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      Using physical activity levels to estimate energy requirements of female athletes

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          Abstract

          [Purpose]

          The goal of this study was to review data on physical activity level (PAL), a crucial index for determining estimated energy requirement (EER), calculated as total energy expenditure (TEE, assessed with doubly labeled water [DLW]) divided by resting metabolic rate (RMR, PAL = TEE/RMR) in female athletes and to understand the methods of assessing athletes’ EERs in the field.

          [Methods]

          For the PAL data review among female athletes, we conducted a PubMed search of the available literature related to the DLW method. DLW studies measuring TEE and RMR were included for the present review.

          [Results]

          Briefly, the mean PAL was 1.71 for collegiate swimmers with moderate training, which was relatively low, but the mean PAL was 3.0 for elite swimmers during summer training camp. This shows that PAL can largely vary even within the same sport depending on the amount of training, and the differences in PAL were remarkable depending on the sport. Aside from the DLW method, there is currently no research tool related to athletes’ EERs that can be used in the field.

          [Conclusion]

          Briefly, the mean PAL was 1.71 for collegiate swimmers with moderate training, which was relatively low, but the mean PAL was 3.0 for elite swimmers during summer training camp. This shows that PAL can largely vary even within the same sport depending on the amount of training, and the differences in PAL were remarkable depending on the sport. Aside from the DLW method, there is currently no research tool related to athletes’ EERs that can be used in the field.

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          Most cited references33

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          Prevention, diagnosis, and treatment of the overtraining syndrome: joint consensus statement of the European College of Sport Science and the American College of Sports Medicine.

          Successful training not only must involve overload but also must avoid the combination of excessive overload plus inadequate recovery. Athletes can experience short-term performance decrement without severe psychological or lasting other negative symptoms. This functional overreaching will eventually lead to an improvement in performance after recovery. When athletes do not sufficiently respect the balance between training and recovery, nonfunctional overreaching (NFOR) can occur. The distinction between NFOR and overtraining syndrome (OTS) is very difficult and will depend on the clinical outcome and exclusion diagnosis. The athlete will often show the same clinical, hormonal, and other signs and symptoms. A keyword in the recognition of OTS might be "prolonged maladaptation" not only of the athlete but also of several biological, neurochemical, and hormonal regulation mechanisms. It is generally thought that symptoms of OTS, such as fatigue, performance decline, and mood disturbances, are more severe than those of NFOR. However, there is no scientific evidence to either confirm or refute this suggestion. One approach to understanding the etiology of OTS involves the exclusion of organic diseases or infections and factors such as dietary caloric restriction (negative energy balance) and insufficient carbohydrate and/or protein intake, iron deficiency, magnesium deficiency, allergies, and others together with identification of initiating events or triggers. In this article, we provide the recent status of possible markers for the detection of OTS. Currently, several markers (hormones, performance tests, psychological tests, and biochemical and immune markers) are used, but none of them meet all the criteria to make their use generally accepted.
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            Real-time estimation of daily physical activity intensity by a triaxial accelerometer and a gravity-removal classification algorithm.

            We have recently developed a simple algorithm for the classification of household and locomotive activities using the ratio of unfiltered to filtered synthetic acceleration (gravity-removal physical activity classification algorithm, GRPACA) measured by a triaxial accelerometer. The purpose of the present study was to develop a new model for the immediate estimation of daily physical activity intensities using a triaxial accelerometer. A total of sixty-six subjects were randomly assigned into validation (n 44) and cross-validation (n 22) groups. All subjects performed fourteen activities while wearing a triaxial accelerometer in a controlled laboratory setting. During each activity, energy expenditure was measured by indirect calorimetry, and physical activity intensities were expressed as metabolic equivalents (MET). The validation group displayed strong relationships between measured MET and filtered synthetic accelerations for household (r 0·907, P < 0·001) and locomotive (r 0·961, P < 0·001) activities. In the cross-validation group, two GRPACA-based linear regression models provided highly accurate MET estimation for household and locomotive activities. Results were similar when equations were developed by non-linear regression or sex-specific linear or non-linear regressions. Sedentary activities were also accurately estimated by the specific linear regression classified from other activity counts. Therefore, the use of a triaxial accelerometer in combination with a GRPACA permits more accurate and immediate estimation of daily physical activity intensities, compared with previously reported cut-off classification models. This method may be useful for field investigations as well as for self-monitoring by general users.
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              Classifying household and locomotive activities using a triaxial accelerometer.

              The purpose of this study was to develop a new algorithm for classifying physical activity into either locomotive or household activities using a triaxial accelerometer. Sixty-six volunteers (31 men and 35 women) participated in this study and were separated randomly into validation and cross-validation groups. All subjects performed 12 physical activities (personal computer work, laundry, dishwashing, moving a small load, vacuuming, slow walking, normal walking, brisk walking, normal walking while carrying a bag, jogging, ascending stairs and descending stairs) while wearing a triaxial accelerometer in a controlled laboratory setting. Each of the three signals from the triaxial accelerometer was passed through a second-order Butterworth high-pass filter to remove the gravitational acceleration component from the signal. The cut-off frequency was set at 0.7 Hz based on frequency analysis of the movements conducted. The ratios of unfiltered to filtered total acceleration (TAU/TAF) and filtered vertical to horizontal acceleration (VAF/HAF) were calculated to determine the cut-off value for classification of household and locomotive activities. When the TAU/TAF discrimination cut-off value derived from the validation group was applied to the cross-validation group, the average percentage of correct discrimination was 98.7%. When the VAF/HAF value similarly derived was applied to the cross-validation group, there was relatively high accuracy but the lowest percentage of correct discrimination was 63.6% (moving a small load). These findings suggest that our new algorithm using the TAU/TAF cut-off value can accurately classify household and locomotive activities. Copyright 2010 Elsevier B.V. All rights reserved.
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                Author and article information

                Journal
                J Exerc Nutrition Biochem
                J Exerc Nutrition Biochem
                JENB
                J Exerc Nutr Biochem
                Journal of Exercise Nutrition & Biochemistry
                한국운동영양학회
                2233-6834
                2233-6842
                31 December 2019
                : 23
                : 4
                : 1-5
                Affiliations
                [1 ] Department of Physical Education, Korea University, Seoul Republic of Korea
                Author notes
                *Jonghoon Park, Ph.D. Department of Physical Education, Korea University, 145 Anam-Ro, Seongbuk-Gu, Seoul, 02841, Republic of Korea. Tel: +82-2-3290-2315 E-mail: jonghoonp@ 123456korea.ac.kr
                Article
                JENB_2019_v23n4_1
                10.20463/jenb.2019.0024
                7004509
                32018339
                64b5b62c-56bd-4e85-899f-2b3c34868591
                ©2019 The Korean Society for Exercise Nutrition

                ©2019 Jonghoon Park.; License Journal of Exercise Nutrition and Biochemistry. This is an open access article distributed under the terms of the creative commons attribution license ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the orginal work is properly cited.

                History
                : 21 September 2019
                : 25 November 2019
                : 25 November 2019
                Funding
                Funded by: College of Education, Korea University
                Categories
                Review Article

                physical activity level,doubly labeled water method,estimated energy requirement,female athletes

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