Cross-national and historical differences in subjective well-being

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1 Published by Oxford University Press on behalf of the International Epidemiological Association ß The Author 2014; all rights reserved. Advance Access publication 28 February 2014 International Journal of Epidemiology 2014;43: doi: /ije/dyt188 Cross-national and historical differences in subjective well-being Anthony F Jorm* and Siobhan M Ryan Melbourne School of Population and Global Health, University of Melbourne, Carlton, Victoria, Australia *Corresponding author. Melbourne School of Population and Global Health, University of Melbourne, 207 Bouverie St, Carlton, Victoria 3010, Australia. ajorm@unimelb.edu.au Accepted 13 August 2013 Background 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. Methods Systematic searches of the literature were carried out using eight academic databases between August 2012 and January Results 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 higherincome countries. Other national factors that affect well-being include income inequality, social welfare, individualism, democracy and freedom, social capital and physical health. Conclusions 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. Keywords Subjective well-being, happiness, life satisfaction, mental health, national differences, historical change Introduction There is now a very large literature on what has been termed subjective well-being (SWB), some of which is labelled under the rubric of happiness research or positive psychology. Given the size and diversity of this field, it is not possible to provide a comprehensive systematic review in this paper. Rather the aim is to focus on a specific area, namely the determinants of national well-being from a global perspective. This is an area of research which is mainly pursued within psychology, economics and political science, rather than within psychiatric epidemiology. Nevertheless, the issues investigated are of broad relevance to psychiatric epidemiologists. One of the aims of this 330

2 SUBJECTIVE WELL-BEING 331 review is to make national well-being research better known to an epidemiological readership and to consider what lessons might be learned for psychiatric epidemiology. Thus, we are interested in ecological studies that investigate SWB with the nation as the unit of analysis. Some studies examine both SWB and its predictors using national aggregates as data, whereas others examine predictors of well-being at both individual and national levels, and consider whether national characteristics are predictors of SWB after adjustment for individual characteristics. For example, does the income of a nation predict SWB over and above the income of the individuals who make up the nation? Some predictors (e.g. democracy, political upheavals, inflation) can only exist at the national level, whereas others can exist at both levels (e.g. income, education). Some studies also investigate historical changes in SWB within nations, looking at whether changes in various national characteristics predict any changes in SWB. There are also differences in analytical approach between such studies. An important one is whether nation fixed effects are included in models. 1 These capture unchanging cultural and institutional influences within nations, so that the correlations are basically between the change in a nation s characteristic and change in the nation s SWB, making most cross-sectional patterns disappear and reducing spurious correlations. SWB is not a unidimensional construct. Factor analytical studies indicate that there is a cognitive component to SWB which involves an evaluation of satisfaction with life, and an affective component which involves positive affect and the absence of negative affect. 2 Whereas these components are correlated at both individual and national levels, they are partly independent and may have somewhat different determinants. Positive affect, negative affect and life satisfaction are constructs associated with what has been called the hedonic view of SWB. An alternative to this is the eudaimonic view, which focuses on the Table 1 Commonly used measures of subjective well-being Measure Single item, self-rated life satisfaction Single item, self-rated happiness Cantril s ladder Positive affect Negative affect extent to which a person s life is in accordance with deeply-held values and the person is fully engaged. 1 Measures derived from the hedonic and eudaimonic views are moderately correlated, indicating that the constructs are different but overlapping. SWB is clearly related to, but different from, the constructs of mental ill health investigated by psychiatric epidemiologists. People who experience mental disorders or are suicidal score lower on measures of SWB. 3 The strongest associations are with the negative affect component of SWB. Depression and anxiety show strong correlations with negative affect. Depression is also related to lower positive affect, but to a lesser degree. 4 These associations are to be expected, given that depressive disorders are defined as involving sad mood and loss of the ability to experience pleasure. It is also notable that depression screening questionnaires sometimes include items that are closely related to measures of SWB. For example, the Center for Epidemiologic Studies Depression (CES-D) scale includes the reversedscored item, I was happy. 5 Similarly, the General Health Questionnaire, which is a screening test for common mental disorders, contains a number of items that tap happiness, satisfaction and other aspects of positive well-being. 6 There are many measures of SWB and its components. However, most of the national data come from large social surveys which have included very brief measures. The main ones are summarized in Table 1. The most commonly used measures are single items measuring life satisfaction and happiness. Life satisfaction items measure the cognitive aspect of SWB and correlate more highly with positive affect than with absence of negative affect, whereas happiness measures correlate more specifically with positive affect. 7 Eudaimonic concepts of SWB have not featured much in the study of cross-national differences, although some work crosses both hedonic and eudaimonic concepts. 8 Despite their brevity, the reliability of the measures in Table 1 is surprisingly Example item content All things considered, how satisfied are you with your life these days? (Response made on 10-point scale) Taking all things together, how would you say things are these days would you say you re very happy, fairly happy, or not too happy these days? Please imagine a ladder with steps numbered from zero at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time? Respondents report whether they experienced specified feelings a lot on the previous day, including enjoyment, love, and smile or laugh a lot. Respondents report whether they experienced specified feelings a lot on the previous day, including worry, sadness, depression, and anger.

