Multicomponent (bio)markers for obesity risk prediction: a scoping review protocol

Show simple item record Vahid, Farhad Dessenne, Coralie Tur, Josep A. Bouzas, Cristina Devaux, Yvan Malisoux, Laurent Monserrat-Mesquida, Margalida Sureda, Antoni Desai, Mahesh S. Turner, Jonathan D. Lamy, Elsa Perez-Jimenez, Maria Ravn-Haren, Gitte Andersen, Rikke Forberger, Sarah Nagrani, Rajini Fontefrancesco, Michele Filippo Onorati, Maria Giovanna Bonetti, Gino Gabriel de-Magistris, Tiziana Bohn, Torsten Ouzzahra, Yacine 2024-03-12T13:25:52Z 2024-03-12T13:25:52Z
dc.description.abstract [eng] Introduction Despite international efforts, the number of individuals struggling with obesity is still increasing. An important aspect of obesity prevention relates to identifying individuals at risk at early stage, allowing for timely risk stratification and initiation of countermeasures. However, obesity is complex and multifactorial by nature, and one isolated (bio)marker is unlikely to enable an optimal risk stratification and prognosis for the individual; rather, a combined set is required. Such a multicomponent interpretation would integrate biomarkers from various domains, such as classical markers (eg, anthropometrics, blood lipids), multiomics (eg, genetics, proteomics, metabolomics), lifestyle and behavioural attributes (eg, diet, physical activity, sleep patterns), psychological traits (mental health status such as depression) and additional host factors (eg, gut microbiota diversity), also by means of advanced interpretation tools such as machine learning. In this paper, we will present a protocol that will be employed for a scoping review that attempts to summarise and map the state-of-the-art in the area of multicomponent (bio)markers related to obesity, focusing on the usability and effectiveness of such biomarkers. Methods and analysis PubMed, Scopus, CINAHL and Embase databases will be searched using predefined key terms to identify peer-reviewed articles published in English until January 2024. Once downloaded into EndNote for deduplication, CADIMA will be employed to review and select abstracts and full-text articles in a two-step procedure, by two independent reviewers. Data extraction will then be carried out by several independent reviewers. Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews and Peer Review of Electronic Search Strategies guidelines will be followed. Combinations employing at least two biomarkers from different domains will be mapped and discussed. Ethics and dissemination Ethical approval is not required; data will rely on published articles. Findings will be published open access in an international peer-reviewed journal. This review will allow guiding future directions for research and public health strategies on obesity prevention, paving the way towards multicomponent interventions.
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dc.relation.isformatof Reproducció del document publicat a:
dc.relation.ispartof Bmj Open, 2024, vol. 14, num. 3, p. e083558-1-e083558-7
dc.rights cc-by (c) Vahid, Farhad et al., 2024
dc.subject.classification 57 - Biologia
dc.subject.classification Ciències de la salut
dc.subject.other 57 - Biological sciences in general
dc.subject.other Medical sciences
dc.title Multicomponent (bio)markers for obesity risk prediction: a scoping review protocol
dc.type info:eu-repo/semantics/article
dc.type info:eu-repo/semantics/publishedVersion 2024-03-12T13:25:52Z
dc.rights.accessRights info:eu-repo/semantics/openAccess

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