socioeconomic inequalities in health : a picture of brazil fiocruz rio de janeiro june 27, 2005...
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Socioeconomic inequalities in health : a Socioeconomic inequalities in health : a picture of Brazilpicture of Brazil
FIOCRUZFIOCRUZ
Rio de Janeiro June 27, 2005Rio de Janeiro June 27, 2005
Célia Landmann Szwarcwald, [email protected]
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%
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
IndicatorRegion
N NE SE S CW
% population 15-49 years old with incomplete fundamental education
63 66 46 49 54
% population living in poverty 39 54 20 19 27
Total fertility rate 2.9 2.5 1.9 1.8 2.0
Infant mortality rate (/1000 LB) 27 38 17 16 19
% Deaths with undefined cause 21.6 26.8 9.2 6.3 6.6
% Deaths by infectious diseases 11.9 12.8 7.1 6.4 8.8
% Under Reported Deaths 28 31 9 5 12
Infant Mortality Rate (/1000 LB) by State. Brazil, 2000
Source: RIPSA -IDB 2002
< 2020 - 3030 – 40>= 40
Infant Mortality Rate
Infant buried in the household backyard Infant buried in the household backyard rural area of Barras (PI - Northeast)rural area of Barras (PI - Northeast)
Infant buried in the household backyard Infant buried in the household backyard Urban area of Barras (PI - Northeast)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.
FavelaRio de Janeiro
Geographic Distribution by Socioeconomic Status. Municipality of Rio de Janeiro
LEGENDHarbor AreaWest AreaCoast AreaSlums
Geographic Distribution of the homicide rate (/100,000) among men aged 15-49 years old. Municipality of Rio de Janeiro
Legend<= 100.0100.1 – 170.0> 170.0
Socioeconomic and Health Indicators. Municipality of Rio de Janeiro
Indicator Harbor Area (Northeast)
Coast Area (South)
Gini Coefficient
Poverty Rate
% Illiterate
Mean income
% Slum Residents
0.61
22.70
10.17
3.10
30.69
0.45
6.21
4.10
12.50
12.40
Life Expectancy
Homicide Rate
Standardized Mortality Rate
Infant Mortality
64.01
211.17
11.23
26.00
73.25
72.08
6.39
17.52
Income inequality and Health inequalityIncome inequality and Health inequalityMethodological ProblemsMethodological Problems
Income distribution - Simulation 1
Income
2019181716151413121110987654321
Lognormal Distribution:Mean=5.0; Std Dev=2.62500
2000
1500
1000
500
0
Income Distribution - Simulation 2
Income
2019181716151413121110987654321
Lognormal Distribution: Mean=5.0; Std Dev=6.82500
2000
1500
1000
500
0
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
Simulation 1
Income (Mean=5.0; Std Dev=2.6)
4035302520151050
Infa
nt
Mo
rta
lity
Ra
te
70
60
50
40
30
20
10
0
Infant Mortality Rate
Simulation 2
Income (Mean=5.0; Std Dev=6.8)
4035302520151050
Infa
nt
Mo
rta
lity
Ra
te
70
60
50
40
30
20
10
0
Infant mortality rate by income deciles
Deciles Simulation 1 Simulation 2
1
2
3
4
5
6
7
8
9
10
14,6
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
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
Ed
uca
tion
al L
evel
Incomplete Fundamental
Education
Incomplete Intermediate
Education
Complete Intermediate Education +
1009080706050403020100
very good
good
moderate
bad
very bad
9% 32% 45% 14%
18% 44% 32% 6%
23% 49% 25%
3%
Proportion (%) of good self-rated health according to monthly household expenditure. Brazil, 2003
Gasto domiciliar total
70006000500040003000200010000
Au
to-a
valia
ção
bo
a
1,0
,8
,6
,4
,2
0,0
Source: WHS, Brazil, 2003.
Proportion(%) of good self-rated health by age group, sex, and educational level
SexAge grou
p
Educational Level
TotalIncomplete fundamental
education
Incomplete intermediate
education
Complete intermediate
education
F 18-29 51.5 64.0 75.9 64.7
30-44 39.6 54.4 73.2 52.5
45-59 25.2 39.7 51.8 32.2
60+ 22.2 33.3 36.7 24.1
Total 33.9 55.1 69.4 47.5
M 18-29 65.8 78.4 83.0 75.2
30-44 57.8 65.3 76.8 64.9
45-59 45.3 61.5 68.5 53.1
60+ 27.9 45.8 45.1 31.4
Total 49.4 69.8 75.3 60,2
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 workersHousewife; 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 variableFemales Males
Exp (b)P-
valueExp(b)
P-value
Age 0.9681 0.000 0.9679 0.000
Indicator of household assets 1.3460 0.000 1.1765 0.008
Education Incomplete fundamental educationIncomplete intermediate educationComplete intermediate education
0.47630.65661.0000
0.0000.006
-
0.71020.98481.0000
NSNS-
Work situation
Non manual workerManual workerHousewifeUnemployedRetired or unable to work
1.00000.88410.86160.94580.7010
-NSNSNSNS
1.00000.5474
-0.58610.4524
-0.000
-0.0110.000
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
Per
cent
(%
)30
25
20
15
10
5
0
2 3 4 5 6 7 81
25%
18%17%
14%
10% 10%
6%
3%
Logistic Regression Results
Independent variableFemales Males
Exp (b)P-
valueExp(b)
P-value
18-29 years old30-44 years old45-59 years old
0.6510.8891.026
0.017NSNS
0.4800.7760.981
0.007NSNS
Has long-duration disease or disability 2.249 0.000 4.004 0.000
Has bodily injury 1.966 0.000 2.030 0.000
Indicator of household assets 0.953 NS 0.839 0.026
Incomplete fundamental educationIncomplete intermediate education
2.2211.754
0.0000.002
1.1281.429
NSNS
Married 0.863 NS 0.606 0.006
Unemployed 1.484 0.023 2.129 0.000
Response Variable: Intense degree of sadness or depression
Logistic Regression Results
Independent variableFemales Males
Exp (b)P-
valueExp(b)
P-value
18-29 years old30-44 years old45-59 years old
0.7410.9941.184
NSNSNS
0.5320.9420.957
0.007NSNS
Has long-duration disease or disability 1.923 0.000 3.084 0.000
Has bodily injury 1.727 0.000 1.929 0.000
Indicator of household assets 0.935 NS 0.928 0.026
Incomplete fundamental educationIncomplete intermediate education
1.6101.407
0.0000.024
1.1031.227
NSNS
Married 1.011 NS 0.889 NS
Unemployed 1.357 0.026 2.602 0.000
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.