Related Experiment Video
Updated: Jun 18, 2026

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults
Published on: February 8, 2019
Regression equations to predict 6-minute walk distance in middle-aged and elderly adults
Sue Jenkins1, Nola Cecins, Bernadine Camarri
1School of Physiotherapy, Curtin University of Technology, Perth, Western Australia. S.Jenkins@curtin.edu.au
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.
More Related Videos
Related Concept Videos
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Regression Toward the Mean

