ArticleInternational journal of epidemiology2019
Precision nutrition: hype or hope for public health interventions to reduce obesity?
Article in International journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.
- Personalized Nutrition Biomarkers and Dietary Strategies for Atherosclerosis Risk Management: A Systematic Review.Nutrients · 2025Pooled it
- Precision nutrition-based interventions for the management of obesity in children and adolescents up to the age of 19 years.The Cochrane database of systematic reviews · 2025Pooled it
- Cost-Effectiveness of Personalised Nutrition in Adults With Overweight and Obesity: PREVENTOMICS Studies in Poland and the UK.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2025Trial
- AI-driven personalization of food systems: From precision nutrition to climate-resilient supply chains.NPJ science of food · 2026Review
- Precision obesity medicine: a translational perspective on epigenetics, the gut microbiome, and AI-assisted multi-omics integration.Frontiers in genetics · 2026Article
- A pilot study of the potential role of ChatGPT in stated-calorie diet planning.International journal of obesity (2005) · 2025Article
- The Effect of Lifestyle and Eating Habits on Obesity.Nutrients · 2025Article
- Personalising dietary advice for disease prevention: concepts and experiences.Pflugers Archiv : European journal of physiology · 2025Review
- Global, regional, and national burden of cardiovascular disease attributable to high body mass index from 1990 to 2021 and projection to 2045.Frontiers in endocrinology · 2025Article
- Economic Evaluation of a Personalized Nutrition Plan Based on Omic Sciences Versus a General Nutrition Plan in Adults with Overweight and Obesity: A Modeling Study Based on Trial Data in Denmark.PharmacoEconomics - open · 2024Article
- Perspective: A Conceptual Framework for Adaptive Personalized Nutrition Advice Systems (APNASs).Advances in nutrition (Bethesda, Md.) · 2023Article
- Artificial intelligence and obesity management: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2023.Obesity pillars · 2023Article
- Machine Learning in Nutrition Research.Advances in nutrition (Bethesda, Md.) · 2022Article
- Perspective: Novel Approaches to Evaluate Dietary Quality: Combining Methods to Enhance Measurement for Dietary Surveillance and Interventions.Advances in nutrition (Bethesda, Md.) · 2022Article
- Metabotyping for Precision Nutrition and Weight Management: Hype or Hope?Current nutrition reports · 2022Review
- Individual differences in the effects of the ACTION-PAC intervention: an application of personalized medicine in the prevention and treatment of obesity.Journal of behavioral medicine · 2022Article
- Perspective: Application of N-of-1 Methods in Personalized Nutrition Research.Advances in nutrition (Bethesda, Md.) · 2021Review
- Article
- Scientific challenges for precision public health.Journal of epidemiology and community health · 2020Review
- Perspective: Guiding Principles for the Implementation of Personalized Nutrition Approaches That Benefit Health and Function.Advances in nutrition (Bethesda, Md.) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-income countries are experiencing an obesity epidemic that follows a socioeconomic gradient, affecting groups of lower socioeconomic status disproportionately. Recent clinical findings have suggested new perspectives for the prevention and treatment of obesity, using personalized dietary approaches. Precision nutrition (PN), also called personalized nutrition, has been developed to deliver more preventive and practical dietary advice than 'one-size-fits-all' guidelines. With interventions becoming increasingly plausible at a large scale thanks to artificial intelligence and smartphone applications, some have begun to view PN as a novel way to deliver the right dietary intervention to the right population. We argue that large-scale PN, if taken alone, might be of limited interest from a public health perspective. Building on Geoffrey Rose's theory regarding the differences in individual and population causes of disease, we show that large-scale PN can only address some individual causes of obesity (causes of cases). This individual-centred approach is likely to have a small impact on the distribution of obesity at a population level because it ignores the population causes of obesity (causes of incidence). The latter are embedded in the populations' social, cultural, economic and political contexts that make environments obesogenic. Additionally, the most socially privileged groups in the population are the most likely to respond to large-scale PN interventions. This could have the undesirable effect of widening social inequalities in obesity. We caution public health actors that interventions based only on large-scale PN are unlikely, despite current expectations, to improve dietary intake or reduce obesity at a population level.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.