Change In Step Count Research Articles

Digital intervention promoting physical activity among obese people (DIPPAO) randomised controlled trial: study protocol

IntroductionPhysical inactivity and excessive sedentary behaviours are major preventable causes in both the development and the treatment of obesity and type 2 diabetes mellitus (T2DM). Nevertheless, current programmes struggle to...

Promoting Physical Activity in a Spanish-Speaking Latina Population of Low Socioeconomic Status With Chronic Neurological Disorders: Proof-of-Concept Study.

BackgroundPhysical activity (PA) is known to improve quality of life (QoL) as well as reduce mortality and disease progression in individuals with chronic neurological disorders. However, Latina women are less likely to participate in recommended levels of PA due to common socioeconomic barriers, including limited resources and access to exercise programs. Therefore, we developed a community-based intervention with activity monitoring and behavioral coaching to target these barriers and facilitate sustained participation in an exercise program promoting PA.ObjectiveThe aim of this study was to determine the feasibility and efficacy of a community-based intervention to promote PA through self-monitoring via a Fitbit and behavioral coaching among Latina participants with chronic neurological disorders. MethodsWe conducted a proof-of-concept study among 21 Spanish-speaking Latina participants recruited from the Los Angeles County and University of Southern California (LAC+USC) neurology clinic; participants enrolled in the 16-week intervention at The Wellness Center at The Historic General Hospital in Los Angeles. Demographic data were assessed at baseline. Feasibility was defined by participant attrition and Fitbit adherence. PA promotion was determined by examining change in time spent performing moderate-to-vigorous PA (MVPA) over the 16-week period. The effect of behavioral coaching was assessed by quantifying the difference in MVPA on days when coaching occurred versus on days without coaching. Change in psychometric measures (baseline vs postintervention) and medical center visits (16 weeks preintervention vs during the intervention) were also examined.ResultsParticipants were of low socioeconomic status and acculturation. A total of 19 out of 21 (90%) participants completed the study (attrition 10%), with high Fitbit wear adherence (mean 90.31%, SD 10.12%). Time performing MVPA gradually increased by a mean of 0.16 (SD 0.23) minutes per day (P<.001), which was equivalent to an increase of approximately 18 minutes in MVPA over the course of the 16-week study period. Behavioral coaching enhanced intervention effectiveness as evidenced by a higher time spent on MVPA on days when coaching occurred via phone (37 min/day, P=.02) and in person (45.5 min/day, P=.01) relative to days without coaching (24 min/day). Participants improved their illness perception (effect size g=0.30) and self-rated QoL (effect size g=0.32). Additionally, a reduction in the number of medical center visits was observed (effect size r=0.44), and this reduction was associated with a positive change in step count during the study period (P.=04).ConclusionsSelf-monitoring with behavioral coaching is a feasible community-based intervention for PA promotion among Latina women of low socioeconomic status with chronic neurological conditions. PA is known to be important for brain health in neurological conditions but remains relatively unexplored in minority populations.Trial RegistrationClinicalTrials.gov NCT04820153; https://clinicaltrials.gov/ct2/show/NCT04820153

Acceptance of physical activity monitoring in cancer patients during radiotherapy, the GIROfit phase 2 pilot trial.

In radiotherapy the timely identification of patients needing intervention and supportive care due to side effects is an important task especially in the outpatient setting. Activity trackers as an increasingly used lifestyle device may enable physicians to monitor patient's physical activity (PA) and to intervene early during the course of radiotherapy. The primary aim of this trial was to assess patient acceptance of PA monitoring in an outpatient setting and to correlate changes in PA with toxicity and changes in quality of life. Patients undergoing radio(chemo-)therapy with a curative intent were eligible to participate in this prospective pilot phase II trial. Patients were instructed to wear a commercially available activity tracker during the course of radiotherapy and four weeks afterwards. Quality of life (QoL) and fatigue was scored using the Functional assessment of Chronic Illness Therapy questionnaire. A linear regression was performed to determine baseline activity and changes in step counts during radiotherapy. We included 23 patients in this trial. Two withdrew consent before the start of treatment, two patients were excluded after prophylactic feeding tube placement and prolonged recovery. Compliance in the remaining 19 patients was high, with availability of step-counts on 92% of the days. Baseline step counts were 6274 for breast cancer patients and 3621 for patients with other entities. Decreasing activity during radiotherapy coincided with the development of side effects and declines in quality of life. Activity trackers as tool to monitor PA during and after radiotherapy were accepted by a majority of the patients included in the current trial. Observed changes in PA correlated with patient reported side effects and QoL in some of the patients.

