Pattern analysis of vegan eating reveals healthy and unhealthy patterns within the vegan diet.

Abstract

OBJECTIVE\nThis study aimed to identify the types of foods that constitute a vegan diet and establish patterns within the diet. Dietary pattern analysis, a key instrument for exploring the correlation between health and disease was used to identify patterns within the vegan diet.\n\n\nDESIGN\nA modified version of the EPIC-Norfolk food frequency questionnaire (FFQ) was created and validated to include vegan foods and launched on social media.\n\n\nSETTING\nUK participants, recruited online.\n\n\nPARTICIPANTS\nA convenience sample of 129 vegans voluntarily completed the FFQ. Collected data was converted to reflect weekly consumption to enable factor and cluster analyses.\n\n\nRESULTS\nFactor analysis identified four distinct dietary patterns including: 1) convenience, (22%); 2) health conscious, (12%); 3) unhealthy, (9%); and 4) traditional vegan (7%). Whilst two healthy patterns were defined, the convenience pattern was the most identifiable pattern with a prominence of vegan convenience meals and snacks, vegan sweets and desserts, sauces, condiments and fats. Cluster analysis identified three clusters, cluster one convenience (26.8%), cluster two, traditional (22%) and cluster 3 health conscious (51.2%). Clusters one and two consisted of an array of ultra-processed vegan food items. Together, both clusters represent almost half of participants and yielding similar results to the predominant dietary pattern, strengthens the factor analysis.\n\n\nCONCLUSIONS\nThese novel results highlight a need for further dietary pattern studies with full nutrition and blood metabolite analysis in larger samples of vegans to enhance and ratify these results.