These varying levels of discordance imply that comparisons of self-reported activity among groups defined by (or substantially varying by) educational attainment or marital status should be done with considerable caution as observed differences may be due, in part, to systematic, differential measurement biases among groups.

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Purpose Endometrial cancer is strongly linked to obesity and inactivity; however, increased physical activity has important benefits even in the absence of weight loss. Resistance (strength) training can deliver these benefits; yet few women participate in resistance exercise. The purpose of this study was to describe both physiological and functional changes following a home-based strength training intervention. Methods Forty post-treatment endometrial cancer survivors within 5 years of diagnosis were enrolled in a pilot randomized trial, comparing twice-weekly home-based strength exercise to wait list control. Participants conducted the exercises twice per week for 10 supervised weeks with 5 weeks of follow-up. Measures included DXA-measured lean mass, functional fitness assessments, blood biomarkers, and quality of life outcomes. Results On average, participants were 60.9 years old (SD = 8.7) with BMI of 39.9 kg/m 2 (SD = 15.2). At baseline, participants had 51.2% (SD = 6.0) body fat, which was not different between groups. Improvements were seen in the 30-s chair sit to stand (d = .99), the 30-s arm curl (d = .91), and the 8-ft up-and-go test (d = .63). No changes were measured for HbA1c or C-reactive protein. No changes were observed for flexibility (chair sit and reach, back scratch tests), 6-min walk test, maximum handgrip test, anxiety, depression, fatigue, or self-efficacy for exercise. Conclusions Home-based muscle-strengthening exercise led to favorable and clinically relevant improvements in 3 of 7 physical function assessments. Physical function, body composition, blood biomarkers, and patient-reported outcomes were feasible to measure. These fitness improvements were observed over a relatively short time frame of 10 weeks.

Introduction/PurposeBecause of the coronavirus disease 2019 (COVID-19) pandemic, many in-person cancer exercise and rehabilitation programs necessarily transitioned to virtual formats to meet the needs of individuals living with and beyond cancer. The purpose of this study was to qualitatively assess program-level facilitators and barriers to virtual exercise program implementation and to identify preferred strategies to overcome implementation barriers.MethodsU.S.-based virtual cancer exercise and rehabilitation programs were recruited from professional networks via an e-mailed screening questionnaire. Eligible programs identified a point of contact for a one-on-one semistructured interview to discuss program-level barriers and facilitators to implementing virtual exercise programs. Interview transcript analysis was conducted via inductive coding techniques using NVivo software. Barriers were categorized according to the Consolidated Framework for Implementation Research, and a prioritized list of strategies to support implementation was created by mapping barriers to a list of Expert Recommendations for Implementing Change.ResultsOf the 41 unique responses received, 24 program representatives completed semistructured interviews. Interviewees represented individual programs, community-based programs, and hospital-based cancer exercise/rehabilitation programs. Analysis showed high correlation between facilitators and barriers by program type, with both program- and individual-level strategies used to implement exercise programs virtually. Strategies that ranked highest to support implementation include promoting program adaptability, building a coalition of stakeholders and identifying program champions, developing an implementation blueprint, altering organizational incentives and allowances, providing education across stakeholder groups, and accessing funding.ConclusionsLearning from the transition of cancer exercise and rehabilitation programs to virtual formats due to the COVID-19 pandemic, we identify program-level barriers and facilitators encountered in the implementation of virtual programs and highlight implementation strategies that are most relevant to overcome common barriers. We present a roadmap for programs to use these strategies for future work in virtual exercise and rehabilitation program implementation.

Background Activity trackers may motivate individuals to engage in healthy behaviors. They are also used in research and may help manage chronic conditions related to lifestyle (1). Traditional trackers that require a separate chest strap and work like an electrocardiograph are being supplemented with other types of trackers. One type is a wrist-worn tracker with a lightemitting diode. It measures the heart rate from tiny changes in skin blood volume by using light reflected from the skin. These new devices are unobtrusive and appropriate for continuous, long-term wear. Although previous studies have shown that they are generally accurate for measuring the number of steps a person takes, less is known about their accuracy when measuring heart rate (2-4). Objective To determine the accuracy of the heart rate measured by light-emitting diode-dependent, wrist-worn activity trackers. Methods We studied 4 commercial, wrist-worn activity trackers that measure the heart rate by using light-emitting diodes. Study participants were 40 healthy consenting adults aged 30 to 65 years without cardiovascular conditions. For each participant, we placed 2 trackers on each wrist in random order by right versus left wrist and by proximal versus distal location on the