Comparison of Different Physical Activity Measures in a Cardiac Rehabilitation Program: A Prospective Study.

Concordant assessments of physical activity (PA) and related measures in cardiac rehabilitation (CR) is essential for exercise prescription. This study compared exercise measurement from an in-person walk test; wearable activity tracker; and self-report at CR entry, completion (8-weeks) and follow-up (16-weeks). Forty patients beginning CR completed the Six-Minute Walk Test (6MWT), Physical Activity Scale for the Elderly (PASE), and wore Fitbit-Flex for four consecutive days including two weekend days. The sample mean age was 66 years; 67% were male. Increased exercise capacity at CR completion and follow-up was detected by a 6MWT change in mean distance (39 m and 42 m; p = 0.01, respectively). Increased PA participation at CR completion was detected by Fitbit-Flex mean change in step counts (1794; p = 0.01). Relative changes for Fitbit-Flex step counts and a 6MWT were consistent with previous research, demonstrating Fitbit-Flex’s potential as an outcome measure. With four days of data, Fitbit-Flex had acceptable ICC values in measuring step counts and MVPA minutes. Fitbit-Flex steps and 6MWT meters are more responsive to changes in PA patterns following exposure to a cardiac rehabilitation program than Fitbit-Flex or PASE-estimated moderate–vigorous PA (MVPA) minutes. Fitbit-Flex step counts provide a useful additional measure for assessing PA outside of the CR setting and accounts for day-to-day variations. Two weekend days and two weekdays are needed for Fitbit-Flex to estimate PA levels more precisely.

Increased physical activity improves gut microbiota composition and reduces short-chain fatty acid concentrations in older adults with insomnia

Physical activity (PA) can improve functional abilities, well-being, and independence in older adults with insomnia. Studies have shown that PA may be linked to changes in the gut microbiota composition and its metabolites’ concentrations. This association among older adults with insomnia, however, is yet to be determined. We explored the relationships between physical activity (PA) levels, gut microbiota composition, and short-chain fatty acid (SCFA) levels in this population. Forty-nine community-dwelling adults with insomnia symptoms, aged 65 and older, participated in this study. Their average daily step-count and sleep continuity measures over a two-week period were calculated based on Actigraphic recordings. Each participant provided fecal samples for the microbiome and SCFA analyses, anthropometric measures, and information via questionnaires on medical history and food consumption. The gut microbiota composition and SCFA concentrations were determined by next-generation sequencing and Gas chromatography-mass spectrometry, respectively. Participants were divided into two groups (more and less active) according to their median step/day count. We compared the microbiota abundance and SCFA concentrations between groups and performed correlation analysis between gut microbiota abundances and study variables. Different microbiota taxa in each PA group and increased SCFAs in feces of less active individuals were found. Changes in step counts were positively or negatively associated with the relative abundance of 19 ASVs, 3 microorganisms at the family level, and 11 microorganisms at the genus level. Furthermore, significant associations were discovered among physical activity, gut microbiota, SCFAs, and sleep parameters. Our findings provide new insights on the relationship between PA, gut microbiota composition, and primary metabolites in older adults with insomnia.

Measuring Productivity, Perceived Stress and Work Engagement of a Nationally Delivered Workplace Step Count Challenge.

