Bergh, Bilsson and Waldenström, Sick of Inequality?

Andreas Bergh, Therese Bilsson and Daniel Waldenström, Sick of Inequality? An introduction to the relationship between inequality and health, Edward Elgar, 2016, viii + 161 pp, 1 78536 420 4, hbk, £65

In 2010, soon after Wilkinson and Pickett published The Spirit Level, the Citizen’s Income Trust published a review essay [1] that pointed out that although Wilkinson and Pickett had shown that a correlation exists between income inequality and health, they had not proved a causal link. And now we have an entire book that asks the same question, amongst others:

How persuasive is the evidence of an inequality effect? If this effect exists, how large is it? Is the relationship causal, or are there other factors that explain why high inequality and adverse health outcomes tend [to] be associated? Does the relationship between inequality and health exist in every type of society, and what kinds of health issues are affected? Which mechanisms cause an unequal income distribution to lead to poor health? How is health affected in a society if everyone grows richer as income inequality increases? (p. 3)

Following an introductory chapter, chapter 2 asks whether health can be measured – ‘different health measures reveal different developments … health is multidimensional’ (pp. 20-21); chapter 3 asks whether inequality (generally understood in this book as income inequality) can be measured – ‘different inequality measures can produce different rankings’ (p. 33); and chapter 4 asks ‘How can economic inequality influence health?’ (p. 38), discusses ‘social structures, psychological phenomena, monetary factors, and political processes’ (p. 47), and finds that sometimes a certain level of inequality can be helpful – for instance, higher economic returns to higher levels of education can inspire people to improve their education.

The heart of the book’s argument is in chapter 5, in which the authors discuss the concepts of ‘correlation’ and ‘causality’, and tackle the question: ‘Do higher incomes lead to better health or does poor health lead to lower incomes?’ (p. 51). The authors find that natural experiments have enabled researchers to draw conclusions in both directions, they discuss the possibility that a third factor might be the cause of a correlation, and they give an account of methods for taking account of missing factors. Particularly important factors turn out to be country-specific ones: that is, ‘all invariant observed and unobserved (or unobservable) factors that distinguish countries’ (p. 65). The level of inequality related to these factors can be calculated: and when such calculations are made, we find that income inequality changes have little effect on health inequality (although GDP per capita, and the density of medical practitioners, do seem to affect health outcomes). Following a worked example, the authors draw the interesting conclusion that

to begin with, we have seen a fairly large negative correlation between income inequality and life expectancy in simple scatter plots. This correlation was reduced by one-half by accounting for differences in national income levels. However, as soon as we adjust for country-specific features that remain constant over time … there is no link whatsoever between the level of inequality and life expectancy … Increased inequality is not followed by a lower level of population health as measured in life expectancy. (p. 70)

This conclusion is not dissimilar to the conclusion in our review article that underlying social structures and processes might be affecting both income inequality and health inequality.

Chapter 6 suggests that aggregate data needs to be supplemented with individual-level data (which it recognises would be a mammoth task) if a truer picture is to emerge; and chapter 7 summarises current research (and finds that different studies come to some very different conclusions about direction of correlation and about causality, and also finds that ‘very few studies offer a proper statistical identification strategy that allows the authors to make causal interpretations of their results’ (p. 106)). Chapter 8 is a call for more research on the relationship between measures of inequality and the mechanisms by which income inequality and health might affect each other; finds that even though the Gini coefficient is generally employed to measure income inequality, different inequalities might be being measured ( – disposable income, wage income, household income, individual income, tax unit income …); and suggests that the Gini coefficient can miss important changes in inequality in parts of the population or in the whole of it. Here the authors have recognised a problem, and they suggest a solution:

that studies of the inequality effect on health should first define the relevant mechanism or mechanisms and determine how they can be detected empirically. Only then should the researcher select an appropriate measure that is able to capture these potential distributional outcomes, be it the poverty rate, top income share or, perhaps, the Gini coefficient. (p. 113) [2]

Chapter 9 sums up the authors’ findings. The conclusion?

The conjecture that people living in rich, unequal countries have worse health than people living in rich, equal countries … is not strongly supported by the data. (p. 115)


support for the notion that subjective wellbeing suffers due to societal differences in income … seems stronger than the support for the notion that we get physically sick from such differences. (p. 116)

This latter conclusion is particularly interesting because it suggests that the level of social cohesion might be a factor, and therefore that social policies designed to enhance social cohesion might improve health outcomes.

It is of course a pleasure to see a robustly researched book that confirms the hesitations expressed in our review of a book that was being enthusiastically received seven years ago. It is even more of a pleasure to be able to suggest that this book will provide a model against which all future social research will need to be tested. What we still don’t have, of course, is any proof that the suggestions made in our review, relating to deeper social structures that affect both income inequality and health inequality, have any substance. Because the suggested deeper social structures could produce inequality effects, they certainly do put in question any proposed causal link between income inequality and health inequality: but there are still no proven causal links. Perhaps there cannot be. What would of course be most interesting to see would be a constructed experiment, such as a Citizen’s Income pilot project, that changed the structure of the benefits system for a representative sample of a population, and therefore changed the deeper social structures for that sample. As the authors of this book frequently point out, long time spans are required for such experiments to produce valid results. Whether a Citizen’s Income pilot project with a sufficiently long time span might be feasible in the near future is the question that this book leaves us with.


[1] Review article: The Spirit Level, by Richard Wilkinson and Kate Pickett

[2] They might also have suggested the Palma: the ratio of the income share of the top 10% to that of the bottom 40%: