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Protein Intake in NCAA Division 1 Soccer Players: Assessment of Daily Amounts, Distribution Patterns, and Leucine Levels as a Quality Indicator

Kwon, Jun, Nishisaka, Morgan M., McGrath, Alexandra F., Kristo, Aleksandra S., Sikalidis, Angelos K., Reaves, Scott K.·2023·Sports

Abstract

Dietary protein is required to support recovery and adaptation following exercise training. While prior research demonstrates that many athletes meet total daily protein needs, intake seems to be predominantly skewed toward the evening meal. An even distribution of protein doses of ≥0.24 g/kg BW consumed throughout the course of a day is theorized to confer greater skeletal muscle anabolism outcomes compared to a skewed pattern of intake. Protein quality is also an important dietary consideration for athletes, with the amino acid leucine seemingly serving as the primary driver of the postprandial anabolic response. The present study investigates protein consumption characteristics among a cohort of NCAA D1 soccer players and evaluates differences between male and female athletes. Athletes were instructed to complete 3-day food diaries, which were subsequently analyzed and compared to UEFA expert group-issued nutrition guidelines for soccer players. Breakfast, lunch, and dinner accounted for 81.4% of the total daily dietary protein intake. Most athletes (77.8%) ingested optimum amounts of protein at dinner but not at breakfast (11.1%) or lunch (47.2%). In addition, statistically significant sex-based differences in daily dietary protein intake, meal-specific protein amounts, and protein quality measures were detected. Findings indicate suboptimal dietary protein intake practices among the collegiate soccer athletes.

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Metadata

Authors
Kwon, J., Nishisaka, M. M., McGrath, A. F., Kristo, A. S., Sikalidis, A. K., & Reaves, S. K.
Venue
Sports
Publisher
MDPI AG
Published
2023-02-14
Volume
11
Issue
2
Pages
45
ISSN
2075-4663
Cited by
9
References
21
Language
en
Funders
Donor contributions to the Athletics Sports Nutrition Fund ((fund ID: MX202))

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.