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According to The Spirit Level, inequality is bad for everyone—including people with higher incomes. That conclusion is evident also in research exploring the impact of inequality on status anxiety. But existing research on this topic is cross-sectional (and gives too much weight to statistical significance). I construct a longitudinal analysis to explore whether status anxiety increases with inequality, especially among higher earners. I use country-level averages of status anxiety for this purpose and ignore individual-level control variables, on the grounds that they are not antecedents of the focal independent variable, inequality. In contrast to previous research, I find that increases in inequality lead to lower levels of status anxiety for higher earners. People at the top appear to benefit from inequality in this sense—a finding that runs against the idea that inequality is bad for everyone.
A series of aggressive restrictive measures were adopted around the world in 2020–2022 to attempt to prevent SARS-CoV-2 from spreading. However, it has become increasingly clear the most aggressive (lockdown) response strategies may involve negative side-effects such as a steep increase in poverty, hunger, and inequalities. Several economic, educational, and health repercussions have fallen disproportionately on children, students, young workers, and especially on groups with pre-existing inequalities such as low-income families, ethnic minorities, and women. This has led to a vicious cycle of rising inequalities and health issues. For example, educational and financial security decreased along with rising unemployment and loss of life purpose. Domestic violence surged due to dysfunctional families being forced to spend more time with each other. In the current narrative and scoping review, we describe macro-dynamics that are taking place because of aggressive public health policies and psychological tactics to influence public behavior, such as mass formation and crowd behavior. Coupled with the effect of inequalities, we describe how these factors can interact toward aggravating ripple effects. In light of evidence regarding the health, economic and social costs, that likely far outweigh potential benefits, the authors suggest that, first, where applicable, aggressive lockdown policies should be reversed and their re-adoption in the future should be avoided. If measures are needed, these should be non-disruptive. Second, it is important to assess dispassionately the damage done by aggressive measures and offer ways to alleviate the burden and long-term effects. Third, the structures in place that have led to counterproductive policies should be assessed and ways should be sought to optimize decision-making, such as counteracting groupthink and increasing the level of reflexivity. Finally, a package of scalable positive psychology interventions is suggested to counteract the damage done and improve humanity's prospects.
A number of recent studies find that integration and multiculturalism policies help soften anti-immigrant attitudes among the broader population. These findings, however, emerge from cross-sectional analyses and are potentially vulnerable to omitted variable bias. The analysis in this paper overcomes that limitation by adopting a longitudinal approach. This approach uses data from repeated cross-sections drawn from the European Social Survey and the European Values Survey. These data can be treated as panels in a longitudinal framework once it is recognised that the relevant variables (including the attitudes variables) can be handled effectively as country-level averages. Multi-level modelling (the default approach in existing research) is not necessary; in particular, there is no need to use individual-level control variables. In a fixed-effects analysis of country-level data, adoption of more open/accommodating integration and/or multiculturalism policies does not lead to a reduction in anti-immigration sentiment. The findings of the cross-sectional studies evidently suffer from significant omitted variable bias.
Happiness/well-being researchers who use quantitative analysis often do not give persuasive reasons why particular variables should be included as controls in their cross-sectional models. One commonly sees notions of a “standard set” of controls, or the “usual suspects”, etc. These notions are not coherent and can lead to results that are significantly biased with respect to a genuine causal relationship.
This article presents some core principles for making more effective decisions of that sort. The contribution is to introduce a framework (the “causal revolution”, e.g. Pearl and Mackenzie 2018) unfamiliar to many social scientists (though well established in epidemiology) and to show how it can be put into practice for empirical analysis of causal questions. In simplified form, the core principles are: control for confounding variables, and do not control for intervening variables or colliders. A more comprehensive approach uses directed acyclic graphs (DAGs) to discern models that meet a minimum/efficient criterion for identification of causal effects.
The article demonstrates this mode of analysis via a stylized investigation of the effect of unemployment on happiness. Most researchers would include other determinants of happiness as controls for this purpose. One such determinant is income—but income is an intervening variable in the path from unemployment to happiness, and including it leads to substantial bias. Other commonly-used variables are simply unnecessary, e.g. religiosity and sex. From this perspective, identifying the effect of unemployment on happiness requires controlling only for age and education; a small (parsimonious) model is evidently preferable to a more complex one in this instance.
