Poster Topical Area: Global Nutrition

Location: Hall D

Poster Board Number: 543

E11-02 - A Proposed Index to Measure Nutrition Governance at the Implementation Level: The Nutrition Governance Index (NGI)

Sunday, Jun 10
8:00 AM – 6:00 PM

Objectives: With a significant international commitment towards achieving the nutrition goals within the Sustainable Development Goals, there is need to generate replicable empirical evidence to measure and understand the role of nutrition governance. We aimed to address this by creating an index called the Nutrition Governance Index (NGI) that measures constraints, challenges and opportunities in translating policies/programs into actions.

Using data from an ongoing longitudinal policy process survey (POSHAN) in Nepal, we purposively selected 520 government and non-government officials from 21 districts in the three agro-ecological zones of Nepal. We selected 24 Likert-scale questionnaire items from six domains and applied principal component analysis (PCA) to retain a single factor per domain. The domains include knowledge of nutrition and assigned roles, collaboration, finance, leadership, capacity and support. Factor scores were calculated for each domain and summed into an aggregate score that ranges from 0 to 100 (Figure 01). A confirmatory factor analysis was conducted to check for construct validity.

Two of the domains passed the checks for high consistency (Table 01) and four of the six indices for construct validity (Table 02). Sensitivity analyses comparing factor-based scores, a summative score index and the weighted-score approach used in these analyses showed almost perfect correlation (Table 03).

This study has demonstrated the possibility of generating a replicable, evidence-based tool to measure nutrition governance at the sub-national level. However, further tests to assess its suitability in various cross-cultural settings and its generalizability to other countries are highly recommended.

Funding Source: United States Agency for International Development (USAID)

CoAuthors: Patrick Webb – Tufts University; Shibani Ghosh – Tufts University; Robin Shrestha – Tufts University; Kedar Baral – Patan Academy of Health Sciences

Grace Namirembe

Data Analyst
Tufts University
Boston, Massachusetts