UNHCR SENS: Nutrition and Health Survey for Dadaab Refugee Camps, 2018
Updated 2mo ago
2filesWEB APP
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Description
8.0% was the weighted prevalence of global acute malnutrition in the Dadaab refugee complex in 2018, falling within the 'poor' category. The UNHCR Standardized Expanded Nutrition Survey (SENS) was conducted between 20 August and 8 September 2018 across three camps to assess malnutrition, anaemia, infant feeding, water, and sanitation. The survey provides data for an estimated population of 208,000 registered refugees, primarily from Somalia.
Use Cases
Assess malnutrition prevalence and severity based on reported global acute malnutrition rates.
Analyze trends in anaemia among children and women based on prevalence data exceeding 40%.
Evaluate infant and young child feeding practices based on reported indicators.
Monitor access to safe drinking water and sanitation gaps based on survey findings.
Compare nutritional status across specific camps (Dagahaley, Ifo, Hagadera) based on camp-level results.
Strengths
Provides specific prevalence figures for key indicators like global acute malnutrition (8.0%) and anaemia (48.9% among women).
Includes temporal comparison, showing improvement from 9.7% global acute malnutrition in 2017.
Offers camp-level breakdowns, identifying Ifo camp as within the 'serious' malnutrition category.
Survey conducted by UNHCR, a recognized authority in refugee contexts.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count is unknown, which may limit suitability assessment.
Data is from 2018; freshness should be verified for current applications.
Provenance
Source
UNHCR - The UN Refugee Agency
Collection Method
Standardized Expanded Nutrition Survey (SENS) conducted via field assessment.
Time Range
Survey conducted 20 August to 8 September 2018.
Freshness
Last updated 2026-04-03 14:25:19.438129; freshness should be verified.
Geography
Dadaab refugee complex in northeastern Kenya (camps: Dagahaley, Ifo, Hagadera).
Primary data formats are PDF and WEB APP, which may require specific tools for extraction and analysis.