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This investigation examined how dispositional compassion and empathy were associated with prosocial behaviors and attitudes in the SARS-CoV-2 pandemic. Every two weeks from March 22 to June 15, 2020, we fielded a survey to a new cohort of adults in the U.S. Compassion related to whether one stayed home to protect others, more hours spent staying home and distancing from others, and more frequent mask wearing in public, in the past two weeks. Compassion also related to greater perceived ability to help others who were negatively affected. Empathy related to more endorsement of understanding others' fear of COVID-19, and less endorsement of the view that others were overreacting to COVID-19. There was an interaction between empathy and political ideology, suggesting that empathy may matter for understanding others' fear among those with more conservative-leaning beliefs. Empathy also related to greater understanding that sheltering-in-place helps prevent the spread of COVID-19. Findings suggest that messaging and interventions to increase compassion and empathy may promote public health behaviors during a pandemic regardless of political orientation. Targeting empathy may be one way to reach individuals with more conservative political beliefs, and it is important to use an evidence-based approach accounting for political party differences in motivated reasoning. [ABSTRACT FROM AUTHOR]

The health effects of sedentary behavior (SB) may be moderated by SB accumulation patterns (e.g., in prolonged bouts). These patterns are challenging to assess thoroughly and interpretably. Purpose: The purpose of this study is to introduce SB profiles (i.e., groups of similar SB accumulation patterns) as a new approach to pattern-focused SB research. Methods: Data came from the National Health and Nutrition Examination Survey (2003–2006). The SB bouts were determined from hip-worn accelerometer data, and k-medoid clustering was used to define three SB profiles (interrupted, intermediate, and prolonged). These were used as the exposure in logistic regression models to examine odds ratios (OR) of having high (>20%) predicted-10-yr risk of cardiovascular disease (CVD). For comparison, the models were also fitted using standard metrics (i.e., tertiles of mean SB bout duration and daily total SB time). Results: Those with interrupted profile (n = 1740) were typically sedentary ~32% of the time, in bouts ≤15 min. Those with intermediate profile (n = 2453) were typically sedentary ~47% of the time, in bouts ≤20 min. Those with prolonged profile (n = 1302) were typically sedentary ~61% of the time, frequently in bouts >20 min. The fully adjusted model showed that high CVD risk was more common for the intermediate (OR, 1.87) and prolonged (OR, 4.65) profiles than the interrupted profile (all P < 0.001). For standard metrics, OR ranged from 1.46 (middle tertile of daily total SB time) to 4.11 (upper tertile of mean bout duration) with all P < 0.002. Conclusions: The SB profiles represent a promising new avenue for understanding and combating adverse SB trends. The value of the approach was highlighted by the strong associations with CVD risk. [ABSTRACT FROM AUTHOR]

The article suggests a COVID-19 containment strategy which identifies COVID-19 cases and social groups at high risk of transmission (HRT). Topics discussed include the implication of superspreading events for containment strategies and prioritizing and deploying resources, benefit of the explicit definition of transmission risk in guidance for COVID-19 case investigation and contract tracing, and usefulness of a framework for HRT social group events investigation for future pandemics.

Background: Prior research examining the relationship between cannabis use, sedentary behavior, and physical activity has generated conflicting findings, potentially due to biases in the self-reported measures used to assess physical activity. This study aimed to more precisely explore the relationship between cannabis use and sedentary behavior/physical activity using objective measures. Methods: Data were obtained from the 2005–2006 National Health and Nutrition Examination Survey. A total of 2,092 participants (ages 20–59; 48.8% female) had accelerometer-measured sedentary behavior, light physical activity, and moderate-to-vigorous physical activity. Participants were classified as light, moderate, frequent, or non-current cannabis users depending on how often they used cannabis in the previous 30 days. Multivariable linear regression estimated minutes in sedentary behavior/physical activity by cannabis use status. Logistic regression modeled self-reported moderate-to-vigorous physical activity in relation to current cannabis use. Results: Fully adjusted regression models indicated that current cannabis users' accelerometer-measured sedentary behavior did not significantly differ from non-current users. Frequent cannabis users engaged in more physical activity than non-current users. Light cannabis users had greater odds of self-reporting physical activity compared to non-current users. Conclusions: This study is the first to evaluate the relationship between cannabis use and accelerometer-measured sedentary behavior and physical activity. Such objective measures should be used in other cohorts to replicate our findings that cannabis use is associated with greater physical activity and not associated with sedentary behavior in order to fully assess the potential public health impact of increases in cannabis use. [ABSTRACT FROM AUTHOR]

