Vulnerable population identified by the nutritional status of women (BMI) as indicator for food security, in sample of households in West Africa study area. Data based on DHS and MICS surveys.
In defining vulnerability, WFP (2009) and IFPRI (2012) have been followed and combined with indicators for food security with health indicators that signal vulnerability in a physical sense. IFPRI's Global Hunger Index uses three indicators to measure hunger: the number of adults being undernourished, the number of children that have low weight for age, and child mortality. Other classifications of food security use the variety of the diet as an indicator, combined with anthropometric data on children. However, in the DHS data there were no information available on child mortality, nor on dietary composition. Given these data limitations, data on nutritional status of women (Body Mass Index, BMI) for women and children (weight for age) have been used as indicators for food security. These data were combined with data on morbidity among adults and children, specifically the occurrence of malaria, cough, and diarrhea. Combinations of indicators have led to a classification of households as being very vulnerable, vulnerable, nearly vulnerable and not vulnerable.
This data set was produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)"project, Work Package 5 (WP5). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.
This study in WP5 aimed to identify, locate and characterize groups that are vulnerable for climate change conditions in two country clusters; one in West Africa (Benin, Burkina Faso, Côte d'Ivoire, Ghana, and Togo) and one in East Africa (Sudan, South Sudan and Uganda). Data used for the study include the Demographic and Health Surveys (DHS) , the Multi Indicator Cluster Survey (MICS) and the Afrobarometer surveys for the socio-economic variables and grid level data on agro-ecological and climatic conditions.
Data publication: 2013-08-01
Supplemental Information:
ClimAfrica was an international project funded by European Commission under the 7th Framework Programme (FP7) for the period 2010-2014. The ClimAfrica consortium was formed by 18 institutions, 9 from Europe, 8 from Africa, and the Food and Agriculture Organization of United Nations (FAO).
ClimAfrica was conceived to respond to the urgent international need for the most appropriate and up-to-date tools and methodologies to better understand and predict climate change, assess its impact on African ecosystems and population, and develop the correct adaptation strategies. Africa is probably the most vulnerable continent to climate change and climate variability and shows diverse range of agro-ecological and geographical features. Thus the impacts of climate change can be very high and can greatly differ across the continent, and even within countries.
The project focused on the following specific objectives:
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Develop improved climate predictions on seasonal to decadal climatic scales, especially relevant to SSA;
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Assess climate impacts in key sectors of SSA livelihood and economy, especially water resources and agriculture;
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Evaluate the vulnerability of ecosystems and civil population to inter-annual variations and longer trends (10 years) in climate;
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Suggest and analyse new suited adaptation strategies, focused on local needs;
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Develop a new concept of 10 years monitoring and forecasting warning system, useful for food security, risk management and civil protection in SSA;
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Analyse the economic impacts of climate change on agriculture and water resources in SSA and the cost-effectiveness of potential adaptation measures.
The work of ClimAfrica project was broken down into the following work packages (WPs) closely connected. All the activities described in WP1, WP2, WP3, WP4, WP5 consider the domain of the entire South Sahara Africa region. Only WP6 has a country specific (watershed) spatial scale where models validation and detailed processes analysis are carried out.
Contact points:
Metadata Contact: FAO-Data
Resource Contact: Lia van Wesenbeeck
Resource Contact: Ben Sonneveld
Resource constraints:
copyright
Online resources:
BMI <16, % of population - Distribution in sample of households in West Africa
BMI 16-18.3, % of population - Distribution in sample of households in West Africa
BMI 18.3-18.6, % of population - Distribution in sample of households in West Africa
BMI >18.6, % of population - Distribution in sample of households in West Africa
A spatially explicit assessment of specific vulnerabilities of the food system due to climate change and the identification of their causes; Technical report
Scenarios of major production systems in Africa
CLIMAFRICA – Climate change predictions in Sub-Saharan Africa: impacts and adaptations
