Aaron J. Coutts
Mark Messina, Heidi Lynch, Jared M. Dickinson, and Katharine E. Reed
Much attention has been given to determining the influence of total protein intake and protein source on gains in lean body mass (LBM) and strength in response to resistance exercise training (RET). Acute studies indicate that whey protein, likely related to its higher leucine content, stimulates muscle protein synthesis to a greater extent than proteins such as soy and casein. Less clear is the extent to which the type of protein supplemented impacts strength and LBM in long-term studies (≥6 weeks). Therefore, a meta-analysis was conducted to compare the effect of supplementation with soy protein to animal protein supplementation on strength and LBM in response to RET. Nine studies involving 266 participants suitable for inclusion in the meta-analysis were identified. Five studies compared whey with soy protein, and four studies compared soy protein with other proteins (beef, milk, or dairy protein). Meta-analysis showed that supplementing RET with whey or soy protein resulted in significant increases in strength but found no difference between groups (bench press: χ2 = 0.02, p = .90; squat: χ2 = 0.22, p = .64). There was no significant effect of whey or soy alone (n = 5) on LBM change and no differences between groups (χ2 = 0.00, p = .96). Strength and LBM both increased significantly in the “other protein” and the soy groups (n = 9), but there were no between-group differences (bench: χ2 = 0.02, p = .88; squat: χ2 = 0.78, p = .38; and LBM: χ2 = 0.06, p = .80). The results of this meta-analysis indicate that soy protein supplementation produces similar gains in strength and LBM in response to RET as whey protein.
Joanne G. Mirtschin, Sara F. Forbes, Louise E. Cato, Ida A. Heikura, Nicki Strobel, Rebecca Hall, and Louise M. Burke
The authors describe the implementation of a 3-week dietary intervention in elite race walkers at the Australian Institute of Sport, with a focus on the resources and strategies needed to accomplish a complex study of this scale. Interventions involved: traditional guidelines of high carbohydrate (CHO) availability for all training sessions; a periodized CHO diet which integrated sessions with low and high CHO availability within the same total CHO intake; and a ketogenic low-CHO high-fat diet. Seven-day menus and recipes were constructed for a communal eating setting to meet nutritional goals as well as individualized food preferences and special needs. Menus also included nutrition support before, during, and after exercise. Daily monitoring, via observation and food checklists, showed that energy and macronutrient targets were achieved. Diets were matched for energy (∼14.8 MJ/d) and protein (∼2.1 g·kg−1·day−1) and achieved desired differences for fat and CHO, with high CHO availability and periodized CHO availability: CHO = 8.5 g·kg−1·day−1, 60% energy, fat = 20% of energy and low-CHO high-fat diet: 0.5 g·kg−1·day−1 CHO, fat = 78% energy. There were no differences in micronutrient intake or density between the high CHO availability and periodized CHO availability diets; however, the micronutrient density of the low-CHO high-fat diet was significantly lower. Daily food costs per athlete were similar for each diet (∼AU$ 27 ± 10). Successful implementation and monitoring of dietary interventions in sports nutrition research of the scale of the present study require meticulous planning and the expertise of chefs and sports dietitians. Different approaches to sports nutrition support raise practical challenges around cost, micronutrient density, accommodation of special needs, and sustainability.
Louise M. Burke, John A. Hawley, Asker Jeukendrup, James P. Morton, Trent Stellingwerff, and Ronald J. Maughan
From the breakthrough studies of dietary carbohydrate and exercise capacity in the 1960s through to the more recent studies of cellular signaling and the adaptive response to exercise in muscle, it has become apparent that manipulations of dietary fat and carbohydrate within training phases, or in the immediate preparation for competition, can profoundly alter the availability and utilization of these major fuels and, subsequently, the performance of endurance sport (events >30 min up to ∼24 hr). A variety of terms have emerged to describe new or nuanced versions of such exercise–diet strategies (e.g., train low, train high, low-carbohydrate high-fat diet, periodized carbohydrate diet). However, the nonuniform meanings of these terms have caused confusion and miscommunication, both in the popular press and among the scientific community. Sports scientists will continue to hold different views on optimal protocols of fuel support for training and competition in different endurance events. However, to promote collaboration and shared discussions, a commonly accepted and consistent terminology will help to strengthen hypotheses and experimental/experiential data around various strategies. We propose a series of definitions and explanations as a starting point for a more unified dialogue around acute and chronic manipulations of fat and carbohydrate in the athlete’s diet, noting philosophies of approaches rather than a single/definitive macronutrient prescription. We also summarize some of the key questions that need to be tackled to help produce greater insight into this exciting area of sports nutrition research and practice.
