ArticleNutrients2022
Examining the Composition of the Oral Microbiota as a Tool to Identify Responders to Dietary Changes.
Article in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Diet-Oral Microbiota Interactions and Salivary Biomarkers of Nutritional Health: A Narrative Review.Nutrients · 2026Review
- The oral-gut microbiota axis: a link in cardiometabolic diseases.NPJ biofilms and microbiomes · 2025Review
- Association Between Dietary Patterns and Subgingival Microbiota: Results From the Oral Infections, Glucose Intolerance, and Insulin Resistance Study (ORIGINS).Journal of clinical periodontology · 2025Article
- Oral microbiome contributions to metabolic syndrome pathogenesis.Frontiers in microbiology · 2025Review
- Healthier Smile: The Role of Diet and Nutrition in the Prevention and Therapy of Caries, Gingivitis, and Periodontitis.Nutrients · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundThe role of diet and nutrition in the prevention of oral diseases has recently gained increasing attention. Understanding the influence of diet on oral microbiota is essential for developing meaningful prevention approaches to oral diseases, and the identification of typical and atypical responders may contribute to this.
methodsWe used data from an experimental clinical study in which 11 participants were exposed to different dietary regimens in five consecutive phases. To analyse the influence of additional nutritional components, we examined changes in bacterial concentrations measured by culture techniques compared to a run-in phase. A measure of correspondence between the mean and individual patterns of the bacterial composition is introduced.
resultsThe distance measures introduced showed clear differences between the subjects. In our data, two typical and three atypical responders appear to have been identified.
conclusionsThe proposed method is suitable to identify typical and atypical responders, even in small datasets. We recommend routinely performing such analyses.
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