A review of statistical methods for dietary pattern analysis.
Background: Dietary pattern analysis is a promising approach to understanding the complex relationship between diet and health. While many statistical methods exist, the literature predominantly focuses on classical methods such as dietary quality scores, principal component analysis, factor analysi...
| Publicado en: | Nutrition Journal Vol. 20; no. 1; pp. 1 - 19 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
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BioMed Central
4/19/2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=149880485&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 149880485 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14752891 1CYY jtl: Nutrition Journal issn: 14752891 maglogo: N pubinfo: dt: 4/19/2021 vid: 20 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 149880485 149880485 NLM33874970 149880485 10.1186/s12937-021-00692-7 NLM33874970 149880485 ppf: 1 ppct: 18 formats: fmt: @attributes: type: P tig: atl: A review of statistical methods for dietary pattern analysis. aug: au: Zhao, Junkang Li, Zhiyao Gao, Qian Zhao, Haifeng Chen, Shuting Huang, Lun Wang, Wenjie Wang, Tong affil: Department of Health Statistics, School of Public Health, Shanxi Medical University, No.56 Xinjian South Road, 030001, Taiyuan, Shanxi province, China sug: subj: Diet Eating Behavior Factor Analysis Reproducibility of Results Human Ferrans and Powers Quality of Life Index ab: Background: Dietary pattern analysis is a promising approach to understanding the complex relationship between diet and health. While many statistical methods exist, the literature predominantly focuses on classical methods such as dietary quality scores, principal component analysis, factor analysis, clustering analysis, and reduced rank regression. There are some emerging methods that have rarely or never been reviewed or discussed adequately.Methods: This paper presents a landscape review of the existing statistical methods used to derive dietary patterns, especially the finite mixture model, treelet transform, data mining, least absolute shrinkage and selection operator and compositional data analysis, in terms of their underlying concepts, advantages and disadvantages, and available software and packages for implementation.Results: While all statistical methods for dietary pattern analysis have unique features and serve distinct purposes, emerging methods warrant more attention. However, future research is needed to evaluate these emerging methods' performance in terms of reproducibility, validity, and ability to predict different outcomes.Conclusion: Selection of the most appropriate method mainly depends on the research questions. As an evolving subject, there is always scope for deriving dietary patterns through new analytic methodologies. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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