Nutrition Knowledge and Dietary Adequacy in Powerlifters
Bibliographic record
Abstract
ABSTRACT: Leonhardt, TPM, Chilibeck, PD, Ko, J, and Zello, GA. Nutrition knowledge and dietary adequacy in powerlifters. J Strength Cond Res 38(11): 1924-1932, 2024-Athletes competing in weight categories (e.g., powerlifters) often restrict food intake approaching competition, which may be detrimental to health and performance. Our purpose was to assess the effect of nutrition knowledge, sex, and time (off-season versus precompetition, when athletes often cut weight) on dietary adequacy in powerlifters. Twenty-three powerlifters (10 females; 30.7 ± 11.2 years) completed questionnaires to assess nutrition knowledge and dietary adequacy. Athletes with higher nutrition knowledge consumed more fruits and nuts and less vitamin B2, B3 across all time points ( p < 0.05) and a greater number (73%) were above the recommended dietary allowance for vitamin D compared with athletes with lower nutrition knowledge (50%) ( p < 0.05). Male powerlifters with higher nutrition knowledge consumed less alcohol and vitamin A than male powerlifters with lower nutrition knowledge ( p < 0.05). Female powerlifters with higher nutrition knowledge consumed less sugar and beverage calories than female powerlifters with lower nutrition knowledge ( p < 0.05). Intake of alcohol and carbohydrate decreased, and meat calories increased from off-season to precompetition ( p < 0.05). Male powerlifters increased B-vitamins, whereas female powerlifters decreased B-vitamin and sugar consumption approaching competition ( p < 0.05). Male powerlifters increased water consumption versus female powerlifters approaching competition (sex × time, p < 0.05). There was no effect of nutrition knowledge on dietary changes approaching competition. Nutrition knowledge, sex, and competitive season affect dietary intake of powerlifters. A higher nutrition knowledge predicts a higher intake of some foods and nutrients important for health and performance. Female powerlifters should pay close attention to the intake of B-vitamins and water before competitions when many are trying to cut weight.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".