Eduardo Lusa, R. Pinto, E. Silva, R. Spinelli, C. S. Correa, L. Kruel
{"title":"PREDICTION OF ONE REPETITION MAXIMUM LOAD BY TOTAL AND LEAN BODY MASS IN TRAINED AND UNTRAINED MEN","authors":"Eduardo Lusa, R. Pinto, E. Silva, R. Spinelli, C. S. Correa, L. Kruel","doi":"10.5604/17342260.1011391","DOIUrl":null,"url":null,"abstract":"Introduction: One repetition maximum test (1RM) is often used to evaluate muscle strength and to prescribe the in ⴀ tensity of strength training. However, the determination of the initial test load, and duration of the test make difficult to use the same in non ⴀindividualised environments. Objective: To determine coefficients to estimate the maximum strength (1RM), based on the relationship between muscular strength, lean body mass and total body mass. Methods: Twenty ⴀeight strength ⴀtrained and non ⴀstrength ⴀtrained men participated in this study. Muscle strength was determined using the 1 RM test in the bench press, supported barbell row, 45° leg press and squat exercise, while body composition was measured using the skinfolds method. After verifying the correlations between muscular strength and body mass and composition, the coefficients to predict the maximal strength were calculated by dividing the value of the 1 RM by the total body mass and lean body mass (kg) and by linear regression equation based in these parameters. Results: Significant correlations were found between body mass and lean body mass with muscular strength in all the exercises ( r = 0.47 ⴀ 0.76, P < 0.05). The greatest correlations were observed between the muscular strength values and lean body mass. There was a significant difference between the coefficients obtained from trained and non ⴀtrained subjects in all the tested exercises ( P < 0.05). Conclusions: The results suggest that the coefficients of prediction of the 1RM should take into account the body composition and the training status of the individuals.","PeriodicalId":93474,"journal":{"name":"Medicina sportiva (Krakow, Poland : English ed.)","volume":"1 1","pages":"111-117"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medicina sportiva (Krakow, Poland : English ed.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5604/17342260.1011391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Introduction: One repetition maximum test (1RM) is often used to evaluate muscle strength and to prescribe the in ⴀ tensity of strength training. However, the determination of the initial test load, and duration of the test make difficult to use the same in non ⴀindividualised environments. Objective: To determine coefficients to estimate the maximum strength (1RM), based on the relationship between muscular strength, lean body mass and total body mass. Methods: Twenty ⴀeight strength ⴀtrained and non ⴀstrength ⴀtrained men participated in this study. Muscle strength was determined using the 1 RM test in the bench press, supported barbell row, 45° leg press and squat exercise, while body composition was measured using the skinfolds method. After verifying the correlations between muscular strength and body mass and composition, the coefficients to predict the maximal strength were calculated by dividing the value of the 1 RM by the total body mass and lean body mass (kg) and by linear regression equation based in these parameters. Results: Significant correlations were found between body mass and lean body mass with muscular strength in all the exercises ( r = 0.47 ⴀ 0.76, P < 0.05). The greatest correlations were observed between the muscular strength values and lean body mass. There was a significant difference between the coefficients obtained from trained and non ⴀtrained subjects in all the tested exercises ( P < 0.05). Conclusions: The results suggest that the coefficients of prediction of the 1RM should take into account the body composition and the training status of the individuals.