Self-assessed health is a better predictor of health than other health indicators

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Table of contents

I Measuring health 
1 Measures of health status 
1.1 Introduction
1.2 Health indicators: content, correlations and discrepancies
1.2.1 What is a good indicator of general health?
1.2.2 Various health indicators to measure “true” health
1.2.3 Another health indicator: the paradoxical self-assessed health
1.3 Health status measures: can we measure “true” health in a better manner?
1.3.1 Towards a correction of individual response effects
1.3.2 Why is the reporting correction advised?
1.3.3 Another solution: providing global health indicators
1.4 Conclusion
2 A new measurement of health encompassing several dimensions of health
2.1 Introduction
2.2 Aggregating several dimensions of health to measure a general and cardinal health status
2.2.1 Why is the continuous aspect desirable?
2.2.2 How can we measure a continuous health variable?
2.3 A health assessment model
2.3.1 The model specification
2.3.2 A set of demographic, socioeconomic and health-related behaviour variables
2.3.3 Using individual characteristics to correct the drawbacks of self- assessed health
2.3.4 Construction of the health index
2.4 Empirical results
2.4.1 Ordered logit models with or without cluster effects
2.4.2 Ordered logit model with cluster effects and varying thresholds
2.4.3 The continuous health indicator
2.5 Comparisons with other constructions
2.5.1 Getting continuity from an “arbitrary” distribution
2.5.2 Getting continuity by combining different health dimensions
2.5.3 Getting continuity using external information
2.5.4 Some elements of discussion
2.6 Conclusion
II Measuring inequalities in health 
3 Measures of health inequality 
3.1 Introduction
3.2 Measurement of inequality in health: orderings and rankings
3.2.1 Stochastic dominance: first and second order
3.2.2 Multidimensional welfare analysis: symmetrical attributes
3.2.3 Multidimensional welfare analysis: asymmetrical attributes
3.2.4 Orderings and rankings: some elements of conclusion
3.3 Measurement of inequalities in health in a unidimensional context: the health Gini index
3.4 Measurement of inequalities in health in a bidimensional context
3.4.1 The pseudo-Gini
3.4.2 The concentration index
3.5 Conclusion
4 Income-related inequalities in health in France
4.1 Introduction
4.2 Health in France in 2004
4.2.1 The French health care system over the last decade
4.2.2 Health in 2004: a social health gradient in France?
4.3 Measuring inequalities in health: which measurement of health should be used?
4.3.1 New approach to measurement of health in Europe: an application to French data
4.3.2 Cardinalisation of self-assessed health: a reliable health distribution in France?
4.3.3 Innovative health index: a first empirical utilisation
4.3.4 Comparisons of the alternative mappings
4.4 Measuring income-related inequality in health
4.4.1 Measurement method
4.4.2 Explaining health within a linear model
4.4.3 Global concentration indices: income-related inequality in health
4.5 Explaining income-related inequality in health
4.5.1 Measurement method
4.5.2 Concentration indices over income
4.5.3 Contribution to the income-related inequality in health
4.5.4 Legitimate or illegitimate income-related inequalities in health?
4.6 Income-related inequality in health in 1998: a comparison with 2004
4.6.1 Measurements of health in 1998
4.6.2 Data and variables
4.6.3 Explaining health within a linear model in 1998: comparisons with 2004
4.6.4 Income-related inequality in health in 1998: comparisons with 2004
4.6.5 Decomposition of inequalities in 1998: comparisons with 2004
4.7 Conclusion
5 From inequalities in health to inequalities of opportunity in health 
5.1 Introduction
5.2 Equality of opportunity in health
5.3 The French part of SHARE: a relevant tool for empirical work
5.3.1 Data and sample
5.3.2 Variables measuring social conditions
5.3.3 Variables measuring health conditions
5.4 A first approach in terms of stochastic dominance
5.4.1 Dominance according to parents’ relative longevity
5.4.2 Dominance according to social background
5.4.3 Dominance according to current socioeconomic status
5.5 A second approach using regression analyses
5.5.1 Influence of social background and parents’ relative longevity
5.5.2 Influence of social background, parents’ relative longevity and cur- rent socioeconomic status
5.5.3 Endogeneity test of the social status in adulthood
5.6 A third approach using concentration indices
5.6.1 Measurement of health: cardinalisation of self-assessed health with SF6D
5.6.2 Inequalities in health related to parents’ relative longevity
5.6.3 A pseudo health concentration index according to parents’ socioeco- nomic status
5.7 Conclusion