Reliability of skinfold measurements and body fat prediction depends on the rater's experience: a cross-sectional analysis comparing expert and novice anthropometrists

Reliability of skinfold measurements and body fat prediction depends on the rater's experience: a cross-sectional analysis comparing expert and novice anthropometrists | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Reliability of skinfold measurements and body fat prediction depends on the rater's experience: a cross-sectional analysis comparing expert and novice anthropometrists Dalmo Roberto Lopes Machado, Leonardo Santos Lopes da Silva, Raquel Vaquero-Cristóbal, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4540605/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In this study, we aimed to identify the variability among anthropometrists with varying levels of experience and its effects on the final interpretations of body composition estimates. Were implied 25 male university students, aged between 18 and 30 years. Skinfold measurements of eight body regions were obtained by two anthropometrists: an expert (more than 20 years of experience) and a novice (initial basic training). The same calibrated adipometer was used to verify the %fat. The results showed that the expert technical error of measurements (TEM) was below the tolerated limits ( 7.5%) for the iliac crest and abdominal skinfolds. The inter-evaluator reliabilities were good for triceps, subscapular, and calf skinfolds; moderate for iliac crest, abdominal, and thigh skinfolds; but poor for biceps skinfolds. Some TEM novice measurements were 2 to 4 times higher than expert. The Bland & Altman analysis showed that inter-evaluator reliabilities were good for triceps, subscapular, and calf (p < 0.001). However, the inter-evaluator reliabilities were moderate for iliac crest, abdominal, and thigh (p < 0.001), and poor for biceps (p = 0.07). There was a significant impact on the predicted %fat, with estimates up to 55.12% higher by the novice compared to the expert. Conclusively, low reliability in estimating body fat emphasizes the importance of measurement training. Measurements by anthropometrists with low expertise levels are unreliable even with standardized protocols and equally calibrated instruments. Health sciences/Health care/Nutrition Health sciences/Health care/Weight management body composition anthropometry nutrition assessment caliper accuracy Figures Figure 1 Figure 2 Figure 3 1 Introduction Anthropometry is a widely used tool for assessing body composition components quickly, practically, and cost-effectively 1 , 2 . Among the most used anthropometric instruments is the skinfold caliper, which provides good accuracy and reliability 3 , 4 . Body composition is measured through skinfold thickness and is usually segmented into a two-compartment model (fat mass and fat-free mass) at the whole-body level (head, trunk, and limbs) 5 . Although multicompartmental models have been proposed for populations ranging from children and adolescents 6 , 7 to older adults 8 and special populations 9 – 11 . Although anthropometry is proposed as a more economically viable alternative. Although anthropometric features are still measured in only two compartments, the estimate of body fat percentage, for example, shows good agreement compared to more sophisticated methods such as dual-energy X-ray absorptiometry (r 2 = 0.76–0.82) 12 . Anthropometry is essential in diagnosing overweight and obesity because of its simple application, low operational cost, and non-invasive nature 13 , 14 . One of the limitations of using skinfold calipers for assessing body composition is the potential for evaluator technical error. In fact, among the methods used for estimating body composition, the highest incidence of technical error of measurement (TEM) can be found in the measurements obtained through this tool 15 . To address this issue, it is essential to carefully consider the accuracy and value of different models of skinfold calipers available on the market, considering specific target populations and evaluation purposes 13 , 16 . This highlights the importance of using standardized protocols and equally calibrated instruments to minimize the occurrence of TEM and ensure reliable measurements. Additionally, ongoing training and regular quality control procedures can help reduce the impact of evaluator technical error and improve the overall accuracy and precision of skinfold measurements. In addition to the technical error of the evaluator, there are also potential errors associated with the equations used to estimate body composition from skinfold measurements. While the 2-C model used in skinfold measurements has been shown to have good agreement with more sophisticated methods such as dual-energy x-ray absorptiometry (DXA) 13 , 17 , there are still limitations to its accuracy, notably the low qualification of the anthropometrists, when they do not have an accurate measurement technique 13 , particularly when assessing regional differences in body fat distribution 18 . Furthermore, there is a multitude of different equations available for estimating body composition from skinfold measurements, and these equations may not be appropriate for all populations 6 , 7 , 9 , 19 . This means that the accuracy of the estimated body composition may be compromised in certain individuals or groups 19 . Also is important to carefully select the appropriate equation based on the specific population being evaluated to ensure the most accurate results possible 20 . Overall, while skinfold measurements are a useful and cost-effective tool for estimating body composition, it is important to acknowledge and address the potential sources of error associated with their use. By doing so, we can improve the accuracy and reliability of these measurements and better support their use in clinical, research, and athletic settings 21 . Additionally, there is the potential for error associated with the skinfold caliper instrument itself. While modern skinfold calipers are generally of high quality and are frequently calibrated, there is still the potential for measurement error due to differences in the pressure applied by the evaluator or variations in the thickness of the skinfold being measured 22 . As such, it is important for evaluators to be well-trained and experienced in the use of skinfold calipers and to follow standardized protocols 13 to minimize the potential for error. Despite standardized measurements using skinfold calipers, different methods and applications are used in professional practice 13 . During measurements, variability in results can occur due to the biological diversity of everyone (which cannot be avoided) and technical errors made by evaluators (which can be reduced through training, protocol standardization, and repeated measurements) 23 , which is where the highest incidence of TEM can be found 15 . In this sense, the evaluator's experience may be a determining factor in the reliability of an appropriate diagnosis of body compartments, whether for planning interventions for health or sports performance. The athletes’ measurements require even greater precision, as they are close to their biological limit and have less tolerance for diagnostic errors. Thus, a professional is expected to competently analyze and interpret the evaluation results 3 . Technical errors are found in both intra- and inter-evaluator measurements and may be influenced by the equations used and the instrument's accuracy. In this sense, the evaluator's experience may be a determinant factor in minimizing these errors and ensuring a reliable diagnosis of body compartments, especially in populations such as athletes, older adults, and very young subjects 21 . Therefore, one of the most important factors that can influence the reliability of anthropometric measurements is the experience level of the rather. Novice anthropometrists with low expertise levels may have difficulty obtaining accurate measurements, even when using standardized protocols and equally calibrated instruments 15 . In contrast, it was expected that experienced anthropometrists with training and a track record of success are more likely to provide reliable and consistent results. However, there is a lack of comparative studies investigating the results of body composition estimation predicted by anthropometrists at different levels of expertise. Therefore, it is not yet completely understood how the experience of anthropometrists affects the reliability and accuracy of skinfold measurements for the estimation of body composition. The absence of comparative studies on this topic underscores the need and the potential to influence not only the accuracy of individual assessments but also the broader validity of research findings and the development of standardized protocols. Thus, the present study aimed to identify the variability among anthropometrists with varying levels of experience and its effects on the final interpretations of body composition estimates. 