as ‘mestizos’’ on average have a 50 % Amerindian heritage versus 50 %
European, whereas ‘mulattos’’ have a 50 % West African heritage versus 50 % European.
Details are provided in Table 2.
We expanded our genetic database further, assuming that some neighboring nations,
such as Germany, Austria, and Switzerland, or the Scandinavian nations, are so similar
genetically as to be nearly indistinguishable. Minkov et al. (2015) provide evidence that
this assumption is plausible.
Table 3shows national prevalence of the rs324420 A allele as well as two average
national happiness indices for 2000–2014, one with predicted scores from two WVS waves
Table 3 continued
Prevalence of
rs324420 A
allele (%)
Average percentage ‘‘very
happy’’ 2000–2004,
2005–2009, 2010–2014,
with predictions from 2
waves
Average percentage ‘‘very
happy’’ 2000–2004,
2005–2009, 2010–2014,
with predictions from
2?1 waves
Tunisia 11.0 (estimate) NA 18.0
Uganda 18.0 NA 27.2
Ukraine 26.0 (estimate) 14.4 14.4
United Kingdom 23.0 (estimate) NA 48.7
Venezuela 35.0 (calculated) NA 57.9
Vietnam 28.0 (estimate) 37.4 37.4
Yemen 11.0 (estimate) NA 19.1
Zambia 18.0 NA 19.7
Zimbabwe 18.0 31.0 31.0
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Table 4 Zero-order correlations between national happiness 2000–2014 and its potential predictors
National prevalence
of the S allele in
5-HTTLPR
National
prevalence of the
A allele in FAAH
GDP per
person in
2005
GDP per
person growth
2012/1998
KK rule of
law index
2005
Harshness of
summers plus
harshness of
winters
Pathogen
prevalence
National happiness index 2000–2014
(with predicted scores from two waves
at a time)
-.18 (n=39) .73* (n=38) .08 (n=45) -.18 (n=43) .04 (n=45) -.51* (n=47) .20 (n=45)
National happiness index 2000–2014
(with predicted scores from two plus
one waves at a time)
-.12 (n=61) .63* (n=56) .18 (n=82) .04 (n=75) .09 (n=83) -.33* (n=85) .08 (n=83)
* Correlation significant at the .001 level
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at a time, and one with predicted scores from two plus one WVS waves. Of note, national
prevalence of the A allele is not significantly correlated with any of the other independent
variables in our study. Therefore, its predictive properties are independent of those of the
other predictors.
Data on the harshness of summers and harshness of winters are provided by van de
Vliert (2009).
Our historical pathogen prevalence data are from Murray and Schaller (2010).
Our national wealth data (GDP per person) are from the World Bank (2014). We used
GDP per person in 2005, which is approximately the middle of the period for which we
made estimates of average national wealth. To obtain a measure of speed of economic
growth, starting shortly before the period of our initial happiness data and ending shortly
before the period of the latest happiness data, we calculated GDP-per-person change from
1998 to 2012 by dividing GDP per person in 2012 by GDP per person in 1998.
The KK rule of law index for 2005 is from the International Bank for Reconstruction
and Development/The World Bank (2007).
3 Results
To validate our national happiness index for 2000–2014, we obtained zero-order corre-
lations between its two versions and component 1 (national scores on positive affect) in
Kuppens et al. (2006). The two versions of our happiness index (with predicted scores from
two WVS waves at a time, and with predicted scores from two plus one waves at a time)
correlate with component 1 at .55 (n=29, p=.002) and .65 (n=39, p\.001). Obvi-
ously, our index and component one measure something quite similar, although they are
derived from very different cross-cultural studies. The second correlation is not far lower
than the correlation between percentage ‘‘very happy’’ in 2010–2014 and percentage ‘‘very
happy’’ in 2000–2005 in the WVS.
Despite confirming this validation, we tested the hypothesis that the happiness measures
in some of the WVS waves are not significantly associated with the variable of main
Table 5 Final results of the
regression analyses with national
happiness 2000–2014 (with pre-
dictions from two waves) as the
dependent variable
RR
2
SE Fchange Sig. Fchange N(countries)
Model summary
.788 .622 8.56 28.76 \.0001 38
Independent
variables
Std
beta
TSig. Correlations VIF
Zero-
order
Partial
Model
National
prevalence of
the A allele in
FAAH
.630 5.99 \.0001 .69 .71 1.02
Harshness of
summers plus
harshness of
winters
-.390 -3.70 .001 -.48 -.53 1.02
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interest in this study, national prevalence of the rs324420 A allele. It is possible that even if
our average 2000–2014 happiness index is highly correlated with prevalence of the A
allele, this is so because of a high significant correlation in only one or two of the three
WVS waves, masking the fact that the happiness measures in one or two other waves yield
insignificant or very low correlations with the genetic index. This would be a blow to the
theory of genetic determinism of national happiness, since national genetic patterns evolve
very slowly. They should produce similar effects across three happiness surveys within a
decade or decade and a half.