Why do people from privileged class backgrounds often misidentify their origins as working class? We address this question by drawing on 175 interviews with those working in professional and managerial occupations, 36 of whom are from middle-class backgrounds but identify as working class or long-range upwardly mobile. Our findings indicate that this misidentification is rooted in a self-understanding built on particular ‘origin stories’ which act to downplay interviewees’ own, fairly privileged, upbringings and instead forge affinities to working-class extended family histories. Yet while this ‘intergenerational self’ partially reflects the lived experience of multigenerational upward mobility, it also acts – we argue – as a means of deflecting and obscuring class privilege. By positioning themselves as ascending from humble origins, we show how these interviewees are able to tell an upward story of career success ‘against the odds’ that simultaneously casts their progression as unusually meritocratically legitimate while erasing the structural privileges that have shaped key moments in their trajectory.
The income inequality hypothesis claims that in rich societies inequality causes a range of health and social problems (henceforth: social ills), e.g. because economic inequality induces feelings of status anxiety and corrodes social cohesion. This paper provides an encompassing test of the income inequality hypothesis by exploring levels and breeding conditions of social ills in 40 affluent countries worldwide, as well as pathways for a subsample of wealthy European countries. Our aggregate-level research is based on a revised and updated Index of Social Ills inspired by Wilkinson and Pickett’s book The Spirit Level, which we compile for both more countries (40) and more years (2000–2015) and combine with survey information about experienced quality-of-life as potential mediators. We get three major results: First, cross-sectionally income inequality is indeed strongly and consistently related to social ills, but so is economic prosperity. Second, while longitudinally changes in inequality do not result in changing levels of social ills, rising prosperity effectively reduces the amount of social ills, at least in Europe. Finally, whereas the cross-sectional analysis indicates that aspects of social cohesion most consistently mediate between economic conditions and social ills, the longitudinal mediation analyses could not ultimately clarify through which pathway rising prosperity reduces social ills. Overall we conclude that the income inequality hypothesis is, at best, too narrow to fully understand health and social problems in rich countries.
This study proposes subjective social status-a person's perception of his/her standing in the social hierarchy-is an important psychological mechanism driving the inequality-satisfaction link. Building on sociological and social-psychological research, it argues (i) the contextual effect of income inequality on subjective well-being is mediated by social status perceptions, and (ii) income inequality moderates the relationship between subjective social status and well-being. The empirical analysis is based on data from the 2012/2013 European Social Survey. Applying multi-level modelling techniques, the study finds income inequality lowers the self-perception of social status and, in turn, the overall well-being of individuals (the mediation argument). It also finds that income inequality increases the importance of subjective social status to life satisfaction (the moderation argument). The results are limited to the European context and should encourage researchers to test the hypotheses in other geographic regions and to dig deeper into the underlying mechanisms explaining if and why income inequality matters to the well-being of individuals.
The goal of this study is to explore the relationship between culture and social well-being, focusing on inferiority feelings. While being respected is widely seen as a key ingredient of a good life, inferiority feelings signal a lack of esteem from others. Previous research has mainly looked at income inequality as the key contextual condition for inferiority feelings and other status concerns, often inspired by the income inequality thesis/Spirit Level paradigm (Wilkinson and Pickett 2010). We contribute to this discussion by extending this paradigm into the cultural realm. Our main assumption is that an inegalitarian culture breeds inferiority feelings, whereas an egalitarian culture dampens them and in this sense is “better”. Within a multi-level framework we combine information on culture, operationalized as collective values and beliefs, retrieved from the European Value Study for 30 European countries, and survey data on inferiority feelings for over 37,000 individuals from the most recent European Quality of Life Survey (2011–12). Our evidence suggests that widespread self-expression values and social trust (as expressions of an egalitarian culture) are indeed better as they dampen individuals’ inferiority feelings while widespread individual blame for poverty (an expression of an inegalitarian culture) heightens them. In further analyses of each income quintile separately, we find evidence that culture matters—for good or worse—for all income groups, except the poorest quintiles. Our results should prompt scholars of social status and social well-being to pay more attention to the impact of culture.
Following the “status anxiety hypothesis,” the psychological consequences of income inequality should be particularly severe for economically vulnerable individuals. However, oddly, income inequality is often found to affect vulnerable low-income and advantaged high-income groups equally. We argue that economic vulnerability is better captured by a financial scarcity measure and hypothesize that income inequality primarily impairs the psychological health of people facing scarcity. First, repeated cross-sectional international data (WVS: 146,034 participants; 105 country-waves) revealed that the within-country effect of national income inequality on feelings of unhappiness was limited to individuals facing scarcity (≈ 25% of the WVS population). Second, longitudinal national data (SHP: 14,790 participants; 15,595 municipality-years) revealed that the within-life-course effect of local income inequality on psychological health problems was also limited to these individuals (< 10% of the Swiss population). Income inequality by itself may not be a problem for psychological health but rather a catalyst for the consequences of scarcity.
