Cost-effectiveness of a physical activity and behaviour maintenance programme on functional mobility decline in older adults: an economic evaluation of the REACT (Retirement in Action) trial.

BACKGROUND: Mobility limitations in older populations have a substantial impact on health outcomes, quality of life, and social care costs. The Retirement in Action (REACT) randomised controlled trial assessed a 12-month community-based group physical activity and behaviour maintenance intervention to help prevent decline in physical functioning in older adults at increased risk of mobility limitation. We aimed to do an economic evaluation of the REACT trial to investigate whether the intervention is cost-effective. METHODS: In this health economic evaluation, we did cost-effectiveness and cost-utility analyses of the REACT programme versus standard care on the basis of resource use, primary outcome, and health-related quality-of-life data measured in the REACT trial. We also developed a decision analytic Markov model that forecasts the mobility of recipients beyond the 24-month follow-up of the trial and translated this into future costs and potential benefit to health-related quality of life using the National Health Service and Personal Social Services perspective. Participants completed questionnaire booklets at baseline, and at 6, 12, and 24 months after randomisation, which included a resource use questionnaire and the EQ-5D-5L and 36-item short-form survey (SF-36) health-related quality-of-life instruments. The cost of delivering the intervention was estimated by identifying key resources, such as REACT session leader time, time of an individual to coordinate the programme, and venue hire. EQ-5D-5L and SF-36 responses were converted to preference-based utility values, which were used to estimate quality-adjusted life-years (QALYs) over the 24-month trial follow-up using the area-under-the-curve method. We used generalised linear models to examine the effect of the REACT programme on costs and QALYs and adjust for baseline covariates. Costs and QALYs beyond 12 months were discounted at 3·5% per year. This is a pre-planned analysis of the REACT trial; the trial itself is registered with ISRCTN (ISRCTN45627165). FINDINGS: The 12-month REACT programme was estimated to cost £622 per recipient to deliver. The most substantial cost components are the REACT session leader time (£309 per participant), venue hire (£109), and the REACT coordinator time (£80). The base-case analysis of the trial-based economic evaluation showed that reductions in health and social care usage due to the REACT programme could offset the REACT delivery costs (£3943 in the intervention group vs £4043 in the control group; difference: -£103 [95% CI -£695 to £489]) with a health benefit of 0·04 QALYs (0·009-0·071; 1·354 QALYs in the intervention group vs 1·314 QALYs in the control group) within the 24-month timeframe of the trial. INTERPRETATION: The REACT programme could be considered a cost-effective approach for improving the health-related quality of life of older adults at risk of mobility limitations. FUNDING: National Institute for Health Research Public Health Research Programme.

Predicting ambulatory energy expenditure in lower limb amputees using multi-sensor methods.

PURPOSE: To assess the validity of a derived algorithm, combining tri-axial accelerometry and heart rate (HR) data, compared to a research-grade multi-sensor physical activity device, for the estimation of ambulatory physical activity energy expenditure (PAEE) in individuals with traumatic lower-limb amputation. METHODS: Twenty-eight participants [unilateral (n = 9), bilateral (n = 10) with lower-limb amputations, and non-injured controls (n = 9)] completed eight activities; rest, ambulating at 5 progressive treadmill velocities (0.48, 0.67, 0.89, 1.12, 1.34m.s-1) and 2 gradients (3 and 5%) at 0.89m.s-1. During each task, expired gases were collected for the determination of [Formula: see text] and subsequent calculation of PAEE. An Actigraph GT3X+ accelerometer was worn on the hip of the shortest residual limb and, a HR monitor and an Actiheart (AHR) device were worn on the chest. Multiple linear regressions were employed to derive population-specific PAEE estimated algorithms using Actigraph GT3X+ outputs and HR signals (GT3X+HR). Mean bias±95% Limits of Agreement (LoA) and error statistics were calculated between criterion PAEE (indirect calorimetry) and PAEE predicted using GT3X+HR and AHR. RESULTS: Both measurement approaches used to predict PAEE were significantly related (P<0.01) with criterion PAEE. GT3X+HR revealed the strongest association, smallest LoA and least error. Predicted PAEE (GT3X+HR; unilateral; r = 0.92, bilateral; r = 0.93, and control; r = 0.91, and AHR; unilateral; r = 0.86, bilateral; r = 0.81, and control; r = 0.67). Mean±SD percent error across all activities were 18±14%, 15±12% and 15±14% for the GT3X+HR and 45±20%, 39±23% and 34±28% in the AHR model, for unilateral, bilateral and control groups, respectively. CONCLUSIONS: Statistically derived algorithms (GT3X+HR) provide a more valid estimate of PAEE in individuals with traumatic lower-limb amputation, compared to a proprietary group calibration algorithm (AHR). Outputs from AHR displayed considerable random error when tested in a laboratory setting in individuals with lower-limb amputation.

