Regression equations to predict 6-minute walk distance in middle-aged and elderly adults

Abstract

Six-minute walk distance (6MWD) is commonly used as a measure of functional exercise capacity in clinical practice and research. Regression equations to predict 6MWD in healthy individuals are available, but the equations predict distances that vary considerably for an individual. The aims of this study were to 1) measure 6MWDs in healthy Caucasian Australians aged 45-85 years; 2) determine whether evidence exists for Australian-specific prediction equations for Caucasian individuals by comparing measured 6MWDs with predicted 6MWDs derived by using published regression equations; and 3) develop regression equations for males and females. One hundred nine subjects (48 males) completed the 6-minute walk test (6MWT). Measurements of height, leg length, weight, habitual physical activity, and peak heart rate (HR) achieved during the 6MWT were obtained. 6MWD (better of two tests) was 682 +/- 73 m (mean +/- SD) and 643 +/- 70 m in the males and females, respectively (p<0.01). Published regression equations underestimated 6MWDs in female subjects. Gender-specific regression equations using age and anthropometric data explained 40% and 43% of the variance in 6MWD in males and females, respectively. Validation of the regression equations in a prospective subject cohort is required.

Teste de caminhada de seis minutos: valores de referência para adultos saudáveis no Brasil

“…However, it should be borne in mind that physically fit individuals were excluded. Habitual physical activity has been evaluated in seven studies of 6MWT reference values, (10)(11)(12)(16)(17)(18)(19) basis of that finding, the 5th percentile for the 6MWD was calculated separately for values above and below the median. The lower limit, transformed into a proportion, was found to be 81% of the value predicted for both groups.…”

“…Of the total of individuals under study, 104 (79%) were considered sedentary (total habitual physical activity questionnaire score < 8.0) and Stature was a relevant anthropometric variable for the prediction of the 6MWD in the present study, as it was in all such studies involving significant samples. (13)(14)(15)(16)(17)19) In the study conducted by Iwama et al, (18) only age and gender were taken into consideration when the regression equation was being derived. However, in the univariate analysis, the authors found that stature had the highest correlation coefficient, and its inclusion in the multivariate equation was therefore obligatory.…”

“…(9)(10)(11)(12)(13) In other studies, the methods and sample size have been appropriate. (14)(15)(16)(17) In a study recently conducted in Brazil and involving 134 individuals, the predicted 6MWD was determined considering only age and gender. (18) However, in most studies, stature is also considered a relevant variable for determining the predicted 6MWD.…”

“…(9,10,(12)(13)(14)(15)(16)(17) Other authors have devised equations indicating that body weight or the body mass index (BMI) significantly influence the predicted 6MWD. (9,10,12,13,15,17) A multicenter study, involving 10 centers in seven countries, determined 6MWD reference values for individuals over 40 years of age. (19) In that study, the 6MWD reference values were found to vary in function of the geographic location; therefore, different countries require specific equations.…”

Incapacity, Handicap, and Oxidative Stress Markers of Male Smokers With and Without COPD

“…Cardiovascular data (such as heart rate and blood pressures) are predictors of 6MWD. 65,66 However, they cannot be advanced as an explanation, since the 2 groups have similar heart rate and blood pressure data and include similar percentages of smokers with chronotropic insufficiency.…”