Sleep and sedentary and active behaviors are linked to cardiovascular disease risk biomarkers, and across a 24-hour day, increasing time in 1 behavior requires decreasing time in another. We explored associations of reallocating time to sleep, sedentary behavior, or active behaviors with biomarkers. Data (n = 2,185 full sample; n = 923 fasting subanalyses) from the cross-sectional 2005-2006 US National Health and Nutrition Examination Survey were analyzed. The amounts of time spent in sedentary behavior, light-intensity activity, and moderate-to-vigorous physical activity (MVPA) were derived from ActiGraph accelerometry (ActiGraph LLC, Pensacola, Florida), and respondents reported their sleep duration. Isotemporal substitution modeling indicated that, independent of potential confounders and time spent in other activities, beneficial associations (P < 0.05) with cardiovascular disease risk biomarkers were associated with the reallocation of 30 minutes/day of sedentary time with equal time of either sleep (2.2% lower insulin and 2.0% lower homeostasis model assessment of β-cell function), light-intensity activity (1.9% lower triglycerides, 2.4% lower insulin, and 2.2% lower homeostasis model assessment of β-cell function), or MVPA (2.4% smaller waist circumference, 4.4% higher high-density lipoprotein cholesterol, 8.5% lower triglycerides, 1.7% lower glucose, 10.7% lower insulin, and 9.7% higher homeostasis model assessment of insulin sensitivity. These findings provide evidence that MVPA may be the most potent health-enhancing, time-dependent behavior, with additional benefit conferred from light-intensity activities and sleep duration when reallocated from sedentary time.

Background Myeloproliferative neoplasm (MPN) patients often report high symptom burden that persists despite the best available pharmacologic therapy. Meditation has gained popularity in recent decades as a way to manage cancer patient symptoms. Objective The aim of this study was to examine the feasibility of 2 different consumer-based meditation smartphone apps in MPN patients and to examine the limited efficacy of smartphone-based meditation on symptoms compared with an educational control group. Methods Patients (n=128) were recruited nationally through organizational partners and social media. Eligible and consented patients were enrolled into 1 of 4 groups, 2 of which received varying orders of 2 consumer-based apps (10% Happier and Calm ) and 2 that received one of the apps alone for the second 4 weeks of the 8-week intervention after an educational control condition. Participants were asked to perform 10 min of meditation per day irrespective of the app and the order in which they received the apps. Feasibility outcomes were measured at weeks 5 and 9 with a Web-based survey. Feasibility outcomes were acceptability, demand, and limited efficacy for depression, anxiety, pain intensity, sleep disturbance, sexual function, quality of life, global health, and total symptom burden. Results A total of 128 patients were enrolled across all 4 groups, with 73.4% (94/128) patients completing the intervention. Of the participants who completed the 10% Happier app, 61% (46/76) enjoyed it, 66% (50/76) were satisfied with the content, and 77% (59/76) would recommend to others. Of those who completed the Calm app, 83% (56/68) enjoyed it, 84% (57/68) were satisfied with the content, and 97% (66/68) would recommend to others. Of those who completed the educational control, 91% (56/61) read it, 87% (53/61) enjoyed it, and 71% (43/61) learned something. Participants who completed the 10% Happier app averaged 31 (SD 33) min/week; patients completing the Calm app averaged 71 (SD 74) min/week. 10% Happier app participants saw small effects on anxiety ( P <.001 d =−0.43), depression ( P =.02; d =−0.38), sleep disturbance ( P =.01; d =−0.40), total symptom burden ( P =.13; d =−0.27), and fatigue ( P =.06; d =−0.30), and moderate effects on physical health ( P <.001; d =0.52). Calm app participants saw small effects on anxiety ( P =.29; d =−0.22...

