Income inequality and health

1. Income inequality and health S V Subramanian Harvard School of Public Health Acknowledgements: Ichiro Kawachi January 6, 2006 PURE Steering Committee and Operation Meeting Dubai, UAE

2. Income inequality: some facts S V Subramanian

3. World inequality S V Subramanian Source: UNDP, 2005, Human Development Report

4. World inequality trend Source: Milanovic B, World Apart: international and world inequality S V Subramanian

5. What is driving global income inequality? • Largely between-country (rather than within-country) • BUT, within country contribution not trivial • Of the 73 countries for which data are available, 53 (80% of the world’s population) have seen inequality rise, while only 9 (4% of the population) have seen it narrow. S V Subramanian

6. Income distribution in the US S V Subramanian

7. Is this news? Sources: 1947-79: Analysis of U.S. Census Bureau data in Economic Policy Institute, The State of Working America 1994-95 (M.E. Sharpe: 1994) p. 37.; 1979-2001: U.S. Census Bureau, Historical Income Tables, Table F-3 S V Subramanian

8. S V Subramanian

9. So what? • Economic residential segregation • Crime and rising prison population • Drag on economic growth • Erosion of social cohesion • Worse health status? S V Subramanian

10. Income and health: a typology • Absolute or Relative • Individual or Community S V Subramanian

11. Income and health: absolute and individual interpretation • Where hi is an individual’s level of well-being (for example, years of life), and yi refers to that individual’s own level of income. • The relationship between individual income and individual health is concave, i.e., a $ increase is accompanied by relatively small or even no improvement in health, beyond a particular level of income. S V Subramanian

12. y2 Health y1 x1 x2 x x3 x4 Income Concavity effect S V Subramanian

13. Income and health: relative and individual interpretation • Inspired by the concept of relative deprivation formulated by Runciman (1966). It is “the extent of the difference between the desired situation and that of the person desiring it”. • “…we can roughly say that A is relatively deprived of X when (i) he does not have X, (ii) he sees some other person or persons, which may include himself at some previous or expected time, as having X (whether or not this is or will be in fact the case), (iii) he wantsX, and (iv) he sees it as feasible that he should have X.” (Runciman 1966) (p.10)” S V Subramanian

14. Income and health: relative and individual interpretation • Where health of an individual is a function of the term (yi-yr ) that denotes the relative gap between an individual’s income, yi, and the income of some reference population, yr . The reference population could be the income of co-workers, neighbors, or the national population. S V Subramanian

15. Income and health: absolute and community interpretation • Health of an individual i in community j is a function of their own income (yij) AND the average income levels of community (Yj) in which the individuals reside. S V Subramanian

16. Income and health: relative and community interpretation • Where Ij refers to a summary measure of income distribution (e.g., Gini coefficient) for the community in which the individual resides. S V Subramanian

17. Pollution effect Life expectancy Effect of income redistribution Income S V Subramanian

18. Income inequality hypothesis:intrinsically multilevel Health of an individual in a community Community Income inequality IndividualAbsolute income IndividualRelative income Community Absolute income For substantive and technical reasons, we need a multilevel regression approach to estimate the above. S V Subramanian

19. What does the evidence using multi-level data-sets suggest? S V Subramanian

20. Detectable patterns in US studies • Positive studies • US states • Wide range of outcomes • Larger samples • Null studies • US counties/metropolitan areas • Smaller samples S V Subramanian

21. OR for Gini based on 0.05 (5%) change in Gini; Note: All models additionally controlled for individual age, sex, marital status, race, years of education, covered by health insurance and state median income.  *The equivalized household income categories were as follows: above $75,000: reference, $50,000-75,000, $30,000-50,000, $15,000-30,000, below $15,000. S V Subramanian

22. OR for Gini based on 0.05 (5%) change in Gini S V Subramanian

23. Detectable patterns in non-US studies • Mostly null, BUT • ALL countries studied thus far are FAR more egalitarian (Sweden, Denmark, Japan, UK) than the US • ALL countries studied are also centralized states, thus raising the issue related to the relevance of a chosen unit of aggregation • Is US an exception; what about societies more unequal than the US? S V Subramanian

24. Income inequality and health in Chile Source: Subramanian et.al., 2003 S V Subramanian

25. Income inequality and health in India Source: Subramanian, Kawachi, Davey Smith (Unpublished) S V Subramanian

26. Mechanisms linking income inequality and health • Access to material resources • Relative comparisons • Social cohesion and social capital S V Subramanian

27. Evidence for RD explanation? • Defining reference groups using combinations of state, race, education, and age, Eibner and Evans (2005) found that high relative deprivation is associated with a higher probability of death, self-reported limitations, body mass index, risky health behaviors, and poor self-reported health. • No association between state mean income and the probability of death • One standard deviation (0.022) increase in the Gini coefficient is associated 8 percent increase in the probability of death. • Gini coefficient AND the relative deprivation measure positively related to mortality, but RD attenuates the coefficient associated with Gini. S V Subramanian Eibner CE, Evans WN. Relative deprivation, poor health habits and mortality. Journal of Human Resources. 2005;40(3):591-620.

28. For better or for worse the Gini is out of the bottle…. If recent global and national economic trends provide any indication, research on income inequality and its potential effects on health will probably be more, and not less, important. S V Subramanian

29. FOR (in the US) Source: Subramanian, Kawachi, 2004 S V Subramanian

30. AGAINST (in the US) Source: Subramanian, Kawachi, 2004 S V Subramanian

31. Outside of the US Source: Subramanian, Kawachi, 2004 S V Subramanian

32. Gini coefficient • Most popular measure of inequality developed by the Italian statistician Corrado Gini (1912). • Typically used to measure income inequality, but can be used to measure distribution on any space. • The Gini coefficient is a number between 0 and 1, where 0 corresponds with perfect equality (where everyone has the same income) and 1 corresponds with perfect inequality (where one person has all the income, and everyone else has zero income). • Algebraically, the Gini is defined as half of the arithmetic average of the sum of the absolute differences between all pairs of incomes in a population, normalized to mean income. S V Subramanian

33. Lorenz curve • Developed by Max O Lorenz (1905) as a graphical representation of income distribution. • Portrays observed income distributions and compares this to a state of perfect income equality. • Graphical expression of verbal statements such as, "the bottom twenty percent of all households have ten percent of the total income“. • Shows, for the bottom x% of households, the percentage y% of the total income which they have. Typically, the percentage of households is plotted on the x-axis, the percentage of income on the y-axis. • The Lorenz curve is used to calculate the Gini coefficient. S V Subramanian

34. Lorenz & Gini Ratio of the area between the line of perfect equality and Lorenz curve is {A}, and the area underneath the Lorenz curve {B}. Expressed as a percentage or as the numerical equivalent of that percentage, which is always a number between 0 and 1. Line of equality {A} Lorenz curve {B} Gini index = A/(A+B) S V Subramanian