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Assessment of Social Transmission of Food Preferences Behaviors
Published on: January 25, 2018
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Multivariate analysis of food consumption profiles in crisis settings
Aleksandra Gorzycka-Sikora1, Nancy Mock2, Michelle Lacey3
1Department of Mathematics, University of Miami, Miami, Florida, United States of America.
Plos One
|March 24, 2023
Summary
Humanitarian agencies can better track food insecurity using a new multivariate modeling framework. This approach analyzes household food consumption data for more detailed insights into the effectiveness of aid programs.
Area of Science:
- Public Health
- Nutrition Science
- Data Science
Background:
- Malnutrition prevention is a key goal for humanitarian organizations.
- Household surveys monitor food insecurity during crises.
- Current methods using aggregate indicators lack detail for program evaluation.
Purpose of the Study:
- To develop a multivariate modeling framework for analyzing household food consumption frequency data.
- To provide more nuanced and interpretable information on food insecurity and aid effectiveness.
- To adapt methods for smaller, variable surveys common in crisis settings.
Main Methods:
- Developed a multivariate modeling framework for bounded, correlated count data.
- Introduced methods to update baseline models for crisis-affected survey data.
- Applied the framework to national consumption data from Yemen (2014, 2016).
Main Results:
- The multivariate framework offers enhanced interpretability compared to aggregate indicators.
- The approach allows for detailed assessment of consumption changes in response to shocks.
- Demonstrated utility in evaluating humanitarian food assistance program impacts.
Conclusions:
- The developed framework improves the analysis of food consumption data in humanitarian contexts.
- This method provides critical insights for optimizing food security interventions.
- Enhanced data analysis supports more effective humanitarian aid delivery.
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