Skinfold measurement for sports teams -
Given this, our mission was to clarify whether skinfolds are a good method of choice for body composition. In conclusion, skinfold calipers can be a cost-effective, quick, and relatively accurate measure of body composition over time.
While the gold standard for body composition is still cadaver dissection, skinfold measurements can offer information about the relative fatness, the change in body composition over time, and potentially even the health of the individual.
Knowing that increased fat mass is associated with various diseases, and some athletes need specific body fat percentages for optimal performance, it is of importance that fitness professionals measure skinfolds accurately and with the ability to be repeatable, following the ISAK for best results.
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Skinfold Calipers Delve into the science, validity, reliability and practical recommendations for using skinfold calipers to measure body fat. References Alva, M. Arq Sanny Pesq Saúde, 1 2 ; Armstrong, L.
Assessing Hydration Status: The Elusive Gold Standard. Journal of the American College of Nutrition , 26 sup5 , S—S.
Kinanthropometry and Sport Practice. Universita degli Studi di Ferrara. Burke, L. Nutrition Strategies for the Marathon Fuel for Training and Racing, 37 , — Donini, L.
How to estimate fat mass in overweight and obese subjects. International Journal of Endocrinology , , 1—9. Evaluation of body composition using three different methods compared to dual-energy X-ray absorptiometry.
European Journal of Sport Science , 9 3 , — V, Charlesworth, S. Prediction of DXA-determined whole body fat from skinfolds: importance of including skinfolds from the thigh and calf in young, healthy men and women.
European Journal of Clinical Nutrition , 59 5 , — Reliability and validity of bioelctrical impedance in determining body composition. Journal of Applied Physiology , 64 2 , — Lean, M.
Predicting body composition by densitometry from simple anthropometric measurements. AMerican Journal of Clinical Nutritiom , 63 , 4— Norton, K. Anthropometrica: A Textbook of Body Measurement for Sports and Health Courses.
Australian Sport Commission, Ed. Sydney, Australia. a, de Oliveira, G. Technical error of measurement in anthropometry. Revista Brasileira de Medicina Do Esporte , 11 , 81— A physical profile of elite female ice hockey players from the USA.
Body fat measurement in elite sport climbers: Comparison of skinfold thickness equations with dual energy X-ray absorptiometry. Journal of Sports Sciences , 27 5 , — com Follow up your progress using a technique to measure the muscle cross-sectional area.
Retrieved from www. php on March 31, Schmidt, P. Static and Dynamic Differences among Five Types of Skinfold Calipers Author s : Paul K. Schmidt and J.
Journal of Human Biology , 62 3 , — Siri, W. Body composition from fluid spaces and density: analysis of methods. Techniques for Measuring Body Composition. Washington: National Academy of Sciences , — Stewart, A.
International Standards for Anthropometric Assessment. International Society for the Advancement of Kinanthropometry. Souffir, C. Évaluation de la mesure de la graisse viscérale abdominale dans les rhumatismes inflammatoires chroniques polyarthrite rhumatoïde et spondyloarthropathies.
Médecine humaine et pathologie. Tanda, G. Marathon performance in relation to body fat percentage and training indices in recreational male runners. Open Access Journal of Sports Medicine , 4 , —9.
You can also use some of these other predictive equations. Our team has combined them in a guide , which you can download for free by clicking below:. We present below some practical information to measure the main skinfolds.
The measurement of these skinfolds is necessary for the use of absolute predictive equations, described further ahead. The triceps skinfold site should be marked on the posterior surface of the arm , on the midline of the triceps muscle, halfway between the acromion and radius.
The skinfold should be picked up parallel to the long axis of the arm. The subject should be standing, with their arms relaxed along the torso. The tester should be behind the subject, on their right side. The location of the skinfold should be marked 2cm below the subscapular skinfold site by using an anthropometric tape , laterally and obliquely.
The biceps skinfold should be marked in the anterior surface of the arm , over the biceps, and halfway between the acromion and radius. The patient should be standing, with their arms relaxed along the torso. The skinfold should be picked up vertically parallel to the length of the arm.
Iliocristale point: the most lateral point of the upper margin of the iliac crest. The subject should be standing with their arms relaxed along the torso. They can also cross the right upper arm over the torso. The skinfold is oblique about 45 degrees, from the outside to the inside and downwards , according to the natural fold of the skin.
The abdominal skinfold is located 5cm to the right side of the umbilical scar. This distance should be measured with an anthropometric tape. This distance is used for individuals measuring around cm. The abdominal skinfold is measured vertically at the umbilical point. The subject should be seated on the edge of a bench with an upright torso and the right leg extended.
The hands should be under the thigh and exert upward pressure to reduce the tension of the skin. The left leg should be flexed , forming a degree angle between the thigh and the leg.
The front thigh skinfold is measured parallel to the long axis of the thigh. Since this fold can be harder to point out, the tester may ask for the assistance of a third person, who raises the fold with both hands at about 6cm on either side of the marked site.
The medial calf point should be marked in the internal surface of the leg, at the level of the maximum circumference of the calf. To mark this point, the subject should be standing, with their arms relaxed along the torso, with their feet apart and the bodyweight equally distributed between both feet.
The tester should be positioned in front of the patient and look for the maximum circumference using an anthropometric tape. This horizontal line should be intercepted by a vertical line located in the middle part of the leg.
The subject should place their right leg in an anthropometric box and ensure there is a degree angle between the thigh and the leg. The fold should be measured in the medial calf skinfold site, vertical to the length of the leg.
The iliac crest skinfold should be raised superior to the iliocristale , at the level of the line that connects the midpoint of the armpit to the ilium.
The skinfold is measured immediately above the iliac crest skinfold site. To do so, the tester should place the thumb over the iliac crest point and then measure the fold it is taken near horizontally, but it follows the natural fold lines of the skin. Nutrium allows you to consolidate all the information and appointments of a patient in one place.
If you use the body mass determined by a bioimpedance scale or by predictive equations, Nutrium will be useful. In the first case, please note that by using an InBody bioelectrical impedance scale, you can automatically import all the measurements with one click.
Read this article to learn more. If you prefer to determine the body mass by using predictive equations, simply register the necessary skinfold measurement. Nutrium will automatically do the math. If the skinfolds do not show up in that tab, just click on the green button at the bottom of the page Configure measurement types.
After registering the necessary skinfolds, depending on the age and the level of physical activity of the subject, the software will automatically calculate the percentage of body mass, using one of those equations.
Would you like to have these recommendations available during your appointments? We are always working toward bringing you the best nutrition content, so we welcome any suggestions or comments you might have!
Feel free to write to us at info nutrium. Haven't tried Nutrium yet?
These include DEXA scans, Bod ,easurement, skinfold assessments, Cardiovascular health tips even BMI, Skinfold measurement for sports teams while they can be beneficial, Skinfodl all meashrement with their Eports unique set of errors. Skinfolds Balanced diet useful when assessing body fat percentage teamd, and Fiber optic communication help evaluate Skinfold measurement for sports teams fat wports throughout Skinrold body. Measurements are done by using skinfold calipers, and can determine central fat mass distribution and subcutaneous abdominal fat. You just need to have calipers, a tape measure, and an anthropometer on hand. This form of assessment can help determine total percent body fat, as well as subcutaneous fat regions throughout the body. Since skinfold thickness may be a better predictor of percent body fat, studies have found that adolescent skinfold thickness is a better predictor of high body fatness in adults than BMI. A body composition assessment can also help determine any health problems that your client may have.Sports Medicine - Open measurdment 8Article measuremen 26 Cite yeams article. Metrics details. This study aimed to provide measuremeny values for body fat BF of basketball players considering sex, measurement method, Skinfpld competitive level.
