Adherence to the EAT-Lancet Diet: Unintended Consequences for the Brain?
Hayley Anne YoungPublished in: Nutrients (2022)
In January 2019, the EAT-Lancet Commission defined a universal reference diet to promote human and environmental health. However, in doing so, the potential consequences for brain health were not considered. Whilst plant-based diets are generally associated with better cognitive and affective outcomes, those that severely limit animal products are not. Therefore, the potential ramifications of the EAT-Lancet diet on cognition, mood, and heart rate variability were considered ( N = 328). Adherence to the Alternative Healthy Eating Index (AHEI) was associated with having a better mood, focused attention, working and episodic memory, and higher heart rate variability. However, when the EAT-Lancet diet was considered, the effects were either smaller or not significant. Cluster analysis identified a dietary style characterised by a strong adherence to the EAT-Lancet recommendation to limit meat intake, representing a sixth of the present sample. This group had a lower Mean Adequacy Ratio (MAR); did not meet the Recommended Nutrient Intake (RNI) for a range of nutrients including protein, selenium, zinc, iron, and folate; and reported a poorer mood. These data highlight the potential unintended consequences of the EAT-Lancet recommendations for nutritional adequacy and affective health in some individuals. There is a need to better optimise the EAT-Lancet diet to support brain health. As we move towards more sustainable diets, these findings emphasise the need to consider how such diets might affect the brain.
Keyphrases
- heart rate variability
- weight loss
- physical activity
- bipolar disorder
- public health
- healthcare
- white matter
- human health
- heart rate
- resting state
- mental health
- health information
- glycemic control
- risk assessment
- functional connectivity
- type diabetes
- heavy metals
- metabolic syndrome
- working memory
- sleep quality
- blood pressure
- social media
- body mass index
- deep learning
- big data
- clinical practice
- brain injury
- artificial intelligence
- oxide nanoparticles