We found that percentage of very happy people, as measured by each of the three latest
WVS waves (2000–2004, 2005–2009, 2010–2014) is highly and significantly correlated
with rs324420 A allele prevalence at .63 (n=43), .54 (n=41), and .84 (n=26). All
these correlations are significant at the .001 level.
We applied this test to the WVS life satisfaction item (mean national values) as well.
We found striking inconsistencies across the three waves. While the 2010–2014 measure
correlates with rs324420 A allele prevalence at .47 (p=.002, n=42), the 2005–2009
measure yields a weak and insignificant correlation of .30 (p=.057, n=40). More
disturbingly, the 2010–2014 life satisfaction measure yields a weak and insignificant
correlation with GDP per person in 2012: r=.26 (p=.073, n=49), even though the
2004–2009 life satisfaction measure correlates with GDP per person in 2005 at .53
(p\.001, n=46). Barring serious measurement errors, this volatility suggests powerful
situational influences on national averages in life satisfaction.
Table 4provides zero-order correlations between the two versions of the national
happiness index 2000–2014 (with predicted scores from two WVS waves at a time, and
with predicted scores from two plus one waves at a time) and the independent variables.
Table 4suggests that the only plausible predictors of the national happiness index
2000–2014 are the prevalence of the A allele in FAA and climate. Our linear regression
models confirmed that the other independent variables are not significant predictors of
national happiness, yielding results far from statistical significance. Therefore, in Tables 5
and 6we provide models with the only two significant predictors of our two happiness
indices.
Table 6 Final results of the
regression analyses with national
happiness 2000–2014 (with pre-
dictions from two ?one waves)
as the dependent variable
RR
2
SE Fchange Sig. Fchange N(countries)
Model summary
.677 .46 10.12 22.39 \.0001 56
Independent
variables
Std
beta
TSig. Correlations VIF
Zero-
order
Partial
Model
National
prevalence of
the A allele in
FAAH
.569 5.61 \.0001 .60 .61 1.01
Harshness of
summers plus
harshness of
winters
-.318 -3.13 .003 -.37 -.32 1.01
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Since national prevalence of the A allele in the FAAH gene is the best predictor of
national differences in happiness, we illustrate this relationship in Fig. 1.
We also ran a series of regression analyses with Kuppens et al.’s (2006) component 1 as
the dependent variable. Regardless of the number or combination of independent variables
in the regression models, the outcome was the same as in the case of the happiness indices
from the WVS, except that this time the climatic variable did not reach statistical sig-
nificance. Across 30–33 countries, only national prevalence of the A allele in FAAH was a
significant predictor, explaining about 33 % of variance in the dependent variable.
We were advised to test the predictive properties of the same independent variables with
respect to single happiness measures (percentage ‘‘very happy’’) from the three latest
waves of the WVS, rather than the composite happiness indices that we obtained by
averaging data from the three latest waves. When the dependent variable was happiness in
2010–2014, the regression model included 36 nations. Prevalence of the A allele in FAAH
Fig. 1 Visual illustration of the relationship between prevalence of the A allele in the FAAH gene and
national happiness
M. Minkov, M. H. Bond
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was the best significant predictor (b=.551, t=5.18, rpartial =.684, p\.0001), fol-
lowed by climatic harshness (b=-.556, t=-4.514, rpartial =-.636, p\.0001). The
other independent variables were not significant predictors. We obtained very similar
results for happiness in the 2005–2009 wave (35 countries), except that this time we also
had a third-ranking significant predictor, rule of law. When the dependent variable was
happiness in 2000–2004 (25 countries) only A allele in FAAH was a significant predictor.
We also tried replacing van de Vliert’s (2009) composite ‘‘harshness of summers plus
harshness of winters’’ variables with his ‘‘harshness of winters’’ and ‘‘harshness of sum-
mers’’, entered as separate independent variables together with A allele prevalence.
‘Harshness of summers’’ was not a significant predictor of happiness. ‘‘Harshness of
winters’’ reached statistical significance (p=.025) but its predictive property was some-
what lower (b=-.314) than that of ‘‘harshness of winters plus harshness of summers’’.
When other independent variables were entered in the model, these results did not change
appreciably.
We tested the hypothesis that our results are affected by our incorrect estimates of the A
allele in FAAH in some countries, whose A allele data in our study are actually based on
neighboring countries or other countries with a similar ethnic composition. After dropping
all such estimates, the number of countries in our model for the 2000–2014 composite
happiness index (with predictions from 2 ?1 waves) fell to 26. The results were essen-
tially the same as before: The best predictor was always A allele prevalence, followed by
the climatic variable. We also built separate models for happiness in 2010–2014,
2005–2009, and 2000–2004. The number of countries fell to 24, 17, and 14, respectively.
Despite the small number of countries and the somewhat different composition of the three
country samples in those three models, our previous results remained unchanged: A allele
prevalence was always the best predictor, followed by ‘‘harshness of winters plus harshness
of summers’’. There were no other significant predictors.
