Assessment of a Diagnostic Tool for Household Poverty and Food Security in Malawi

In Malawi, USAID's Livelihoods and Food Security Technical Assistance II (LIFT II) project, managed by FHI 360, aims to support service providers in the northern area of Balaka District with a diagnostic tool that will collect essential poverty and food security data, as well as be useful in helping local stakeholder staff provide referrals to other service providers. The goals of the present study were to understand how LIFT II could help service providers make efficient, effective, and appropriate referrals to services within the district, and also to learn how LIFT II could classify clients into the three categories of household poverty/vulnerability: Provide, Protect, and Promote.

The first step in LIFT II’s investigation was to collect data using a series of tools. In August 2013, LIFT II hired and trained a team of six local data collectors to conduct 312 clients interviews at three health facilities in Balaka District: Balaka District Hospital, DREAM (Andiamo Health Center), and Kalembo Health Center—three sites where nutrition and HIV care services are meant to be integrated through Malawi’s Nutrition Care, Support, and Treatment (NCST) program. Household poverty and vulnerability data were collected using two tools:

• Grameen Foundation’s Progress out of Poverty Index (PPI), and
• a custom designed tool based on a series of the most frequent questions to appear on the Progress out of Poverty Indices and USAID’s Poverty Assessment Tool (PAT) across all of sub-Saharan Africa.

Household food security data were collected using three tools, all developed by the USAID-funded Food and Nutrition Technical Assistance (FANTA) project:

1. the Household Hunger Score (HHS),
2. the Household Dietary Diversity Score (HDDS), and
3. the Months Assessment of a Diagnostic Tool for Household Poverty and Food Security in Balaka District, Malawi of Adequate Household Provisioning (MAHFP).

LIFT II collected data on a final series of questions to gauge community interest in, understanding of, and perceived barriers to referrals.

The second step in the investigation was to conduct a thorough debrief with data collectors to assess their perceptions of the diagnostic tool's utility and suitability as an aid in making efficient, effective and appropriate referrals, as well as any perceived benefits they would expect to find by classifying clients into the provide-protect-promote framework.

Below are some of the key findings from the assessment:

• Efficient referrals do not take a long time to complete.
• Effective referrals allow us to collect data about clients to improve referral programming.
• Appropriate referrals provide a client with information about a service that is right for them and their household.
• PPI and other data can be used to classify clients.

Read the entire brief here.