Average Step Count Research Articles

The Role of Body Mass Index on Physical Activity, Symptoms, and Related Outcomes Following Pediatric Concussion

To determine the step count and self-reported activity levels for obese and non-obese pediatric patients following concussion and predict self-reported symptoms, quality of life, and psychological health over time. Participants completed the Post-Concussion Symptom Scale (PCSS), Pediatric Quality of Life (PedsQL), and Behavioral Symptom Inventory-18 (BSI-18) at an initial visit (<72 hours), 3-5 days post-injury, 10-18 days post-injury, and 1 and 2 months post-injury. Physical activity data (eg, step count) were collected via a commercial actigraph. Participants were categorized into obese and non-obese body mass index (BMI) groups based on age- and sex-adjusted growth standards. Mann Whitney U tests compared groups while nonparametric series regression models examined the effect of obese BMI and average daily step count on PCSS, PedsQL, and BSI-18 outcomes at 1- and 2-months post-injury. 194 participants were included: 153 (78.9%; M=14.6 ± 2.4 years; 50% female) in the non-obese group and 41 (21.1%; M=14.2 ± 2.0 years; 44% female) in the obese group. The obese group had a 22.8% lower average daily step count in the week post-injury (p=0.02). At 2-months, there was a significant association between obese BMI and worse PCSS total score (p=0.042), PedsQL (p=0.017), and BSI-18 anxiety (p=0.046). Average daily step count in the first week post-injury was associated with a higher PCSS total score at 2 months (p=0.031). Pediatric patients following concussion with an obese BMI had a lower daily average step count in the week after injury and exhibited worse concussion symptoms, quality of life, and anxiety at 2 months compared with those with a non-obese BMI.

Increasing step count of employees through the Semmelweis Workplace Health Promotion Program

Abstract Background Lifestyle greatly contributes to the development of age-related diseases. The goal of the Semmelweis University’s ‘Semmelweis Workplace Health Promotion Program’ is to develop interventions that facilitate healthy ageing. The aim of its first intervention was to increase the step count of participants by incorporating motivational elements offered through the university’s Center of Preventive Services. Methods A randomized controlled trial was conducted in spring 2024 with three study groups: those undergoing motivational interviews (MI, n = 49), those receiving motivational emails (ME, n = 51), and a control group (n = 53). Intervention groups (MI+ME) received weekly emails for 8 weeks emphasizing the benefits of increased step count and providing feedback on achievements. The MI group also took part in 4 biweekly consultations. Mean step counts of last week and energy expended while walking (MET) calculated from the International Physical Activity Questionnaire were recorded five and three times, respectively. Mixed model regressions were conducted for two pre-planned comparisons: MI+ME vs. controls, and MI vs. ME. Results Intervention groups exhibited a significant increase in average step count (1001 steps; 95% Confidence Interval [95% CI]: 349-1651) as a result of the program, while the control group experienced a non-significant decrease. This was accompanied by a significant increase in energy expenditure for walking (45 MET; 95% CI: 4-87) in intervention groups and a non-significant decrease for the control group. The study found no significant differences in step count and energy expenditure between the two intervention groups (MI vs. ME). Conclusions Our results suggest that workplace health promotion programs may effectively increase physical activity, and thus may be key in tackling the challenges posed by aging demographics. Preliminary findings did not indicate a superiority between email-based and motivational interview-based motivation. Key messages • Workplace health promotion is an essential tool in promoting healthy aging among the working-age population. • Step-count programs based on motivational interviewing serve as an effective and simple tool in increasing physical activity.

Comparison of step-count outcomes across seven different activity trackers: a free-living experiment with young and older adults

BackgroundThere are now many different types of activity trackers, including pedometers and accelerometers, to estimate step counts per day. Previous research has extensively examined step-count measurements using activity trackers across various settings while simultaneously wearing different devices.; however, older adults frequently display distinct walking patterns and gait speeds compared to younger adults. This study aimed to compare the step-count between older and younger adults by having them simultaneously wear seven different activity trackers in free-living experiments.MethodsThis study included 35 younger adults (21–43 yrs) and 57 physically independent older adults (65–91 yrs). All participants simultaneously wore one pedometer and six activity trackers: ActiGraph GT3X + Wrist and Hip, Omron Active Style Pro HJA-350IT, Panasonic Actimarker, TANITA EZ-064, Yamasa TH-300, and Yamasa AS-200 for seven days. A regression equation was also used to assess inter-device compatibility.ResultsWhen comparing wrist-worn ActiGraph to the six hip-worn activity trackers, the wrist-worn ActiGraph consistently recorded step counts over 4,000 steps higher than hip-worn activity trackers in both groups (range, 3000–5000 steps). Moreover, when comparing the ActiGraph worn on the wrist to that worn on the hip, the proportion was higher among older adults compared to younger ones (younger: 131%, older: 180%). The Actimarker recorded the highest average step counts among six hip-worn devices, with 8,569 ± 4,881 overall, 9,624 ± 5,177 for younger adults, and 7,890 ± 4,562 for older adults. The difference between the hip-worn ActiGraph and Active Style Pro was just about 70 steps/day overall. The correlation among all devices demonstrated a very high consistency, except for the wrist-worn ActiGraph (r = 0.874–0.978).ConclusionsStep counts recorded from seven selected consumer-based and research-grade activity trackers and one pedometer, except for the wrist-worn ActiGraph. showed a variation of approximately 1700 steps (range, 1265–2275 steps) steps for both groups, yet maintained a high correlation with each other. These findings will be valuable for researchers and clinicians as they compare step counts across different studies or representative surveys conducted globally.