We also compared the percentages of ‘‘very happy’’ respondents in two ethnically
diverse countries—Malaysia and Singapore—whose different ethnicities have co-existed
for a long time. This situation controls for a potential recent-arrival effect that can enhance
or suppress the average happiness of a group of immigrants. The results are presented in
Table 7.
The results demonstrate clear differences between countries and ethnicities. The
observed ethnic differences and rankings are stable, with a single exception: Indians score
slightly higher (instead of slightly lower) than Malays in Singapore 2000–2004.
Table 7 Percentage ‘‘very
happy’’ by main ethnicity in
Malaysia and Singapore
Malaysia 2010–2014 Malay 59.7
Indian 57.0
Chinese 47.6
Singapore 2010–2014 Malay 49.9
Indian 47.5
Chinese 35.6
Malaysia 2005–2009 Malay 43.3
Indian 33.9
Chinese 32.8
Singapore 2000–2004 Indian 44.0
Malay 42.1
Chinese 25.2
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Unfortunately, we do not have genetic data for the Indians who live in Malaysia and
Singapore and can only speculate that the observed stability in these rankings of ethnic
groups has a genetic component.
1
Although our study focuses on happiness as a form of positive affect, and not on life
satisfaction, we were advised to test the predictive properties of our independent variables
with respect to average life satisfaction as measured by the World Values Survey. When all
independent variables were entered simultaneously, in a model with 35 countries, the
2010–2014 measure of life satisfaction was predicted only by prevalence of the A allele in
FAAH (b=.441, t=2.63, partial r=.445, p=.014). However, the 2005–2009 measure
of life satisfaction was predicted only by ‘‘harshness of winters plus harshness of sum-
mers’’ (b=-.540, t=-2.371, partial r=-.415, p=.025). Thus, the predictors of life
satisfaction depend on the period of study and country sample.
4 Discussion
This is the first study showing that national differences in happiness, defined as the hedonic
component of SWB or positive affect, have a genetic component. Somewhat surprisingly,
these differences are not associated with the polymorphisms of the serotonin gene, but only
with those in the FAAH gene. Nations with the highest prevalence of the A allele in
rs324420 of the FAAH gene have the highest percentages of very happy people, and this
association is quite strong. Vice versa, nations with the lowest prevalence of that allele
have the lowest percentages of very happy people. The former group of nations consists
mostly of northern Latin American countries, with relatively high percentages of
Amerindians or people of mixed Euro-American descent, as well as West African coun-
tries. The data in Kidd (2014) are unequivocal: Amerindians have the highest prevalence of
the rs324420 A allele in the FAAH gene. The main tribes of Nigeria—Hausa and Yor-
uba—are next in the ranking.
The lowest prevalence of the A allele is found in some Arab and East Asian nations,
most of which have low happiness scores. Differences in happiness between Northern and
Central or South Europeans also seem attributable to the genetic differences between them,
since Northern Europeans have a much higher prevalence of the A allele.
However, Northeast Europeans (Russians and Estonians) are not among the nations that
have a very low prevalence of the A allele. Their very low happiness scores are obviously
not due to a deficiency of anandamide alone. They may be a lasting effect of the economic
and political difficulties that the East European nations continue to experience in their
transition to capitalism and democracy, in accordance with the findings of Veenhoven
(2001) and Inglehart et al. (2008). Alternatively, it is possible that other, hitherto unknown,
genes explain the low happiness scores of East Europeans.
1
We were advised that genetically heterogeneous countries, such as Malaysia and Singapore, can be
expected to have greater internal dispersion of happiness scores than genetically homogeneous countries,
such as Japan. However, heterogeneity versus homogeneity should not be measured simply as presence or
absence of diverse ethnic groups, but also in terms of the structure of the population. It is possible that a
country like Singapore, where over 80 % are ethnic Chinese, the remaining less than 20 % Indians and
Malays create a relatively low dispersion. Vice versa, in a country with large socioeconomic inequality, such
as the US, South Africa, and Brazil, there may be a relatively large dispersion even among the same ethnic
group. We cannot expect that the FAAH genes will explain all the variance in positive affect at the
individual level. Factors such as socioeconomic status may play an equally important role.
M. Minkov, M. H. Bond
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We must also acknowledge that a few nations in the WVS evidence large fluctuations in
their percentages of very happy people that obviously have nothing to with their genetic
heritage. Some of these fluctuations are fully explicable by the changing socioeconomic
conditions in those countries. The percentage of very happy people in Rwanda has risen
dramatically recently, apparently because the effect of the 1994 genocide is beginning to
wear off. Inversely, the percentage of very happy people in Egypt has fallen recently, most
likely as a result of the political turmoil and economic difficulties that Egyptians have
experienced in recent years. Although our analysis cannot capture these changes, it seems
plausible to accept that they can affect not only a nation’s cognitive appraisal of its well-
being, but also the positive affect that most citizens experience.
Our analysis suggests that differences in economic growth do not explain differences in
happiness. This finding must not be misinterpreted. It does not necessarily prove that
happiness and economic growth have nothing in common. First, strictly speaking, we have
not studied the effect of economic growth on happiness but the effect of differences in
economic growth on differences in happiness. These are two different types of study.