Objective: To evaluate whether sedentary time (ST) and/or sedentary behavior patterns are related to incident diabetes in the U.S.'s oldest age-groups.Research Design and Methods: Women without physician-diagnosed diabetes (n = 4,839, mean ± SD age = 79 ± 7 years) wore accelerometers for ≥4 days and were followed up to 6 years for self-reported newly diagnosed diabetes requiring treatment with medications. Hazard ratios (HRs) for incident diabetes were estimated across quartiles of accelerometer-measured ST and mean bout duration with use of Cox proportional hazards models. We conducted isotemporal substitution analyses using Cox regression and tested associations with risk for diabetes after statistically replacing ST with light physical activity (PA) or moderate-to-vigorous PA (MVPA) and after replacing light PA with MVPA.Results: During 20,949 person-years, 342 diabetes cases were identified. Women in ST quartile (Q)2, Q3, and Q4 (vs. Q1) had incident diabetes HR 1.20 (95% CI 0.87-1.65), 1.33 (0.97-1.82), and 1.21 (0.86-1.70); Ptrend = 0.04. Respective HRs following additional adjustment for BMI and MVPA were 1.04 (95% CI 0.74-1.47), 1.04 (0.72-1.50), and 0.85 (0.56-1.29); Ptrend = 0.90. Fully adjusted isotemporal substitution results indicated that each 30 min of ST replaced with MVPA (but not light PA) was associated with 15% lower risk for diabetes (HR 0.85 [95% CI 0.75-0.96]; P = 0.01); the HR for replacing 30 min of light PA with MVPA was 0.85 (95% CI 0.73-0.98); P = 0.03. Mean bout duration was not associated with incident diabetes.Conclusions: Statistically replacing ST or light PA with MVPA was associated with lower diabetes risk in older women. While reducing ST is important for several health outcomes, results indicate that to reduce diabetes risk among older adults, the primary public health focus should be on increasing MVPA. [ABSTRACT FROM AUTHOR]

Background: Sedentary behavior (SB) is linked to negative health outcomes in older adults. Most studies use summary values, e.g., total sedentary minutes/day. Diurnal timing of SB accumulation may further elucidate SB-health associations. Methods: Six thousand two hundred four US women (mean age = 79 ± 7; 50% White, 34% African-American) wore accelerometers for 7-days at baseline, yielding 41,356 person-days with > 600 min/day of data. Annual follow-up assessments of health, including physical functioning, were collected from participants for 6 years. A novel two-phase clustering procedure discriminated participants' diurnal SB patterns: phase I grouped day-level SB trajectories using longitudinal k-means; phase II determined diurnal SB patterns based on proportion of phase I trajectories using hierarchical clustering. Mixed models tested associations between SB patterns and longitudinal physical functioning, adjusted for covariates including total sedentary time. Effect modification by moderate-vigorous-physical activity (MVPA) was tested. Results: Four diurnal SB patterns were identified: p1 = high-SB-throughout-the-day; p2 = moderate-SB-with-lower-morning-SB; p3 = moderate-SB-with-higher-morning-SB; p4 = low-SB-throughout-the-day. High MVPA mitigated physical functioning decline and correlated with better baseline and 6-year trajectory of physical functioning across patterns. In low MVPA, p2 had worse 6-year physical functioning decline compared to p1 and p4. In high MVPA, p2 had similar 6-year physical functioning decline compared to p1, p3, and p4. Conclusions: In a large cohort of older women, diurnal SB patterns were associated with rates of physical functioning decline, independent of total sedentary time. In particular, we identified a specific diurnal SB subtype defined by less SB earlier and more SB later in the day, which had the steepest decline in physical functioning among participants with low baseline MVPA. Thus, diurnal timing of SB, complementary to total sedentary time and MVPA, may offer additional insights into associations between SB and physical health, and provide physicians with early warning of patients at high-risk of physical function decline. [ABSTRACT FROM AUTHOR]

Background: Evidence that higher sedentary time is associated with higher risk for cardiovascular disease (CVD) is based mainly on self-reported measures. Few studies have examined whether patterns of sedentary time are associated with higher risk for CVD.Methods: Women from the Objective Physical Activity and Cardiovascular Health (OPACH) Study (n=5638, aged 63-97, mean age=79±7) with no history of myocardial infarction (MI) or stroke wore accelerometers for 4-to-7 days and were followed for up to 4.9 years for CVD events. Average daily sedentary time and mean sedentary bout duration were the exposures of interest. Cox regression models estimated hazard ratios (HR) and 95% confidence intervals (CI) for CVD using models adjusted for covariates and subsequently adjusted for potential mediators (body mass index (BMI), diabetes, hypertension, and CVD-risk biomarkers [fasting glucose, high-density lipoprotein, triglycerides, and systolic blood pressure]). Restricted cubic spline regression characterized dose-response relationships.Results: There were 545 CVD events during 19,350 person-years. Adjusting for covariates, women in the highest (≥ ~11 hr/day) vs. the lowest (≤ ~9 hr/day) quartile of sedentary time had higher risk for CVD (HR=1.62; CI=1.21-2.17; p-trend <0.001). Further adjustment for potential mediators attenuated but did not eliminate significance of these associations (p-trend<.05, each). Longer vs. shorter mean bout duration was associated with higher risks for CVD (HR=1.54; CI=1.27-2.02; p-trend=0.003) after adjustment for covariates. Additional adjustment for CVD-risk biomarkers attenuated associations resulting in a quartile 4 vs. quartile 1 HR=1.36; CI=1.01-1.83; p-trend=0.10). Dose-response associations of sedentary time and bout duration with CVD were linear (P-nonlinear >0.05, each). Women jointly classified as having high sedentary time and long bout durations had significantly higher risk for CVD (HR=1.34; CI=1.08-1.65) than women with both low sedentary time and short bout duration. All analyses were repeated for incident coronary heart disease (MI or CVD death) and associations were similar with notably stronger hazard ratios.Conclusions: Both high sedentary time and long mean bout durations were associated in a dose-response manner with increased CVD risk in older women, suggesting that efforts to reduce CVD burden may benefit from addressing either or both component(s) of sedentary behavior. [ABSTRACT FROM AUTHOR]

