Prepared for the International Conference on Health in the African Diaspora—ICHAD 2012 July, 2012
Afro-descendants in Latin America and challenges of measuring health gaps Luana Marques G. Ozemela Judith Anne Morrison Brittney Elise Bailey Josh Colston
Gender and Diversity Division (GDI) Inter-American Development Bank
Outline
Motivation Data Used Methodology Findings Suggestions for future research
Motivation
Race impacts health outcomes
Indirect channels
Direct channels
• Higher exposure to health damaging factors • Social vulnerability • Aggravated consequences of illness on socio-economic condition
• Genetic predisposition or aggravated/difficult treatment • Deprivation of access to health care • Unequal treatment
Race health gaps have an economic cost Negative impact on current and future generation’s health Loss in current and future earnings/income
Lower incentives to make health investments (fewer preventive consultations) Higher rates of stress, depression, or other mental problems associated to poorer access to health care. Higher pressure in public services such as public health care and social protection programs
Methodology and Data
Questions we wanted to explore 1. What is the magnitude of race and ethnic inequalities in health? 2. Are these inequalities persistent after controlling for differences in socio-economic condition? 3. Have race-related inequalities narrowed or widened over time?
Planned Approach 1. 2. 3. 4.
Define race category groups Define health outcome variables Define socio-economic condition variables Estimate race differences and calculate statistical significance of differences 5. Estimate differences and calculate statistical significance after controlling for socio-economic condition 6. For analysis overtime, repeat the previous steps using a comparable dataset (same race question and categories, health outcome and socio-economic condition variables)
Planned Variables Self-assessed health status Fertility
Administrative data
Antenatal care Infant mortality Maternal mortality
+
Chronic condition Access to services
Attained education
Sample survey data
Data used covers more than 95% of Afrodescendants living in LAC
* The analysis excluded Chile, Venezuela, Paraguay, Mexico, El Salvador, Bolivia and Argentina due to lack of microdata from Household Surveys including a question to identify the Afro-descendant populations. Source: Inter-American Development Bank (2012). “Ethnic Group Identification in Household Surveys Released Between 2000 and 2011� , anticipated technical note includes household survey and census data for 21 countries
Information actually available and used Brazil
Colombia
Two datasets with same race question . and categories Variables Available
.
Self-assessed health status
.
Ecuador
Peru .
Antenatal care Infant mortality
.
Maternal mortality
.
.
.
.
.
.
.
.
.
Prevalence of chronic condition Access to services Attained education
.
Data Used
Brazil – Pesquisa Nacional por Amostra de Domicilio Brazil –Administrative Data Colombia - Encuesta Nacional de Calidad de Vida Ecuador - Encuesta de Condiciones de Vida Peru - Encuesta Nacional de Hogares
Note: MICS (Multiple Indicator Cluster) , DHS (Demographic and Health) and national health surveys have not yet included afrodescendant categories.
Quality of race data in surveys % Afro-descendant population by country
Brazil
Ecuador
Peru
a b c d
Census
Latest Household Survey
50.8%
51.1%
• •
Parda (brown) Preta (black)
10.6%
8.5%
• • • •
Raizal del archipiélago Palenquero Negro Mulato (afrodescendiente)
7.2%
4.5%
• • •
Negro Mulato Afroecuatoriano
• • •
Negro Mulato Zambo
a
Colombia
Categories
b
c
d
n/a
1.9%
African Descendants
National Census (2010) / Pesquisa Nacional por Amostra de Domicilio (2009) National Census (2005) adjusted for pop growth/ Encuesta Nacional de Calidad de Vida (2010) National Census (2010) / Encuesta de Empleo, Desempleo y Subempleo (2010) National Census (2007) adjusted for pop growth / Encuesta Nacional de Hogares (2010)
Sample weights in use in all datasets
Findings
Ecuador
Access to health service Reason for not seeking service, % by race/ethnicity 50 45 40 35 30 25 20 15 10 5 0 Minor case (of sickness)
Lack time
Distance from Health Facility Blancos/Mestizos
Costs Afrodescendientes
Source: Encuesta Nacional de Condiciones de Vida (2006)
Ecuador
Poor service
Other
Differences after controlling for education
The race gap between those who consider health costs as a primary reason for not seeking medical attention: Urban areas: gap falls as education level increases social class? Rural areas: gap increases as education level increases discrimination?
