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Identifying and characterizing shared and ethnic background site-specific dietary patterns in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Articolo
Data di Pubblicazione:
2025
Citazione:
Identifying and characterizing shared and ethnic background site-specific dietary patterns in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) / R. De Vito, B. Stephenson, D. Sotres-Alvarez, A. Siega-Riz, J. Mattei, M. Parpinel, B.A. Peters, S.A. Bainter, M.L. Daviglus, L. Van Horn, V. Edefonti. - In: NUTRITION JOURNAL. - ISSN 1475-2891. - 24:1(2025 Dec), pp. 71.1-71.21. [10.1186/s12937-025-01138-0]
Abstract:
Background: A posteriori dietary patterns (DPs) are critical for capturing actual dietary behaviour. However, assessing their reproducibility across (sub)populations requires novel modelling approaches beyond descriptive statistics. Multi-study factor analysis derives DPs that are shared among all studies/subpopulations and those specific to a study or subpopulation of interest. Bayesian implementation of the multi-study factor analysis (BMSFA) is more flexible than frequentist as it imposes fewer assumptions and improves factor selection. Methods: We applied BMSFA to 24-h dietary recalls from the baseline visit (2008–2011) of the US Hispanic Community Health Study/Study of Latinos (n = 16,415). The analysis was conducted on 42 common nutrients to identify shared and subpopulation-specific DPs. Subpopulations were defined based on the cross-classification of ethnic background (Cuban, Dominican Republic, Mexican, Puerto Rican, Central and South American) and study site (Bronx, Chicago, Miami, San Diego) resulting in 12 Ethnic Background Site (EBS) categories. Regression analysis characterized DPs in terms of food groups, overall diet quality, socio-demographic/lifestyle factors, adjusting for survey design. Results: We identified four shared DPs across all EBS categories: Plant-based foods, Processed foods, Dairy products, and Seafood. Additionally, twelve EBS-specific DPs were identified—one for each EBS category. Most EBS-specific DPs were further grouped into overarching profiles: Animal vs. vegetable source, Animal source only, and Poultry vs. dairy products, to capture nuances within animal-based DPs. Puerto Rican background participants from Chicago expressed a strikingly different DP from all others (i.e., high on beta-carotene and low on starch/iron/thiamin). Higher overall diet quality was observed with increasing categories of Plant-based foods, Seafood, and the “Puerto Rican background – Chicago” EBS-specific DP, whereas increasing categories of Dairy products, Processed foods, and the remaining EBS-specific DPs were related to lower diet quality. Compared to non-US-born participants, US-born individuals had significantly higher adjusted mean scores in absolute value for most DPs. Specifically, they exhibited lower adherence to the Plant-based foods and Dairy products DPs but higher adherence to Processed foods, Seafood, and six EBS-specific DPs. Conclusions: The BMSFA successfully captured sources of dietary homogeneity and heterogeneity among US Hispanic/Latino adults across ethnic backgrounds and study sites. The study highlighted the crucial role of nativity on DPs.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Bayesian analysis; Bayesian multi-study factor analysis; Dietary patterns; Factor analysis; Hispanic Community Health Study/Study of Latinos; Hispanics/Latinos; Multi-study factor analysis; Reproducibility of dietary patterns
Elenco autori:
R. De Vito, B. Stephenson, D. Sotres-Alvarez, A. Siega-Riz, J. Mattei, M. Parpinel, B.A. Peters, S.A. Bainter, M.L. Daviglus, L. Van Horn, V. Edefonti
Autori di Ateneo:
EDEFONTI VALERIA CARLA ( autore )
Link alla scheda completa:
https://air.unimi.it/handle/2434/1166775
Link al Full Text:
https://air.unimi.it/retrieve/handle/2434/1166775/3077853/DeVIto_HCHS_wsuppmat.pdf
Progetto:
INDACO: Incorporating Nonadditivity and nonlinearity within the Dietary patterns And Cancer risk association: statistics and machine learning to create novel research Opportunities from dietary assessment to cancer prediction
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Settore MEDS-24/A - Statistica medica
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Realizzato con VIVO | Progettato da Cineca | 25.11.5.0