Commentary: Income inequality and health: The end of the story?

John Lyncha and George Davey Smithb

a Department of Epidemiology and Institute for Social Research, University of Michigan, 109 Observatory Street, Ann Arbor, MI 48109–2029, USA.
b Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol BS8 2PR, UK.

Over the last 10 years, there are few issues that have captured the imagination of public health researchers and advocates, as has the question, whether income inequality drives population health. This was indeed a ‘big idea‘1 that attracted contributions from scholars motivated by the humanitarian potential of showing how health could be improved through greater equity and social justice.2 The question facing us now is whether this idea has had its 15 minutes of academic fame? Our own work3 and several papers recently published in the British Medical Journal prompted an editorial comment by Johan Mackenbach that ‘... evidence for a correlation between income inequality and the health of the population is slowly dissipating‘.4

It is therefore timely, that the International Journal of Epidemiology has revisited Rodgers' study5 as it was the first to directly examine links between income distribution and health, although these issues had been raised in Preston's seminal paper 4 years earlier.6 Rodgers' overall concern was to try to understand the determinants of mortality change, especially in regard to developing countries, and he presaged many of the issues which have since occupied researchers in this field. He recognized that specific factors like clean water, sanitation, food supply and health care—aspects of social infrastructure investment—were important but empirically difficult to disentangle because they tend to be highly collinear with each other and with income. That realization certainly remains salient today.7 He noted that disentangling their specific contributions was important for policy formulation, but not ‘critical for a description of mortality changes in the process of development’ (p. 343). He thus set aside the messy issues of figuring out appropriate confounders and specifying causal pathways that might link aspects of development, income, inequality and population health. Rodgers also explicated what Gravelle later referred to as the ‘artefact’ explanation,8 and showed how the curvilinear individual association between income and health will produce an apparent effect of income inequality on health at the population level. However, he was unable to directly examine this because he only used aggregate data. The issue of control for individual income has been seen as crucial by several later researchers.9–11

Rodgers examined different characterizations of the income and inequality variables in regard to life expectancy and infant mortality. Throughout the paper, Rodgers presented the most robust formulations of his statistical models, as judged by P-values and the amount of variance explained (R2 value). He was thus primarily concerned with the efficient predictive statistical functioning of the models, not whether they were causal representations. Indeed, he considered it self-evident that ‘the overall economic status of individuals is likely to dominate health changes‘5 and that there is a ‘sequence of causation which goes from income to mortality via a number of intermediate variables with which we need not necessarily concern ourselves here‘.5 He also clearly left open the possibility that associations between income inequality and health could be due to confounding by health and social services, including provision of education.12 Nevertheless, he argued that there was 5–10 years difference in life expectancy between relatively egalitarian and less egalitarian countries. And thus, the first empirical plank in the income inequality and health story was in place.

How should we interpret this in light of more recent studies about links between income inequality and health? Rodgers' study attempted to show that income inequality differences between countries, net of absolute income differences, contributed to variation in average levels of health. For international comparisons of this sort, it is now clear that results are sensitive to country selection, time periods and sources of income data. Rodgers used 56 unnamed countries with income data from different time periods, the quality of which is likely to have varied considerably. So in hindsight it is hard to know what to conclude from his analysis. Given our experiences working in this area, we would not be surprised to find that under certain data selection criteria, associations may or may not be found. Even with contemporary income data from different sources, there are uncomfortably modest correlations between income inequality measures for the same countries and same time periods. Regarding international associations, it seems we are limited to using the best data available, and our recent analyses have shown no overall association between income inequality and life expectancy, but like Rodgers, did show consistent associations with child health outcomes.3

Is there an association between income inequality and health? The evidence that income inequality affects mortality differences across richer countries is not strong, except for infant health outcomes.7 There is little evidence that the extent of income inequality, especially after adjustment for individual income, affects health within countries other than the US.4,13 The unadjusted aggregate-level association within the US seems solid, but conceptual and empirical questions remain over what constitutes appropriate confounders and pathways, at both the aggregate and individual levels.11,12 Finally, the appropriate reference group for social comparisons is unclear: if income inequality influences health through the psychological consequences of individuals perceiving themselves as being in inferior situations to other individuals, what are the groups—according to geographical proximity, age, sex, ethnicity, salience of presence—to which people compare themselves? Intriguing preliminary data suggest that choice of comparison group can influence the statistical associations between income inequality and health that are observed.14

So, which way forward? We would urge readers to consider several intersecting issues, lest we throw the ‘social inequality baby’ out with the ‘income inequality bathwater’. First, several empirical issues—such as that of appropriate social comparison reference group—have yet to be fully explored and these may change the overall evaluation of the income inequality and health literature. Second, social inequality is multidimensional —it is not limited to income differences—and is expressed in education, occupation, housing, access to services and discrimination according to ethnicity, gender and age. The interconnections between these dimensions are intricate and difficult to disentangle with the relatively crude measures we employ. Third, ‘health’ is a multidimensional construct that is not captured by death statistics—something we have under-emphasized in our previous work. While the evidence for links between income inequality and disease-specific mortality is generally weak, that does not preclude an important role for income inequality in reducing quality of life, and adding to the misery and drudgery that characterize the existence of many people living in rich and poor countries. Despite recent findings from the US15 and Japan16 not being supportive of an easily detectable influence on self-rated health or symptoms of psychological distress, it is still plausible that while income inequality, per se, may not cause cancer or stroke, it does contribute to human suffering. Fourth, income distributions come from somewhere —they are the result of particular historical, cultural, economic and political processes,17 and their influence on population health should be understood as markers of complex historical forces acting over the lifetimes of successive birth cohorts, which may not be expected to reveal themselves in cross-sectional (rather than time-lagged) correlations.18 Would anyone seriously argue that the decades of greater general social (and income) equality of the Nordic countries has had nothing to do with generating better population health profiles? This does not deny that there are cause-specific factors that generate particular variations in health between those countries, or that there are other pathways to longer national life expectancy, such as in France or Japan. But it is hard to make the case that these historical patterns of equitable social investments, via both publicly and privately held resources, have had no impact on better population health in the Nordic countries, or conversely that the systematic lack of such broad-based historical investments in the UK and US has had no impact on population health in those countries.

Finally, even if as Mackenbach suggests,4 all the research on income inequality and health has done is to help us rediscover the crucial role that individual income plays, then this remains a worthwhile lesson. Individual incomes are primarily the result of market-driven distributions and government-sponsored redistributions of income. Does income distribution affect health? Of course it does, because it affects individual incomes. For this reason alone it warrants the continuing attention of public health researchers and advocates. The fact that we can muster little evidence to show that the extent of income inequality, per se, affects population health through mechanisms other than what income inequality indexes in terms of material resources acting over the life course of individuals within populations, is not an argument against income redistribution. Redistribution works, especially in those countries like the UK and US where income deprivation is a particularly salient component of the multiple deprivations that exist in those countries. Lets take up the challenge and see how well it really does work.19

References

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