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food components
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How do the indices based on the EAT-Lancet recommendations ... medrxiv.org May 14, 2024 11 facts
claimDietary indices used to measure adherence to EAT-Lancet recommendations vary primarily in their scoring systems, food components, units, energy adjustments, and cut-off points.
claimDietary indices for EAT-Lancet adherence have valid unidimensional structures, meaning the combination of food components within each index accurately reflects the same construct, supporting the use of total scores.
claimDietary indices that assess food components with quantitative scoring captured dietary variability, were less dependent on energy intake, and converged to a large extent with nutritional indicators.
procedureTo assess the homogeneity of food components within dietary indices, Pearson’s correlation is used for quantitative indices, polychoric correlation for semi-quantitative scales, and tetrachoric correlation for dichotomous data.
referenceThe EAT-Lancet Index (ELI) consists of 14 food components divided into 7 positive components (emphasized foods) and 7 negative components (limited foods).
referenceThe EAT-Lancet Diet Score (ELDS) consists of 14 food components and uses a binary scoring system where one point is assigned to each component for meeting recommended intakes in grams per day without energy adjustment.
claimIt is recommended that the use of total scores in dietary indices be complemented by a detailed analysis of the food components.
referenceThe EAT-Lancet Diet Index (ELD-I) assesses the proximity of a diet to the EAT-Lancet reference for 14 food components using a quantitative scoring system.
measurementELD-I, PHDI, and WISH explain the variability of food components at 57%, 47%, and 32% respectively, supporting their structural validity.
referenceThe Healthy and Sustainable Diet Index (HSDI) assesses compliance with EAT-Lancet recommendations using a binary scoring system based on the percentage of energy intake from 13 food components.
procedureStructural equation modelling (SEM) was used to test the structural validity of the indices, using maximum likelihood estimation to determine model fit when predicting correlations among food components through a single underlying continuous latent variable (total index score).