Background: Food frequency questionnaires (FFQs) have been developed and validated for various populations. To our knowledge, however, no FFQ has been validated for young athletes. Here, we investigated whether an FFQ that was developed and validated to estimate dietary intake in middle-aged persons was also valid for estimating that in young athletes. Methods: We applied an FFQ that had been developed for the Japan Public Health Center-based Prospective Cohort Study with modification to the duration of recollection. A total of 156 participants (92 males) completed the FFQ and a 3-day non-consecutive 24-hour dietary recall (24hDR). Validity of the mean estimates was evaluated by calculating the percentage differences between the 24hDR and FFQ. Ranking estimation was validated using Spearman’s correlation coefficient (CC), and the degree of miscategorization was determined by joint classification. Results: The FFQ underestimated energy intake by approximately 10% for both males and females. For 35 nutrients, the median (range) deattenuated CC was 0.30 (0.10 to 0.57) for males and 0.32 (−0.08 to 0.62) for females. For 19 food groups, the median (range) deattenuated CC was 0.32 (0.17 to 0.72) for males and 0.34 (−0.11 to 0.58) for females. For both nutrient and food group intakes, cross-classification analysis indicated extreme miscategorization rates of 3% to 5%. Conclusions: An FFQ developed and validated for middle-aged persons had comparable validity among young athletes. This FFQ might be useful for assessing habitual dietary intake in collegiate athletes, especially for calcium, vitamin C, vegetables, fruits, and milk and dairy products.

The aim of this study was to evaluate the effects of egg white protein compared to carbohydrate intake prior to exercise on fat free mass (FFM), one repetition maximum (1RM) muscle strength and blood biochemistry in female athletes. Thirty healthy female collegiate athletes were recruited for this study and matched by sport type, body fat percentage and 1RM leg curl muscle strength. Participants were randomly divided into two groups: protein group (15.0 g egg white protein; 75 kcal) and carbohydrate group (17.5 g maltodextrin, 78 kcal). Supplements were administered daily at the same time in a double-blind manner prior to training during an 8-week period. Measurements were performed before and after the 8-week regimen. The mean dietary energy intake did not change throughout the study period. FFM and 1RM assessments (i.e., leg curl, leg extension, squat, and bench press) increased in both groups. Furthermore, serum urea and serum citrulline levels after the 8-week regimen increased significantly only in the protein group. Our findings indicated that compared to the carbohydrate supplement, the protein supplement was associated with some changes in protein metabolites but not with changes in body composition or muscle strength.

We evaluated the validity and reproducibility of estimated sugar intakes using a food frequency questionnaire (FFQ) among middle-aged Japanese adults in the Japan Public Health Centre-Based Prospective (JPHC) study. In subsamples of the JPHC study (Cohorts I and II in multiple areas), we computed Spearman’s correlations of FFQ results with urine sugar concentrations and dietary records (DR) for validity; we evaluated correlations between two FFQs for reproducibility. During 1994–1998, participants (Cohort I: n = 27 [men], n = 45 [women]) provided two (spring and fall) 24-h urine samples and completed 7-consecutive-day DR per season (I: n = 99, n = 113; II: n = 168, n = 171) and two FFQs (147 food items) at yearly intervals (I: n = 101, n = 108; II: n = 143, n = 146). Sugar intakes from FFQ were correlated with urinary sugar (de-attenuated correlations: 0.40; 95%CI: 0.19, 0.58). After adjustment for sociodemographic and lifestyle variables, correlations between FFQ and DR for men and women were 0.57 (0.42, 0.69) and 0.41 (0.24, 0.55) (I) and 0.56 (0.44, 0.65) and 0.34 (0.20, 0.47) (II), respectively. Correlations between FFQs for men and women were 0.63 (0.49, 0.73) and 0.55 (0.41, 0.67) (I) and 0.66 (0.55, 0.74) and 0.63 (0.52, 0.72) (II). In conclusion, our study showed moderate FFQ validity and reproducibility for sugar intake evaluation.