Second, the effect of national economic growth in the past decade may not have been
evenly distributed, especially across the members of rich nations. Instead, the benefits of
that growth may have accrued mostly to those who were already rich. This phenomenon
may have suppressed the potential effect of growing national wealth on national happiness.
It was not the aim of this study to examine the predictors of national differences in life
satisfaction in detail. Yet, our brief analysis of that variable suggests somewhat greater
volatility than in the case of happiness. The results depend on the period of study and the
country sample. We can tentatively conclude that, since happiness and life satisfaction are
not completely independent, the genetic factor is probably involved in both, although its
effect on the latter is not as strong as on the former. It appears that situational factors at the
national level can more strongly suppress the effect of genetic factor on differences in life
satisfaction.
The results of our study may sound somewhat disturbing for nations that are not
endowed with beneficial genes and climatic factors. However, we must reiterate that we
have studied only national differences, not absolute measures. In other words, we have not
shown that a nation’s genetic and climatic heritage doom a particular country to a specific
happiness score. Despite that heritage, a nation’s happiness score can rise or fall as a
function of various situational factors. What our study shows is that despite these situa-
tional factors, differences in happiness between nations remain relatively stable.
We have also found that national differences in genetic heritage do not provide a good
explanation of national differences in life satisfaction. The genetic effect of genes and
climate on the way that most people in a particular nation evaluate their lives may be
considerably smaller than the genetic effect on hedonic balance.
There are limitations to our study. First, we worked with a number of estimated scores.
However, our findings hold even if we drop estimates based on neighboring countries or
countries with a similar ethnic composition. Also, although it is possible that some of our
estimates are far from perfect, it is highly unlikely that all of them are skewed in the same
wrong direction. Our findings would be seriously challenged if future genetic studies
discovered that, for instance, in terms of the prevalence of the A allele of the FAAH gene,
the Hong Kong Chinese are genetically closer to Amerindians than to the Han of the
People’s Republic, or that the Amerindians of Columbia are more similar to Arabs than to
Mexican and Brazilian Amerindians. Yet, this is highly unlikely. In fact, Minkov et al.
(2015) worked with a variety of different estimates concerning the prevalence of the S
allele in 5-HTTLPR and showed that the final results are little affected.
A Genetic Component to National Differences in Happiness
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We must also acknowledge that it seems somewhat surprising that the prevalence of a
single genetic allele can have such an enormous effect on national differences in happiness.
But we must point out that Dincheva et al. (2015) reported unusually high effects of the
rs324420 polymorphism at the individual level, whereas aggregation to a higher level of
analysis, such as nations, in principle results in higher effects than those observed at the
individual level. Although many genes that have so far been tested for relationships with
personality and cognition tend to yield minuscule effects at the individual level, the FAAH
gene may be an exception.
Further, the geographic distribution of the rs324420 polymorphism is fairly clear. It
replicates some well-known genetic contrasts, especially those between Asian and
Amerindian populations. It is quite possible that the FAAH gene is not the only one
involved in the national happiness equation. Other, at present unknown, genes may pro-
duce similar effects and their polymorphisms may have a similar geographic distribution.
In that sense, the FAAH gene may be a marker for a large package of genes that affect
national differences in happiness.
The geographic distribution of the rs324420 polymorphism warrants a study in its own
right. What environmental factors have resulted in population differences in the occurrence
of the A allele in FAAH? The main problem in attempting an answer to that question is that
we do not know the time when the rs324420 polymorphism appeared. When geneticists
reach consensus on that point, researchers should examine the climatic and other envi-
ronmental conditions across the globe at that time and attempt to correlate those data with
prevalence of the A allele at the ethnic, rather than national level.
Yet, we cannot fail to notice the high occurrence of the A allele in equatorial and
tropical environments in the Americas and Africa and the lower occurrence of that allele
around the Mediterranean Sea than in Northern Europe. It seems that some equatorial and
tropical environments select for a higher occurrence of the A allele as a counterbalance to
environmental stressors. A similar process may have occurred across Northern Europe.
Although current estimates of pathogen prevalence and climatic differences do not cor-
relate significantly with A allele occurrence at the national level, a different picture could
emerge if environmental factors in the past, at the time of the appearance of the rs324420
polymorphism, were compared with ethnic data from the same period.
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... Higher values in this variable indicate greater individualism. However, Hofstede's measure is now several decades old which makes it potentially outdated (Minkov et al., 2017;Minkov and Kaasa, 2020;Beugelsdijk & Welzel, 2018). For this reason, we also collected an alternative index of individualism-collectivism which was published more recently (Minkov et al., 2017), and covered 55 nations in our sample, to replicate our key analyses. ...
... However, Hofstede's measure is now several decades old which makes it potentially outdated (Minkov et al., 2017;Minkov and Kaasa, 2020;Beugelsdijk & Welzel, 2018). For this reason, we also collected an alternative index of individualism-collectivism which was published more recently (Minkov et al., 2017), and covered 55 nations in our sample, to replicate our key analyses. ...