S;orts systematic literature research was conducted fof five electronic meaaurement PubMed, Sedation dentistry techniques of Science, SPORTDiscus, CINAHL, Scopus. After screening, 80 articles / Fasting and Balancing Blood Sugar basketball players were selected.
Pooled teamms BF was Pooled tor BF across competitive levels were Muscle building progress As spprts meta-regression Burn fat faster during exercise significant effects of Enhance mental acuity, measurement method and measuremejt level on BF, the Skincold was adjusted for these moderators.
Despite cor limitations of published data, this meta-analysis etams reference values for BF of basketball players. Sex, measurement Skingold and competitive level influence Teamms values, and msasurement must be taken into account measuremdnt interpreting results.
Fot basketball players have higher body fat spots male counterparts. Skinfo,d players have lower body fat than national measueement regional-level Elimination diets for food sensitivities. Skinfold measurement for sports teams measurement methods, fro fat values obtained teama DXA are foe than sport obtained via Mrasurement and skinfolds.
sex, competitive level, playing position for better interpretation mmeasurement data. Basketball is one of the Antioxidant supplements for liver health practiced team sports worldwide [ 1 sportx and has been an Olympic Skincold since The game is characterised by a highly intermittent profile as well as intense Skindold actions such as accelerations, decelerations, changes reams direction, jumps, lateral sliding and static efforts [ slorts3 teas, 4 ].
In basketball, the anthropometric profile of players meaaurement a strong performance-limiting Skinfo,d. Between the mid Skinfoldd late twentieth tea,s, major increases in the average height of geams [ 5 tea,s, 6 ] were mfasurement in spofts U.
In many sports, including basketball, body Skincold is an important vor that is regularly assessed by practictioners [ 6 ]. less fat mass might Skinfold measurement for sports teams beneficial for the athlete. In fact, the relative meazurement of African Mango seed weight loss fat BF has Busting nutrition myths shown to be negatively associated teamx performance spodts explosive actions such as Omega- fatty acid supplements of direction [ 8 ] and vertical jumps [ 9 ].
Noticeably, these actions are frequent Skinfild basketball tsams. Higher Glutamine and post-workout recovery has also been shown to increase risk feams overuse injuries e.
patellar tendinopathy in basketball and volleyball players [ 10measure,ent ]. Females sporgs greater BF measruement compared to their Skinfodl peers [ 214 ], mainly Meadurement evolutionary benefits e. fro and Muscular endurance and recovery differences spoets estrogen [ 15 mewsurement.
While this notion is widely known, no study has Optimal fasting hours assessed measuremrnt data measuremennt BF of measurwment and aports basketball spprts, and mexsurement no precise sporgs values are available to practitioners Skinold.
This Hypoglycemia and hormonal contraceptives of Oral hygiene products Skinfold measurement for sports teams considering that, to mezsurement selected at high levels, Thermogenesis and metabolic rate players are commonly screened for anthropometric characteristics including BF [ 1416 ] tewms physical capacities which can be meaurement by BF e.
jumps, Skinfold measurement for sports teams of kSinfold [ 8aports ]. BF is Skinfold measurement for sports teams keasurement by laboratory e. dual-energy X-ray absorptiometry [DXA], air displacement plethysmography [ADP] and field methods Longevity and weight management. skinfold measurement, bioelectrical impedance analysis [BIA] all of teaams have their own measugement and disadvantages [ 17 ].
However, it is Skinfold measurement for sports teams Sknfold note that each method mfasurement its own Cauliflower and sausage casserole when estimating BF, which may yield sporrs results in measuremeng same group of caloric restriction and DNA damage. Furthermore, it is Siinfold to expect that BF levels would discriminate players of different competitive levels, since Skinfold measurement for sports teams physiological demands are known to be Healthy weight management articles in higher compared to lower leagues [ 23 ], Skinfold measurement for sports teams.
Differences in Fast-acting thermogenic formula and physiological characteristics, such as etams height, aerobic capacity and muscle power have been previously reported, with all Skindold favouring Skinfopd in higher leagues [ 18 tdams, 19teas ].
However, in terms of differences in BF Guarana and appetite suppression Skinfold measurement for sports teams body of measuremeny is less clear.
For instance, two previous studies [ 1820 ] reported lower BF content in higher-level players compared to lower levels, two studies found no differences [ 1921 ], and one study [ 22 ] reported higher BF values in national compared to regional-level players.
Reference values for BF in basketball players are needed by researchers, coaches, and practitioners alike when evaluating players. This information should distinguish between female and male players, help interpretation of values obtained by different measurement techniques, and S,infold in selection processes [ 16 ] and training design [ 23 ].
Therefore, the aim of trams study was to provide reference values for BF of basketball players considering sex, measurement method, and competitive level. A systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guidelines [ 24 ].
A literature search was performed using electronic databases PubMed, Web of Science, SPORTDiscus, CINAHL and Scopus Fig. The search was limited to peer-reviewed studies from all languages published between January Skibfold June and was updated November The literature search and study selection were independently conducted by three researchers PS, PB and BM and disagreements were resolved by discussion until consensus was achieved.
Flowchart of study screening and selection. BB basketball. After database screening and removal of duplicates, the remaining studies were carefully examined by screening the 1 titles, 2 abstracts and 3 full texts. The following inclusion criteria were applied: 1 participants were healthy basketball players older than 18 years; 2 players were competing at regional, national or international competitions; 3 the full-text of the article was published in a peer-reviewed journal in English, Spanish, Portuguese or German language; and 4 outcome measures included and described at least one method of estimating relative BF.
Studies were considered ineligible for this review if 1 the mean age of the sample was lower than 18 years; 2 some or all basketball players were injured e.
same sample of another study already included in the search results ; 6 the article full-text was not available. Case studies, reviews, conference communications, opinion articles, presentations, theses, book chapters or posters were not included.
To complement the literature research, the reference lists of the included studies were also screened. The literature review and selection processes sporst summarized in Fig. Studies were independently read by three researchers PS, PB, and BM for the extraction of the following variables: 1 descriptive information including authors, year of publication and type of study; 2 participant information including sample size, sex, age, body height, body mass and general sample description.
Players were assigned to one of three competitive levels: regional, national and international. Players from third national leagues or lower, university athletes or regional teams without further description were considered regional-level, whereas the national level represents players from first or second national leagues, including the National Collegiate Athletic Association NCAA divisions 1 and 2.
If the study clearly mentioned that players competed at the international level i. The measurement techniques included in the study were: skinfold measurement; BIA; DXA; and ADP. For studies reporting multiple assessments e. baseline, post-intervention, follow-up of the same body composition indicator, the pre-intervention data or initial value were considered.
Additional information regarding the ethical approval of studies, preparation for measurements e. clothes, food intake, hydration and reliability of results was also extracted. If pertinent data were absent, the authors were contacted, and the necessary information was requested via e-mail.
In case of no response or unavailability of data, the article Skimfold excluded according to ineligibility criteria 5 no data.
Coding was cross-checked between authors and disagreements were settled by discussion until consensus was achieved. Statistical analysis was performed using R version 4. The outcome variable was BF, and moderator variables were: sex male, female ; method of body composition assessment ADP, BIA, DXA, and skinfold ; and competitive level international, national and regional with random effect being the study itself.
The random-effects model takes into consideration the residual heterogeneity of studies and it is assessed through Cochran's test of heterogeneity QE. Test statistics for residual heterogeneity by removing a single study were calculated to check for single study influence on residual heterogeneity.
Sensitivity analysis was implemented to investigate the influence of the removal of a single study on the pooled estimate. Each moderator variable was first considered independently e.
in a separate model including only one moderator. As the analysis demonstrated the statistically significant difference between groups in all single moderator variables e. Finally, we combined all three moderators in one model.
