Background Many older adults spend the majority of their waking hours sitting, which increases their risk of chronic diseases. Given the challenges that many older adults face when engaging in moderate-to-vigorous physical activity, understanding the health benefits of decreasing sitting time and increasing the number of sit-to-stand transitions is needed to address this growing public health concern. Objective The aim of this 3-arm randomized controlled trial is to investigate how changes in sitting time and brief sit-to-stand transitions impact biomarkers of healthy aging and physical, emotional, and cognitive functioning compared with a healthy attention control arm. Methods Sedentary and postmenopausal women (N=405) will be recruited and randomly assigned to 1 of the 3 study conditions for 3 months: healthy living attention control (Healthy Living), reduce sitting time (Reduce Sitting), and increase sit-to-stand transitions (Increase Transitions). Assessments conducted at baseline and 3 months included fasting blood draw, blood pressure, anthropometric measurements, physical functioning, cognitive testing, and 7 days of a thigh-worn accelerometer (activPAL) and a hip-worn accelerometer (ActiGraph). Blood-based biomarkers of healthy aging included those associated with glycemic control (glycated hemoglobin, fasting plasma insulin and glucose, and homeostatic model assessment of insulin resistance). Results Recruitment began in May 2018. The intervention is ongoing, with data collection expected to continue through the end of 2022. Conclusions The Rise for Health study is designed to test whether 2 different approaches to interrupting sitting time can improve healthy aging in postmenopausal women. Results from this study may inform the development of sedentary behavior guidelines and interventions to reduce sitting time in older adults. Trial Registration ClinicalTrials.gov NCT03473145; https://clinicaltrials.gov/ct2/show/NCT03473145 International Registered Report Identifier (IRRID) DERR1-10.2196/28684
TPS6626 Background: Exercise can alleviate side effects of chemotherapy, improve quality of life (QOL), and positively impact disease specific and overall survival. Despite the benefits of physical activity (PA), many patients’ activity levels decrease during chemotherapy. Wearable devices, such as the Fitbit, can provide insight into patterns of activity, and help encourage behavior change. The aims of this study are: 1) determine the feasibility/acceptability of using a Fitbit to measure PA and sleep throughout chemotherapy for breast cancer; 2) describe patterns of PA, sedentary time, and sleep during chemotherapy; 3) explore associations of activity and sleep with QOL. Methods: Non-metastatic breast cancer patients from UCSF and UCSD will be enrolled prior to starting chemotherapy. Eligibility criteria include ability to speak/read English, walk unassisted, and access to internet or Fitbit compatible smart phone. Patients sign informed consent, receive a Fitbit Charge HR and guidance on how to use the device. Patients are instructed to wear the Fitbit throughout their adjuvant or neoadjuvant chemotherapy and 6 months post therapy and to sync the Fitbit at least weekly. Patients complete surveys at start, midpoint, end, and 6 months post chemotherapy. Questionnaires include PROMIS anxiety, depression, physical function, fatigue, cognitive function, social roles, comfort with technology and usefulness of the Fitbit. Fitabase database collects minute level activity, sleep, and heart rate. To assess feasibility, we will evaluate if a participant wears FitBit for at least 10 hour per day for ≥ 80% of the days during chemotherapy. We will use mixed effects regression models to assess patterns of PA and associations between activity and QOL. All models will include activity time and Fitbit wear time and will control for the potential confounding effects of age and other demographic or clinical variables. As of February 6 2017, 48 out of a planned 80 patients are enrolled. Acknowledgment: Athena Breast Health Network investigators and patients; support at UCSD by NCI (U54 CA155435-01) and by gift from Carol Vassiliadis and family; NCI grant K07CA181323 to SH; UCSF M Zion Health Fund Award, GBCTB unrestricted funding and TriValley SOCKS to MM. Clinical trial information: NCT03041545.
