The mother of underlying causes – economic ranking and health inequality

The mother of underlying causes – economic ranking and health inequality

This is an extract from a paper published in Social Science and medicine, available online January 10th 2015

Wilkinson and Pickett’s findings, first published on-line in 2005 have helped to reveal the strong relationships between economic inequality and poor health outcomes in affluent nations (Wilkinson and Pickett, 2006). Their initial findings are reminiscent of the early evidence that smoking among groups of doctors increased the likelihood of members of each group dying of lung cancer. The strong correlation between smoking and cancer was understood long before a specific cause was clearly outlined.

In this paper (Pickett and Wilkinson 2015), published ten year after the initial announcement of their findings, the authors bring together the beginnings of a case of there being plausible underlying biological and related casual explanations for why people in more economically unequal affluent countries suffer worse health. They suggest that ‘Inequality is increasing in most regions of the world, rapidly in most rich countries over the past three decades’. However, income inequality has increased much faster in the UK and USA than in most other affluent nations and it has fallen in some countries (Dorling, 2014).

When rich countries are compared it is clear that those societies with greater rates of economic inequality contain populations experiencing worse overall health outcomes along with a series of other poor outcomes many of which might be expected to be harmful to overall population health, such as higher rates of imprisonment, greater obesity and lower trust or more anxiety.

Here is a figure from this short paper suggesting that even the amount of walking and cycling people do in each country may, directly and indirectly, be linked to social inequalities:

Proportion of people walking or cycling as their main means of travel. Note: Each circle is a country drawn in proportion to its population. Belgium and Austria and not included because they are not in the Paris top income dataset. Sources: Paris top incomes dataset and Buehler and Pucher (2012).

Proportion of people waking or cycling as their main means of travel. Note: Each circle is a country drawn in proportion to its population. Belgium and Austria and not included because they are not in the Paris top income dataset.
Sources: Paris top incomes dataset and Buehler and Pucher (2012).