... However, we have uploaded all data and code with the hope that more targeted future studies can examine interactions between our fixed effects to explain patterns of cross-cultural variation in depression. Other studies may also seek to add further main effects, such as other dimensions of cultural variance (e.g., Schwartz, 2012) and other potential sources of genetic variance across populations that could be linked to depression (see Minkov & Bond, 2017). ...
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The prevalence of depression varies widely across nations, but we do not yet understand what underlies this variation. Here we use estimates from the Global Burden of Disease study to analyze the correlates of depression across 195 countries and territories. We begin by identifying potential cross-correlates of depression using past clinical and cultural psychology literature. We then take a data-driven approach to modeling which factors correlate with depression in zero-order analyses, and in a multiple regression model that controls for covariation between factors. Our findings reveal several potential correlates of depression, including cultural individualism, daylight hours, divorce rate, and GDP per capita. Cultural individualism is the only factor that remains significant across all our models, even when adjusting for spatial autocorrelation, mental healthcare workers per capita, multicollinearity, and outliers. These findings shed light on how depression varies around the world, the sociocultural and environmental factors that underlie this variation, and potential future directions for the study of culture and mental illness.
... According to Minkov and Bond (2017), the main predictors of national differences in happiness (i.e. subjective well-being, SWB) are closely connected to "national economic development, democratization, and increasing social tolerance" among different ethnic groups of a nation. ...
... subjective well-being, SWB) are closely connected to "national economic development, democratization, and increasing social tolerance" among different ethnic groups of a nation. Hence, taking the current socio-political challenges faced by the CIM into consideration, it is understandable that in comparison to the other ethnic groups in Malaysia, CIM have been found to have the lowest level of happiness and SWB (Minkov & Bond, 2017). ...
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This chapter presents the experiences of Chinese in Malaysia (CIM), in the context of mental health services. As the second largest ethnic group in Malaysia, CIM is diverse in its dialectic subculture, education, generation, geography, and degree of assimilation to the mainstream culture. The chapter introduces the ecological characteristics of CIM and how they shape the unique psychological challenges. Though CIM are known for their multilingual ability, strong work ethics, emphasis on education, and family piety, the clashes between tradition and modern values, the marginalized position in the Malaysian political arena, the stereotype of overachiever in education, and the “brain drain” movement of young elite CIM, have all caused a strain in CIM families as well as individuals. Moreover, they face both external and internal barriers in getting quality mental health care. It is therefore imperative to promote a mental health discipline that is open to serve CIM, as well as being sensitive to its cultural and historical backdrop.
... (2) If γ 2 < 0, happiness inequality has an inverted U-shaped relation with economic growth (a concave curve); in this condition, if γ 1 > 0, the relationship is consistent with the subjective wellbeing Kuznets curve hypothesis and the turning point can be calculated as −γ 1 2γ 2 (in this case, −γ 1 2γ 2 > 0). 38 . The surveyed individuals are asked to rate their happiness on a 5-point Likert scale ranging from 1 (very unhappy) to 5 (very happy). ...
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Happiness studies generally investigate average levels of happiness rather than happiness inequality between regions, and studies of social inequality usually measure it based on the distribution of life opportunities (e.g., income) rather than life results (e.g., happiness). Inspired by the Kuznets curve, which illustrates the inverted U-shaped correlation between income inequality and economic growth, this study investigates whether there is a subjective wellbeing Kuznets curve. It uses data from ten waves of the Chinese General Social Survey to construct a panel data set and runs panel data models to investigate the hypothesized curvilinear relationship between happiness inequality and economic growth. The results show that happiness inequality, measured as the standard deviations of respondents’ self-reported happiness, first increases and then decreases as per-capita GDP increases in Chinese provinces. These findings strongly support the subjective wellbeing Kuznets curve hypothesis and suggest that strategies for reducing happiness inequality must consider stages of economic development.
... If we look at the 'genetic' strand of this literature, several studies focus on which could be the candidate gene(s) able to affect happiness. Minkov and Bond (2017) clearly explain that the causal link between genetics and happiness is due to the role played by serotonin -a chemical in the human brain that maintains mood balance and particularly affects the probability of depression and suicide. Many studies analyse the role of the serotonin transporter promoter polymorphism (5-HTTLPR) (e.g., De Neve et al., 2012;Benjamin et al., 2012;De Neve, 2011). ...
... The origins of happiness are very complicated [28]. For a long time, the similarity in happiness levels among family members over generations seems to indicate that genetic factors may play an important role in happiness [29,30]. Some common genes or genetic variants associated with happiness have indeed been found [31][32][33]. ...