Background : Machine learning has been used for classification of physical behavior bouts from hip-worn accelerometers; however, this research has been limited due to the challenges of directly observing and coding human behavior “in the wild.” Deep learning algorithms, such as convolutional neural networks (CNNs), may offer better representation of data than other machine learning algorithms without the need for engineered features and may be better suited to dealing with free-living data. The purpose of this study was to develop a modeling pipeline for evaluation of a CNN model on a free-living data set and compare CNN inputs and results with the commonly used machine learning random forest and logistic regression algorithms. Method : Twenty-eight free-living women wore an ActiGraph GT3X+ accelerometer on their right hip for 7 days. A concurrently worn thigh-mounted activPAL device captured ground truth activity labels. The authors evaluated logistic regression, random forest, and CNN models for classifying sitting, standing, and stepping bouts. The authors also assessed the benefit of performing feature engineering for this task. Results : The CNN classifier performed best (average balanced accuracy for bout classification of sitting, standing, and stepping was 84%) compared with the other methods (56% for logistic regression and 76% for random forest), even without performing any feature engineering. Conclusion : Using the recent advancements in deep neural networks, the authors showed that a CNN model can outperform other methods even without feature engineering. This has important implications for both the model’s ability to deal with the complexity of free-living data and its potential transferability to new populations.
BACKGROUND Sedentary behavior among breast cancer survivors is associated with increased risk of poor physical function and worse quality of life. While moderate to vigorous physical activity can improve outcomes for cancer survivors, many are unable to engage in that intensity of physical activity. Decreasing sitting time may be a more feasible behavioral target to potentially mitigate the impact of cancer and its treatments. OBJECTIVE The purpose of this study was to investigate the feasibility and preliminary impact of an intervention to reduce sitting time on changes to physical function and quality of life in breast cancer survivors, from baseline to a 3-month follow-up. METHODS Female breast cancer survivors with self-reported difficulties with physical function received one-on-one, in-person personalized health coaching sessions aimed at reducing sitting time. At baseline and follow-up, participants wore the activPAL (thigh-worn accelerometer; PAL Technologies) for 3 months and completed physical function tests (4-Meter Walk Test, Timed Up and Go, and 30-Second Chair Stand) and Patient-Reported Outcomes Measurement Information System (PROMIS) self-reported outcomes. Changes in physical function and sedentary behavior outcomes were assessed by linear mixed models. RESULTS On average, participants (n=20) were aged 64.5 (SD 9.4) years; had a BMI of 30.4 (SD 4.5) kg/m<sup>2</sup>; and identified as Black or African American (n=3, 15%), Hispanic or Latina (n=4, 20%), and non-Hispanic White (n=14, 55%). Average time since diagnosis was 5.8 (SD 2.2) years with participants receiving chemotherapy (n=8, 40%), radiotherapy (n=18, 90%), or endocrine therapy (n=17, 85%). The intervention led to significant reductions in sitting time: activPAL average daily sitting time decreased from 645.7 (SD 72.4) to 532.7 (SD 142.1; β=–112.9; <i>P</i>=.001) minutes and average daily long sitting bouts (bout length ≥20 min) decreased from 468.3 (SD 94.9) to 366.9 (SD 150.4; β=–101.4; <i>P</i>=.002) minutes. All physical function tests had significant improvements: on average, 4-Meter Walk Test performance decreased from 4.23 (SD 0.95) to 3.61 (SD 2.53; β=–.63; <i>P</i>=.002) seconds, Timed Up and Go performance decreased from 10.30 (SD 3.32) to 8.84 (SD 1.58; β=–1.46; <i>P</i>=.003) seconds, and 30-Second Chair Stand performance increased from 9.75 (SD 2.81) to 13.20 completions (SD 2.53; β=3.45; <i>P</i><.001). PROMIS self-reported physical function score improved from 44.59 (SD 4.40) to 47.12 (SD 5.68; β=2.53; <i>P</i>=.05) and average fatigue decreased from 52.51 (SD 10.38) to 47.73 (SD 8.43; β=–4.78; <i>P</i>=.02). CONCLUSIONS This 3-month pilot study suggests that decreasing time spent sitting may be helpful for breast cancer survivors experiencing difficulties with physical function and fatigue. Reducing sitting time is a novel and potentially more feasible approach to improving health and quality of life in cancer survivors.
