Dietary index for gut microbiota (DI-GM) and cognitive function: NHANES findings and validation in a Hong Kong cohort with metagenomic data
Bibliographic record
Abstract
BACKGROUND: The diet-gut-microbiota-brain axis is critical for maintaining brain health. The Dietary Index for Gut Microbiota (DI-GM), comprising beneficial and unfavorable components, may serve as a proxy for this connection, yet its association with cognition remains underexplored. METHODS: This study examined the relationship between DI-GM, its components, and cognitive function in older adults using data from the National Health and Nutrition Examination Survey (NHANES). Findings were validated in an independent Hong Kong osteoporosis cohort (OS cohort) with gut metagenomic data to assess of microbiota's mediating role in diet-cognition relationship. Cognitive assessment in NHANES utilized the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST), while the OS cohort employed the Hong Kong version of the Montreal Cognitive Assessment (HK-MoCA). DI-GM was calculated from 24-hour dietary recalls. The diet-cognition associations were assessed by weighted multivariate regressions, supplemented by restricted cubic spline (RCS), subgroup, correlation network, and mediation analyses. RESULTS: Higher DI-GM was significantly associated with better performance on DSST (OR=0.90; 95 % CI: 0.82, 0.99; p = 0.033). The beneficial-to-gut-microbiota score (BGMS) associated with lower psychometric mild cognitive impairment (p-MCI) risk (OR=0.88; 95 % CI: 0.80, 0.98; p = 0.022) and better CERAD immediate and delayed recall and DSST (all p < 0.05). The beneficial-to-gut-microbiota components like dietary fiber demonstrated protective effects across cognitive domains, while refined grains was associated with poorer cognition. In the OS cohort, higher dietary fiber intake correlated with higher HK-MoCA score (p < 0.05) and increased abundance of fermenting bacteria. Among these species, Eubacterium ventriosum mediated the beneficial effect of dietary fiber intake on dementia risk reduction, with an indirect effect of -0.014 (95 % CrI: -0.040, -0.001), accounting for approximately 12.7 % of the total effect. CONCLUSION: Higher adherence to beneficial-to-gut-microbiota dietary patterns, as reflected by DI-GM, was associated with better cognitive function in older adults. These findings highlight the importance of a gut-microbiota-targeted diet in maintaining cognitive health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".