OBJECTIVE: To describe the solutions adopted in the multiple steps of the use of multivariate techniques to obtain a dietary pattern (DP) concerning: the objective of the studies, the selection of the method for measuring food intake, the criteria for grouping the foods, the number of food groups used, the number of DP obtained, and the nomenclature criteria. METHODS: The articles were selected from MEDLINE and Lilacs scientific databases using the following keywords: "dietary patterns" versus "factor analysis"; "principal components analysis"; "cluster analysis" and "reduced regression rank." The initial search resulted in 1,752 articles. After inclusion and exclusion criteria, 189 publications were selected. RESULTS: The following aspects were relevant among the studies: the prevalence of the principal component analysis (PCA); the prevalence of the use of 4 to 5 DPs in the studies of association with health outcomes; the use of 30 or more food groups from the food frequency questionnaire (FFQ); the prevalence of studies that associated DPs with health outcomes and socioeconomic factors; and the heterogeneity of criteria used throughout the analytical stages of the multivariate techniques. CONCLUSION: The heterogeneity between the publications concentrates on the criteria for food grouping, the nomenclature, and the number of dietary patterns calculated, which varied depending on the number of food groups present in these analyses. To understand, apply, and explore in full, the multivariate techniques has become necessary in order to improve the reliability of the results and, consequently, to improve the relationships with health outcomes and socioeconomic factors.
OBJECTIVE: To describe the solutions adopted in the multiple steps of the use of multivariate techniques to obtain a dietary pattern (DP) concerning: the objective of the studies, the selection of the method for measuring food intake, the criteria for grouping the foods, the number of food groups used, the number of DP obtained, and the nomenclature criteria. METHODS: The articles were selected from MEDLINE and Lilacs scientific databases using the following keywords: "dietary patterns" versus "factor analysis"; "principal components analysis"; "cluster analysis" and "reduced regression rank." The initial search resulted in 1,752 articles. After inclusion and exclusion criteria, 189 publications were selected. RESULTS: The following aspects were relevant among the studies: the prevalence of the principal component analysis (PCA); the prevalence of the use of 4 to 5 DPs in the studies of association with health outcomes; the use of 30 or more food groups from the food frequency questionnaire (FFQ); the prevalence of studies that associated DPs with health outcomes and socioeconomic factors; and the heterogeneity of criteria used throughout the analytical stages of the multivariate techniques. CONCLUSION: The heterogeneity between the publications concentrates on the criteria for food grouping, the nomenclature, and the number of dietary patterns calculated, which varied depending on the number of food groups present in these analyses. To understand, apply, and explore in full, the multivariate techniques has become necessary in order to improve the reliability of the results and, consequently, to improve the relationships with health outcomes and socioeconomic factors.
Authors: Hye Ah Lee; Hyo Jeong Hwang; Se Young Oh; Eun Ae Park; Su Jin Cho; Hae Soon Kim; Hyesook Park Journal: Nutrients Date: 2016-12-23 Impact factor: 5.717
Authors: Ewelina Wesołowska; Agnieszka Jankowska; Elżbieta Trafalska; Paweł Kałużny; Mariusz Grzesiak; Jolanta Dominowska; Wojciech Hanke; Gemma Calamandrei; Kinga Polańska Journal: Int J Environ Res Public Health Date: 2019-03-02 Impact factor: 3.390
Authors: Elisabet Fernández-Gómez; Trinidad Luque-Vara; Pablo José Moya-Fernández; María López-Olivares; Miguel Ángel Gallardo-Vigil; Carmen Enrique-Mirón Journal: Nutrients Date: 2020-10-23 Impact factor: 5.717