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Marching artists are a unique group of athletes whose performance can be influenced by nutrition. Because physical demands are thought to be moderate to high, adequate energy and a variety of nutrient-dense foods are needed. The purpose of this study was to examine diet quality, physical activity, and eating behavior of marching artists across elite and nonelite competition levels. This cross-sectional analysis used the validated National Cancer Institute Diet History Questionnaire II, International Physical Activity Questionnaire, and Eating Behavior Patterns Questionnaire. Diet quality was assessed using the Healthy Eating Index (HEI) 2010. Marching artists who participated in marching band in 2015 were eligible. Those in Drum Corps International (DCI) were considered part of the elite level; all others were considered nonelite. Chi-square analyses assessed associations between categorical variables and competition level, and independent sample t-tests assessed differences between continuous variables among competition level. Participants (n = 323) included 228 (71%) DCI members and 95 (29%) non-DCI members who reported a mean age of 19.8 ± 1.9 years. DCI members reported higher physical activity levels (p < 0.001) and fewer meal-skipping behaviors compared to non-DCI members (p < 0.001). The overall mean HEI score was 58.8 ± 10.3, with no difference between competition levels. Only one participant overall (<1%) met the recommended intake level of whole grains. Additionally, 2% of participants met the sodium restriction recommendation and 7% met the empty calorie upper limit. Suboptimal diet quality combined with high levels of physical activity is a problem for marching artists that should be addressed through carefully planned interventions.

A survey was used to collect anonymous cross-sectional data on demographics, exercise habits, and use of creatine and other supplements by exercisers in civilian (C) and military (M) health clubs. M (n = 133) reported more aerobic training and less use of creatine and protein supplements than C(n = 96, p < .05). Supplement users (SU, n = 194) and nonusers (SNU, n = 35) engaged in similar frequency and duration of aerobic exercise, as well as number of resistance exercise repetitions, but SU completed more sets for each resistance exercise (x̄ ± SE, 5 ± 1) than SNU (3 ± 1, p ≤ .05). Significant (p ≤ .05) associations were observed between SU and resistance training goal of strength (as opposed to endurance), as well as greater frequency of resistance training. Male gender, resistance training goal of strength, lower frequency and duration of aerobic training, and use of protein, ß-hydroxy-ß-methyl butyrate, and androstenedi-one/dehydroepiandrosterone supplements were all associated with creatine use (p < .05). For creatine users, the dose and length of creatine supplementation was 12.2±2.7g•day^·1 for 40 ± 5 weeks. Popular magazines were the primary source of information on creatine (69%) compared to physicians (14%) or dietitians (10%, p ≤ .0001). This study underscores two potential public health concerns: (a) reliance on popular media rather than allied-health professionals for information on creatine, and (b) use of creatine, a popular supplement with unknown long-term effects, in combination with other anabolic supplements of questionable efficacy and/or safety.

Increasing evidence has suggested that physical activity may modulate gut microbiome composition. We investigated associations of long-term regular exercise with gut microbiota among middle-aged and older urban Chinese individuals. Gut microbiota was assessed using 16S ribosomal ribonucleic acid gene sequencing of stool samples from 2,151 participants from the Shanghai Women’s Health Study and Shanghai Men’s Health Study. Participants were free of cancer, diabetes, and cardiovascular diseases at the time of stool sample collection. Physical activity was assessed in repeat surveys between 1996 and 2015 using validated questionnaires. Regular exercise was defined as any type of leisure-time physical activity with a standard metabolic equivalent score >3.0. Stool samples were collected using the 95% ethanol method between 2015 and 2018 with an average of 3.0 years (SD = 0.9) after the latest exposure assessment. General linear regression and permutational multivariate analysis of variance were carried out to evaluate associations of microbial α- and β-diversity with regular exercise participation. Logistic regression and linear regression models were used to evaluate the prevalence and relative abundance of individual taxa in association with regular exercise. Regular exercise was significantly associated with β-diversity (Bray–Curtis and Jaccard dissimilarities, both false discovery rates = 0.03%, 0.12% and 0.09% variance explained, respectively) but not with α-diversity. Relative abundance of genus Ruminococcus was significantly lower among regular exercisers compared with nonexercisers (median relative abundance: 0.64% vs. 0.81%, false discovery rate <0.10). Further studies are needed to validate the findings from this study and evaluate health benefits of regular exercise on gut microbiota.

Precise protein supplementation strategies for muscle improvement are still lacking. The timing or type of protein supplementation has been debated as a window of opportunity to improve muscle mass, strength, and physical performance. We conducted a network meta-analysis of randomized controlled trials with protein supplements and resistance training. PubMed, Web of Science, Cochrane Library, and SPORTDiscus databases were searched until May 1, 2023. We included 116 eligible trials with 4,711 participants that reported on 11 timing and 14 types of protein supplementation. Compared with placebo, protein supplementation after exercise (mean difference [MD]: 0.54 kg [95% confidence intervals 0.10, 0.99] for fat-free mass, MD: 0.34 kg [95% confidence intervals 0.10, 0.58] for skeletal muscle mass) and at night (MD: 2.85 kg [0.49, 5.22] for handgrip strength, MD: 12.12 kg [3.26, 20.99] for leg press strength) was most effective in improving muscle mass and strength, respectively (moderate certainty). Milk proteins (milk, whey protein, yogurt, casein, and bovine colostrum), red meat, and mixed protein were effective for gains in both muscle mass and strength (moderate certainty). No timing or type of protein showed a significant enhancement in physical performance (timed up-to-go test, 6-min walk test, and gait speed). Pre/postexercise and Night are key recommended times of protein intake to increase muscle mass and strength, respectively. Milk proteins are the preferred types of protein supplements for improving muscle mass and strength. Future randomized controlled trials that directly compare the effects of protein timing or types are needed. This trial was registered at International Prospective Register of Systematic Reviews as CRD42022358766.

In the United States, the Dietary Supplement Health and Education Act of 1994 (DSHEA) classified dietary supplements as a subcategory of food, exempting manufacturers from providing premarket evidence of product safety and efficacy. Under DSHEA, agencies such as the U.S. Food and Drug Administration (FDA) cannot inspect supplements until after the products have entered the marketplace. Recognizing that both limited resources and DSHEA prevent the FDA from conducting broad-based inspections on a regular basis, disreputable manufacturers have spiked products with drugs such as anabolic steroids and amphetamines. With contaminated supplements now causing athletes to fail drug tests and, in some instances, threatening public health, it becomes important to examine sources of supplement information. This article reviews 53 studies that have addressed athlete information sources about dietary supplements. It finds that athletes, in general, rely heavily on coaches and trainers as well as friends and family for information. Relative to U.S. athletes, those competing internationally appear more likely to seek information from a physician or nutritionist. The article offers recommendations for individuals and organizations based on the most frequent information sources identified by athletes.