Implementing Physical Activity Studies During COVID-19 and Winter Storms: Lessons Learned

Patient recruitment and retention are challenging for longitudinal studies. Stay-at-home restrictions for the Galveston and Houston regions in 2020 for COVID-19 and in 2021 for the Winter Storms shut down elective healthcare activities and created additional recruitment barriers during the implementation of a 12-month study examining the physical function of older adults receiving a total knee arthroplasty. This presentation describes recruitment and retention strategies during natural disasters. Ten participants started the study during the pandemic and 6 remained through the winter storms (3 withdrew, 1 no showed). Physical activity monitors were distributed and collected through mail, patient reported outcomes were completed online or over the phone, clinician-initiated measures were only collected when clinics were open, and efforts were made to minimize staff burden and follow evolving hospital guidelines. Most importantly, regular communication and follow-up with participants, research team, and department personnel created a sense of community.

Active With Whom? Examining the Social Context of Physical Activity in Individuals After Stroke and Their Partners

Engaging in regular moderate-to-vigorous intensity physical activity (MVPA) is crucial to reduce future health risk for individuals living with the effects of a stroke and their partners. Although numerous studies point to the importance of social factors in physical activity engagement, little is known about with whom individuals after stroke and their partners engage in physical activity with and whether different physical activity companions are uniquely associated with MVPA. Eighty-nine community-dwelling individuals after stroke (Mage = 68.64, SD = 10.44; 74% male) and 83 partners (Mage = 66.04, SD = 9.91; 24% male) completed 14 consecutive days of daily life assessments that included wearing physical activity monitors (accelerometers) and self-reporting physical activity companions (n = 1,961 days). Results show that average levels of MVPA were correlated between partners (r = 0.38), as were day-to-day MVPA fluctuations (r = 0.34). Importantly, for individuals after stroke, being active with their partner, but not with any other physical activity companion, was linked with elevated daily MVPA. In contrast, for partners of individuals after stroke, engaging in physical activity with a variety of different companions (partner, other family member, friend, colleague) was each associated with higher MVPA in daily life. For both individuals after stroke and their partners being active by oneself (without a companion) on a given day was not associated with elevated MVPA. Findings suggest that interventions that promote physical activity engagement should consider the role of meaningful others, with the partner being particularly key for individuals living with chronic health conditions.

Reliability, Validity and Responsiveness of Physical Activity Monitors in Patients with Inflammatory Myopathy

Objective Idiopathic inflammatory myopathies (IIM) cause proximal muscle weakness, which affect activities of daily living. Wearable physical activity monitors (PAMs) objectively assess continuous activity with potential clinical usefulness in IIM assessment. We examined the psychometric characteristics for PAM outcomes in IIM. Methods Adult IIM patients were prospectively evaluated (baseline, 3 and 6-months) in an observational study. A waist-worn PAM (ActiGraph GT3X-BT) assessed average step counts/min, peak 1-min cadence, and vector magnitude/min. Validated myositis core set measures (CSM) including manual muscle testing (MMT), physician global disease activity (MD global), patient global disease activity (Pt global), extra-muscular disease activity (Ex-muscular global), HAQ-DI, muscle enzymes, and patient-reported physical function were evaluated. Test-retest reliability, construct validity, and responsiveness were determined for PAM measures and CSM using Pearson correlations and other appropriate analyses. Results 50 adult IIM patients enrolled [mean (SD) age, 53.6 (±14.6); 60% female, 94% Caucasian]. PAM measures showed strong test-retest reliability, moderate-to-strong correlations at baseline with MD global (r=-0.37- -0.48), Pt-global (r=-0.43- -0.61), HAQ-DI (r=-0.47- -0.59) and MMT (r = 0.37–0.52), and strong discriminant validity for categorical MMT and HAQ-DI. Longitudinal association with MD global (r=-0.38- -0.44), MMT (r = 0.50–0.57), HAQ-DI (r=-0.45- -0.55), and functional tests (r = 0.30–0.65) were moderate-to-strong. PAM measures were responsive to MMT improvement (≥10%) and moderate-to-major improvement on ACR/EULAR myositis response criteria. Peak 1-min cadence had the largest effect size and Standardized Response Means (SRMs). Conclusion PAM measures showed promising construct validity, reliability, and longitudinal responsiveness; especially peak 1-min cadence. PAMs provide valid outcome measures for future use in IIM clinical trials.

Step-Counting Validity of Wrist-Worn Activity Monitors During Activities With Fixed Upper Extremities

Little is known about validity of wrist-worn physical activity monitors during activities when an arm-swing is not present. The purpose of this study was to compare the step-counting validity of wrist-worn activity monitors (Fitbit Charge HR Series 2, ActiGraph GT9X Link, Apple Watch Series 4) during functional physical activities with fixed upper extremities. Tasks included treadmill walking at 3 mph and five free-living tasks (walking with a baby doll on the left hip and the right hip, holding groceries, and pushing a stroller while walking and while jogging). Device step counts were compared to hand-counted steps from GoPro video footage. Fitbit Charge had less error when compared to the left ActiGraph in both stroller walking and jogging, treadmill walking, and grocery walking tasks (p < .001 to .020). For grocery walking, walking with a baby on the right, and walking with a baby on the left, device percentage errors ranged from 0 (0.5%) to −7.6 (15.8%). For stroller jogging, stroller walking, and treadmill walking, device percentage errors ranged from −8.3 (7.3%) to −94.3 (17.9%). Tasks with the hands fixed to an item that also had contact with the floor (stroller and treadmill) had more error than when participants held an item that was not in contact with the floor (doll and groceries). Though wrist-worn, consumer-grade step-counting devices typically undercount steps in general, consumers should be aware that their devices may particularly undercount steps during activities with the hands fixed. This may be especially true with items in contact with the floor.

Physical Activity Monitor Accuracy for Overground Walking and Free-Living Conditions Among Pregnant Women

Purpose: We aimed to determine the step-count validity of commonly used physical activity monitors for pregnancy overground walking and during free-living conditions. Methods: Participants (n = 39, 12–38 weeks gestational age) completed six 100-step overground walking trials (three self-selected “normal pace”, three “brisk pace”) while wearing five physical activity monitors: Omron HJ-720 (OM), New Lifestyles 2000 (NL), Fitbit Flex (FF), ActiGraph Link (AG), and Modus StepWatch (SW). For each walking trial, monitor-recorded steps and criterion-measured steps were assessed. Participants also wore all activity monitors for an extended free-living period (72 hours), with the SW used as the criterion device. Mean absolute percent error (MAPE) was calculated for overground walking and free-living protocols and compared across monitors. Results: For overground walking, the OM, NL, and SW performed well (<5% MAPE) for normal and brisk pace walking trials, and also when trials were analyzed by actual speeds. The AG and FF had significantly greater MAPE for overground walking trials (11.9–14.7%). Trimester did affect device accuracy to some degree for the AG, FF, and SW, with error being lower in the third trimester compared to the second. For the free-living period, the OM, NL, AG, and FF significantly underestimated (>32% MAPE) actual steps taken per day as measured by the criterion SW (M [SD] = 9,350 [3,910]). MAPE for the OM was particularly high (45.3%). Conclusion: The OM, NL, and SW monitors are valid measures for overground step-counting during pregnancy walking. However, the OM and NL significantly underestimate steps by second and third trimester pregnant women in free-living conditions.

Effect of Short Term Weight Loss on Appetite and Satiety Hormones in Overweight Female Adults

Objectives The objective of this study was to test if short term weight loss has an effect on appetite and satiety hormones in a group of overweight female adults. It was hypothesized that participants who lost weight over a short period show changes in Ghrelin and Leptin. Methods Twelve healthy overweight female adults participating in a weight management program volunteered to wear physical activity monitors (FitBit Blaze), and log food intake over a period of 24 hours on the days when whole blood was drawn to measure plasma hormone concentrations. Energy deficit was determined through subtracting calories expended from the calories consumed. This causal-comparative study identified 7 women (Group 1) who lost at least 1% of their body mass in two weeks and compared their results to 5 women (Group 2) who did not. Hormone Group 1 Group 2 Groups Total Groups Total Week 1 Week 3 Week 1 Week 3 Week 1 Week 3 P-values Ghrelin (pg/ml) 50.12 (49.96) 21. 79 (12.89) 149.07 (82.20) 79.21 (93.23) 91.35 (80.09) 45.72 (64.23) 0.017 Leptin (ng/mL) 10.08 (5.74) 9.12 (5.26) 7.56 (6.37) 7.73 (5.60) 9.03 (5.87) 8.54 (5.19) 0.481 Results Mean (SD) body mass for Group 1 decreased significantly (P &lt; 0.001)) from 85.80 (19.16) to 84.80 (19.21) kg, whereas Group 2 did not show significant change (68.62 + 5.42 vs. 68.70 + 5.46 kg). Mean (SD) energy deficits during the study period did not differ significantly between the groups. However there was a decreasing trend (P = 0.075) in Group 2 which had a 55 calories deficit in week 1 vs. 522 calories in week 3. Means (SD) hormone levels for each group by week (1 vs. 3) are given below. Ghrelin and Leptin levels did not differ between the weeks in each of the groups. However when groups were combined, significant differences in Ghrelin were observed between the weeks (P = 0.017). Similar findings were not observed for Leptin (P 0.481). Correlational analysis showed a significant moderate relationship (r = 0.655) between Ghrelin levels and Energy Deficit at the first week of the study. However this relationship was not significant in the Week 3. Conclusions There were significant associations between plasma Ghrelin levels and Energy Deficits during the beginning of the study, however, these relationships diminished over time. These findings need further research. Funding Sources The study was supported by the UCM Professional Enhancement Grant.