2 Methods Type of Study The present research followed a descriptive, cross-sectional design. The sample recruitment was non-probabilistic by convenience. The calculation to establish the sample size was performed with Rstudio 3.15.0 software (Rstudio Inc., Boston, MA, USA), using the ‘pwr’ package 24 . The significance level was set at α = 0.05. The standard deviation (SD) for total sample was set based on previous studies on the variable’s fat percentage for men (SD = 2.17) 20 . With an estimated error of (d) 0,85% for fat percentage, a sample of 25 subjects was required. Participants A sample of 25 healthy young male university students participated in the study. The participants, residents of Ribeirao Preto - SP, signed the Informed Consent Form (ICF) and declaration of Helsinki. All stages of the study were conducted at the Laboratory of Kinanthropometry and Human Performance (LACIDH) of the School of Physical Education and Sport of Ribeirao Preto - USP. Eligibility criteria and ethical aspects The study included participants who met the following criteria: a) male sex; b) aged between 18 and 25 years; c) self-reported as healthy; d) without amputated body parts, and e) not using medication or substances that could affect body composition. Exclusion criteria were applied to remove participants with incomplete data from the analysis or who decided to withdraw their participation in the study. The guidelines and ethical aspects of research with human beings were followed according to the Declaration of Helsinki, and the Free and Informed Consent Term signed by each participant was also obtained, being approved by the respective Ethics and Research Committees (CAAE: 49292915.7.0000.5659). Measurements The eight skinfold sites (triceps, biceps, subscapular, iliac crest, abdominal, thigh, and calf) according to the standardized reference 18 , were measured by two assessors: an expert 1 (with more than 20 years of professional experience in anthropometry) and a novice 2 (with basic initial training but without practice time). The assessors used the same instrument, a calibrated Harpenden® caliper. A triple measurement system was adopted, with the median recorded. The assessors performed the skinfold measurements in different environments, to avoid interference between the results. Estimation of body fat To obtain the body fat percentage of everyone, the formula proposed by Peterson et al. (2003) 19 for men aged between 18 and 56 years was used: % body fat = 20.94878 + (age * 0.1166) - (stature [cm] * 0.11666) + ([Triceps + Thigh + Iliac crest + Subscapular] * 0.42696) - ([Triceps + Thigh + Iliac crest + Subscapular2] * 0.00159). Analysis of technical error in measurement The objective of determining the absolute TEM of skinfolds between evaluators with different levels of experience was calculated using the formula: TEM = √[(∑Diff2)/2n]. Subsequently, the determination of the relative TEM percentage was calculated using the formula: %TEM = (TEM / mean) * 100. The classification of intra-rater TEM was carried out according to the criteria established by Norton & Olds et al. (2000) 25 , which considers acceptable values of < 5% for expert anthropometrists and < 7.5% for novice anthropometrists. The inter-evaluator technical measurements error Additionally, was to assess the agreement of measurements between the anthropometrists and determine their variability. To calculate the inter-evaluator TEM, the same steps described earlier for calculating the intra-rater TEM should be followed. The procedures are the same, but the skinfold measurements to be considered in the calculations should be performed by the two anthropometrists who should be evaluated, using the same group of volunteers 15 . Finally, was analyzed the predictive agreement of body fat between the anthropometrists. Predictive validity refers to the "validity based on the correlation between the assessment results R-N and a predicted future behavior" 26 . Statistical analysis Descriptive measures (mean, standard deviation, and 95% confidence interval [CI]) were used to characterize the sample. To verify inter-evaluator agreement for skinfolds and body %fat, the intraclass correlation coefficient (ICC) and Bland & Altman 27 . plots were used. The ICC classification consists of values less than 0.5 are indicative of poor reliability, values between 0.5 and 0.75 indicate moderate reliability, values between 0.75 and 0.9 indicate good reliability, and values greater than 0.90 indicate excellent reliability 28 . All analyses were performed using SPSS 20.0 software. Bland & Altman plots were performed using GraphPad Prism 9.3 software. The significance level was set at 5%. [1] between 900 and 3200 measurements per year were performed. [2] academic-university literacy in anthropometry, close to 100 measurements. 3 Results Table 1 reports the descriptive characteristics of the sample. The young adults (22 years old) showed low variability among themselves for body mass (95% CI: 74.3 to 82.9) and stature (95% CI: 174.0 to 180.0), revealing homogeneity of the sample in our study. Table 1 Descriptive characteristics of the sample (young men; n = 25), according to the measurement of each rater. Variables Expert rater Novice rater Mean SD CI (95%) Mean SD CI (95%) Stature (cm) 177.0 7.2 174.0 to 180.0 177.0 7.2 174.0 to 180.0 Body mass (kg) 78.6 10.4 74.3 to 82.9 78.6 10.4 74.3 to 82.9 Age (years) 22.0 2.7 20.8 to 23.1 22.0 2.7 20.8 to 23.1 Skinfold thickness Triceps (mm) 10.4 4.2 8.7 to 12.2 11.7 5.0 9.7 to 13.8 Biceps (mm) 5.4 2.0 4.6 to 6.3 16.5 7.4 13.4 to 19.5 Subscapular (mm) 17.7 9.5 13.8 to 21.6 16.3 6.6 13.6 to 19.0 Iliac crest (mm) 22.0 12.0 17.0 to 27.0 18.3 7.7 15.1 to 21.5 Abdominal (mm) 23.4 12.2 18.3 to 28.4 19.0 8.5 15.5 to 22.5 Thigh (mm) 16.6 7.6 13.4 to 19.7 15.8 6.3 13.2 to 18.3 Calf (mm) 10.7 4.4 8.9 to 12.5 10.8 3.6 9.3 to 12.2 Body Fat (%) 22.6 5.6 20.3 to 24.9 41.0 5.4 38.8 to 43.2 Caption: SD = standard deviation; CI = confidence interval. To address our first objective, Fig. 1 presents the intra-rater and inter-evaluator relative TEM (%TEM) for all skinfolds. The expert rater remained below the tolerated limits ( 7.5%). To address our second objective, Fig. 2 presents the inter-evaluator ICC and Bland & Altman plot for skinfold values. The inter-evaluator reliabilities were good for triceps (ICC: 0.84 [95% CI: 0.60 to 0.93]), subscapular (ICC: 0.82 [95% CI: 0.63 to 0.91]), and calf (ICC: 0.89 [95% CI: 0.76 to 0.95]) (p < 0.001). However, the inter-evaluator reliabilities were moderate for iliac crest (ICC: 0.65 [95% CI: 0.34 to 0.83]), abdominal (ICC: 0.68 [95% CI: 0.34 to 0.85]), and thigh (ICC: 0.69 [95% CI: 0.41 to 0.85]) (p < 0.001). Notably, the inter-evaluator reliability for biceps skinfold was poor (ICC: 0.096 [95% CI: -0.077 to 0.348; p = 0.07]). In accordance with our third objective, Fig. 3 presents the inter-evaluator ICC and Bland & Altman plot for the body %fat value. It was observed that there was poor reliability between the anthropometrists (ICC: 0.13 [95% CI: -0.01–0.46; p = 0.07]). 