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Happiness is the foundation of a better life and a goal that people pursue; however, happiness levels among university students are low. The purpose of this study is to explore the main factors influencing student happiness. A nationwide cross-sectional study was conducted in China in 2020. Data on student happiness was collected using the Oxford Happiness Questionnaire, and students’ personal, familial, and social information were obtained using another questionnaire. Logistic regression analysis was employed to examine the association between student happiness and these factors in terms of odds ratio (OR) and 95% confidence interval (CI). A total of 2186 valid questionnaires were obtained. Firstly, student happiness was found to be associated with personal factors. The results found that happiness was significantly associated with state of health, the adjusted OR (95% CI) = 3.41 (2.01–5.79) for healthy students compared to unhealthy students, and that happiness decreased with the student’s age (OR = 0.79 and 95% CI = 0.63–0.98). Secondly, the research suggested that happiness was associated with familial factors. Both frequent contact with family and a harmonious relationship with parents significantly enhanced happiness with ORs (95% CIs) 1.42 (1.17–1.71) and 2.32 (1.83–2.95), respectively. Thirdly, student happiness was associated with several social factors. Students who performed well academically, who went to sleep early, and who were in a loving relationship were found to be happier than those with poor academic performance, went to sleep late, and who were single, for which the ORs (95% CIs) were, respectively, 1.87 (1.51–2.32), 1.50 (1.24–1.81), and 1.32 (1.09–1.60). The survey identified several key personal, familial, and social factors influencing university student happiness, which can provide an effective measure to improve their happiness.
... Multiple previous findings of twin studies such as Lykken and Tellegen (1996) and Weiss, Bates and Luciano (2008) suggest that most of the variation among individuals in the stable component of happiness over a lifetime can be attributed to genetics, at least in the Western societies where the studies have been performed. This stable component can be approximated by repeated measurements many years or decades apart (Bartels, 2015;Inglehart & Klingemann, 2000;Minkov & Bond, 2017;Nes, 2010;Nes & Røysamb, 2017). Arguably, environmental factors are more important than genes as determinants of contentment with social life in developing countries, although genetics is often found to be the more important influence on happiness in developed countries. ...
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Previous studies have found that average cognitive ability at the national level, which has been called national intelligence and scaled as IQ, is an important determinant of economic growth at the cross-national level. The current study re-investigates the claim that being a happier society weakens the positive association between IQ and economic growth. It investigates whether there is a threshold effect of happiness on the relationship between national IQ and economic growth between 1960 and 2017. Controlling for endogeneity with instrumental variables (IVs), the results confirmed that the relationship between IQ and economic growth is weaker in countries with high levels of self-reported happiness. The diminishing returns of IQ for economic growth can be recognized above a threshold level of 6.25 on the zero-to-10 happiness scale. The suggested explanation is that higher levels of happiness tend to reduce the aspiration for higher productivity among the people, which reduces the impact of cognitive human capital on economic growth.
... Taking the current sociopolitical challenges faced by the Chinese into e.Proofing | Springer https://eproofing.springer.com/books_v3/printpage.php?token=NX81A... consideration, it is understandable that, in comparison to the other ethnic groups in Malaysia, the Chinese have been found to have the lowest level of happiness and subjective well-being (Minkov and Bond 2017). Continuing emigration and a low birth rate are resulting in a decline of the Chinese population in the country. ...
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This chapter presents the experiences of Chinese in Malaysia, in the context of mental health services. As the second largest ethnic group in Malaysia, the Chinese population is diverse in its subculture, education, generation, geography, and degree of assimilation to the mainstream culture. The chapter introduces the ecological characteristics in Malaysia and how they shape the unique mental health challenges of the Chinese. Though the Chinese are known for their multilingual ability, strong work ethic, emphasis on education, and family piety, clashes between traditional and modern values, their marginalized position in the Malaysian political arena, the stereotype of the economically successful minority, and the “brain drain” of young well-educated Chinese have all caused a strain in Chinese individuals and families across the lifespan. Moreover, they face both external and internal barriers in getting quality mental health care. It is therefore imperative to promote a mental health service model that is able to meet Chinese psychological needs, as well as being sensitive to the culture and history of the Chinese communities.
Chapter
This chapter briefly summarizes recent research in genetics and the neurosciences that hold out hope for a better understanding of human happiness. Among other issues, it outlines the ongoing controversy between geneticists and psychologists as to whether people have an inherited set point of happiness that is relatively fixed, or whether psychological interventions can lead to meaningful long-term improvements. An introduction is provided to some of the concepts underlying the measurement of health-related quality of life.
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This study explores the factors that affect visits between national leaders in the world, shedding light on their ancestral origins. We combine data on visits involving Chinese leaders from 1993 to 2013 with genetic distance that captures ethnic differences transmitted intergenerationally. Empirical analysis shows that there are more visits between Chinese leaders and leaders of countries that have smaller genetic distance to China. Furthermore, the impact of genetic distance is achieved primarily through trade and positioning of political relationships, which are proxies for economic and political exchanges, respectively. Our findings show that ancestral relatedness plays an important part in modern diplomatic activities.
