The use of accelerometer-based monitors for the measurement of physical activity (PA) has increased substantially over the last several years. These devices are typically worn on the body and have internal clocks and large memory capacities making them well suited as a non- invasive objective method of tracking physical activity patterns for days to weeks. Typically, accelerometer data are converted to estimates of energy expenditure (EE) by using single linear regression equations. However, such equations are exclusively developed to capture the lower extremity movements of ambulatory populations and thus are not applicable to wheelchair users who rely on their upper extremities for mobility. We recently evaluated three off-the-shelf accelerometer-based monitors in estimating EE among 45 full-time manual wheelchair users with spinal cord injury (SCI). The results revealed large discrepancies between each device output and indirect calorimetry for wheelchair related activities such as wheelchair propulsion and arm ergometry. Building upon this previous work, this proposal addresses the need for a PA assessment tool suitable for tracking free-living PA and EE among veterans with spinal cord injury & disorders (SCI/D), especially those who use manual wheelchairs as their primary means of mobility. We will team up two VA centers in this proposed project (i.e., the Center of Excellence on Wheelchairs and Associated Rehabilitation Engineering in Pittsburgh, PA and the Center for Medical Consequences of SCI in Bronx, NY) to develop an ecologically valid EE prediction model for veterans with SCI/D and evaluate its performance extensively under naturalistic conditions.
The specific aims of the study are to: 1) to develop machine-learning based prediction models of EE in MWUs with SCI/D based on accelerometer-based activity monitors using a variety of activities that will range from sedentary behaviors to vigorous PAs (n=84); 2) to evaluate the accuracy and precision of the new EE prediction model in a separate sample of MWUs with SCI/D under semi-naturalistic and naturalistic conditions (n=24); and 3) to evaluate the long-term validity of the new EE prediction model in a separate sample of MWUs with SCI/D under naturalistic conditions (n=16). We expect this proposal will result in an accurate and precise assessment tool for estimating free-living EE and time spent in light, moderate, and vigorous PA in veterans with SCI/D. Veterans with SCI/D could use the tool to regularly and accurately self-monitor their everyday PA and EE to increase their self-awareness - a prerequisite for healthy decision making and long-term lifestyle change. Researchers and clinicians could use the tool to objectively and accurately assess PA interventions and determine appropriate interventions for weight management. The proposed tool could facilitate better personal and clinical decisions on PA, energy balance, and healthier lifestyle for both veteran and non-veteran populations with SCI/D.
The prevalence of obesity and other chronic conditions such as cardiovascular disease and diabetes among veterans with SCI/D is widely documented. Physical inactivity and energy imbalance are common risk factors for these conditions. However, there are no objective assessment tool that can help veterans with SCI/D to track their free-living physical activities and energy expenditure. This proposal directly supports the mission of the VHA SCI/D Program by delivering such a tool to help veterans with SCI/D and professionals make better personal and clinical decisions on physical activity, energy balance, and healthier lifestyle. A healthy lifestyle in veterans with SCI/D could reduce the incidence and severity of secondary conditions, reduce direct healthcare cost, and lead to better overall health and higher quality of life.