4 Discussion Our study made significant contributions by determining the intra-evaluator TEM and assessing the reliability of skinfold and body %fat measurements using the ICC and Bland & Altman plots. Our findings revealed that the expert evaluator had acceptable TEM values for all skinfold measurements, while the novice evaluator exceeded the tolerable limits for iliac crest and abdominal skinfolds. The ICC and Bland & Altman plots demonstrated good reliability for triceps, subscapular and calf measurements, moderate reliability for iliac crest and abdominal measurements, and poor reliability for biceps measurements. Additionally, our results indicated a poor inter-evaluator reliability for body %fat, suggesting that the differences between anthropometrists significantly affected the calculated percentage of body fat. These findings highlight the importance of considering the expertise and experience of anthropometrists to obtain reliable and accurate estimations of body composition. It is noteworthy that both experienced and novice anthropometrists followed the same procedures for taking skinfold measurements. In a study by Oliveira et al. (2020) 29 , comparisons were made between anthropometrists with and without adherence to the method and certification from the International Society for the Advancement of Kinanthropometry (ISAK). In contrast to our findings, the study observed that an evaluator with a more refined technique did not achieve an acceptable classification for intra-evaluator error in one of the four anthropometric measurements conducted. In this regard, it is essential to ensure precision during anthropometric measurement by: a) the evaluator has precision in repeating their measurements; b) they consistently adopt the same technique; and c) when inter-evaluator error is unknown, the same evaluator should always perform the measurement on the individual. The need for TEM for all anthropometric measurements, including the variation in agreement of skinfold measurements (good, moderate, and poor) between anthropometrists, is highlighted. It is important to emphasize that anthropometric measurements with higher TEM values require the evaluator, whether experienced or novice, to practice the measurement numerous times to reduce error and increase agreement between anthropometrists within the same work setting 30 . On the other hand, the absolute measurement (expressed in millimeters) should be also considered. The absolute values provide information concerning local fat distribution in the body, and provides an index to determine adiposity, since subcutaneous fat reflects the amount of fat present in the adipose tissue 31 . Therefore, a potential difference between expert and novice anthropometrists may be evident by looking at absolute values. In the present study, it was found that the novice evaluator exceeded the tolerable limit of TEM for the iliac crest and abdominal skinfolds, while this did not happen in any of the cases in the expert anthropometrist. This in turn affected the inter-evaluator reliability for these skinfolds. Previous studies have shown that it is the higher skinfolds, such as these two trunk skinfolds, have a higher variability in compressibility when the caliper is applied 32 . Therefore, it is these types of skinfolds where variations in anthropometric technique can introduce a greater margin of error in measurement, especially affecting anthropometrists with limited experience. This is especially important when you consider that trunk skinfolds such as the iliac crest and abdominal skinfolds are variables used in most anthropometric fat mass estimation formulas 20 . Based on the results of the present investigation, it would be necessary to emphasize in anthropometry training, especially in the measurement of higher skinfolds and trunk skinfolds, to avoid inadequate assessment of skinfolds by novice anthropometrists. Regarding the poor inter-evaluator agreement observed in our study regarding the prediction of body %fat, it highlights the importance of evaluator experience in reducing the chances of making inaccurate diagnoses 33 . A study evaluated the performance of three anthropometrists with different levels of knowledge and practical experience in measurement techniques, as well as the impact on nutritional diagnosis 34 . It was observed that less practice and previous training resulted in more errors during measurements, leading to low precision and accuracy, especially for body circumferences and skinfolds. Inadequate collection of skinfold measurements by less trained anthropometrists resulted in errors in the classification of nutritional diagnosis regarding body %fat. Therefore, periodic training in anthropometry is recommended to ensure reliable results, both at the individual and collective level 35 . Several strengths of our study should be considered. The use of TEM allows for the assessment of the precision and accuracy of anthropometric measurements, as well as the identification of systematic and random errors during the measurement process. Thus, it is an important tool for standardizing measurement protocols and training anthropometrists, which can increase the quality and reliability of anthropometric measurements. Additionally, TEM can assist in monitoring the quality of measurements over time, enabling the identification of potential issues, and adjusting improve the precision and accuracy of measurements. Therefore, the use of TEM can contribute to the comparison of results across different studies and/or anthropometrists, which is crucial for advancing knowledge in the field of anthropometry. Although our results are promising, some limitations should be considered. The small sample size may be a limiting factor for understanding TEM on a larger scale, although our study sample is homogeneous (see Table 1 ). Another limitation is the presence of only one anthropometrists in each category. This may not reflect the variability found in a larger sample of anthropometrists, and it does not allow for a more precise comparison of performance between the groups. Therefore, it is important to have a significant number of anthropometrists in each group to increase the reliability of the results and determine whether experience and prior training are determining factors in reducing TEM. Through this investigation, we hope to provide valuable insights into the importance of anthropometrists’ experience in obtaining reliable measurements of body composition, and ultimately, to inform best practices for accurate body composition assessment in clinical and research settings. TEM should be regularly monitored to prevent estimation errors. Even in contexts where estimates are not derived (e.g., sum of skinfold thicknesses), calculating and reporting TEM is necessary. Studies that present measurements made by anthropometrists with high TEM or fail to report TEM values of their anthropometrists should be interpreted with caution. Anthropometrists with high TEM should undergo training until TEM becomes acceptable. For future studies, we suggest investigating the relationship between evaluator experience and the precision of anthropometric measurements to identify the minimum levels of experience required to obtain accurate and reliable measurements. Comparing different equipment and techniques for anthropometric measurement would also be valuable in identifying the most precise and reliable methods for different populations and study objectives. Lastly, exploring the relationship between TEM and the accuracy of body composition assessment methods such as bioelectrical impedance analysis and dual-energy X-ray absorptiometry would provide further insights into the field. Continued research in these areas will contribute to enhancing the accuracy and reliability of anthropometric measurements, thereby improving our understanding of how rater experience impacts measurement outcomes. To achieve this, providing standardized training and ongoing education to anthropometrists is essential, ensuring their competence in performing accurate measurements. Experienced anthropometrists can improve the reliability of measurements and minimize the risk of overestimating or underestimating body composition in different populations, including athletes, older adults, and young subjects. This previous experience can ensure the reliability of an appropriate diagnosis of body compartments, minimizing the chances of under/overestimation in different populations (i.e., athletes, older adults, and young subjects) 13 . However, we still do not know how much of this experience is decisive in skinfold measurements, especially when comparing expert and novice anthropometrists. In this study, we determined the intra-rater technical error of skinfold measurements for both expert and novice anthropometrists, as well as the agreement of skinfold and %bodyfat measurements between anthropometrists. The inter-rater measurements of skinfolds with varying levels of expertise were not always statistically significant, despite standardization of the measurement protocol and the use of equally calibrated skinfold calipers. However, differences observed in the TEM suggest that the precision in assessing body composition does not solely depend on potential measurement variation, but rather on the stability achieved through experience. The experience of the anthropometrists also directly influences the accuracy of %bodyfat prediction. Therefore, less experienced anthropometrists can benefit from theoretical and practical training to enhance the objectivity and reliability of their assessments. Declarations Ethics approval and consent to participate The guidelines and ethical aspects of research with human beings were followed according to the Declaration of Helsinki, the Free and Informed Consent Term signed by each participant was also obtained. This study was approved by Ethics and Research Committees (CAAE: 49292915.7.0000.5659). Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This research received no external funding. Author Contribution DRLM, VCR performed conduction of experiments, wrote introduction, methods, results, and discussion sections. LSLS, MFTJ, APS, PPA, LFM, ASO and, RVC improved interpretation analysis and reviewed the manuscript. JM draft the manuscript and improved interpretation analysis and reviewed English Grammar and Spelling. DRLM, PJMP supervised the study, draft the manuscript, and gave final approval for the version submitted for publication. All authors contributed to the article and approved the submitted version. Acknowledgments We thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Data Availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Utkualp, N. & Ercan, I. Anthropometric Measurements Usage in Medical Sciences. BioMed Research International 2015, e404261 (2015). Abdalla, P. P. et al. Anthropometric equations to estimate appendicular muscle mass from dual-energy X-ray absorptiometry (DXA): A scoping review. Archives of Gerontology and Geriatrics 110, 104972 (2023). Machado, D. R. L. & Silva, L. S. L. da. 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RBNE - Revista Brasileira de Nutrição Esportiva 13, 657–665 (2019). Garrido-Chamorro, R., Sirvent-Belando, J. E., González-Lorenzo, M., Blasco-Lafarga, C. & Roche, E. Skinfold Sum: Reference Values for Top Athletes. International Journal of Morphology 30, 803–809 (2012). Bini, A., Amaral, T. F., Oliveira, B. M. P. M., Carvalho, P. R. & Teixeira, V. H. Skinfolds compressibility and calliper’s time response in male athletes. Progr Nutr 20, 273–278 (2018). Heymsfield, S. B. et al. Digital anthropometry: a critical review. Eur J Clin Nutr 72, 680–687 (2018). Bagni, U. V., Fialho Junior, C. do C. & Barros, D. C. de. Influência do erro técnico de medição em antropometria sobre o diagnóstico nutricional. Nutrire Rev. Soc. Bras. Aliment. Nutr (2009). Geeta, A. et al. Reliability, technical error of measurements and validity of instruments for nutritional status assessment of adults in Malaysia. Singapore Med J 50, 1013–1018 (2009). Additional Declarations No competing interests reported. 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Machado","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYDCCA0DM2ABE7A0MDA9I08IDZCUAOTzEa5FIIFIL3+3TiR9+7rCT7Zd8Y/gh4RdDnj0hLZLncjdL9p5JNp45O8dYIrGPoZigLQZneDdIM7YxJ264nWMgkdjDAESEtWz+zdhWn7jh5hnjH8Rq2Qa05XDihhs8ZhIJP4jQIgnUYtnbdtx4Zk9amUVig0QxKLDxAj6gw278bKuW7Wc/vPnGhz82eaAoJQEwtoFihzTwh4FkLaNgFIyCUTD8AQDGDEc/nPSCRQAAAABJRU5ErkJggg==","orcid":"","institution":"Universidade do Algarve","correspondingAuthor":true,"prefix":"","firstName":"Dalmo","middleName":"Roberto Lopes","lastName":"Machado","suffix":""},{"id":319526782,"identity":"7500fc49-d2e6-4ee7-a5bf-ee8ad57834b7","order_by":1,"name":"Leonardo Santos Lopes da Silva","email":"","orcid":"","institution":"University of Sao Paulo","correspondingAuthor":false,"prefix":"","firstName":"Leonardo","middleName":"Santos Lopes da","lastName":"Silva","suffix":""},{"id":319526783,"identity":"8ade71b8-d623-4577-821b-b5f1d0ba8af9","order_by":2,"name":"Raquel Vaquero-Cristóbal","email":"","orcid":"","institution":"Universidad Católica de Murcia","correspondingAuthor":false,"prefix":"","firstName":"Raquel","middleName":"","lastName":"Vaquero-Cristóbal","suffix":""},{"id":319526784,"identity":"06a1d72a-d8f5-4bfc-ae5d-2bb6c5aa1b21","order_by":3,"name":"Victor Carvalheiro Rosa","email":"","orcid":"","institution":"University of Sao Paulo","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"Carvalheiro","lastName":"Rosa","suffix":""},{"id":319526785,"identity":"2645d4e9-22d7-4193-9a4c-dcf8574da395","order_by":4,"name":"Marcio Fernando Tasinafo Júnior","email":"","orcid":"","institution":"University of Sao Paulo","correspondingAuthor":false,"prefix":"","firstName":"Marcio","middleName":"Fernando Tasinafo","lastName":"Júnior","suffix":""},{"id":319526786,"identity":"77478976-90fb-4c74-80a7-2fea16596be2","order_by":5,"name":"André Pereira dos Santos","email":"","orcid":"","institution":"University of Sao Paulo","correspondingAuthor":false,"prefix":"","firstName":"André","middleName":"Pereira dos","lastName":"Santos","suffix":""},{"id":319526787,"identity":"0b180885-74a2-4572-80bf-9d9997a39b6f","order_by":6,"name":"Pedro Pugliesi Abdalla","email":"","orcid":"","institution":"University of Sao Paulo","correspondingAuthor":false,"prefix":"","firstName":"Pedro","middleName":"Pugliesi","lastName":"Abdalla","suffix":""},{"id":319526788,"identity":"3ca4913b-6c98-49bd-bb6c-065c4139ed33","order_by":7,"name":"Lisa Fernanda Mazzonetto","email":"","orcid":"","institution":"University of Sao Paulo","correspondingAuthor":false,"prefix":"","firstName":"Lisa","middleName":"Fernanda","lastName":"Mazzonetto","suffix":""},{"id":319526789,"identity":"f63943a5-3030-4cba-9b0a-d099bb874805","order_by":8,"name":"Alcivandro Sousa Oliveira","email":"","orcid":"","institution":"University of Sao Paulo","correspondingAuthor":false,"prefix":"","firstName":"Alcivandro","middleName":"Sousa","lastName":"Oliveira","suffix":""},{"id":319526790,"identity":"8760cd9b-e8a5-4ad0-88f3-7b49cfe6437a","order_by":9,"name":"Jorge Mota","email":"","orcid":"","institution":"University of Porto","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Mota","suffix":""},{"id":319526791,"identity":"319da9f3-b400-4aa9-906a-ec1cb0e96a35","order_by":10,"name":"Pablo Jorge Marcos-Pardo","email":"","orcid":"","institution":"University of Almería","correspondingAuthor":false,"prefix":"","firstName":"Pablo","middleName":"Jorge","lastName":"Marcos-Pardo","suffix":""}],"badges":[],"createdAt":"2024-06-06 13:14:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4540605/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4540605/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59182587,"identity":"0bfd3fb5-7639-4d6d-bd82-7a494dc0c7bc","added_by":"auto","created_at":"2024-06-27 11:00:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":76606,"visible":true,"origin":"","legend":"\u003cp\u003eTechnical error of measurement (TEM) of skinfold thickness analyzed in this study, from expert (black diamond) and novice (white diamond) anthropometrists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003eThe acceptable TEM for expert anthropometrists is \u0026lt;5%, while for novice anthropometrists is \u0026lt;7.5%.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4540605/v1/eb19694e8455f7537fd79f17.png"},{"id":59182586,"identity":"2b2326e2-027e-4310-a34d-56b2fe168080","added_by":"auto","created_at":"2024-06-27 11:00:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":78645,"visible":true,"origin":"","legend":"\u003cp\u003eThe Bland–Altman plot (inter-evaluator reliability) and intraclass correlation coefficient (ICC) of skinfolds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e(a) triceps; (b) biceps; (c) subscapular; (d) iliac crest; (e) abdominal; (f) thigh; (g) calf.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4540605/v1/2303ab8a8e14b3e800644578.png"},{"id":59182580,"identity":"02392216-0047-4324-9c9b-7f4e2a99b56a","added_by":"auto","created_at":"2024-06-27 11:00:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":185196,"visible":true,"origin":"","legend":"\u003cp\u003eThe Bland–Altman plot (inter-evaluator reliability), intraclass correlation coefficient (ICC) of body %fat, and statistical significance.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4540605/v1/c427a985d8a90a1f7f6ef35b.png"},{"id":71611789,"identity":"af5ab9af-2549-4f5c-bb02-ece50ebf8843","added_by":"auto","created_at":"2024-12-17 06:54:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":803695,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4540605/v1/ed2eec24-b744-41d1-a9ab-fd86cb086454.pdf"},{"id":59182585,"identity":"861d0bcd-37cb-4d76-a592-2662b9a801f3","added_by":"auto","created_at":"2024-06-27 11:00:46","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":91614,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEchecklistcrosssectional.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4540605/v1/88076323d53a24bc439deca2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Reliability of skinfold measurements and body fat prediction depends on the rater's experience: a cross-sectional analysis comparing expert and novice anthropometrists","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eAnthropometry is a widely used tool for assessing body composition components quickly, practically, and cost-effectively\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Among the most used anthropometric instruments is the skinfold caliper, which provides good accuracy and reliability\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Body composition is measured through skinfold thickness and is usually segmented into a two-compartment model (fat mass and fat-free mass) at the whole-body level (head, trunk, and limbs)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Although multicompartmental models have been proposed for populations ranging from children and adolescents\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e to older adults\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and special populations\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Although anthropometry is proposed as a more economically viable alternative. Although anthropometric features are still measured in only two compartments, the estimate of body fat percentage, for example, shows good agreement compared to more sophisticated methods such as dual-energy X-ray absorptiometry (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.76\u0026ndash;0.82)\u003csup\u003e12\u003c/sup\u003e. Anthropometry is essential in diagnosing overweight and obesity because of its simple application, low operational cost, and non-invasive nature\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOne of the limitations of using skinfold calipers for assessing body composition is the potential for evaluator technical error. In fact, among the methods used for estimating body composition, the highest incidence of technical error of measurement (TEM) can be found in the measurements obtained through this tool\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. To address this issue, it is essential to carefully consider the accuracy and value of different models of skinfold calipers available on the market, considering specific target populations and evaluation purposes\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. This highlights the importance of using standardized protocols and equally calibrated instruments to minimize the occurrence of TEM and ensure reliable measurements. Additionally, ongoing training and regular quality control procedures can help reduce the impact of evaluator technical error and improve the overall accuracy and precision of skinfold measurements.\u003c/p\u003e \u003cp\u003eIn addition to the technical error of the evaluator, there are also potential errors associated with the equations used to estimate body composition from skinfold measurements. While the 2-C model used in skinfold measurements has been shown to have good agreement with more sophisticated methods such as dual-energy x-ray absorptiometry (DXA)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, there are still limitations to its accuracy, notably the low qualification of the anthropometrists, when they do not have an accurate measurement technique\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, particularly when assessing regional differences in body fat distribution\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Furthermore, there is a multitude of different equations available for estimating body composition from skinfold measurements, and these equations may not be appropriate for all populations\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. This means that the accuracy of the estimated body composition may be compromised in certain individuals or groups\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Also is important to carefully select the appropriate equation based on the specific population being evaluated to ensure the most accurate results possible\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Overall, while skinfold measurements are a useful and cost-effective tool for estimating body composition, it is important to acknowledge and address the potential sources of error associated with their use. By doing so, we can improve the accuracy and reliability of these measurements and better support their use in clinical, research, and athletic settings\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAdditionally, there is the potential for error associated with the skinfold caliper instrument itself. While modern skinfold calipers are generally of high quality and are frequently calibrated, there is still the potential for measurement error due to differences in the pressure applied by the evaluator or variations in the thickness of the skinfold being measured\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. As such, it is important for evaluators to be well-trained and experienced in the use of skinfold calipers and to follow standardized protocols\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e to minimize the potential for error. Despite standardized measurements using skinfold calipers, different methods and applications are used in professional practice\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. During measurements, variability in results can occur due to the biological diversity of everyone (which cannot be avoided) and technical errors made by evaluators (which can be reduced through training, protocol standardization, and repeated measurements)\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, which is where the highest incidence of TEM can be found\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In this sense, the evaluator's experience may be a determining factor in the reliability of an appropriate diagnosis of body compartments, whether for planning interventions for health or sports performance. The athletes\u0026rsquo; measurements require even greater precision, as they are close to their biological limit and have less tolerance for diagnostic errors. Thus, a professional is expected to competently analyze and interpret the evaluation results\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Technical errors are found in both intra- and inter-evaluator measurements and may be influenced by the equations used and the instrument's accuracy. In this sense, the evaluator's experience may be a determinant factor in minimizing these errors and ensuring a reliable diagnosis of body compartments, especially in populations such as athletes, older adults, and very young subjects\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, one of the most important factors that can influence the reliability of anthropometric measurements is the experience level of the rather. Novice anthropometrists with low expertise levels may have difficulty obtaining accurate measurements, even when using standardized protocols and equally calibrated instruments\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In contrast, it was expected that experienced anthropometrists with training and a track record of success are more likely to provide reliable and consistent results. However, there is a lack of comparative studies investigating the results of body composition estimation predicted by anthropometrists at different levels of expertise. Therefore, it is not yet completely understood how the experience of anthropometrists affects the reliability and accuracy of skinfold measurements for the estimation of body composition. The absence of comparative studies on this topic underscores the need and the potential to influence not only the accuracy of individual assessments but also the broader validity of research findings and the development of standardized protocols. Thus, the present study aimed to identify the variability among anthropometrists with varying levels of experience and its effects on the final interpretations of body composition estimates.