3 332 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY good at the individual level, e.g over 1 year for life satisfaction. 9 When aggregated at the national level, it is much higher. For example, mean life satisfaction of nations has been found to correlate 0.93 over 1 year in the same survey series, and 0.97 across different survey datasets. 3 The correlation across different SWB measures is also high, with life satisfaction and happiness levels correlating across nations. 10,11 These national summary measures of SWB also correlate to some degree with psychiatric indicators. Across nations, the percentage who are very happy was found to correlate 0.37 with the suicide rate, 12 whereas two indicators of national SWB correlated 0.46 and 0.66, respectively, with national means on the Beck Depression Inventory. 13 Similarly, a composite measure of national SWB correlated 0.60 with a composite measure of mental ill health. 14 In comparing the responses to such simple questions across nations, the issue inevitably arises of whether the measures can be validly compared across different language and cultural groups. Supporting crosscultural comparability, there is evidence that different measures of SWB tend to give comparable national rankings; for example, experience sampling of momentary mood, frequency of smiling and memory for good vs bad events have been compared with more commonly used questionnaire measures. 15 Furthermore, bilinguals give similar ratings in each language, and countries with multiple national languages give similar ratings for each language group. 16 Comparable factors of positive and negative affect have also been found across cultures. 7 On the other hand, there is evidence that people from individualist cultures assess SWB somewhat differently from people in collectivist cultures, with emotions more important in the former and social norms in the latter. 17 There is also some evidence for differential use of response scales across nations, which is revealed when anchoring vignettes are used to assess comparability of ratings. 18 Studies that examine change in SWB over time within a nation would seem less susceptible to these problems than crossnational studies, because changes in the interpretation of items are likely to be small over a few decades. However, it remains possible that exposure to greater education or television could have subtly altered the meanings of words in recent times. 19 The change in meaning of the word gay over a generation shows that rapid semantic changes can occur. Methods Searches for relevant studies were carried out using eight academic databases (Academic Search Complete, Google Scholar, Medline, PsycARTICLES, PsycINFO, Psychological and Behavioural Sciences, Scopus and SocINDEX) between August 2012 and January 2013, depending on the database. Databases were searched using a search term relating to SWB ( wellbeing or well-being or life satisfaction or positive affect or happiness ) as well as a term relating to national differences ( national differences or nations or across nations ) and/or historical change ( historical change or historical differences or across history or history ). Reference lists of articles identified as relevant from the initial search were handsearched for additional relevant sources. To be included in this review, a study had to include a measure of SWB as an outcome (not as a predictor), and examine the data at the country level, either across countries or within a country over time. Studies were excluded if they were reviews that did not report novel analyses, used measures of mental ill health rather than SWB or focussed on SWB of a specific age group (e.g. students or older people). No limitations regarding publication dates were applied. Using these criteria, our initial search located 367 publications, which was reduced to 78 after applying the inclusion and exclusion criteria. Results Key datasets and the problem of replication There are many studies reporting novel analyses of national SWB data, but this number is deceptive. Most studies are based on a relatively small number of datasets, the main ones being summarized in Table 2. These datasets all provide one or more measures of national SWB. Studies using these datasets often pair them with data on national characteristics derived from other datasets. Because these other datasets may not cover the same range of countries, the N for analyses may differ across publications even when using the same SWB data. Furthermore, some of the datasets involve repeat surveys over time, so similar analyses may be carried out on the same issue at different time points. For these reasons, it is difficult to regard publications as independent or to say that a finding has been replicated. Another notable feature of this literature is that the predictors of national SWB tend to be highly correlated. Although many predictors show strong associations when examined individually, these tend to reduce or disappear in multivariate analyses. For this reason, predictors may give very different results depending on what other factors are adjusted for. The major predictor that is consistently found in the literature is national income, as measured by GDP per capita or other indicator. Therefore, all other predictors examined in this review consider findings that have, at a minimum, been adjusted for national income. Alternative measures of SWB As described earlier, national SWB is most commonly measured by summary statistics on life satisfaction,

