Human fraining— Consistent weight loss Additional file Body composition and endurance training Anf of methodological quality assessment undertaken on included studies. Acta Paediatr compoistion Article CAS PubMed Central Google Scholar. TC, HDL-C and TG concentrations were assessed using the enzymatic colorimetric method, while LDL-C levels were calculated from the Friedewald formula. The longer the length of training the larger the achieved benefits.

Body composition and endurance training -

Gluconeogenesis and hepatic glycogenolysis during exercise at the lactate threshold. Enqvist JK, Mattsson CM, Johansson PH, Brink-Elfegoun T, Bakkman L, Ekblom BT. Energy turnover during 24 hours and 6 days of adventure racing. Fudge BW, Easton C, Kingsmore D, Kiplamai FK, Onywera VO, Westerterp KR, et al.

Elite Kenyan endurance runners are hydrated day-to-day with ad libitum fluid intake. Garcia-Roves PM, Terrados N, Fernandez SF, Patterson AM. Macronutrients intake of top level cyclists during continuous competition--change in the feeding pattern.

Gorsuch J, Long J, Miller K, Primeau K, Rutledge S, Sossong A, et al. The effect of squat depth on multiarticular muscle activation in collegiate cross-country runners. Griffith RO, Dressendorfer RH, Fullbright GD, Wade CE. Testicular function during exhaustive endurance training.

Phys Sportsmed. Havemann L, Goedecke JH. Nutritional practices of male cyclists before and during an ultraendurance event. Heinonen A, Oja P, Kannus P, Sievanen H, Manttari A, Vuori I.

Bone mineral density of female athletes in different sports. Bone Miner. Herring JL, Mole PA, Meredith CN, Stern JS.

Effect of suspending exercise training on resting metabolic rate in women. Jones PJ, Leitch CA. Validation of doubly labeled water for measurement of caloric expenditure in collegiate swimmers.

Jurimae J, Jurimae T, Pihl E. Rowing ergometer performance and anaerobic capacity in college rowers. Jurimae J, Hofmann P, Jurimae T, Maestu J, Purge P, Wonisch M, et al.

Plasma adiponectin response to sculling exercise at individual anaerobic threshold in college level male rowers. Jurimae J, Jurimae T.

Plasma leptin responses to prolonged sculling in female rowers. Jurimae J, Purge P, Jurimae T. Effect of prolonged training period on plasma adiponectin in elite male rowers. Horm Metab Res. Jurimae J, Ramson R, Maestu J, Jurimae T, Arciero PJ, Braun WA, et al.

Interactions between adipose, bone, and muscle tissue markers during acute negative energy balance in male rowers. Koshimizu T, Matsushima Y, Yokota Y, Yanagisawa K, Nagai S, Okamura K, et al.

Basal metabolic rate and body composition of elite Japanese male athletes. J Med Invest. Lazzer S, Salvadego D, Rejc E, Buglione A, Antonutto G, di Prampero PE. The energetics of ultra-endurance running.

Maestu J, Jurimae J, Purge P, Ramson R, Jurimae T. Performance improvement is associated with higher postexercise responses in interleukin-6 and tumor necrosis factor concentrations.

Magkos F, Yannakoulia M, Kavouras SA, Sidossis LS. The type and intensity of exercise have independent and additive effects on bone mineral density. Maïmoun L, Manetta P, Leroux S. Testosterone is significantly reduced in endurance athletes without impact on bone mineral density.

Horm Res. Martin MK, Martin DT, Collier GR, Burke LM. Voluntary food intake by elite female cyclists during training and racing: influence of daily energy expenditure and body composition. Medelli J, Lounana J, Menuet JJ, Shabani M, Cordero-MacIntyre Z.

Is osteopenia a health risk in professional cyclists? J Clin Densitom. Moses K, Manore MM. Development and testing of a carbohydrate monitoring tool for athletes.

Motonaga K, Yoshida S, Yamagami F, Kawano T, Takeda E. Estimation of total daily energy expenditure and its components by monitoring the heart rate of Japanese endurance athletes.

J Nutr Sci Vitaminol Tokyo. Muoio DM, Leddy JJ, Horvath PJ, Awad AB, Pendergast DR. Effect of dietary fat on metabolic adjustments to maximal VO2 and endurance in runners. Ousley-Pahnke L, Black DR, Gretebeck RJ. Dietary intake and energy expenditure of female collegiate swimmers during decreased training prior to competition.

Palazzetti S, Rousseau AS, Richard MJ, Favier A, Margaritis I. Antioxidant supplementation preserves antioxidant response in physical training and low antioxidant intake. Palm R, Jürimäe J, Mästu J, Purge P, Jürimäe T, Rom K, et al. Relationship between body composition and aerobic capacity values in well-trained male rowers.

Acta Kinesiol Universitatis Tartu. Penteado VS, Castro CH, Pinheiro Mde M, Santana M, Bertolino S, de Mello MT, et al. Diet, body composition, and bone mass in well-trained cyclists. Phillips SM, Atkinson SA, Tarnopolsky MA, MacDougall JD. Gender differences in leucine kinetics and nitrogen balance in endurance athletes.

Roberts D, Smith DJ. Training at moderate altitude: iron status of elite male swimmers. J Lab Clin Med. Santos DA, Dawson JA, Matias CN, Rocha PM, Minderico CS, Allison DB, et al.

Reference values for body composition and anthropometric measurements in athletes. PLoS One. Article PubMed PubMed Central CAS Google Scholar. Sato A, Shimoyama Y, Ishikawa T, Murayama N.

Dietary thiamin and riboflavin intake and blood thiamin and riboflavin concentrations in college swimmers undergoing intensive training. Schena F, Pattini A, Mantovanelli S. Iron status in athletes involved in endurance and in prevalently anaerobic sports.

In: Kies CV, Driskell JA, editors. Sports nutrition: minerals and electrolytes. Boca Raton: CRC Press; Schenk K, Gatterer H, Ferrari M, Ferrari P, Cascio VL, Burtscher M. Bike Transalp liquid intake and its effect on the body's fluid homeostasis in the course of a multistage, cross-country, MTB marathon race in the central Alps.

Clin J Sport Med. Sherman WM, Doyle JA, Lamb DR, Strauss RH. Dietary carbohydrate, muscle glycogen, and exercise performance during 7 d of training. Simsch C, Lormes W, Petersen KG, Baur S, Liu Y, Hackney AC, et al.

Training intensity influences leptin and thyroid hormones in highly trained rowers. Sundby OH, Gorelick ML S. Relationship between functional hamstring: quadriceps ratios and running economy in highly trained and recreational female runners.

Tomten SE, Hostmark AT. Energy balance in weight stable athletes with and without menstrual disorders. Vaiksaar S, Jurimae J, Maestu J, Purge P, Kalytka S, Shakhlina L, et al. No effect of menstrual cycle phase on fuel oxidation during exercise in rowers. Witard OC, Jackman SR, Kies AK, Jeukendrup AE, Tipton KD.

Effect of increased dietary protein on tolerance to intensified training. Yeater R, Reed C, Ullrich I, Morise A, Borsch M.

Resistance trained athletes using or not using anabolic steroids compared to runners: effects on cardiorespiratory variables, body composition, and plasma lipids. Zajac A, Poprzecki S, Maszczyk A, Czuba M, Michalczyk M, Zydek G.

The effects of a ketogenic diet on exercise metabolism and physical performance in off-road cyclists. Zalcman I, Guarita HV, Juzwiak CR, Crispim CA, Antunes HK, Edwards B, et al. Nutritional status of adventure racers. Download references. The authors thank Elena Hartmann M. Human Movement Sciences and Laura Oberholzer B.

Health Science and Technology for their valuable assistance during the literature selection process and quality assessment of relevant articles. JH participated in the design of the study; carried out the data acquisition, analysis and interpretation of the results; and drafted the manuscript.

BK, YS, and KM participated in the conception and design; analysis and interpretation of the results; drafting and revisions of the manuscript for important intellectual content. All authors read and approved the final manuscript. Juliane Heydenreich, Bengt Kayser, Yves Schutz, and Katarina Melzer declare that there are no conflicts of interests regarding the publication of this paper.

Swiss Federal Institute of Sport Magglingen SFISM, Hauptstrasse , , Magglingen, Switzerland. Faculty of Biology and Medicine, University of Lausanne, Lausanne, , Switzerland.