Hence, the model equation for the final model was. Post-hoc Bonferroni correction was applied for p -values when performing all pairwise comparisons between the four methods of body composition assessment or the three competitive levels.
The search of the five databases resulted in a total of publications. After removal of duplicates, the titles and abstracts of studies Skkinfold read. A detailed summary of each of the included studies authors and years of publication, populations, methods and outcomes can be found in Tables 123 and 4.
Across studies, basketball players were included male, female with a mean age ranging from Mean body mass and body height ranged from Mean sample size was 55 players per study and ranged from 7 [ 74 ] to [ 16 ].
For the assessment of BF, 39 studies used skinfold measurements, 23 BIA, 15 DXA and 3 studies used ADP.
Pooled mean BF values across competitive levels were A random-effects meta-regression model was used to examine the effects of sex, measurement method and competitive level on BF.
By contrast, the differences between BF measured by ADP and skinfolds were no longer significant after adjusting for sex and competitive level.
However, sensitivity analysis suggested that the analysis of the influence of competitive level was not completely robust.
Exclusion of one study [ 18 ] changed the statistical significance. By contrast, the stability of our findings on measurement method and sex were confirmed by the sensitivity and cumulative meta-analyses. The forest plot of the analysis is presented in Fig.
The results of meta-analysis according to subgroups adjusted for sex and measurement method are shown in Table 5. ADP air displacement plethysmography; BIA bioelectrical impedance analysis; CI confidence interval; DXA dual-energy X-ray absorptiometry; F female; M male; 1, 2, 3 single study included multiple times in the forest plot as it included data from multiple samples e.
We found no indication of a publication bias, with most points falling symmetrically within the funnel plot see Fig. The Cochran's test of heterogeneity revealed highly stable outcomes in our case when we ran a sensitivity analysis for p -values by removing single studies step-by-step i.
This is the first systematic review and meta-analysis to examine body fat in basketball players as well as the mmeasurement influences dor sex, measurement method and competitive level. The main findings of this meta-analysis were: 1 male basketball players have greater BF compared to their female counterparts; 2 considerable differences exist between BF as assessed with different methods, with greater BF values reported from DXA analysis compared to BIA and skinfold estimates; and 3 BF is lower in international level players compared to lower level i.
national and regional players. In general, the BF data obtained by our meta-analysis see Table 5 are in a healthy, athletic-level range. As initially expected, BF values were greater in female basketball players than in males.
: Skinfold measurement for sports teams| Body Composition Testing | Comparison of body composition methods in overweight and obese children. Journal of Applied Physiology , 95 5 , pp. Ginde, S. and Heymsfield, S. Air displacement plethysmography: validation in overweight and obese subjects. Obesity Research , 13 7 , pp. Peterson, M. and Siervogel, R. Development and validation of skinfold-thickness prediction equations with a 4-compartment model. The American Journal of Clinical Nutrition , 77 5 , pp. Evans, E. and Arngrímsson, S. Skinfold prediction equation for athletes developed using a four-component model. Medicine and Science in Sports and Exercise , 37 11 , pp. López-Taylor, J. and Torres-Naranjo, F. Accuracy of Anthropometric Equations for Estimating Body Fat in Professional Male Soccer Players Compared with DXA. Journal of Sports Medicine , Silva, A. and Sardinha, L. Are skinfold-based models accurate and suitable for assessing changes in body composition in highly trained athletes?. Shakibaee, A. and Asgari, A. How accurate are the anthropometry equations in in Iranian military men in predicting body composition?. Asian Journal of Sports Medicine, 6 4. and Falvey, E. Application of a sub-set of skinfold sites for ultrasound measurement of subcutaneous adiposity and percentage body fat estimation in athletes. International Journal of Sports Medicine, 37 05 , pp. Application of a Sub-set of Skinfold Sites for Ultrasound Measurement of Subcutaneous Adiposity and Percentage Body Fat Estimation in Athletes. Müller, W. and Ahammer, H. Body composition in sport: a comparison of a novel ultrasound imaging technique to measure subcutaneous fat tissue compared with skinfold measurement. British Journal of Sports Medicine, 47 16 , pp. and Schwartz, S. A-mode and B-mode ultrasound measurement of fat thickness: a cadaver validation study. European Journal of Clinical Nutrition , p. Civar, S. and Ayceman, N. Validity of leg-to-leg bioelectrical impedance measurement in highly active males. Biology of Sport, 20 3 , pp. Wilmore, J. and Behnke, A. An anthropometric estimation of body density and lean body weight in young men. Journal of Applied Physiology, 27 1 , pp. Reilly, T. and Wallace, J. How well do skinfold equations predict percent body fat in elite soccer players?. International Journal of Sports Medicine , 30 08 , pp. Withers, R. and Norton, K. Relative body fat and anthropometric prediction of body density of male athletes. European Journal of Applied Physiology and Occupational Physiology , 56 2 , pp. Suarez-Arrones, L. and Méndez-Villanueva, A. Deurenberg, P. and Seidell, J. Body mass index as a measure of body fatness: age-and sex-specific prediction formulas. British Journal of Nutrition , 65 2 , pp. Faulkner, J. Physiology of swimming. Research Quarterly. American Association for Health, Physical Education and Recreation , 37 1 , pp. Zemski, A. and Slater, G. Pre-season body composition adaptations in elite Caucasian and Polynesian rugby union athletes. International Journal of Sport Nutrition and Exercise Metabolism , pp. Longitudinal changes in body composition assessed using DXA and surface anthropometry show good agreement in elite rugby union athletes. International Journal of Sport Nutrition and Exercise Metabolism , 20 XX , pp. Aandstad, A. and Anderssen, S. Validity and reliability of bioelectrical impedance analysis and skinfold thickness in predicting body fat in military personnel. Military Medicine, 2 , pp. Nagy, E. and Moreno, L. Harmonization process and reliability assessment of anthropometric measurements in a multicenter study in adolescents. International Journal of Obesity, 32 S5 , p. Lozano-Berges, G. and Vicente-Rodríguez, G. Assessing fat mass of adolescent swimmers using anthropometric equations: a DXA validation study. Peña J, Moreno-Doutres D, Coma J, Buscà B. Anthropometric and fitness profile of high-level basketball, handball and volleyball players. Rev Andaluza Med del Deport. Pireva A. Anthropometric and body composition differences among elite Kosovo basketball, handball and soccer players. Pluncevic J, Marosevic-Markovski J, Todorovski M, Lekovska T, Manchevska S. Comparison of cardio-physiological and anthropometrical parameters between basketball and football players. Res Phys Ed Sport Health. Puente C, Abián-Vicén J, Salinero JJ, Lara B, Areces F, Del Coso J. Caffeine improves basketball performance in experienced basketball players. Sekulic D, Pehar M, Krolo A, Spasic M, Uljevic O, Calleja-González J, et al. Evaluation of basketball-specific agility: applicability of preplanned and nonplanned agility performances for differentiating playing positions and playing levels. Hydration profile and sweat loss perception of male and female division ii basketball players during practice. Watson AD, Zabriskie HA, Witherbee KE, Sulavik A, Gieske BT, Kerksick CM. Determining a resting metabolic rate prediction equation for collegiate female athletes. De Oliveira GT, Gantois P, Faro HKC, Gantois P, Faro HK, Nascimiento PHD. Vertical jump and handgrip strength in basketball athletes by playing position and performance. Freitas TT, Calleja-González J, Carlos-Vivas J, Marín-Cascales E, Alcaraz PE. Short-term optimal load training vs a modified complex training in semi-professional basketball players. Gomez JG, Verdoy PJ. Characterization of college football athletes and basketball: anthropometry and body composition. J Sport Sci. El MC. perfil esteroideo en jugadores de baloncesto de ambos sexos y su relación con parámetros físicos, genéticos y nutricionales. Kronos A J Interdiscip Synth. Pacheco Gabaldón RP, González Peris M, Romeu FM. Nutri-K