Dietary Intake and Energy Expenditure During Two Different Phases of Athletic Training in Female Collegiate Lacrosse Players

Energy balance and energy availability of female basketball players during the preparation period

OBJECTIVE

To determine the level of energy balance and energy availability (EA) in female basketball players during the preparation period.

METHODS

Fifteen basketball players (age: 19.53 ± 1.3 years; height: 173.6 ± 8.95 cm; weight: 67.55 ± 14.34 kg; training experience: 9.6 ± 2.7 years) and 15 age and body mass index-matched controls (age: 19.53 ± 1.1 years; height: 169.4 ± 5.06 cm; weight: 63.10 ± 6.14 kg) participated in the study. Resting metabolic rate (RMR) and body composition were measured by the indirect calorimetric method and dual-energy x-ray absorptiometry, respectively. A 3-day food diary was used to determine macronutrients and energy intake while a 3-day physical activity log was used to determine energy expenditure. Independent Samples t-test was used for data analysis.

RESULTS

The daily energy intake and expenditure of female basketball players were 2136.5 ± 594.9 kcal·day-1 and 2953.8 ± 614.5 kcal·day-1, respectively, indicating 817 ± 779 kcal·day-1 of negative energy balance. One hundred percent and 66.6% of the athletes failed to meet the carbohydrate and protein intake recommendations, respectively. EA of female basketball players was 33.04 ± 15.69 kcal·fat free mass-1·day-1 and the percentages of athletes who had negative energy balance, low EA, and reduced EA were 80%, 40%, and 46.7%, respectively. However, despite the low and decreased EA, the measured RMR to predicted RMR ratio (RMRratio) was 1.31 ± 0.17 and the body fat percentage (BF%) was 31.00 ± 5.21%.

CONCLUSION

This study shows that female basketball players have a negative energy balance during the preparation period which can be partly explained by insufficient carbohydrate intake. Although most of the athletes experienced low or reduced EA during the preparation period, the physiologically normal RMRratio and relatively high BF% indicate that this is a transient situation. In this regard, strategies to prevent the development of low EA and negative energy balance during the preparation period will contribute to positive training adaptations throughout the competition period.

Contributing Factors to Low Energy Availability in Female Athletes: A Narrative Review of Energy Availability, Training Demands, Nutrition Barriers, Body Image, and Disordered Eating

Relative Energy Deficiency in sport is experiencing remarkable popularity of late, particularly among female athletes. This condition is underpinned by low energy availability, which is a byproduct of high energy expenditure, inadequate energy intake, or a combination of the two. Several contributing factors exist that may predispose an athlete to low energy availability, and therefore a holistic and comprehensive assessment may be required to identify the root causes. The focus of the current narrative review is to discuss the primary contributing factors as well as known risk factors for low energy availability among female athletes to help practitioners increase awareness on the topic and identify future areas of focus.

How Does the Dietary Intake of Female Field-Based Team Sport Athletes Compare to Dietary Recommendations for Health and Performance? A Systematic Literature Review

Field-based team sports present large energetic demands given their intermittent high-intensity nature. Current evidence suggests that the dietary intake of female athletes may be insufficient to meet such demands, resulting in negative consequences for athletic performance and health. The primary aim of this review was to therefore assess the adequacy of dietary intake of female field-based team sport athletes when compared to dietary recommendations. A systematic search of databases, including PubMed, Web of Science, SPORTDiscus, and OpenGrey, was performed from the earliest record available until July 2020, obtaining an initial total of 2588 articles. To be included within the final review, articles were required to provide a quantitative assessment of baseline dietary intake specific to the target population. A total of 20 studies (n = 462) met the full eligibility criteria. A majority reported that the dietary intake of female field-based team sport athletes was insufficient in overall energy (2064 ± 309 kcal·day^-1), carbohydrate (4.3 ± 1.2 g·kg·day^-1), and iron intake (13.6 ± 6.2 mg·day^-1) when compared to recommendations. Future research is required to establish why female team sport athletes consistently demonstrate deficient dietary practices, and to explore the potential negative consequences of this.

Reliability and validity of the physical activity monitor for assessing energy expenditures in sedentary, regularly exercising, non-endurance athlete, and endurance athlete adults

Background

Inertial sensors, such as accelerometers, serve as convenient devices to predict the energy expenditures (EEs) during physical activities by a predictive equation. Although the accuracy of estimate EEs especially matter to athletes receive physical training, most EE predictive equations adopted in accelerometers are based on the general population, not athletes. This study included the heart rate reserve (HRR) as a compensatory parameter for physical intensity and derived new equations customized for sedentary, regularly exercising, non-endurance athlete, and endurance athlete adults.

Methods

With indirect calorimetry as the criterion measure (CM), the EEs of participants on a treadmill were measured, and vector magnitudes (VM), as well as HRR, were simultaneously recorded by a waist-worn accelerometer with a heart rate monitor. Participants comprised a sedentary group (SG), an exercise-habit group (EHG), a non-endurance group (NEG), and an endurance group (EG), with 30 adults in each group.

Results

EE predictive equations were revised using linear regression with cross-validation on VM, HRR, and body mass (BM). The modified model demonstrates valid and reliable predictions across four populations (Pearson correlation coefficient, r: 0.922 to 0.932; intraclass correlation coefficient, ICC: 0.919 to 0.930).

Conclusion

Using accelerometers with a heart rate monitorcan accurately predict EEs of athletes and non-athletes with an optimized predictive equation integrating the VM, HRR, and BM parameters.