Home-Based Exercise Enhances Health-Related Quality of Life in Persons With Spinal Cord Injury: A Randomized Controlled Trial.

OBJECTIVE: To assess the influence of a home-based exercise intervention on indices of health-related quality of life (HRQOL) in persons with spinal cord injury (SCI). DESIGN: This was a randomized controlled trial (HOMEX-SCI; ISRCTN57096451). After baseline laboratory testing and a week of free-living physical activity monitoring, eligible participants were randomly assigned (2:1 allocation ratio) to a home-based moderate-intensity upper-body exercise intervention group (INT, n=13), or a lifestyle maintenance control group (CON, n=8), for 6 weeks. SETTING: Home-based with short laboratory visits immediately before and after the intervention/control period. PARTICIPANTS: Inactive participants (N=21) with chronic (>1yr) SCI (injury level

A community-based physical activity intervention to prevent mobility-related disability for retired older people (REtirement in ACTion (REACT)): study protocol for a randomised controlled trial.

BACKGROUND: The REtirement in ACTion (REACT) study is a multi-centre, pragmatic, two-arm, parallel-group randomised controlled trial (RCT) with an internal pilot phase. It aims to test the effectiveness and cost-effectiveness of a community, group-based physical activity intervention for reducing, or reversing, the progression of functional limitations in older people who are at high risk of mobility-related disability. METHODS/DESIGN: A sample of 768 sedentary, community-dwelling, older people aged 65 years and over with functional limitations, but who are still ambulatory (scores between 4 and 9 out of 12 in the Short Physical Performance Battery test (SPPB)) will be randomised to receive either the REACT intervention, delivered over a period of 12 months by trained facilitators, or a minimal control intervention. The REACT study incorporates comprehensive process and economic evaluation and a nested sub-study which will test the hypothesis that the REACT intervention will slow the rate of brain atrophy and of decline in cognitive function assessed using magnetic resonance imaging (MRI). Outcome data will be collected at baseline, 6, 12 and 24 months for the main study, with MRI sub-study data collected at baseline, 6 and 12 months. The primary outcome analysis (SPPB score at 24 months) will be undertaken blinded to group allocation. Primary comparative analyses will be on an intention-to-treat (ITT) basis with due emphasis placed on confidence intervals. DISCUSSION: REACT represents the first large-scale, pragmatic, community-based trial in the UK to target the non-disabled but high-risk segment of the older population with an intervention to reduce mobility-related disability. A programme that can successfully engage this population in sufficient activity to improve strength, aerobic capacity, coordination and balance would have a major impact on sustaining health and independence. REACT is also the first study of its kind to conduct a full economic and comprehensive process evaluation alongside the RCT. If effective and cost-effective, the REACT intervention has strong potential to be implemented widely in the UK and elsewhere. TRIAL REGISTRATION: ISRCTN, ID: ISRCTN45627165 . Retrospectively registered on 13 June 2016. Trial sponsor: University of Bath. Protocol Version 1.5.

Impact of anatomical placement of an accelerometer on prediction of physical activity energy expenditure in lower-limb amputees.