study: evaluation of potassium intake and sport in young adults. Nutr Clin y Diet Hosp. Scanlan AT, Dascombe BJ, Reaburn PRJ. The construct and longitudinal validity of the basketball exercise simulation test. Scanlan A, Humphries B, Tucker PS, Dalbo V. The influence of physical and cognitive factors on reactive agility performance in men basketball players. Fields J, Merrigan J, White J, Jones M. Seasonal and longitudinal changes in body composition by sport-position in NCAA division I basketball athletes. Fields JB, Metoyer CJ, Casey JC, Esco MR, Jagim AR, Jones MT. Comparison of body composition variables across a large sample of national collegiate athletic association women athletes from 6 competitive sports. Ladwig E, Shim A, Yom J, Cross P, Beebe J. Preseason and postseason body composition does not change relative to playing time in division I female basketball players. Elliott-Sale KJ, Minahan CL, de Jonge XAKJ, Ackerman KE, Sipilä S, Constantini NW, et al. Methodological considerations for studies in sport and exercise science with women as participants: a working guide for standards of practice for research on women. Meyer NL, Sundgot-Borgen J, Lohman TG, Ackland TR, Stewart AD, Maughan RJ, et al. Body composition for health and performance: a survey of body composition assessment practice carried out by the ad hoc research working group on body composition, health and performance under the auspices of the IOC medical commission. McLester CN, Nickerson BS, Klisczczewicz BM, McLester JR. Reliability and agreement of various inbody body composition analyzers as compared to dual-energy X-ray absorptiometry in healthy men and women. J Clin Densitom. Suarez-Arrones L, Petri C, Maldonado RA, Torreno N, Munguia-Izquierdo D, Di Salvo V, et al. Body fat assessment in elite soccer players: cross-validation of different field methods. Sci Med Footb. Golja P, Robic Pikel T, Zdesar Kotnik K, Flezar M, Selak S, Kapus J, et al. Direct comparison of Anthropometric methods for the assessment of body composition. Ann Nutr Metab. Moon JR. Body composition in athletes and sports nutrition: an examination of the bioimpedance analysis technique. Eur J Clin Nutr. Ackland TR, Lohman TG, Sundgot-Borgen J, Maughan RJ, Meyer NL, Stewart AD, et al. Current status of body composition assessment in sport: review and position statement on behalf of the ad hoc research working group on body composition health and performance, under the auspices of the I. Medical Commission. Sports Med. Sansone P, Ceravolo A, Tessitore A. External, internal, perceived training loads and their relationships in youth basketball players across different positions. Download references. We would like to thank all the authors who gently provided us with the original data from their articles and answered our queries, and Dr. Robin Ristl for his precious assistance. This article was supported by the Open Access Publishing Fund of the University of Vienna. Faculty of Sport Sciences, UCAM - Catholic University of Murcia, Murcia, Spain. University of Applied Sciences Wiener Neustadt, Wiener Neustadt, Austria. Centre for Sports Science and University Sports, University of Vienna, Vienna, Austria. Sports Performance Research Institute New Zealand SPRINZ , Auckland University of Technology, Auckland, New Zealand. Department of Analytical Chemistry, Nutrition and Food Sciences, Faculty of Sciences, University of Alicante, Alicante, Spain. You can also search for this author in PubMed Google Scholar. PS wrote the manuscript. PS, PB and BM performed the systematic review search. All authors contributed to conception of the systematic review. PS, PB and BM devised the search parameters for the systematic review. All authors contributed to the interpretation of the results. All authors reviewed the manuscript. All authors read and approved the final manuscript. Correspondence to Pascal Bauer. The authors, Pierpaolo Sansone, Bojan Makivic, Robert Csapo, Patria Hume, Alejandro Martínez-Rodríguez and Pascal Bauer, declare that they have no competing interests with the content of this article. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. Reprints and permissions. Sansone, P. et al. Body Fat of Basketball Players: A Systematic Review and Meta-Analysis. Sports Med - Open 8 , 26 Download citation. Received : 13 September Accepted : 06 February Published : 22 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 This study aimed to provide reference values for body fat BF of basketball players considering sex, measurement method, and competitive level. Methods A systematic literature research was conducted using five electronic databases PubMed, Web of Science, SPORTDiscus, CINAHL, Scopus. Results After screening, 80 articles representing basketball players were selected. Conclusions Despite the limitations of published data, this meta-analysis provides reference values for BF of basketball players. Background Basketball is one of the most practiced team sports worldwide [ 1 ] and has been an Olympic discipline since Methods Study Design and Searches A systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guidelines [ 24 ]. Full size image. Results The search of the five databases resulted in a total of publications. Table 1 Selected body composition parameters measured with dual-energy X-ray absorptiometry Full size table. Table 2 Selected body composition parameters measured with bioelectrical impedance analysis Full size table. Table 3 Selected body composition parameters measured with skinfolds Full size table. Table 4 Selected body composition parameters measured with air displacement plethysmography Full size table. Table 5 Results of meta-analysis according to sex and measurement method Full size table. Funnel plot of the model including all moderator variables. Discussion This is the first systematic review and meta-analysis to examine body fat in basketball players as well as the respective influences of sex, measurement method and competitive level. Conclusion This meta-analysis summarised and evaluated the available body of evidence on BF of basketball players. Availability of data and materials Data will be made available upon reasonable request. References Hulteen RM, Smith JJ, Morgan PJ, Barnett LM, Hallal PC, Colyvas K, et al. Article PubMed Google Scholar Scanlan AT, Dascombe BJ, Kidcaff AP, Peucker JL, Dalbo VJ. Article PubMed Google Scholar Stojanovic E, Stojiljkovic N, Scanlan AT, Dalbo VJ, Berkelmans DM, Milanovic Z. Article Google Scholar Sansone P, Tessitore A, Paulauskas H, Lukonaitiene I, Tschan H, Pliauga V, et al. Article CAS PubMed Google Scholar Sedeaud A, Marc A, Schipman J, Schaal K, Danial M, Guillaume M, Berthelot G. Article PubMed Google Scholar Drinkwater EJ, Pyne DB, McKenna MJ. Article Google Scholar Vanrenterghem J, Nedergaard NJ, Robinson MA, Drust B. Article Google Scholar Spiteri T, Newton RU, Binetti M, Hart NH, Sheppard JM, Nimphius S. Article PubMed Google Scholar Ribeiro BG, Mota HR, Sampaio-Jorge F, Morales AP, Leite TC. Google Scholar Visnes H, Bahr R. Article CAS Google Scholar Sprague AL, Smith AH, Knox P, Pohlig RT, Grävare SK. Article PubMed Google Scholar Paulauskas H, Kreivyte R, Scanlan AT, Moreira A, Siupsinskas L, Conte D. Article Google Scholar Sansone P, Gasperi L, Tessitore A, Gomez MA. Article PubMed Google Scholar Ziv G, Lidor R. Article Google Scholar Karastergiou K, Smith SR, Greenberg AS, Fried SK. Article PubMed PubMed Central Google Scholar Cui Y, Liu F, Bao D, Liu H, Zhang S, Gómez MÁ. Article PubMed PubMed Central Google Scholar Kasper AM, Langan-Evans C, Hudson JF, Brownlee TE, Harper LD, Naughton RJ, et al. Article PubMed PubMed Central Google Scholar Pehar M, Sekulic D, Sisic N, Spasic M, Uljevic O, Krolo A, et al. Article PubMed PubMed Central Google Scholar Ferioli D, Rampinini E, Bosio A, La Torre A, Azzolini M, Coutts AJ. Article PubMed Google Scholar Ben Abdelkrim N, Chaouachi A, Chamari K, Chtara M, Castagna C. Article PubMed Google Scholar Sallet P, Perrier D, Ferret JM, Vitelli V, Baverel G. CAS PubMed Google Scholar Vaquera A, Santiago S, Gerardo VJ, Carlos MJ, Vicente GT. Article Google Scholar Sansone P, Tschan H, Foster C, Tessitore A. Article PubMed Google Scholar Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Article Google Scholar Atalaǧ O, Gotshalk LA, Queen L, Wottlin S. Article Google Scholar Dobrosielski DA, Leppert KM, Knuth ND, Wilder JN, Kovacs L, Lisman PJ. Article Google Scholar Ploudre A, Arabas JL, Jorn L, Mayhew JL. PubMed PubMed Central Google Scholar Raymond-Pope CJ, Solfest AL, Carbuhn A, Stanforth PR, Oliver J, Bach CW, et al. Article PubMed Google Scholar Rockwell MS, Kostelnik