Harty, Patrick S.

Energy drinks are a commonly consumed beverage, and studies suggest a possible performance-enhancing effect. A Google Scholar search using the keywords “energy drinks” and “exercise” yields numerous results, underscoring the voluminous research on this topic. However, there are questions regarding the effectiveness and safety of energy drinks. These questions include, but are not limited to: (1) What are the main active ingredients in energy drinks? (2) Do energy drinks assist in weight management? (3) Do energy drinks enhance aerobic performance? (4) Do energy drinks enhance athletic speed? (5) Do energy drinks improve reaction time? (6) Do energy drinks enhance lean tissue mass? (7) Can energy drinks improve cognitive performance? (8) Does the acute consumption of energy drinks elevate resting energy expenditure? (9) Is there any evidence to suggest that energy drinks are more effective than an identical serving of caffeine alone? (10) Are there sex differences in the response to energy drink consumption? (11) Do energy drinks affect sleep or sleepiness? (12) Should pregnant women avoid energy drinks? (13) Do energy drinks adversely affect cardiovascular function? (14) Does consuming energy drinks cause brain damage? (15) What are other safety considerations regarding energy drinks? (16) Is there any evidence to suggest that energy drinks are more effective than an identical serving of caffeine alone? (17) If caffeine is the main active ingredient in energy drinks and coffee, why is there a discrepancy in the adverse events reported for each? To address these questions, we performed an evidence-based scientific evaluation of the literature on energy drink supplementation.

Abstract Jagim, AR, Harty, PS, Jones, MT, Fields, JB, Magee, M, Smith-Ryan, AE, Luedke, J, and Kerksick, CM. Fat-free mass index in sport: normative profiles and applications for collegiate athletes. J Strength Cond Res 38(9): 1687–1693, 2024—Recent concerns have been raised regarding the ethical considerations of conducting body composition assessments in sports. Specific apprehensions pertain to the inappropriate use of percent body fat and the limited application of the results to performance and recovery. Fat-free mass index (FFMI), a height-adjusted assessment of FFM, can serve as an alternative body composition metric to focus on in sports. Fat-free mass index provides valuable context regarding an optimal amount of FFM, accounting for skeletal frame and height while helping to qualify an athlete's FFM as low, moderate, or high. This review posits that shifting the focus of body composition measures to FFM can support more ideal targets across athletic seasons, careers, and the return to play after injury. In addition, a FFM focus may help change the perception of body composition assessment and how athletes perceive their current body because of the increased focus on the FFM compartment and the goal of maximizing tissue accrual, rather than focusing on fat loss. Fat-free mass index is calculated by dividing FFM (kg) by height (m 2 ) and can serve to normalize FFM, relative to height, and enable comparisons across athletes, sport types, and sex. Previous research has identified differences in FFMI across sex and among sport categories. Still, there is a need for more published data to develop optimal ranges for FFMI across sex, sports, and positions. As more data become available, FFMI has the potential to provide normative guidelines for optimal FFM development, performance, and injury risk reduction. The purpose of the current review was to summarize FFMI values across collegiate sport categories and competitive status to provide normative profiles, according to sex and sport type.