Workplace step count challenges show promise with regard to increasing physical activity, with walking linked to many positive physical and mental health benefits. Few studies have investigated their effects on work-related outcomes. The aim of this study was to describe (1) the process of collecting work-related outcomes as part of a real-world workplace intervention, the Step Count Challenge, and (2) report step counts and work-related outcomes (productivity, perceived stress and work engagement) during the Step Count Challenge. This pre-post study was conducted as part of a four-week 2018 National Step Count Challenge (SCC) in Scotland, UK. A survey was administered to collect self-reported steps, productivity (HWQ), perceived stress (Cohen Perceived Stress Scale) and work engagement (UWES) on the week prior to the intervention starting (baseline), week 1 and week 4. Process data such as recruitment and response rates were monitored throughout. Of 2042 employees who signed up to the SCC, baseline data were reported for 246 (12% of total; mean age 42.5 years, 83% female). Process data suggest low uptake to the study and poor compliance between surveys time points. Preliminary data suggest positive changes in step counts (3374 steps/day by week 4), stress and productivity. No changes in work engagement were found. The findings highlight the need to integrate research more effectively into real-world interventions, including a true baseline period. The Step Count Challenge may have positive change on some work-related outcomes warranting further investigation into how robust research designs can be delivered without negatively influencing real-world interventions.

Defining The Optimal Duration Of Familiarization For An INT Intervention For Children With Autism

PURPOSE: A period of familiarization to exercise interventions is recommended for children with autism spectrum disorder (ASD). Unknown, however, is how long this familiarization period should be to ensure optimal engagement in the exercise intervention. To address this gap in understanding, this study sought to define the required duration needed for a familiarization period for a school-based integrative neuromuscular training (INT) intervention for children with ASD. METHODS: Nine children (6.9 years ±1.5) with a diagnosis of ASD were recruited to complete a school-based INT intervention, partaking in three, one-hour weekly sessions for seven weeks. The INT intervention was implemented via games aimed at the interests of the children and was adapted to each child’s specific needs. Pedometer data were collected for seven weeks, and the average number of steps taken per week were calculated. Completion of the familiarization period was denoted by a significant increase in step count between weeks, followed by a plateau or continued increase in subsequent weeks. Data were analysed using a one-way ANOVA, and Tukey's post hoc analysis, to identify changes in step counts over time. Statistical significance was set at an alpha level of p < 0.05. RESULTS: There was a significant effect for time over the seven weeks (p < 0.01). Post hoc analysis displayed significant differences and a greater number of steps taken following week five (p < 0.05) with no significant increases in steps between weeks five, six, and seven suggesting a plateau occurred. Steps averaged 48 ± 9.6 per minute for week one and increased to an average of 68 ± 4.9 per minute for week seven. CONCLUSIONS: Results indicate that a familiarization period of four weeks is needed when introducing an INT intervention to children with ASD.

The role of fitness trackers and tailored feedback messages in motivating endometrial cancer survivors to increase physical activity: results of the MOVES trial

Objectives: Endometrial cancer (EC) survivors are often overweight or obese and may benefit from increased physical activity. Increases in daily step count of 2,000 steps per day has been shown to improve cardiovascular health. We sought to assess a fitness intervention (fitness tracker + tailored feedback messages) for EC survivors. Methods: A prospective trial of EC survivors was undertaken from September 2018 to December 2019. Thirty-nine survivors were approached for enrollment with 36 randomized (18 intervention, 18 control). All participants received a fitness tracker. Survivors were randomized 1:1 to receipt or non-receipt of weekly tailored feedback messages. The primary outcome was change in average daily step count from baseline (week 1) to study completion (week 12). Secondary outcomes included acceptability, and changes in metabolic lab parameters (serum glucose, LDL, and insulin levels), body mass index (BMI) and waist to hip ratio (W/H). The trial was powered to detect a clinically significant change in daily step count of 2,000 steps. Comparisons of baseline to study completion labs were made using the Wilcoxon Two-sample test. Student's T-test was used for comparisons of control and intervention groups. Results: At baseline, there was no difference in BMI (35.9 vs 36.7, p=0.81) or W/H ratio (0.9 vs 0.89, p=0.40) between control and intervention arms. Baseline daily step count was 5291 steps in the control arm and 4295 in the intervention arm (p=0.16). There was no difference in baseline metabolic labs including glucose (100 vs 103, p=0.85), serum insulin (13.1 vs 16.8, p=0.78), and LDL (150 vs 113, p=0.07). The intervention group saw a statistical change in average daily step count (4295 to 5332, p=0.02). The control group did not have a statistically significant change (5291 to 5600, p=0.40). For the primary outcome of average daily step count change, there was no statistically significant difference between the two groups (+309 control vs +1037 intervention, p=0.21). There was no difference in change in BMI (-0.27 vs -0.02, p=0.7), glucose (+1 vs -3, p=0.29), LDL (-9.1 vs -3.5, p=0.95) or insulin (-2.15 vs -1.95, p=0.32) between the control and intervention arms. Regarding acceptability, survivors found the feedback to be helpful (87%) and easy to understand (87%). Two-thirds of survivors found the messages to be motivating, 47% desired increased frequency of messaging, and 53% thought the weekly message was adequate. Overall, 33% of intervention survivors versus 22% of control survivors had decline in fitness tracker use during the intervention, resulting in missing step data (p=0.46). Conclusions: A fitness intervention using fitness trackers and tailored feedback messaging may improve physical activity as measured by daily step count in EC survivors, however, significant noncompliance with fitness tracker use was seen in both groups by study end. Tailoring the frequency of feedback messages to survivor preference may be important to optimizing this intervention.

A pilot study of physical activity in newly diagnosed elderly patients with multiple myeloma.

e20027 Background: Compared to a baseline normative population, patients with multiple myeloma (MM) have decreased physical function[1]. Studies have revealed that sarcopenia[2, 3], decreased performance status[4], and poor performance on biometric testing[3, 5] predicts worse survival in patients with advanced, incurable malignancies. Physical activity (PA) has been shown to mitigate these effects and in some cases improve cancer specific survival [6-9]. However, there is a need for further research in this area for patients with hematologic malignancies. Here in we describe the results of a pilot study to assess a physical activity intervention in elderly patients with newly diagnosed multiple myeloma. Methods: We designed a single arm, feasibility study utilizing physical and behavioral therapy interventions to help participants adhere to a prescribed exercise program. Eligible patients (age ≥65 years old) were recruited from the multiple myeloma treatment clinic. Baseline, 3-month and 6-month assessments occurred. The intervention included both text messaging and video visits with behavioral coaches and physical therapists to monitor activity levels, review and modify exercise plans, , and enhance motivation and self-efficacy. Our primary aim was to establish the feasibility of recruitment, enrollment, and adherence of the exercise intervention. Our secondary objective was to evaluate changes in fitness (6 minute walk test, grip strength, and the Short Physical Performance Battery). Results: Between 11/18/2019-03/04/2020, 9 participants enrolled on the study (goal of 20). New enrollment was halted due to the COVID-19 pandemic. Median age of the participants was 70 (range 65-86). Six (67%) were female. Eight participants (89%) completed the 6-month intervention. Participants completed 97.8% of the scheduled visits. At 3 and 6 months there was a mean change of moderate/vigorous activity of 26.0% (SD 89.6%) and -0.5% (SD 56.4%) respectively. At 3 and 6 months there was a mean change in step count per day of -5.1% (SD 25.3%) and -1.3% (SD 32.2%) respectively. Overall fitness was preserved over the 6-month period. Conclusions: Prior to COVID-19 pandemic, the study was on track to meet feasibility endpoints of recruitment, enrollment, and retention. The primary endpoint of increasing physical activity was not met. However, adults in our region experienced a 20-30% reduction in physical activity during the pandemic [10]. In the target population, reductions in the absence of intervention may have been even greater, given their pronounced vulnerability to COVID-19 complications. Thus, the true benefits of the intervention may have been difficult to detect during this period. Lack of a control arm is a limiting factor in making further conclusions about the potential benefits of our intervention.

The Effectiveness of an Annual Nationally Delivered Workplace Step Count Challenge on Changing Step Counts: Findings from Four Years of Delivery.

