Low Cognitive Function Is Strongly Associated with The Intake of EPA and DHA in Adolescent Female Football Players in North Sumatra, Indonesia
Bibliographic record
Abstract
Background: Cognitive function refers to an individual’s ability to process information, influenced by several factors, including genetics, the environment, and key nutrients such as omega-3 fatty acids—specifically Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA). Objective: The purpose of this study was to examine the relationship between EPA and DHA intake on cognitive function of amateur female adolescent football players in North Sumatra in 2024. Methods: The research design used was observational analytic involving cross-sectional design. The total sample that participated was 79 amateur female youth football players by filling out the Montreal Cognitive Assessment (MOCA) questionnaire as a cognitive assessment and filling out the Food Recall for assessing EPA and DHA intake. The analysis used SPSS 29.0 software and the analysis of EPA and DHA food recall used the NutriSurvey application. Results: The results of this study indicate that there is a strong positive correlation between EPA and DHA intake and the cognitive function of amateur female adolescent football players, with a strong correlation value of r = 0.676 ( p < 0.001). Conclusion: Eicosapentaenoic Acid and DHA intakes are strongly correlated with cognitive function in amateur female adolescent football players. Focusing on increasing daily EPA and DHA intakes is expected to improve cognitive function, especially in female adolescent athletes. Keywords: youth, nutrition intake, sport, thinking process, omega 3
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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 | 0.000 | 0.001 |
| 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".