Socioeconomic inequalities in health : a picture of Brazil FIOCRUZ Rio de Janeiro June 27, 2005 Célia Landmann Szwarcwald, FIOCRUZ

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 years with incomplete fundamental education: 53%  Proportion of population living in poverty: 31%

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.

Regional Inequalities Indicator Region NNESESCW % population years old with incomplete fundamental education % population living in poverty Total fertility rate Infant mortality rate (/1000 LB) % Deaths with undefined cause % Deaths by infectious diseases % Under Reported Deaths

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

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

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

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.

Favela Rio de Janeiro

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

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

Socioeconomic and Health Indicators. Municipality of Rio de Janeiro IndicatorHarbor Area (Northeast) Coast Area (South) Gini Coefficient Poverty Rate % Illiterate Mean income % Slum Residents Life Expectancy Homicide Rate Standardized Mortality Rate Infant Mortality

Income inequality and Health inequality Methodological Problems

Income distribution - Simulation 1

Income Distribution - Simulation 2

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

Infant mortality rate by income deciles DecilesSimulation 1Simulation ,6 12,4 11,4 10,5 9,8 9,2 8,6 8,0 7,4 6,2 27,3 19,4 16,3 13,9 12,2 10,8 9,4 8,2 6,9 4,9

World Health Survey Brazilian Results

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

Self rated health state by educational level

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

Proportion(%) of good self-rated health by age group, sex, and educational level Sex Age grou p Educational Level Total Incomplete fundamental education Incomplete intermediate education Complete intermediate education F Total M Total ,2

 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. Methods - SES

Logistic Regression Results Independent variable FemalesMales Exp (b) P- value Exp(b) P- value Age Indicator of household assets EducationIncomplete fundamental education Incomplete intermediate education Complete intermediate education NS - Work situation Non manual worker Manual worker Housewife Unemployed Retired or unable to work NS Response Variable: Good self-rated health

Proportion (%) of individuals that answered severe or extreme degree of problems 1.Animus Status 5.Vision 2.Pain/Disconfort 6.Interpersonal Activities 3. Sleep/Energy 7. Mobility 4. Cognition 8. Self Care Percent (%) % 18% 17% 14% 10% 6% 3%

Logistic Regression Results Independent variable FemalesMales Exp (b) P- value Exp(b) P- value years old years old years old NS NS Has long-duration disease or disability Has bodily injury Indicator of household assets0.953NS Incomplete fundamental education Incomplete intermediate education NS Married0.863NS Unemployed Response Variable: Intense degree of sadness or depression

Logistic Regression Results Independent variable FemalesMales Exp (b) P- value Exp(b) P- value years old years old years old NS NS Has long-duration disease or disability Has bodily injury Indicator of household assets0.935NS Incomplete fundamental education Incomplete intermediate education NS Married1.011NS0.889NS Unemployed Response Variable: Severe degree of worry or anxiety

 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. WHS Results - Socioeconomic inequalities in health state

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.