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

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 (R-2) 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), Delta BPES rating (r=0.25) and Delta heart 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 R-2=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.