Accurately Inferring Compliance to Five Major Food Guidelines Through Simplified Surveys: Applying Data Mining to the UK National Diet and Nutrition Survey

JMIR Public Health and Surveillance
Nicholas Rosso, Philippe Giabbanelli

Abstract

National surveys in public health nutrition commonly record the weight of every food consumed by an individual. However, if the goal is to identify whether individuals are in compliance with the 5 main national nutritional guidelines (sodium, saturated fats, sugars, fruit and vegetables, and fats), much less information may be needed. A previous study showed that tracking only 2.89% of all foods (113/3911) was sufficient to accurately identify compliance. Further reducing the data needs could lower participation burden, thus decreasing the costs for monitoring national compliance with key guidelines. This study aimed to assess whether national public health nutrition surveys can be further simplified by only recording whether a food was consumed, rather than having to weigh it. Our dataset came from a generalized sample of inhabitants in the United Kingdom, more specifically from the National Diet and Nutrition Survey 2008-2012. After simplifying food consumptions to a binary value (1 if an individual consumed a food and 0 otherwise), we built and optimized decision trees to find whether the foods could accurately predict compliance with the major 5 nutritional guidelines. When using decision trees of a similar size to previous...Continue Reading

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Citations

Jul 30, 2021·Critical Reviews in Food Science and Nutrition·Larissa Oliveira ChavesJosefina Bressan
Sep 16, 2021·Applied Physiology, Nutrition, and Metabolism = Physiologie Appliquée, Nutrition Et Métabolisme·Mélina Côté, Benoît Lamarche

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Software Mentioned

Weka
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Open Science Framework
SMOTE

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