Association of Daily Step Count and Postoperative Complication among All of Us Research Participants.

The association between preoperative wearable device step counts and surgical outcomes has not been examined using commercial devices linked to electronic health records (EHR). This study measured the association between daily preoperative step counts and postoperative complications. Data was obtained using the All of Us (AOU) Research program, a nationwide initiative to collect EHR and health-related data from the population. Included were patients who underwent a surgical procedure included in the National Surgical Quality Improvement Program (NSQIP) targeted procedures dataset. Excluded were patients who did not have available physical activity FitBit data. Primary outcome was the development of a postoperative complication. All analyses were performed in the AOU researcher workbench. Of 27,150 patients who underwent a surgical procedure, 475 participants with preoperative wearable data were included. 74.7% were female and 85.2% were White. The average age was 57.2 years. The overall rate of postoperative complications was 12.6%. Patients averaging fewer than 7,500 daily steps were at increased odds for developing a postoperative complication (OR 1.83, 95% CI [1.01, 3.31]). Following adjustment for age, sex, race, comorbid disease, body mass index (BMI), and relative procedure risk, patients with a baseline average steps/day < 7,500 were at increased odds for postoperative complication (aOR = 2.06, 95% CI [1.05, 4.06]). This study found an increase in overall postoperative complication rate in patients recording lower average preoperative step counts. Patients with a baseline of less than 7,500 steps per day had increased odds of postoperative complications in this cohort. This data supports the use of wearable devices for surgical risk stratification and suggests step count may measure preoperative fitness.

Continuous remote monitoring of performance status in patients with NSCLC through fitness tracker–derived life-log data.

1568 Background: Traditional methods for assessing the performance status of cancer patients often rely on clinical evaluations and patient-reported histories. This study utilizes life-log data derived from fitness trackers (FTs) in patients with non-small cell lung cancer (NSCLC) to offer a comprehensive and dynamic perspective on performance status throughout their treatment. Methods: Patients with NSCLC scheduled for a minimum of 12 weeks of treatment were enrolled. Custom software facilitated the remote collection of life-log data from participants' FTs (Fitbit Inspire 3), encompassing step count, calories burned, heart rate, sleep patterns, etc. Quality of life surveys assessing patient-reported outcomes (PROs) were completed during regular visits (every 3 weeks) and unscheduled visits (USV), in addition to collecting clinical data such as laboratory parameters and body composition metrics. An end-of-monitoring survey assessed participants' familiarity with this monitoring approach. The study aimed to correlate FT data with clinical parameters and identify patterns predictive of treatment related USVs. Results: Of the 98 enrolled patients, 69 patients (70.4%) completed the 12-week follow-up. The cohort predominantly consisted of older adults (≥65 years) (55.1%) and patients in palliative care (75.5%), with most undergoing cytotoxic chemotherapy (66.3%) and some receiving oral agents (20%). FT-based remote monitoring revealed that older patients had a comparable 12-week completion rate to younger patients. (69.2% vs. 76.2%, P=0.604). Analysis of life-log data from three days before a visit (D-3) to the visit day (D0) showed significant reductions in average step counts ( P=0.022) and walking distance ( P=0.021) for USVs compared to regular visits, while resting heart rate (HR) showed a significant increase for USVs ( P=0.049). PRO-based PROMIS physical function scores and EQ-5D-3L scores showed a significant correlation with both D-3 to D0 acquired resting HR ( P&lt;0.001, P=0.002) and average step counts ( P=0.011, P=0.013), respectively. End of monitoring survey was done from 72 participants indicating high satisfaction and familiarity with the FT-based remote monitoring system, median score of 90 out of 100. Conclusions: FT-derived life-log data effectively captured dynamic performance status in NSCLC patients, correlating with clinical outcomes and PRO. These findings support further research into FT data's predictive value for clinical interventions, underscoring its potential in personalized remote patient management.

Associations of between- and within-day patterns of physical activity accumulation with arterial stiffness and indices of microvascular health-Evidence from The Maastricht study.

While physical activity (PA) is understood to promote vascular health, little is known about whether the daily and weekly patterns of PA accumulation associate with vascular health. Accelerometer-derived (activPAL3) 6- or 7-day stepping was analyzed for 6430 participants in The Maastricht Study (50.4% women; 22.4% Type 2 diabetes mellitus (T2DM)). Multivariable regression models examined associations between stepping metrics (average step count, and time spent slower and faster paced stepping) with arterial stiffness (measured as carotid-femoral pulse wave velocity (cfPWV)), and several indices of microvascular health (heat-induced skin hyperemia, retinal vessel reactivity and diameter), adjusting for confounders and moderators. PA pattern metrics were added to the regression models to identify associations with vascular health beyond that of stepping metrics. Analyses were stratified by T2DM status if an interaction effect was present. Average step count and time spent faster paced stepping was associated with better vascular health, and the association was stronger in those with compared to those without T2DM. In fully adjusted models a higher step count inter-daily stability was associated with a higher (worse) cfPWV in those without T2DM (std β = 0.04, p = 0.007) and retinal venular diameter in the whole cohort (std β = 0.07, p = 0.002). A higher within-day variability in faster paced stepping was associated with a lower (worse) heat-induced skin hyperemia in those with T2DM (std β = -0.31, p = 0.008). Above and beyond PA volume, the daily and weekly patterns in which PA was accumulated were additionally associated with improved macro- and microvascular health, which may have implications for the prevention of vascular disease.

Agreement between the activPAL accelerometer and direct observation during a series of gait and sit-to-stand tasks in people living with cervical dystonia.

Accelerometers are commonly used for the assessment of PA; however, these devices have not been validated in people with dystonia who experience movement limitations. To properly understand movement behaviors and deliver accurate exercise prescription in this population, the validity of these devices must be tested. This study aimed to validate step count and postural transitions detected by the activPAL accelerometer (AP) against direct observation (DO) during two functional assessments: the 30-s sit-to-stand (30STS) and 6-min usual-pace walk tests. Methods: A total of 11 participants with cervical dystonia (CD) (male/female n = 5/6; mean age = 61 years; BMI = 24 kg/m2) performed the 6-min usual pace walking and 30STS while wearing the activPAL. A trained observer counted steps and observed the number of sit-to-stands. The average step count detected with AP and DO was 651.8 (218-758) and 654.5 (287-798) respectively. The average transitions detected were 11 (4-16) and 12 (4-17) respectively. Both methods showed good agreement and there was a statistically significant and strong correlation between the two methods, i.e., transitions (r = 0.983, p = 0.0001), and step counts (r = 0.9841, p = 0.0001). There is a good agreement between activPAL and direct observation for step counts and transitions between sitting and standing in people living with CD.

Association between changes in habitual stepping activity and cognition in older adults

Advancing age is associated with declines in cognitive function. Although physical activity is thought to protect against this decline, it is unclear how a short-term uptake in daily steps or a decline in day-to-day step variability may contribute to cognition among older adults. We tested associations between changes in step counts, day-to-day step variability and executive cognitive functions among older adults taking part in a physical activity intervention. Thirty-seven older adults (33 females; 71.4 ± 6.3 years) completed a 10-week personalized physical activity intervention. Participants wore a Fitbit to measure daily step counts throughout the study. They also completed a computerized Stroop task before and after the intervention. Average step counts and step count variability via average-real-variability (ARV) were determined. Compared to pre-intervention, step counts increased (p < 0.001) and step variability decreased post-intervention (p = 0.04). Models describing the changes in step counts and ARV over the 10-weeks were cubic (both, p < 0.04). Reaction times during the simple (p = 0.002) and switching (p = 0.04) conditions were faster post-intervention. Change in step variability was positively associated with the change in reaction time for the switching condition (β = 0.029, p = 0.002). On average, a reduction in day-to-day step variability was associated with improvements in cognitive flexibility.

Physical activity and sleep changes among children during the COVID-19 pandemic

Daily routines, including in-person school and extracurricular activities, are important for maintaining healthy physical activity and sleep habits in children. The COVID-19 pandemic significantly disrupted daily routines as in-person school and activities closed to prevent spread of SARS-CoV-2. We aimed to examine and assess differences in objectively measured physical activity levels and sleep patterns from wearable sensors in children with obesity before, during, and after a period of school and extracurricular activity closures associated with the COVID-19 pandemic. We compared average step count and sleep patterns (using the Mann–Whitney U Test) before and during the pandemic-associated school closures by using data from activity tracker wristbands (Garmin VivoFit 3). Data were collected from 94 children (aged 5–17) with obesity, who were enrolled in a randomized controlled trial testing a community-based lifestyle intervention for a duration of 12-months. During the period that in-person school and extracurricular activities were closed due to the COVID-19 pandemic, children with obesity experienced objectively-measured decreases in physical activity, and sleep duration. From March 15, 2020 to March 31, 2021, corresponding with local school closures, average daily step count decreased by 1655 steps. Sleep onset and wake time were delayed by about an hour and 45 min, respectively, while sleep duration decreased by over 12 min as compared with the pre-closure period. Step counts increased with the resumption of in-person activities. These findings provide objective evidence for parents, clinicians, and public health professionals on the importance of in-person daily activities and routines on health behaviors, particularly for children with pre-existing obesity. Trial Registration: Clinical trial registration: NCT03339440

Changes in the Step Counts of University Students Living in Hokkaido during the COVID-19 Pandemic

Background. Coronavirus disease (COVID-19) countermeasures, such as lockdowns, have been reported to reduce people’s physical activity levels. Purpose. To determine changes in the step counts among university students before and after the COVID-19 pandemic and identify the risk factors for decreased step counts. Materials and Methods. An online questionnaire was sent by e-mail to 1,851 students enrolled in a university in Hokkaido, Japan; of these, 127 participated. The questionnaire items were average monthly step counts from October 2019 to March 2022, type of residence, part-time job, club activities, personal demographics, height, and weight. The average step counts in October/November 2019 (before the pandemic) were used as the baseline, and changes in step counts were studied at five time points (every 6 months): April/May 2020 (first state of emergency declared), October/November 2020 (period of contained infection), April/May 2021 (second state of emergency declared), and October/November 2021 (period of contained infection). We also examined changes in the number of steps due to different lifestyle factors and factors that contributed to decreased step counts during the study period. Results. Significantly lower step counts than those at baseline were observed in April/May 2020 and April/May 2021; however, there was no significant difference in October/November 2020 and October/November 2021 compared with baseline. In addition, significantly lower step counts were observed in April/May 2020 than in April/May 2021. The risk of decreased step counts was significantly associated with nonparticipation in club activities, even after adjustment for other variables. Conclusion. The step counts of university students decreased significantly during the declaration of a state of emergency and recovered to pre-pandemic levels after the declaration was lifted. Lifestyle status revealed differences in the number of steps taken before and after the pandemic. Nonparticipation in club activities was identified as a major risk factor for a decrease in step counts.

Association of Daily Physical Activity With Motivation in Prefrail and Frail Older Adults Living in Retirement Communities.

Older adults living in retirement communities are an understudied population, and the association between their motivation and daily physical activity is unknown. We recruited participants (n = 173) living in a retirement community who completed the Behavioral Regulation in Exercise Questionnaire-2 and wore an activPAL accelerometer to evaluate this relationship. Participants had a median age of 81years and demonstrated low levels of daily activity with an average step count of 3,637 (±1,965)steps per day and 52 (±25)min of daily stepping time. External motivation was negatively associated with the square root of daily step count (β = -4.57; p < .001) and square root of daily stepping time (β = -0.49; p < .001). Older adults living in retirement communities demonstrated low levels of daily activity, with a negative association between external motivation and daily activity. Strategies are needed to make an active lifestyle supportive and enticing for older adults in these communities.

Functional Connectivity, Physical Activity, and Behavioral Abnormality in Patients with Vascular Cognitive Impairment

Purpose of the research: Neuropsychiatric Symptoms (NPSs) can negatively impact the survival and quality of life in Vascular Cognitive Impairment (VCI) patients. Physical Activity (PA) has been shown to reduce NPSs in dementia patients, possibly by influencing synaptic plasticity. This study investigates the relationship between NPSs, Default Mode Network (DMN), and PA in patients with VCI. Methods: The study included 42 VCI patients. Functional Connectivity (FC) within the DMN and neurobehavioral performance was assessed. NPSs were categorized. The severity of Hyperactivity and Behavioral Symptoms (HBS) was quantified using a Hyperactivity and Behavioral Composite Score (HBCS). Patients’ PA levels were measured using Fitbit Charge 2. Principal results: After accounting for disease severity, increased FC between the left Posterior Cingulate Cortex (PCC) seed and the right inferior parietal gyrus was linked to more severe HBS. There was an inverse correlation between HBCS and average step counts per day (steps/d) as well as average distance per day (km/d). This suggests that higher levels of PA were associated with less severe HBS. HBCS was also inversely correlated with steps/d and km/d, reinforcing the idea that increased PA was linked to reduced symptom severity. Major conclusions: The study concludes that increased FC within the DMN is associated with more severe HBS in VCI patients. Greater levels of PA (measured by step counts and distance) were associated with a reduction in the severity of HBS. This suggests that FC within the DMN may play a role in the modulation of HBS by PA in VCI patients.

Use of Apple Watch to Acquire Baseline Wearable Biometric Data for Patients with Sickle Cell Disease and Correlations to Symptoms Such As Pain and Fatigue

Background: Sickle cell disease (SCD) is an inherited blood disorder that impacts the structure of red blood cells. The most common complication of SCD are vaso-occlusive crises (VOCs), commonly called pain crisis. Frequency and intensity of VOCs can differ among individuals. The unpredictable nature of VOCs increases risk of further complications, limits daily activities, affects mental well-being, and decreases health related quality of life. The use of mHealth and wearables for those living with SCD allows the opportunity to better understand pain and general wellbeing through real time data and analysis. Objectives: We aimed to: 1) Establish a comprehensive baseline health profile for individuals with SCD; and 2) determine potential relationships between patient reported symptoms and biometric data. Methods: Following IRB approval, patients entering the SCD clinic or the SCD Day Hospital at Duke University were approached, consented, and provided with the Nanbar Health app. Participants were instructed to make entries at least once daily and wear an Apple Watch throughout the day for 6 months. If a participant did not have Apple devices, an iOS Apple smartphone and/or Apple Watch series SE were provided. Self-reported general symptoms were recorded in the Nanbar Health app on scales from 0 (none) to 10 (most severe). General wellbeing was rated on an emoji scale, converted to 1 (worst/'frowny face') to 5 (best/'smiley face'). The biometric data from wearable collected included heart rate, step count, heart rate variability (HRV), resting heart rate (RHR), respiratory rate, and O2 saturation. For participants that had their own Apple Watch, 3 months of retroactive data was acquired. Statistical and network analysis was performed to analyze the correlations between symptoms, biometric data, and the general wellbeing of the participant. Results: Over 3 months, 18 participants were enrolled in the study. Median age of participant was 25 (IQR 21-33), 10 females, all Black/African American, and most either HgbSS (72%) or HgbSC (16%). Participants logged symptoms in the app 597 times over 93 days with a median of 0.33 entries/day/patient (IQR 0.22-0.44). The average pain score participants reported was 5.9 (SD 2.4, n=220). The three most reported symptoms, besides pain, were tiredness (22.1%), headache (5.2%), and priapism (5%). The patient-reported general feeling average was 3.3 (n=597, SD 1.6). Heart rate (n=74646), HRV (n=1277), and step count (n=1566) were the most recorded biometrics from the wearables. The average heart rate, HRV, and step count were 105.1 bpm (SD 26.8), 31.9 ms (SD 13.3), and 4100 steps/day (SD 5960), respectively. Significant expected correlations include between pain and priapism (r=0.85, p&amp;lt;0.01), aching and pain (r=0.78, p&amp;lt;0.01), and feeling bad and aching (r= -0.74, p&amp;lt;0.01). We also found feeling well correlated positively to back pain and tired correlated negatively with aching (see Table 1). Using network analysis of biometrics, RHR and HRV had a higher expected influence on patient feeling compared to the other biometrics collected. Conclusion: Baseline biometric characteristics for patients were similar to other diseases with chronic pain and as expected, pain is the most common symptom reported. Our data reflected lower HRV compared to healthy individuals and consistent with other disorders characterized by chronic pain. However, compared to other chronic pain disorders, patients with SCD appeared to have lower HRV values. There was no strong correlation (&amp;gt;0.7) between biometrics obtained by the watch and SCD patient-reported pain scores. Our study found a strong significant correlation between priapism and feeling cold. The strongest correlation was between feeling tired and feeling cold, however, tired/fatigue was also significantly correlated with priapism and feeling cold, although negatively correlated with aching. Limitations to conducting comprehensive analyses and making direct comparisons with other conditions include discrepancies in biometrics due to high variability and participant adherence. These limitations underscore the need to enroll more patients and improve patient adherence to improve the reliability of biometric data in future studies. Future efforts will compare the use of other mHealth devices besides the Apple Watch and expand to patients outside our institution.

Associations between glycemic variability, sleep quality, and daily steps in subjects without diabetes using wearable devices

BackgroundSince there are limited studies on the associations between glycemic variability (GV) and sleep quality or physical activity in subjects without diabetes, we evaluated the associations between GV, as assessed by continuous glucose monitoring (CGM), and both sleep quality and daily steps using wearable devices in healthy individuals. MethodsForty participants without diabetes were monitored by both an intermittently scanned CGM and a smartwatch-type activity tracker for 2 weeks. The standard deviation (SD) and coefficient of variation (CV) of glucose were evaluated as indices of GV. The activity tracker was used to calculate each participant's average step count per day. We also calculated sleep duration, sleep efficiency, and sleep latency based on data from the activity tracker. Spearman's correlation coefficient was used to assess the association between GV and sleep indices or daily steps. For each participant, periods were divided into quartiles according to step counts throughout the day. We compared mean parameter differences between the periods of lowest quartile and highest quartile (lower 25% and upper 25%). ResultsSD glucose was significantly positively correlated with sleep latency (R = 0.23, P < 0.05). There were no significant correlations among other indices in GV and sleep quality (P > 0.05). SD glucose and CV glucose levels in the upper 25% period of daily steps were lower than those in the lower 25% period in each participant (both, P < 0.01). ConclusionIn subjects without diabetes, GV evaluated by intermittently scanned CGM was positively associated with the time to fall asleep. Furthermore, GV in the days of larger daily steps was decreased compared to the days of smaller daily steps in each participant.

Enhancing Physical and Psychosocial Health of Older Adults in Saudi Arabia through Walking: Comparison between Supervised Group-Based and Non-Supervised Individual-Based Walking.

Walking is widely recognized as one of the most common and effective forms of physical activity, particularly for older adults. This study examined the comparative effects of two types of walking interventions, including supervised group-based intervention (SGBI) and non-supervised individual-based intervention (NSIBI), on frailty syndrome, cognitive functions or skills, and health-related quality of life among sedentary older Saudi individuals. A 15-week double-blinded, randomized controlled trial (RCT) including three groups (two were intervention groups while the other was the control group) was conducted among older adults who were inactive to examine the effect of different forms of walking interventions on frailty syndrome, cognitive functions, and health-related quality of life. A total of 107 participants, including 65 males and 42 females, were divided into three groups, which include SGBI, NSIBI, and the control group. Frailty syndrome was measured using the physical performance test (PPT), while cognitive function and health-related quality of life were assessed using the Mini-mental State Examination (MMSE) and the Short Form 36 (SF 36) health survey questionnaire. One-way repeated measures analysis of variance (ANOVA) and one-way analysis of covariance (ANCOVA) with the pre- and post-tests were performed for within- and between-group differences. while post-test data for the control group participants were absent due to the change in elderly center regulation, and they were excluded from the analysis. Hence, the comparison was stated only between the intervention groups. Both of the intervention groups (SGBI and NSIBI) showed significant within-subject differences in the Physical Function subscale of the health-related quality of life scale only, with F(1,20) = 23.03, p < 0.001, and F(1,18) = 27.22, p < 0.001, respectively. On the other hand, the Physical Performance Test revealed significant [F(2,51) = 9.21, p < 0.001] between-group differences in the post-test based on the baseline values. In addition, the average step count of older adults was increased from 4000 steps per session to around 7000 steps per session in the intervention group. The average heart rate of the NSIBI group did not show a visible change, and the resting heart rate of both groups showed a slightly declining trend throughout the intervention period. The walking intervention significantly increased participants' physical function, which is a component of health-related quality of life and physical performance (frailty level), along with average daily step counts for older adults in Saudi Arabia. Regular engagement in the recommended level of walking is strongly advisable for Saudi Arabian older adults to maintain their overall quality of life at this stage.

Applying Average Real Variability to Quantifying Day–Day Physical Activity and Sedentary Postures Variability: A Comparison With Standard Deviation

Intraindividual activity variability is often overlooked, with some existing work using SD as a variability metric. However, average real variability (ARV) may be a more suitable metric as it accounts for temporal variability. The purpose of this exploratory study was to (a) apply ARV analyses to habitual activity outcomes; (b) assess the agreement between ARV and SD for habitual step counts, standing time, and sedentary time; and (c) determine the relationship between activity variability (SD and ARV) with average activity values. One hundred and eighty-nine participants (37 ± 22 years, 109 females) wore the activPAL inclinometer on their thigh 24 hr/day for 6.4 ± 0.9 days. SD and ARV were calculated for each participant across their wear time. A Wilcoxon signed-rank test revealed that ARV was significantly higher than SD for step count, standing time, and sedentary time (all, p &lt; .001). Equivalence testing demonstrated mixed equivalence for step counts (10%), standing time (12%), and sedentary time (14%). SD and ARV were highly correlated to each other for all activity metrics (all, ρ &gt; .857, p &lt; .001). SD was moderately (ρ = .601, p &lt; .001) and weakly (ρ = .296, p &lt; .001) correlated with average step count and standing time, respectively. ARV was weakly correlated with average step count and standing time (both: ρ &lt; .499, p &lt; .001). However, average sedentary time was not associated with SD or ARV (both, p &gt; .177). While the two measurements of variability were strongly correlated, they cannot be used interchangeably. More monitoring research should consider intraindividual activity variability and use methods, such as ARV, that consider the temporal nature of day–day activity.

Data-driven physical actigraphy patterns relate to cognitive and vascular health in older adults

Health benefits of physical activity (PA) are well known; however, specific PA patterns that relate most strongly to cognitive aging outcomes are poorly understood. We characterized latent profiles of PA among older adults and examined associations with cognition and vascular burden. 124 functionally normal older adults wore a Fitbit™ for 30 days. Daily average step count, sedentary time (0 steps/min), and high-intensity time (≥120 steps/min) were calculated. Participants completed neurocognitive testing assessing cognitive domains of executive functioning and memory; medical history, from which vascular burden (i.e., a count of cardiovascular conditions) was calculated; and brain MRI (n = 44). Subgroups with similar PA patterns were identified via latent profile analysis. Three latent PA classes emerged: Class 1Low PA (n = 49), Class 2Average PA (n = 59), and Class 3High-intensity PA (n = 16). PA class related to executive functioning and vascular burden, driven by better outcomes in Class 3 than Class 1. Sex-stratified analyses revealed these associations were strongest in males. Post hoc analyses showed a positive association between high-intensity PA and white matter integrity among males. High-intensity PA related to better cognitive and vascular health, particularly among males. Findings inform physical activity-specific and person-specific recommendations for optimal cognitive aging.

A prospective study evaluating the association of patient-reported outcomes with activity level and sleep patterns in sarcoma survivors.

12085 Background: Sarcomas are a rare heterogeneous malignancy group affecting both sexes and all ages. Treatment is often intensive, resulting in long-term toxicities. Given the rarity of sarcoma, there is a paucity of data defining physical and emotional outcomes. The Cohort to Augment the Understanding of Sarcoma Survivorship Across the Lifespan (CAUSAL) was constructed at Vanderbilt University Medical Center (VUMC) to evaluate health-related outcomes. Methods: Sarcoma patients treated at VUMC from 2012 – present are enrolled into CAUSAL. Patient demographics, tumor and treatment data are abstracted from the electronic medical record. Participants complete surveys including PROMIS-57 consisting of seven domains including physical function, sleep disturbance, fatigue, and satisfaction with participation in social roles, which are reported here. Participants who have completed treatment are given a FitBit to track activity level and sleep over 12 weeks. Data are synced to an online platform, Fitabase. Body mass index (BMI) is assessed at study entry. For each participant, FitBit data were summarized using medians. To estimate the association between PROMIS-57 scores and activity and sleep data (FitBit), linear regression models were fit controlling for age, sex, and BMI of participants. Results: Of 306 CAUSAL participants who completed the PROMIS-57, 193 were post completion of sarcoma therapy. Of these, 76 also had FitBit data and are included in this analysis. Median step count was 5826 (quartiles: 3668, 7967), which was lower than average Fit Bit step count data for the US population (8170). Median daily active minutes was 252 minutes (quartiles: 174, 307). Median duration of sleep was 447 minutes (quartiles:381, 474) which was greater than the average reported by FitBit for the general US population (436 min). Step count was correlated with higher physical function score (p &lt; 0.001). A 10-point increase in physical function led to an average increase of 1291 (95% CI: 609,1973) steps when adjusting for age and sex. Compared with participants receiving treatment within 30 days prior to CAUSAL enrollment, participants not receiving treatment had 4.50 (95% CI: 1.53, 7.47) higher physical function score and 6.26 (95% CI: 1.87, 10.65) higher satisfaction in their social roles. There was no correlation between minutes of sleep recorded by FitBit and PROMIS responses. Conclusions: Using PROMIS-57, and FitBits, we demonstrated an association between higher step counts and self-reported higher physical function but did not find a correlation between FitBit recorded activity level/sleep and self-reported sleep disturbance or fatigue scores. Further, our data suggests patients with sarcoma sleep more and walk less than the general US population. As enrollment continues in CAUSAL, we will focus on PROMIS scores over time and their association with activity level and sleep.

TRACK & ACT: a pragmatic randomised controlled trial exploring the comparative effectiveness of pedometers and activity trackers for changing physical activity and sedentary behaviour in inactive individuals

BackgroundPedometers have been shown to be effective for increasing physical activity, however the potential additional effects of activity trackers, and their added capacity to simultaneously modify sedentary behaviour, has not been thoroughly explored. This study aimed to explore the comparative effectiveness of two activity trackers and a pedometer for improving daily step count and moderate-vigorous physical activity (MVPA), and reducing sedentary behaviour in inactive adults.Methods48 inactive participants were allocated to one of three groups based on their workplace. Each group randomly received either a Fitbit ONE, Jawbone UP or Digi-Walker SW200 pedometer (PED) for 8-weeks and an orientation session to their respective device. Participants were informed about the study aims and were provided with their respective devices and where applicable, the associated Apps. Participants intentionally received no other active intervention components to simulate as closely as possible the experience of purchasing a device ‘off the shelf’. Step count, MVPA and time in sedentary behaviour were measured using accelerometry (Actigraph GT3X+) at baseline and four-, eight- and 16-weeks. Analyses were conducted using linear mixed-effect regression models to compare changes from baseline. Post-hoc tests of model estimates compared each activity tracker group to the pedometer group. Model estimates are reported for baseline-16 week follow-up.ResultsAt baseline, average (standard deviation) step count, MVPA and time spent sedentary was 6557 (2111) steps/day, 23 (13) minutes/day and 10.3 (1.0) hours/day in the PED group, 7156 (1496) steps/day, 26 (12) minutes/day and 9.3 (1.2) hours/day in the ONE group and 6853 (1281) steps/day, 29 (10) minutes/day and 10.1 (1.0) hours/day in the UP group. At 16-weeks, based on estimates from the linear mixed-effect regression model, the ONE and UP groups increased step count by 129 steps/day (95% CI − 1497, 1754) and 504 steps/day more (95% CI − 1120, 2130), respectively, than the PED group. For MVPA, the ONE and UP groups increased by 2.3 min/day (95% CI − 10.9, 15.4) and 2.7 min/day more (95% CI − 10.5, 15.8), respectively, than the PED group. For sedentary behaviour, the ONE group had 34 min/day more in time spent sedentary than the PED group (95% CI − 35, 104), while the UP group had 53 min/day more in time spent sedentary than the PED group (95% CI − 18, 123).ConclusionsAll three groups demonstrated an increase in steps and MVPA, and a decrease in time spent in sedentary behaviour, however there was substantial individual variation in these outcomes indicating considerable uncertainty about the relative effectiveness of activity trackers and pedometers in improving PA and sedentary behaviour. Randomised controlled trials with adequate sample sizes are indicated.Trial registrationACTRN12623000027617 (retrospectively registered 11/1/2023).

Offloading of Diabetic Neuropathic Plantar Ulcers: Secondary Analysis of Step Activity and Ulcer Healing.

Although it is well-known that offloading devices facilitate healing in people with diabetes and neuropathic plantar ulcers, little is known about how step activity affects healing. The purposes of this study were to compare: (1) healing outcomes (time to healing, percentage of ulcers healed); (2) healing rates by ulcer location; and (3) step activity (daily step count, daily peak mean cadence) among patients using either total contact casts (TCCs) or removable cast walker boots (RCWs). The study included 55 participants (TCC, 29; RCW, 26) with diabetes mellitus, peripheral neuropathy, and a Wagner grade 1 or 2 neuropathic plantar ulcer. Each participant wore an activity monitor for 14 consecutive days. Step activity and healing variables were assessed using independent t tests, Kruskal-Wallis, Kaplan-Meier, and Mantel-Cox log-rank tests. Mean participant age was 55 (SD, 11) years. The percentage of ulcers healed was lower in the RCW group versus the TCC group (65% vs 93%). If healed, average healing rate was 77 (SD, 48) days in the TCC group and 138 (SD, 143) days in the RCW group. Survival distribution by ulcer location was different for RCW forefoot than other locations (132 ± 13 days vs 91 ± 15, 75 ± 11, and 102 ± 36 days for TCC forefoot, TCC-midfoot/hindfoot, and RCW-midfoot/hindfoot, respectively; χ2 = 10.69, P = .014). Average step count was 2,597 in the RCW group versus 1,813 steps in the TCC group (P = .07). The daily peak mean cadence for 20-, 30-, or 60-minute periods was greater with RCW use. Step activity in participants with RCWs was increased compared with those with TCCs. Because of their potential to be easily removable, RCWs may impair ulcer healing by allowing greater step activity.