Costs as primary reason, by education level and geography 70 60
50 40 30 20 10 0 Urban
Urban- Primary
*Urban-Second. Blancos/Mestizos
Source: Encuesta Nacional de Condiciones de Vida (2006)
Ecuador
Rural Afrodescendientes
*Rural-Primary
Rural- Secondary
Fertility and Infant Mortality Rates Blanco, Mestizo
Negro, Mulato
Age-specific fertility rate
250.0 200.0 150.0 100.0 50.0 0.0 14-19
20-24
25-29
30-34 35-39 Age group
Blanco, Mestizo Births 223,727 Infant deaths 2,394
Ecuador
40-44
45-49
Negro, Mulato 17,484 111
Infant mortality rate
10.7
6.3
Total fertility rate
2.5
3.3
General fertility rate
75.9
102.8
Colombia
Self-Assessed Health Status White/Mestizo
Afro-descendants
70
60 50 40 30 20 10 0 Very Good Source: Encuesta de Calidad de Vida (2010)
Colombia
Good
Regular
Bad
Colombia Source: Encuesta de Calidad de Vida (2010)
Departments
CHOCO
ARCHIPIELAGO
VALLE DEL CAUCA
NARIﾃ前
BOLIVAR
PUTUMAYO
CESAR
14
12
10 80
70
8 60
6 50
40
4 30
2 20
10
0 0
% Afro-descendants
%White/Mestizo wih poor health
ANTIOQUIA
Total
LA GUAJIRA
CORDOBA
CAUCA
RISARALDA
META
BOGOTA D.C
AMAZONAS
CUNDINAMARCA
%Afro wih poor health
SANTANDER
MAGDALENA
SUCRE
ATLANTICO
ARAUCA
TOLIMA
CAQUETA
HUILA
CASANARE
NORTE DE SANTANDER
BOYACA
QUINDIO
CALDAS
% reporing poor health status
Self-Assessed Health Status, by state %Afro-descendants 100
90
Preventive Consultations (at least once yr) White/Mestizo
Afro-descendant
50 45 40 35 30 25 20 15 10 5 0 Physician
Dental
Source: Encuesta de Calidad de Vida (2010)
Colombia
Physician and Dental
None
State Name
CHOCO
ARCHIPIELAGO
VALLE DEL CAUCA
NARIﾃ前
BOLIVAR
%Afro with no consultation
PUTUMAYO
CESAR
ANTIOQUIA
LA GUAJIRA
CORDOBA
CAUCA
RISARALDA
META
%White/Mestizo with no consultation
BOGOTA D.C
AMAZONAS
CUNDINAMARCA
SANTANDER
MAGDALENA
SUCRE
ATLANTICO
ARAUCA
TOLIMA
CAQUETA
HUILA
CASANARE
NORTE DE SANTANDER
BOYACA
QUINDIO
CALDAS
% with no preventive consultations
Lack of preventive consultations, by State % Afro
100 100
90 90
80 80
70 70
60 60
50 50
40 40
30 30
20 20
10 10
0 0
Peru
Access to health services (2003) White/Mestizo
Afro-Peruano
80
Percentage of respondents
70 60 50 40 30 20 10 0 Costs
Distance to Trust Not Needed Unbelief in Home Health Facility medicine medication Reasons for not going to doctor to solve the problem
Source: ENAHO (2003)
Peru
No insurance
Access to health services (2010) White/Mestizo
80
Afro-Peruano
Percentage of respondents
70 60 50
40 30 20 10 0 Costs
Peru
Distance to Lack Time Trust Not Home No Health Needed Remedies insurance Facility Reasons for not going to doctor to solve problem
Source: ENAHO (2010)
Poor Service
Other
Fertility and Infant Mortality Rates Blanco, Mestizo
Negro, Mulato
Age-specific fertility rate
450 400 350 300
250 200 150 100 50 0 14-19
20-24
Births Infant deaths
30-34 35-39 Age group
40-44
45-49
Blanco, Mestizo Negro, Mulato 742,416 30,950 n/a n/a
Infant mortality rate
n/a
n/a
Total fertility rate
6.1
7.2
177.0
215.3
General fertility rate
Peru
25-29
Brazil
The debate on black-mixed disaggregation (from labor economics literature) There is racial ambiguity among afro-descendants where “whiter” responses reflect individual’s economic ambitions (Lovell 1994) Little difference in the socio-economic condition of blacks and mixed individuals (Silva 1978; Lovell 1998; Arcand & D’Hombres 2004; Ozemela 2012) Severe discrimination is faced by blacks compared to mixed individuals (Arcand & D’Hombres 2004; Ozemela 2012)
Identification in live biths Live Births
Total
White
Preto + Mixed
Preto
Mixed
Sample Survey (Selfidentification)
2,576,803
1,108,656
1,459,744
201,478
1,258,266
Administrative data (identification by health personnel)
2,715,143
1,284,697
1,432,013
46,086
1,385,927
0.98
0.23
Ratio A/S
1.05
1.16
1.10
Sistema de Informações sobre Nascidos Vivos–2009 Pnad 2009
•
Aggregation is needed to avoid racial ambiguity in classification in Surveys and Administrative data.
•
Aggregation is problematic if one wishes to identify those mostly affected by discrimination in health.
