Balanced diet linked to better brain health and cognition, large-scale study shows

In a recent study published in the journal Nature Mental Health, researchers investigated the brain health domains of individuals identified with four distinct dietary subtypes, namely starch-free, vegetarian, high-protein-low-fiber, and balanced. Using neuroimaging and behavioral, biochemical, and genetic analyses, they found that individuals in the balanced diet subtype showed better cognitive functions and mental health than the others.

Study: Associations of dietary patterns with brain health from behavioral, neuroimaging, biochemical and genetic analyses. Image Credit: Elena Eryomenko / ShutterstockStudy: Associations of dietary patterns with brain health from behavioral, neuroimaging, biochemical and genetic analyses. Image Credit: Elena Eryomenko / Shutterstock


Food liking, a key driver of dietary patterns, significantly influences health outcomes, including chronic diseases and mental health. Understanding its impact on brain health is vital for developing effective dietary interventions to enhance overall well-being. A growing body of evidence suggests that dietary patterns significantly impact cognitive function and mental health.

The relationship between dietary patterns and brain health potentially involves alterations in molecular biomarkers, gut microbiota, and brain structure and function. Links have been observed between high sugar and saturated fat intake to cognitive decline and psychiatric disorders. Furthermore, unhealthy diets, like the Western pattern, are shown to be associated with higher risks of depression and other psychiatric conditions compared to balanced diets rich in plant-based foods. Contrarily, the Mediterranean diet is shown to be associated with better brain health and a reduced risk of neurodegenerative diseases.

Various traditional dietary patterns, including Western, Mediterranean, and vegetarian/plant-based patterns, have emerged based on food quantities, variety, and frequency of consumption. However, the findings on their association with brain health are inconsistent due to variations in study scopes, sample sizes, and criteria for defining dietary patterns, highlighting the need for a standardized classification system and studies across diverse populations. To address this gap, researchers in the present study utilized data-driven methods to identify dietary patterns and their associations with brain health outcomes.

About the study

The present study obtained food-liking data from the United Kingdom (UK) Biobank. A total of 181,990 participants who completed a food-liking questionnaire were included. The mean age of the participants was 70.7 years, and about 57% were female. The data were then analyzed using principal component analysis (PCA) and hierarchical clustering to identify food-liking subtypes. Further, differences in various brain health indicators, including mental health, cognitive function, biomarkers, and brain magnetic resonance imaging (MRI) traits, were assessed among these subtypes using one-way analysis of covariance (ANCOVA). The study included measures of anxiety, depressive symptoms, mental distress, psychotic experiences, self-harm, trauma, and well-being as indicators of brain health.

Longitudinal data on mental disorders were also analyzed using Cox proportional hazards models to examine the differences among the subtypes. Structural equation models (SEMs) were used to examine the relationships between dietary patterns and brain health. Finally, genome-wide association analysis (GWAS) and gene expression analysis were conducted to study the genetic basis of food-liking subtypes and potential biological pathways.

Results and discussion

Four distinct food-liking subtypes were identified among the studied participants: (1) starch-free or low-starch pattern (18.09%), (2) vegetarian pattern (5.54%), (3) high protein and low fiber pattern (19.39%), and (4) balanced pattern (56.98%). Quantitative scores confirmed the robustness of the relationship between food liking and actual food consumption patterns among the individuals.

The balanced pattern, subtype 4, showed the lowest measures for mental health issues and the highest scores for overall well-being and cognitive functions, indicating improved brain health and cognition than the other subtypes. On the other hand, subtypes 2 and 3 showed lower scores in well-being and higher scores in mental health issues. Compared to subtype 4, subtype 3 exhibited reduced gray matter volumes in regions like the postcentral gyrus, indicating potential neurological differences. In contrast, subtype 2 displayed increased volumes in the thalamus and precuneus. Sixteen genes were found to differ between subtype 3 and subtype 4, and they were associated with biological processes linked to mental health and cognition. Further, subtype 3 showed differences in 127 biomarkers and 1,266 single nucleotide polymorphisms as compared to subtype 4.

This large-scale study provides pioneering insights into the intricate relationship between food preferences and brain health, cognition, and mental well-being, offering the potential for targeted interventions and educational practices to promote overall health. However, the study is limited by its reliance on food-liking data rather than actual consumption, potential selection bias in the UK Biobank sample, potential oversimplification of mental health assessment measures, and an incomplete consideration of key dietary components like tryptophan and omega-3/6 fatty acids.


In conclusion, the present study reveals that dietary patterns among the older population may significantly impact mental health, cognitive functions, genetics, and brain imaging. Emphasizing the importance of balanced diets, the findings call for early-age dietary education to promote long-term brain health. Further research is urged to explore the long-term associations between dietary patterns and brain health across various age groups, especially during adolescence and middle age.