4 SUBJECTIVE WELL-BEING 333 Table 2 Commonly used multinational datasets of subjective well-being Dataset Measurement used No. of countries included Years of assessment Euro-barometer Survey Series Self-report happiness item 79 Annually Self-report life satisfaction item European Values Survey Self-report happiness item , 1990, 1999/2000 Self-report life satisfaction item Gallup poll Cantril s ladder 132 Annually Self-report life satisfaction item Positive affect (PA) Negative affect (NA) German Socio Economic Self-report happiness item 1 Annually Panel Study (GSOEP) United States General Social Self-report happiness item 1 Annually Survey World Values Study Group Self-report happiness item , , , Self-report life satisfaction item , World Database of Happiness (composite of multiple national surveys) Diener dataset (1995) (combines data from 4 datasets) Composite of multiple measurement tools re-scaled on a 10-point scale (includes: self-report happiness items, self-report life satisfaction items, Cantril s ladder) 4 measures of SWB: (1) Combined self-report single-item measures of happiness and life satisfaction (2) The last measure of happiness recorded for each nation reported in the 1993 World Database of Happiness (3 & 4) Measures of life satisfaction & happiness where available happiness or affect. However, a number of alternative measures have been proposed, which are not reviewed in any detail here given the limited attention they have received in the literature. These include flourishing (which combines hedonic and eudaimonic aspects of well-being), 8 inequality in SWB, 20 inequality-adjusted happiness, 21,22 and happy life expectancy. 23,24 Such measures may have much to offer and require further research. Norms for national SWB A notable finding in national surveys is that people tend to rate themselves as happy or satisfied with life. For example, when life satisfaction is scaled from 0 to 100, most people in highly developed countries score between 40 and 100 and the mean score is around 75, and even the lowest countries score above ,26 This finding has been interpreted to imply that SWB may be subject to a homeostatic mechanism Annually Dataset included data collected between 1980 & 1985 National income The predictor examined most often in cross-national studies has been national income, as indicated by real income per capita. Consistent associations with national SWB have been found across different datasets and adjusting for a wide range of other predictors. 12,20,26 32 Although most of the evidence has been from nation-level studies, national income is also a predictor after adjusting for individual income in multi-level analyses. 11,33,34 When the association is plotted, there is a stronger association among poorer countries and a levelling off of gains at higher levels of national income. If a logarithmic transformation is applied to income, the association becomes linear 35 (as illustrated in Figure 1). The association with national income may be stronger for life satisfaction than for measures of affect. 11,33 There has also been a substantial amount of research on this issue using time series data. A seminal publication by Richard Easterlin in the 1970s argued

5 334 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY Figure 1 Scatter plots showing the association between GDP per capita in US$ and SWB. Panel 1 shows the curvilinear relationship and Panel 2 shows the linear relationship when GDP per capita is log transformed. Data on SWB are combined data from World Values Surveys (Source: and data for GDP is for 2007 (Source:

6 SUBJECTIVE WELL-BEING 335 that whereas income was associated with SWB in cross-sectional data, time series data from the USA showed no increase in national SWB over time, despite steady growth in real income per person. 36 This happiness-income paradox, or Easterlin Paradox, continues to be a major source of debate. If true, this paradox implies that economic growth should not be the main aim of policy. Subsequent research has supported Easterlin s observation that SWB has not improved in the USA despite economic growth, 19,37 but improvements have been observed in other high-income countries, including in Europe and Japan. 38,39 However, there is also evidence that rapid economic growth can have a negative effect on SWB ( unhappy growth ) if it leads to greater inequality and aspirations that exceed achievements. 40 This phenomenon has been observed, for example, in China from 1990 to the early 2000s. 41 More sophisticated time series analyses have found evidence that economic growth is associated with greater SWB. 35,42 Easterlin and colleagues have also carried out more recent time series analyses on data from several countries. 