Show me what you eat: Assessing diets remotely through pictures
Goal: Using real-time smartphone meal pictures sent by rural or urban households to better monitor and assess the quality of their diets, and provide tailored recommendations to improve them. Detailed information on household and individual dietary intake is crucial for adequate nutritional monitori...
| Autores principales: | , |
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| Formato: | Brief |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2021
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/142117 |
| _version_ | 1855517611234689024 |
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| author | Ceballos, Francisco Hernandez, Manuel A. |
| author_browse | Ceballos, Francisco Hernandez, Manuel A. |
| author_facet | Ceballos, Francisco Hernandez, Manuel A. |
| author_sort | Ceballos, Francisco |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Goal: Using real-time smartphone meal pictures sent by rural or urban households to better monitor and assess the quality of their diets, and provide tailored recommendations to improve them. Detailed information on household and individual dietary intake is crucial for adequate nutritional monitoring and designing interventions to improve diets. Common recall-based methods are generally time consuming, costly, and subject to non-negligible measurement errors and potential biases. In addition, the scope of information that can be obtained in a regular survey is typically limited. Detailed diaries, in turn, are effort- and time-intensive and prone to errors. With increasing mobile penetration in both urban and rural areas, meal pictures can overcome some of these difficulties, providing real-time, detailed food intake information of individuals remotely and at a minimal cost. Moreover, pictures can be obtained over extended periods of time, beyond the standard short spans (i.e. 24-hours) in recall survey questions, with little to no data quality loss. Such rich consumption data can help identify and better understand vulnerabilities and nutritional imbalances —including specific macronutrient or micronutrient gaps or excesses—, and open the door for low-cost, individually tailored digital interventions to promote healthier diets. Moreover, crowdsourced data allow to identify locally available, affordable foods rich in specific nutrients consumed by similar households in the area. Interventions, in turn, can be delivered through text messages, interactive voice response (IVR), or phone calls, or videos or interactive games integrated into an app, benefitting from a two-way communication channel with individuals. |
| format | Brief |
| id | CGSpace142117 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1421172025-11-06T04:23:14Z Show me what you eat: Assessing diets remotely through pictures Ceballos, Francisco Hernandez, Manuel A. urban population rural population diet digital technology Goal: Using real-time smartphone meal pictures sent by rural or urban households to better monitor and assess the quality of their diets, and provide tailored recommendations to improve them. Detailed information on household and individual dietary intake is crucial for adequate nutritional monitoring and designing interventions to improve diets. Common recall-based methods are generally time consuming, costly, and subject to non-negligible measurement errors and potential biases. In addition, the scope of information that can be obtained in a regular survey is typically limited. Detailed diaries, in turn, are effort- and time-intensive and prone to errors. With increasing mobile penetration in both urban and rural areas, meal pictures can overcome some of these difficulties, providing real-time, detailed food intake information of individuals remotely and at a minimal cost. Moreover, pictures can be obtained over extended periods of time, beyond the standard short spans (i.e. 24-hours) in recall survey questions, with little to no data quality loss. Such rich consumption data can help identify and better understand vulnerabilities and nutritional imbalances —including specific macronutrient or micronutrient gaps or excesses—, and open the door for low-cost, individually tailored digital interventions to promote healthier diets. Moreover, crowdsourced data allow to identify locally available, affordable foods rich in specific nutrients consumed by similar households in the area. Interventions, in turn, can be delivered through text messages, interactive voice response (IVR), or phone calls, or videos or interactive games integrated into an app, benefitting from a two-way communication channel with individuals. 2021-05-19 2024-05-22T12:09:59Z 2024-05-22T12:09:59Z Brief https://hdl.handle.net/10568/142117 en Open Access application/pdf International Food Policy Research Institute Ceballos, Francisco; and Hernandez, Manuel A. 2021. Show me what you eat: Assessing diets remotely through pictures. Show Me What You Eat Project May 2021. Washington, DC: International Food Policy Research Institute (IFPRI). https://doi.org/10.2499/p15738coll2.134407. |
| spellingShingle | urban population rural population diet digital technology Ceballos, Francisco Hernandez, Manuel A. Show me what you eat: Assessing diets remotely through pictures |
| title | Show me what you eat: Assessing diets remotely through pictures |
| title_full | Show me what you eat: Assessing diets remotely through pictures |
| title_fullStr | Show me what you eat: Assessing diets remotely through pictures |
| title_full_unstemmed | Show me what you eat: Assessing diets remotely through pictures |
| title_short | Show me what you eat: Assessing diets remotely through pictures |
| title_sort | show me what you eat assessing diets remotely through pictures |
| topic | urban population rural population diet digital technology |
| url | https://hdl.handle.net/10568/142117 |
| work_keys_str_mv | AT ceballosfrancisco showmewhatyoueatassessingdietsremotelythroughpictures AT hernandezmanuela showmewhatyoueatassessingdietsremotelythroughpictures |