Context: Nutrition knowledge can influence dietary choices and impact on athletic performance. Valid and reliable measures are needed to assess the nutrition knowledge of athletes and coaches. Objectives: (1) To systematically review the published literature on nutrition knowledge of adult athletes and coaches and (2) to assess the quality of measures used to assess nutrition knowledge. Data Sources: MEDLINE, CINAHL, SPORTDiscuss, Web of Science, and SCOPUS. Study Selection: 36 studies that provided a quantitative measure of nutrition knowledge and described the measurement tool that was used were included. Data extraction: Participant description, questionnaire description, results (mean correct and responses to individual items), study quality, and questionnaire quality. Data synthesis: All studies were of neutral quality. Tools used to measure knowledge did not consider health literacy, were outdated with regards to consensus recommendations, and lacked appropriate and adequate validation. The current status of nutrition knowledge in athletes and coaches is difficult to ascertain. Gaps in knowledge also remain unclear, but it is likely that energy density, the need for supplementation, and the role of protein are frequently misunderstood. Conclusions: Previous reports of nutrition knowledge need to be interpreted with caution. A new, universal, up-to-date, validated measure of general and sports nutrition knowledge is required to allow for assessment of nutrition knowledge.

BackgroundAppropriate dietary intake can have a significant influence on athletic performance. There is a growing consensus on sports nutrition and professionals working with athletes often provide dietary education. However, due to the limitations of existing sports nutrition knowledge questionnaires, previous reports of athletes’ nutrition knowledge may be inaccurate.MethodsAn updated questionnaire has been developed based on a recent review of sports nutrition guidelines. The tool has been validated using a robust methodology that incorporates relevant techniques from classical test theory (CTT) and Item response theory (IRT), namely, Rasch analysis.ResultsThe final questionnaire has 89 questions and six sub-sections (weight management, macronutrients, micronutrients, sports nutrition, supplements, and alcohol). The content and face validity of the tool have been confirmed based on feedback from expert sports dietitians and university sports students, respectively. The internal reliability of the questionnaire as a whole is high (KR = 0.88), and most sub-sections achieved an acceptable internal reliability. Construct validity has been confirmed, with an independent T-test revealing a significant (p < 0.001) difference in knowledge scores of nutrition (64 ± 16%) and non-nutrition students (51 ± 19%). Test-retest reliability has been assured, with a strong correlation (r = 0.92, p < 0.001) between individuals’ scores on two attempts of the test, 10 days to 2 weeks apart. Three of the sub-sections fit the Rasch Unidimensional Model.ConclusionsThe final version of the questionnaire represents a significant improvement over previous tools. Each nutrition sub-section is unidimensional, and therefore researchers and practitioners can use these individually, as required. Use of the questionnaire will allow researchers to draw conclusions about the effectiveness of nutrition education programs, and differences in knowledge across athletes of varying ages, genders, and athletic calibres.Electronic supplementary materialThe online version of this article (doi:10.1186/s12970-017-0182-y) contains supplementary material, which is available to authorized users.

Sports nutrition professionals aim to influence nutrition knowledge, dietary intake and body composition to improve athletic performance. Understanding the interrelationships between these factors and how they vary across sports has the potential to facilitate better-informed and targeted sports nutrition practice. This observational study assessed body composition (DXA), dietary intake (multiple-pass 24-hr recall) and nutrition knowledge (two previously validated tools) of elite and subelite male players involved in two team-based sports; Australian football (AF) and soccer. Differences in, and relationships between, nutrition knowledge, dietary intake and body composition between elite AF, subelite AF and elite soccer players were assessed. A total of 66 (23 ± 4 years, 82.0 ± 9.2 kg, 184.7 ± 7.7 cm) players participated. Areas of weaknesses in nutrition knowledge are evident (57% mean score obtained) yet nutrition knowledge was not different between elite and subelite AF and soccer players (58%, 57% and 56%, respectively, p > .05). Dietary intake was not consistent with recommendations in some areas; carbohydrate intake was lower (4.6 ± 1.5 g/kg/day, 4.5 ± 1.2 g/kg/day and 2.9 ± 1.1 g/kg/day for elite and subelite AF and elite soccer players, respectively) and protein intake was higher (3.4 ± 1.1 g/kg/day, 2.1 ± 0.7 g/kg/day and 1.9 ± 0.5 g/kg/day for elite and subelite AF and elite soccer players, respectively) than recommendations. Nutrition knowledge was positively correlated with fat-free soft tissue mass (n = 66; r = .051, p = .039). This insight into known modifiable factors may assist sports nutrition professionals to be more specific and targeted in their approach to supporting players to achieve enhanced performance.

The measurement of nutrition knowledge is an important consideration for individuals working in the nutrition field. Improved methods in the development of nutrition knowledge questionnaires, such as the use of factor analysis or Rasch analysis, will enable more confidence in reported measures of nutrition knowledge.

