Descriptive statistics for variables of interest.

<p>BAT = Balance and Tone; 1× RT = once-weekly resistance training; 2× RT = twice- weekly resistance training; BMI = weight in kilograms/height in square meters; Baseline Stroop and Trial completion Stroop performance = Stroop color words condition subtracted by Stroop coloured x's condition; Δ in Stroop = Stroop Baseline subtracted by Trial completion Stroop; Δ in Sub-total fat mass = Final fat mass subtracted by Baseline fat mass (a positive number represents an increase in fat mass and a negative number represents a decrease in fat mass); Δ in Sub-total lean mass = Final lean mass subtracted by Baseline lean mass (a positive number represents an increase in lean mass and a negative number represents a decrease in lean mass).</p

Multiple linear regression model assessing the contribution of fat and lean mass composition to trial completion Stroop test performance.

*<p> = significance at p<0.05.</p><p>Δ in Sub-total fat mass = Baseline fat mass subtracted by Final fat mass; Δ in Sub-total lean mass = Final lean mass subtracted by Baseline lean mass.</p

An Economic Evaluation of Resistance Training and Aerobic Training versus Balance and Toning Exercises in Older Adults with Mild Cognitive Impairment

<div><p>Background</p><p>Mild cognitive impairment (MCI) represents a critical window to intervene against dementia. Exercise training is a promising intervention strategy, but the efficiency (i.e., relationship of costs and consequences) of such types of training remains unknown. Thus, we estimated the incremental cost-effectiveness of resistance training or aerobic training compared with balance and tone exercises in terms of changes in executive cognitive function among senior women with probable MCI.</p><p>Methods</p><p>Economic evaluation conducted concurrently with a six-month three arm randomized controlled trial including eighty-six community dwelling women aged 70 to 80 years living in Vancouver, Canada. Participants received twice-weekly resistance training (n = 28), twice weekly aerobic training (n = 30) or twice-weekly balance and tone (control group) classes (n = 28) for 6 months. The primary outcome measure of the Exercise for Cognition and Everyday Living (EXCEL) study assessed executive cognitive function, a test of selective attention and conflict resolution (i.e., Stroop Test). We collected healthcare resource utilization costs over six months.</p><p>Results</p><p>Based on the bootstrapped estimates from our base case analysis, we found that both the aerobic training and resistance training interventions were less costly than twice weekly balance and tone classes. Compared with the balance and tone group, the resistance-training group had significantly improved performance on the Stroop Test (<i>p</i> = 0.04).</p><p>Conclusions</p><p>Resistance training and aerobic training result in health care cost saving and are more effective than balance and tone classes after only 6 months of intervention. Resistance training is a promising strategy to alter the trajectory of cognitive decline in seniors with MCI.</p><p>Trial Registration</p><p>ClinicalTrials.gov <a href="http://clinicaltrials.gov/ct2/show/NCT00958867" target="_blank">NCT00958867</a>.</p></div

The mean squared errors associated with Model 1, Model 2, and Model 3, to compare the model with top 10 variables selected at each cross-validation loop with the model with only one variable of baseline MoCA and also with model with all the 32 variables.

<p>Model 1: Standard Regression Model with One Variable of Baseline MoCA.</p><p>Model 2: Standard Regression Model with Six Variables Consistently Selected at Every Cross-Validation Loop.</p><p>Model 3: Standard Regression Model Using All 32 Variables.</p><p>Abbreviations: MoCA: Montreal Cognitive Assessment.</p><p>The mean squared errors associated with Model 1, Model 2, and Model 3, to compare the model with top 10 variables selected at each cross-validation loop with the model with only one variable of baseline MoCA and also with model with all the 32 variables.</p

The process of variable selection using the elastic net method.

<p>Step 1 shows the generation of train and test sets for each cross-validation loops. We used jackknifing technique to assign one participant to the test set and the rest to the training set. In Step 2, the optimized model is estimated for the training set, using elastic net method. This model has minimized squared error on each cross-validation loop. This model is then tested on the test set in Step 3. After the whole process is repeated over all the participants to avoid the bias, we selected the variables which were consistently selected on all the cross-validation loops. There were 6 variables which were selected in this way.</p