The Spirit Level Theory developed by Richard Wilkinson and Kate Pickett claims that low-inequality societies are better societies because people are plagued less by status anxiety, and previous research has largely supported this idea. With the aim of broadening the knowledge about status anxiety, this article examines a crucial component of status anxiety – the feeling of not counting much in the eyes of others – within a multilevel framework for 27 European countries, using the European Quality of Life Survey 2011/2012. We first clarify which individual characteristics in particular result in status anxiety: labor market exclusion and low-income position. Second, influenced by the seminal work of Pierre Bourdieu in Distinction, we explore a societal condition of status anxiety that appears to be particularly salient due to its visibility in everyday life: cultural class divisions. Our evidence suggests that the extent of class divisions in cultural consumption fuels status anxiety, over and above the effects of income inequality and national affluence. Thus, we advocate a sociocultural redirection of the Spirit Level framework.
The income inequality hypothesis states that income inequality has a negative effect on individual’s health, partially because it reduces social trust. This article aims to critically assess the income inequality hypothesis by comparing several analytical strategies, namely OLS regression, multilevel regression, fixed effects models and fixed effects models using pseudo panel data. To test the hypothesis, data from two studies conducted between 1981 and 2014 were combined: the World Values Survey and the European Values Study. Three frequently used measures of health were taken into account. In the OLS and multilevel models, income inequality was often associated with better health, whereas in the fixed effects and pseudo panel data, income inequality was associated with poorer health, suggesting that the unexpected results of the OLS and multilevel methods might be explained by unobserved confounders. Furthermore, in almost all of the models, social trust mediates the relationship between income inequality and health, showing the importance of this mechanism. Interestingly, the pseudo panel data offer the strongest support for the income inequality hypothesis, suggesting that better controlling for confounding factors and/or more carefully monitoring cohort effects, may result in a better understanding whether and how income inequality can be harmful for people’s health.
Is there a positive association between a nation’s income inequality and concerns with status competition within that nation? Here we use Google Correlate and Google Trends to examine frequency of internet search terms and find that people in countries in which income inequality is high search relatively more frequently for positional brand names such as Prada, Louis Vuitton, or Chanel. This tendency is stronger among well-developed countries. We find no evidence that income alone is associated with searches for positional goods. We also present evidence that the concern with positional goods does not reflect non-linear effects of income on consumer spending, either across nations or (extending previous findings that people who live in unequal US States search more for positional goods) within the USA. It is concluded that income inequality is associated with greater concerns with positional goods, and that this concern is reflected in internet searching behaviour.
Previous research has shown that having rich neighbors is associated with reduced levels of subjective well-being, an effect that is likely due to social comparison. The current study examined the role of income inequality as a moderator of this relative income effect. Multilevel analyses were conducted on a sample of more than 1.7 million people from 2,425 counties in the United States. Results showed that higher income inequality was associated with stronger relative income effects. In other words, people were more strongly influenced by the income of their neighbors when income inequality was high. (PsycINFO Database Record
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Whether income inequality is related to population health is still open to debate. We aimed to critically assess the relationship between income inequality and mortality in 43 European countries using comparable data between 1987 and 2008, controlling for time-invariant and time-variant country-level confounding factors. Annual data on income inequality, expressed as Gini index based on net household income, were extracted from the Standardizing the World Income Inequality Database. Data on life expectancy at birth and age-standardized mortality by cause of death were obtained from the Human Lifetable Database and the World Health Organization European Health for All Database. Data on infant mortality were obtained from the United Nations World Population Prospects Database. The relationships between income inequality and mortality indicators were studied using country fixed effects models, adjusted for time trends and country characteristics. Significant associations between income inequality and many mortality indicators were found in pooled cross-sectional regressions, indicating higher mortality in countries with larger income inequalities. Once the country fixed effects were added, all associations between income inequality and mortality indicators became insignificant, except for mortality from external causes and homicide among men, and cancers among women. The significant results for homicide and cancers disappeared after further adjustment for indicators of democracy, education, transition to national independence, armed conflicts, and economic freedom. Cross-sectional associations between income inequality and mortality seem to reflect the confounding effects of other country characteristics. In a European context, national levels of income inequality do not have an independent effect on mortality.
