Excess weight and physical inactivity are modifiable risk factors for breast cancer. Behavioral intervention is particularly important among women with an elevated risk profile. This trial tested an intervention that trained women to use a self-monitoring website to increase activity and lose weight. Women with BMI ≥27.5 kg/m(2) at elevated breast cancer risk were randomized to the intervention (N = 71) or usual care (N = 34). The intervention group received telephone-based coaching and used web-based self-monitoring tools. At 6 months, significant weight loss was observed in the intervention group (4.7 % loss from starting weight; SD = 4.7 %) relative to usual care (0.4 % gain; SD = 3.0 %) (p < 0.0001). By 12 months, the intervention group had lost 3.7 % of weight (SD = 5.4 %), compared to 1.3 % (SD = 4.2) for usual care (p = 0.003). At 12 months, accelerometer-measured moderate-to-vigorous physical activity increased by 12 min/day (SD = 24) compared to no change in usual care (p = 0.04. In summary, this web- and phone-based approach produced modest but significant improvements in weight and physical activity for women at elevated breast cancer risk.

PURPOSE:This study aimed to improve estimates of sitting time from hip-worn accelerometers used in large cohort studies by using machine learning methods developed on free-living activPAL data. METHODS:Thirty breast cancer survivors concurrently wore a hip-worn accelerometer and a thigh-worn activPAL for 7 d. A random forest classifier, trained on the activPAL data, was used to detect sitting, standing, and sit-stand transitions in 5-s windows in the hip-worn accelerometer. The classifier estimates were compared with the standard accelerometer cut point, and significant differences across different bout lengths were investigated using mixed-effect models. RESULTS:Overall, the algorithm predicted the postures with moderate accuracy (stepping, 77%; standing, 63%; sitting, 67%; sit-to-stand, 52%; and stand-to-sit, 51%). Daily level analyses indicated that errors in transition estimates were only occurring during sitting bouts of 2 min or less. The standard cut point was significantly different from the activPAL across all bout lengths, overestimating short bouts and underestimating long bouts. CONCLUSIONS:This is among the first algorithms for sitting and standing for hip-worn accelerometer data to be trained from entirely free-living activPAL data. The new algorithm detected prolonged sitting, which has been shown to be the most detrimental to health. Further validation and training in larger cohorts is warranted.

Background

Direct-to-consumer trackers and devices have potential to enhance theory-based physical activity interventions by offering a simple and pleasant way to help participants self-monitor their behavior. A secondary benefit of these devices is the opportunity for investigators to objectively track adherence to physical activity goals across weeks or even months, rather than relying on self-report or a small number of accelerometry wear periods. The use of consumer trackers for continuous monitoring of adherence has considerable potential to enhance physical activity research, but few studies have been published in this rapidly developing area.

Objective

The objective of the study was to assess the trajectory of physical activity adherence across a 16-week self-monitoring intervention, as measured by the Fitbit tracker.

Methods

Participants were 25 overweight or obese, postmenopausal women enrolled in the intervention arm of a randomized controlled physical activity intervention trial. Each participant received a 16-week technology-based intervention that used the Fitbit physical activity tracker and website. The overall study goal was 150 minutes/week of moderate to vigorous intensity physical activity (MVPA) and 10,000 steps/day; however, goals were set individually for each participant and updated at Week 4 based on progress. Adherence data were collected by the Fitbit and aggregated by Fitabase. Participants also wore an ActiGraph GT3X+ accelerometer for 7 days prior to the intervention and again during Week 16.

Results

The median participant logged 10 hours or more/day of Fitbit wear on 95% of the 112 intervention days, with no significant decline in wear over the study period. Participants averaged 7540 (SD 2373) steps/day and 82 minutes/week (SD 43) of accumulated "fairly active" and "very active" minutes during the intervention. At Week 4, 80% (20/25) of women chose to maintain/increase their individual MVPA goal and 72% (18/25) of participants chose to maintain/increase their step goal. Physical activity levels were relatively stable after peaking at 3 weeks, with only small declines of 8% for steps (P=.06) and 14% for MVPA (P=.05) by 16 weeks.