PURPOSE: To assess the influence of the anatomical placement of a tri-axial accelerometer on the prediction of physical activity energy expenditure (PAEE) in traumatic lower-limb amputees during walking and to develop valid population-specific prediction algorithms. METHODS: Thirty participants, consisting of unilateral (n = 10), and bilateral (n = 10) amputees, and non-injured controls (n = 10) volunteered to complete eight activities; resting in a supine position, walking on a flat (0.48, 0.67, 0.89, 1.12, 1.34 m.s-1) and an inclined (3 and 5% gradient at 0.89 m.s-1) treadmill. During each task, expired gases were collected and an Actigraph GT3X+ accelerometer was worn on the right hip, left hip and lumbar spine. Linear regression analyses were conducted between outputs from each accelerometer site and criterion PAEE (indirect calorimetry). Mean bias ± 95% limits of agreement were calculated. Additional covariates were incorporated to assess whether they improved the prediction accuracy of regression models. Subsequent mean absolute error statistics were calculated for the derived models at all sites using a leave-one out cross-validation analysis. RESULTS: Predicted PAEE at each anatomical location was significantly (P< 0.01) correlated with criterion PAEE (P<0.01). Wearing the GT3X+ on the shortest residual limb demonstrates the strongest correlation (unilateral; r = 0.86, bilateral; r = 0.94), smallest ±95% limits of agreement (unilateral; ±2.15, bilateral ±1.99 kcal·min-1) and least absolute percentage error (unilateral; 22±17%, bilateral 17±14%) to criterion PAEE. CONCLUSIONS: We have developed accurate PAEE population specific prediction models in lower-limb amputees using an ActiGraph GT3X+ accelerometer. Of the 3 anatomical locations considered, wearing the accelerometer on the side of the shortest residual limb provides the most accurate prediction of PAEE with the least error in unilateral and bilateral traumatic lower-limb amputees.

Validity and reliability of a novel 3D scanner for assessment of the shape and volume of amputees' residual limb models.

BACKGROUND: Objective assessment methods to monitor residual limb volume following lower-limb amputation are required to enhance practitioner-led prosthetic fitting. Computer aided systems, including 3D scanners, present numerous advantages and the recent Artec Eva scanner, based on laser free technology, could potentially be an effective solution for monitoring residual limb volumes. PURPOSE: The aim of this study was to assess the validity and reliability of the Artec Eva scanner (practical measurement) against a high precision laser 3D scanner (criterion measurement) for the determination of residual limb model shape and volume. METHODS: Three observers completed three repeat assessments of ten residual limb models, using both the scanners. Validity of the Artec Eva scanner was assessed (mean percentage error <2%) and Bland-Altman statistics were adopted to assess the agreement between the two scanners. Intra and inter-rater reliability (repeatability coefficient <5%) of the Artec Eva scanner was calculated for measuring indices of residual limb model volume and shape (i.e. residual limb cross sectional areas and perimeters). RESULTS: Residual limb model volumes ranged from 885 to 4399 ml. Mean percentage error of the Artec Eva scanner (validity) was 1.4% of the criterion volumes. Correlation coefficients between the Artec Eva and the Romer determined variables were higher than 0.9. Volume intra-rater and inter-rater reliability coefficients were 0.5% and 0.7%, respectively. Shape percentage maximal error was 2% at the distal end of the residual limb, with intra-rater reliability coefficients presenting the lowest errors (0.2%), both for cross sectional areas and perimeters of the residual limb models. CONCLUSION: The Artec Eva scanner is a valid and reliable method for assessing residual limb model shapes and volumes. While the method needs to be tested on human residual limbs and the results compared with the current system used in clinical practice, it has the potential to quantify shape and volume fluctuations with greater resolution.

Measurement of Physical Activity and Energy Expenditure in Wheelchair Users: Methods, Considerations and Future Directions.

