Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023)
This dataset originates from a cross-sectional study conducted in 2023 to assess and characterize the food environment in both urban informal and rural settings in Kenya. The primary objective was to map and analyse food availability across vendor locations, with a specific focus on understanding th...
| Main Authors: | , , , , |
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| Format: | Conjunto de datos |
| Language: | Inglés |
| Published: |
2025
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| Online Access: | https://hdl.handle.net/10568/177340 |
| _version_ | 1855515218330779648 |
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| author | Odongo, Nicanor Obiero Akingbemisilu, Tosin Harold Jordan, Irmgard Induli, Irene Mudiovo Termote, Celine |
| author_browse | Akingbemisilu, Tosin Harold Induli, Irene Mudiovo Jordan, Irmgard Odongo, Nicanor Obiero Termote, Celine |
| author_facet | Odongo, Nicanor Obiero Akingbemisilu, Tosin Harold Jordan, Irmgard Induli, Irene Mudiovo Termote, Celine |
| author_sort | Odongo, Nicanor Obiero |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This dataset originates from a cross-sectional study conducted in 2023 to assess and characterize the food environment in both urban informal and rural settings in Kenya. The primary objective was to map and analyse food availability across vendor locations, with a specific focus on understanding the differences and similarities in food diversity between Nairobi’s Viwandani informal settlement and Makueni’s Kiima Kiu ward. The study aimed to answer key questions, including: i. What types of food vendors operate in urban, informal, and rural settings? ii. What is the diversity of foods available at individual vendor outlets? iii. What is the quality of food environment in terms of healthy and unhealthy food availability? iv. How does food diversity vary within the vendor neighbourhood? v. Are there structural or spatial disparities in vendor distribution and food accessibility across urban and rural settings? The dataset includes geocoded vendor data, vendor typologies (ambulant/mobile vendors, butchers, cereal shops, cooked food street vendors, kiosks, supermarkets, mom-and-pop shops, stalls/tabletop and restaurants, direct farm sales, home vendors and wholesalers. ), food groups sold, and gender of vendors. It also captures vendor neighbourhood food diversity, which offers a novel lens for evaluating the food environment beyond individual vendors. Data were collected using a digital survey tool on Open Data Kit (ODK) and securely managed via the FormShare platform. The study contributes to food systems research by offering scalable methodologies to assess the built food environment, especially in under-researched rural contexts. Major subject areas include food systems, nutrition environment mapping, rural-urban disparities, public health, informal economies, and geospatial analysis. This dataset is particularly useful for researchers, policymakers, and development practitioners interested in food environment profiling, urbanization impacts on food systems, spatial analysis of vendor access, and nutrition-sensitive planning.
Methodology: 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 was calculated within radii of 50m, 100m, and 200m from each vendor location, capturing the food exposure landscape accessible to consumers. Data quality was ensured through trained enumerators, real-time supervision, and automated consistency checks within the tool. Ethical clearance was obtained from the Alliance of Bioversity International and CIAT IRB (2023-IRB22), Amref Ethics and Scientific Review Committee (ESRC P1451/2023), and NACOSTI (P/23/28871). |
| format | Conjunto de datos |
| id | CGSpace177340 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| record_format | dspace |
| spelling | CGSpace1773402025-10-24T19:40:14Z Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023) Odongo, Nicanor Obiero Akingbemisilu, Tosin Harold Jordan, Irmgard Induli, Irene Mudiovo Termote, Celine fruits food environment fruit vegetables non-communicable diseases rural-urban food supply chains This dataset originates from a cross-sectional study conducted in 2023 to assess and characterize the food environment in both urban informal and rural settings in Kenya. The primary objective was to map and analyse food availability across vendor locations, with a specific focus on understanding the differences and similarities in food diversity between Nairobi’s Viwandani informal settlement and Makueni’s Kiima Kiu ward. The study aimed to answer key questions, including: i. What types of food vendors operate in urban, informal, and rural settings? ii. What is the diversity of foods available at individual vendor outlets? iii. What is the quality of food environment in terms of healthy and unhealthy food availability? iv. How does food diversity vary within the vendor neighbourhood? v. Are there structural or spatial disparities in vendor distribution and food accessibility across urban and rural settings? The dataset includes geocoded vendor data, vendor typologies (ambulant/mobile vendors, butchers, cereal shops, cooked food street vendors, kiosks, supermarkets, mom-and-pop shops, stalls/tabletop and restaurants, direct farm sales, home vendors and wholesalers. ), food groups sold, and gender of vendors. It also captures vendor neighbourhood food diversity, which offers a novel lens for evaluating the food environment beyond individual vendors. Data were collected using a digital survey tool on Open Data Kit (ODK) and securely managed via the FormShare platform. The study contributes to food systems research by offering scalable methodologies to assess the built food environment, especially in under-researched rural contexts. Major subject areas include food systems, nutrition environment mapping, rural-urban disparities, public health, informal economies, and geospatial analysis. This dataset is particularly useful for researchers, policymakers, and development practitioners interested in food environment profiling, urbanization impacts on food systems, spatial analysis of vendor access, and nutrition-sensitive planning. Methodology: 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 was calculated within radii of 50m, 100m, and 200m from each vendor location, capturing the food exposure landscape accessible to consumers. Data quality was ensured through trained enumerators, real-time supervision, and automated consistency checks within the tool. Ethical clearance was obtained from the Alliance of Bioversity International and CIAT IRB (2023-IRB22), Amref Ethics and Scientific Review Committee (ESRC P1451/2023), and NACOSTI (P/23/28871). 2025 2025-10-24T19:39:12Z 2025-10-24T19:39:12Z Dataset https://hdl.handle.net/10568/177340 en Open Access Odongo, N.O.; Akingbemisilu, T.H.; Jordan, I.; Induli, I.M.; Termote, C. (2025) Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023). https://doi.org/10.7910/DVN/YPVRMJ |
| spellingShingle | fruits food environment fruit vegetables non-communicable diseases rural-urban food supply chains Odongo, Nicanor Obiero Akingbemisilu, Tosin Harold Jordan, Irmgard Induli, Irene Mudiovo Termote, Celine Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023) |
| title | Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023) |
| title_full | Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023) |
| title_fullStr | Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023) |
| title_full_unstemmed | Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023) |
| title_short | Food Environment Mapping in Urban Informal (Nairobi) and Rural (Makueni) Kenya: A Cross-Sectional Vendor Survey Data (2023) |
| title_sort | food environment mapping in urban informal nairobi and rural makueni kenya a cross sectional vendor survey data 2023 |
| topic | fruits food environment fruit vegetables non-communicable diseases rural-urban food supply chains |
| url | https://hdl.handle.net/10568/177340 |
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