As an introduction to the papers of this special issue on Consequences of Economic Inequality we first underline with a simple empirical exercise the relevance of studying the subject of consequences of economic inequality in many socially important fields. Next, we sketch the two main theoretical perspectives on the channels by which inequality exerts its effects: on the one hand, the psychosocial, which stresses the role of individual status and stratification, and, on the other hand, the neo-material, which puts the focus on resources at people's disposal. In our view the two are not mutually exclusive. Thirdly, we present each of the contributions and relate their results to these main perspectives. We find support for the view that inequality can magnify not only the differences between individuals or households in the resources at their disposal, but also the association between these resources and politics, well-being and social stratification.
The multilevel model has become a staple of social research. I textually and formally explicate sample design features that, I contend, are required for unbiased estimation of macro-level multilevel model parameters and the use of tools for statistical inference, such as standard errors. After detailing the limited and conflicting guidance on sample design in the multilevel model didactic literature, illustrative nationally-representative datasets and published examples that violate the posited requirements are identified. Because the didactic literature is either silent on sample design requirements or in disagreement with the constraints posited here, two Monte Carlo simulations are conducted to clarify the issues. The results indicate that bias follows use of samples that fail to satisfy the requirements outlined; notably, the bias is poorly-behaved, such that estimates provide neither upper nor lower bounds for the population parameter. Further, hypothesis tests are unjustified. Thus, published multilevel model analyses using many workhorse datasets, including NELS, AdHealth, NLSY, GSS, PSID, and SIPP, often unwittingly convey substantive results and theoretical conclusions that lack foundation. Future research using the multilevel model should be limited to cases that satisfy the sample requirements described.
Originating in econometrics and statistics, the counterfactual model provides a natural framework for clarifying the requirements for valid causal inference in the social sciences. This article presents the basic potential outcomes model and discusses the main approaches to identification in social science research. It then addresses approaches to the statistical estimation of treatment effects either under unconfoundedness or in the presence of unmeasured heterogeneity. As an update to Winship & Morgan's (1999) earlier review, the article summarizes the more recent literature that is characterized by a broader range of estimands of interest, a renewed interest in exploiting experimental and quasi-experimental designs, and important progress in the areas of semi- and nonparametric estimation of treatment effects, difference-in-differences estimation, and instrumental variable estimation. The review concludes by highlighting implications of the recent econometric and statistical literature for sociological research practice.
People's self-perception biases often lead them to see themselves as better than the average person (a phenomenon known as self-enhancement). This bias varies across cultures, and variations are typically explained using cultural variables, such as individualism versus collectivism. We propose that socioeconomic differences among societies--specifically, relative levels of economic inequality--play an important but unrecognized role in how people evaluate themselves. Evidence for self-enhancement was found in 15 diverse nations, but the magnitude of the bias varied. Greater self-enhancement was found in societies with more income inequality, and income inequality predicted cross-cultural differences in self-enhancement better than did individualism/collectivism. These results indicate that macrosocial differences in the distribution of economic goods are linked to microsocial processes of perceiving the self.
Analysis of mortality trends over 40 years in England and Wales showed that mortality from coronary heart disease had become progressively more common in working-class men and women than in those from the middle and upper classes. The change was most noticeable for men. Whereas in 1931 and 1951 heart disease was more common in men of social classes I and II, by 1961 it was more common in men of classes IV and V. This change in social-class distribution can only partly be explained by changes in diagnostic methods. The worsening mortality of classes IV and V correlated with relatively more smoking, a higher consumption of sugar, and a lower consumption of wholemeal bread in these classes. There was no correlation between change in heart disease and change in the social-class pattern of fat consumption.
The well-known Easterlin paradox points out that average happiness has remained constant over time despite sharp rises in GNP per head. At the same time, a micro literature has typically found positive correlations between individual income and individual measures of subjective well-being. This paper suggests that these two findings are consistent with the presence of relative income terms in the utility function. Income may be evaluated relative to others (social comparison) or to oneself in the past (habituation). We review the evidence on relative income from the subjective well-being literature. We also discuss the relation (or not) between happiness and utility, and discuss some nonhappiness research (behavioral, experimental, neurological) related to income comparisons. We last consider how relative income in the utility function can affect economic models of behavior in the domains of consumption, investment, economic growth, savings, taxation, labor supply, wages, and migration.