Faculty of Medicine, University of Fribourg, Fribourg, , Switzerland. You can also search for this author in PubMed Google Scholar. Correspondence to Juliane Heydenreich.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4. Reprints and permissions. Heydenreich, J. et al. Total Energy Expenditure, Energy Intake, and Body Composition in Endurance Athletes Across the Training Season: A Systematic Review. Sports Med - Open 3 , 8 Download citation.

Received : 07 September Accepted : 24 January Published : 04 February Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all SpringerOpen articles Search. Download PDF. Abstract Background Endurance athletes perform periodized training in order to prepare for main competitions and maximize performance.

Methods An electronic database search was conducted on the SPORTDiscus and MEDLINE January —31 January databases using a combination of relevant keywords. Results From citations, articles were identified as potentially relevant, with 82 meeting all of the inclusion criteria.

Conclusions Limitations of the present study included insufficient data being available for all seasonal training phases and thus low explanatory power of single parameters. Key Points Endurance athletes show training seasonal fluctuations in TEE, energy intake, and body composition.

Full size image. Methods The review protocol was developed according to the Meta-analysis of Observational Studies in Epidemiology Guidelines for meta-analyses and systematic reviews of observational studies [ 53 ]. Search Strategy A systematic literature search was performed to retrieve articles pertaining to body composition, energy intake, and TEE in endurance athletes across the training season.

Literature Selection Two researchers independently assessed the eligibility of the records by screening the title, abstract, and keywords for inclusion and exclusion criteria. Methodological Quality Assessment All relevant articles were examined for full methodological quality using a modified version of the Downs and Black [ 55 ] checklist for the assessment of the methodological quality of randomized and non-randomized studies of health care interventions.

Table 1 Clustering of seasonal training phases for body composition, energy intake, and total energy expenditure Full size table. Results Description of Studies and Assessment Methods The flow chart for the study selection process is shown in Fig. Table 2 Characteristics of the studies included in the review of body composition BC , energy intake EI , and total energy expenditure TEE Full size table.

Table 3 Physical characteristics of included study estimates Full size table. Energy balance EB of male endurance athletes during preparation and competition phase. Energy balance EB of female endurance athletes during preparation and competition phase.

Table 5 Body composition of included study estimates across the season Full size table. Strengths and Limitations This is, to our knowledge, the first systematic review focusing on fluctuations in TEE, energy intake, and body composition in endurance athletes.

Conclusions Our analysis highlights the important seasonal fluctuations in TEE, energy intake, and body composition in male and female endurance athletes across the training season.

References Ravussin E, Bogardus C. CAS PubMed Google Scholar Westerterp KR. Article CAS PubMed Google Scholar Stellingwerf T. Article PubMed Google Scholar Zapico AG, Calderon FJ, Benito PJ, Gonzalez CB, Parisi A, Pigozzi F, et al. CAS PubMed Google Scholar Fiskerstrand A, Seiler KS.

Article CAS PubMed Google Scholar Neal CM, Hunter AM, Galloway SD. Article PubMed Google Scholar Westerterp KR, Saris WH, van Es M, ten Hoor F. CAS Google Scholar Thomas DT, Erdman KA, Burke LM. Article CAS PubMed Google Scholar O'Connor H, Slater G.

Chapter Google Scholar Fudge BW, Westerterp KR, Kiplamai FK, Onywera VO, Boit MK, Kayser B, et al. Article CAS PubMed Google Scholar Sundgot-Borgen J, Meyer NL, Lohman TG, Ackland TR, Maughan RJ, Stewart AD, et al.

Article PubMed Google Scholar World Health Organization WHO. Google Scholar Issurin VB. Article PubMed Google Scholar Matveyev L. Google Scholar Bompa T, Haff G. Google Scholar Stellingwerff T, Boit MK, Res PT.

Article PubMed Google Scholar Stellingwerff T, Maughan RJ, Burke LM. Article PubMed Google Scholar Burke LM, Hawley JA, Wong SH, Jeukendrup AE.

Article PubMed Google Scholar Maughan RJ, Burke LM. Article CAS PubMed Google Scholar Rodriguez NR, Di Marco NM, Langley S. Article PubMed CAS Google Scholar Burke LM, Mujika I.

Article CAS PubMed Google Scholar Mujika I, Stellingwerff T, Tipton K. Article CAS PubMed Google Scholar Shaw G, Koivisto A, Gerrard D, Burke LM. Article CAS PubMed Google Scholar Shaw G, Boyd KT, Burke LM, Koivisto A.

Article CAS PubMed Google Scholar Burke LM, Millet G, Tarnopolsky MA. Article PubMed Google Scholar Jeukendrup AE. Article PubMed Google Scholar Vilaca KH, Ferriolli E, Lima NK, Paula FJ, Moriguti JC.

Article CAS PubMed Google Scholar Lohman M, Tallroth K, Kettunen JA, Marttinen MT. Article CAS PubMed Google Scholar Nana A, Slater GJ, Stewart AD, Burke LM.

Article PubMed Google Scholar Saunders MJ, Blevins JE, Broeder CE. CAS PubMed Google Scholar Madden AM, Smith S.

Article CAS PubMed Google Scholar Temple D, Denis R, Walsh MC, Dicker P, Byrne AT. Article PubMed Google Scholar Magkos F, Yannakoulia M.

Article PubMed Google Scholar Bemben DA, Buchanan TD, Bemben MG, Knehans AW. PubMed Google Scholar Carbuhn AF, Fernandez TE, Bragg AF, Green JS, Crouse SF.

Article PubMed Google Scholar Kabasakalis A, Kalitsis K, Tsalis G, Mougios V. Article CAS PubMed Google Scholar LaForgia J, Withers RT, Williams AD, Murch BJ, Chatterton BE, Schultz CG, et al.

Article CAS PubMed Google Scholar Loftin M, Warren B, Mayhew J. Article Google Scholar Noland RC, Baker JT, Boudreau SR, Kobe RW, Tanner CJ, Hickner RC, et al. Article CAS PubMed Google Scholar Siders WA, Bolonchuk WW, Lukaski HC.

CAS PubMed Google Scholar Siders WA, Lukaski HC, Bolonchuk WW. CAS PubMed Google Scholar Barr SI, Costill DL. Article CAS PubMed Google Scholar Couzy F, Lafargue P, Guezennec CY. Article CAS PubMed Google Scholar Desgorces FD, Chennaoui M, Gomez-Merino D, Drogou C, Guezennec CY.

Article CAS PubMed Google Scholar Garcia-Roves PM, Terrados N, Fernandez S, Patterson AM. Article CAS PubMed Google Scholar Hassapidou MN, Manstrantoni A.

Article CAS Google Scholar Jensen CD, Zaltas ES, Whittam JH. CAS PubMed Google Scholar Margaritis I, Palazzetti S, Rousseau AS, Richard MJ, Favier A. Article CAS PubMed Google Scholar Papadopoulou SK, Gouvianaki A, Grammatikopoulou MG, Maraki Z, Pagkalos IG, Malliaropoulos N, et al.

Article PubMed PubMed Central Google Scholar Peters EM, Goetzsche JM. Article CAS PubMed Google Scholar Taylor SR, Rogers GG, Driver HS. Article CAS PubMed Google Scholar Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Article CAS PubMed Google Scholar Orwin R.

Google Scholar Downs SH, Black N. Article CAS PubMed PubMed Central Google Scholar Fox AS, Bonacci J, McLean SG, Spittle M, Saunders N. Article PubMed Google Scholar Wang ZM, Pierson Jr RN, Heymsfield SB.

CAS PubMed Google Scholar Higgins, Green, editors. Chichester, West Sussex, England: Wiley-Blackwell Gravetter F, Wallnau L. Google Scholar Bescós R, Rodríguez FA, Iglesias X, Knechtle B, Benítez A, Marina M, et al. Article CAS Google Scholar Rehrer NJ, Hellemans IJ, Rolleston AK, Rush E, Miller BF.

Article CAS PubMed Google Scholar Hulton AT, Lahart I, Williams KL, Godfrey R, Charlesworth S, Wilson M, et al. Article CAS PubMed Google Scholar Costa RJ, Gill SK, Hankey J, Wright A, Marczak S. Article CAS PubMed Google Scholar Morris FL, Payne WR.