Background: High amounts of time spent sitting can increase cardiovascular disease risk and are deleteriously associated cardio-metabolic risk biomarkers. Though evidence suggests that accruing sitting time in prolonged periods may convey additional risk, verification using high-quality measures is needed. We examined this issue in adults from the Australian Diabetes, Obesity and Lifestyle Study, using accurate measures of sitting accumulation. Methods: In 2011/12, 739 adults aged 36 to 89 years (mean±SD 58±10 years) wore activPAL3™ monitors (which provide accurate objective measures of sitting); 678 provided ≥4 valid days of monitor data and complete cardio-metabolic biomarker and confounder data. Multivariable linear regression models examined associations of sitting time, sitting time accrued in ≥30 minute bouts (prolonged sitting time), and three measures of sitting accumulation patterns with cardio-metabolic risk markers: body mass index (BMI), waist circumference, blood pressure, high- and low- density lipoprotein (HDL and LDL) cholesterol, triglycerides, glycated haemoglobin (HbA1c), fasting plasma glucose (FPG) and 2-hour post-load glucose (PLG). Interactions tests examined whether associations of sitting time with biomarkers varied by usual sitting bout duration. Results: Adjusted for potential confounders, greater amounts of sitting time and prolonged sitting time were significantly (p<0.05) deleteriously associated with BMI, waist circumference, HDL cholesterol, and triglycerides. Total sitting time was also significantly associated with higher PLG. Sitting accumulation patterns of frequently interrupted sitting (compared to patterns with relatively more prolonged sitting) were significantly beneficially associated with BMI, waist circumference, HDL cholesterol, triglycerides, PLG, and with FPG. Effect sizes were typically larger for accumulation patterns than for sitting time. Significant interactions (p<0.05) showed that associations of sitting time with HDL, triglycerides and PLG became more deleterious the longer at a time sitting was usually accumulated. Conclusions: Adding to previous evidence reliant on low-quality measures, our study showed that accumulating sitting in patterns where sitting was most frequently interrupted had significant beneficial associations with several cardio-metabolic biomarkers and that sitting for prolonged periods at a time may exacerbate some of the effects of sitting time. The findings support sedentary behavior guidelines that promote reducing and regularly interrupting sitting. [ABSTRACT FROM AUTHOR]

Children are at risk for adverse health outcomes from occupant-controllable indoor airborne contaminants in their homes. Data are needed to design residential interventions for reducing low-income children's pollutant exposure. Using customized air quality monitors, we continuously measured fine particle counts (0.5 to 2.5 microns) over a week in living areas of predominantly low-income households in San Diego, California, with at least one child (under age 14) and at least one cigarette smoker. We performed retrospective interviews on home characteristics, and particle source and ventilation activities occurring during the week of monitoring. We explored the relationship between weekly mean particle counts and interview responses using graphical visualization and multivariable linear regression (base sample n = 262; complete cases n = 193). We found associations of higher weekly mean particle counts with reports of indoor smoking of cigarettes or marijuana, as well as with frying food, using candles or incense, and house cleaning. Lower particle levels were associated with larger homes. We did not observe an association between lower mean particle counts and reports of opening windows, using kitchen exhaust fans, or other ventilation activities. Our findings about sources of fine airborne particles and their mitigation can inform future studies that investigate more effective feedback on residential indoor-air-quality and better strategies for reducing occupant exposures. [ABSTRACT FROM AUTHOR]

Objectives: Preventive health services are important for child development, and parents play a key role in facilitating access to services. This study examined how parents' reasons for not having a usual source of care were associated with their children's receipt of preventive services. Methods: We used pooled data from the 2011-2014 National Health Interview Survey (n = 34 843 participants). Parents' reasons for not having a usual source of care were framed within the Penchansky and Thomas model of access and measured through 3 dichotomous indicators: financial barriers (affordability), attitudes and beliefs about health care (acceptability), and all other nonfinancial barriers (accessibility, accommodation, and availability). We used multivariable logistic regression models to test associations between parental barriers and children's receipt of past-year well-child care visits and influenza vaccinations, controlling for other child, family, and contextual factors. Results: In 2014, 14.3% (weighted percentage) of children had at least 1 parent without a usual source of care. Children of parents without a usual source of care because they "don't need a doctor and/or haven't had any problems" or they "don't like, trust, or believe in doctors" had 35% lower odds of receiving well-child care (adjusted odds ratio = 0.65; 95% CI, 0.56-0.74) and 23% lower odds of receiving influenza vaccination (adjusted odds ratio = 0.77; 95% CI, 0.69-0.86) than children of parents without those attitudes and beliefs about health care. Financial and other nonfinancial parental barriers were not associated with children's receipt of preventive services. Results were independent of several factors relevant to children's access to preventive health care, including whether the child had a usual source of care. Conclusions: Parents' attitudes and beliefs about having a usual source of care were strongly associated with their children's receipt of recommended preventive health services. Rates of receipt of child preventive services may be improved by addressing parents' attitudes and beliefs about having a usual source of care. Future studies should assess causes of these associations. [ABSTRACT FROM AUTHOR]

Background: Total sedentary time varies across population groups with important health consequences. Patterns of sedentary time accumulation may vary and have differential health risks. The purpose of this study is to describe sedentary patterns of older adults living in retirement communities and illustrate gender and age differences in those patterns. Methods: Baseline accelerometer data from 307 men and women (mean age = 84±6 years) who wore ActiGraph GT3X+ accelerometers for ≥ 4 days as part of a physical activity intervention were classified into bouts of sedentary time (<100 counts per minute). Linear mixed models were used to account for intra-person and site-level clustering. Daily and hourly summaries were examined in mutually non-exclusive bouts of sedentary time that were 1+, 5+, 10+, 20+, 30+, 40+, 50+, 60+, 90+ and 120+ minutes in duration. Variations by time of day, age and gender were explored. Results: Men accumulated more sedentary time than women in 1+, 5+, 10+, 20+, 30+, 40+, 50+ and 60+ minute bouts; the largest gender-differences were observed in 10+ and 20+ minute bouts. Age was positively associated with sedentary time, but only in bouts of 10+, 20+, 30+, and 40+ minutes. Women had more daily 1+ minute sedentary bouts than men (71.8 vs. 65.2), indicating they break up sedentary time more often. For men and women, a greater proportion of time was spent being sedentary during later hours of the day than earlier. Gender differences in intra-day sedentary time were observed during morning hours with women accumulating less sedentary time overall and having more 1+ minute bouts. Conclusions: Patterns identified using bouts of sedentary time revealed gender and age differences in the way in which sedentary time was accumulated by older adults in retirement communities. Awareness of these patterns can help interventionists better target sedentary time and may aid in the identification of health risks associated with sedentary behavior. Future studies should investigate the impact of patterns of sedentary time on healthy aging, disease, and mortality. [ABSTRACT FROM AUTHOR]

Purpose: Maximal oxygen uptake (V ̇ O 2 max ) is the criterion measure of cardiorespiratory fitness. Lower cardiorespiratory fitness is a strong predictor of poor health outcomes, including all-cause mortality. Because V ̇ O 2 max testing is resource intensive, several non–exercise-based V˙O2max prediction equations have been published. We assess these equations' ability to predict measured V˙O2max, recalibrate these equations, and quantify the association of measured and predicted V˙O2max with all-cause mortality. Methods: Baltimore Longitudinal Study of Aging participants with valid V˙O2max tests were included (n = 1080). Using published V˙O2max prediction equations, we calculated predicted V˙O2max and present performance metrics before and after recalibration (deriving new regression estimates by regressing measured V˙O2max on Baltimore Longitudinal Study of Aging covariates). Cox proportional hazards models were fit to quantify associations of measured, predicted, and recalibration-predicted values of V˙O2max with mortality. Results: Mean age and V˙O2max were 69.0 ± 10.4 yr and 21.6 ± 5.9 mL·kg−1·min−1, respectively. The prediction equations yielded root mean square error values ranging from 4.2 to 20.4 mL·kg−1·min−1. After recalibration, these values decreased to 3.9–4.2 mL·kg−1·min−1. Adjusting for all covariates, all-cause mortality risk was 66% lower for the highest quartile of measured V˙O2max relative to the lowest. Predicted V˙O2max variables yielded similar estimates in unadjusted models but were not robust to adjustment. Conclusions: Measured V˙O2max is an extremely strong predictor of all-cause mortality. Several published V˙O2max prediction equations yielded the following: 1) reasonable performance metrics relative to measured V˙O2max especially when recalibrated, and 2) all-cause mortality hazard ratios similar to those of measured V˙O2max, especially when recalibrated, yet 3) were not robust to adjustment for basic demographic covariates likely because these were used in the equation for predicted V˙O2max. [ABSTRACT FROM AUTHOR]

Background: Perception of health risk can influence household rules, but little is known about how the perception of harm from cannabis secondhand smoke (cSHS) is related to having a complete ban on in-home cannabis smoking. We examined this association among a nationally representative sample of United States adults. Methods: Respondents were 21,381 adults from the cross-sectional Marijuana Use and Environmental Survey recruited from December 2019-February 2020. Perceived harm of cSHS exposure (extremely harmful, somewhat harmful, mostly safe, or totally safe) and complete ban of cannabis smoking anywhere in the home (yes or no) were self-reported. Logistic regression for survey-weighted data estimated covariate-adjusted odds ratios (OR) and 95% confidence intervals (CI) for the association between perceived harm of cSHS and complete ban on in-home cannabis smoking. Stratified subgroup analyses (by cannabis smoking status, cannabis use legalization in state of residence, and children under age 6 living in the home) were conducted to quantify effect measure modification of the association between perception of harm and complete ban. Results: A complete ban on in-home cannabis smoking was reported by 71.8% of respondents. Eight percent reported cSHS as "totally safe"; 20.5% "mostly safe"; 38.3% "somewhat harmful"; and 33.0% "extremely harmful". Those who reported cSHS as "extremely harmful" had 6 times the odds of a complete ban on in-home cannabis smoking (OR = 6.0, 95%CI = 4.9–7.2) as those reporting smoking as "totally safe". The odds of a complete ban were higher among those reporting cSHS as "somewhat harmful" (OR = 2.6, 95%CI = 2.2–3.1) or "mostly safe" (OR = 1.4, 95%CI = 1.2–1.7) vs those reporting cSHS as "totally safe". In each subgroup of cannabis smoking status, state cannabis use legalization, and children under the age of 6 living in the home, perceived harm was associated with a complete ban on in-home cannabis smoking. Conclusions: Our study demonstrates perceiving cSHS as harmful is strongly associated with having a complete in-home cannabis smoking ban. With almost a third of US adults perceiving cSHS as at least "mostly safe", there is strong need to educate the general population about potential risks associated with cSHS exposure to raise awareness and encourage adoption of household rules prohibiting indoor cannabis smoking. [ABSTRACT FROM AUTHOR]

Background: Good lower extremity physical functioning is paramount to healthy aging as it prevents social isolation, enables civic engagement, and facilitates physical activity. Strong evidence links physical functioning with all-cause mortality, but little is known about its relationship to cardiovascular disease (CVD). Methods: Women (n=5043, mean age=79±7) with no history of myocardial infarction or stroke completed the Short Physical Performance Battery (SPPB) consisting of three timed tasks to assess standing balance, strength (5 chair stands), and gait (4m walk). Results were summarized using prespecified cutpoints yielding a score from 0 (worst) to 12 (best). Women were followed for CVD events for up to 6 years. Hazard ratios (HR) were estimated for women with poor, low, moderate, and high functioning (respective SPPB ranges for each group; 0-3, 4-6, 7-9, and 10-12) using Cox proportional hazard models adjusted for several covariates including accelerometer-measured moderate to vigorous physical activity (MVPA) and sedentary behavior. Effect modification of associations between SPPB and CVD by age, MVPA, Reynolds Risk Score, race-ethnicity, and self-rated health were tested by including multiplicative interaction terms in fully adjusted Cox models with statistical significance for interactions set to 0.10. Results: Covariate-adjusted HRs (95% CIs) for CVD [ 1.00 (ref.); 0.85 (0.62, 1.15); 0.69 (0.51, 0.93); 0.49 (0.35, 0.68)] and CVD mortality [ 1.00 (ref.); 0.72 (0.45, 1.15); 0.44 (0.27, 0.72); 0.35 (0.19, 0.62)] decreased across poor, low, moderate, and high SPPB subgroups, respectively (p-trend<.001 [ABSTRACT FROM AUTHOR]

Introduction: Experimental evidence suggests sedentary time (ST), in part, contributes to cardiovascular disease risk by eliciting detrimental hemodynamic changes (blood pooling, turbulent blood flow) in the lower limbs. However, few studies have examined the association of ST and peripheral artery disease (PAD). Hypothesis: We hypothesized that longer daily ST is associated with higher odds of PAD, independent of moderate-to-vigorous physical activity (MVPA). Methods: We examined cross-sectional associations of accelerometer-measured ST (measured over 7 days) and the ankle brachial index (ABI) among 7,677 Hispanic adults (ages 45-74) who were enrolled in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). ST (<100 counts/min) was standardized to 16 hours/d of wear time. Using multivariable logistic regression accounting for the complex survey design, we analyzed quartiles of ST then used restricted cubic splines (RCS) to assess non-linear associations of ST with odds of PAD (ABI ≤ 0.9), all models controlled for claudication, MVPA, and traditional cardiovascular risk factors. Results: Median ST was 12.2 hours/day (76% of wear time) and 366 (5%) participants had PAD. Using RCS with 3 knots (10th, 50th & 90th percentile), ST had a significant non-linear association with PAD (p= 0.004). As seen in the dose-response figure, a threshold effect was seen such that time spent above median ST was associated with significantly higher odds of PAD. For example, compared to median ST, 2 hours above median ST (14.2 hours/day) was associated with 1.60 times the odds of PAD (OR 1.60, 1.24-2.07). Conclusions: Among Hispanic/Latino adults, higher ST is associated with higher odds of PAD, independent of claudication, MVPA, and traditional cardiovascular risk factors. Importantly, this effect was only observed at higher levels of ST. Further study is warranted to determine if reducing high levels of ST may reduce risk of PAD or prevent progression of the disease. [ABSTRACT FROM AUTHOR]

Background: We examined the associations between accelerometry-measured physical activity (PA) and incidence of 13 cancers among a cohort of postmenopausal women.Methods: In this prospective study, 6382 women wore ActiGraph GT3X+ accelerometers at the hip for up to 7 days during 2012-2013, and were followed over a median of 4.7 years for diagnosis of 13 invasive cancers. Calibrated intensity cut points were used to define minutes per day of total, light and moderate-to-vigorous PA. We used multivariable Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for tertiles, and one-standard deviation (SD) unit increments of PA exposures in relation to cancer incidence. We examined effect measure modification by age, race/ethnicity, body mass index and smoking history.Results: The highest (vs. lowest) tertiles of total, light and moderate-to-vigorous PA were associated with covariate-adjusted HRs of 0.72 (95% CI = 0.53-0.97), 0.81 (95% CI = 0.60-1.09) and 0.66 (95% CI = 0.48-0.91), respectively. In age-stratified analyses, HRs for total PA were lower among women <80 years (HRper one-SD = 0.75, 95% CI = 0.63-0.90) than among women ≥80 years (HRper one-SD = 0.99, 95% CI = 0.82-1.18) (PInteraction = 0.03). Race/ethnicity, BMI and smoking did not strongly modify these associations.Conclusions: Engaging in physical activity may play a beneficial role in the prevention of certain cancers in older women. [ABSTRACT FROM AUTHOR]

Background: Hip-worn accelerometer cut-points have poor validity for assessing children's sedentary time, which may partly explain the equivocal health associations shown in prior research. Improved processing/classification methods for these monitors would enrich the evidence base and inform the development of more effective public health guidelines. The present study aimed to develop and evaluate a novel computational method (CHAP-child) for classifying sedentary time from hip-worn accelerometer data. Methods: Participants were 278, 8–11-year-olds recruited from nine primary schools in Melbourne, Australia with differing socioeconomic status. Participants concurrently wore a thigh-worn activPAL (ground truth) and hip-worn ActiGraph (test measure) during up to 4 seasonal assessment periods, each lasting up to 8 days. activPAL data were used to train and evaluate the CHAP-child deep learning model to classify each 10-s epoch of raw ActiGraph acceleration data as sitting or non-sitting, creating comparable information from the two monitors. CHAP-child was evaluated alongside the current practice 100 counts per minute (cpm) method for hip-worn ActiGraph monitors. Performance was tested for each 10-s epoch and for participant-season level sedentary time and bout variables (e.g., mean bout duration). Results: Across participant-seasons, CHAP-child correctly classified each epoch as sitting or non-sitting relative to activPAL, with mean balanced accuracy of 87.6% (SD = 5.3%). Sit-to-stand transitions were correctly classified with mean sensitivity of 76.3% (SD = 8.3). For most participant-season level variables, CHAP-child estimates were within ± 11% (mean absolute percent error [MAPE]) of activPAL, and correlations between CHAP-child and activPAL were generally very large (> 0.80). For the current practice 100 cpm method, most MAPEs were greater than ± 30% and most correlations were small or moderate (≤ 0.60) relative to activPAL. Conclusions: There was strong support for the concurrent validity of the CHAP-child classification method, which allows researchers to derive activPAL-equivalent measures of sedentary time, sit-to-stand transitions, and sedentary bout patterns from hip-worn triaxial ActiGraph data. Applying CHAP-child to existing datasets may provide greater insights into the potential impacts and influences of sedentary time in children. [ABSTRACT FROM AUTHOR]

Objective: The primary aim was to assess associations between total steps per day and incident diabetes, whereas the secondary aim was to assess whether the intensity and/or cadence of steps is associated with incident diabetes.Research Design and Methods: Women without physician-diagnosed diabetes (n = 4,838; mean [SD] age 78.9 [6.7] years) were followed up to 6.9 years; 395 developed diabetes. Hip-worn ActiGraph GT3X+ accelerometers worn for 1 week enabled measures of total, light-intensity, and moderate- to vigorous-intensity (MV-intensity) steps per day. Using Cox proportional hazards analysis we modeled adjusted change in the hazard rate for incident diabetes associated with total, light-intensity, and MV-intensity steps per day. We further estimated the proportion of the steps-diabetes association mediated by BMI.Results: On average, participants took 3,729 (SD 2,114) steps/day, of which 1,875 (791) were light-intensity steps and 1,854 ± 1,762 were MV-intensity. More steps per day were associated with a lower hazard rate for incident diabetes. Confounder-adjusted models for a 2,000 steps/day increment yielded hazard ratio (HR) 0.88 (95% CI 0.78-1.00; P = 0.046). After further adjustment for BMI, HR was 0.90 (95% CI 0.80-1.02; P = 0.11). BMI did not significantly mediate the steps-diabetes association (proportion mediated = 17.7% [95% CI -55.0 to 142.0]; P = 0.09]). The relationship between MV-intensity steps per day (HR 0.86 [95% CI 0.74-1.00]; P = 0.04) and incident diabetes was stronger than for light-intensity steps per day (HR 0.97 [95% CI 0.73-1.29]; P = 0.84).Conclusions: These findings suggest that for older adults, more steps per day are associated with lower incident diabetes and MV-intensity steps are most strongly associated with a lower hazard of diabetes. This evidence supports that regular stepping is an important risk factor for type 2 diabetes prevention in older adults. [ABSTRACT FROM AUTHOR]

Background: Recent evidence suggests that prolonged sitting and its adverse impact on glycaemic indicators appear to be proportional to the degree of insulin resistance. To investigate this finding in a free-living context, we aimed to examine associations of device-measured 24-h time-use compositions of sitting, standing, stepping, and sleeping with fasting glucose (FPG) and 2 h post-load glucose (2hPLG) levels, and to examine separately the associations with time-use compositions among those at lower and at higher risk of developing type 2 diabetes. Methods: Cross-sectional analyses examined thigh-worn inclinometer data (activPAL, 7 day, 24 h/day protocol) from 648 participants (aged 36-80 years) at either lower (< 39 mmol/mol; < 5.7% HbA1c) or higher (≥39 mmol/mol; ≥5.7% HbA1c) diabetes risk from the 2011-2012 Australian Diabetes, Obesity and Lifestyle study. Multiple linear regression models were used to examine associations of differing compositions with FPG and 2hPLG, with time spent in each behaviour allowed to vary up to 60 min. Results: In general, the associations with the FPG within the time-use compositions were small, with statistically significant associations observed for sitting and sleeping (in the lower diabetes risk group) and standing (in higher diabetes risk group) only. For 2hPLG, statistically significant associations were observed for stepping only, with findings similar between lower (β = − 0.12 95%CI:−0.22, − 0.02) and higher (β = − 0.13 95%CI:−0.26, − 0.01) risk groups. Varying the composition had minimal impact on FPG; however 1 h less sitting time and equivalent increase in standing time was associated with attenuated FPG levels in higher risk only (Δ FPG% = − 1.5 95%CI: − 2.4, − 0.5). Large differences in 2hPLG were observed for both groups when varying the composition. One hour less sitting with equivalent increase in stepping was associated with attenuated 2hPLG, with estimations similar in lower (Δ 2hPLG% = − 3.8 95%CI: − 7.3, − 0.2) and higher (Δ 2hPLG% = − 5.0 95%CI: − 9.7, − 0.0) risk for diabetes. Conclusions: In middle-aged and older adults, glycaemic control could be improved by reducing daily sitting time and replacing it with stepping. Standing could also be beneficial for those at higher risk of developing type 2 diabetes. [ABSTRACT FROM AUTHOR]

National guidelines recommend physically active interruptions to sitting time; however, the characteristics of these interruptions are broadly stated and ill-defined. A robust methodology for population surveillance for such interruptions is needed. Purpose: To describe the frequency and characteristics (i.e. duration, stepping time, and estimated intensity) of all interruptions and physically active interruptions to adults' free-living sitting time (i.e. transitions from sitting to upright posture) across segments of the population. Methods : Australian Diabetes, Obesity and Lifestyle study participants (321 men; 406 women; mean +/- standard deviation, 58.0 +/- 10.3 yr) wore the activPAL3(TM) for >=1 valid day. The characteristics of interruptions from laboratory studies demonstrating health benefits were selected to define active interruptions (>=5 min upright and/or >=2 min stepping) and ambulatory interruptions (>=2 min stepping). The frequency and characteristics of all, active, and ambulatory interruptions were described and compared by age, sex, diabetes status, and body mass index. Results : Adults averaged 55.0 +/- 21.8 interruptions per day, but only 20.3 +/- 6.7 were active and 14.0 +/- 5.4 were ambulatory. Median (25th, 75th percentile) duration was 2.6 min (0.9, 7.8 min), stepping time was 0.8 min (0.3, 2.0 min), and estimated energy expenditure was 4.3 metabolic equivalents (MET)[middle dot]min-1 (1.4, 12.5 MET[middle dot]min-1). Those who were older, had obesity, or had diabetes had significantly (P < 0.05) fewer interruptions of all types and less stepping time during active interruptions than their counterparts (Cohen's d < 0.2). Conclusions : Free-living interruptions were often less active than interruptions performed in effective acute laboratory studies and their content varied widely between population groups. Monitoring all interruptions, as well as those that are more active, is advisable to provide a comprehensive understanding of free-living sedentary behavior. [ABSTRACT FROM AUTHOR]

Introduction: Sitting patterns predict several healthy aging outcomes. These patterns can potentially be measured using hip-worn accelerometers, but current methods are limited by an inability to detect postural transitions. To overcome these limitations, we developed the Convolutional Neural Network Hip Accelerometer Posture (CHAP) classification method. Methods: CHAP was developed on 709 older adults who wore an ActiGraph GT3X+ accelerometer on the hip, with ground-truth sit/stand labels derived from concurrently worn thigh-worn activPAL inclinometers for up to 7 d. The CHAP method was compared with traditional cut-point methods of sitting pattern classification as well as a previous machine-learned algorithm (two-level behavior classification). Results: Forminute-level sitting versus nonsitting classification, CHAP performed better (93% agreement with activPAL) than did other methods (74%-83% agreement). CHAP also outperformed other methods in its sensitivity to detecting sit-to-stand transitions: cut-point (73%), TLBC (26%), andCHAP (83%). CHAP's positive predictive value of capturing sit-to-stand transitions was also superior to other methods: cut-point (30%), TLBC (71%), and CHAP (83%). Day-level sitting pattern metrics, such as mean sitting bout duration, derived from CHAP did not differ significantly from activPAL, whereas other methods did: activPAL (15.4 min of mean sitting bout duration), CHAP (15.7 min), cut-point (9.4 min), and TLBC (49.4 min). Conclusion: CHAP was the most accurate method for classifying sit-tostand transitions and sitting patterns from free-living hip-worn accelerometer data in older adults. This promotes enhanced analysis of older adult movement data, resulting in more accurate measures of sitting patterns and opening the door for large-scale cohort studies into the effects of sitting patterns on healthy aging outcomes. [ABSTRACT FROM AUTHOR]

