Advances in methods for characterising dietary patterns: a scoping review.

ABSTRACT: There is a growing focus on understanding the complexity of dietary patterns and how they relate to health and other factors. Approaches that have not traditionally been applied to characterise dietary patterns, such as latent class analysis and machine learning algorithms, may offer opportunities to characterise dietary patterns in greater depth than previously considered. However, there has not been a formal examination of how this wide range of approaches has been applied to characterise dietary patterns. This scoping review synthesised literature from 2005 to 2022 applying methods not traditionally used to characterise dietary patterns, referred to as novel methods. MEDLINE, CINAHL and Scopus were searched using keywords including latent class analysis, machine learning and least absol

SUBMITTER: Hutchinson JM 

PROVIDER: S-EPMC12198347 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature