Machine learning-assisted optimization of dietary intervention against dementia risk

Clinical Snapshot

Key Findings

• P Value: Not specified in abstract

• Effect Size: 36% relative risk reduction (HR 0.64)

• Primary Outcome: All-cause dementia incidence over 10 years

• Nnt Or Sensitivity: Hazard ratio 0.64 comparing highest vs lowest tertiles of MODERN diet adherence

• Confidence Interval: 95% CI: 0.43-0.93

Clinical Application

MODERN score (0-7) appears practical for clinical use, focusing on 8 specific food groups including accessible options like green leafy vegetables and berries Highly relevant to Australian practice given similar dietary patterns and dementia burden. Could inform RACGP guidelines on cognitive health and complement existing Dietary Guidelines for Australians Middle-aged to elderly adults at risk of cognitive decline, particularly those seeking evidence-based dietary guidance for dementia prevention

Abstract

A healthy diet has been associated with a reduced risk of dementia. Here we devised a Machine learning-assisted Optimizing Dietary intERvention against demeNtia risk (MODERN) diet based on data from 185,012 UK Biobank participants, 1,987 of whom developed all-cause dementia over 10 years. We first identified 25 food groups associated with dementia in a food-wide association analysis. Second, we ranked their importance using machine learning and prioritized eight groups (for example, green leafy vegetables, berries and citrus fruits). Finally, we established and externally validated a MODERN score (0-7), which showed stronger associations with lower risk of dementia-related outcomes (hazard ratio comparing highest versus lowest tertiles: 0.64, 95% CI: 0.43-0.93) than the a priori-defined MIND diet (0.75, 0.61-0.92). Across 63 health-related outcomes, the MODERN diet showed particularly significant associations with mental/behavioural disorders. Multimodal neuroimaging, metabolomics, inflammation and proteomics analyses revealed potential pathways and further support the potential of MODERN diet for dementia prevention.

References

1. 1.Chen, S. J., Chen, H., You, J., Chen, S. D., Fu, Y., Zhang, W., Huang, L., Feng, J. F., Gao, X., Cheng, W., Yuan, C., & Yu, J. T. (2025). Machine learning-assisted optimization of dietary intervention against dementia risk. Nature Human Behaviour. https://doi.org/10.1016/j.neuroimage.2020.117002