Dahan da Cunha Nascimento1,2, Ivo Vieira de Sousa Neto3, Bruno Saraiva1, Adamor da Silva Lima4, James Wilfred Navalta5, Guilherme Borges Pereira6, Jeffrey M Willardson7, Fabiani Lage Rodrigues Beal2, Jonato Prestes1. 1. Department of Physical Education, Catholic University of Brasilia (UCB). 2. Department of Gerontology, Catholic University of Brasilia, UCB, Brasilia. 3. Laboratory of Molecular Analysis, Graduate program of Sciences and Technology of Health, University of Brasilia (UNB), Distrito Federal. 4. Department of Physical Education, University of Brasilia (UNB), Brasilia, Brazil. 5. Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Nevada, USA. 6. Programa Interinstitucional de Pós-Graduação em Ciências Fisiológicas. Laboratório de Fisiologia do Exercício do Departamento de Ciências Fisiológicas da Universidade Federal de São Carlos (UFSCar), Brasil. 7. Health and Human Performance Department, Montana State University Billings, Billings, Montana USA.
Abstract
BACKGROUND: Repeated measures analysis of covariance and three-way analysis of variance with repeated measures are common statistical methods. For a valid interpretation of blood pressure (BP) response to exercise, a variety of additional statistical methods must be implemented. Four additional statistical methods are presented: technical error of measurement (SEM), smallest real difference (SRD), magnitude-based inference and mixed effect modeling technique (MEM). The aim of this perspective article is to demonstrate how to apply already known statistical analyses regarding BP responsiveness in order to improve interpretation and achieve higher reliability for future studies in exercise science. METHODS: A total of 27 hypertensive older women (aged 68.37 ± 5.55 years) participated in the present study. A whole-body resistance training (RT) program was performed on two nonconsecutive days per week for 10 weeks. BP was monitored during the 10-week RT intervention and after 15 weeks of detraining. First, individuals were classified as high and low responders, then statistical methods to analyze data included the use of SEM, SRD, magnitude-based inference and MEM. RESULTS: When magnitude-based inference was used to classify responsiveness, most participants displayed a trivial response. Decrements in SBP between 1 and 10 mmHg were not clinically meaningful but fell within the measurement error of the SBP measurements. Baseline SBP and time of training predicted post-SBP response. CONCLUSION: Changes over time and declines in SBP might not be a SRD and fell in the SEM. Moreover, SBP responsiveness was the result of inappropriate control of covariates such as period of training.
BACKGROUND: Repeated measures analysis of covariance and three-way analysis of variance with repeated measures are common statistical methods. For a valid interpretation of blood pressure (BP) response to exercise, a variety of additional statistical methods must be implemented. Four additional statistical methods are presented: technical error of measurement (SEM), smallest real difference (SRD), magnitude-based inference and mixed effect modeling technique (MEM). The aim of this perspective article is to demonstrate how to apply already known statistical analyses regarding BP responsiveness in order to improve interpretation and achieve higher reliability for future studies in exercise science. METHODS: A total of 27 hypertensive older women (aged 68.37 ± 5.55 years) participated in the present study. A whole-body resistance training (RT) program was performed on two nonconsecutive days per week for 10 weeks. BP was monitored during the 10-week RT intervention and after 15 weeks of detraining. First, individuals were classified as high and low responders, then statistical methods to analyze data included the use of SEM, SRD, magnitude-based inference and MEM. RESULTS: When magnitude-based inference was used to classify responsiveness, most participants displayed a trivial response. Decrements in SBP between 1 and 10 mmHg were not clinically meaningful but fell within the measurement error of the SBP measurements. Baseline SBP and time of training predicted post-SBP response. CONCLUSION: Changes over time and declines in SBP might not be a SRD and fell in the SEM. Moreover, SBP responsiveness was the result of inappropriate control of covariates such as period of training.
Authors: Dahan da Cunha Nascimento; Diane Nogueira Paranhos Amorim; Vicente Paulo Alves; Karla Helena Coelho Vilaça E Silva; Whitley Stone Journal: Osteoporos Sarcopenia Date: 2022-09-30
Authors: Ivo Vieira de Sousa Neto; Dahan da Cunha Nascimento; Jonato Prestes; Eduardo Fernandes da Fonseca; Rodrigo Souza Celes; Nicholas Rolnick; Yuri Gustavo de Sousa Barbalho; Alessandro de Oliveira Silva; Marina Morato Stival; Luciano Ramos de Lima; Silvana Schwerz Funghetto Journal: Biology (Basel) Date: 2022-03-31