Combating Food Insecurity in the U.S. Navy

Abstract

To combat food insecurity, the Department of the Navy will increase the Basic Needs Allowance (BNA) total household income requirement up to 150 percent of the Federal Poverty Guideline (FPG) in accordance with the National Defense Authorization Act of 2023. This thesis uses machine learning techniques on comparable civilian data to create a model that best predicts the risk of food insecurity and the characteristics of Sailors who are food insecure. To measure the effectiveness of the BNA, this study simulates the increase in total household income up to 130 percent and 150 percent FPG, with and without the Basic Allowance for Housing included in the total household income calculation and reruns the prediction model to see the changes in predicted risk of food insecurity. The model suggests that 17.6 percent of Sailors are food insecure. Additionally, the BNA in each simulation insignificantly decreases the food insecurity rate. Less than 1 percent of Sailors qualify for the BNA, while 17 percent are predicted to be food insecure. Therefore, the BNA provides an insufficient amount of allowance to an inadequate number of families to effectively reduce food insecurity in the Navy

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2023
Accession Number
AD1212932

Entities

People

  • Alan J. Lee

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Active Duty
  • Budgets
  • Covid-19
  • Data Sets
  • Department Of Defense
  • Diseases
  • Economic Analysis
  • Education
  • Employment
  • Enlisted Personnel
  • Families (Human)
  • Food Insecurity
  • Machine Learning
  • Mental Disorders
  • Military Families
  • National Security
  • Predictive Modeling
  • Security
  • Simulations
  • Statistics
  • United States
  • United States Naval Academy

Fields of Study

  • Agricultural and Food sciences

Readers

  • Cybersecurity.
  • Industrial Economics
  • Personnel Management and Statistics in the Military and Department of Defense

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks