Dietary supplements, sports foods, and ergogenic supplements are consumed to increase performance, recovery, and health, but risk contamination with illegal substances. Third-party testing programs may assist in regulating the purity and safety of supplements, yet athletes' attitudes and use of such programs are not widely reported. This study examined nutritional supplement knowledge, attitudes, and use, as well as the purchase of third-party tested supplements among university student-athletes (
N
= 138). Knowledge of nutritional supplements yielded a median and (IQR) score of 25% (17 to 42%). Sixteen percent of student-athletes said they were knowledgeable about supplements and their effects,
p
< 0.001. All athletes stated they used a dietary supplement or sports food at least once within the last 12 months, and 77% consumed at least one “claimed to be” ergogenic supplement. Sixty-six percent of student-athletes purchased nutritional supplements not provided by the athletic department. Females athletes were more likely to consume a combination of vitamins and single minerals, a larger variety of sports foods, exotic berries, herbs, maca root powder, ribose, ephedra, colostrum, and hydroxy-methyl-buterate (HMB) than males. Over 90% believed it was essential to know if a supplement was third-party tested. However, only 57% stated the supplements bought were third-party tested. No sex differences were found for nutritional supplement knowledge, attitudes, and use of third-party testing programs. Our results indicate a need to improve student-athletes' attitudes toward and knowledge of nutritional supplements, and the initiation of programs to assist in the choosing and consuming of third-party tested supplements.
Our objective was to determine self-reported accuracy of an athletic population using two different urine color (Uc) charts (8-color vs. 7-color Uc chart). After approval by the Institutional Review Board, members of an athletic population (n = 189, 20 (19–22) year old student- or tactical athletes and coaches, with n = 99 males and n = 90 females) scored their Uc using two charts. To determine the diagnostic value of Uc, results were compared with urine concentration (osmolality and urine specific gravity, USG). Uc was scored slightly darker with the 8-color vs. 7-color Uc chart (2.2 ± 1.2 vs. 2.0 ± 1.2, respectively, p < 0.001), with a moderate correlation between charts (r = 0.76, 95% CI: 0.69–0.81). Bland-Altman analysis showed a weak reporting bias (r = 0.15, p = 0.04). The area under the curve for correct urine sample classification ranged between 0.74 and 0.86. Higher accuracy for both methods was found when Uc scores were compared to USG over osmolality, indicated by 4.8–14.8% range in difference between methods. The optimal Uc cut-off value to assess a low vs. a high urine concentration for both Uc charts varied in this study between 1 and ≤2 while accuracy for charts was similar up to 77% when compared to USG.
Context: Urine color (Uc) is used to asses urine concentration when lab techniques are not feasible.
Objective: To compare the accuracy of Uc scoring using four different light conditions and two different scoring techniques with a 7-color Uc chart. Additionally to assess the results' generalizability, a subsample was compared to scores obtained from fresh samples.
Design: Descriptive laboratory study.
Samples: 178 previously frozen urine samples were scored and n=78 samples were compared to its own fresh outcomes.
Main outcome measure: Urine color and accuracy for classifying urine samples were calculated using receiver operating characteristics (ROC) analysis, allowing to compare the diagnostic capacity against a 1.020 urine specific gravity (USG) cut-off and defining optimal Uc cut-off value.
Results: Uc was significantly different between light conditions (P<0.01), with the highest accuracy (80.3%) of correctly classifications of low or high urine concentrations occurring at the brightest light condition. Lower light intensity scored 1.5–2 shades darker on a 7-color Uc scale than bright conditions (P<0.001), with urine color but no further practical differences for accuracy between scoring techniques. Frozen was 0.5–1 shade darker than freshly measured Uc (P<0.004), but they were moderately correlated (r=0.64). A Bland-Altman plot showed that reporting bias mainly affects darker Uc without impacting the diagnostic ability of the method.
Conclusions: Uc scoring, accuracy and Uc cut-off values are affected by lighting condition but not by scoring technique, with higher accuracy and a one-shade lower Uc cut-off value at the brightest light (i.e. LED flashlight).
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