Health Inequality: An Introduction to Concepts, Theories and Methods by Mel Bartley

Health Inequality: An Introduction to Concepts, Theories and Methods by Mel Bartley

Author:Mel Bartley [Bartley, Mel]
Language: eng
Format: azw3
ISBN: 9780745691121
Publisher: Wiley
Published: 2016-12-04T16:00:00+00:00


Is income distribution related to population health?

The research on the deleterious influence of income inequality not only on health but also (and even more strongly) on other forms of social pathology has been very well summarized in Wilkinson’s book, Unhealthy Societies, and Wilkinson and Pickett’s highly influential The Spirit Level. Readers are strongly advised to consult these very wellexpressed and persuasive accounts (Wilkinson 1996; Wilkinson and Pickett 2009). The key idea is that, after a certain level of average income per person is reached in a society, additions to this average do not seem to improve that society’s health any further. This is not the same as the effects seen in the studies we have been considering of the social and economic position and circumstances (such as income, social class based on occupation, or prestige) of individuals. As far as studies are able to tell us, the health of individuals within a country seems to be better the more prestige they have acquired, and the more favourable the conditions under which they are employed. ‘Average’ levels of health within social classes, income or status groups within a country, similarly, are better the higher the average income in the group. There is no limit above which further improvement in health does not take place. By contrast, when you compare countries (as opposed to comparing groups of people within countries), it seems from many (if not all) studies that population health, as measured by life expectancy, does not continue getting better the higher the total amount of money earned by everyone in the country. Figure 7.1 shows the well-known Preston Curve that relates the annual income of the average person in a nation to the average life expectancy of that nation. Beyond a level of around $7,000 per year, income is no longer related to life expectancy.

However, in many studies it appears that even above $7,000 per year average per capita income, countries (and other geopolitical units, such as American states) do have higher life expectancy if their total amount of income is more evenly distributed. These differences in income distribution are measured in studies in several different ways. One of the ways most often used to summarize the relationship between individual incomes is the so-called Gini coefficient. Without going into the complex construction of this measure, we can look at a similar measure, the coefficient of variation, which just divides the mean (average) income in a population by its standard deviation. The standard deviation gives the average amount by which each individual’s income deviates from the average for everyone (this is not exactly how statisticians would calculate a standard deviation in a study, but it explains the general idea.).

Table 7.1 gives an imaginary example of two populations with the same average income, but with a wide range of difference between each individual income and the average. It shows how these two different populations have different coefficients of variation. Each population has five members, and the average income in both populations is $5,800 per year.



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