Conclusions

These data indicate that a sophisticated, direct-to-consumer activity tracker encouraged high levels of self-monitoring that were sustained over 16 weeks. Further study is needed to determine how to motivate additional gains in physical activity and evaluate the long-term utility of the Fitbit tracker as part of a strategy for chronic disease prevention.

Trial registration

Clinicaltrials.gov NCT01837147; http://clinicaltrials.gov/ct2/show/NCT01837147 (Archived by WebCite at http://www.webcitation.org/6d0VeQpvB).

Background

Physical activity after cancer diagnosis improves quality of life and may lengthen survival. However, objective data in cancer survivors are limited and no physical activity tracker has been validated for use in this population.

Objective

The aim of this study was to validate the Fitbit One's measures of physical activity over 7 days in free-living men with localized prostate cancer.

Methods

We validated the Fitbit One against the gold-standard ActiGraph GT3X+ accelerometer in 22 prostate cancer survivors under free-living conditions for 7 days. We also compared these devices with the HJ-322U Tri-axis USB Omron pedometer and a physical activity diary. We used descriptive statistics (eg, mean, standard deviation, median, interquartile range) and boxplots to examine the distribution of average daily light, moderate, and vigorous physical activity and steps measured by each device and the diary. We used Pearson and Spearman rank correlation coefficients to compare measures of physical activity and steps between the devices and the diary.

Results

On average, the men wore the devices for 5.8 days. The mean (SD) moderate-to-vigorous physical activity (MVPA; minutes/day) measured was 100 (48) via Fitbit, 51 (29) via ActiGraph, and 110 (78) via diary. The mean (SD) steps/day was 8724 (3535) via Fitbit, 8024 (3231) via ActiGraph, and 6399 (3476) via pedometer. Activity measures were well correlated between the Fitbit and ActiGraph: 0.85 for MPVA and 0.94 for steps (all P<.001). The Fitbit's step measurements were well correlated with the pedometer (0.67, P=.001), and the Fitbit's measure of MVPA was well correlated with self-reported activity in the diary (0.84; P<.001).

Conclusions

Among prostate cancer survivors, the Fitbit One's activity and step measurements were well correlated with the ActiGraph GT3X+ and Omron pedometer. However, the Fitbit One measured two times more MVPA on average compared with the ActiGraph.

The purpose of this study was to compare estimates of sedentary time on weekdays vs. weekend days in older adults and determine if these patterns vary by measurement method. Older adults (N = 230, M = 83.5, SD = 6.5 years) living in retirement communities completed a questionnaire about sedentary behavior and wore an ActiGraph accelerometer for seven days. Participants engaged in 9.4 (SD = 1.5) hr per day of accelerometer-measured sedentary time, but self-reported engaging in 11.4 (SD = 4.9) hr per day. Men and older participants had more accelerometer-measured sedentary time than their counterparts. The difference between accelerometer-measured weekday and weekend sedentary time was nonsignificant. However, participants self-reported 1.1 hr per day more sedentary time on weekdays compared with weekend days. Findings suggest self-reported but not accelerometer-measured sedentary time should be investigated separately for weekdays and weekend days, and that self-reports may overestimate sedentary time in older adults.

Purpose

To examine associations between dimensions of sedentary behavior and cognitive function in breast cancer survivors.

Methods

Sedentary behavior variables were measured using thigh-worn activPALs, and included total daily sitting time, time in long sitting bouts, sit-to-stand transitions, and standing time. Cognitive function was assessed using the NIH Toolbox Cognitive Domain. Separate multivariable linear regression models were used to examine associations between sedentary behavior variables with the cognitive domain scores of attention, executive functioning, episodic memory, working memory, and information processing speed.