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Concerns have been raised as to the potentially deleterious effects of advertising on society. We examine this issue given the recent calls to explore the societal effects of international business activities, the substantive nature of advertising spending globally, and the movement by governments to hold businesses accountable for societal harms. We build upon the general theory of competitive rationality, suggesting a positive relationship between advertising spending and happiness at the country level. We integrate an institutional economics framework into the general theory of competitive rationality to understand country effects. We explore whether institutional environments (i.e., political, regulatory, and social) are associated with happiness and/or moderate the relationship between advertising spending and happiness. We empirically examine these relationships using a 34-country, 9-year unbalanced panel dataset. Our findings indicate that advertising spending at the country level is positively associated with happiness, even when accounting for country-level institutional direct and moderating effects. We discuss our results in comparison to prior findings, highlighting implications for international marketing theory and practice, and setting forth a foundation for debate and research in the field.
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Cross-species studies enable rapid translational discovery and produce the broadest impact when both mechanism and phenotype are consistent across organisms. We developed a knock-in mouse that biologically recapitulates a common human mutation in the gene for fatty acid amide hydrolase (FAAH) (C385A; rs324420), the primary catabolic enzyme for the endocannabinoid anandamide. This common polymorphism impacts the expression and activity of FAAH, thereby increasing anandamide levels. Here, we show that the genetic knock-in mouse and human variant allele carriers exhibit parallel alterations in biochemisty, neurocircuitry and behaviour. Specifically, there is reduced FAAH expression associated with the variant allele that selectively enhances fronto-amygdala connectivity and fear extinction learning, and decreases anxiety-like behaviours. These results suggest a gain of function in fear regulation and may indicate for whom and for what anxiety symptoms FAAH inhibitors or exposure-based therapies will be most efficacious, bridging an important translational gap between the mouse and human.
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It is well known that intelligence consists of a variety of interactional and cognitive skills and abilities (e.g. tradecraft; critical and divergent thinking; perception of foreign information). Decision making is defined as the conscious choice between given options, relating to a problem. Both genetic background and environment comprise key elements for personality characteristics of the human being. The aim of this study is to determine the frequency distribution of rs324420, rs1800497, rs363050, rs6265, rs1328674 polymorphisms known to be involved in individual personality characteristics, in 830 Greek Subjects. The study is independent from direct clinical measurements (e.g. IQ measurements; physiological tests). The population of the volunteers is described, based on genotype, sex, with the respective gene frequencies, including the Minor Allele Frequency (MAF). A potential influence of the volunteer gender with the above characteristics (based on genotypes and alleles) is examined and finally, volunteers are classified as follows: A volunteer receives + 1, for each genotype/allele, which enhances his intelligence or his decision-making. In contrast, he receives − 1, for each genotype/allele, which relegates the individual characteristic. No statistically significant gender-characteristics correlation is observed. According to their genetic profile, a rate of 92.5%, of the volunteers may be characterized by prudence and temperance of thought, with only a small proportion of them (7.5%) may be classified as genetically spontaneous and adventurous. Regarding intelligence, the study population may lay around average and a little above it, at a rate of 96.3%, while the edges of the scale suggest only a 0.5% of the volunteers, who, although the “smartest”, somehow seem to lack prudence. In conclusion, individuals with low cognitive ability may be more prudent than others and vice versa, while the “smartest” ones tend to be more risky, in decision-making. Therefore, intelligence and decision-making may, after all, be less linked to each other than expected.
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This research provides novel insights into the evolutionary basis of cultural norm development and maintenance. We yield evidence for a unique culture–gene coevolutionary model between ecological threat, allelic frequency of the serotonin transporter polymorphism (5-HTTLPR), cultural tightness–looseness—the strength of norms and tolerance for deviance from norms—and moral justifiability. As hypothesized, the results across 21 nations show that: (a) propensity for ecological threat correlates with short (S) allele frequency in the 5-HTTLPR, (b) allelic frequency in the 5-HTTLPR and vulnerability to ecological threat both correlate with cultural tightness–looseness, (c) susceptibility to ecological threat predicts tightness–looseness via the mediation of S allele carriers, and (d) frequency of S allele carriers predicts justifiability of morally relevant behavior via tightness–looseness. This research highlights the importance of studying the interplay between environmental, genetic, and cultural factors underlying contemporary differences in social behavior and presents an empirical framework for future research. Electronic supplementary material The online version of this article (doi:10.1007/s40167-013-0009-x) contains supplementary material, which is available to authorized users.
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Everyone, everyday, everywhere has to cope with climatic cold or heat to satisfy survival needs, using money. This point of departure led to a decade of innovative research on the basis of the tenet that climate and affluence influence each other's impact on culture. Evert Van de Vliert discovered survival cultures in poor countries with demanding cold or hot climates, self-expression cultures in rich countries with demanding cold or hot climates, and easygoing cultures in poor and rich countries with temperate climates. These findings have implications for the cultural consequences of global warming and local poverty. Climate protection and poverty reduction are used in combination to sketch four scenarios for shaping cultures, from which the world community has to make a principal and principled choice soon. © Evert Van de Vliert 2009 and Cambridge University Press, 2009.
