A systematic review of interventions targeting modifiable factors that impact dietary intake in athletes.

Appropriate dietary intake has been found to positively impact athletes' performance, body composition and recovery from exercise. Strategies to optimise dietary intake often involve targeting one or more of the many factors that are known to influence dietary intake. This review aims to investigate the types and effectiveness of interventions used to impact modifiable factors of dietary intake in athletes. MEDLINE, CINAHL, SPORTDiscus and Web of Science were searched from inception to May 2022 for intervention studies that measured dietary intake with a quantitative tool and explored at least one factor thought to influence the dietary intake of adult athletes. Study quality was assessed using the ADA Quality Criteria Checklist: Primary Research. Twenty-four studies were included. The most common interventions focused on nutrition education (n 10), macronutrient adjustment (n 7) and physical activity (n 5). The three most common factors thought to influence dietary intake addressed were nutrition knowledge (n 12), hunger and appetite (n 8), and body composition (n 4). Significant changes in dietary intake were found in sixteen studies, with nutrition education interventions returning significant results in the largest proportion of studies (n 8). Study quality within this review was mostly average (n 4 < 50 %, n 19 50-80 %, n 1 > 80 %). As studies included were published between 1992 and 2021, interventions and factors explored in older studies may require up-to-date research to investigate possible differences in results due to time-related confounders.

Nutritional intake in high-performance para athletes.

OBJECTIVE: This study aimed to describe the eating habits of para-athletes who attended a specialized training center in Brazil. METHODS: Participants were recruited from the Sports Training Center at the Universidade Federal de Minas Gerais, Brazil. Energy, macronutrient (expressed in absolute terms and relative to body weight), fiber, cholesterol, and micronutrient intakes were assessed via a food frequency questionnaire, based on intakes over the preceding 12 mo. Sociodemographic factors were assessed using a purpose-designed survey, which included self-reported weight and height. Differences in nutrient intake based on sex, age, body mass index, and sporting factors were evaluated. RESULTS: A total of 30 para-athletes (in para athletics, para-powerlifting, para-swimming, and para-taekwondo) were included in the study. The median total energy intake was 4089 (2855-5829) kcal. The median consumption of carbohydrates, proteins, and fats was 512.3 (358.7-853.5), 184.5 (118.5-246.4), and 137.1 (96.8-189.5) g/d, respectively. Adolescent athletes had higher protein intakes than adult athletes (P = 0.02). Para-athletes with a longer sports career had lower consumption of fiber (P = 0.01) and thiamine (P = 0.02). Participants with a higher body mass index had higher intake of alcohol (P = 0.04) and monounsaturated fats (P = 0.01). Higher consumption of alcohol was also reported by older para-athletes (P = 0.02). CONCLUSIONS: We identified a higher saturated fat intake in male than in female para-athletes as well as higher protein intake (g/kg) in younger compared with older athletes. In addition, sociodemographic characteristics influenced the dietary intake of some para-athletes, such as length of sports career, age, and income.

Overweight and Obesity: The Interplay of Eating Habits and Physical Activity.

The prevalence of overweight and obesity has been steadily increasing over the last 50 years, with worldwide obesity rates tripling since 1975, thus reaching pandemic proportions [...].

A systematic review update of athletes' nutrition knowledge and association with dietary intake.

Athletes' dietary intakes sometimes do not meet sports nutrition guidelines. Nutrition knowledge (NK) is one factor that may influence dietary intake, but NK measurement tools are often outdated or unvalidated, and results regarding athletes' NK are equivocal. The aims of this systematic review were to update previous systematic reviews by examining athletes' NK and to assess the relationship between athletes' general NK, sport NK and dietary intake. MEDLINE, CINAHL, Scopus, SPORTDiscus, Web of Science and Cochrane were searched for studies published between November 2015 and November 2020 that provided a quantitative measure of NK and described the NK tool used. Twenty-eight studies were included, study quality was assessed using JBI checklists and data on NK score and diet intake was extracted. Eight studies utilised validated, up-to-date NK measurement tools. Mean general and sport NK% scores varied between 40·2% ± 12·4 and 70 % ± 9. Mean protein and carbohydrate consumption was 1·1-3·4 g/kg.bw/d and 2·4-4·6 g/kg.bw/d, respectively. Weak-to-moderate, positive associations were found between NK and positive dietary behaviours. Due to a wide variety of NK measurement tools used, it is difficult to synthesise results to determine overall NK in athletes. Overall, there appears to be a low standard of knowledge. Quality of measurement tools for NK has improved but remains an issue. Future studies should use relevant, current validated NK tools or validate tools in their study population. More research is needed into the relationship between NK and other modifiable factors influencing dietary intake.

Modifications to the nutrition for sport knowledge questionnaire (NSQK) and abridged nutrition for sport knowledge questionnaire (ANSKQ).

New evidence and feedback from colleagues have led to modifications to the Nutrition for Sport Knowledge Questionnaire (NSKQ) and Abridged Nutrition for Sport Knowledge Questionnaire (ANSKQ). The changes predominately affect questions regarding the nutrient content of foods, protein recommendations and the legality of supplements. Some English language edits have also been made.

Development and validation of a brief general and sports nutrition knowledge questionnaire and assessment of athletes' nutrition knowledge.

BACKGROUND: The 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. METHODS: Rasch 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). RESULTS: Validation - 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). CONCLUSIONS: The A-NSKQ is a valid and reliable, brief questionnaire designed to assess general NK (GNK) and SNK.

The nutrition for sport knowledge questionnaire (NSKQ): development and validation using classical test theory and Rasch analysis.

BACKGROUND: Appropriate 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. METHODS: An 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. RESULTS: The 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. CONCLUSIONS: The 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.

Developing and validating a nutrition knowledge questionnaire: key methods and considerations.

OBJECTIVE: To outline key statistical considerations and detailed methodologies for the development and evaluation of a valid and reliable nutrition knowledge questionnaire. DESIGN: Literature on questionnaire development in a range of fields was reviewed and a set of evidence-based guidelines specific to the creation of a nutrition knowledge questionnaire have been developed. The recommendations describe key qualitative methods and statistical considerations, and include relevant examples from previous papers and existing nutrition knowledge questionnaires. Where details have been omitted for the sake of brevity, the reader has been directed to suitable references. RESULTS: We recommend an eight-step methodology for nutrition knowledge questionnaire development as follows: (i) definition of the construct and development of a test plan; (ii) generation of the item pool; (iii) choice of the scoring system and response format; (iv) assessment of content validity; (v) assessment of face validity; (vi) purification of the scale using item analysis, including item characteristics, difficulty and discrimination; (vii) evaluation of the scale including its factor structure and internal reliability, or Rasch analysis, including assessment of dimensionality and internal reliability; and (viii) gathering of data to re-examine the questionnaire's properties, assess temporal stability and confirm construct validity. Several of these methods have previously been overlooked. CONCLUSIONS: 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.