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cp\u003eType of Study\u003c/p\u003e \u003cp\u003eThe present research followed a descriptive, cross-sectional design. The sample recruitment was non-probabilistic by convenience. The calculation to establish the sample size was performed with Rstudio 3.15.0 software (Rstudio Inc., Boston, MA, USA), using the \u0026lsquo;pwr\u0026rsquo; package\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The significance level was set at α\u0026thinsp;=\u0026thinsp;0.05. The standard deviation (SD) for total sample was set based on previous studies on the variable\u0026rsquo;s fat percentage for men (SD\u0026thinsp;=\u0026thinsp;2.17)\u003csup\u003e20\u003c/sup\u003e. With an estimated error of (d) 0,85% for fat percentage, a sample of 25 subjects was required.\u003c/p\u003e \u003cp\u003eParticipants\u003c/p\u003e \u003cp\u003eA sample of 25 healthy young male university students participated in the study. The participants, residents of Ribeirao Preto - SP, signed the Informed Consent Form (ICF) and declaration of Helsinki. All stages of the study were conducted at the Laboratory of Kinanthropometry and Human Performance (LACIDH) of the School of Physical Education and Sport of Ribeirao Preto - USP.\u003c/p\u003e \u003cp\u003eEligibility criteria and ethical aspects\u003c/p\u003e \u003cp\u003eThe study included participants who met the following criteria: a) male sex; b) aged between 18 and 25 years; c) self-reported as healthy; d) without amputated body parts, and e) not using medication or substances that could affect body composition. Exclusion criteria were applied to remove participants with incomplete data from the analysis or who decided to withdraw their participation in the study.\u003c/p\u003e \u003cp\u003e The guidelines and ethical aspects of research with human beings were followed according to the Declaration of Helsinki, and the Free and Informed Consent Term signed by each participant was also obtained, being approved by the respective Ethics and Research Committees (CAAE: 49292915.7.0000.5659).\u003c/p\u003e \u003cp\u003eMeasurements\u003c/p\u003e \u003cp\u003eThe eight skinfold sites (triceps, biceps, subscapular, iliac crest, abdominal, thigh, and calf) according to the standardized reference\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, were measured by two assessors: an expert\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e1\u003c/a\u003e (with more than 20 years of professional experience in anthropometry) and a novice\u003ca class=\"FNLink\" href=\"#Fn2\" id=\"#FNLinkFn2\"\u003e2\u003c/a\u003e (with basic initial training but without practice time).\u003c/p\u003e \u003cp\u003eThe assessors used the same instrument, a calibrated Harpenden\u0026reg; caliper. A triple measurement system was adopted, with the median recorded. The assessors performed the skinfold measurements in different environments, to avoid interference between the results.\u003c/p\u003e \u003cp\u003eEstimation of body fat\u003c/p\u003e \u003cp\u003eTo obtain the body fat percentage of everyone, the formula proposed by Peterson et al. (2003)\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e for men aged between 18 and 56 years was used: % body fat\u0026thinsp;=\u0026thinsp;20.94878 + (age * 0.1166) - (stature [cm] * 0.11666) + ([Triceps\u0026thinsp;+\u0026thinsp;Thigh\u0026thinsp;+\u0026thinsp;Iliac crest\u0026thinsp;+\u0026thinsp;Subscapular] * 0.42696) - ([Triceps\u0026thinsp;+\u0026thinsp;Thigh\u0026thinsp;+\u0026thinsp;Iliac crest\u0026thinsp;+\u0026thinsp;Subscapular2] * 0.00159).\u003c/p\u003e \u003cp\u003eAnalysis of technical error in measurement\u003c/p\u003e \u003cp\u003eThe objective of determining the absolute TEM of skinfolds between evaluators with different levels of experience was calculated using the formula: TEM = \u0026radic;[(\u0026sum;Diff2)/2n]. Subsequently, the determination of the relative TEM percentage was calculated using the formula: %TEM = (TEM / mean) * 100. The classification of intra-rater TEM was carried out according to the criteria established by Norton \u0026amp; Olds et al. (2000)\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, which considers acceptable values of \u0026lt;\u0026thinsp;5% for expert anthropometrists and \u0026lt;\u0026thinsp;7.5% for novice anthropometrists.\u003c/p\u003e \u003cp\u003eThe inter-evaluator technical measurements error\u003c/p\u003e \u003cp\u003eAdditionally, was to assess the agreement of measurements between the anthropometrists and determine their variability. To calculate the inter-evaluator TEM, the same steps described earlier for calculating the intra-rater TEM should be followed. The procedures are the same, but the skinfold measurements to be considered in the calculations should be performed by the two anthropometrists who should be evaluated, using the same group of volunteers\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFinally, was analyzed the predictive agreement of body fat between the anthropometrists. Predictive validity refers to the \"validity based on the correlation between the assessment results R-N and a predicted future behavior\"\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eStatistical analysis\u003c/p\u003e \u003cp\u003eDescriptive measures (mean, standard deviation, and 95% confidence interval [CI]) were used to characterize the sample. To verify inter-evaluator agreement for skinfolds and body %fat, the intraclass correlation coefficient (ICC) and Bland \u0026amp; Altman\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. plots were used. The ICC classification consists of values less than 0.5 are indicative of poor reliability, values between 0.5 and 0.75 indicate moderate reliability, values between 0.75 and 0.9 indicate good reliability, and values greater than 0.90 indicate excellent reliability\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. All analyses were performed using SPSS 20.0 software. Bland \u0026amp; Altman plots were performed using GraphPad Prism 9.3 software. The significance level was set at 5%.\u003c/p\u003e\n\u003cp\u003e[1] between 900 and 3200 measurements per year were performed.\u003c/p\u003e\n\u003cp\u003e[2] academic-university literacy in anthropometry, close to 100 measurements.\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e reports the descriptive characteristics of the sample. The young adults (22 years old) showed low variability among themselves for body mass (95% CI: 74.3 to 82.9) and stature (95% CI: 174.0 to 180.0), revealing homogeneity of the sample in our study.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDescriptive characteristics of the sample (young men; n\u0026thinsp;=\u0026thinsp;25), according to the measurement of each rater.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eExpert rater\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cp\u003eNovice rater\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCI (95%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCI (95%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStature (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e177.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e174.0 to 180.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e177.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e174.0 to 180.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody mass (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.3 to 82.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.3 to 82.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.8 to 23.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.8 to 23.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSkinfold thickness\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTriceps (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.7 to 12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.7 to 13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiceps (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6 to 6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.4 to 19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSubscapular (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.8 to 21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.6 to 19.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIliac crest (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.0 to 27.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.1 to 21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdominal (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.3 to 28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.5 to 22.