Spatial Patterns and Health-Based Characterization of the Retail Food Environment in Mexico City.

The public health burden of obesity and non-communicable diseases in Mexico is one of the highest in the world, and one of its main causes is the change in diet of the population. The urban food environment has been suggested as a key contributor towards the increasing deterioration in diets. Our objective was to present the first spatial and health characterization of the food environment of Mexico City. The data source was the National Statistics Directory of Economic Units 2020, which provides data on the urban supply of food and beverages. Food outlets were classified into 14 types according to the food items that are mainly sold. Local spatial autocorrelation methods were used to assess the existence of spatial patterns. The results suggest all types of food outlet showed high- density clusters and low -density clusters, with the geographic location of these clusters varying based on the type of establishment and by socioeconomic status of the census tracts. This paper puts forward a health-based classification of food retail outlets, to identify the spatial distribution of food outlets in relation to nutrition and health. This could guide researchers and policymakers towards improvements, particularly to direct interventions towards specific areas of the city. [ABSTRACT FROM AUTHOR]