Article CAS PubMed PubMed Central Google Scholar Ormsbee MJ, Arciero PJ. Article PubMed Google Scholar Boulay MR, Serresse O, Almeras N, Tremblay A.

Article CAS PubMed Google Scholar Sjodin AM, Andersson AB, Hogberg JM, Westerterp KR. Article CAS PubMed Google Scholar Schulz LO, Alger S, Harper I, Wilmore JH, Ravussin E.

CAS PubMed Google Scholar Hill RJ, Davies PS. Article PubMed Google Scholar Trappe TA, Gastaldelli A, Jozsi AC, Troup JP, Wolfe RR. Article CAS PubMed Google Scholar Winters KM, Adams WC, Meredith CN, Loan MD, Lasley BL.

Article CAS PubMed Google Scholar Thompson FE, Byers T. CAS PubMed Google Scholar Brouns F, Saris WH, Stroecken J, Beckers E, Thijssen R, Rehrer NJ, et al.

Article PubMed Google Scholar Subar AF, Freedman LS, Tooze JA, Kirkpatrick SI, Boushey C, Neuhouser ML, et al. Article CAS PubMed PubMed Central Google Scholar Loucks AB, Kiens B, Wright HH. Article PubMed Google Scholar Loucks AB. Article PubMed Google Scholar Melin A, Tornberg AB, Skouby S, Moller SS, Sundgot-Borgen J, Faber J, et al.

Article CAS PubMed Google Scholar Nana A, Slater GJ, Hopkins WG, Halson SL, Martin DT, West NP, et al. Article PubMed Google Scholar Ball SD, Altena TS, Swan PD. Article CAS PubMed Google Scholar Armstrong LE, Casa DJ, Emmanuel H, Ganio MS, Klau JF, Lee EC, et al.

Article PubMed Google Scholar Berg U, Enqvist JK, Mattsson CM, Carlsson-Skwirut C, Sundberg CJ, Ekblom B, et al. Article CAS PubMed Google Scholar Brewer CP, Dawson B, Wallman KE, Guelfi KJ.

Article CAS PubMed Google Scholar Brinkworth GD, Buckley JD, Bourdon PC, Gulbin JP, David A. Article PubMed Google Scholar Decombaz J, Gmuender B, Sierro G, Cerretelli P.

CAS PubMed Google Scholar Dellavalle DM, Haas JD. Article CAS PubMed Google Scholar Desgorces FD, Chennaoui M, Drogou C, Guezennec CY, Gomez-Merino D. CAS PubMed Google Scholar Drenowatz C, Eisenmann JC, Carlson JJ, Pfeiffer KA, Pivarnik JM.

Article CAS PubMed Google Scholar Drenowatz C, Eisenmann JC, Pivarnik JM, Pfeiffer KA, Carlson JJ. Article PubMed Google Scholar Emhoff CA, Messonnier LA, Horning MA, Fattor JA, Carlson TJ, Brooks GA.

Article CAS PubMed Google Scholar Enqvist JK, Mattsson CM, Johansson PH, Brink-Elfegoun T, Bakkman L, Ekblom BT. Article PubMed Google Scholar Fudge BW, Easton C, Kingsmore D, Kiplamai FK, Onywera VO, Westerterp KR, et al. Article PubMed Google Scholar Garcia-Roves PM, Terrados N, Fernandez SF, Patterson AM.

Article CAS PubMed Google Scholar Gorsuch J, Long J, Miller K, Primeau K, Rutledge S, Sossong A, et al. Article PubMed Google Scholar Griffith RO, Dressendorfer RH, Fullbright GD, Wade CE. Article CAS PubMed Google Scholar Havemann L, Goedecke JH. Article CAS PubMed Google Scholar Heinonen A, Oja P, Kannus P, Sievanen H, Manttari A, Vuori I.

Article CAS PubMed Google Scholar Herring JL, Mole PA, Meredith CN, Stern JS. Article CAS PubMed Google Scholar Jones PJ, Leitch CA. During the postmenopausal stage, women may experience a series of physiological changes in several cardiometabolic health outcomes 7 , 8.

Some of the common changes include increased body weight and fat mass, especially redistribution of body fat toward abdominal areas, which contributes to the development of negative cardiometabolic outcomes 9 — In this regard, menopausal age in women may be associated with increased prevalence of obesity and obesity-related disorders, including metabolic syndrome Insufficient physical activity is associated with poor menopausal outcomes and increased health risk during the postmenopausal stage of life 14 , while lifestyle interventions with either type of exercise is appropriate and effective in promoting the physiological or psychological outcomes in postmenopausal women As a non-pharmacological strategy, exercise training has been shown to be effective, safe, and important to attenuate the age-induced health adversities, and may attribute to improve cardiometabolic outcomes 16 , The beneficial effects of exercise intervention are mainly relied on the type of exercise.

Resistance training RT is known for improving the muscle strength and mass, as well as benefitting the sarcopenia-related phenotypes 18 — Aerobic training AT is known for improving pulmonary function and decreasing fat mass, especially visceral fat in older adults 22 — However, it is claimed that AT also improves muscle function and lead to skeletal muscle hypertrophy.

Therefore, AT also considered as a viable training method to combat sarcopenia in the elderly population 25 — Besides, previous meta-analyses have confirmed the beneficial effects of RT on muscle mass 28 , 29 and AT on fat mass 22 in older adults.

Although several meta-analyses have explored the effects of exercise training in older adults, yet no meta-analysis focused on postmenopausal women and their physical fitness status. Given that this population is affected by hormonal imbalance during aging, such hormonal changes are associated with poor outcomes in health and fitness related variables.

The aim of this systematic review and meta-analysis was to elucidate the effects of exercise training on body composition, including muscle mass, fat-free mass FFM , fat mass, body fat percentage, waist circumference, and visceral fat in postmenopausal women.

Subgroup analyses were conducted for the variables, including age of participants, and duration and type of exercise training aerobic, resistance, and combined to identify the influential variable and to emphasize the practical and clinical importance of exercise.

This systematic review and meta-analysis was conducted in accordance with the latest guidelines of Preferred Reporting Items for Systematic Review and Meta-Analysis PRISMA 30 , and the Cochrane Handbook of Systematic Reviews of Interventions This study was registered with PROSPERO International prospective register of systematic reviews ID: CRD In addition, reference lists of all retrieved records and previous meta-analyses 32 , 33 were screened for relevant articles.

After removing duplicate publications, the titles, abstracts, and keywords of the remaining studies were screened to assess the study eligibility for full-text review against inclusion and exclusion criteria.

Then, the full-texts of the studies that met criteria were further screened. The search strategy and screening processes were conducted independently by two authors AM and MS , and any disagreements were resolved through discussion with another author MKh.

According to the PRISMA latest guidelines 30 and our study purpose, we have followed these criteria to include or exclude the articles.

In order to maximize generalizability, participants included middle-aged to older women who were postmenopausal, ranging from healthy absence of disease diagnosis to frail with chronic diseases. Exercise training modalities included any mode of exercise training, such as aerobic training, resistance training, combined training, functional training, yoga, high-intensity interval training HIIT and Tai chi.

For the main outcomes, studies were included that measured at least one of the following body composition item: muscle mass and volume, muscle and fiber cross-sectional area CSA , fat-free mass FFM or lean mass if FFM was not available , fat mass, body fat percentage, waist circumference, and visceral fat.

Waist circumference was measured by tape and recorded in cm or inches. Exclusion criteria include non-English, non-full text articles conference abstracts , intervention with a duration of less than 4 weeks, and non-original studies. Two reviewers A H M and M H S independently extracted the following data from each included study: 1 study characteristics, including study design and year of publication; 2 participant characteristics, including sample size, biological sex, health status, age, and body mass index BMI ; 3 intervention characteristic, including training type, intensity, frequency, duration; and supervision of exercise sessions; 4 outcome variables and assessment methodologies; 5 pre- and post-intervention means and standard deviations SD , or mean changes and their SD values for outcomes.

In addition, when required, Getdata Graph Digitizer software was used for extracting data from figures For studies with multiple intervention arms, all comparisons were included and subsequently the sample size of the repeated intervention was divided by the number of comparisons to avoid double counting.

