Spatial accessibility and availability measures and statistical properties in the food environment.

Area of Science:

• Health Sciences
• Spatial Statistics
• Geographic Information Systems (GIS)

Background:

• Spatial accessibility and availability indices are increasingly vital in health research.
• Evaluating the statistical reliability of these indices is essential for accurate health outcome analysis.
• Existing methods lack robust inferential capabilities for comparing different study regions.

Purpose of the Study:

• To develop and validate statistical tests for spatial accessibility and availability indices.
• To enable inferential comparisons of food access between distinct geographic areas.
• To assess the performance of these tests using simulation and real-world data.

Main Methods:

• Extensive simulations using cluster models for local food outlet density.
• Derivation of Monte Carlo critical values for statistical tests.
• Development of tests for mean differences and differences in Moran's I (spatial autocorrelation).

Main Results:

• Monte Carlo critical values were successfully derived for various statistical tests.
• The developed tests demonstrated the ability to make inferential comparisons between study areas.
• Simulations confirmed the utility of the new statistical approaches for spatial health data.

Conclusions:

• The proposed statistical tests enhance the inferential power of spatial accessibility and availability indices.
• These methods provide a statistically sound basis for comparing food access across different regions.
• The study offers valuable tools for researchers investigating the health impacts of food environments.