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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/67382

    Título
    Nutritional and lifestyle features in a Mediterranean cohort: An epidemiological instrument for categorizing metabotypes based on a computational algorithm
    Autor
    García Perea, Aquilino
    Fernández Cruz, Edwin
    de la O Pascual, Victor
    Gonzalez Zorzano, Eduardo
    Moreno Aliaga, María J.
    Tur, Josep A.
    Martínez Hernández, José AlfredoAutoridad UVA Orcid
    Año del Documento
    2024
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Medicina, 2024, Vol. 60, Nº. 4, 610
    Zusammenfassung
    Background and Objectives: Modern classification and categorization of individuals’ health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers’ health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. Materials and Methods: A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. Results: A total of 46.4% of the sample (n = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). Conclusions: The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies.
    Materias (normalizadas)
    Metabotype
    Lifestyles assessment
    Healthcare
    Precision nutrition
    Machine learning
    Cluster
    Materias Unesco
    32 Ciencias Médicas
    3212 Salud Publica
    3206 Ciencias de la Nutrición
    1203.17 Informática
    ISSN
    1648-9144
    Revisión por pares
    SI
    DOI
    10.3390/medicina60040610
    Patrocinador
    Instituto de Salud Carlos III, CIBER de Fisiopatología de la Obesidad y Nutrición (CIBEROBN) y Fondo Europeo de Desarrollo Regional (FEDER) - (grants CB12/03/30038; CB22/03/00068; CB12/03/30002)
    Version del Editor
    https://www.mdpi.com/1648-9144/60/4/610
    Propietario de los Derechos
    © 2024 The authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/67382
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP52 - Artículos de revista [181]
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    Dateien zu dieser Ressource
    Nombre:
    Nutritional-and-Lifestyle-Features.pdf
    Tamaño:
    1.354Mb
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