Food Consumption Scores and Food Consumption Groups Creation and Validation.
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Transcript of Food Consumption Scores and Food Consumption Groups Creation and Validation.
Food Consumption Scores and Food Consumption
GroupsCreation and Validation
Data Analysis plan
Create the Food Consumption Score Group foods by category (cereals, pulses, vegetables, fruit,
meat & fish, milk, sugar, oil Create the score based on frequency of consumption by group
times weight of each group and summing each group
Validate the FCS as a Food Security Indicator Correlation with various other indicators
Create Food Consumption Groups to answer: Who are the food insecure? How many are they? Where are they? Why are they insecure? Create basic statistics on how many in each group Explore further who they are by various strata (agro-ecological
zone, governate, urban vs. rural, etc)
Validating the FCSCorrelations with FCS
Reduced CSI Correlation Coefficient -0.329
Sig (2-tailed) 0.00
Wealth Index Correlation Coefficient 0.546
Sig (2-tailed) 0.00
Percent of total expenditure on food
Correlation Coefficient -0.124
Sig (2-tailed) 0.00
How many times In the past 7 days did not have enough food or money to buy food
Correlation Coefficient -0.321
Sig (2-tailed) 0.00
FCG Thresholds
An FCS of 21 in Yemen is composed of oil, sugar and cereals (staple)
Because the value of sugar and oil consumption was daily (7 times a week), we have used a higher threshold for grouping. In order to properly evaluate this high sugar and oil diet as poor, we have changed our thresholds as follows: Poor < 28 Borderline 28.5 – 42Acceptable >42.5
FCG by Governate
Rayma, Ad Daleh, Amran and Al Marha show the highest proportion of poor food consumption group
FCG by Agro-ecological zone
FCG by Urban / Rural
FCG by Main Livelihood Activity
FCG by Household Status
Literacy RateHigh Dependency
FCG Poor 39.1% 30.1%*
Borderline 50.3% 26.9%*
Acceptable 62.2% 18.0%
*The difference between Poor and Borderline in regards to high dependency was not found to be statistically significant
Conclusions
FCS is strongly correlated with other key food security indicators
The dietary patterns of the poorest households (in terms of food consumption) are highly reliant on sugars and oil
Generally, rural households are worse off as are households in the North Highlands
More analysis is needed to further profile the most food insecure