ORIGINAL ARTICLE   Free

European Journal of Physical and Rehabilitation Medicine 2019 December;55(6):824-33

DOI: 10.23736/S1973-9087.19.05687-9

Copyright © 2019 EDIZIONI MINERVA MEDICA

lingua: Inglese

Predictive models for the six-minute walk test considering the walking course and physical activity level

Vívian P. ALMEIDA ¹, Arthur S. FERREIRA ¹, Fernando S. GUIMARÃES ^{1, 2}, Jannis PAPATHANASIOU ^{3, 4}, Agnaldo J. LOPES ^{1, 5} ✉

¹ Rehabilitation Sciences Post-Graduate Program, Augusto Motta University Center (UNISUAM), Rio de Janeiro, Brazil; ² Department of Physical Therapy, School of Medicine, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; ³ Department of Medical Imaging, Allergology and Physiotherapy, Faculty of Dental Medicine, Medical University of Plovdiv, Plovdiv, Bulgaria; ⁴ Department of Kinesitherapy, Faculty of Public Health, Medical University of Sofia, Sofia, Bulgaria; ⁵ Medical Sciences Post-Graduate Program, School of Medical Sciences, State University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazil

BACKGROUND: In recent decades, space limitations in the clinical environment have forced health professionals to administer the six-minute walk test (6MWT) using a 20-m or even a 10-m course. However, course length and physical activity level (PAL) affect the test outcomes.
AIM: To develop a reference equation for the 6MWT that takes into account the effects of course length and PAL on the walking distance.
DESIGN: Cross-sectional study.
SETTING: Federal University of the State of Rio de Janeiro.
POPULATION: Two hundred fifteen healthy adults.
METHODS: All subjects performed the 6MWT on 10-, 20- and 30-m courses. Eight regression models were constructed considering the association between the six-minute walking distance (6MWD) and heart rate, perceived effort (scores from the Borg’s Perceived Exertion Scale-BPES), PAL (classification according to the International Physical Activity Questionnaire, IPAQ), as well as anthropometric and demographic variables. The models were analyzed for the coefficients of determination (R2) and statistical significance at P<0.05.
RESULTS: A nonlinear increase in the means of the 6MWDs obtained using the three course lengths was observed (591±70, 652±79 and 678±85 m for course lengths of 10, 20 and 30 m, respectively, with P<0.001). The 6MWD correlated positively with the following variables: sex (r=0.20), body height (r=0.30), IPAQ classification (r=0.14), ΔBPES rating (r=0.25) and Δheart rate (HR, r=0.23), with P<0.001 for all. In contrast, the 6MWD correlated negatively with age (r=-0.23) and Body Mass Index (BMI, r=-0.18), with P<0.001 for both. The regression model with the highest coefficient of determination (adjusted R2=0.36) included the following variables: sex, age, BMI, course length (CL), BPES, HR, and IPAQ.
CONCLUSIONS: The length of the course strongly impacts individual performance on the 6MWT in a predominantly young adult population. Furthermore, IPAQ-assessed PAL is an important independent predictor of 6MWD.
CLINICAL REHABILITATION IMPACT: The incorporation of course length in the prediction of 6MWD allows the use of a prediction equation that includes the effects of different course sizes. PAL should be used in the prediction of 6MWD.

KEY WORDS: Walk test; Exercise test; Reference values