Furthermore, for studies that did not provide sufficient information, we have contacted the corresponding author of the relevant articles. The methodological quality for each included study was assessed by two independent reviewers AM and MS using the Physiotherapy Evidence Database PEDro tool 38 , and any disagreements were resolved through discussion with another author MKh.

However, we excluded 2 items including blinding of participants and intervention providers because these could not feasibly be blinded with regard to assigned exercise conditions during studies, and this may not influence the quality of studies Therefore, study quality was assessed based on the remaining 9 items.

Each source of bias was judged as low, high, or unclear due to insufficient detail Supplementary Table 2. In addition, sensitivity analyses were performed by omitting each study individually to determine whether results changed significantly.

Subgroup analyses were performed when there were more than 3 interventions for each subgroup. Interpretation of effect sizes was conducted using Cochrane guidelines as follows: 0.

In addition, trim and fill correction was used to address the potential effects of publication bias where relevant The search strategy retrieved records from PubMed, 1, records from Web of Science, records from CINAHL, and 1, records from MEDLINE.

After examination for duplicates, 1, articles were excluded, and then 2, articles were excluded after reviewing the titles and abstracts. A total of articles were identified for full-text assessment based on inclusion and exclusion criteria. An additional articles were excluded due to the reasons presented in Figure 1.

Finally, articles of randomized controlled trials with parallel arm-trials were included in the meta-analysis Figure 1. A total of 5, postmenopausal women were included in the meta-analysis. The mean age of participants was ranged from 51 to ~89 yrs.

Sample size of individual studies was ranged from 14 to participants. To increase the generalizability of our meta-analysis results, postmenopausal women regardless of their health status, comprised a wide range of health absence of disease and chronic disease characteristics metabolic diseases, cardiovascular diseases, cancer, and osteoporosis were included.

Full details of participant characteristics are summarized in Supplementary Table 1. Exercise training characteristics are summarized in Supplementary Table 1. All included studies compared the effects of exercise training versus a control group using random allocation.

Intervention durations of included studies was ranged from 4 weeks to 18 months, while frequency of exercise sessions was ranged from 1 to 7 per week, with three sessions being the most common. For type of exercise training, most of the included studies conducted aerobic, resistance, or combined training, and others used water-based exercise, yoga, Tai chi, Pilates, yoga and Korean dance, and functional training.

Exercise training was supervised in several studies, while other studies followed both supervised and unsupervised exercise training during the intervention period.

However, supervision details were not clearly reported in few studies. After accounting missing studies 5 studies with the trim and fill method, the overall change was 0. In addition, sensitivity analysis by omitting individual studies showed that significance did not change.

Subgroup analyses revealed a significant increase in muscle mass in middle-aged SMD: 0. Figure 2 Forest plot of the effects of exercise training versus control on muscle mass. SMD, standardized mean difference.

Based on 15 intervention arms, exercise training increased muscle and fiber CSA SMD: 0. Subgroup analyses revealed a significant increase in muscle mass in older adults SMD: 0.

Figure 3 Forest plot of the effects of exercise training versus control on muscle and fiber CSA. Based on 56 intervention arms, exercise training increased FFM WMD: 0.

After accounting missing studies 6 studies with the trim and fill method, the overall change was 0. Subgroup analyses revealed a significant increase in FFM mass in middle-aged WMD: 0. Figure 4 Forest plot of the effects of exercise training versus control on FFM. WMD, weighted mean difference.

Based on 43 intervention arms, exercise training decreased fat mass WMD: After accounting missing studies 16 studies with the trim and fill method, the overall change was Sensitivity analysis by omitting individual studies showed that significance did not change. Subgroup analyses revealed a significant decrease in fat mass in middle-aged adults WMD: Figure 5 Forest plot of the effects of exercise training versus control on fat mass.

Based on 85 intervention arms, exercise training decreased body fat percentage WMD: After accounting missing studies 28 studies with the trim and fill method, the overall change was Subgroup analyses revealed a significant decrease in fat percentage in middle-aged adults WMD: Figure 6 Forest plot of the effects of exercise training versus control on body fat percentage.

Based on 26 intervention arms, exercise training decreased waist circumference WMD: After accounting missing studies 3 studies with the trim and fill method, the overall change was Subgroup analyses revealed a significant decrease in waist circumference in middle-aged WMD: Figure 7 Forest plot of the effects of exercise training versus control on waist circumference.

Based on 11 intervention arms, exercise training decreased visceral fat SMD: After accounting missing studies 1 studies with the trim and fill method, the overall change was Figure 8 Forest plot of the effects of exercise training versus control on visceral fat.

In this meta-analysis with a large sample size, we have assessed the effects of exercise training on body composition, including muscle mass, muscle and fiber CSA, lean mass or fat-free mass, fat mass, body fat percentage, waist circumference, and visceral fat in postmenopausal women.

Our main findings revealed that exercise training positively influenced the body composition components, including muscle mass, muscle fiber CSA, FFM, fat mass, body fat percentage, waist circumference, and visceral fat in postmenopausal women.

Greater beneficial effects on fat mass outcomes were evidenced with aerobic training, whereas greater beneficial effects on muscle mass outcomes were reported with resistance training. In addition, a majority of these beneficial effects appears to be occurred with medium- and long-term interventions and also in middle-aged and older postmenopausal women.

The loss of muscle mass is considered to be an important contributor of strength loss in older adults with advancing age Menopausal period is associated with loss of muscle mass and muscle strength, which may progress to sarcopenia over a period of time 45 , and this phenomenon is primarily linked with natural decrease of estrogen in postmenopausal women 46 — Natural decline in estrogen was reported to cause endocrine dysfunction, metabolic syndrome, decreased bone mass density, muscle mass and strength, and increased visceral fat mass 45 , Nevertheless, loss of muscle mass due to age cannot be ruled-out as older men also represented with higher prevalence of sarcopenia.

Previous studies have shown sex-specific absolute loss of muscle loss, where elderly men are likely to have more muscle mass than elderly women, but tend to lose muscle mass faster 49 — Although men experienced greater loss of absolute muscle mass, women experienced greater decrements in muscle quality In this context, either type of exercise training is a practical strategy to prevent or delay the age-induced loss of muscle mass in men and women.

Previous reviews and meta-analyses have determined the effectiveness of exercise training and indicated that exercise is a one of the best approach to prevent and treat the muscle weakness in older adults 53 — 56 , however less is known about such benefits among postmenopausal women specifically.

Of particular importance for postmenopausal women with a high risk for sarcopenia, our results confirmed the positive effects of exercise training on muscle mass.

Although aerobic training may also have minimal effects on muscle size 57 , our results suggested that resistance training is important for increasing muscle mass, and did not indicate significant increases for aerobic training interventions.

Nevertheless, combined training was similarly effective as compared with resistance training. These results are consistent with previous meta-analyses indicating that resistance training increased muscle mass in older adults and even very old adults 28 , Although older men may gain more absolute muscle size in response to resistance exercise training, there are no biological sex differences in relative muscle strength gains The similar adaptations may be due to the fact that neither protein synthesis nor mTOR signaling differ between the biological sexes following resistance training Our results indicate that combined training is also effective for increasing muscle mass and FFM, suggesting that in postmenopausal women, muscle mass development can also be improved by combining resistance training with aerobic training.

In addition, our results suggested that muscle mass and FFM were increased irrespective of age groups in postmenopausal women. These adaptions are consistent with previous reviews suggesting the positive effects of resistance training in middle-aged, older, and very old adults 28 , 56 , However, it should be noted that muscle fiber CSA results should be interpreted with caution due to the small number of studies in some subgroups.

Despite the fact that exercise training is effective in reducing the fat mass, evidence regarding the types of exercise training in postmenopausal women is scarce. Although exercise training combined with diet has been shown to be an effective strategy for weight loss and fat mass reduction, regardless of exercise type, some systematic reviews and meta-analyses concluded that exercise interventions effectively reduced fat mass 59 — In general, our results suggested that exercise training is effective for reducing the adiposity markers including fat mass, body fat percentage, visceral fat, and waist circumference.

The potential mechanism for reductions in adiposity are related to altered energy balance where energy is expended during exercise as well as shortly after exercise as the body recovers, and increases in resting metabolic rate that follow increased lean body mass However, it is important to note that the type of exercise is important as a moderator of the effectiveness of exercise training on fat mass.

