Dairy intake and cognitive function in Canadian older adults
Bibliographic record
Abstract
Background: Dietary intake is one of the modifiable factors that may affect older adults’ cognitive function in their later years. Few research has considered the potential role of dairy foods on cognitive function. Methods: Across-sectional study was undertaken in 2014. Cognitive function was assessed using The Montreal Cognitive Assessment (MoCA), Rey Complex Figure Test and Recognition Trial (RCFT), Trail-Making Test (TMT), Victoria Stroop Test (VST) and the Digit Span Test (DST). Dietary intake was assessed via estimated 5-day food intake records and analyzed for saturated fat, vitamin D and calcium. Results: A total of 32 participants (8 males and 24 females) (average age= 70.59± 7.07 years; BMI=27.59±4.45 kg/m^2) completed the study. No differences were found between the group who consumed However, a number of associations were found between the nutrients (vitamin D, saturated fat, calcium) found in dairy foods and cognitive performance. A positive correlation was found between the level of vitamin D and the RCFT [r=0.367], the DST [r=0.390], and the MoCA [r=0.362]. Also, a negative correlation was found between the level of saturated fat and performance on the RCFT [r=-0.361]. However, no association was found between calcium level in dairy foods and performance on any of the cognitive tasks. Conclusion: Consumption of dairy foods is associated with better performance on cognitive tasks but underlying mechanisms are still to be determined.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".