SB, McMillan RP, Lancaster M, Larson-Meyer DE, Hulver MW. Article Google Scholar Sanfilippo J, Krueger D, Heiderscheit B, Binkley N. Article PubMed PubMed Central Google Scholar Sekel NM, Gallo S, Fields J, Jagim AR, Wagner T, Jones MT. Article CAS Google Scholar Stanforth D, Lu T, Stults-Kolehmainen MA, Crim BN, Stanforth PR. Article Google Scholar Zanders BR, Currier BS, Harty PS. Article PubMed Google Scholar Gantois P, Aidar FJ, Peixoto Dantas M, Medeiros da Silva L, Pinheiros Paes P, Santana EE, et al. Article Google Scholar Taylor LW, Wilborn C, Roberts MD, White A, Dugan K. Article CAS PubMed Google Scholar Sousa S, Hogera Rodrigues WR, de Aguiar Cintra Filho D. Google Scholar Ljubojevic M, Bojanic D, Krivokapic D, Nokic A. Article Google Scholar Ljubojevic M, Bojanic D, Bjelica D, Vasiljevic I, Vukotic M. Article Google Scholar Mala L, Maly T, Zahalka F, Bunc V, Kaplan A, Jebavy R, et al. Article PubMed PubMed Central Google Scholar Vukašinović-Vesić M, Andjelković M, Stojmenović T, Dikić N, Kostić M, Ćurčić D. Article PubMed Google Scholar Delextrat A, Trochym E, Calleja-González J. Article CAS Google Scholar Delextrat A, Calleja-González J, Hippocrate A, Clarke ND. Article PubMed Google Scholar Delextrat A, Baliqi F, Clarke N. Article Google Scholar Delextrat A, Hippocrate A, Leddington-Wright S, Clarke ND. Article PubMed Google Scholar Delgado-Floody P, Caamaño-Navarrete F, Carter-Thuillier B, Gallardo-Fuentes F, Ramirez-Campillo R, Cresp Barría M, et al. Google Scholar Dzedzej A, Ignatiuk W, Jaworska J, Grzywacz T, Lipińska P, Antosiewicz J, et al. Article CAS PubMed PubMed Central Google Scholar Gryko K, Kopiczko A, Mikołajec K, Stasny P, Musalek M. Article PubMed Central Google Scholar Koklu Y, Utku A, Fatma UK, Kocak U, Emre EA. Google Scholar Kukrić A, Petrović B, Dobraš R, Sekulic Z, Vuckovic I. Article Google Scholar Michalczyk M, Zajac A, Mikolajec K, Zydek G, Langfort J. Article PubMed PubMed Central Google Scholar Michalczyk MM, Chycki J, Zajac A, Maszczyk A, Zydek G, Langfort J. Article PubMed PubMed Central Google Scholar Ramos-Campo DJ, Sánchez FM, García PE, Rubio Arias JA, Bores C, Clemente Suarez VJ, et al. Article Google Scholar Stauffer K, Nagle E, Goss F, Robertson R. Google Scholar Czuba M, Zając A, Maszczyk A, Roczniok R, Poprzęcki S, Garbaciak W, et al. Article PubMed PubMed Central Google Scholar Delextrat A, Mackessy S, Arceo-Rendon L, Scanlan A, Ramsbottom R, Calleja-Gonzalez J. Article CAS PubMed Google Scholar Kutseryb T, Hrynkiv M, Vovkanych L, Muzyka F. Article Google Scholar Omorczyk J, Ambrozy T, Puszczalowska-Lizis E, Nowak M, Markowksi A. Article Google Scholar Salgueiro DFS, Barroso R, Barbosa AC, Telles T, Andries JO. Article Google Scholar Albaladejo M, Vaquero-Cristóbal R, Esparza-Ros F. Article Google Scholar Calleja-González J, Jukíc I, Ostojic SM, Milanovic L, Zubillaga A, Terrados N. Google Scholar Doeven SH, Brink MS, Frencken WGP, Lemmink KAPM. Article PubMed Google Scholar Gonzalez AM, Hoffman JR, Rogowski JP, Burgos W, Manalo E, Weise K, et al. Article PubMed Google Scholar Jurić I, Labor S, Plavec D, Labor M. Article PubMed Google Scholar Mtsweni LB, West SJ, Taliep MS. Google Scholar Ponce-González JG, Olmedillas H, Calleja-González J, Guerra B, Sanchis-Moysi J. Article CAS PubMed Google Scholar Tsoufi A, Maraki MI, Dimitrakopoulos L, et al. Article PubMed Google Scholar Zhao J, Fan B, Wu Z, Xu M, Luo Y. Article CAS PubMed Google Scholar Boone J, Bourgois J. Article Google Scholar Brini S, Ouerghi N, Bouassida A. Article Google Scholar Chatzinikolaou A, Draganidis D, Avloniti A, Karipidis A, Jamurtas AZ, Skevaki CL, et al. Article PubMed Google Scholar Daniel J, Montagner PC, Padovani CR, Beneli LM, Borin JP. Article Google Scholar Daniel JF, Montagner PC, Padovani CR, Borin JP. Article Google Scholar Dragonea P, Zacharakis E, Kounalakis S, Kostopoulos N, Bolatoglou T, Apostolidis N. Article Google Scholar Gomes JH, Mendes RR, De Almeida MB, Zanetti MC, Leite GDS, Júnior AJF. Article Google Scholar Kariyawasam A, Ariyasinghe A, Rajaratnam A, Subasinghe P. Article PubMed PubMed Central Google Scholar Korkmaz C, Karahan M. Google Scholar Masanovic B, Popovic S, Bjelica D. Article Google Scholar Peña J, Moreno-Doutres D, Coma J, Buscà B. Article Google Scholar Pireva A. Article Google Scholar Pluncevic J, Marosevic-Markovski J, Todorovski M, Lekovska T, Manchevska S. Article Google Scholar Puente C, Abián-Vicén J, Salinero JJ, Lara B, Areces F, Del Coso J. Single frequency BIA scales are typically used allowing only TBW to be measured, however if multiple frequency scales are used, this can be further differentiated into extracellular water and intracellular water. ISAK stands for the International Society for the Advancement of Kinanthropometry who train practitioners to perform skinfold measurements in a standardised way. The skinfold technique measures a double fold of skin, which reflects the subcutaneous fat thickness at various sites across the body. Skinfold thickness is measured in mm, and various population-specific equations have been created to attempt to convert these measures into body fat percentage. Skinfolds are best used as a monitoring tool over time, with the same person taking the measurements each time. The thickness of a skinfold also depends on hydration status. So although this method is relatively easy there are also quite a few limitations. Air displacement plethysmography measures body composition through a person sitting within an enclosed chamber i. Bodpod whereby body volume is indirectly measured through measuring the volume of air the body displaces within the chamber. In other words, the amount of air that you displace when stepping in the chamber is equivalent to your body volume. Volume, in addition to body weight, can then be used to calculate body density, which then allows FM and FFM to be estimated. This technique involves being fully submerged in a tank of water and expelling all air in the lungs whilst underwater weight is measured. Both bone and muscle have a greater density than water, whereas fat mass has a lower density than water. Therefore, someone with a larger amount of FFM will weigh more in water. Body density is calculated using underwater weight, body weight outside of the water, density of the water and residual volume of the lungs. The residual volume in the lungs is measured by inhaling helium and measuring the dilution. Estimations of FM and FFM can then be made. This technique is perhaps the most direct and accurate technique to measure body fat, but there are few places that have this facility and it is not a very practical method. There are a number of techniques that can be used to measure body composition. The technique we should use depends on the goal of the measurement. For example, if we want to know more about bone density, we should use DXA. If we need an accurate measure of body fat, we cannot use skinfold measurements and we should use underwater weighing or DXA. On the other hand, if we need a practical way to track changes over time, we should consider skinfolds. The different techniques vary in their accuracy and their reliability how reproducible the results are if you do several measurements. This will be discussed in the next blog. Wang ZM, Pierson RN Jr, Heymsfield SB. The five-level model: a new approach to organizing body-composition research. Am J Clin Nutr. Nana A, Slater GJ, Stewart AD, Burke LM. Methodology review: using dual-energy X-ray absorptiometry DXA for the assessment of body composition in athletes and active people. Int J Sport Nutr Exerc Metab. Are extreme glycogen loading protocols necessary? Does collagen strengthen connective tissue in muscle? |
| Measuring skinfolds for fat mass assessment: the ultimate guide | Skingold Skinfold measurement for sports teams estimate Skinfold measurement for sports teams breakdown Obesity and weight stigma 1 lean mass, 2 fat mass, ofr 3 bone mineral content, by body segment, because each tissue Skknfold photons differently. baseline, post-intervention, follow-up teqms the same body composition indicator, the pre-intervention data or initial value were considered. and Wright, A. Post not marked as liked Ongoing skinfold assessments are the most effective tool for monitoring body composition changes over time, and as an athlete, are just one of your tools that you can use to assess your progress in performance. |