Background: to develop sport-specific and effective dietary advice, it is important to understand the dietary intakes of team sport athletes. This systematic literature review aims to (1) assess the dietary intakes of professional and semi-professional team sport athletes and (2) to identify priority areas for dietetic intervention. Methods: an extensive search of MEDLINE, Sports DISCUS, CINAHL, Web of Science, and Scopus databases in April–May 2018 was conducted and identified 646 studies. Included studies recruited team sport, competitive (i.e., professional or semi-professional) athletes over the age of 18 years. An assessment of dietary intake in studies was required and due to the variability of data (i.e., nutrient and food group data) a meta-analysis was not undertaken. Two independent authors extracted data using a standardised process. Results: 21 (n = 511) studies that assessed dietary intake of team sport athletes met the inclusion criteria. Most reported that professional and semi-professional athletes’ dietary intakes met or exceeded recommendations during training and competition for protein and/or fat, but not energy and carbohydrate. Limitations in articles include small sample sizes, heterogeneity of data and existence of underreporting. Conclusions: this review highlights the need for sport-specific dietary recommendations that focus on energy and carbohydrate intake. Further exploration of factors influencing athletes’ dietary intakes including why athletes’ dietary intakes do not meet energy and/or carbohydrate recommendations is required.

BackgroundSports Dietitians aim to assist in improving performance by developing nutrition knowledge (NK), enhancing dietary intake and optimising body composition of athletes. In a high-pressure environment, it is important to identify factors that may compromise an athlete’s nutrition status. Body composition assessments are regularly undertaken in sport to provide feedback on training adaptions; however, no research has explored the impact of these assessments on the dietary intake of professional athletes.MethodsThis cross-sectional study assessed dietary intake (7-day food diary), nutrition knowledge (Nutrition for Sport Knowledge Questionnaire) and body composition (Dual-energy X-ray absorptiometry) of 46 professional male Australian football (AFL) athletes during a 2017 pre-season training week (7 days) where body composition assessments were undertaken. Dietary intake was assessed against International Olympic Committee recommendations for professional athletes.ResultsOverall, no athlete met dietary their recommended energy intake (15 ± 1.1 vs. 9.1 ± 1.8 MJ, respectively) or carbohydrate recommendations (6–10 vs. 2.4 ± 0.9 g·kg-1·day-1). Only 54% met protein recommendations. Secondary analyses demonstrated significant associations between education status and energy intake (P < 0.04) and vegetable intake (P < 0.03), with higher levels of education being associated with higher intakes. A moderately positive association was observed between NK scores and meeting estimated energy requirements (r = 0.33, P = 0.03). NK scores were also positively associated with protein (r = 0.35, P = 0.02), fibre (r = 0.51, P = 0.001) and calcium intakes (r = 0.43, P = 0.004).ConclusionsThis research identified that the dietary intake of professional AFL athletes during a pre-season training week where body composition assessments were undertaken did not meet current recommendations. Several factors may influence the dietary intake of AFL athletes, including lower education levels, poor NK and dietary intake restriction surrounding body composition assessment. Athletes may require support to continue with performance-based nutrition plans in periods surrounding body composition assessment.

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BackgroundThe Nutrition for Sport Knowledge Questionnaire (NSKQ) is an 89-item, valid and reliable measure of sports nutrition knowledge (SNK). It takes 25 min to complete and has been subject to low completion and response rates. The aim of this study was to develop an abridged version of the NSKQ (A-NSKQ) and compare response rates, completion rates and NK scores of the NSKQ and A-NSKQ.MethodsRasch analysis was used for the questionnaire validation. The sample (n = 181) was the same sample that was used in the validation of the full-length NSKQ. Construct validity was assessed using the known-group comparisons method. Temporal stability was assessed using the test-retest reliability method. NK assessment was cross-sectional; responses were collected electronically from members of one non-elite Australian football (AF) and netball club, using Qualtrics Software (Qualtrics, Provo, UT).ResultsValidation - The A-NSKQ has 37 items that assess general (n = 17) and sports (n = 20) nutrition knowledge (NK). Both sections are unidimensional (Perc5% = 2.84% [general] and 3.41% [sport]). Both sections fit the Rasch Model (overall-interaction statistic mean (SD) = − 0.15 ± 0.96 [general] and 0.22 ± 1.11 [sport]; overall-person interaction statistic mean (SD) = − 0.11 ± 0.61 [general] and 0.08 ± 0.73 [sport]; Chi-Square probability = 0.308 [general] and 0.283 [sport]). Test-retest reliability was confirmed (r = 0.8, P < 0.001 [general] and r = 0.7, P < 0.001 [sport]). Construct validity was demonstrated (nutrition students = 77% versus non-nutrition students = 60%, P < 0.001 [general] and nutrition students = 60% versus non-nutrition students = 40%, P < 0.001 [sport]. Assessment of NK - 177 usable survey responses from were returned. Response rates were low (7%) but completion rates were high (85%). NK scores on the A-NSKQ (46%) are comparable to results obtained in similar cohorts on the NSKQ (49%). The A-NSKQ took on average 12 min to complete, which is around half the time taken to complete the NSKQ (25 min).ConclusionsThe A-NSKQ is a valid and reliable, brief questionnaire designed to assess general NK (GNK) and SNK.Electronic supplementary materialThe online version of this article (10.1186/s12970-018-0223-1) contains supplementary material, which is available to authorized users.