Dispositional and situational attributions for why the rich live longer than the poor

Abstract

Despite considerable focus on predictors of attitudes towards economic inequality, there is less psychological research into attitudes towards other unequal outcomes between the rich and poor, including differences in health and life expectancy. Two studies examine whether causal attributions for these socioeconomic health inequalities predict attitudes towards them. A cross-sectional study of 332 UK and US respondents showed that most respondents indicate a preference for some degree of income inequality but no life expectancy inequality between the richest and poorest in society. These preferences for equal life expectancy for the rich and poor were significantly less likely for respondents who viewed health inequalities to be caused by dispositional factors (e.g., self-control, ability or effort). In a second preregistered cross-sectional study (n = 602), dispositional attributions negatively predicted self-reported concern about health inequality, whilst endorsing situational attributions (e.g., discrimination and prejudice, wages) was positively associated with concerns on this issue. Moreover, situational attributions positively predicted support for six policy proposals for reducing health inequality, while dispositional attributions were associated with increased support for some of these interventions and decreased support for others. Despite very distinct distribution preferences for income and life expectancy outcomes, causal attributions continue to predict attitudes towards health inequality and associated policy interventions.

Public preferences to trade-off gains in total health for health equality: Discrepancies between an abstract scenario versus the real-world scenario presented by COVID-19

“…This survey considered one dimension of health inequality – income. Income differences in health have been a focus of much research in economics (e.g., Ali et al, 2017; Cookson et al, 2018; Costa-Font and Cowell, 2019) and in health psychology (e.g., Bridger et al, 2023). Of course, there are other important dimensions of health inequality, such as race (e.g., Abedi et al, 2021) and age (e.g., Lloyd-Sherlock et al, 2022).…”

“…It would be instructive to learn, for instance, whether those who levelled down in this survey would also sacrifice years of education from the top and bottom of the income distribution if doing so would reduce educational inequality. Presumably they would because anyone willing to sacrifice years of life to reduce inequality in health outcomes would, assuming they recognize socioeconomic differences in education as one of the drivers of health inequality (e.g., Bridger et al, 2023), surely also be willing to sacrifice years of education to promote equality.…”

When is health inequality acceptable? Appraisals of inevitability, complexity and causal explanations

“…There is already considerable study of the UK public's view of health inequality (2, 10) and we wished to include respondents from another English-speaking country with high levels of inequality. In line with previous work, (2,11,30) we asked participants to indicate the priority with which these life expectancy differences should be addressed (Study 1) and agreement that something should be done about them (Study 2), as well as about the overall acceptability of life expectancy inequality (Studies 1 and 2). We present participants with one of six bases of categorization: genetics, lifestyle choices, income, education, neighbourhood and social class.…”

“…One commonly examined basis of categorization is income, as in studies of income-related health inequality aversion, (13) ideal health distributions across income quintiles (12) or views on life expectancy differences between the rich and the poor. (11) These provide valuable insights, but they do not re ect the diversity of categorizations actually employed in health inequality research. In their mapping analysis of health equity research, Collyer & Smith (14) identi ed at least eight different clusters of leading international researchers working in the area.…”

“…(7)(8)(9) Others use simpler survey designs to ask about acceptable levels of health or income inequality in society. (10)(11)(12) One feature common to these distinct approaches is that preferences, views or attitudes are typically elicited in a bivariate manner. (8, 10) By this we refer to the fact that health inequalities are presented as a function of another grouping or domain, which we call different bases of categorization (or categorizations for brevity) hereafter.…”