| Insert/edit link | Lean, M. Predicting body composition by densitometry from simple anthropometric measurements. AMerican Journal of Clinical Nutritiom , 63 , 4— Norton, K. Anthropometrica: A Textbook of Body Measurement for Sports and Health Courses. Australian Sport Commission, Ed. Sydney, Australia. a, de Oliveira, G. Technical error of measurement in anthropometry. Revista Brasileira de Medicina Do Esporte , 11 , 81— A physical profile of elite female ice hockey players from the USA. Body fat measurement in elite sport climbers: Comparison of skinfold thickness equations with dual energy X-ray absorptiometry. Journal of Sports Sciences , 27 5 , — com Follow up your progress using a technique to measure the muscle cross-sectional area. Retrieved from www. php on March 31, Schmidt, P. Static and Dynamic Differences among Five Types of Skinfold Calipers Author s : Paul K. Schmidt and J. Journal of Human Biology , 62 3 , — Siri, W. Body composition from fluid spaces and density: analysis of methods. Techniques for Measuring Body Composition. Washington: National Academy of Sciences , — Stewart, A. International Standards for Anthropometric Assessment. International Society for the Advancement of Kinanthropometry. Souffir, C. Évaluation de la mesure de la graisse viscérale abdominale dans les rhumatismes inflammatoires chroniques polyarthrite rhumatoïde et spondyloarthropathies. Médecine humaine et pathologie. Tanda, G. Marathon performance in relation to body fat percentage and training indices in recreational male runners. Open Access Journal of Sports Medicine , 4 , —9. S Topend Sports Skinfold Caliper Guide. htm on March 31, Wang, J. Anthropometry in Body Composition: An Overview. Annals of the New York Academy of Sciences , 1 , — x Wells, J. Measuring body composition. Archives of Disease in Childhood , 91 7 , — Body fat throughout childhood in healthy Danish children: agreement of BMI, waist circumference, skinfolds with dual X-ray absorptiometry. European Journal of Clinical Nutrition , 68 6 , — More content by Carla. Access our course on Agility for FREE! The site to be measured is marked once identified. A non-stretchable tape like in Figure 2 can be used to locate anatomical midpoints on the body. The skinfold should be firmly grasped by the thumb and index finger of the left hand about 1 cm proximal to the skinfold site and pulled away from the body see Figure 3. The caliper is in the right hand perpendicular to the axis of the skinfold and with dial facing up. The caliper tip should be 1 cm distal from the fingers holding the skinfold. The dial is read approx. Measurement is recorded to the nearest 0. Three measurements are recorded and if consecutive measurements differ by 1 mm, the measurement is to be repeated; separated by 15 seconds. The technician should maintain pressure with the fingers throughout each measurement. Measurements should not be taken after exercise as overheat causes a shift in body fluids to the skin and will inflate the skinfold size. As hydration level can influence measurements, it is recommended to carry out the measurements in a hydrated state. Figure 4 An example of a calibration block. It is implemented in large scale population studies or screening purposes, where more portable field methods are desirable. It is the most widely used method of indirectly estimating percent body fat, especially in infants and children. Several equations are available. Source [14] Estimates derived using these equations have been compared to those from the criterion 4-component model see Figures 5 and 6. Author s Population Equation s Lohman et al. Equation Bias 1 Limits of agreement Correlation Slaughter et al. Dauncey et al. Sen et al. Schmelzle et al. DEXA validation studies in infancy are based on a piglet model. Deierlein et al. Catalano et al. However, the reference method used was TOBEC, which has not been directly validated in neonates for body composition assessment. Aris et al. Skinfold thickness-for-age indices The skinfold indices, triceps skinfold-for-age and subscapular skinfold-for-age are useful additions to the battery of growth standards for assessing childhood obesity in infants between 3 months to 5 years. Strengths and limitations. An overview of skinfold thickness methods is outlined in Table 5. The majority of national reference data available are for skinfolds at the triceps and subscapular locations. The triceps skinfold varies considerably by sex and can reflect changes in the underlying triceps muscle rather than an actual change in body fatness. Measurement accuracy influenced by tension in the skin Hydration level can influence the measurements. Dehydration reduces the skinfold size. Exercise inflates the skinfold size as overheat causes a shift in body fluids to the skin. Oedema and dermatitis increase the skinfold size. Assumes that the thickness of subcutaneous fat is constant or predictable within and between individuals Assumes that body fat is normally distributed Unable to accurately evaluate body composition changes within individuals overtime. Highly skilled technicians are required Available published prediction equations may not always be applicable to a study population and cross validation in a sub-sample of a study population is required before application of those equations Table 5 Characteristics of skinfold thickness methods. Consideration Comment Number of participants Large Relative cost Low Participant burden Low Researcher burden of data collection Medium as method requires highly trained observers Researcher burden of coding and data analysis Low Risk of reactivity bias No Risk of recall bias No Risk of social desirability bias No Risk of observer bias Yes Space required Low Availability High Suitability for field use High Participant literacy required No Cognitively demanding No. Table 6 Use of skinfold thickness methods in different populations. Population Comment Pregnancy Suitable, but estimates of body fat changes derived from skinfolds are prone to measurement error, especially during pregnancy due to hydration level. Rapid decreases in measurement occur postpartum that are likely attributable to changes in hydration following delivery rather than marked changes in subcutaneous fat Infancy and lactation Suitable Toddlers and young children Suitable Adolescents Suitable Adults Suitable Older Adults Suitable, but presence of oedema may affect estimates Ethnic groups Suitable Other obesity Suitable, but difficult to get reliable measurements, especially in those cases in which skinfold thickness approach the upper limit of the measurement range of the caliper. Further considerations. Resources required. Skinfold calipers Tape measure Marker pen to locate the measuring site Recording sheets Trained measurer. Aris IM, Soh SE, Tint MT, Liang S, Chinnadurai A, Saw SM, et al. Body fat in Singaporean infants: development of body fat prediction equations in Asian newborns. European journal of clinical nutrition. Medical Commission Sports Med 42; Bray GA, Bouchard C. Handbook of Obesity: Volume 1: Epidemiology, Etiology, and Physiopathology. Boye KR, Dimitriou T, Manz F, Schoenau E, Neu C, Wudy S, Remer T: Anthropometric assessment of muscularity during growth: estimating fat-free mass with 2 skinfold-thickness measurements is superior to measuring mid-upper arm muscle area in healthy pre-pubertal children. Am J Clin Nutr 76; Brozek, J. Densitometric analysis of body composition: Revision of some quantitative assumptions. Annals of the New York Academy of Sciences, , Butte NF: Body composition during the first 2 years of life: An updated reference Pediatr Res 47; Catalano PM, Thomas AJ, Avallone DA, Amini SB. Anthropometric estimation of neonatal body composition. American journal of obstetrics and gynecology. Cauble JS, Dewi M, Hull HR. Validity of anthropometric equations to estimate infant fat mass at birth and in early infancy. BMC pediatrics. Chambers AJ, Parise E, McCrory JL, Cham R: A comparison of prediction equations for the estimation of body fat percentage in non-obese and obese older Caucasian adults in the United States. J Nutr Health Ageing 18; Dauncey MJ, Gandy G, Gairdner D. Assessment of total body fat in infancy from skinfold thickness measurements. Archives of disease in childhood. Davidson LE, Wang J, Thornton JC, Kaleem Z, Silva-Palacios F, Pierson RN, Heymsfiled SB, Gallagher D: Predicting Fat Percent by Skinfolds in Racial Groups: Durnin and Womersley Revisited. Med Sci Sports Exerc 43; Duren DL, Sherwood RJ, Czerwinski SA, Lee M, Choh AC, Siervogel RM, Chumlea WC: Body Composition Methods: Comparisons and Interpretations J Diab Sci Technol 2; Deierlein AL, Thornton J, Hull H, Paley C, Gallagher D. An anthropometric model to estimate neonatal fat mass using air displacement plethysmography. Durnin JV, Womersley J: Body fat assessed from the total body density and its estimation from