Paths for All’s 8-week online Workplace Step Count Challenge (SCC) is a flagship program of Scotland’s National Walking Strategy. The aim of this study was to examine changes in step counts throughout the duration of the SCC, across four years of delivery. Participants were those who registered for the 2015–2018 SCCs, and reported demographic data at registration. Participants self-reported their device-measured step count for each day of the SCC. Following data screening, mean daily steps for each week were calculated. Linear mixed models (R nlme procedure), controlling for the within subject nature of the step count measure, were used to explore changes in steps over time. Gender and age group (<45 years; ≥45 years) were entered into a subsequent model. Separate models were created for each year of the SCC and for all years combined. Participants (n = 10,183) were predominantly women (76.8%), aged <45 (54.6%) and ≥45 years. In general, steps increased each week compared to week 1 (p < 0.001), with a significant increase evident at all but seven of 28 data points. Across the four years of SCC, the increase in steps at week 8 compared to week 1 ranged from 506 to 1223 steps per day, making a substantial contribution to the recommended physical activity levels for health. There was no consistent age or gender effect. The findings provide support for the continued investment in such workplace interventions.

Effects of an mHealth App (Kencom) With Integrated Functions for Healthy Lifestyles on Physical Activity Levels and Cardiovascular Risk Biomarkers: Observational Study of 12,602 Users.

BackgroundMobile health (mHealth) apps are considered to be potentially powerful tools for improving lifestyles and preventing cardiovascular disease (CVD), although only few have undergone large, well-designed epidemiological research. “kencom” is a novel mHealth app with integrated functions for healthy lifestyles such as monitoring daily health/step data, providing tailored health information, or facilitating physical activity through group-based game events. The app is linked to large-scale Japanese insurance claims databases and annual health check-up databases, thus comprising a large longitudinal cohort.ObjectiveWe aimed to assess the effects of kencom on physical activity levels and CVD risk factors such as obesity, hypertension, dyslipidemia, and diabetes mellitus in a large population in Japan.MethodsDaily step count, annual health check-up data, and insurance claim data of the kencom users were integrated within the kencom system. Step analysis was conducted by comparing the 1-year average daily step count before and after kencom registration. In the CVD risk analysis, changes in CVD biomarkers following kencom registration were evaluated among the users grouped into the quintile according to their change in step count.ResultsA total of 12,602 kencom users were included for the step analysis and 5473 for the CVD risk analysis. The participants were generally healthy and their mean age was 44.1 (SD 10.2) years. The daily step count significantly increased following kencom registration by a mean of 510 steps/day (P<.001). In particular, participation in “Arukatsu” events held twice a year within the app was associated with a remarkable increase in step counts. In the CVD risk analysis, the users of the highest quintile in daily step change had, compared with those of the lowest quartile, a significant reduction in weight (–0.92 kg, P<.001), low-density lipoprotein cholesterol (–2.78 mg/dL, P=.004), hemoglobin A1c (HbA1c; –0.04%, P=.004), and increase in high-density lipoprotein cholesterol (+1.91 mg/dL, P<.001) after adjustment of confounders.ConclusionsThe framework of kencom successfully integrated the Japanese health data from multiple data sources to generate a large, longitudinal data set. The use of the kencom app was significantly associated with enhanced physical activity, which might lead to weight loss and improvement in lipid profile.

Using Wearable Biosensors to Predict Length of Stay for Patients with IBD After Bowel Surgery.

