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      Lung Function and Respiratory Muscle Adaptations of Endurance- and Strength-Trained Males

      research-article
      Sports
      MDPI
      respiratory mouth pressures, respiratory muscles, resistance training, muscle strength, exercise performance

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          Abstract

          Diverse exercise-induced adaptations following aerobic endurance compared to strength-training programs is well documented, however, there is paucity of research specifically focused on adaptations in the respiratory system. The aim of the study was to examine whether differences in lung function and respiratory muscle strength exist between trainers predominately engaged in endurance compared to strength-related exercise. A secondary aim was to investigate if lung function and respiratory muscle strength were associated with one-repetition maximum (1RM) in the strength trainers, and with VO 2 max and fat-free mass in each respective group. Forty-six males participated in this study, consisting of 24 strength-trained (26.2 ± 6.4 years) and 22 endurance-trained (29.9 ± 7.6 years) participants. Testing involved measures of lung function, respiratory muscle strength, VO 2 max, 1RM, and body composition. The endurance-trained compared to strength-trained participants had greater maximal voluntary ventilation (MVV) (11.3%, p = 0.02). The strength-trained compared to endurance-trained participants generated greater maximal inspiratory pressure (MIP) (14.3%, p = 0.02) and maximal expiratory pressure (MEP) (12.4%, p = 0.02). Moderate–strong relationships were found between strength-trained respiratory muscle strength (MIP and MEP) and squat and deadlift 1RM (r = 0.48–0.55, p ≤ 0.017). For the strength-trained participants, a strong relationship was found between MVV and VO 2 max (mL·kg −1·min −1) (r = 0.63, p = 0.003) and a moderate relationship between MIP and fat-free mass (r = 0.42, p = 0.04). It appears that endurance compared to strength trainers have greater muscle endurance, while the latter group exhibits greater respiratory muscle strength. Differences in respiratory muscle strength in resistance trainers may be influenced by lower body strength.

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          Most cited references46

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          A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research.

          Intraclass correlation coefficient (ICC) is a widely used reliability index in test-retest, intrarater, and interrater reliability analyses. This article introduces the basic concept of ICC in the content of reliability analysis.
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            Progressive statistics for studies in sports medicine and exercise science.

            Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.
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              Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations.

              The aim of the Task Force was to derive continuous prediction equations and their lower limits of normal for spirometric indices, which are applicable globally. Over 160,000 data points from 72 centres in 33 countries were shared with the European Respiratory Society Global Lung Function Initiative. Eliminating data that could not be used (mostly missing ethnic group, some outliers) left 97,759 records of healthy nonsmokers (55.3% females) aged 2.5-95 yrs. Lung function data were collated and prediction equations derived using the LMS method, which allows simultaneous modelling of the mean (mu), the coefficient of variation (sigma) and skewness (lambda) of a distribution family. After discarding 23,572 records, mostly because they could not be combined with other ethnic or geographic groups, reference equations were derived for healthy individuals aged 3-95 yrs for Caucasians (n=57,395), African-Americans (n=3,545), and North (n=4,992) and South East Asians (n=8,255). Forced expiratory value in 1 s (FEV(1)) and forced vital capacity (FVC) between ethnic groups differed proportionally from that in Caucasians, such that FEV(1)/FVC remained virtually independent of ethnic group. For individuals not represented by these four groups, or of mixed ethnic origins, a composite equation taken as the average of the above equations is provided to facilitate interpretation until a more appropriate solution is developed. Spirometric prediction equations for the 3-95-age range are now available that include appropriate age-dependent lower limits of normal. They can be applied globally to different ethnic groups. Additional data from the Indian subcontinent and Arabic, Polynesian and Latin American countries, as well as Africa will further improve these equations in the future.
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                Author and article information

                Journal
                Sports (Basel)
                Sports (Basel)
                sports
                Sports
                MDPI
                2075-4663
                10 December 2020
                December 2020
                : 8
                : 12
                : 160
                Affiliations
                Exercise, Health and Performance Faculty Research Group, School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Lidcombe, NSW 2141, Australia; daniel.hackett@ 123456sydney.edu.au ; Tel.: +61-2-9351-9294; Fax: +61-2-9351-9204
                Author information
                https://orcid.org/0000-0002-2504-3942
                Article
                sports-08-00160
                10.3390/sports8120160
                7764033
                33321800
                43e4e784-0352-4f02-8875-d723b7a90350
                © 2020 by the author.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 November 2020
                : 08 December 2020
                Categories
                Article

                respiratory mouth pressures,respiratory muscles,resistance training,muscle strength,exercise performance

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