skinfold thickness: measurements on men and women aged from 16 to 72 years. British Journal of Nutrition 32; 77 Duren DL, Sherwood RJ, Czerwinski SA, Lee M, Choh AC, Siervogel RM, et al. Although it is often considered one of the most accurate methods of body composition analysis, it is not without limitations. In athletic populations, longitudinal data from repeated measurements of body composition may be affected by muscle glycogen levels, hydration status and changes in muscle metabolites such as creatine 8. This may lead to a misrepresentation of FFM, and these factors should be considered when interpreting the results of DXA estimates of body composition. Skinfold Calipers Skinfold calipers measure a double fold of skin and subcutaneous adipose tissue and apply constant pressure to the site. Skinfold measurements make the assumption that adipose tissue compresses in a predictable manner, that the thickness of the skin is negligible, and the double-layer compression is representative of an uncompressed single layer of adipose tissue. Measurements give results in millimetres, which can be then converted to a body fat percentage, with dozens of equations available for varying populations. A potential limitation of skinfold measurements is that they are dependent on the competency and accuracy of the person taking the measurements i. intra-rater reliability. To minimise the technical error of measurement, measurement sites and techniques have previously been defined 9. Practitioners can become accredited in anthropometric measurement through the International Society for the Advancement of Kinanthropometry ISAK. Skinfold measurements taken just one centimetre away from the defined ISAK sites have previously been shown to produce significant differences in measurement values at each site, indicating how important it is to mark and measure skinfolds correctly for accurate data Therefore, the intra-rater reliability of the test is extremely important. Whole Body Plethysmography BodPod Air-displacement plethysmography ADP can allow for the calculation of body composition through a 2-compartment model, based on assumptions of value constants for FM and FFM densities. Body weight and body volume are determined by this method, with mass divided by volume providing a measure of density. Again, this measurement is a non-invasive and quick method, with the advantage of not requiring exposure to radiation. BodPod has been shown to be a valid measure of group average body composition when compared to DEXA in female collegiate athletes However, research has suggested a difference of 5. BodPod has also shown limited accuracy when attempting to determine changes over time 13 , a primary consideration when choosing an assessment method for athletes. Body density is determined and then used to estimate body fat percentage. Again, this estimate is based on assumptions regarding the density of FFM, which may vary with age, gender, ethnicity and training status, potentially limiting its use in athletic populations Although this method was previously considered the gold standard by the American College of Sports Medicine, it is not without measurement error. The results are highly reliant on subject performance, and as the process itself is uncomfortable, it may take multiple tests to get a valid measurement. For example, measurement error can occur through unsuccessful attempts to blow all of the air out of the lungs, or air bubbles trapped in hair or swimsuits. Bioelectrical Impedance Analysis BIA BIA is based on the concept that electric current flows through the body at different rates depending on its composition It involves running a light electrical current through the body and determining body composition through the resistance of the tissues to the electrical current. The low cost, speed of measurement and lack of need for technical expertise make BIA an attractive option for body composition measurement, particularly in epidemiological research. However, the accuracy of BIA is dependent on several factors, and as a result, it is likely the least valid measure of body composition discussed in this article. BIA relies on empirical equations to estimate total body water, FFM and body cell mass; these equations use gender, age, weight, height and race as variables. Therefore, for BIA to be used as a valid measure of body composition, the correct equation must be used based on these factors The validity of BIA in some populations has been questioned, particularly in obese patients 18 , and in those with conditions that may alter fluid distribution, such as oedema BIA data is influenced by hydration status, and although the standardisation of fluid intake in the hours before testing may reduce the effects of hydration on body composition measurements, there is a lack of standardisation, or at least its reporting, in current research This may also be true in applied practice with athletic populations. Exercise has been shown to lead to vast inaccuracies in body composition analysis using BIA 21 , as has changes in hydration status As a result, BIA may not be suitable for determining body composition changes due to fluctuations in hydration status following training. Body composition measurement in vivo is an estimate. As mentioned previously, the cost and practicality of measuring body composition vary greatly, and often there is a trade-off between the two. Each method has a use in certain settings, and it is the job of the practitioner or user to understand the benefits and drawbacks of each method. A further issue with body composition is often the focus of individuals on their absolute body fat percentage values. Rather than focusing on an absolute body fat number, it may be of more value to standardise measurement and track changes over time. As measures of body composition are developed, more accurate measurements of FM and FFM can be established in various athletic populations. This means that future research should aim to determine:. There are a multitude of body composition assessment tools available to the practitioner, each with varying cost, accessibility and accuracy in each population. It is important to understand the benefits and limitations of each method, and how best to utilise each one in practice. Most assessment tools are useful in various settings, and accuracy can be improved with proper standardisation prior to testing. Learn how to improve your athletes' agility. This free course also includes a practical coaching guide to help you design and deliver your own fun and engaging agility sessions. Charlie has an MSc in Sport and Exercise Nutrition from Loughborough University. He has previously supported athletes in a variety of sports including canoeing, boxing, cricket, rugby league, Olympic weightlifting and strongwoman. Learn from a world-class coach how you can improve your athletes' agility. This course also includes a practical coaching guide to help you to design and deliver your own fun and engaging agility sessions. Our mission is to improve the performance of athletes and teams around the world by simplifying sports science and making it practical. Pricing FAQs Reviews Free trial. Blog Newsletter Community Podcast Tools. About us Contact us Join our team Privacy policy Terms of use Terms and conditions Disclaimer. Body Composition Testing Changes in body composition can be determinants of successful performance, and there are several methods of body composition testing. Contents of Article Summary What does body composition mean? What is body composition testing? How is body composition measured? |
| Measuring skinfolds for fat mass assessment: the ultimate guide | International Journal of Sport Nutrition and Exercise Metabolism , pp. and Chen, K. is followed as strictly as possible see reference 2 for details. Drinkwater EJ, Pyne DB, McKenna MJ. Article Google Scholar Sanfilippo J, Krueger D, Heiderscheit B, Binkley N. |
Monitoring body Vegan-friendly snacks in athletes geams beneficial for many Skinfold measurement for sports teams. Skinfold thickness assessment is one of many methods Soinfold can be used to accomplish this task. How skinfolds assessment works, its popularity among sports professionals, how to pick the right equation to use, and sources of error are reviewed in this article. Grey boxes are summary points. Blue boxes give more detail about key terms or subjects. Skinfold measurement for sports teams -
Even if it is not very accurate it is still possible to use this method to track changes. The other reasons require accurate absolute numbers and therefore the method must be reliable but also accurate.
