Socioeconomic inequalities in health : a picture of Brazil

1. Socioeconomic inequalities in health : a picture of Brazil FIOCRUZ Rio de Janeiro June 27, 2005 Célia Landmann Szwarcwald, FIOCRUZ celials@cict.fiocruz.br

2. Socio-Demographic Context • Brazilian population: 170 million inhabitants • Life expectancy at birth: 69.0 • Infant mortality rate: 25/1000 LB • Total fertility rate: 2.2 • Percentage of urban population: 84 % • Percentage of individuals aged 15-49 years with incomplete fundamental education: 53% • Proportion of population living in poverty: 31%

3. Socio-Demographic Context • The country is politically and geographically divided into 5 distinct macro-regions: North, Northeast, Southeast, South and Center-West • Each region has its own physical, demographic and socioeconomic aspects. • The North and the Northeast have the lowest socioeconomic development. • The Southeast is the most important region economically and concentrates 44% of the Brazilian population.

4. Regional Inequalities

5. Infant Mortality Rate (/1000 LB) by State. Brazil, 2000 Infant Mortality Rate < 20 20 - 30 30 – 40 >= 40 Source: RIPSA -IDB 2002

6. Infant buried in the household backyard rural area of Barras (PI - Northeast)

7. Infant buried in the household backyard Urban area of Barras (PI - Northeast)

8. Income Inequality • Brazil has extreme disparities in the income distribution. • The income share of the upper decile is 47% while the income share of the poorest decile is only 1%. • Inequalities in health within the country are related to the enormous concentration of poverty and very poor living standards of great part of the Brazilian population. • In the metropolitan areas, poor people concentrate in deprived communities (slums). These low-income communities are generally characterized by lack of basic infrastructure services, inadequate housing, and excessive crowding.

9. Favela Rio de Janeiro

11. Geographic Distribution by Socioeconomic Status. Municipality of Rio de Janeiro LEGEND Harbor Area West Area Coast Area Slums

12. Geographic Distribution of the homicide rate (/100,000) among men aged 15-49 years old. Municipality of Rio de Janeiro Legend <= 100.0 100.1 – 170.0 > 170.0

13. Socioeconomic and Health Indicators. Municipality of Rio de Janeiro

14. Income inequality and Health inequalityMethodological Problems

15. Income distribution - Simulation 1

16. Income Distribution - Simulation 2

17. Log-Log model Ln (y) = Ln (20) – 0.5 Ln (x/5) y = Infant Mortality Rate (/1000 LB) x = Income

20. Infant mortality rate by income deciles

21. World Health Survey Brazilian Results celials@cict.fiocruz.br

22. Methods • The sample size was 5000 adults (aged 18+ years old). • Self-evaluation of health state: In general, how would you rate your health today?

23. Incomplete Fundamental Education 9% 32% 45% 14% Incomplete Intermediate Education 18% 44% 32% 6% Educational Level very good good Complete Intermediate Education + 23% 25% 49% moderate bad 3% very bad 0 10 20 30 40 50 60 70 80 90 100 Self rated health state by educational level

24. Proportion (%) of good self-rated health according to monthly household expenditure. Brazil, 2003 Source: WHS, Brazil, 2003.

25. Proportion(%) of good self-rated health by age group, sex, and educational level

26. Methods - SES • To examine socioeconomic inequalities in health state, three variables were considered: • Index of household assets; • Weighted sum of household assets, where each weight is the complement of the asset relative frequency. • Educational level (incomplete fundamental education; incomplete intermediate education; complete intermediate education and more) • Work situation • Manual and non manual workers • Housewife; unemployed; unable for work • Logistic regression models were used to analyze socio-economic inequalities in self perception of health, controlling by age and sex.

27. Logistic Regression Results Response Variable: Good self-rated health

28. 30 25 20 Percent (%) 15 10 5 0 1 2 4 5 6 7 8 3 Proportion (%) of individuals that answered severe or extreme degree of problems 25% 18% 17% 14% 10% 10% 6% 3%

29. Logistic Regression Results Response Variable: Intense degree of sadness or depression

30. Logistic Regression Results Response Variable: Severe degree of worry or anxiety

31. WHS Results - Socioeconomic inequalities in health state • The results of the analysis indicated a pronounced social gradient: among women, incomplete education and material deprivation were the most contributing factors for deterioration of health perception; among men, besides material deprivation, the work related indicators (manual work; unemployment; work retirement or incapacity) were also important determinant factors. • Overall 25% reported animus status related problems. Unemployment was a very strong determinant of severe degree of depression and anxiety feelings, for both males and females. • The large prevalence of animus status problems is probably influenced by the actual socioeconomic context. Besides the problems resulting from the high income inequality, the persistent unemployment rate has increased social exclusion.

32. Conclusions • Although many health policies have been implemented to mitigate effects of poverty, the strong heterogeneity of health state in the country still reflects the adverse socioeconomic conditions. • The health inequality is expressed at different geographic levels, from macro-regional differences to intra-state and intra-city variations. • At some geographic levels, absolute poverty is the key explanatory variable. For variation within metropolitan areas, residential poverty clustering seems to be the most important factor. • Monitoring health inequalities in Brazil is a must for health system performance assessment. Not only because equity is one of the principles that rules the Brazilian health system (SUS), but also because we believe it is possible to reduce health inequalities through effective actions. • However, considering only individual socioeconomic determinants is not enough. Our challenge is to consider social and organizational characteristics of communities that are important to understand health differences, and which are not completely explained by the aggregated individual characteristics.