Abstract Brandner, CF, Harty, PS, Luedke, JA, Erickson, JL, and Jagim, AR. Sport differences in fat-free mass index among a diverse sample of NCAA Division III collegiate athletes. J Strength Cond Res 36(8): 2212–2217, 2022—Fat-free mass index (FFMI) is becoming a popular metric to determine an athlete's potential for future fat-free mass accrual or to identify athletes who may be at risk for low fat-free mass (FFM). The aim of the current study was to examine sport-specific differences in FFMI among a cohort of collegiate athletes. NCAA Division III male ( n = 98; age: 20.1 ± 1.6 years, height: 1.82 ± 0.06 m, body mass: 92.7 ± 17.5 kg, %BF: 15.6 ± 8.8%) and female ( n = 92; age: 19.45 ± 1.1 years, height: 1.68 ± 0.06 m, body mass: 65.16 ± 11.04 kg, %BF: 22.71 ± 5.9%) athletes completed a body composition assessment using air displacement plethysmography. Fat-free mass index was calculated by dividing FFM by height squared. The mean ± SD FFMI was significantly higher ( p < 0.05) for males (23.37 ± 2.41 kg·m −2 ) compared with females (17.54 ± 1.8 kg·m −2 ). There was a significant main effect for sport category. Post hoc analysis indicated that throwers had a higher ( p < 0.001) FFMI (mean difference, 95% confidence interval) compared with sprinters and soccer athletes (4.17, 2.03–6.32 kg·m −2 ), endurance and weight-sensitive athletes (4.91, 2.67–7.14 kg·m −2 ), and court sport athletes (4.39, 1.97–6.81 kg·m −2 ), respectively, among female athletes. Post hoc analysis indicated that football players had a higher ( p < 0.01) FFMI than distance runners (3.89, 2.15, 5.62) and wrestlers (2.23, 0.78, 3.68), among male athletes. These findings indicate that sex differences in FFMI exist, with differences identified between sports. These findings can guide strength and nutritional programming decisions by providing sport-specific normative data profiles.

Background: Energy drinks are one of the most popular packaged beverage products consumed within the United States (US). Energy drinks are considered a functional beverage, a category that also includes sports drinks and nutraceutical beverages. Purpose: The focus of the current study was to examine the nutrition fact panels of the top selling commercially available energy drink and energy shot products within the US to characterize common ingredient profiles to help establish a standard definition and ingredient profile of energy drinks and energy shots for consumers, health care practitioners, and researchers. Methods: The top 75 commercially available energy drinks and shots were identified and compiled from multiple commercial retail websites as of September 2021. For the purpose of this study, an energy drink must have met the following criteria: (A) marketed as an energy drink; (B) purported to improve energy, focus, or alertness; (C) not sold as a dietary supplement (no supplement fact panels); (D) manufactured as a pre-packaged and ready-to-drink beverage; and (E) contains at least three of (1) caffeine, (2) B-vitamins, (3) sugar, (4) taurine, (5) creatine, (6) quercetin, (7) guarana, (8) ginseng, (9) coenzyme Q10, or (10) branched chain amino acids. Energy shots must have met similar criteria to be included: (A) marketed as an energy shot; (B) purported to improve energy, focus, or alertness; (C) sold as a dietary supplement; (D) manufactured as a pre-packaged beverage with a small volume (<3.5 mL); and (E) contains at least three of the ingredients stated above. Results: Twenty energy shots and fifty-five energy drinks were included in this analysis. The number of ingredients per product (mean ± SD) was 18.2 ± 5.7, with 15 products containing proprietary blends with undisclosed ingredient amounts. The relative prevalence and average amounts of the top ingredients were as follows: caffeine (100%; 174.4 ± 81.1 mg), vitamin B6 (72%; 366.9 ± 648.1 percent daily value (%DV)), vitamin B3 (67%; 121.44 ± 69.9% DV), vitamin B12 (67%; 5244.5 ± 10,474.6% DV), vitamin B5 (37.3%; 113.6 ± 76.6% DV), and taurine (37.3%; amounts undisclosed). Conclusions: Our findings suggest a high prevalence of caffeine and B-vitamins in these energy products, with many of the formulations containing well above the recommended daily value of B-vitamins.

