Leveraging digital tools and crowdsourcing approaches to generate high-frequency data for diet quality monitoring at population scale in Rwanda

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dc.creatorManners, Rhys
dc.creatorAdewopo, Julius
dc.creatorNiyibituronsa, M.
dc.creatorRemans, R.
dc.creatorGhosh, A.
dc.creatorSchut, Marc
dc.creatorEgoeh, S.G.
dc.creatorKilwenge, R.
dc.creatorFraenzel, A.
dc.date2022-01-07
dc.date2022-11-22T10:58:59Z
dc.date2022-11-22T10:58:59Z
dc.date.accessioned2026-06-27T15:58:29Z
dc.descriptionDiet quality is a critical determinant of human health and increasingly serves as a key indicator for food system sustainability. However, data on diets are limited, scattered, often project-dependent, and current data collection systems do not support high-frequency or consistent data flows. We piloted in Rwanda a data collection system, powered by the principles of citizen science, to acquire high frequency data on diets. The system was deployed through an unstructured supplementary service data platform, where respondents were invited to answer questions regarding their dietary intake. By combining micro-incentives with a normative nudge, 9,726 responses have been crowdsourced over 8 weeks of data collection. The cost per respondent was <$1 (system set-up, maintenance, and a small payment to respondents), with interactions taking <15min. Exploratory analyses show that >70% of respondents consume tubers and starchy vegetables, leafy vegetables, fruits, legumes, and wholegrains. Women consumed better quality diets than male respondents, revealing a sex-based disparity in diet quality. Similarly, younger respondents (age 24 years) consumed the lowest quality diets, which may pose significant risks to their health and mental well-being. Middle-income Rwandans were identified to have consumed the highest quality diets. Long-term tracking of diet quality metrics could help flag populations and locations with high probabilities of nutrition insecurity, in turn guiding relevant interventions to mitigate associated health and social risks.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/125562
dc.identifier.urihttp://hdl.handle.net/123456789/118964
dc.languageen
dc.publisherFrontiers Media
dc.rightsOpen Access
dc.sourceManners, R., Adewopo, J., Niyibituronsa, M., Remans, R., Ghosh, A., Schut, M., ... & Fraenzel, A. (2022). Leveraging digital tools and crowdsourcing approaches to generate high-frequency data for diet quality monitoring at population scale in Rwanda. Frontiers in Sustainable Food Systems, 5: 804821, 1-14.
dc.subjectdiet
dc.subjectnutrition
dc.subjectmonitoring
dc.subjectfood security
dc.subjectgrain legumes
dc.subjectrwanda
dc.titleLeveraging digital tools and crowdsourcing approaches to generate high-frequency data for diet quality monitoring at population scale in Rwanda
dc.typeJournal Article

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Instituto Internacional de Agricultura Tropical (IITA)