It remains unknown whether ambulation or sleep predicts postoperative length of stay for patients with IBD. We aim to identify the utility of wearable biosensors in predicting postoperative length of stay for patients with IBD. Associations of postoperative length of stay with step count/sleep duration/sleep efficiency measured by wearable biosensors were examined. The best-fitting multivariable linear regression model predicting length of stay was constructed using stepwise model selection. Final sample included 37 patients. Shorter sleep duration on postoperative day 4 (r = 0.51, p = 0.043) or 5 (r = 0.81, p = 0.0045) or higher sleep efficiency on postoperative day 5 (r = -0.77, p = 0.0098) was associated with a shorter length of stay. Additionally, a more positive change in sleep efficiency from postoperative day 4-5 was associated with a shorter length of stay (r = -0.77, p = 0.024). The best-fitting multivariable linear regression model revealed Clavien-Dindo grade 1 (p = 0.045) and interaction between Clavien-Dindo grade 2/3a and mean daily steps (p = 0.00038) are significant predictors of length of stay. The following variables were not significantly associated with length of stay: mean daily steps/sleep duration/sleep efficiency, average rate of change in these three variables, and changes in step count between successive postoperative days 1-5, sleep duration between successive postoperative days 2-5, and sleep efficiency between successive postoperative days 2-4. We demonstrated the utility of activity and sleep data from wearable biosensors in predicting length of stay. Patients with more severe complications may benefit more (i.e., reduced postoperative length of stay) from increased ambulation. However, overall, sleep duration/efficiency did not predict length of stay.

COVID-19 versus physical inactivity – a self-reported questionnaire study

Objective: COVID-19 is linked with significant mortality and morbidity. To curb the spread of the pandemic, curfews and lockdowns were imposed in many countries, leading to reduced physical activity (PA) irrespective of race, ethnicity, or income level. Although some papers documented how PA level was affected by COVID-19 in children and elderly in some countries, no similar data is available in Turkey during the pandemic. Therefore, we aimed to document the changes in step count in Turkey following the first reported case.

Web-Based Physical Activity Intervention for COPD: Differences Between Rural and Urban Veterans

Physical activity is recommended for all patients with chronic obstructive pulmonary disease (COPD), a disease prevalent among older adults. Rural Veterans often lack access to in-person services to support behavior change. Technology can be used to overcome these barriers. This secondary analysis of a randomized controlled trial compared engagement (weekly website-logons) and efficacy (step-count change) measures of a 4-month technology-based physical activity intervention between rural and urban Veterans with COPD. Rural-urban commuting codes (RUCA) were used to classify participants (N=239; mean age=66.7±8.84 years) as ‘rural’ or ‘urban’. Participants were randomized 2:1 to a pedometer and website with iterative, individualized step-count feedback and goals, motivational and informational messages, and an online community (intervention group, n=155, 45.8% rural) or to receive a pedometer-alone (waitlist-control group, n=84, 44% rural). General linear modeling estimated the adjusted effect of rurality on intervention response. There was no significant rural-urban difference in weekly website-logons (3.33 vs. 3.17; p=.364). There was a significant interaction between rurality and group on step-count change (p=.045). Among rural participants, both intervention and controls increased their step counts (567.32 vs. 732.30; p=.769). Among urban participants, the intervention group demonstrated a significantly higher change in step-counts compared to controls (1052.67 vs. -313.57; p=.008). Results suggest that rural participants increased their step-counts similarly whether they received a pedometer alone or used the intervention, whereas only urban participants who used the intervention increased their step counts. It is possible that simply receiving the pedometer alone was sufficient for behavior change in the rural participants.

Long-Term Effects of Pedometer-Based Physical Activity Coaching in Severe COPD: A Randomized Controlled Trial.

Background and ObjectiveLimited evidence on long-term effects of physical activity programs in COPD is available. The aim of the study was to investigate the effects of a three-month program combining physical activity counselling and pedometer-based feedback in addition to usual care, followed by a nine-month unsupervised observation period as compared to usual care in participants with severe to very severe COPD.MethodsParticipants were randomized to either a control group receiving usual care or an intervention group receiving motivational support, an activity diary with an individual step count goal (ie, an increase of ≥15% from baseline) and a pedometer in addition to usual care. The intervention ended after three months and an unsupervised observational period followed until twelve months. Primary outcome was daily step count after one year.ResultsSeventy-four participants were included, 61 (82%) completed the study. Linear regression modelling, adjusted for baseline step count, showed no significant difference in change in step count after 12 months between the groups (Β = 547.33, 95% CI = −243.55/1338.20).ConclusionA three-month program combining physical activity counselling and pedometer-based feedback in addition to usual care does not attenuate the declining course of physical activity in participants with severe and very severe COPD during a long term follow-up of one year as compared to usual care. This result was primarily determined by the low intervention response rates to the combined program.Clinical Trial Registrationwww.ClinicalTrials.gov, NCT03114241.