In line with a systematic review conducted by Schwingshackl and colleagues 65 , our results confirmed that aerobic training was effective in reducing fat mass, with small effects for resistance training Reductions in fat mass and related indicators following aerobic training interventions may be due to energy expenditure during the exercise bouts, which is likely to be higher as compared with resistance training 65 , In addition, we found that both aerobic and resistance trainings are effective in reducing body fat percentage.

However, it should be noted that body fat percentage, particularly following resistance training interventions may include reduced fat mass as well as increased FFM, and our results also showed a significant increase in FFM with resistance training.

Furthermore, we found that aerobic training is effective in reducing waist circumference and visceral fat, which was not the case for resistance training with regard to waist circumference. Visceral fat is known to be an important risk factor for many chronic diseases such as type 2 diabetes and cardiovascular diseases In addition, waist circumference is considered as a surrogate clinical measure for visceral abdominal fat mass In our study, there were a small number of studies that determined visceral fat, and therefore we could not perform subgroup analysis.

But subgroup analysis based on exercise type, revealed significant reductions in waist circumference The results for aerobic training were obtained from 3 studies, whereas there were 16 studies included for resistance exercise, which should be considered when interpreting the results.

Furthermore, our results indicated that combined training is effective for decreasing body fat percentage and waist circumference, suggesting that this type of training may be a suitable strategy for optimization of the combination of both fat loss and muscle gain in postmenopausal women. These results are important, especially regarding age factor, indicating the effectiveness of exercise training for postmenopausal women at any age.

Exercise training is also considered to be effective intervention for improving musculoskeletal health by a positive effect on bone mineral density 68 , Given that the increase in fat mass and the loss LBM affects on bone mineral density in postmenopausal women 70 , exercise training may have a positive effect on bone mineral density by improving body composition.

Our study has limitations that should be considered when interpreting the results. For outcome assessments, included studies measured body composition using different methods, which may lead to differences in reported results. There were significant heterogeneities among included studies with respect to some outcomes that may be due to differences in exercise interventions, participant characteristics, and the quality of the included studies.

We did not include any limitations regarding the health of participants, and non-communicable chronic diseases such as obesity and type 2 diabetes may influence exercise training adaptations. In addition, we did not include any limitations on the age of participants.

However, we performed subgroup analysis on middle-aged and older adults, showing positive effects of exercise regardless of age. Finally, we did not include bone mineral density as a outcomes.

Kelley GA, Kelley KA, Tran ZV Aerobic exercise and resting blood pressure: a meta-analytic review of randomized, controlled trials.

Prev Cardiol — Kim J, Wang Z, Heymsfield SB, Baumgartner RN, Gallagher D Total-body skeletal muscle mass: estimation by a new dual-energy X-ray absorptiometry method.

Kim J, Heshka S, Gallagher D et al Intermuscular adipose tissue-free skeletal muscle mass: estimation by dual-energy X-ray absorptiometry in adults.

Kotani K, Tokunaga K, Fujioka S et al Sexual dimorphism of age-related changes in whole-body fat distribution in the obese. Int J Obes Relat Metab Disord — Kraemer WJ, Patton JF, Gordon SE et al Compatibility of high-intensity strength and endurance training on hormonal and skeletal muscle adaptations.

Kraemer WJ, Nindl BC, Ratamess NA et al Changes in muscle hypertrophy in women with periodized resistance training. Laaksonen DE, Lakka H, Salonen JT, Niskanen LK, Rauramaa R, Lakka TA Low levels of leisure-time physical activity and cardiorespiratory fitness predict development of the metabolic syndrome.

Diabetes Care — Laaksonen DE, Niskanen L, Lakka HM, Lakka TA, Uusitupa M Epidemiology and treatment of the metabolic syndrome.

Ann Med — Lakka TA, Laaksonen DE Physical activity in prevention and treatment of the metabolic syndrome. Appl Physiol Nutr Metab — Leon AS, Sanchez OA Response of blood lipids to exercise training alone or combined with dietary intervention.

Med Sci Sports Exerc S—S McCarthy JP, Pozniak M, Agre JC Neuromuscular adaptations to concurrent strength and endurance training. Nindl BC, Harman EA, Marx JO et al Regional body composition changes in women after 6 months of periodized physical training.

Pascot A, Lemieux S, Lemieux I et al Age-related increase in visceral adipose tissue and body fat and the metabolic risk profile of premenopausal women.

Pritchard JE, Nowson CA, Strauss BJ, Carlson JS, Kaymakci B, Wark JD Evaluation of dual energy X-ray absorptiometry as a method of measurement of body fat. Eur J Clin Nutr — Rockl KS, Witczak CA, Goodyear LJ Signaling mechanisms in skeletal muscle: acute responses and chronic adaptations to exercise.

IUBMB Life — Sallinen J, Pakarinen A, Fogelholm M et al Serum basal hormone concentrations and muscle mass in aging women: effects of strength training and diet. Int J Sport Nutr Exerc Metab — Seip RL, Moulin P, Cocke T et al Exercise training decreases plasma cholesteryl ester transfer protein.

Arterioscler Thromb — Shen W, Punyanitya M, Chen J et al Waist circumference correlates with metabolic syndrome indicators better than percentage fat. Obesity Silver Spring — Sipilä S, Suominen H Effects of strength and endurance training on thigh and leg muscle mass and composition in elderly women.

Stefanick ML, Mackey S, Sheehan M, Ellsworth N, Haskell WL, Wood PD Effects of diet and exercise in men and postmenopausal women with low levels of HDL cholesterol and high levels of LDL cholesterol.

N Engl J Med — Tracy BL, Ivey FM, Hurlbut D et al Muscle quality. Effects of strength training in to year-old men and women. Tsuzuku S, Kajioka T, Endo H, Abbott RD, Curb JD, Yano K Favorable effects of non-instrumental resistance training on fat distribution and metabolic profiles in healthy elderly people.

Vasankari TJ, Kujala UM, Vasankari TM, Ahotupa M Reduced oxidized LDL levels after a month exercise program. Vincent KR, Braith RW, Bottiglieri T, Vincent HK, Lowenthal DT Homocysteine and lipoprotein levels following resistance training in older adults.

Wannamethee SG, Shaper AG, Lennon L, Whincup PH Decreased muscle mass and increased central adiposity are independently related to mortality in older men. Download references. This study was partly supported by a grant from the Ministry of Education, Finland and the Central Finland Health Care District, Jyväskylä Finland.

Department of Biology of Physical Activity, University of Jyväskylä, P. Box 35 VIV , , Jyväskylä, Finland. Department of Medicine, Kuopio University Hospital, University of Kuopio, Kuopio, Finland.

Department of Physiology, University of Kuopio, Kuopio, Finland. Department of Health Sciences, University of Jyväskylä, Jyväskylä, Finland. Human Performance Laboratory, Department of Kinesiology, University of Connecticut, Storrs, CT, USA.

You can also search for this author in PubMed Google Scholar. Correspondence to Elina Sillanpää. Reprints and permissions. Sillanpää, E. et al.

Compsoition password? Recover password. Remembered your password? Back to login. BBody your goal is to burn fat, gain muscle definition and shape, or simply improve your conditioning, there is one workout that trumps them all. That workout?

Body composition and endurance training -

Finally, as you complete these workouts, you should also notice that you are getting superior muscular density as well. Now that you know all the benefits this training has to offer, how do you add it to your workout protocol? The muscular endurance protocol involves ditching a target rep range and instead, performing as many reps as you can in a given time frame.

This is then continued until the entire circuit is finished, upon which, you can repeat again. For the purpose of the exercise line-up below, I want you to use this second work to rest ratio, move through the entire series of exercises, and then rest for 2 minutes.

Are you ready? Perform as many reps as possible of each exercise for 40 seconds followed by a 20 seconds rest one after the other with no rest in between. Next time you want to put your body to the test and see remarkable progress in your physique, give this workout a try.

BUILD A BETTER YOU - INSIDE FITNESS - SINCE New customer? Create your account Lost password? Your cart is empty. Written by Funk Roberts Whether your goal is to burn fat, gain muscle definition and shape, or simply improve your conditioning, there is one workout that trumps them all.