This case study features an Olympic-level female middle-distance runner implementing a science-based approach to body composition periodization. Data are emerging to suggest that it is not sustainable from a health and/or performance perspective to be at peak body composition year-round, so body composition needs to be strategically periodized. Anthropometric (n = 44), hematological, other health measures, and 1,500-m race performances (n = 83) were periodically assessed throughout a 9-year career. General preparation phase (September to April) featured the athlete at ∼2–4% over ideal competition phase body weight (BW) and body fat (%), with optimal energy availability being prioritized. The competition body composition optimization phase (May to August) included creating an individualized time frame and caloric deficit with various feedback metrics (BW, performance, and hunger) to guide the process. There were significant seasonal fluctuations in anthropometric outcomes between phases (47.3 ± 0.8 vs. 48.3 ± 0.9 kg BW; 53.6 ± 7.8 vs. 61.6 ± 9.7 mm International Society for the Advancement of Kinanthropometry sum of 8 [So8] skinfolds; p < .01), and a significant correlation of decreasing So8 during the peak competition period over her career (r = −.838; p = .018). The range of body composition during the competition period was 46.0–48.0 kg BW and a So8 range was 42.0–55.9 mm. There were also significant positive correlations between slower 1,500-m race times and increasing So8 (r = .437; p < .01), estimated fat mass (r = .445; p < .01), and BW (r = .511; p < .0001). The athlete only had two career injuries. This case study demonstrates a body composition periodization approach that allowed for targeted peak yearly performances, which improved throughout her career, while maximizing training adaptation and long-term athlete health through optimal energy availability.
Kirsty J. Elliott-Sale, Adam S. Tenforde, Allyson L. Parziale, Bryan Holtzman, and Kathryn E. Ackerman
The term Relative Energy Deficiency in Sport was introduced by the International Olympic Committee in 2014. It refers to the potential health and performance consequences of inadequate energy for sport, emphasizing that there are consequences of low energy availability (EA; typically defined as <30 kcal·kg−1 fat-free mass·day−1) beyond the important and well-established female athlete triad, and that low EA affects populations other than women. As the prevalence and consequences of Relative Energy Deficiency in Sport become more apparent, it is important to understand the current knowledge of the hormonal changes that occur with decreased EA. This paper highlights endocrine changes that have been observed in female and male athletes with low EA. Where studies are not available in athletes, results of studies in low EA states, such as anorexia nervosa, are included. Dietary intake/appetite-regulating hormones, insulin and other glucose-regulating hormones, growth hormone and insulin-like growth factor 1, thyroid hormones, cortisol, and gonadal hormones are all discussed. The effects of low EA on body composition, metabolic rate, and bone in female and male athletes are presented, and we identify future directions to address knowledge gaps specific to athletes.
Barbara Drinkwater has been a lifelong champion of equality for women in many areas of life well before it was widely accepted. Her “walking the walk” of women breaking barriers in traditional male roles in administration and leadership is exemplified by her election as the first woman president of the American College of Sports Medicine in 1988. Some of the controversial areas in which Barbara was vocal in the arena of women in sport, besides triad/relative energy deficiency in sport, include increased opportunity and participation, total equality, acceptance of diversity, intolerance of harassment and abuse, and fairness with transgender athletes. She co-founded the evidence-based advocacy group on the international stage known as Women Sport International. As a physiologist, Barbara has had a major influence on attention to the health of the female athlete, and she produced the original pioneering work in the field. Her impactful study, “Bone mineral density after resumption of menses in amenorrheic athletes,” was published in the Journal of the American Medical Association in 1986. Since that time, the female athlete triad has set the stage for research and treatment to enhance women in physical activity at all levels.