IMPORTANCEHigher amounts of physical activity are associated with increased longevity. However, whether different leisure time physical activity types are differentially associated with mortality risk is not established. OBJECTIVES To examine whether participation in equivalent amounts of physical activity (7.5 to <15 metabolic equivalent of task [MET] hours per week) through different activity types is associated with mortality risk and to investigate the shape of the dose-response association. DESIGN, SETTING, AND PARTICIPANTS Participants in this cohort were respondents from the National Institutes of Health-AARP Diet and Health Study who completed the follow-up questionnaire between 2004 and 2005. This questionnaire collected data on weekly durations of different types of physical activities. Mortality was ascertained through December 31, 2019. EXPOSURES MET hours per week spent participating in the following activities: running, cycling, swimming, other aerobic exercise, racquet sports, golf, and walking for exercise. MAIN OUTCOMES AND MEASURES All-cause, cardiovascular, and cancer mortality. Separate multivariable-adjusted Cox proportional hazards regression models were fitted to estimate hazard ratios (HRs) and 95% CIs of mortality for each of the 7 types of leisure time physical activities, as well as the sum of these activities. RESULTS A total of 272 550 participants (157 415 men [58%]; mean [SD] age at baseline, 70.5 [5.4] years [range, 59-82 years]) provided information on types of leisure time activity, and 118 153 (43%)died during a mean (SD) follow-up of 12.4 (3.9) years. In comparison with those who did not participate in each activity, 7.5 to less than 15 MET hours per week of racquet sports (HR, 0.84; 95% CI, 0.75-0.93) and running (HR, 0.85; 95% CI, 0.78-0.92) were associated with the greatest relative risk reductions for all-cause mortality, followed by walking for exercise (HR, 0.91; 95% CI, 0.89-0.93), other aerobic activity (HR, 0.93; 95% CI, 0.90-0.95), golf (HR, 0.93; 95% CI, 0.90-0.97), swimming (HR, 0.95; 95% CI, 0.92-0.98), and cycling (HR, 0.97; 95% CI, 0.95-0.99). Each activity showed a curvilinear dose-response association with mortality risk; low MET hours per week of physical activity for any given activity type were associated with a large reduction in mortality risk, with diminishing returns for each increment in activity thereafter. Associations were similar for cardiovascular and cancer mortality. CONCLUSIONS AND RELEVANCEThis cohort study of older individuals found differences between different types of leisure time activities and mortality risk, but there were significant associations between participating in 7.5 to less than 15 MET hours per week of any activity and mortality risk.

ObjectivePhysical activity plays a key role in cancer survivorship. The purpose of this investigation was to (a) describe the post-surgical physical activity trajectories of endometrial (n = 65) and ovarian (n = 31) cancer patients and (b) identify clinical and demographic predictors of physical activity over time.Methods96 participants wore an Actiwatch accelerometer for three days at each of three time points (one week, one month and four months) after surgical intervention for their endometrial or ovarian cancer diagnosis. Analyses were conducted using linear mixed effects regression modeling in SAS 9.4.ResultsFor both tumor types, although physical activity levels increased with time after surgery, even at four months patients were performing only a small fraction of the 150 minutes of recommended weekly moderate to vigorous physical activity. At 1 week, subjects were completing on average 14 minutes/week (SD = 4) of moderate-to-vigorous physical activity, compared to 14 minutes/week (SD = 2) of moderate-to-vigorous physical activity at four months post-surgery (p < .05). Better self-rated health was associated with higher physical activity (p = 0.02) in endometrial cancer survivors only. BMI, age, surgery type and use of neoadjuvant chemotherapy were not associated with activity over time.ConclusionsOur findings suggest that physical activity levels are different for those with better self-rated health, but those individuals are still insufficiently active. This study adds new information describing the trajectories and variables that influence physical activity in gynecologic cancer survivors after surgery and highlights the need for health promotion interventions in this population.

Background Activity trackers are now ubiquitous in certain populations, with potential applications for health promotion and monitoring and chronic disease management. Understanding the accuracy of this technology is critical to the appropriate and productive use of wearables in health research. Although other peer-reviewed validations have examined other features (eg, steps and heart rate), no published studies to date have addressed the accuracy of automatic activity type detection and duration accuracy in wearable trackers. Objective The aim of this study was to examine the ability of 4 commercially available wearable activity trackers (Fitbits Flex 2, Fitbit Alta HR, Fitbit Charge 2, and Garmin Vívosmart HR), in a controlled setting, to correctly and automatically identify the type and duration of the physical activity being performed. Methods A total of 8 activity types, including walking and running (on both a treadmill and outdoors), a run embedded in walking bouts, elliptical use, outdoor biking, and pool lap swimming, were tested by 28 to 34 healthy adult participants (69 total participants who participated in some to all activity types). Actual activity type and duration were recorded by study personnel and compared with tracker data using descriptive statistics and mean absolute percent error (MAPE). Results The proportion of trials in which the activity type was correctly identified was 93% to 97% (depending on the tracker) for treadmill walking, 93% to 100% for treadmill running, 36% to 62% for treadmill running when preceded and followed by a walk, 97% to 100% for outdoor walking, 100% for outdoor running, 3% to 97% for using an elliptical, 44% to 97% for biking, and 87.5% for swimming. When activities were correctly identified, the MAPE of the detected duration versus the actual activity duration was between 7% and 7.9% for treadmill walking, 8.7% and 144.8% for treadmill running, 23.6% and 28.9% for treadmill running when preceded and followed by a walk, 4.9% and 11.8% for outdoor walking, 5.6% and 9.6% for outdoor running, 9.7% and 13% for using an elliptical, 9.5% and 17.7% for biking, and was 26.9% for swimming. Conclusions In a controlled setting, wearable activity trackers provide accurate recognition of the type of some common physical activities, especially outdoor walking and running and walking on a treadmill. The accuracy of measurement of activity duration varied considerably by activity type and tracker model and was poor for complex sets of activity, such as a run embedded within 2 walking segments.