ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2024
Identifying dietary consumption patterns from survey data: a Bayesian nonparametric latent class model.
Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A Bayesian mixture model approach to examining neighbourhood social determinants of health in endometrial cancer care in Massachusetts.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2026Article
- A social-ecological trap theory-informed investigation of dietary patterns in southwestern Madagascar.Frontiers in nutrition · 2026Article
- baysc: An R package for Bayesian survey clustering.Journal of open source software · 2026Article
- TREE-REGULARIZED BAYESIAN LATENT CLASS ANALYSIS FOR IMPROVING WEAKLY SEPARATED DIETARY PATTERN SUBTYPING IN SMALL-SIZED SUBPOPULATIONS.The annals of applied statistics · 2025Article
- Article
- Examining Generalizability of Nutrient-Based Food Patterns and Their Cross-Sectional Associations with Cardiometabolic Health for Hispanic/Latino Adults in the US: Results from the National Health and Nutrition Examination Survey (NHANES) and the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).medRxiv : the preprint server for health sciences · 2023Article
- Racial and ethnic heterogeneity in diets of low-income adult females in the United States: results from National Health and Nutrition Examination Surveys from 2011 to 2018.The American journal of clinical nutrition · 2023Observational
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Dietary assessments provide the snapshots of population-based dietary habits. Questions remain about how generalisable those snapshots are in national survey data, where certain subgroups are sampled disproportionately. We propose a Bayesian overfitted latent class model to derive dietary patterns, accounting for survey design and sampling variability. Compared to standard approaches, our model showed improved identifiability of the true population pattern and prevalence in simulation. We focus application of this model to identify the intake patterns of adults living at or below the 130% poverty income level. Five dietary patterns were identified and characterised by reproducible code/data made available to encourage further research.
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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.