Evaluation of the diet of crossfit participants in a Crossfit affiliate box in Sofia, Bulgaria
Bibliographic record
Abstract
Както при повечето спортове, така и практикуващите CrossFit трябва да съчетават оптимално белтъци, въглехидрати и мазнини, с цел осигуряване на енергийните нужди, поддържането на положителен азотен баланс и по-бързото отстраняване на метаболитните продукти. Целта на настоящото изследване е да се оцени храненето при мъже и жени, практикуващи CrossFit в лицензирана CrossFit зала в София, България, и да се сравни с припоръките при високоинтензивни натоварвания. Методи: изследването е проведено с 26 мъже (на средна възраст 30.6 г.) и 17 жени (на средна възраст 30.3 г.), които попълниха въпросник за хранене. Изчислихме дневния прием на белтъци, въглехидрати и мазнини (гр кг дневно и гр дневно), техните относителни стойности в проценти и енергийния им прием (kcal дневно). Енергийните нужди изчислихме от базовата обмяна, умножен по коефициент на физическа активност. Резултати: Бяха изчислени следните средни консумации гр кг дневно (белтъци: мъже – 1.6±0.48, жени – 1.4±0.34; въглехидрати: мъже – 5.1±2.05, жени – 4.2±1.84; мазнини: мъже – 1.1±0.43, жени –1.2±0.52). Енергийният прием и стойностите на консумираните въглехидрати бяха по-ниски от препоръките за натоварвания с висока интензивност. Заключение: по-ниската консумация на въглехидрати повлиява негативно енергийния прием, но без значителен риск от ефективното протичане на възстановителните процеси дългосрочен план. Библиография: Зайкова, Диляна. Хранителен режим при състезатели по борба класически стил от национално и международно ниво. Предизвикателства и перспективи пред спортната наука, 2017, с. 73-82. Зайкова, Диляна, и Любомир Петров. "Оценка на храненето при спортовете културизъм, вдигане на тежести и силов трибой." Предизвикателства и перспективи пред спортната наука, Специфика на подготовката в различни спортни дисциплини, 2017, с. 58-64. Aerenhouts, Dirk, et al. "Energy and Macronutrient Intake in Adolescent Sprint Athletes: A Follow-up Study." Journal of Sports Sciences, vol. 29, no. 1, 2011, pp. 73-82. American College of Sports Medicine and Academy of Nutrition and Dietics, Dietitians of Canada. ACSM, 2016. Burke, Louise, et al. "Carbohydrates for Training and Competition." Journal of Sports Sciences, vol. 9, 2011, pp. 17-27. Escobar, Kurt, et al. "The Effect of a Moderately Low and High Carbohydrate Intake on Crossfit Performance." International Journal of Exercise Science, vol. 9, no. 3, 2016, pp. 460-470. Glassman, Greg. "Meal Plans." CrossFit Journal, vol. 21, 2004, pp. 1-10. Glassman, Greg. "The CrossFit Training Guide." CrossFit Journal, 2010, pp. 1-115. Gleeson, Michael, et al. "Exercise, Nutrition and Immune Function." Journal of Sports Sciences, vol. 22, 2004, pp. 115-125. Harris, J., and Francis Benedict. A Biometric Study of Basal Metabolism in Man. Carnegie Institute of Washington, 1919. Jäger, Ralf, et al. "International Society of Sports Nutrition Position Stand: Protein and Exercise." Journal of the International Society of Sports Nutrition, vol. 14, 2017, pp. 20. Kerksick, Chad, et al. "ISSN Exercise and Sports Nutrition Review Update: Research and Recommendations." Journal of International Society of Sports Nutrition, vol. 15, 2018, pp. 38. Koehler, Karsten, et al. "Low Energy Availability in Exercising Men is Associated with Reduced Leptin and Insulin but not with Changes in Other Metabolic Hormones." Journal of Sports Sciences, vol. 34, 2016, pp. 1921-1929. Kreider, Richard, et al. "ISSN Exercise & Sport Nutrition Review: Research & Recommendations." Journal of International Society of Sports Nutrition, vol. 2, no. 7, 2010, pp. 7. Loveless, Meredith. "Female Athlete Triad." Current Opinion in Obstetrics & Gynecology, vol. 29, 2017, pp. 301-305. McArdle, William, et al. Exercise Physiology, Nutrition, Energy and Human Performance. Seventh edition, Lippincott Williams & Wilkins, 2010. Miteva, Silvia, et al. "Nutrition and Body Composition of Elite Rhythmic Gymnasts from Bulgaria." International Journal of Sports Science & Coaching, vol. 15, no. 1, 2020, pp. 108-116. Phillips, Stuart, and Luc Van Loon. "Dietary Protein for Athletes: From Requirements to Optimum Adaptation." Journal of Sports Sciences, vol. 29, 2011, pp. 29-38. Prentice, A., and S. Jebb. "Beyond Body Mass Index." Obesity Reviews, vol. 2, no. 3, 2001, pp. 141-147. Schaafsma, Gertjan. "The Protein Digestibility-corrected Amino Acid Score." Journal of Nutrition, vol. 130, 2000, pp. 1865-1867. Sousa, Mónica, et al. "Dietary Strategies to Recover from Exercise-Induced Muscle Damage." International Journal of Food Science and Nutrition, vol. 65, no. 2, 2014, pp. 151-163. Stulnig, Thomas. "The Zone Diet and Metabolic Control in Type 2 Diabetes." Journal of the American College of Nutrition, vol. 34, no. 1, 2015, pp. 39-41. Thomas, Travis, et al. "Nutrition and Athletic Performance." Official Journal of the American College of Sports Medicine, vol. 48, no. 3, 2016, pp. 543-568.
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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 | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".