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We offer a critical overview of studies associating genetic differences in the 5-HTTLPR VNTR in the serotonin-transporter gene with societal differences. We also highlight recent findings from individual-level research on 5-HTTLPR generating new hypotheses concerning the effect of genes on culture. We provide an expanded national index reflecting 5-HTTLPR S-allele prevalence as an improved tool for future research. Our preliminary tests of this tool suggest that national S-allele prevalence is not associated with individualism as has been claimed, but with national neuroticism, IQ and school achievement, Hofstede’s fifth dimension of long-term orientation, and Minkov’s societal hypometropia—a measure of risk acceptance and short-term vision in life history strategy. We encourage detailed research of these associations in future studies.
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The existence of a genetic factor behind group-level differences in life history strategy (LHS) has long been disputed. A number of recent studies suggest that some polymorphisms in the androgen receptor gene AR, the dopamine receptor gene DRD4, and the 5-HTTLPR VNTR of the serotonin transporter gene are associated with risk acceptance versus prudence and a short-term versus long-term time orientation, which are important aspects of LHS. We integrated studies from diverse nations reporting the prevalence of these three polymorphisms for many countries. We collected national indices for each of the three polymorphisms and found that they define a strong, single factor, yielding a single LHS-related, national genetic index. As expected, this index is strongly associated with reported national measures of LHS and time orientation, even after controlling for socioeconomic variables. The genetic effect seems especially strong across societies with high socioeconomic inequality.
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This paper discusses correlations between certain genetic characterestics of the human populations and their aggregate levels of tolerance and happiness. We argue that a major cause of the systematic clustering of genetic characteristics may be climatic conditions linked with relatively high or low levels of parasite. This may lead certain populations to develop gene pools linked with different levels of avoidance of strangers, which helped shape different cultures, both of which eventually helped shape economic development. Still more recently, this combination of distinctive cultural and economic and perhaps genetic factors has led some societies to more readily adopt gender equality and high levels of social tolerance, than others. More tolerant societies tend to be happier because they create a more relaxed environment conducive to happiness.
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Culture-gene coevolutionary theory posits that cultural values have evolved, are adaptive and influence the social and physical environments under which genetic selection operates. Here, we examined the association between cultural values of individualism-collectivism and allelic frequency of the serotonin transporter functional polymorphism (5-HTTLPR) as well as the role this culture-gene association may play in explaining global variability in prevalence of pathogens and affective disorders. We found evidence that collectivistic cultures were significantly more likely to comprise individuals carrying the short (S) allele of the 5-HTTLPR across 29 nations. Results further show that historical pathogen prevalence predicts cultural variability in individualism-collectivism owing to genetic selection of the S allele. Additionally, cultural values and frequency of S allele carriers negatively predict global prevalence of anxiety and mood disorder. Finally, mediation analyses further indicate that increased frequency of S allele carriers predicted decreased anxiety and mood disorder prevalence owing to increased collectivistic cultural values. Taken together, our findings suggest culture-gene coevolution between allelic frequency of 5-HTTLPR and cultural values of individualism-collectivism and support the notion that cultural values buffer genetically susceptible populations from increased prevalence of affective disorders. Implications of the current findings for understanding culture-gene coevolution of human brain and behaviour as well as how this coevolutionary process may contribute to global variation in pathogen prevalence and epidemiology of affective disorders, such as anxiety and depression, are discussed.
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There is a growing body of population survey data on national subjective well-being which allows comparisons across countries and across periods. Key issues in this work are as follows. Can response to questions on well-being be meaningfully compared across countries and periods? What social conditions are associated with greater well-being both between countries and across periods? Are there lessons for how global well-being might be improved? This review aims to give an overview of this area and its relevance to psychiatric epidemiology. Systematic searches of the literature were carried out using eight academic databases between August 2012 and January 2013. Subjective well-being involves multiple components, including cognitive evaluation of satisfaction with life and emotional state, and these are separable from mental ill health. Although there are difficulties in measuring subjective well-being in comparable ways cross-culturally, there is sufficient evidence of validity to make comparisons meaningful. The subjective well-being of nations increases with income per capita, but gains are smaller in higher-income countries. Other national factors that affect well-being include income inequality, social welfare, individualism, democracy and freedom, social capital and physical health. Economic growth of lower-income nations will improve global subjective well-being. However, this needs to be sustainable or it will reduce the well-being of future generations. Higher-income nations need to focus on other determinants of well-being. Research on cross-national well-being suggests a number of directions that may be profitably pursued in psychiatric epidemiology.
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Corruption research largely rests on institutional and economic theories. Biological, psychological, and anthropological theories and research can provide unique insights on corporate corruption. Following the emerging perspective of gene–environment interaction in cross-cultural research, the current research presents an economic–genetic theory of corporate corruption across cultures. By examining 30 societies, I found a positive interactive effect of wealth and the 5HTTLPR-SS/SL frequency on corporate corruption mediated by cultural endorsement of self-protective leadership (CESPL). Additionally, the 5HTTLPR-SS/SL frequency moderated the positive effect of CESPL on corporate corruption and CESPL mediated the wealth effect on corporate corruption in societies with low 5HTTLPR-SS/SL frequencies. These findings shed novel light on research on corporate corruption and cross-cultural leadership.