An infrequently studied question is how diverse combinations of built environment (BE) features relate to physical activity (PA) for older adults. We derived patterns of Geographical Information Systems- (GIS) measured BE features and explored how they accounted for differences in objective and self-reported PA, sedentary time, and BMI in a sample of older adults. Senior Neighborhood Quality of Life Study participants (N=714, aged 66–97 years, 52.1% women, 29.7% racial/ethnic minority) were sampled in 2005–2008 from the Seattle-King County, WA and Baltimore, MD-Washington, DC regions. Participants’ home addresses were geocoded, and net residential density, land use mix, retail floor area ratio, intersection density, public transit density, and public park and private recreation facility density measures for 1-km network buffers were derived. Latent profile analyses (LPAs) were estimated from these GIS-based measures. In multilevel regression models, profiles were compared on accelerometer-measured moderate-to-vigorous PA (MVPA) and sedentary time and self-reported PA, adjusting for covariates and clustering. Analyses were conducted in 2014–2015. LPAs yielded three profiles: low walkability/transit/recreation (L-L-L); mean walkability/transit/recreation (M-M-M); and high walkability/transit/recreation (H-H-H). Three PA outcomes were more favorable in the HHH than the LLL profile group (difference of 7.2 minutes/day for MVPA, 97.8 minutes/week for walking for errands, and 79.2 minutes/week for walking for exercise; all ps < 0.02). The most and least activity-supportive BE profiles showed greater differences in older adults’ PA than did groupings based solely on a 4-component walkability index, suggesting that diverse BE features are important for healthy aging.

BackgroundThe purpose of this study is to determine the feasibility of three widely used wearable sensors in research settings for 24 h monitoring of sleep, sedentary, and active behaviors in middle-aged women.MethodsParticipants were 21 inactive, overweight (M Body Mass Index (BMI) = 29.27 ± 7.43) women, 30 to 64 years (M = 45.31 ± 9.67). Women were instructed to wear each sensor on the non-dominant hip (ActiGraph GT3X+), wrist (GENEActiv), or upper arm (BodyMedia SenseWear Mini) for 24 h/day and record daily wake and bed times for one week over the course of three consecutive weeks. Women received feedback about their daily physical activity and sleep behaviors. Feasibility (i.e., acceptability and demand) was measured using surveys, interviews, and wear time.ResultsWomen felt the GENEActiv (94.7 %) and SenseWear Mini (90.0 %) were easier to wear and preferred the placement (68.4, 80 % respectively) as compared to the ActiGraph (42.9, 47.6 % respectively). Mean wear time on valid days was similar across sensors (ActiGraph: M = 918.8 ± 115.0 min; GENEActiv: M = 949.3 ± 86.6; SenseWear: M = 928.0 ± 101.8) and well above other studies using wake time only protocols. Informational feedback was the biggest motivator, while appearance, comfort, and inconvenience were the biggest barriers to wearing sensors. Wear time was valid on 93.9 % (ActiGraph), 100 % (GENEActiv), and 95.2 % (SenseWear) of eligible days. 61.9, 95.2, and 71.4 % of participants had seven valid days of data for the ActiGraph, GENEActiv, and SenseWear, respectively.ConclusionTwenty-four hour monitoring over seven consecutive days is a feasible approach in middle-aged women. Researchers should consider participant acceptability and demand, in addition to validity and reliability, when choosing a wearable sensor. More research is needed across populations and study designs.

Characterizing neighborhood environments in relation to physical activity is complex. Latent profiles of parents’ perceptions of neighborhood characteristics were examined in relation to accelerometer-measured moderate-to-vigorous physical activity (MVPA) among 678 children (ages 6-12) in two US regions. Neighborhood environment profiles derived from walkability, transit access, aesthetics, crime and traffic safety, pedestrian infrastructure, and recreation/park access were created for each region. The San Diego County profile lowest on walkability and recreation/park access was associated with an average of 13 fewer minutes/day of children’s out-of-school MVPA compared to profiles higher on walkability and recreation/park access. Seattle/King County profiles did not differ on children’s MVPA. Neighborhood environment profiles were associated with children’s MVPA in one region, but results were inconsistent across regions.