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThigh (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.4 to 19.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.2 to 18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCalf (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.9 to 12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.3 to 12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBody Fat (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.3 to 24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.8 to 43.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eCaption: SD\u0026thinsp;=\u0026thinsp;standard deviation; CI\u0026thinsp;=\u0026thinsp;confidence interval.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTo address our first objective, Fig.\u0026nbsp;1 presents the intra-rater and inter-evaluator relative TEM (%TEM) for all skinfolds. The expert rater remained below the tolerated limits (\u0026lt;\u0026thinsp;5%) for all skinfold measurements, while the novice rater exceeded the tolerated limits for iliac crest and abdominal skinfolds (\u0026gt;\u0026thinsp;7.5%).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo address our second objective, Fig.\u0026nbsp;2 presents the inter-evaluator ICC and Bland \u0026amp; Altman plot for skinfold values. The inter-evaluator reliabilities were good for triceps (ICC: 0.84 [95% CI: 0.60 to 0.93]), subscapular (ICC: 0.82 [95% CI: 0.63 to 0.91]), and calf (ICC: 0.89 [95% CI: 0.76 to 0.95]) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, the inter-evaluator reliabilities were moderate for iliac crest (ICC: 0.65 [95% CI: 0.34 to 0.83]), abdominal (ICC: 0.68 [95% CI: 0.34 to 0.85]), and thigh (ICC: 0.69 [95% CI: 0.41 to 0.85]) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, the inter-evaluator reliability for biceps skinfold was poor (ICC: 0.096 [95% CI: -0.077 to 0.348; p\u0026thinsp;=\u0026thinsp;0.07]).\u003c/p\u003e\n\u003cp\u003eIn accordance with our third objective, Fig.\u0026nbsp;3 presents the inter-evaluator ICC and Bland \u0026amp; Altman plot for the body %fat value. It was observed that there was poor reliability between the anthropometrists (ICC: 0.13 [95% CI: -0.01\u0026ndash;0.46; p\u0026thinsp;=\u0026thinsp;0.07]).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eOur study made significant contributions by determining the intra-evaluator TEM and assessing the reliability of skinfold and body %fat measurements using the ICC and Bland \u0026amp; Altman plots. Our findings revealed that the expert evaluator had acceptable TEM values for all skinfold measurements, while the novice evaluator exceeded the tolerable limits for iliac crest and abdominal skinfolds. The ICC and Bland \u0026amp; Altman plots demonstrated good reliability for triceps, subscapular and calf measurements, moderate reliability for iliac crest and abdominal measurements, and poor reliability for biceps measurements. Additionally, our results indicated a poor inter-evaluator reliability for body %fat, suggesting that the differences between anthropometrists significantly affected the calculated percentage of body fat. These findings highlight the importance of considering the expertise and experience of anthropometrists to obtain reliable and accurate estimations of body composition.\u003c/p\u003e \u003cp\u003eIt is noteworthy that both experienced and novice anthropometrists followed the same procedures for taking skinfold measurements. In a study by Oliveira et al. (2020) \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, comparisons were made between anthropometrists with and without adherence to the method and certification from the International Society for the Advancement of Kinanthropometry (ISAK). In contrast to our findings, the study observed that an evaluator with a more refined technique did not achieve an acceptable classification for intra-evaluator error in one of the four anthropometric measurements conducted. In this regard, it is essential to ensure precision during anthropometric measurement by: a) the evaluator has precision in repeating their measurements; b) they consistently adopt the same technique; and c) when inter-evaluator error is unknown, the same evaluator should always perform the measurement on the individual.\u003c/p\u003e \u003cp\u003eThe need for TEM for all anthropometric measurements, including the variation in agreement of skinfold measurements (good, moderate, and poor) between anthropometrists, is highlighted. It is important to emphasize that anthropometric measurements with higher TEM values require the evaluator, whether experienced or novice, to practice the measurement numerous times to reduce error and increase agreement between anthropometrists within the same work setting \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. On the other hand, the absolute measurement (expressed in millimeters) should be also considered. The absolute values provide information concerning local fat distribution in the body, and provides an index to determine adiposity, since subcutaneous fat reflects the amount of fat present in the adipose tissue \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Therefore, a potential difference between expert and novice anthropometrists may be evident by looking at absolute values.\u003c/p\u003e \u003cp\u003eIn the present study, it was found that the novice evaluator exceeded the tolerable limit of TEM for the iliac crest and abdominal skinfolds, while this did not happen in any of the cases in the expert anthropometrist. This in turn affected the inter-evaluator reliability for these skinfolds. Previous studies have shown that it is the higher skinfolds, such as these two trunk skinfolds, have a higher variability in compressibility when the caliper is applied \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Therefore, it is these types of skinfolds where variations in anthropometric technique can introduce a greater margin of error in measurement, especially affecting anthropometrists with limited experience. This is especially important when you consider that trunk skinfolds such as the iliac crest and abdominal skinfolds are variables used in most anthropometric fat mass estimation formulas \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Based on the results of the present investigation, it would be necessary to emphasize in anthropometry training, especially in the measurement of higher skinfolds and trunk skinfolds, to avoid inadequate assessment of skinfolds by novice anthropometrists.\u003c/p\u003e \u003cp\u003eRegarding the poor inter-evaluator agreement observed in our study regarding the prediction of body %fat, it highlights the importance of evaluator experience in reducing the chances of making inaccurate diagnoses \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. A study evaluated the performance of three anthropometrists with different levels of knowledge and practical experience in measurement techniques, as well as the impact on nutritional diagnosis \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. It was observed that less practice and previous training resulted in more errors during measurements, leading to low precision and accuracy, especially for body circumferences and skinfolds. Inadequate collection of skinfold measurements by less trained anthropometrists resulted in errors in the classification of nutritional diagnosis regarding body %fat. Therefore, periodic training in anthropometry is recommended to ensure reliable results, both at the individual and collective level \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral strengths of our study should be considered. The use of TEM allows for the assessment of the precision and accuracy of anthropometric measurements, as well as the identification of systematic and random errors during the measurement process. Thus, it is an important tool for standardizing measurement protocols and training anthropometrists, which can increase the quality and reliability of anthropometric measurements. Additionally, TEM can assist in monitoring the quality of measurements over time, enabling the identification of potential issues, and adjusting improve the precision and accuracy of measurements. Therefore, the use of TEM can contribute to the comparison of results across different studies and/or anthropometrists, which is crucial for advancing knowledge in the field of anthropometry.