An appropriate energy intake supports optimal body function, determines the capacity for intake of macronutrients and micronutrients, and assists in manipulating body composition in athletes [ 9 ].

It is a challenge for each endurance athlete to appropriately match energy intake and TEE in order to achieve energy balance and thus, weight stability, both on a micro level i. This allows runners and cyclists to reach greater economy of movement and better thermoregulatory capacity from a favorable ratio of weight to surface area and less insulation from subcutaneous fat tissue.

Elite endurance athletes are therefore characterized by low body mass and body fat content. For example, in elite Kenyan endurance runners, the body fat percentage was 7. In the same athletes, body mass index BMI was However, these athletes were in peak physical conditions as the investigations were undertaken and a low body fat percentage and body weight might be an advantage for competition.

Achieving a negative energy balance and a concomitant loss of body and fat masses in preparation for competition can be accomplished in phases with high daily TEE solely by the reduction of energy intake, since any further training load increases could cause overtraining [ 12 ]. Therefore, the nutritional goals and requirements of endurance athletes are not static over the training year.

Since endurance athletes undertake a periodized training program and follow periodized body composition goals, the nutritional support also needs to be periodized [ 9 ]. Usually, the annual training schedule of an elite endurance athlete is divided into distinct phases, each with very specific objectives.

This is necessary to maximize physiological adaptations for improved performance, usually scheduled to peak around the main competitions of the year [ 14 ].

The principle of training periodization was first introduced in the s by the Soviet trainer Leo Matveyev [ 15 ] and has not fundamentally changed since then [ 14 ]. The basis of this model is to prepare the athlete for one or more major competitions during the year by separating the training into the following three main phases macrocycles : preparatory, competitive, and transition phases [ 15 ].

The preparatory phase is characterized by predominantly high-volume training at moderate intensities, which improves endurance capacity and provides a more efficient use of fuel substrates. During the late preparatory phase, training volume is reduced while intensity is gradually increased.

The goal of this phase is to reach peak performance and to transfer the training effects into the competitive phase, where exercise intensity is the highest.

In the week before an important competition, volume and intensity are typically decreased taper phase to allow the body to optimally recover for competition. The days and weeks after a main competition are characterized by low-intensity and low-volume training, with goals to induce regeneration and to prepare the athlete mentally and physically for the next training cycle transition phase [ 14 , 16 ].

Although the concept of training periodization in elite endurance sports has been established for a long time, the coupling of periodized training with nutrition and body composition has gained scientific awareness only recently [ 17 ].

Nowadays, there are guidelines for carbohydrate, protein, and fat intake during training and competition phases, not exclusively focusing on endurance sports [ 19 — 21 ]. Meanwhile, for endurance athletes, sport-specific dietary intake recommendations were developed only for a few endurance disciplines e.

But it remains unclear whether endurance athletes are actually following these nutrient guidelines across all seasonal training phases.

The validity of either body composition, energy intake, or TEE-determination in athletes strongly depends on the methods used. The measurement of body composition in general is prone to error. It has been shown that acute food or fluid ingestion [ 28 ], subject positioning [ 29 ], previous physical activity [ 30 ], and hydration status [ 31 ] have an impact on reliability of body composition measurement.

Since endurance athletes often train several times per day, it might be difficult to assure best conditions for body composition assessment. According to a recent methodology review performed by Nana et al. However, other methods like skinfold measurements require highly experienced investigators [ 32 ] and strongly depend on the number of measurement sites and the formula used to calculate the percentage of body fat [ 33 ].

Therefore, it is important to report standardization protocols in order to evaluate the quality of data assessment. It was shown that the magnitude of under-reporting increases as energy requirements increase [ 34 ]. Since endurance athletes are often characterized by high TEE, we must assume that these athletes are very prone to a high percentage of under-reporting.

For determination of TEE objective methods such as doubly labelled water DLW or heart frequency measurements are available. However, in many studies subjective methods such as activity records and activity questionnaires are used in order to assess the activity level and TEE of subjects.

These methods estimate TEE or activity level and their validity strongly depends on the breadth of the activity dimensions analyzed. Therefore, the purpose of this study was to 1 systematically analyze TEE, energy intake, and body composition in highly trained athletes of various endurance disciplines and of both sexes with focusing on objective assessment methods and 2 analyze fluctuations in these parameters across the training season.

We hypothesized that endurance athletes show large fluctuations of TEE during different seasonal training phases due to differing exercise loads, and concomitant alterations in energy intake and body composition. The review protocol was developed according to the Meta-analysis of Observational Studies in Epidemiology Guidelines for meta-analyses and systematic reviews of observational studies [ 53 ].

A systematic literature search was performed to retrieve articles pertaining to body composition, energy intake, and TEE in endurance athletes across the training season. One researcher JH conducted the search for publications on 31 January in the electronic databases MEDLINE via PubMed and SPORTDiscus with Full Text via EBSCOHost.

A hand search of relevant reviews was performed to obtain additional articles missed by the database search. No individual or organization was contacted to receive further publications. Limits included articles published in the English language, human studies, and publishing date limits between and January Keywords were searched as free text in the title, abstract, and subject heading.

A detailed overview of search strategies in the two databases can be obtained in Additional file 1 : Table S1. Two researchers independently assessed the eligibility of the records by screening the title, abstract, and keywords for inclusion and exclusion criteria.

An agreement between the two researchers was quantified by kappa statistics [ 54 ]. The full texts of all abstracts meeting the eligibility criteria were retrieved and subjected to a second assessment for relevance performed by one author JH.

Articles were excluded from the review if 1 the article was only in abstract form or a case report, 2 data could not be split between the sexes where both male and female subjects were analyzed , 3 body composition was assessed by skinfold measurements, 4 daily TEE was assessed by the use of questionnaires, and 5 descriptive quantitative results were not reported in a text or tabular form.

Any difference in assessments between the two researchers was discussed in the first instance or resolved by a third author KM. All relevant articles were examined for full methodological quality using a modified version of the Downs and Black [ 55 ] checklist for the assessment of the methodological quality of randomized and non-randomized studies of health care interventions.

According to Fox et al. The maximum possible total score was Two researchers assessed the study quality independently, with differences resolved by consensus or by a third author KM. The agreement between the two researchers was quantified by kappa statistics [ 54 ]. Based on the assessment of the methodological study quality, no studies were excluded and no additional analyses were undertaken.

The methodological quality of the included studies is shown in Additional file 2 : Table S2. If the same subjects were analyzed during different time points in the same seasonal phase e.

To enable comparisons between studies, reported units were converted into standard units. These conversions were performed by using the reported mean values of the outcomes. According to the definition by Wang et al.

Duplicate publications from the same data set were identified according to the criteria published in the Cochrane Handbook for Systematic Reviews of Intervention [ 58 ]. The most complete record was then used for data extraction. According to the traditional periodization model, the reported seasonal training phases of data assessment were clustered into three groups that included the preparation phase, the competition phase, and the transition phase [ 14 — 16 ].

A detailed overview of the clustering can be obtained in Table 1. The main outcome measures were body composition fat mass, FFM , energy intake, and TEE of endurance athletes across the season.

Once all of the relevant data were extracted, the weighted mean and standard deviation of the weighted mean were calculated for the main outcome variables.

Based on the number of subjects examined within the study, relative to the total number of subjects examined for the specific variable, a percentage weight w was allocated to each result within each outcome variable and used for the calculation of the overall weighted mean X̅ w and standard deviation of the weighted mean SD w for each variable [ 59 ].

Statistical analyses were performed using the statistical software SPSS statistics version 22 for Windows IBM Corp. Kolmogorov-Smirnov tests were performed to check for normal distributions. All parameters were normally distributed except body mass, fat mass, and FFM.

To test for comparisons of subgroups, one-factorial analyses of variance ANOVAs with Scheffé post hoc tests parametric and Kruskal-Wallis tests H -test with Mann-Whitney U post hoc tests non-parametric were performed.

When multiple non-parametric post hoc tests were applied, Bonferroni-adjusted alpha levels were applied. Since parameters for body composition were not normally distributed, we abstained from multiple statistical comparisons between seasonal training phases and endurance disciplines to reduce the risk of type I errors.