Inequality in the distribution of income and wealth has come to the fore as a core concern across the industrialized world. Here we examine what has happened to income inequality across the rich countries in recent decades. We discuss the range of factors that appear to be driving inequality upwards, notably the role of technological change, globalization, and national institutions and policies. We look at how rising inequality might undermine economic growth and squeeze the middle, and assess the extent to which it has actually done so. We assess whether rising inequality is associated with worsening outcomes and inequalities across various social domains. Finally, we review emerging evidence on the role that rising inequality may be playing in the ‘revolt of the angry’ and rise of populism.
This article documents wide‐ranging revisions to the Standardized World Income Inequality Database (SWIID), which seeks to maximize the comparability of income inequality estimates for the broadest possible coverage of countries and years.
Two k‐fold cross‐validations, by observation and by country, are used to evaluate the SWIID's success in predicting the Luxembourg Income Study (LIS), recognized in the field as setting the standard for comparability.
The cross‐validations indicate that the new SWIID's estimates and their uncertainty are even more accurate than previous versions, extending its advantage in comparability over alternate income inequality data sets.
Given its superior coverage and comparability, the SWIID remains the optimum source of data for broadly cross‐national research on income inequality.
In this paper, we review and integrate the contemporary literature on the societal effects of income inequality, drawing on social, personality, developmental, and organizational psychology, sociology, political science, economics, and public health. Living in highly unequal regimes is associated with both increased mistrust and increased anxiety about social status; these psychological mechanisms help explain some of the negative outcomes associated with income inequality, such as lower happiness, lower social cohesion, weaker morality, higher mortality, worse health, and weaker governance.
Did mandatory busing programs in the 1970s increase the school achievement of disadvantaged minority youth? Does obtaining a college degree increase an individual's labor market earnings? Did the use of the butterfly ballot in some Florida counties in the 2000 presidential election cost Al Gore votes? If so, was the number of miscast votes sufficiently large to have altered the election outcome? At their core, these types of questions are simple cause-and-effect questions. Simple cause-and-effect questions are the motivation for much empirical work in the social sciences. This book presents a model and set of methods for causal effect estimation that social scientists can use to address causal questions such as these. The essential features of the counterfactual model of causality for observational data analysis are presented with examples from sociology, political science, and economics.
To understand the mechanisms behind social inequality, this address argues that we need to more thoroughly incorporate the effects of status-inequality based on differences in esteem and respect-alongside those based on resources and power. As a micro motive for behavior, status is as significant as money and power. At a macro level, status stabilizes resource and power inequality by transforming it into cultural status beliefs about group differences regarding who is "better" (esteemed and competent). But cultural status beliefs about which groups are "better" constitute group differences as independent dimensions of inequality that generate material advantages due to group membership itself. Acting through micro-level social relations in workplaces, schools, and elsewhere, status beliefs bias evaluations of competence and suitability for authority, bias associational preferences, and evoke resistance to status challenges from low-status group members. These effects accumulate to direct members of higher status groups toward positions of resources and power while holding back lower status group members. Through these processes, status writes group differences such as gender, race, and class-based life style into organizational structures of resources and power, creating durable inequality. Status is thus a central mechanism behind durable patterns of inequality based on social differences.
The empirical association between income inequality, population health, and other social problems is now well established, and the research literature suggests that the relationship is not artefactual. Debate is still ongoing as to the cause of this association. Wilkinson, Marmot, and colleagues have argued for some time that the relationship stems from the psycho-social effects of status comparisons. Here, income inequality is a marker of a wider status hierarchy that provokes an emotional stress response in individuals that is harmful to health and well-being. We label this the 'status anxiety hypothesis'. If true, this would imply a structured relationship between income inequality at the societal level, individual income rank, and anxiety relating to social status. This article sets out strong and weak forms of the hypothesis and then presents three predictions concerning the structuring of 'status anxiety' at the individual level given different levels of national income inequality and varying individual income. We then test these predictions using data from a cross-national survey of >34,000 individuals carried out in 2007 in 31 European countries. Respondents from low-inequality countries reported less status anxiety than those in higher inequality countries at all points on the income rank curve. This is an important precondition of support for the status anxiety hypothesis and may be seen as providing support for the weaker version of the hypothesis. However, we do not find evidence to support a stronger version of the hypothesis which we hold requires the negative effect of income rank on status anxiety to be exacerbated by increasing income inequality.
