R Script for the Analysis of Retail Food Environment Quality in Viwandani and Makueni Kenya with Spatial Lens

A cross-sectional vendor mapping survey was conducted between September and December 2023 in two Kenyan counties: Viwandani informal settlement in Nairobi (urban) and Kiima Kiu in Makueni (rural). The study aimed to assess vendor-level and neighbourhood-level food diversity within distinct food environments. All food vendors within the selected administrative boundaries were observed and geocoded. Vendors were defined as individuals selling food items, either exclusively or alongside non-food items. Enumerators used a structured digital tool developed on Open Data Kit (ODK), deployed via the FormShare platform, to record vendor type, gender, and the range of food groups sold. Photographs of vendor outlets were also taken to aid classification. Vendor neighbourhood food diversity for healthy and unhealthy foods was calculated within radii of 50m, 100m, and 200m from each vendor location using geopandas in Python, capturing the food exposure landscape accessible to consumers. The FE Quality R code which assess food environment quality using the global dietary recommendation framework includes all the scripts for descriptive analysis conducted on the cleaned data, and it can be reproduced in R using the same dataset.