For comparisons of energy intake and TEE during different seasonal training phases, paired t -tests were used. The separate analysis of studies, where energy intake and TEE were assessed in parallel, and longitudinal studies that reported energy intake during different training season phases, were performed using the free software for meta-analysis Review Manager 5 version 5.

The flow chart for the study selection process is shown in Fig. Data were extracted from 82 studies in endurance athletes, with 53 studies assessing body composition, 48 energy intake, and 14 TEE.

The kappa value of 0. Flow chart for the present systematic review. The characteristics of the included studies for body composition, energy intake, and TEE are shown in Table 2.

In Additional file 3 : Table S3, an overview of excluded studies and the reasons for their exclusion can be found.

The cumulative number of subjects included in the analysis was Runners On average, the mean age, VO 2max , and training volume of study estimates were A detailed overview of physical characteristics of included study estimates is shown in Table 3.

Body composition was assessed by DXA in In Ten studies For determination of energy intake, dietary records Dietary recall 3. Half of the studies Other methods included heart rate monitoring The studies using heart rate monitoring for estimation of TEE used individual derived linear relationships between heart rate and oxygen consumption HR—VO 2 during different tasks to estimate the oxygen cost and energy expenditure during the observation period.

Two third of the studies used the h heart rate recordings and the individual HR—VO 2 relationship to estimate TEE gross calculation. Two studies calculated TEE by summation of activity energy expenditure based on individual HR—VO 2 relationship and resting metabolic rate RMR; net calculation.

In total, 14 studies where TEE was assessed during various seasonal training phases were identified by the literature search. In addition, due to limited data, no separations between the sexes and endurance disciplines of TEE were performed.

No data for TEE of females during competition phase available. Table 4 provides a detailed overview of the absolute and relative energy intakes differentiated by sex, endurance discipline, and seasonal training phase.

Reasons for the lower energy intake in female rowers might be that during preparation phase the athletes often reduce their energy intake in order to reduce concomitantly their body weight to start in the lightweight category. Runners, in general, profit from a low body mass since greater economy of movement and better thermoregulatory capacity from a favorable ratio of weight to surface area and less insulation from subcutaneous fat tissue is reached [ 10 ].

A separate analysis of energy balance was performed by including only studies where both energy intake and expenditure were assessed in parallel. The relative energy deficit was 6. Forest plot for comparison of energy intake during preparation and competition phase in endurance athletes.

In more than half However, a separate statistical analysis assessing seasonal training phase differences of TEE between eumenorrheic and amenorrheic athletes could not be performed, since the cumulative number of subjects was too low in the single training phases.

Since the percentage of female data on total data varies between the seasonal training phases, we further split the data by sex. Fat-free mass and fat mass of endurance athletes during preparation, competition, and transition phase.

In more than one third However, a separate analysis between eumenorrheic and amenorrheic athletes could not be performed, since the cumulative number of subjects during the different seasonal training phases was too low. We found that some, but not all, of the investigated outcomes depended on the time point of data assessment during seasonal training.

TEE was highest during the competition phase and higher than energy intake in all seasonal training phases. Alterations in TEE did not lead to adaptations of energy intake in females, whereas in males, a higher absolute energy intake during the competition phase was observed.

The finding that male endurance athletes demonstrated the highest fat mass values during the competition phase and the lowest FFM during the transition phase seems to be an anomaly from the pooling of data.

Our systematic search initially yielded many studies where TEE, energy intake, or body composition in endurance athletes were investigated.

This is unfortunate since our analysis clearly illustrates how training volume and related TEE vary importantly with seasonal training phases. Specifically and expectedly, both absolute and relative TEEs were significantly higher during the competition phase compared to the preparation phase.

During the transition phase, limited data for TEE and energy intake of endurance athletes was available. Only for body composition, it was possible to compare with other seasonal training phases, although the number of study estimates and therefore, explanatory power, was weak.

Future research on elite athletes should focus on the effects of a sudden stop or reduction in TEE on body composition e. There exist only a few studies with conflicting results where this question has been examined.

Ormsbee and Arciero investigated the effects of 5 weeks of detraining on body composition and RMR in eight male and female swimmers [ 65 ]. RMR decreased, whereas fat mass and body weight increased with detraining.

In contrast, LaForgia et al. showed that after 3 weeks of detraining, no differences in RMR and percentage of fat mass occurred in male endurance athletes [ 38 ]. Unfortunately, energy intake was not reported in either of these studies.

The most obvious explanation for these energy deficits is likely the classical issue of under-reporting energy intake through self-assessment in human studies.

Since under-reporting increases in magnitude as energy requirements increase [ 34 ], we must assume that under-reporting in the present study estimates was more important during the competition phase. Another explanation for the negative energy balance might be the low accuracy and precision of methods used to estimate energy intake in athletes in the articles included in our review.

For example, mostly dietary records with a mean observation time of 4. According to Magkos and Yannakoulia, for athletes, a 3—7-day diet-monitoring period would be enough for reasonably accurate and precise estimations of habitual energy and macronutrient consumption [ 34 ].

However, other methods like FFQs and dietary recalls were also used for energy intake estimations. These methods are both memory-dependent and show lower accuracy and precision than prospective methods like dietary records [ 72 ].

However, even when only articles were considered where energy intake was assessed by the use of dietary records, the error remained high 2. Finally, the high negative energy balance during the competition phase may also be explained by the fact that, apart from one study, all included studies investigated the TEE during the days with actual competition and not during habitual training days in the competition phase.

Thus, it is likely that the TEE during this phase was over-estimated. During the preparation phase, a negative energy balance leading to increased energy store utilization might be desirable by coaches and athletes to reach a sport-specific body composition, but during the competition phase, body composition should not be modified anymore since it is typically already at its optimum.

There was one study in which dietary intake was strictly controlled since the subjects were in confinement. Brouns et al. simulated a Tour de France race in a metabolic chamber and calculated the daily energy balance from the energy expended and energy intake as calculated from daily food and fluid consumption [ 73 ].

They found a positive energy balance during active rest days whereas during the exercise days, a significant negative energy balance was observed. The authors concluded that if prolonged intensive cycling increases energy expenditure to levels above a certain threshold probably around 20 MJ or kcal , athletes are unable to consume enough conventional food to provide adequate energy to compensate for the increased energy expenditure.

The authors of a recent review addressing the criticisms regarding the value of self-reported dietary intake data reasoned that these should not be used as a measure of energy intake [ 74 ]. Thus, there is an urgent need for better methods of dietary intake quantification, such as dietary biomarkers and automated image analysis of food and drink consumption [ 74 ].

Thus, energy balance is an output from those systems. Since the results of the present study indicate a high negative energy balance in endurance athletes, we must assume that the athletes also demonstrate low energy availability.

However, due to the limited data, it was not possible to account for other clinical markers e. We recommend that energy balance-related studies in endurance athletes should also assess and report clinical markers, such as bone mineral density and menstrual status, in order to assess the clinical consequences of the mismatch of TEE and energy intake.

The aggregate analysis yielded a surprising finding. In male endurance athletes, the absolute and relative fat mass was highest during the competition phase. In contrast, during the transition phase, FFM was lowest, which goes along with our expectations with a decrease in exercise volume and intensity.

For the female athletes, we did not find these fluctuations in body composition, except for a higher body fat content during the preparation phase compared to the transition phase. We believe that these findings are due to the paucity of data and to the fact that the number and type of athletes varied between seasonal training phases.

Further studies with longitudinal assessments of body composition are required to support these findings. However, in only 5. According to Nana et al. It has been shown that the use of a non-standardized protocol increased the variability for total and fat-free soft tissue mass compared to a standard protocol, which might include a loss in ability to detect an effect of an intervention that might have relevance for sports performance [ 78 ].

The use of non-standardized protocols and the concomitant higher variability might explain some of the unexpected findings of body composition changes in athletes of the present study.

In male endurance athletes, absolute energy intake was higher during the competition phase compared to the preparation phase. The relative energy intake was not different, which can be explained by the apparent significant increase of body mass during the competition phase, and is likely an artifact of the aggregation of data from various studies.

In female athletes, neither absolute nor relative energy intake was different between seasonal phases. When focusing on longitudinal studies that assessed energy intake during different training seasons in the same cohort, there was a tendency for male athletes to show greater fluctuations in energy intake.

In female cross-country skiers, the energy intake was higher during the preparation phase [ 50 ], whereas in female runners and swimmers, the energy intake was higher during the competition phase [ 47 ].