Fertility and Infant Mortality Rates, PNAD Branco, asiatico
Preto
Pardo
Age-specific fertility rate
120.0
100.0 80.0 60.0
40.0 20.0 0.0 14-19
20-24
25-29
30-34
35-39
40-44
45-49
Age group
Births Infant deaths Infant mortality rate
Brazil
Total fertility rate General fertility rate
White and Black & Asian Black Mixed Mixed 1,110,413 202,140 1,263,673 1,465,813 10,830 1,656 15,167 16,823 9.8
8.2
12.0
11.5
1.4
1.7
1.7
1.7
42.5
52.6
54.3
54.1
Maternal mortality rate and education 800
Mortality Rate per 100 000 live births
700
600 White
Mixed
Black
500
400
300
200
100
0
< 3 years
4-7 years Years of Education
Source: DATSUS 2011
Brazil
> 8 years
Trends in marternal mortality Maternal Mortality Rate per 100 000 live births
450
Black
400 350 300
> 12 years education (black)
250 200 150
Mixed 100 < 3 years education (all races) 50 0 1990 Source: DATASUS
Brazil
White > 12 years education (all races) 2001
2010
2015
Suggestions for Future Research/Policy
Mapping Race Health Gaps in LAC
Coverage
• • • •
Quality
Aggregation
Indicators
Gaps
What are the determinants of the race health gaps? What territories are most affected? What is the role of discrimination in the access to health? What are the economic costs involved in the expansion in the access to health care of excluded populations? • What are the economic benefits?
Challenges with data
Household surveys are one of the richest sources of information for national socio-economic statistics, however…
They lack health and ethnicity data Limited information on basic health outcomes (antenatal care, access to health services, among others) Difficult to find race/ethnicity and health data available in consecutive surveys making it difficult to draw comparisons or establish trends.
The quality of sample estimates need further attention or analyses drawn from indicators derived from HH surveys may be unreliable.
Afro-descendant sample size too small to capture certain health outcomes or to run multivariate analysis, in some cases
Disaggregation within race/ethnic groups need to be evaluated country by country.
Suggestions for Policy: Improve coverage and quality of race data in existing sample surveys Include afro-descendant categories in all health surveys such as MICS, DHS and national health surveys Improve administrative records of health establishments to collect race/ethnicity data. Develop a national system of indicators to monitor the Afrodescendant population’s health. Evaluate the impact of universal health interventions on the health of the African descent Develop surveys and pilot studies to monitor the compliance of health institutions with non-discriminatory standards of care
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Background Slides
Cause of death not investigated/disclosed Percentage of cases not investigated Region White
Black
Mixed
Total
North
26%
54%
33%
33%
Northeast
27%
39%
26%
28%
Southeast
8%
11%
10%
9%
South
6%
-
9%
6%
Center West
23%
38%
17%
22%
National
13%
25%
22%
19%
Source: MS/SVS/DASIS - Sistema de Informações sobre Mortalidade – SIM 2011
Brazil
Vulnerability to maternal mortality Death outside a health inditution
512
Race/color black
412
< 3 years education
120
Northeast
70
National
59
0
100
200
300
400
500
Maternal Mortality Rate (per 100 000 live births) Source: DATASUS 2011
Brazil
600
Maternal mortality ratio per 100,000 live births
Brazil and the top 8 worse Latin American countries 450 400 350 300
250 200 150 100
50 0
Brazil and the top 8 worse LAC countries Source: United Nations Statistics Division - Millennium Development Goals Indicators latest year available MS/SVS/DASIS - Sistema de Informações sobre Mortalidade – SIM 2011
Brazil
Maternal deaths in 2010 by race/color Total Number of Live Births
Total Number of Deaths
Region White
North
Black
Mixed
Total
White
Black
Mixed
Total
45 394
2 094
246 229
293 717
27
13
138
178
Northeast
136 071
9 315
634 987
780 373
96
64
383
543
Southeast
673 158
23 047
379 785 1 075 990
265
80
228
573
South
339 757
7 465
20 709
367 931
154
11
23
188
87 784
2 018
107 330
197 132
53
13
59
125
1 282 164
43 939
1 389 040 2 715 143
595
181
831
1 607
Center West National
Source: MS/SVS/DASIS - Sistema de Informações sobre Mortalidade – SIM Black = Preto Mixed = Pardo White = Branco
Brazil
Race-sensitive projects IDB (Afrodescendant populations’ health) Loan to Rio de Janeiro State (Brazil): Youth at Risk – Sexual and reproductive health to prevent adolescent pregnancy
Loan to Rio Grande do Sul State (Brazil): Youth Violence Prevention – Control and prevention of violence to curb the rise in homicide rates among youth
Supporting the Health Sector Reform (Ecuador) – Race sensitive review program for training of health care personnel
Loan to (Honduras): Social Protection Network Program – Development of a health services outreach model to expand access of geographically isolated populations