Margo Mountjoy, Jorunn Sundgot-Borgen, Louise Burke, Kathryn E. Ackerman, Cheri Blauwet, Naama Constantini, Constance Lebrun, Bronwen Lundy, Anna Melin, Nanna Meyer, Roberta Sherman, Adam S. Tenforde, Monica Klungland Torstveit, and Richard Budgett
Ida A. Heikura, Arja L.T. Uusitalo, Trent Stellingwerff, Dan Bergland, Antti A. Mero, and Louise M. Burke
We aimed to (a) report energy availability (EA), metabolic/reproductive function, bone mineral density, and injury/illness rates in national/world-class female and male distance athletes and (b) investigate the robustness of various diagnostic criteria from the Female Athlete Triad (Triad), Low Energy Availability in Females Questionnaire, and relative energy deficiency in sport (RED-S) tools to identify risks associated with low EA. Athletes were distinguished according to benchmarks of reproductive function (amenorrheic [n = 13] vs. eumenorrheic [n = 22], low [lowest quartile of reference range; n = 10] versus normal testosterone [n = 14]), and EA calculated from 7-day food and training diaries (< or >30 kcal·kg−1 fat-free mass·day−1). Sex hormones (p < .001), triiodothyronine (p < .05), and bone mineral density (females, p < .05) were significantly lower in amenorrheic (37%) and low testosterone (40%; 15.1 ± 3.0 nmol/L) athletes, and bone injuries were ∼4.5-fold more prevalent in amenorrheic (effect size = 0.85, large) and low testosterone (effect size = 0.52, moderate) groups compared with others. Categorization of females and males using Triad or RED-S tools revealed that higher risk groups had significantly lower triiodothyronine (female and male Triad and RED-S: p < .05) and higher number of all-time fractures (male Triad: p < .001; male RED-S and female Triad: p < .01) as well as nonsignificant but markedly (up to 10-fold) higher number of training days lost to bone injuries during the preceding year. Based on the cross-sectional analysis, current reproductive function (questionnaires/blood hormone concentrations) appears to provide a more objective and accurate marker of optimal energy for health than the more error-prone and time-consuming dietary and training estimation of EA. This study also offers novel findings that athlete health is associated with EA indices.
Sarah Staal, Anders Sjödin, Ida Fahrenholtz, Karen Bonnesen, and Anna Katarina Melin
Ballet dancers are reported to have an increased risk for energy deficiency with or without disordered eating behavior. A low ratio between measured (m) and predicted (p) resting metabolic rate (RMRratio < 0.90) is a recognized surrogate marker for energy deficiency. We aimed to evaluate the prevalence of suppressed RMR using different methods to calculate pRMR and to explore associations with additional markers of energy deficiency. Female (n = 20) and male (n = 20) professional ballet dancers, 19–35 years of age, were enrolled. mRMR was assessed by respiratory calorimetry (ventilated open hood). pRMR was determined using the Cunningham and Harris–Benedict equations, and different tissue compartments derived from whole-body dual-energy X-ray absorptiometry assessment. The protocol further included assessment of body composition and bone mineral density, blood pressure, disordered eating (Eating Disorder Inventory-3), and for females, the Low Energy Availability in Females Questionnaire. The prevalence of suppressed RMR was generally high but also clearly dependent on the method used to calculate pRMR, ranging from 25% to 80% in males and 35% to 100% in females. Five percent had low bone mineral density, whereas 10% had disordered eating and 25% had hypotension. Forty percent of females had elevated Low Energy Availability in Females Questionnaire score and 50% were underweight. Suppressed RMR was associated with elevated Low Energy Availability in Females Questionnaire score in females and with higher training volume in males. In conclusion, professional ballet dancers are at risk for energy deficiency. The number of identified dancers at risk varies greatly depending on the method used to predict RMR when using RMRratio as a marker for energy deficiency.