However, summing up both studies, no significant differences between training season phases were found. In contrast, male endurance athletes showed a significantly higher energy intake during the competition phase, as seen in male runners [ 44 ], cross-country skiers [ 50 ], swimmers [ 43 ], and triathletes [ 49 ].

Although some of the included studies showed greater energy intake in male endurance athletes during the preparation phase cyclists [ 46 , 48 ], swimmers [ 43 ] , the power of these studies was too low to change the results. However, since energy intake varies in male endurance athletes depending on the training season phase, it indeed seems appropriate to adapt dietary recommendations according to the different training season phases, as proposed by Stellingwerff et al.

This is, to our knowledge, the first systematic review focusing on fluctuations in TEE, energy intake, and body composition in endurance athletes. To increase the robustness of the outcomes of our systematic review, we excluded articles where body composition was estimated by skinfold measurements and equations.

The accuracy of skinfold measurements depends on the number of measurement sites and the formula used to calculate the percentage of body fat [ 33 ]. Since there are many different techniques [ 79 ], it is impossible to compare results accurately between studies.

Furthermore, skinfold measurements cannot be used to assess intra-abdominal adipose tissue and are highly variable when assessors with limited training and experience perform the measurements [ 32 ]. Of course, since skinfolds are very often used for body composition assessments, the exclusion of these articles reduced the total number of articles measuring body composition, which were included in the present systematic review.

The inclusion of articles with skinfold body composition determination would have led to a higher number of study estimates and comparisons of different seasonal training phases would have a higher explanatory power.

The same is true for estimations of TEE. We included only articles measuring TEE in a more objective way such as DLW and excluded articles where TEE was assessed by questionnaires or activity records. This led to the inclusion of a limited number of high-quality studies.

Limitations of the present study relate to the limited cumulative number of subjects, which provided a low explanatory power, and the classification of the different seasonal training phases. In the literature, several similar-sounding terms have been used to describe time points of data collection in athletes.

However, assigning the appropriate classification into one of the three seasonal training phases is essential and has a great impact on the final analysis.

Furthermore, if articles reported several time points of data collection within one seasonal training phase, we included only the first time point into the analysis in order to assure standardization and avoid selection bias. The exclusion of other time points might have led to the loss of interesting data.

Our analysis highlights the important seasonal fluctuations in TEE, energy intake, and body composition in male and female endurance athletes across the training season. The present review supports the statement of the current position stand of the American College of Sports Medicine ACSM that energy and nutrient requirements are not static and that periodized dietary recommendations should be developed [ 9 ].

Importantly, our analysis again shows the uselessness of self-reported dietary intake, a well-known limitation to energy balance studies, in endurance athletes.

The important underreporting suggested by our analysis again raises the question of whether self-reported energy intake data should be used for the determination of energy intake and illustrates the need for more valid and applicable energy intake assessment methods in free-living humans [ 74 ].

Since we observed a lack of data during the transition phase, future research should focus on the assessment of TEE, energy intake, and body composition on a reduction in training intensity and volume, such as at the end of the competitive season.

In addition, future studies dealing with energy balance and nutrient intake in elite endurance athletes should always mention the time point of data assessments e. Ravussin E, Bogardus C. Relationship of genetics, age, and physical fitness to daily energy expenditure and fuel utilization.

Am J Clin Nutr. CAS PubMed Google Scholar. Westerterp KR. Physical activity and physical activity induced energy expenditure in humans: measurement, determinants, and effects. Front Physiol.

Billat VL, Demarle A, Slawinski J, Paiva M, Koralsztein JP. Physical and training characteristics of top-class marathon runners.

Med Sci Sports Exerc. Article CAS PubMed Google Scholar. Stellingwerf T. Case study: Nutrition and training periodization in three elite marathon runners. Int J Sport Nutr Exerc Metab. Article PubMed Google Scholar.

Zapico AG, Calderon FJ, Benito PJ, Gonzalez CB, Parisi A, Pigozzi F, et al. Evolution of physiological and haematological parameters with training load in elite male road cyclists: a longitudinal study.

J Sports Med Phys Fitness. Fiskerstrand A, Seiler KS. Training and performance characteristics among Norwegian international rowers Scand J Med Sci Sports.

Neal CM, Hunter AM, Galloway SD. A 6-month analysis of training-intensity distribution and physiological adaptation in Ironman triathletes.

J Sports Sci. Westerterp KR, Saris WH, van Es M, ten Hoor F. Use of the doubly labeled water technique in humans during heavy sustained exercise. J Appl Physiol CAS Google Scholar. Thomas DT, Erdman KA, Burke LM.

American College of Sports Medicine Joint Position Statement. Nutrition and Athletic Performance. O'Connor H, Slater G. Losing, gaining and making weight for athletes. In: Lanham-New S, Stear S, Sherriffs M, Collins A, editors.

Sport and exercise nutrition. West Sussex: Wiley-Blackwell; Chapter Google Scholar. Fudge BW, Westerterp KR, Kiplamai FK, Onywera VO, Boit MK, Kayser B, et al. Evidence of negative energy balance using doubly labelled water in elite Kenyan endurance runners prior to competition.

Br J Nutr. Sundgot-Borgen J, Meyer NL, Lohman TG, Ackland TR, Maughan RJ, Stewart AD, et al. How to minimise the health risks to athletes who compete in weight-sensitive sports review and position statement on behalf of the Ad Hoc Research Working Group on Body Composition, Health and Performance, under the auspices of the IOC Medical Commission.

Br J Sports Med. World Health Organization WHO. Obesity: preventing and managing the global epidemic. Report of a WHO Consultation, WHO Technical Report Series Geneva: World Health Organization; Google Scholar.

Issurin VB. New horizons for the methodology and physiology of training periodization. Sports Med. Matveyev L. Periodisierung des sportlichen Trainings. Bompa T, Haff G. Theory and methodology of training. Champaign: Human Kinetics; Stellingwerff T, Boit MK, Res PT. Nutritional strategies to optimize training and racing in middle-distance athletes.

Cardiac hypertrophy leads to increased stroke volume and increased maximum cardiac output. It leads to an Increase in number of red blood cells and capillarisation the process of new capillaries forming which takes place in the alveoli in the lungs and in the skeletal muscle, therefore increasing the amount of oxygen transferred to working muscles and CO2 removed.

This can help obese people in their day to day lives by giving them a more efficient transport system. Also transformations to the respiratory system, leading to increased vital capacity, increased number of functioning alveoli and the strength of respiratory muscles internal and external intercostal and diaphragm increased lung capacity and volume.

Endurance exercise is often combined in training programmes with other exercises, such as HIIT and resistance training , to achieve more successful results.

A trial that used a combination of both endurance and HIIT training on groups of obese participants using either HIIT, Endurance or combined training found that while there was no significant differences observed between the groups, improvement in V̇o 2peak was observed only in the combined training group.

Endurance exercise has a lot to offer in the battle against obesity, with both long term and short term benefits to the body. With effects such as lowering BMI and total body fat composition, decreasing body mass and increasing lung capacity, endurance training can improve the lifestyles of many obese people.

Prescribing endurance exercise to obese patients is step in the right direction for medical health professionals, in combating the obesity epidemic currently being faced.

Endurance activity keeps the heart, lungs and circulatory system healthy and improves overall fitness. As a result, people who get the recommended regular physical activity can reduce the risk of many diseases such as diabetes, heart disease, stroke and obesity.

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Cmposition We Body composition and endurance training a systematic review and meta-analysis to investigate the effect Athletic performance snack ideas exercise training on body composition outcomes in postmenopausal women. Body composition and endurance training PubMed, Annd of Science, CINAHL, and Medline were searched to identify composiyion randomized controlled trials which traibing effect of exercise trraining versus control in postmenopausal women. Results: One hundred and one studies involving 5, postmenopausal women were included in the meta-analysis. Furthermore, subgroup analyses results revealed that aerobic and combined training had greater beneficial effects on fat mass outcomes, whereas resistance and combined training had greater beneficial effects on muscle mass outcomes. Discussion: Overall, our results revealed that exercise training is effective for improving body composition in postmenopausal women. To be specific, aerobic training is effective on fat loss, whereas resistance training is effective on muscle gain.

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