Exploration of Functional Food Consumption in Older Adults in Relation to Food Matrices, Bioactive Ingredients, and Health
Bibliographic record
Abstract
The functional food industry is expanding, yet research into consumer perceptions of functional foods is limited. Older adults could benefit from functional foods due to age-related food and health issues. This research gathered information about functional foods from community-dwelling older adults (n = 200) who completed a researcher-administered questionnaire about consumption, food matrices, bioactive ingredients, and health areas addressed through functional foods. Overall prevalence of functional food consumption was found to be 93.0%. Commonly consumed foods included yogurt with probiotics (56.0%), eggs with omega-3 fatty acids (37.0%), and bread with fiber (35.5%). Functional food matrices primarily consumed were yogurt (51.5%), bread (44.0%), and cereal (40.0%). The primary functional food bioactive consumed was dietary fiber (79.5%). Most participants (86.2%) indicated that they consume functional foods to improve health, and the major areas specified were osteoporosis/bone health (67.5%), heart disease (61.0%), and arthritis (55.0%). These results inform health professionals regarding the potential of functional foods to support health among older adults.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".