43,44 They have concluded that income does affect SWB in the short term, but over the long term (10 years or more) there is no gain. Another view is that, whereas raising incomes does have a mainly short-term effect on SWB, there is also a smaller long-term effect, so that there are lasting gains from economic growth. 42 The benefits of economic growth for SWB continue to be debated, but there does appear to be good evidence that the gains from increases in income are greater in poorer than in richer countries. 28,45 A number of explanations have been put forward to explain the diminishing returns. These include that SWB is influenced more by relative income ( keeping up with the Joneses ) rather than absolute income, 46 that people in rich countries adapt to increases in their income, 46 that changes in other domains (greater working hours) offset the gains from increases in income 47 and that income is important because it allows us to satisfy basic needs and there is less to gain once these needs are met. 48,49 It has been argued that further economic growth will only increase SWB in high-income countries if it allows people to pursue rewarding activities in pursuit of meaningful goals, such as improving close relationships or the quality of working life. 49 There have also been suggestions that national SWB could be improved by changing the reference group with which people compare themselves (e.g. their ancestors or people who are worse off), and that people need to be better informed about the value of seeking happiness in non-pecuniary domains (e.g. family life) 50 which are less subject to adaptation and social comparison than is income. 46 Finally, it is possible that the form of the association between national income and SWB cannot be meaningfully determined because of the use of ordinal scales to measure SWB. It could be argued that, with an ordinal scale, any monotonic transformation is acceptable. Income inequality There have been a number of analyses examining whether income inequality contributes to SWB over and above income per capita. Because high-income nations tend to have less inequality, it is necessary that income be adjusted for. For example, in one nation-level study of 54 nations, there was a correlation of 0.84 between GDP per capita and the Gini coefficient of income inequality, making it difficult to separate these predictors in a regression analysis. 51 In this study, after adjusting for income, inequality had no additional predictive power. By contrast, a more recent nation-level analysis of 51 nations found an effect of inequality on SWB after adjusting for income, but in this analysis a different indicator of income inequality was used which had a lower correlation with GDP per capita ( 0.45). 52 Multi-level analyses have mainly supported a role for income inequality. Two multi-level analyses of European data found that inequality was associated with lower SWB after adjusting for individual income 53 and after adjusting for both individual and national income. 20 By contrast, a multi-level analysis of data from 41 countries found that inequality predicted higher SWB after adjusting for individual and national income. However, this finding was due to the inclusion of Latin American and post-soviet countries, the former of which have a high level of inequality but high SWB, and the latter a low level of inequality but low SWB. 11 A time series analysis of changes in SWB over 25 years in eight high-income countries also found that decreases in inequality were associated with increases in SWB. 50 Social welfare and progressive taxation Other variables closely related to income inequality are the extent of social welfare and progressive taxation. A nation-level analysis of 40 nations found no association between social security expenditure and SWB. By contrast, a time series analysis of data from 12 European nations found that unemployment benefits helped ameliorate the impact of unemployment on SWB. 1 Similarly, a time series analysis of data from 18 industrial democracies found that welfare state generosity (as indicated by pensions, support for the ill and disabled and unemployment benefits) had a positive effect on SWB. 54 A multilevel analysis of 41 nations found that welfare expenditure was associated with greater life satisfaction, but not with greater happiness. 11 A nation-level analysis of 54 nations found that progressive taxation was associated with greater SWB after adjusting for national income and income inequality. 55 A mediation analysis found that this association with progressive taxation was mediated by