Results

Thirty breast cancer survivors with a mean age of 62.2 (SD = 7.8) years who were 2.6 (SD = 1.1) years since diagnosis completed study assessments. In multivariable linear regression models, more time spent standing was associated with faster information processing (b: 5.78; p = 0.03), and more time spent in long sitting bouts was associated with worse executive function (b: -2.82; p = 0.02), after adjustment for covariates. No other sedentary behavior variables were statistically significantly associated with the cognitive domains examined in this study.

Conclusions

Two important sedentary constructs that are amenable to intervention, including time in prolonged sitting bouts and standing time, may be associated with cognitive function in breast cancer survivors. More research is needed to determine whether modifying these dimensions of sedentary behavior will improve cognitive function in women with a history of breast cancer, or prevent it from declining in breast cancer patients.

Background

Studies have shown self-monitoring can modify health behaviors, including physical activity (PA). This study tested the utility of a wearable sensor/device (Fitbit(®) One™; Fitbit Inc., San Francisco, CA) and short message service (SMS) text-messaging prompts to increase PA in overweight and obese adults.

Materials and methods

Sixty-seven adults wore a Fitbit One tracker for 6 weeks; half were randomized to also receive three daily SMS-based PA prompts. The Fitbit One consisted of a wearable tracker for instant feedback on performance and a Web site/mobile application (app) for detailed summaries. Outcome measures were objectively measured steps and minutes of PA by intensity using two accelerometers: Actigraph™ (Pensacola, FL) GT3X+ (primary measure) at baseline and Week 6 and Fitbit One (secondary measure) at baseline and Weeks 1, 2, 3, 4, 5, and 6.

Results

Mixed-model repeated-measures analysis of primary measures indicated a significant within-group increase of +4.3 (standard error [SE]=2.0) min/week of moderate- to vigorous-intensity PA (MVPA) at 6-week follow-up (p=0.04) in the comparison group (Fitbit only), but no study group differences across PA levels. Secondary measures indicated the SMS text-messaging effect lasted for only 1 week: the intervention group increased by +1,266 steps (SE=491; p=0.01), +17.8 min/week MVPA (SE=8.5; p=0.04), and +38.3 min/week total PA (SE=15.9; p=0.02) compared with no changes in the comparison group, and these between-group differences were significant for steps (p=0.01), fairly/very active minutes (p<0.01), and total active minutes (p=0.02).

Conclusions

These data suggest that the Fitbit One achieved a small increase in MVPA at follow-up and that the SMS-based PA prompts were insufficient in increasing PA beyond 1 week. Future studies can test this intervention in those requiring less help and/or test strategies to increase participants' engagement levels.

Background

Sedentary behavior is associated with increased risk of poor outcomes in breast cancer survivors, but underlying mechanisms are not well understood. This pilot study explored associations between different aspects of sedentary behaviors (sitting, prolonged sitting, sit-to-stand transitions, and standing) and breast cancer risk-related biomarkers in breast cancer survivors (n = 30).

Methods

Sedentary behavior variables were objectively measured with thigh-worn activPALs. Breast cancer risk-related biomarkers assessed were C-reactive protein (CRP), insulin, and homeostatic model assessment of insulin resistance (HOMA-IR) and were measured in fasting plasma samples. Linear regression models were used to investigate associations between sedentary behavior variables and biomarkers (log CRP, insulin, and HOMA-IR).

Results

Sit-to-stand transitions were significantly associated with insulin resistance biomarkers (P < .05). Specifically, each 10 additional sit-to-stand transitions per day was associated with a lower fasting insulin concentration (β = -5.52; 95% CI, -9.79 to -1.24) and a lower HOMA-IR value (β = -0.22; 95% CI, -0.42 to -0.03). Sit-to-stand transitions were not significantly associated with CRP concentration (P = .08). Total sitting time, long sitting bouts, and standing time were not significantly associated with CRP, insulin, or HOMA-IR (P > .05).