Accurately measuring physical activity and energy expenditure in persons with chronic physical disabilities who use wheelchairs is a considerable and ongoing challenge. Quantifying various free-living lifestyle behaviours in this group is at present restricted by our understanding of appropriate measurement tools and analytical techniques. This review provides a detailed evaluation of the currently available measurement tools used to predict physical activity and energy expenditure in persons who use wheelchairs. It also outlines numerous considerations specific to this population and suggests suitable future directions for the field. Of the existing three self-report methods utilised in this population, the 3-day Physical Activity Recall Assessment for People with Spinal Cord Injury (PARA-SCI) telephone interview demonstrates the best reliability and validity. However, the complexity of interview administration and potential for recall bias are notable limitations. Objective measurement tools, which overcome such considerations, have been validated using controlled laboratory protocols. These have consistently demonstrated the arm or wrist as the most suitable anatomical location to wear accelerometers. Yet, more complex data analysis methodologies may be necessary to further improve energy expenditure prediction for more intricate movements or behaviours. Multi-sensor devices that incorporate physiological signals and acceleration have recently been adapted for persons who use wheelchairs. Population specific algorithms offer considerable improvements in energy expenditure prediction accuracy. This review highlights the progress in the field and aims to encourage the wider scientific community to develop innovative solutions to accurately quantify physical activity in this population.

Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

PURPOSE: To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE) in manual wheelchair users (MWUs). METHODS: Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg) completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1) and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. GT3X+ and GENEActiv accelerometers were worn on the right wrist (W) and upper arm (UA). Linear regression analysis was conducted between outputs from each accelerometer and criterion PAEE, measured using indirect calorimetry. Subsequent error statistics were calculated for the derived regression equations for all four device/location combinations, using a leave-one-out cross-validation analysis. RESULTS: Accelerometer outputs at each anatomical location were significantly (p < .01) associated with PAEE (GT3X+-UA; r = 0.68 and GT3X+-W; r = 0.82. GENEActiv-UA; r = 0.87 and GENEActiv-W; r = 0.88). Mean ± SD PAEE estimation errors for all activities combined were 15 ± 45%, 14 ± 50%, 3 ± 25% and 4 ± 26% for GT3X+-UA, GT3X+-W, GENEActiv-UA and GENEActiv-W, respectively. Absolute PAEE estimation errors for devices varied, 19 to 66% for GT3X+-UA, 17 to 122% for GT3X+-W, 15 to 26% for GENEActiv-UA and from 17.0 to 32% for the GENEActiv-W. CONCLUSION: The results indicate that the GENEActiv device worn on either the upper arm or wrist provides the most valid prediction of PAEE in MWUs. Variation in error statistics between the two devices is a result of inherent differences in internal components, on-board filtering processes and outputs of each device.

Predicting physical activity energy expenditure in manual wheelchair users.

PURPOSE: This study aimed to assess the influence of anatomical placement of an accelerometer on physical activity energy expenditure prediction in manual wheelchair users. METHODS: Ten accelerometer units (ActiGraph GT3X+) were attached to a multiaxis shaker table and subjected to a sinusoidal oscillation procedure to assess mechanical validity and reliability. Fifteen manual wheelchair users (mean ± SD: age, 36 ± 11 yr; body mass, 70 ± 12 kg) then completed five activities, including desk work and wheelchair propulsion (2, 4, 6, and 8 km·h). Expired gases were collected throughout. GT3X+ accelerometers were worn on the right wrist, upper arm, and waist. The relations between physical activity counts and metabolic rate were subsequently assessed, and bias ± 95% limits of agreement was calculated. RESULTS: During mechanical testing, coefficients of variation ranged from 0.2% to 4.7% (intraunit) and 0.9% to 5.2% (interunit) in all axes. During human exercise testing, physical activity counts at each anatomical location was significantly (P < 0.01) correlated with metabolic rate (wrist, r = 0.93; upper arm, r = 0.87; waist, r = 0.73). The SEE for each correlation were 3.34, 4.38, and 6.07 kJ·min for the wrist, upper arm, and waist, respectively. The absolute bias ± 95% limits of agreement values were 0.0 ± 6.5 kJ·min, 0.0 ± 8.5 kJ·min, and 0.0 ± 11.8 kJ·min for the wrist, upper arm, and waist, respectively. CONCLUSIONS: The ActiGraph GT3X+ is a reliable tool for determining mechanical movements within the physiological range of human movement. Of the three anatomical locations considered, a wrist-mounted accelerometer explains more of the variance and results in the lowest random error when predicting physical activity energy expenditure in manual wheelchair users.