7 336 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY greater public satisfaction with services like education and public transportation. Other economic factors Given the interests of economists in this area of research, a number of other economic factors have been investigated, but will only be mentioned briefly here. Unemployment is known to be associated with lower SWB at the individual level. Surprisingly, it does not appear to be associated with SWB in nation-level studies, after adjustment for a range of other predictors, including national income. 31,56 However, time series studies do find that unemployment is associated with lower SWB. 1,47,57,58 The findings are similar to inflation, with time series studies 47,57 59 showing more consistent associations than cross-sectional nation-level studies. 27,31 Individualism versus collectivism Nations have been distinguished according to the value they place on individualism vs collectivism. Individualist nations put more emphasis on individuals taking care of themselves and their immediate families, whereas collectivist ones put more emphasis on people looking after each other and loyalty to the group. This dimension has been measured by expert rating of nations or summary statistics from surveys of values held by employees in various countries. One of the difficulties with evaluating this predictor is that it correlates around 0.8 with GDP per capita, making the two hard to separate in multiple regressions. 32,51 Individualism is also strongly associated with the extent of a nation s human rights and gender equality. 32 A further complicating factor in comparing nations on this variable is that people in individualistic nations may evaluate their satisfaction with life differently from those in collectivist ones, giving greater weight to affect when making ratings. 17 Several cross-sectional nation-level studies have examined individualism. Despite the problems caused by multicollinearity with other national characteristics, a number of these studies have found that individualism predicts national SWB even after adjusting for income and other variables. 25,51,60 However, other cross-sectional nationlevel studies have not found an independent effect of individualism. 32,61,62 The one multi-level study also supported a role for individualism, after adjusting for a range of individual and national variables. 63 There is some evidence that individualism may relate more strongly to SWB when the association is examined only within high-income nations. 32 There is also evidence that it may be more strongly associated with life satisfaction than with affect, 60 and that it may relate more to lower negative affect than to positive affect. 7 Political factors A number of analyses have examined the association of national SWB with ratings of democracy, political freedom, human rights or economic freedom. Again, these factors are hard to examine independently in cross-sectional nation-level studies because of very high correlations with national income and individualism. 32,64 In cross-sectional nation-level studies the findings are mixed, some finding no association after adjusting for national income 31,32,65 and others finding some residual association. 12,30,62 However, a clearer pattern emerges when the cross-sectional associations are compared across points in time. The association was high around 1981, then became low in the 1990s after the democratization of Communist countries, but has risen slightly since These findings indicate that the association may alter during times of major political change. 67 It has also been suggested that big drops in national SWB might be a cause rather than an effect of political change. 67 In the only time series study, covering the period , SWB was found to increase along with the extent to which societies allow free choice, which was driven by economic development, democratization and increasing social tolerance. 68 Social capital Social capital refers to a community s social networks and the associated norms of reciprocity and trust. In studies reviewed here, it has been measured in various ways, but most commonly by the extent of membership in voluntary organizations. In ecological studies, measures of social capital are associated with SWB 69 even after adjusting for economic predictors. 27 Average number of memberships is also found to be a predictor in a multilevel analysis, 70,71 and growth in memberships was associated with growth in SWB in a times series analysis of a range of countries. 72 Physical health Physical health is a reliable predictor of SWB at the individual level, so might be expected to be a predictor at the national level as well. The major national indicator that has been investigated is life expectancy. When the simple nation-level association is examined, life expectancy is very highly correlated with life satisfaction and happiness, 30,60,73 but not with affect. 60,74 Fewer studies have examined the association adjusting for other predictors. Where this has been done, the association persisted in one nation-level analysis 31 and one multi-level analysis, 47 but not in another multi-level analysis. 70 An association has also been reported between happiness and life satisfaction and self-reported hypertension in European nations. 75 Given that both SWB and life expectancy are important national indicators in their own right, Veenhoven has proposed that they should be

