Sick of Inequality?
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Sick of Inequality?

An Introduction to the Relationship between Inequality and Health

Andreas Bergh, Therese Nilsson and Daniel Waldenström

There is a clear trend in rich countries that despite rising incomes and living standards, the gap between rich and poor is widening. What does this mean for our health? Does increasing income inequality affect outcomes such as obesity, life expectancy and subjective well-being? Are rich and poor groups affected in the same ways? This book reviews the latest research on the relationship between inequality and health. It provides the reader with a pedagogical introduction to the tools and knowledge required to understand and assess the issue. Main conclusions from the literature are then summarized and discussed critically.
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Chapter 5: Correlation or causality? Interpreting scatter plots and regressions

Andreas Bergh, Therese Nilsson and Daniel Waldenström

Extract

The relationship between inequality at the country level, measured as the Gini coefficient for disposable income, and health measured using life expectancy at birth can be illustrated using a scatter plot such as the one in Figure 5.1. In this graph, each dot represents a country for which inequality is measured along the x-axis and life expectancy is measured along the y-axis. The straight line in the diagram indicates the best fit. The line has a downward slope, which means that the global correlation between these variables is negative: a higher level of income inequality is associated with lower life expectancy. However, if we were to look at the situation within a specific country, we might see the opposite relationship. Using data from 21 Swedish counties, Figure 5.2 shows that life expectancy is higher in counties with a higher level of income inequality. In Sweden, roughly the same picture can be seen at the municipal level. On average, municipalities with higher levels of income inequality have higher life expectancies at birth.

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