Energy needs of female team-sport athletes are poorly understood with no evidence highlighting differences present between scheduled activities. The purpose of this study was to examine the difference in energy expenditure between NCAA Division II female basketball (BBALL) and lacrosse (LAX) athletes during different scheduled team activities. Female BBALL (n = 13; 19.8 ± 1.3 yrs; 173.9 ± 13.6 cm; 74.6 ± 9.1kg; 27.1 ± 3.2%fat) and LAX (n = 20; 20.4 ± 1.8yrs; 168.4 ± 6.6cm; 68.8 ± 8.9kg; 27.9 ± 3.1%fat) athletes were outfitted with heart rate and activity monitors during four consecutive days on five different occasions (20 days total) across an entire academic year to assess differences in total daily activity energy expenditure (TDEE), activity energy expenditure (AEE), and physical activity level (PAL). Data were categorized by type of scheduled daily activities: Practice, Game, Conditioning, or Off. Independent of day type, TDEE, AEE, and PAL levels were greater (p < 0.05) in BBALL athletes. For each sport, TDEE, AEE, and PAL were significantly different (p < 0.05) between classified activity days. BBALL and LAX athletes experienced higher values on game days for TDEE, AEE, and PAL, with the lowest values experienced on off days. In conclusion, calculated levels of TDEE, AEE, and PAL in female collegiate BBALL and LAX athletes were determined to be different, irrespective of the scheduled activity.

Abstract Objective . Bioimpedance devices are commonly used to assess health parameters and track changes in body composition. However, the cross-sectional agreement between different devices has not been conclusively established. Thus, the objective of this investigation was to examine the agreement between raw bioelectrical variables (resistance, reactance, and phase angle at the 50 kHz frequency) obtained from three bioimpedance analyzers. Approach . Healthy male ( n = 76, mean ± SD; 33.8 ± 14.5 years; 83.9 ± 15.1 kg; 179.4 ± 6.9 cm) and female ( n = 103, mean ± SD; 33.4 ± 15.9 years; 65.6 ± 12.1 kg; 164.9 ± 6.4 cm) participants completed assessments using three bioimpedance devices: supine bioimpedance spectroscopy (BIS), supine single-frequency bioelectrical impedance analysis (SFBIA), and standing multi-frequency bioelectrical impedance analysis (MFBIA). Differences in raw bioelectrical variables between the devices were quantified via one-way analysis of variance for the total sample and for each sex. Equivalence testing was used to determine equivalence between methods. Main results . Significant differences in all bioelectrical variables were observed between the three devices when examining the total sample and males only. The devices appeared to exhibit slightly better agreement when analyzing female participants only. Equivalence testing using the total sample as well as males and females separately revealed that resistance and phase angle were equivalent between the supine devices (BIS, SFBIA), but not with the standing analyzer (MFBIA). Significance . The present study demonstrated disagreement between different bioimpedance analyzers for quantifying raw bioelectrical variables, with the poorest agreement between devices that employed different body positions during testing. These results suggest that researchers and clinicians should employ device-specific reference values to classify participants based on raw bioelectrical variables, such as phase angle. If reference values are needed but are unavailable for a particular bioimpedance analyzer, the set of reference values produced using the most similar analyzer and reference population should be selected.

This case study examined changes in body composition, resting metabolic rate (RMR), aerobic capacity, and daily physical activity in a patient who had ulcerative colitis and underwent ileal pouch-anal anastomosis (IPAA) surgery. Body composition, RMR, and peak oxygen consumption (VO2peak) were assessed prior to surgery and four, eight, and 16 weeks after IPAA surgery. Daily physical activity data were extracted from a wrist-worn activity tracker preoperatively and 16 months postoperatively. At baseline, total body mass was 95.3 kg; body fat, 11.6%; lean body mass, 81.1 kg; RMR, 2416 kcal/d; and VO2peak, 42.7 mL/kg/min. All values decreased from baseline at four weeks postoperatively, body mass was 85.2 kg (−10.5%); body fat, 10.9% (−6.0%); lean body mass, 73.1 kg (−9.9%); RMR 2210 kcal/d (−8.5%) and VO2peak, 25.5 mL/kg/min (−40.3%). At 16 weeks postoperatively, most parameters were near their baseline levels (within 1–7%), exceptions were VO2peak, which was 20.4% below baseline, and RMR, which increased to nearly 20% above baseline. After the patient had IPAA surgery, his total and lean body masses, RMR, and aerobic capacity were markedly decreased. Daily physical activity decreased postoperatively and likely contributed to the decreased aerobic capacity, which may take longer to recover compared to body composition and RMR parameters.