Conclusions

Sit-to-stand transitions may be an intervention target for reducing insulin resistance in breast cancer survivors, which may have favorable downstream effects on cancer prognosis.

Background

As wearable sensors/devices become increasingly popular to promote physical activity (PA), research is needed to examine how and which components of these devices people use to increase their PA levels.

Aims

(1) To assess usability and level of engagement with the Fitbit One and daily SMS-based prompts in a 6-week PA intervention, and (2) to examine whether use/ level of engagement with specific intervention components were associated with PA change.

Methods

Data were analyzed from a randomized controlled trial that compared (1) a wearable sensor/ device (Fitbit One) plus SMS-based PA prompts, and (2) Fitbit One only, among overweight/ obese adults (N = 67). We calculated average scores from Likert-type response items that assessed usability and level of engagement with device features (e.g., tracker, website, mobile app, and SMS-based prompts), and assessed whether such factors were associated with change in steps/day (using Actigraph GT3X+).

Results

Participants reported the Fitbit One was easy to use and the tracker helped to be more active. Those who used the Fitbit mobile app (36%) vs. those who did not (64%) had an increase in steps at 6-week follow-up, even after adjusting for previous web/app use: +545 steps/ day (SE = 265) vs. -28 steps/ day (SE = 242) (p = .04).

Conclusions

Level of engagement with the Fitbit One, particularly the mobile app, was associated with increased steps. Mobile apps can instantly display summaries of PA performance and could optimize self-regulation to activate change. More research is needed to determine whether such modalities might be cost-effective in future intervention research and practice.

RATIONALE & OBJECTIVE: People with end-stage kidney disease (ESKD) have very low physical activity, and the degree of inactivity is strongly associated with morbidity and mortality. We assessed the feasibility and effectiveness of a 12-week intervention coupling a wearable activity tracker (FitBit) and structured feedback coaching versus wearable activity tracker alone on changes in physical activity in hemodialysis patients. STUDY DESIGN: Randomized controlled trial. SETTING & PARTICIPANTS: 55 participants with ESKD receiving hemodialysis who were able to walk with or without assistive devices recruited from a single academic hemodialysis unit between January 2019 and April 2020. INTERVENTIONS: All participants wore a Fitbit Charge 2 tracker for a minimum of 12 weeks. Participants were randomly assigned 1:1 to a wearable activity tracker plus a structured feedback intervention versus the wearable activity tracker alone. The structured feedback group was counseled weekly on steps achieved after randomization. OUTCOME: The outcome was step count, and the main parameter of interest was the absolute change in daily step count, averaged per week, from baseline to completion of 12 weeks intervention. In the intention-to-treat analysis, mixed-effect linear regression analysis was used to evaluate change in daily step count from baseline to 12-weeks in both arms. RESULTS: Out of 55 participants, 46 participants completed the 12-week intervention (23 per arm). The mean age was 62 (± 14 SD) years; 44% were Black, and 36% were Hispanic. At baseline, step count (structured feedback intervention: 3,704 [1,594] vs wearable activity tracker alone: 3,808 [1,890]) and other participant characteristics were balanced between the arms. We observed a larger change in daily step count in the structured feedback arm at 12 weeks relative to use of the wearable activity tracker alone arm (Δ 920 [±580 SD] versus Δ 281 [±186 SD] steps; between-group difference Δ 639 [±538 SD] steps; P<0.05). LIMITATIONS: Single-center study and small sample size. CONCLUSION: This pilot randomized controlled trial demonstrated that structured feedback coupled with a wearable activity tracker led to a greater daily step count that was sustained over 12 weeks relative to a wearable activity tracker alone. Future studies are required to determine longer-term sustainability of the intervention and potential health benefits in hemodialysis patients. FUNDING: Grants from industry (Satellite Healthcare) and government (National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK). TRIAL REGISTRATION: Registered at ClinicalTrials.gov with study number NCT05241171.