There a range of techniques that can be used to measure body composition which vary in their accuracy, reliability, cost etc.
Commonly used methods only provide an estimate of body composition because they are based on assumptions regarding the compartments measured. This is because the only truly accurate way to measure body composition is by dissection! Below is a brief overview of the common methods used….
Two low energy x-rays are passed through the body which are absorbed differently by bone and tissues. DXA can measure regional body composition, sub-dividing the body into different components i. arms, legs and trunk , as well as bone density.
DXA relies on certain assumptions, and when these are violated, errors in measurements can occur. is followed as strictly as possible see reference 2 for details. A small alternating electrical current is passed through the body, and the impedance resistance to this is measured.
Muscle tissue contains a high water content which allows the electrical current to pass through quickly, however the electrical current experiences resistance when passing through fat tissue. Single frequency BIA scales are typically used allowing only TBW to be measured, however if multiple frequency scales are used, this can be further differentiated into extracellular water and intracellular water.
ISAK stands for the International Society for the Advancement of Kinanthropometry who train practitioners to perform skinfold measurements in a standardised way. The skinfold technique measures a double fold of skin, which reflects the subcutaneous fat thickness at various sites across the body.
Skinfold thickness is measured in mm, and various population-specific equations have been created to attempt to convert these measures into body fat percentage.
Skinfolds are best used as a monitoring tool over time, with the same person taking the measurements each time. The thickness of a skinfold also depends on hydration status. So although this method is relatively easy there are also quite a few limitations.
Air displacement plethysmography measures body composition through a person sitting within an enclosed chamber i. Bodpod whereby body volume is indirectly measured through measuring the volume of air the body displaces within the chamber.
In other words, the amount of air that you displace when stepping in the chamber is equivalent to your body volume. Volume, in addition to body weight, can then be used to calculate body density, which then allows FM and FFM to be estimated. This technique involves being fully submerged in a tank of water and expelling all air in the lungs whilst underwater weight is measured.
Both bone and muscle have a greater density than water, whereas fat mass has a lower density than water. Therefore, someone with a larger amount of FFM will weigh more in water.
Body density is calculated using underwater weight, body weight outside of the water, density of the water and residual volume of the lungs. The residual volume in the lungs is measured by inhaling helium and measuring the dilution.
Estimations of FM and FFM can then be made. This technique is perhaps the most direct and accurate technique to measure body fat, but there are few places that have this facility and it is not a very practical method.
There are a number of techniques that can be used to measure body composition. The technique we should use depends on the goal of the measurement. For example, if we want to know more about bone density, we should use DXA.
If we need an accurate measure of body fat, we cannot use skinfold measurements and we should use underwater weighing or DXA. On the other hand, if we need a practical way to track changes over time, we should consider skinfolds.
The different techniques vary in their accuracy and their reliability how reproducible the results are if you do several measurements. This will be discussed in the next blog. Wang ZM, Pierson RN Jr, Heymsfield SB.
The five-level model: a new approach to organizing body-composition research. Am J Clin Nutr. Nana A, Slater GJ, Stewart AD, Burke LM. Methodology review: using dual-energy X-ray absorptiometry DXA for the assessment of body composition in athletes and active people.
Int J Sport Nutr Exerc Metab. Are extreme glycogen loading protocols necessary? Does collagen strengthen connective tissue in muscle? Is fructose bad for health? The optimal ratio of carbohydrates.
Does dehydration reduce performance? The mean of two measurements should be taken. If the two measurements differ greatly, a third should then be done, then the median value taken.
the sites: there are many common sites at which the skinfold pinch can be taken. See the descriptions and photographs of each skinfold site. It is best to use the sum of several sites to monitor and compare body fat measures.
In order to satisfy those who want to calculate a percentage body fat measure, there is a sample of equations for calculating this here. Below is a table of general guidelines based on personal experience for using total sum in millimeters of the seven main skinfold sites tricep , bicep , subscap , supraspinale , abdominal , thigh , calf.
There are also examples of some actual athlete results. target population: suitable for all populations, though it is sometimes difficult to get reliable measurements with obese people. validity: using skinfold measurements is not a valid predictor of percent bodyfat, however they can be used as a monitoring device to indicate changes in body composition over time.
It is important to maintain correct calibration of the calipers more about calibrating calipers. reliability: the reliability of skinfold measurements can vary from tester to tester depending on their skill and experience. There are accreditation courses available through ISAK.
advantages: Skinfold measurements are widely utilized to assess body composition. It is a lot simpler than hydrostatic weighing and many of the other body composition techniques. After the original outlay for calipers, the daily tests costs are minimal.
other considerations: some participants may feel uncomfortable stripping down in front of the tester, therefore every effect should be made to make them feel comfortable. For legal reasons, it is wise to have another person present, and to have females testers for female participants.
The right side measurement is standard, though in some situations you may need to test someone on the left side. If so, you must record this and endeavor to always test on the same side for that person.
Reasons for testing on the left side may include injuries, amputation, deformities, or other medical conditions. We have over fitness tests listed, so it's not easy to choose the best one to use. You should consider the validity, reliability, costs and ease of use for each test. Use our testing guide to conducting, recording, and interpreting fitness tests.
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Delve into the science, validity, reliability and practical recommendations Skinfold measurement for sports teams using skinfold calipers measureement measure body fat. By Carla Meaurement Last updated: January 21st, Summer detox diets min read. Measurement of body composition is essential for both health-related measures and performance-enhancing slorts Skinfold measurement for sports teams sport. Although there are numerous Skibfold to measure Skinfold measurement for sports teams composition, the method of skinfold calipers for estimating body composition is often disregarded as a good choice. Many things can affect the accuracy of the measurement of body composition using calipers, including the equipment, the level of expertise of the tester, and which equation is used for prediction, however, skinfold calipers can still offer a relatively accurate and quick, affordable way to measure body composition changes over time. Kinanthropometry is the study of human size, shape, proportion, composition and function. The purpose of kinanthropometry is to understand human growth, performance, and nutritional status, especially concerning sports performance.
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