Effect of Adding Telephone-Based Brief Coaching to an mHealth App (Stay Strong) for Promoting Physical Activity Among Veterans: Randomized Controlled Trial.

BackgroundThough maintaining physical conditioning and a healthy weight are requirements of active military duty, many US veterans lose conditioning and rapidly gain weight after discharge from active duty service. Mobile health (mHealth) interventions using wearable devices are appealing to users and can be effective especially with personalized coaching support. We developed Stay Strong, a mobile app tailored to US veterans, to promote physical activity using a wrist-worn physical activity tracker, a Bluetooth-enabled scale, and an app-based dashboard. We tested whether adding personalized coaching components (Stay Strong+Coaching) would improve physical activity compared to Stay Strong alone.ObjectiveThe goal of this study is to compare 12-month outcomes from Stay Strong alone versus Stay Strong+Coaching.MethodsParticipants (n=357) were recruited from a national random sample of US veterans of recent wars and randomly assigned to the Stay Strong app alone (n=179) or Stay Strong+Coaching (n=178); both programs lasted 12 months. Personalized coaching components for Stay Strong+Coaching comprised of automated in-app motivational messages (3 per week), telephone-based human health coaching (up to 3 calls), and personalized weekly goal setting. All aspects of the enrollment process and program delivery were accomplished virtually for both groups, except for the telephone-based coaching. The primary outcome was change in physical activity at 12 months postbaseline, measured by average weekly Active Minutes, captured by the Fitbit Charge 2 device. Secondary outcomes included changes in step counts, weight, and patient activation.ResultsThe average age of participants was 39.8 (SD 8.7) years, and 25.2% (90/357) were female. Active Minutes decreased from baseline to 12 months for both groups (P<.001) with no between-group differences at 6 months (P=.82) or 12 months (P=.98). However, at 12 months, many participants in both groups did not record Active Minutes, leading to missing data in 67.0% (120/179) for Stay Strong and 61.8% (110/178) for Stay Strong+Coaching. Average baseline weight for participants in Stay Strong and Stay Strong+Coaching was 214 lbs and 198 lbs, respectively, with no difference at baseline (P=.54) or at 6 months (P=.28) or 12 months (P=.18) postbaseline based on administrative weights, which had lower rates of missing data. Changes in the number of steps recorded and patient activation also did not differ by arm.ConclusionsAdding personalized health coaching comprised of in-app automated messages, up to 3 coaching calls, plus automated weekly personalized goals, did not improve levels of physical activity compared to using a smartphone app alone. Physical activity in both groups decreased over time. Sustaining long-term adherence and engagement in this mHealth intervention proved difficult; approximately two-thirds of the trial’s 357 participants failed to sync their Fitbit device at 12 months and, thus, were lost to follow-up.Trial RegistrationClinicalTrials.gov NCT02360293; https://clinicaltrials.gov/ct2/show/NCT02360293International Registered Report Identifier (IRRID)RR2-10.2196/12526

Three-Year Longitudinal Association Between Built Environmental Factors and Decline in Older Adults' Step Count: Gaining insights for Age-Friendly Urban Planning and Design.

This study examined the longitudinal association between the change in the step count of older adults and the neighborhood-built environment (BE) in Yokohama, Japan. We analyzed pedometer data in March 2016 and March 2019 that were acquired from 21,557 older adults aged 65–79 years at baseline, who lived in 758 neighborhoods in Yokohama City and participated in the Yokohama Walking Point Program (YWPP). Six BE variables were computed, for each of which neighborhoods were classified into quartiles. Using multilevel regression analysis, we examined the association between the BE variables, baseline step count, and change in step count. Higher population density, lower intersection density, and the second shortest quartile of the average distance to the nearest railway station were associated with a higher baseline step count. A lower intersection density and shorter average distance to the nearest railway station were associated with a smaller decline. The lowest quartile of population density was inversely associated with step-count decline. In conclusion, the neighborhood BEs were not only associated with their step count at baseline, but also widened the disparity of the step count over the three years. These findings would contribute to creating age-friendly cities where older adults can maintain and promote their health.

