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By using our site, you acknowledge that you have read and understand our Privacy Policy and Terms of Use. Share 2 Share Email. March 25, Credit: CC0 Public Domain. More information: Katherine E. DOI: Provided by University of Otago.

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Wenner and Nina S. LoBuono, and Melinda M. We provide complimentary e-inspection copies of primary textbooks to instructors considering our books for course adoption. Most VitalSource eBooks are available in a reflowable EPUB format which allows you to resize text to suit you and enables other accessibility features. Where the content of the eBook requires a specific layout, or contains maths or other special characters, the eBook will be available in PDF PBK format, which cannot be reflowed.

For both formats the functionality available will depend on how you access the ebook via Bookshelf Online in your browser or via the Bookshelf app on your PC or mobile device. Stay on CRCPress. Preview this Book. Add to Wish List. Close Preview. Toggle navigation Additional Book Information. Description Table of Contents Editor s Bio. In the case of athletic subjects, the DRI predictive equation showed a clear bias negatively proportional to the subjects' TEE. The results from this study suggest that the DRI predictive equation could be used to obtain EER in non-athlete female college students at a group level.

However, this equation would be difficult to use in the case of athletes at the group and individual levels. The development of a new and more appropriate equation for the prediction of energy expenditure in athletes is proposed. Adequate energy intake is essential for athletic performance [ 1 ]. In order to maintain energy balance, energy intake must match energy expenditure. Athletes are under higher physiological demands due to their high levels of physical activity, which lead to elevated energy expenditure. Therefore, athletes have higher energy requirements in comparison to the rest of the population [ 2 ].

Helping Female Athletes Confront Their Three Greatest Opponents – Penn Medicine

In the case of weight management, athletes cannot overly restrict their energy consumption due to increased risk of losing lean tissue [ 3 ]. In female athletes, long-term negative energy balance and inadequate nutrient intake have been associated with various health consequences, including menstrual disorders and bone health problems [ 4 , 5 ]. Accurate measurement of total energy expenditure TEE is important for estimation of energy requirements in relation to negative energy balance, particularly among female athletes given the special concerns explained above.

Details of this method, which uses water labeled with stable 2 H and 18 O isotopes, are given elsewhere [ 6 ]. Despite its high accuracy, the DLW method is limited by its high cost. Therefore, other more affordable methods, including predictive equations for estimated energy requirements EER , are needed.

This DRI equation takes into consideration the activity levels of populations and individuals by applying a physical activity coefficient PA derived from physical activity level PAL.

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Validation studies on the accuracy of the DRI predictive equation for EER have been conducted in different population groups [ 9 , 10 , 11 ]. However, to our knowledge, few studies have been conducted on female athletes. Therefore, our study attempted to add new knowledge to the field of nutrition, particularly with regard to EER in the population of female athletes. Participants were 16 women aged between 19 and 24 years studying at Gangneung-Wonju National University during the period of the study.

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The first of two groups was composed of eight athletes tennis players , whereas the remaining eight were non-athletic women. After data collection, one subject was removed from the non-athlete group due to missing data, bringing the number of subjects to seven in this group and the total number to 15 participants. There was a significant difference in measurement period between the two groups.

Before the investigations, written informed consent was obtained from all participants. Anthropometric measurements and body composition assessment were performed using standard procedures.

Weight, height, and body composition were measured using Inbody Biospace Co. Body mass index BMI was calculated as body weight kg divided by square of body height m. All measurements were done with subjects wearing the lightest clothes possible to reduce error.


Calibration of the system was performed before every measurement, and automatic calibration was set every 5 minutes during the measurement. Measurement was conducted in a thermo-neutral room where the temperature was maintained as constant, with an average of Before the REE measurement, subjects were instructed to fast for at least 12 hours and abstain from vigorous activities for the 24 hours preceding the measurement. During the REE measurement, subjects laid on a bed with the head covered by a canopy for at least 15 minutes. On the first day of the measurements day 0 , subjects' baseline urine samples were collected for determination of background isotope levels before the dose administration.

Collected samples were kept in well-sealed bottles. Each subject was then given a measured oral dose of DLW containing 0. One hour after the dose administration, subjects voided their bladders, but this urine was not collected. The second and third urine samples were collected 3 and 4 hours, respectively, after the dose ingestion. For the athletic group, subsequent urine collection was carried out on day 1, day 2, day 7, and day 8, whereas for the non-athletic group, subsequent urine samples were collected on day 1, day 2, day 13, and day The difference in observation period between the two groups was based on the fact that water turn-over is more rapid in athlete participants compared to non-athletes [ 13 ].

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  7. This difference in water turnover rate may lead to error, which can be corrected by reducing the length of the measurement period in high activity subjects [ 13 ].