ArticleNutrition journal2017
Stability-based validation of dietary patterns obtained by cluster analysis.
Article in Nutrition journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reproducibility and Validity of A Posteriori Dietary Patterns: A Systematic Review.Advances in nutrition (Bethesda, Md.) · 2020Pooled it
- Data-Driven Clustering Approach to Derive Taste Perception Profiles from Sweet, Salt, Sour, Bitter, and Umami Perception Scores: An Illustration among Older Adults with Metabolic Syndrome.The Journal of nutrition · 2021Trial
- Article
- Omnivorous and plant-based dietary patterns: a comparative analysis using data-driven and index-based approaches.European journal of nutrition · 2026Article
- Imaging-derived neuromuscular ultrasound phenotypes are associated with functional status in amyotrophic lateral sclerosis.Journal of neurology · 2026Article
- Traditional and Non-Traditional Clustering Techniques for Identifying Chrononutrition Patterns in University Students.Nutrients · 2026Article
- Preschoolers in severely food insecure Guatemalan Mayan households consume a monotonous grain-based diet.BMC public health · 2025Article
- Exploration of dietary patterns in southern China: application-based comparison of factor analysis and latent class analysis.Journal of health, population, and nutrition · 2025Article
- Dietary patterns, cooking methods and breast cancer risk in Mexico: An exploratory case-control study.Nutrition and health · 2024Article
- Profiling the socioeconomic characteristics, dietary intake, and health status of Korean older adults for nutrition plan customization: a comparison of principal component, factor, and cluster analyses.Epidemiology and health · 2024Article
- Clusters of carbohydrate-rich foods and associations with type 2 diabetes incidence: a prospective cohort study.Nutrition journal · 2023Article
- Obesogenic diet and metabolic syndrome among adolescents in India: data-driven cluster analysis.BMC cardiovascular disorders · 2023Article
- Population food intake clusters and cardiovascular disease incidence: a Bayesian quantifying of a prospective population-based cohort study in a low and middle-income country.Frontiers in nutrition · 2023Article
- Dietary patterns of 5-year-old children and their correlates: findings from a multi-ethnic Asian cohort.The British journal of nutrition · 2022Article
- Letter to the Editor: on the stability and internal consistency of component-wise sparse mixture regression-based clustering.Briefings in bioinformatics · 2022Article
- The effect of different methods to identify, and scenarios used to address energy intake misestimation on dietary patterns derived by cluster analysis.Nutrition journal · 2021Article
- A review of statistical methods for dietary pattern analysis.Nutrition journal · 2021Review
- Analysis of dietary patterns and nutritional adequacy in lactating women: a multicentre European cohort (ATLAS study).Journal of nutritional science · 2021Article
- Dietary Patterns and Health Outcomes among African American Maintenance Hemodialysis Patients.Nutrients · 2020Article
- Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCluster analysis is a data-driven method used to create clusters of individuals sharing similar dietary habits. However, this method requires specific choices from the user which have an influence on the results. Therefore, there is a need of an objective methodology helping researchers in their decisions during cluster analysis. The objective of this study was to use such a methodology based on stability of clustering solutions to select the most appropriate clustering method and number of clusters for describing dietary patterns in the NESCAV study (Nutrition, Environment and Cardiovascular Health), a large population-based cross-sectional study in the Greater Region (N = 2298).
methodsClustering solutions were obtained with K-means, K-medians and Ward's method and a number of clusters varying from 2 to 6. Their stability was assessed with three indices: adjusted Rand index, Cramer's V and misclassification rate.
resultsThe most stable solution was obtained with K-means method and a number of clusters equal to 3. The "Convenient" cluster characterized by the consumption of convenient foods was the most prevalent with 46% of the population having this dietary behaviour. In addition, a "Prudent" and a "Non-Prudent" patterns associated respectively with healthy and non-healthy dietary habits were adopted by 25% and 29% of the population. The "Convenient" and "Non-Prudent" clusters were associated with higher cardiovascular risk whereas the "Prudent" pattern was associated with a decreased cardiovascular risk. Associations with others factors showed that the choice of a specific dietary pattern is part of a wider lifestyle profile.
conclusionThis study is of interest for both researchers and public health professionals. From a methodological standpoint, we showed that using stability of clustering solutions could help researchers in their choices. From a public health perspective, this study showed the need of targeted health promotion campaigns describing the benefits of healthy dietary patterns.
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