improving health equity_ergo_10.13.11

CORE Group’s Spring MeetingBaltimore, May 11, 2011

Alex Ergo, PhDBroad Branch Associates

Do MCHIP-Supported Interventions Reach the Poor?

How can we know?

The Maternal and Child Health Integrated Program (MCHIP)

USAID Bureau for Global Health’s flagship maternal, newborn and child health program

Working in well over 30 countries worldwide

MCHIP supports programming and opportunities for integration in: Maternal, Newborn and Child Health Immunization, Family Planning, Malaria,

HIV/AIDS Water & Sanitation, Urban Health, Health

Systems Strengthening

Introduction

MCHIP would like to know whether the interventions it supports reach the poor

What can be done when equity was not built into the design?

This presentation presents two possible analyses that MCHIP might consider during implementation

Analysis 1

What is the Socio-Economic Profile of the Beneficiaries of the Program?

See for example: Gwatkin DR, Rutstein S, Johnson K, Suliman E, Wagstaff A & Amouzou A (2007). Socio-economic differences in health, nutrition, and population: Nepal. Washington, DC: World Bank. (also includes slight variation)

Analysis 1 – Basic Steps

Step 1: Look for a recent household survey that uses an asset index as a proxy for socio-economic position

Step 2: Obtain questions used to collect the data necessary for the calculation of the asset index

Step 3: Conduct interviews using same questions

Step 4: Generate rural/urban-specific asset indices (optional)

Step 5: Create rural/urban-specific asset quintiles (optional)

Step 6: Calculate the asset index for each respondent

Step 7: Assign respondents to socio-economic quintiles

Step 8: Assess the distribution of beneficiaries across asset quintiles

Analysis 1 – Basic Steps

Step 1: Look for a recent household survey that uses an asset index as a proxy for socio-economic position

Examples:

Demographic and Health Survey (DHS)

Living Standards Measurement Survey (LSMS)

Multiple Indicator Cluster Survey (MICS)

Analysis 1 – Basic Steps

Step 2: Obtain questions used to collect the data necessary for the calculation of the asset indexExample:

Analysis 1 – Basic Steps

Step 3: Interview an adequately large sample of patients attending the facility-based service(s) of interest (exit interviews)

OR

Interview an adequately large sample of individuals/households benefitting from the community-based intervention (household visits)

Analysis 1 – Basic Steps

Step 4 (optional): Create rural/urban-specific asset quintilesSome assets may relate differently to wealth in rural and urban settings

E.g. type of flooring material; ownership of poultry

If the necessary technical expertise is available, conduct separate Principal Component Analyses for rural and urban data in the original household survey to generate rural/urban-specific asset indices

Analysis 1 – Basic Steps

Step 5 (optional): Generate rural/urban-specific asset indicesMany assets tend to be more associated with urban wealth than with rural wealth

E.g. access to basic services is overall better in urban areas than rural areas

Urban households cluster in the richer quintiles Rural households cluster in the poorer quintiles

Analysis 1 – Basic Steps

Step 5 (optional): Generate rural/urban-specific asset indicesMany assets tend to be more associated with urban wealth than with rural wealth

Poorest 2nd Middle 4th Top0%

20%

40%

60%

80%

100%

Rural Urban

Analysis 1 – Basic Steps

Step 5 (optional): Generate rural/urban-specific asset indicesMany assets tend to be more associated with urban wealth than with rural wealth

Create rural/urban-specific asset quintiles:

Using the rural/urban-specific asset indices generated under step 4 (optional)

OR

Using available country-level household asset indices

Analysis 1 – Basic Steps

Step 6: Calculate the asset index for each respondent:

Using rural/urban-specific weights calculated under step 4 (optional)

OR

Using the original survey’s weights

Analysis 1 – Basic Steps

Step 6: Calculate the asset index for each respondent:

Example:

… … …

Analysis 1 – Basic Steps

Step 7: Assign respondents to socio-economic quintiles:

Using rural/urban-specific cut-off points calculated under step 4 (optional)

OR

Using the original survey’s cut-off points

Analysis 1 – Basic Steps

Step 7: Assign respondents to socio-economic quintiles:

Example:

Analysis 1 – Basic Steps

Step 8: Assess the distribution of beneficiaries across asset quintilesExample:

Poorest 2nd Middle 4th Top0%

10%20%30%40%

Pro-poor Neutral Not pro-poor

Under what conditions can Analysis 1 be adopted?

Availability of a recent DHS, LSMS, MICS or other household survey collecting information on asset ownership, access to basic services and dwelling characteristics

Intervention supported by MCHIP is facility-based and it is possible to conduct exit interviews ORIntervention supported by MCHIP is community-based and it is possible to conduct household interviews

Analysis 2

Are Program Resources Reaching the Poorest Geographic Areas

Analysis 2 – Basic Steps

20

Step 1: Look for a recent poverty map of the country

(these typically include poverty headcount ratios by region/district/…: i.e. % of the population living below the poverty line)

Example: Coulombe H. 2005, Ghana census-based poverty map: district and sub-district level results. Ghana Statistical Service. The estimates relate to the year 2000.

Analysis 2 – Basic Steps

21

Step 2: Indicate areas of intervention on poverty map

Example: Vietnam poverty map

Analysis 2 – Basic Steps

District Population

Program Resources Allocated

Program Resources Allocated Per Capita

Poverty Headcount

Ratio

Jomoro 110,972 174,226 1.57 0.491

Nzema East 142,523 89,789 0.63 0.446

Ahanta West 94,826 146,980 1.55 0.378

Shama-Ahanta 366,215 377,201 1.03 0.264

Mpohor-Wassa 122,752 130,117 1.06 0.292

Wassa West 231,952 278,342 1.20 0.222

Wassa Amenefi 234,155 297,377 1.27 0.324

Aowin-Suaman 118,978 172,518 1.45 0.350

Juabeso-Bia 244,456 479,134 1.96 0.346

Sefwi Wiawso 149,247 211,931 1.42 0.345

… … … … …22

Step 3: Calculate resource allocation per capita by district

23

20%25%30%35%40%45%50%0.5

1

1.5

2 Juabeso-Bia

Poverty Headcount Ratio

US

$ P

er

Cap

ita

Nzema East

Analysis 2 – Basic Steps

Step 4: Plot US$ per capita against poverty headcount ratio

Under what conditions can Analysis 2 be adopted?

Availability of a recent poverty map

Intervention supported by MCHIP is targeting specific geographical areas

Thank you!

wwww.mchip.net

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