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Disentangling Poverty and Place of Residence for Family Planning Strategic Planning
1. Disentangling poverty and
place of residence
for family planning strategic planning
Karen G. Fleischman Foreit
MEASURE Evaluation PRH
Achieving Equity in Family Planning
2. Equity begins and ends with measurement
Who shows the disparities?
How big are the disparities?
How do we know that our interventions are
reaching the people with the disparities?
How do we know if we have made an impact?
Achieving Equity in Family Planning
3. Who is poor?
Relative poverty
• Wealth quintiles, usually derived from
household assets
Absolute poverty
• Defined against some standard of income
and/or expenditures
Achieving Equity in Family Planning
4. Urban-rural differences are common
30 Rural
Urban
25
% Using Modern FP
20
15
10
5
0
Achieving Equity in Family Planning
5. …as are differences by wealth quintile
30 Bottom quintile
Top quintile
25
% Using Modern FP
20
15
10
5
0
Achieving Equity in Family Planning
6. But residence and wealth go together
Kenya 2003
30% Urban Rural
% Interviewed women
20%
10%
0%
Bottom 2nd 3rd 4th Top
Wealth Quintile
Achieving Equity in Family Planning
7. …making it hard to interpret differences
Kenya 2003
30% Urban Rural
% Interviewed women
20%
10%
0%
Bottom 2nd 3rd 4th Top
Wealth Quintile
Achieving Equity in Family Planning
8. Methods
Secondary analysis DHS standard recode files
Separate urban and rural strata
Rank by wealth score within strata
Create residence-specific wealth quintiles
Analyze outcome indicators by residence-
specific quintiles
Achieving Equity in Family Planning
10. Wealth and Residence: Ghana 2008
30% 30%
Urban
% Using a Modern Method
% Using a Modern Method
Rural
20% 20%
10% 10%
National
0% 0%
Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5
Achieving Equity in Family Planning
11. Wealth and Residence: Senegal 2005
30% 30%
Urban
% Using a Modern Method
% Using a Modern Method
Rural
20% 20%
10% 10%
National
0% 0%
Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5
Achieving Equity in Family Planning
12. Wealth and Residence: Zambia 2007
60% 60%
% Using a Modern Method
% Using a Modern Method
50% 50%
40% 40%
30% 30%
20% 20%
Urban
10% 10%
National Rural
0% 0%
Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5
Achieving Equity in Family Planning
13. Wealth and Residence: Kenya 2003
60% 60%
% Using a Modern Method
% Using a Modern Method
50% 50%
40% 40%
30% 30%
20% 20%
Urban
10% 10%
National Rural
0% 0%
Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5
Achieving Equity in Family Planning
14. Wealth and Residence: Kenya 2008
60% 60%
% Using a Modern Method
% Using a Modern Method
50% 50%
40% 40%
30% 30%
20% 20%
Urban
10% 10%
National Rural
0% 0%
Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5
Achieving Equity in Family Planning
15. Limitations of assets-based quintiles
Track over-all trends in family planning
outcomes
X Do not match individual consumption
measures of poverty
Achieving Equity in Family Planning
16. Match-up between consumption and
assets measures of poverty
>1 quintile +/- 1 quintile Exact match
100%
% Match w/ consumption
80%
60%
40%
20%
0%
Bottom 2nd 3rd 4th Top
Assets-based Quintile
Ecuador 2004 RHS
Achieving Equity in Family Planning
17. Match-up between consumption and
assets measures of poverty
>1 quintile +/- 1 quintile Exact match
100%
% Match w/ consumption
80%
60%
40%
20%
0%
Bottom 2nd 3rd 4th Top
Assets-based Quintile
Ethiopia 2005 DHS
2004/5 HIES
Achieving Equity in Family Planning
18. Conclusions
Disaggregate place of residence and relative
poverty to identify pockets of greatest
disparities and to assess impact
Use consumption-based measures of poverty
to monitor uptake of program interventions
by the poor
Achieving Equity in Family Planning
The Ecuador RHS included both household assets and direct measures of consumption – the “gold standard” for comparisons
In this comparison, we infer household consumption by matching items between the DHS and the Household Income and Expenditure Survey. Ethiopia was the worst match we found. We conducted the same analysis for Bangladesh and Malawi. Bangladesh came out very similar to Ecuador, and Malawi came out in the middle.