The overwhelming majority of quantitative work in sociology reports levels of statistical significance. Often, significance is reported with little or no discussion of what it actually entails philosophically, and this can be problematic when analyses are interpreted. Often, significance is understood to represent the probability of the null hypothesis (usually understood as a lack of relationship between two or more variables). This understanding is simply erroneous. The first section of this paper deals with this common misunderstanding. The second section gives a history of significance testing in the social sciences, with reference to the historical foundations of many common misinterpretations of significance testing. The third section is devoted to a discussion of the consequences of misinterpreting statistical significance for sociology. It is argued that reporting statistical significance provides sociology with very little value, and that the consequences of misinterpreting significance values outweighs the benefits of their use.
Income inequality is strongly associated with infant mortality across countries, but whether this association is causal has not been established. In their commentary in this issue of Social Science & Medicine, Regidor et al. (2012) argue that this association has disappeared in recent years, and question the premise of a causal link. This paper empirically tests the impact of income inequality on infant mortality in a fixed effects model that exploits the evolution of income inequality over a 38-year period, controlling for all time-invariant differences across countries. Data came from the Standardized World Income Inequality Database, containing yearly estimates for the period 1960-2008 in 34 countries member of the Organization for Economic Co-operation and Development (OECD), linked to infant mortality data from the OECD Health database. Infant mortality was modelled as a function of income inequality in a country and year fixed effects model, incorporating controls for changing economic and labour conditions. In a model without country fixed effects, a one-point increase in the Gini coefficient was associated with a 7% increase in the infant mortality rate (Rate ratio[RR] = 1.07, 95% Confidence Interval [CI] 1.04, 1.09). Controlling for differences across countries in a country fixed effects model, however, income inequality was no longer associated with infant mortality (RR = 1.00, 0.98, 1.01). Similar results were obtained when using lagged values of income inequality for up to 15 years, and in models that controlled for changing labour and economic conditions. Findings suggest that in the short-run, changes in income inequality are not associated with changes in infant mortality. A possible interpretation of the discrepancy between cross-country correlations and fixed effects models is that social policies that reduce infant mortality cluster in countries with low income inequality, but their effects do not operate via income. Findings highlight the need to examine the impact of more specific social policies on infant mortality.
Objective. Cross-national research on the causes and consequences of income inequality has been hindered by the limitations of existing inequality data sets: greater coverage across countries and over time is available from these sources only at the cost of significantly reduced comparability across observations. The goal of the Standardized World Income Inequality Database (SWIID) is to overcome these limitations.
Methods. A custom missing-data algorithm was used to standardize the U.N. University's World Income Inequality Database; data collected by the Luxembourg Income Study served as the standard.
Results. The SWIID provides comparable Gini indices of gross and net income inequality for 153 countries for as many years as possible from 1960 to the present, along with estimates of uncertainty in these statistics.
Conclusions. By maximizing comparability for the largest possible sample of countries and years, the SWIID is better suited to broad cross-national research on income inequality than previously available sources.
I. Gratification over advances of others: the tunnel effect introduced, 545. — II. Some evidence, 548.— III. Consequences for integration and revolution, 550.— IV. From gratification to indignation, 552.— V. The tunnel effect: social, historical, cultural, and institutional determinants of its strength, 553. —VI. An alternative reaction: apprehension over advances of others, 559.— VII.Concluding remarks, 560.— Mathematical appendix, 562.
The Whitehall study of British civil servants begun in 1967, showed a steep inverse association between social class, as assessed by grade of employment, and mortality from a wide range of diseases. Between 1985 and 1988 we investigated the degree and causes of the social gradient in morbidity in a new cohort of 10,314 civil servants (6900 men, 3414 women) aged 35-55 (the Whitehall II study). Participants were asked to answer a self-administered questionnaire and attend a screening examination. In the 20 years separating the two studies there has been no diminution in social class difference in morbidity: we found an inverse association between employment grade and prevalence of angina, electrocardiogram evidence of ischaemia, and symptoms of chronic bronchitis. Self-perceived health status and symptoms were worse in subjects in lower status jobs. There were clear employment-grade differences in health-risk behaviours including smoking, diet, and exercise, in economic circumstances, in possible effects of early-life environment as reflected by height, in social circumstances at work (eg, monotonous work characterised by low control and low satisfaction), and in social supports. Healthy behaviours should be encouraged across the whole of society; more attention should be paid to the social environments, job design, and the consequences of income inequality.
Supply-side tax cuts and the truth about the Reagan economic record. Cato Institute Policy Analysis No. 261