Statistical analysis
All statistical analyses and visualisations were performed in RStudio [Excluding the metagenomic and metabolomic data, changes from baseline within study phases and differences between study phases were assessed using mixed-effects models. In all models, age, BMI, habitual alcohol intake and diet order were included as fixed effects, with the participant as the random effect.For gut microbial analysis, Bray–Curtis dissimilarity was performed to assess beta diversity and ordination plots generated for visualisation. Differences within and between study phases in beta diversity were compared using a permutational multivariate analysis of variance. Alpha diversity was measured using Shannon index, inverse Simpson index, Fisher’s index and species richness (CHAO1 estimates). As microbiome sequencing data can contain a considerable number of zeros, we applied geometric mean of pairwise ratio (GMPR), a normalization method for zero-inflated data [For metabolomics, multivariate statistical analysis was performed using MetaboAnalyst 5.0 [For all statistical analyses, a 