Final report - Link Nutrition Causal Analysis (October 2019-March 2020): Grand Bassa, Grand Cape Mount, Rural Montserrado, Rivercess, and Sinoe Counties

Originally published
View original



Bordering the Atlantic coast, Grand Cape Mount, Grand Bassa, Montserrado, Rivercess, and Sinoe Counties are among the five counties of Liberia with the highest burden of stunting in the country.
Continued challenges in food security, water, hygiene and sanitation, as well as gender undermine child and maternal nutrition across the eight livelihood zones of these five counties. Rates of stunting remain chronically high, exceeding 30% in the five counties per the 2018 CFSNS. The Government of Liberia’s national development plan for 2018 – 2023 therefore includes nutrition as a priority area, with the national target to reduce stunting to 22% by 2023. In an attempt to address complex root causes of stunting, GOL and implementing partners have been making efforts to scale up nutrition specific and nutrition sensitive interventions.

A part of this initiative to reduce rates of stunting, the Liberia WASH Consortium set out to conduct formative research to better understand the context-specific causes of stunting and determinants of related behaviours. Three out of five consortium members, i.e. Action Against Hunger, Concern Worldwide and Water Aid, engaged in the delivery of assessments, namely the Link NCA Nutrition Causal Analysis, Barrier Analysis and Cost of Diet Assessment, to build a solid evidence base for future interventions adapted to an in-depth understanding of the context and community priorities.

The Link NCA study is a critical part of this approach, allowing a better understanding of the underlying causes of stunting and the linkages between nutrition, food security and livelihoods, water, sanitation and hygiene, gender and other thematic areas. The key findings drawn from the analysis will inform the design of the second and third phases of the project, supported by awareness raising and advocacy efforts, in order to develop an integrated optimal response aimed at reducing rates of stunting in the study area.