ArticleBMJ nutrition, prevention & health2020
Closing the gap: data-based decisions in food, nutrition and health systems: proceedings of the Fifth International Summit on Medical and Public Health Nutrition Education and Research.
Article in BMJ nutrition, prevention & health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Topic Modeling Analysis of Children's Food Safety Management Using BigKinds News Big Data: Comparing the Implementation Times of the Comprehensive Plan for Children's Dietary Safety Management.Foods (Basel, Switzerland) · 2025Article
- Optimizing clinical nutrition research: the role of adaptive and pragmatic trials.European journal of clinical nutrition · 2023Review
- Global architecture for the nutrition training of health professionals: a scoping review and blueprint for next steps.BMJ nutrition, prevention & health · 2022Article
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Authors and funding
6 authors.
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Abstract
introductionLike many of the biological sciences, nutrition has rapidly become a science which relies heavily on data collection, analysis and presentation. Knowledge gaps exist where data does not, and so the fifth annual International Summit on Medical and Public Health Nutrition Education and Research was held to address the theme of 'Closing the Gap: Data-based Decisions in Food, Nutrition and Health Systems'.
settingHomerton College, University of Cambridge, Cambridge in July 2019. KEY
findingsData-driven decision making is more likely to lead to positive change in areas such as malnutrition, food insecurity and food production. These decisions must be informed by multiple stakeholders from various backgrounds in multisectorial collaboration. Case examples presented at the Summit contribute to the International Knowledge Application Network in Nutrition 2025, which aims to help identify and close gaps in nutrition and healthcare.
conclusionsFormation of international networks are required to advance nutrition research, identify gaps and generate high-quality data. These data can be used to adequately train healthcare professionals resulting in positive impact on clinical and public health. Strengthening collaboration between existing networks will be essential in sharing data for better health outcomes.
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