Can RSScan footscan(®) D3D™ software predict injury in a military population following plantar pressure assessment? A prospective cohort study.

BACKGROUND: Injury in initial military training is common with incidences from 25 to 65% of recruits sustaining musculoskeletal injury. Risk factors for injury include extrinsic factors such as rapid onset of high volume training, but intrinsic factors such as lower limb biomechanics and foot type. Prediction of injury would allow more effective training delivery, reduce manpower wastage and improve duty of care to individuals by addressing potential interventions. Plantar pressure interpretation of footfall has been shown to reflect biomechanical intrinsic abnormality although no quantifiable method of risk stratification exists. OBJECTIVE: To identify if pressure plate assessment of walking gait is predictive of injury in a military population. METHOD: 200 male subjects commencing Naval Officer training were assessed by plantar pressure plate recording, of foot contact pressures. A software interpretation, D3D™, stratified the interpretation to measure 4 specific areas of potential correction. Participants were graded as to high, medium and low risk of injury and subsequently followed up for injury through their basic training. RESULTS: Seventy two percent of all injuries were attributed to subjects in the high and medium risk of injury as defined by the risk categorization. 47% of all injuries were sustained in the high-risk group. Participants categorized in the high-risk group for injury were significantly more likely to sustain injury than in medium or low groups (p<0.001, OR 5.28 with 95% CI 2.88, 9.70). CONCLUSIONS: Plantar pressure assessment of risk for overuse lower limb injury can be predictive of sustaining an overuse injury in a controlled training environment.

Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort.

This study developed a multivariate model to predict free-living energy expenditure (EE) in independent military cohorts. Two hundred and eighty-eight individuals (20.6 ± 3.9 years, 67.9 ± 12.0 kg, 1.71 ± 0.10 m) from 10 cohorts wore accelerometers during observation periods of 7 or 10 days. Accelerometer counts (PAC) were recorded at 1-minute epochs. Total energy expenditure (TEE) and physical activity energy expenditure (PAEE) were derived using the doubly labelled water technique. Data were reduced to n = 155 based on wear-time. Associations between PAC and EE were assessed using allometric modelling. Models were derived using multiple log-linear regression analysis and gender differences assessed using analysis of covariance. In all models PAC, height and body mass were related to TEE (P < 0.01). For models predicting TEE (r (2) = 0.65, SE = 462 kcal · d(-1) (13.0%)), PAC explained 4% of the variance. For models predicting PAEE (r (2) = 0.41, SE = 490 kcal · d(-1) (32.0%)), PAC accounted for 6% of the variance. Accelerometry increases the accuracy of EE estimation in military populations. However, the unique nature of military life means accurate prediction of individual free-living EE is highly dependent on anthropometric measurements.

An investigation of a novel three-dimensional activity monitor to predict free-living energy expenditure.

The aim of this study was to assess the capability of the 3dNX accelerometer to predict energy expenditure in two separate, free-living cohorts. Twenty-three adolescents and 14 young adults took a single dose of doubly labelled water and wore a 3dNX activity monitor during waking hours for a 10-day period while carrying out their normal routines. Multiple linear regression with backward elimination was used to establish the strength of the associations between various indices of energy expenditure, physical activity counts, and anthropometric variables. 3dNX output accounted for 27% and 35% of the variance in the total energy expenditure of the adolescent and young adult cohort, respectively. The explained variance increased to 78%, with a standard error of estimate of 7%, when 3dNX output was combined with body composition variables. The 3dNX accelerometer can be used to predict free-living daily energy expenditure with a standard error of estimate of 1.65 MJ in adolescents and 1.52 MJ in young adults. The inclusion of anthropometric variables reduces the error to approximately 1 MJ. Although it remains to cross-validate these models in other populations, early indications suggest that the 3dNX provides a useful method of predicting energy expenditure in free-living individuals.