8 SUBJECTIVE WELL-BEING 337 combined into an index of happy life-expectancy, 23 somewhat analogous to the concepts of disabilityand quality-adjusted life-years. Other predictors This review has covered the predictors that have been investigated most consistently in the literature. However, there is limited evidence for a range of other factors. Positive influences include business climate, 56 quality of government, 70 average importance of god/religion, 71 length of time a society has been democratic, 76 literacy, 77 national personality tending towards high extraversion and low neuroticism, 10 value placed on leisure and thrift, 12 fulfilment of societal needs, 78 the natural environment, 65 Christian majority, 79 having a bicameral parliament 79 and openness to trade. 79 Negative influences include environmental degradation, 47 crime, 47 average number of hours worked, 47 extreme climates, 31 Buddhist religion 31 and living in a post-communist society. 79 Discussion There is clear evidence from nation-level studies that social, economic and political features of nations are associated with their SWB, and clear evidence from multilevel analyses that these national features contribute to SWB over and above characteristics of the individuals that make up the nation. However, given the nature of the methodologies used, definite causality is difficult to establish. It is generally assumed that the national features drive SWB, but reverse causality is a possibility. For example, drops in SWB could lead to political change in a nation, 67 or SWB could lead to economic growth. 80 In this literature, the most researched national variable has been income. It is clear that increases in income improve the SWB of a nation, but the returns appear to diminish at higher levels. These findings underscore the importance of further economic development for poorer nations. However, the dilemma for the world is that economic growth which is based on non-renewable resources will not be sustainable. If nations use up resources to produce short-term improvements in SWB, then this will be at the expense of the SWB of future generations. Such short-term strategies have been used by human populations in the past with unfortunate consequences, and have been called future eating. 81 Fortunately, there are other income-related strategies for increasing national SWB, including reducing the range or skew of income distribution and changing the reference group with which people compare their wealth. 50 It is also important for high-income nations to examine strategies for increasing SWB which go beyond income. Indeed, it has been argued that high-income nations are undergoing a change in values away from reducing material scarcity towards postmaterialist self-expression values, such as personal autonomy and job creativity. 82 When examining predictors other than national income, it is striking that these predictors tend to be highly correlated both with income and with each other. It appears that national SWB is associated with a package involving higher income, relative equality, individualism, social welfare, political stability and democracy, and high life expectancy. Regression analyses attempt to tease these apart, but may be attempting to answer an artificial question. It may not be meaningful to ask about the effects of one predictor holding others constant, because the others may be conditions required for changes in this predictor. A major aim of this review is to examine lessons that can be learned for psychiatric epidemiology. Psychiatric epidemiology has largely focused on risk factors within a nation and very little is known about national determinants. Given that mental disorders are associated with lower SWB, we might expect that some of these national factors may also be relevant to national mental ill health. The limited evidence available supports this. One study found that anxiety was lower in more individualistic countries and was more protective than national income. 83 Another study found that mean depression scores were lower in nations that were high in income, more highly educated, having a high level of information available through media, egalitarian and more democratic, and had more civil, human and political rights. 13 On the other hand, a study of depression prevalence rates from the World Health Organization World Health Surveys found no association with gross national income or nation-level inequality. 84 However, given that the construct of SWB has only partial overlap with constructs of mental ill health, there are likely to be differential patterns of association with national characteristics and there would be merit in looking at both types of outcomes in the same study. Another lesson may be in the use of brief survey items to allow comparisons across nations and across time. In psychiatric epidemiology, the emphasis has been on using diagnostic instruments to arrive at disorder prevalence rates, as exemplified by World Health Organization s World Mental Health Initiative. 85 These surveys involve complex interviews and scoring algorithms, and the cross-cultural portability of the methods can be questioned. 86 For example, it seems hard to accept that Nigeria and China could have a much lower prevalence of mental disorders than The Netherlands or New Zealand, given that such findings seem inconsistent with findings on SWB. By contrast, SWB research has used very brief measures that can be easily incorporated in social surveys. Simple measures have also proved useful in general health surveys, with a single question about self-rated health known to be a predictor of mortality. 87 It may be possible to