\u003c/p\u003e \u003cp\u003eAlthough our results are promising, some limitations should be considered. The small sample size may be a limiting factor for understanding TEM on a larger scale, although our study sample is homogeneous (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Another limitation is the presence of only one anthropometrists in each category. This may not reflect the variability found in a larger sample of anthropometrists, and it does not allow for a more precise comparison of performance between the groups. Therefore, it is important to have a significant number of anthropometrists in each group to increase the reliability of the results and determine whether experience and prior training are determining factors in reducing TEM.\u003c/p\u003e \u003cp\u003eThrough this investigation, we hope to provide valuable insights into the importance of anthropometrists\u0026rsquo; experience in obtaining reliable measurements of body composition, and ultimately, to inform best practices for accurate body composition assessment in clinical and research settings. TEM should be regularly monitored to prevent estimation errors. Even in contexts where estimates are not derived (e.g., sum of skinfold thicknesses), calculating and reporting TEM is necessary. Studies that present measurements made by anthropometrists with high TEM or fail to report TEM values of their anthropometrists should be interpreted with caution. Anthropometrists with high TEM should undergo training until TEM becomes acceptable.\u003c/p\u003e \u003cp\u003eFor future studies, we suggest investigating the relationship between evaluator experience and the precision of anthropometric measurements to identify the minimum levels of experience required to obtain accurate and reliable measurements. Comparing different equipment and techniques for anthropometric measurement would also be valuable in identifying the most precise and reliable methods for different populations and study objectives. Lastly, exploring the relationship between TEM and the accuracy of body composition assessment methods such as bioelectrical impedance analysis and dual-energy X-ray absorptiometry would provide further insights into the field.\u003c/p\u003e \u003cp\u003eContinued research in these areas will contribute to enhancing the accuracy and reliability of anthropometric measurements, thereby improving our understanding of how rater experience impacts measurement outcomes. To achieve this, providing standardized training and ongoing education to anthropometrists is essential, ensuring their competence in performing accurate measurements. Experienced anthropometrists can improve the reliability of measurements and minimize the risk of overestimating or underestimating body composition in different populations, including athletes, older adults, and young subjects. This previous experience can ensure the reliability of an appropriate diagnosis of body compartments, minimizing the chances of under/overestimation in different populations (i.e., athletes, older adults, and young subjects) \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, we still do not know how much of this experience is decisive in skinfold measurements, especially when comparing expert and novice anthropometrists.\u003c/p\u003e \u003cp\u003eIn this study, we determined the intra-rater technical error of skinfold measurements for both expert and novice anthropometrists, as well as the agreement of skinfold and %bodyfat measurements between anthropometrists. The inter-rater measurements of skinfolds with varying levels of expertise were not always statistically significant, despite standardization of the measurement protocol and the use of equally calibrated skinfold calipers. However, differences observed in the TEM suggest that the precision in assessing body composition does not solely depend on potential measurement variation, but rather on the stability achieved through experience. The experience of the anthropometrists also directly influences the accuracy of %bodyfat prediction. Therefore, less experienced anthropometrists can benefit from theoretical and practical training to enhance the objectivity and reliability of their assessments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The guidelines and ethical aspects of research with human beings were followed according to the Declaration of Helsinki, the Free and Informed Consent Term signed by each participant was also obtained. This study was approved by Ethics and Research Committees (CAAE: 49292915.7.0000.5659).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConflict of Interest\u003c/strong\u003e \u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDRLM, VCR performed conduction of experiments, wrote introduction, methods, results, and discussion sections. LSLS, MFTJ, APS, PPA, LFM, ASO and, RVC improved interpretation analysis and reviewed the manuscript. JM draft the manuscript and improved interpretation analysis and reviewed English Grammar and Spelling. DRLM, PJMP supervised the study, draft the manuscript, and gave final approval for the version submitted for publication. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eWe thank the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior - Brasil (CAPES) - Finance Code 001.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUtkualp, N. \u0026amp; Ercan, I. Anthropometric Measurements Usage in Medical Sciences. \u003cem\u003eBioMed Research International\u003c/em\u003e 2015, e404261 (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdalla, P. 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Singapore Med J 50, 1013\u0026ndash;1018 (2009).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"body composition, anthropometry, nutrition assessment, caliper, accuracy","lastPublishedDoi":"10.21203/rs.3.rs-4540605/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4540605/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, we aimed to identify the variability among anthropometrists with varying levels of experience and its effects on the final interpretations of body composition estimates. Were implied 25 male university students, aged between 18 and 30 years. Skinfold measurements of eight body regions were obtained by two anthropometrists: an expert (more than 20 years of experience) and a novice (initial basic training). The same calibrated adipometer was used to verify the %fat. The results showed that the expert technical error of measurements (TEM) was below the tolerated limits (\u0026lt;\u0026thinsp;5%) for all skinfold measurements, while the novice exceeded the rater (\u0026gt;\u0026thinsp;7.5%) for the iliac crest and abdominal skinfolds. The inter-evaluator reliabilities were good for triceps, subscapular, and calf skinfolds; moderate for iliac crest, abdominal, and thigh skinfolds; but poor for biceps skinfolds. Some TEM novice measurements were 2 to 4 times higher than expert. The Bland \u0026amp; Altman analysis showed that inter-evaluator reliabilities were good for triceps, subscapular, and calf (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, the inter-evaluator reliabilities were moderate for iliac crest, abdominal, and thigh (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and poor for biceps (p\u0026thinsp;=\u0026thinsp;0.07). There was a significant impact on the predicted %fat, with estimates up to 55.12% higher by the novice compared to the expert. Conclusively, low reliability in estimating body fat emphasizes the importance of measurement training. Measurements by anthropometrists with low expertise levels are unreliable even with standardized protocols and equally calibrated instruments.\u003c/p\u003e","manuscriptTitle":"Reliability of skinfold measurements and body fat prediction depends on the rater's experience: a cross-sectional analysis comparing expert and novice anthropometrists","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-27 11:00:36","doi":"10.21203/rs.3.rs-4540605/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"88996732-4495-4378-9a73-dfada798b124","owner":[],"postedDate":"June 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33784910,"name":"Health sciences/Health care/Nutrition"},{"id":33784911,"name":"Health sciences/Health care/Weight management"}],"tags":[],"updatedAt":"2024-12-17T06:53:55+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-27 11:00:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4540605","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4540605","identity":"rs-4540605","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}