A trajectory analysis of daily step counts during a physician-delivered intervention

ObjectivesHigher steps are associated with lower mortality and cardiovascular event rates. We previously demonstrated that tailored physician-delivered step count prescriptions successfully increased steps/day in adults with type 2 diabetes mellitus (T2DM) and/or hypertension. In the present analysis, we examined patterns of step count change and the factors that influence different responses. DesignLongitudinal observational study MethodsActive arm participants (n=118) recorded steps/day. They received a step count prescription from their physician every 3–4 months. We computed mean steps/day and changes from baseline for sequential 30-day periods. Group-based trajectory modeling was applied. ResultsFour distinct trajectories of mean steps/day emerged, distinguishable by differences in baseline steps/day: sedentary (19%), low active (40%), somewhat active (30%) and active (11%). All four demonstrated similar upward slopes. Three patterns emerged for the change in steps from baseline: gradual decrease (30%), gradual increase with late decline (56%), and rapid increase with midpoint decline (14%); thus 70% had an increase from baseline. T2DM (odd ratios [OR]: 3.7, 95% CI 1.7, 7.7) and age (OR per 10-year increment: 2, 95% CI 1.3, 2.8) were both associated with starting at a lower baseline but participants from these groups were no less likely than others to increase steps/day. ConclusionsT2DM and older age were associated with lower baseline values but were not indicators of likelihood of step count increases. A physician-delivered step count prescription and monitoring strategy has strong potential to be effective in increasing steps irrespective of baseline counts and other clinical and demographic characteristics.

Feasibility and preliminary effects of a peer-led motivationally-embellished workplace walking intervention: A pilot cluster randomized trial (the START trial)

Walking interventions can be effective in increasing physical activity amongst physically inactive employees. However, despite their promising potential regarding sustainability and scalability, peer-led workplace walking interventions have not been tested. We evaluated a peer-led workplace group walking intervention designed to engage physically inactive employees. A 16-week pilot cluster randomized controlled trial consisted of enhanced (5 worksites; n = 50 participants) and minimal treatment (3 worksites; n = 47) conditions. All participants were provided with a Fitbit Zip and information on health benefits of walking. Enhanced treatment participants had access to a mobile phone app incorporating behavior change techniques, were trained on principles of autonomous motivation, and had a peer leader trained in a motivationally supportive communication style. Feasibility assessments included recruitment and drop-out rates, assessment completion rates, training acceptability (walkers and peer leaders), and intervention acceptability (walkers only). Outcomes assessed included movement-related behaviors (assessed via activPAL devices), cardio-metabolic risk factors, motivation to walk, and well-being, and these measures were taken at baseline and post-intervention. The results supported intervention feasibility. Preliminary efficacy evidence was mixed. Markers of cardio-metabolic risk improved in the enhanced treatment only. Autonomous motivation increased in both conditions. There were no changes in step counts, standing, and sitting time, or well-being. Further fine tuning is needed before a definitive RCT.Australian and New Zealand Clinical Trials Registry: ACTRN12618000807257.

Custom-Made Daily Routine Increases the Number of Steps Taken by Frail Older Adults.

This study examined whether the number of steps taken by frail older adults increased after two types of interventions (custom-made daily routine [CDR] vs. exercise) were conducted over 12 weeks. The participants were 36 frail older adults aged 84.5 ± 6.0 years who attended a day-care center. They were assigned to one of three groups: CDR (n = 13), home-based exercise (HE, n = 10), or control (CON, n = 13). A wrist-worn accelerometer was used to measure their step count in 24 hr for 6 days. The CDR group demonstrated a daily step count change of approximately 25%, which was significantly higher than that of the CON group (effect size [r] = .51, p = .040). There were no significant changes in the HE group. Thus, a CDR might be useful for increasing the number of steps in frail older adults.