Global variations in health and mortality: evaluating the relative income hypothesis

(also see video version)http://www.cmm.bristol.ac.uk/learning-

training/videos/index.shtml

Min-Hua Jen and Kelvyn Jones School of Geographical Sciences

LEMMA, University of Bristol

Structure of talk

• The changing patterns of global life expectancy, 1970-2000?

• The relative income hypothesis as an explanation, but the problem of aggregate analysis

• Evaluating the relative income hypothesis using the World Value Survey: a combined micro and macro analysis

Key question: are there groups of countries with a similar underlying and distinctive trajectory?

INPUT (simplest possible mode) • Yij Life expectancy for time i in place j• Tij Time for occasion i in place j: 1970 to 2002• How many latent groups? Fit sequence 1, 2…• The order of the polynomial for trends; usually LE 3

OUTPUT• Polynomial trends for each group with a distinctive trajectory• BIC: a goodness of fit measure, penalized by complexity of

model; using here in a highly exploratory mode!

Latent group trajectory models

One and two group solutions

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One trajectory

Two trajectories

Latent trajectory models: global mortality

Ten group solutionG1

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So Far• Substantial differences between countries

• Evidence of growing differences between countries in recent years

• Strong ‘macro geography’eg continuing improvement in W Europe and N America;

major improvement in North Africa and the Middle East;

stagnation in the western former satellite Soviet states;major decline in the former Soviet Union.

• In search of an explanation for differences in advanced economies…………The relative income hypothesis

Relative income hypothesisDevelopment of the argument by Richard Wilkinson in

‘Unhealthy societies’ (1996) ‘Mind the gap’ (2000)• Very highly summarised here …

1 Income and health: within-country relationsAge adjusted mortality of 300k white American men by median family income;

marked negative relationship; poor die young

Relative income (continued)2: GNP and health: between-country relations

Life expectancy and GNP per capita in OECD countries, 1993In advanced economies: no relation

3 Income inequality and Health

Life expectancy and income distribution in developed countries

Most egalitarian: live longer

Relative income Summary of the argument

• In the developed world, it is not the richest countries which have the best health, but the most egalitarian (US, 1996,3)

• ‘where income is related to social status, as it is within countries, it is also related to health. Where income differences mean little or nothing for people’s position in the social hierarchy (such as those between countries) income makes little difference to health. This strongly implies that psychosocial pathways are important (MTG,2000, 10-11)

•‘Income distribution is linked to social cohesion which is turn is linked to mortality’ (US, 1996,ix)

Relative income (continued)Underlying psycho-social model

Incomeinequality

Material Circumstances

Health Inequality

Dominance Hierarchy

Gaps inSocial Status

AnxietyStress

Violence

Social CohesionSocial Capital

LifeExpectancy

SocietalStructures

Psycho-socialPathways

Outcomes

Simulated non-linear relation between income and mortality

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Individual Income

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Artificial relation between mortality and inequality

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Coefficient of variation

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Multilevel analysis

NO between country

Variation

But: The problem of aggregate analysis

Evaluating the Relative income hypothesis • Requires micro and macro analysis simultaneously

• Are there effects for income inequality (macro) after taking account of individual income (micro)

• Last ten years, dozens of studies have done this with mixed results

•But none done at the scale at which Wilkinson made the original argument: Countries

•The World Value Survey…………..have to use self-rated health; no mortality data with individual income exists on a global basis

The World Values Survey• Response: “All in all, how would you describe your state of health these days? (Good, Fair and Poor) with Good as the base.

•Structure: respondents with 4 waves (1981, 1990, 1995, 2001) in 69 countries. a representative national sample of at least 1,000 people, (not every country is included at each wave)

•Predictors-Micro: household income, age, sex and marital status -Macro: World Bank country-level income data on GDP per capita (in purchase power parity for 2004 US dollar) on an annual basis; income inequality data comes from UTIP-UNIDO project ( University of Texas)

-Modelling : 3- level (170k respondents, 4 waves, 69 countries) multilevel multinomial model fitted in MLwiN

The World Values Survey Some results• Differences between countries (after taking account of age and sex)

•13 fold difference between countries with the most and least poor health (Ukraine versus Switzerland)

Effects for Individual variables• Differences between countries

• Individual Income: non-linear ‘dose response’

Effect of inequality

• After taking account of individual income

• Above threshold:Unequal countries have lower odds of reporting poor cf good health! Essentially flat relation

• for no income group is the relation as posited by Wilkinson

Conclusions

• Substantial differences between countries in self-reported health after taking account of age and sex

• Individual income has clear effect: poorer people report worse health

•Income inequality does not have the hypothesized pattern of egalitarian societies reporting better health

• There remains substantial differences between countries even after taking account of micro and macro variables; in particular the Former Communist report high levels of poor health

• Problem of data quality…European Household Panel Survey