The naming extensions to the Generic Security Service Application Programming Interface (GSS-API) provide a mechanism for applications to discover authorization and personalization information associated with GSS-API names.The Extensible Authentication Protocol GSS-API mechanism allows an Authentication, Authorization, and Accounting (AAA) peer to provide authorization attributes alongside an authentication response.It also supplies mechanisms to process Security Assertion Markup Language (SAML) messages provided in the AAA response.This document describes how to use the Naming Extensions API to access that information.
Background: No physical activity (PA) interventions have specifically targeted Latino men despite marked health disparities in this group. Therefore, we explored the feasibility of designing a PA intervention for Latino men. Methods: We conducted six qualitative interviews with Latino men and used their feedback to modify an existing PA intervention, then conducted a 12-week demonstration trial of the adapted intervention. Results: Themes from interviews included work and family conflicts and preferring team sports. In the demonstration trial of the modified intervention, participants (N = 10) increased PA from 1.3 minutes/week (SD = 4.75) at baseline to 125.5(SD = 154.86) at follow-up (p < .05). Retention was high and participants expressed enthusiasm for the program. Conclusions: Existing interventions could be effectively modified to target physical activity in Latino men.
Abstract Background Obesity is a major health concern for breast cancer survivors, being associated with high recurrence and reduced efficacy during cancer treatment. Metformin treatment is associated with reduced breast cancer incidence, recurrence and mortality. To better understand the underlying mechanisms through which metformin may reduce recurrence, we aimed to conduct metabolic profiling of overweight/obese breast cancer survivors before and after metformin treatment. Methods Fasting plasma samples from 373 overweight or obese breast cancer survivors randomly assigned to metformin (n = 194) or placebo (n = 179) administration were collected at baseline, after 6 months (Reach For Health trial), and after 12 months (MetBreCS trial). Archival samples were concurrently analyzed using three complementary methods: untargeted LC–QTOF-MS metabolomics, targeted LC–MS metabolomics (AbsoluteIDQ p180, Biocrates), and gas chromatography phospholipid fatty acid assay. Multivariable linear regression models and family-wise error correction were used to identify metabolites that significantly changed after metformin treatment. Results Participants (n = 352) with both baseline and study end point samples available were included in the analysis. After adjusting for confounders such as study center, age, body mass index and false discovery rate, we found that metformin treatment was significantly associated with decreased levels of citrulline, arginine, tyrosine, caffeine, paraxanthine, and theophylline, and increased levels of leucine, isoleucine, proline, 3-methyl-2-oxovalerate, 4-methyl-2-oxovalerate, alanine and indoxyl-sulphate. Long-chain unsaturated phosphatidylcholines (PC ae C36:4, PC ae C38:5, PC ae C36:5 and PC ae C38:6) were significantly decreased with the metformin treatment, as were phospholipid-derived long-chain n-6 fatty acids. The metabolomic profiles of metformin treatment suggest change in specific biochemical pathways known to impair cancer cell growth including activation of CYP1A2, alterations in fatty acid desaturase activity, and altered metabolism of specific amino acids, including impaired branched chain amino acid catabolism. Conclusions Our results in overweight breast cancer survivors identify new metabolic effects of metformin treatment that may mechanistically contribute to reduced risk of recurrence in this population and reduced obesity-related cancer risk reported in observational studies. Trial registration ClinicalTrials.gov identifier: NCT01302379 and EudraCT Protocol #: 2015-001001-14.
A novel line of research has emerged, suggesting that daily feeding-fasting schedules that are synchronized with sleep-wake cycles have metabolic implications that are highly relevant to breast cancer. We examined associations of nighttime fasting duration with biomarkers of breast cancer risk among women in the 2009-2010 U.S. National Health and Nutrition Examination Survey.