Use of consumer monitors for estimating energy expenditure in youth

The purpose of this study was to compare energy expenditure (EE) estimates from 5 consumer physical activity monitors (PAMs) to indirect calorimetry in a sample of youth. Eighty-nine youth (mean (SD); age, 12.3 (3.4) years; 50% female) performed 16 semi-structured activities. Activities were performed in duplicate across 2 visits. Participants wore a Cosmed K4b2(criterion for EE), an Apple Watch 2 (left wrist), Mymo Tracker (right hip), and Misfit Shine 2 devices (right hip; right shoe). Participants were randomized to wear a Samsung Gear Fit 2 or a Fitbit Charge 2 on the right wrist. Oxygen consumption was converted to EE by subtracting estimated basal EE (Schofield’s equation) from the measured gross EE. EE from each visit was summed across the 2 visit days for comparison with the total EE recorded from the PAMs. All consumer PAMs estimated gross EE, except for the Apple Watch 2 (net Active EE). Paired t tests were used to assess differences between estimated (PAM) and measured (K4b2) EE. Mean absolute percent error (MAPE) was used to assess individual-level error. The Mymo Tracker was not significantly different from measured EE and was within 15.9 kcal of measured kilocalories (p = 0.764). Mean percent errors ranged from 3.5% (Mymo Tracker) to 48.2% (Apple Watch 2). MAPE ranged from 16.8% (Misfit Shine 2 – right hip) to 49.9% (Mymo Tracker).Novelty Only the Mymo Tracker was not significantly different from measured EE but had the greatest individual error. The Misfit Shine 2 – right hip had the lowest individual error. Caution is warranted when using consumer PAMs in youth for tracking EE.

Criterion validity for step counting in four consumer-grade physical activity monitors among older adults with and without rollators

Background Few studies have investigated the measurement properties of consumer-grade physical activity monitors (PAMs) in older adults. Therefore, we investigated the criterion validity of consumer-grade PAMs in older adults and whether the measurement properties differed between older adults with and without rollators and whether worn on the hip or at the wrist. Methods Consumer-grade PAMs were eligible for inclusion in this study if they: 1) could be fastened at the hip as well as on the wrist, 2) were simple in function and design and thus easy to use for participants with minimal technical skills, 3) included step-counting as outcome measure and 4) were powered by a button cell battery. Participants performed self-paced walking for six minutes while two physiotherapists counted their steps with a click-counter. The average of the two counts was used as criterion. The participants wore 16 monitors, four located bilaterally on both hips and wrists. Our prior expectation was that all monitors would have at least moderate criterion validity for all participants, good criterion validity for participants walking without a rollator and poor criterion validity for participants walking with a rollator. Results Four physical activity monitors were included in this study; Misfit Shine, Nokia GO, Jawbone UP Move and Garmin Vivofit 3. A total of 103 older adults participated. Nokia GO was excluded from this study due to technical issues. Therefore, we present results on the frequency of data loss, ICC (1, 2) and percentage measurement error for Misfit Shine, Garmin Vivofit 3 and Jawbone UP Move located on four different positions. Conclusions The hip-worn PAMs did not differ significantly in terms of measurement error or criterion validity. Wrist-worn monitors cannot adequately measure number of steps in a population of older adults using rollators. The hip-worn PAMs were superior to wrist-worn PAMs among older adults with and without rollators.