Positive impacts of personalized dietary advice based on socio-demographic and cognitive characteristics

02 Aug 2024 --- Personalized dietary advice that increases fruit and vegetable consumption and reduces the intake of saturated fat and sugar based on individuals’ socio-demographic, cognitive and sensory aspects can effectively increase health, according to a new study.

Researchers developed eight cluster models based on individual characteristics and included data from 3,654 UK households.

“Results showed that, when compared to generic advice, participants that received matched personalized advice were significantly more likely to indicate they would change their diet,” state the authors of the paper, based at the University of Reading, UK, and the European Food Information Council, Belgium.

“Overall, this study demonstrated that the power of personalizing food choice advice, based on a combination of individual characteristics, can be more effective than current approaches in motivating dietary change. Our study also emphasizes the viability of addressing population health through automatically delivered web-based personalized advice.”

The study, published in Appetite, used the characteristics of the eight identified clusters to create eight separate personalized “food choice advice.” It assessed their ability to motivate the participants to consume more fruit and vegetables and less saturated fat and sugar.

More fruit and veggies, less fat and sugar
The research team presented 218 of the participants with either generic “EatWell” advice from the UK Government, advice tailored to their allocated cluster (matched personalized) or advice tailored to a different cluster (unmatched personalized).

The research findings reveal that the participants who received matched personalized advice were significantly more likely to indicate they would change their diet than those who received generic or unmatched personalized advice.

The authors argue that this highlights the potential power of providing alternative food choices.

The paper points out that “given the final study was conducted online, and the cluster modeling could be easily integrated into an online application, the findings also contribute to evidence regarding the feasibility of using diet apps to deliver effective food advice to the general population.”

Research conducted at the Taipei Medical University, Taiwan, into the potential use of AI chatbots to provide personalized nutritional advice revealed that AI estimations of energy, carbohydrate and fat contents are similar to those of qualified nutritionists, while the technology struggles with protein estimation.

This feature is provided by Food Ingredients First’s sister website, Nutrition Insight.

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