9 338 INTERNATIONAL JOURNAL OF EPIDEMIOLOGY develop similarly simple measures that are cross-culturally portable for mental ill health. These would not give prevalence estimates, but could be used to measure national and historical trends at a population level. For example, using the single-item happiness rating from SWB research, responses can be scored to examine the percentage who are very unhappy in addition to the percentage who are very happy, and the correlates are somewhat different. 12 If such measures were used in national surveys on a regular basis, they could provide a complement to use of the suicide rate, which has been the major available indicator for cross-national and time series analysis. Although the emphasis of this review has been on what the study of national SWB can teach psychiatric epidemiology, there is also potential for transfer in the other direction. Some of the central risk factors that dominate psychiatric epidemiology have received little attention as potential determinants of national SWB. These include factors such as childhood adversity (including child abuse), parenting practices, traumatic and other adverse life events, working conditions, social support and substance use. Funding The lead author is funded by an NHMRC Australia Fellowship. Conflict of interest: None declared. KEY MESSAGES A number of socio-economic factors are associated greater national well-being, including income per capita, income inequality, social welfare, individualism, democracy and freedom, social capital and physical health. Economic growth of poorer nations will improve global well-being. To achieve sustainability, wealthier nations need to focus on other determinants of subjective wellbeing. Research on cross-national well-being has lessons for psychiatric epidemiology, in terms of the types of determinants studied and the use of brief cross-culturally portable measures. References 1 Di Tella R, MacCulloch RJ, Oswald AJ. The macroeconomics of happiness. Rev Econ Stat 2003;85: Lucas RE, Diener E, Suh E. Discriminant validity of wellbeing measures. J Pers Soc Psychol 1996;71: Diener E, Inglehart R, Tay L. Theory and validity of life satisfaction scales. Soc Indic Res 2012;112: Clark LA, Watson D. Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. J Abnorm Psychol 1991;100: Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas 1977;1: Huppert FA, Whittington JE. Evidence for the independence of positive and negative well-being: Implications for quality of life assessment. Br J Health Psychol 2003;8: Kuppens P, Ceulemans E, Timmerman ME, Diener E, Kim-Prieto C. Universal intracultural and intercultural dimensions of the recalled frequency of emotional experience. J Cross Cult Psychol 2006;37: Huppert FA. Flourishing across Europe: application of a new conceptual framework for defining well-being. Soc Indic Res 2013;110: Lucas RE, Brent Donnellan M. Estimating the reliability of single-item life satisfaction measures: results from four national panel studies. Soc Indic Res 2012;105: Lynn M, Steel P. National differences in subjective wellbeing: the interactive effects of extraversion and neuroticism. J Happiness Stud 2006;7: Haller M, Hadler M. How social relations and structures can produce happiness and unhappiness: an international comparative analysis. Soc Indicat Res 2006; 75: Minkov M. Predictors of differences in subjective well-being across 97 nations. Cross Cult Res 2009;43: Van Hemert DA, Van De Vijver FJ, Poortinga YH. The Beck Depression Inventory as a measure of subjective well-being: a cross-national study. J Happiness Stud 2002; 3: Fischer R, Van de Vliert E. Does climate undermine subjective well-being? A 58-nation study. Pers Soc Psychol Bull 2011;37: Diener E, Oishi S, Lucas RE. Personality, culture, and subjective well-being: emotional and cognitive evaluations of life. Annu Rev Psychol 2003;54: Layard PRG. Happiness: Lessons From a New Science. London: Allen Lane, Suh E, Diener E, Oishi S, Triandis HC. The shifting basis of life satisfaction judgments across cultures: emotions versus norms. J Pers Soc Psychol 1998;74: Kapteyn A, Smith JP, Van Soest A. Are Americans really less happy with their incomes? Rev Income Wealth 2013;59: Blanchflower DG, Oswald AJ. Is Well-being U-Shaped Over the Life Cycle? IZA Discussion Papers, No Bonn, Germany: Institute for the Study of Labor, Fahey T, Smyth E. Do subjective indicators measure welfare? Evidence from 33 European societies. Eur Soc 2004; 6:5 27.

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