Time spent sitting is positively correlated with endothelial dysfunction and cardiovascular disease risk. The underlying molecular mechanisms are unknown. MicroRNAs contained in extracellular vesicles (EVs) reflect cell/tissue status and mediate intercellular communication. We explored the association between sitting patterns and microRNAs isolated from endothelial cell (EC)-derived EVs. Using extant actigraphy based sitting behavior data on a cohort of 518 postmenopausal overweight/obese women, we grouped the woman as Interrupted Sitters (IS; N = 18) or Super Sitters (SS; N = 53) if they were in the shortest or longest sitting pattern quartile, respectively. The cargo microRNA in EC-EVs from the IS and SS women were compared. MicroRNA data were weighted by age, physical functioning, MVPA, device wear days, device wear time, waist circumference, and body mass index. Screening of CVD-related microRNAs demonstrated that miR-199a-5p, let-7d-5p, miR-140-5p, miR-142-3p, miR-133b level were significantly elevated in SS compared to IS groups. Group differences in let-7d-5p, miR-133b, and miR-142-3p were validated in expanded groups. Pathway enrichment analyses show that mucin-type O-glycan biosynthesis and cardiomyocyte adrenergic signaling (P < 0.001) are downstream of the three validated microRNAs. This proof-of-concept study supports the possibility that CVD-related microRNAs in EC-EVs may be molecular transducers of sitting pattern-associated CVD risk in overweight postmenopausal women. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Limited evidence exists to inform physical activity (PA) and sedentary behavior guidelines for older people, especially women. Rigorous evidence on the amounts, intensities, and movement patterns associated with better health in later life is needed.Methods/design: The Objective PA and Cardiovascular Health (OPACH) Study is an ancillary study to the Women's Health Initiative (WHI) Program that examines associations of accelerometer-assessed PA and sedentary behavior with cardiovascular and fall events. Between 2012 and 2014, 7048 women aged 63-99 were provided with an ActiGraph GT3X+ (Pensacola, Florida) triaxial accelerometer, a sleep log, and an OPACH PA Questionnaire; 6489 have accelerometer data. Most women were in their 70s (40%) or 80s (46%), while approximately 10% were in their 60s and 4% were age 90 years or older. Non-Hispanic Black or Hispanic/Latina women comprise half of the cohort. Follow-up includes 1-year of falls surveillance with monthly calendars and telephone interviews of fallers, and annual follow-up for outcomes with adjudication of incident cardiovascular disease (CVD) events through 2020. Over 63,600 months of calendar pages were returned by 5,776 women, who reported 5,980 falls. Telephone interviews were completed for 1,492 women to ascertain the circumstances, injuries and medical care associated with falling. The dataset contains extensive information on phenotypes related to healthy aging, including inflammatory and CVD biomarkers, breast and colon cancer, hip and other fractures, diabetes, and physical disability.Discussion: This paper describes the study design, methods, and baseline data for a diverse cohort of postmenopausal women who wore accelerometers under free-living conditions as part of the OPACH Study. By using accelerometers to collect more precise and complete data on PA and sedentary behavior in a large cohort of older women, this study will contribute crucial new evidence about how much, how vigorous, and what patterns of PA are necessary to maintain optimal cardiovascular health and to avoid falls in later life.Clinical Trials Registration: ClinicalTrials.gov identifier NCT00000611 . Registered 27 October 1999. [ABSTRACT FROM AUTHOR]

Background: Few studies characterize older adult physical activity and sitting patterns using accurate accelerometer and concurrent posture measures. In this descriptive paper, we report accelerometer data collection protocols, consent rates, and physical behavior measures from a population-based cohort study (Adult Changes in Thought, ACT).Methods: The ACT study holds enrollment steady at approximately 2000 members of Kaiser Permanente Washington aged 65+ without dementia undergoing detailed biennial assessments. In 2016 the ACT-Activity Monitor (ACT-AM) sub-study was initiated to obtain data from wearing activPAL and ActiGraph devices for 7 days following regular biennial visits. We describe the methods protocol of ACT-AM and present characteristics of people who did and did not consent to wear devices. We compute inverse probability of response weights and incorporate these weights in linear regression models to estimate means and 95% confidence intervals (CI) of device-based pattern metrics, adjusted for wear time and demographic factors, and weighted to account for potential selection bias due to device-wear consent.Results: Among 1885 eligible ACT participants, 56% agreed to wear both devices (mean age 77 years, 56% female, 89% non-Hispanic white, 91% with post-secondary education). On average, those who agreed to wear devices were younger and healthier. Estimated mean (95% CI) activPAL-derived sitting, standing, and stepping times were 10.2 h/day (603-618 min/day), 3.9 h/day (226-239 min/day), and 1.4 h/day (79-84 min/day), respectively. Estimated mean ActiGraph derived sedentary (Vector Magnitude [VM] < =18 counts/15 s), light intensity (VM 19-518 counts/15 s), and moderate-to-vigorous intensity (VM > 518 counts/15 s) physical activity durations were 9.5 h/day (565-577 min/day), 4.5 h/day (267-276 min/day), and 1.0 h/day (59-64 min/day). Participants who were older, had chronic conditions, and were unable to walk a half-mile had higher sedentary time and less physical activity.Conclusions: Our recruitment rate demonstrates the feasibility of cohort participants to wear two devices that measure sedentary time and physical activity. Data indicate high levels of sitting time in older adults but also high levels of physical activity using cut-points developed for older adults. These data will help researchers test hypotheses related to physical behavior and health in older adults in the future. [ABSTRACT FROM AUTHOR]

Interventions are needed to protect the health of children who live with smokers. We pilot-tested a real-time intervention for promoting behavior change in homes that reduces second hand tobacco smoke (SHS) levels. The intervention uses a monitor and feedback system to provide immediate auditory and visual signals triggered at defined thresholds of fine particle concentration. Dynamic graphs of real-time particle levels are also shown on a computer screen. We experimentally evaluated the system, field-tested it in homes with smokers, and conducted focus groups to obtain general opinions. Laboratory tests of the monitor demonstrated SHS sensitivity, stability, precision equivalent to at least 1 µg/m3, and low noise. A linear relationship (R2 = 0.98) was observed between the monitor and average SHS mass concentrations up to 150 µg/m3. Focus groups and interviews with intervention participants showed in-home use to be acceptable and feasible. The intervention was evaluated in 3 homes with combined baseline and intervention periods lasting 9 to 15 full days. Two families modified their behavior by opening windows or doors, smoking outdoors, or smoking less. We observed evidence of lower SHS levels in these homes. The remaining household voiced reluctance to changing their smoking activity and did not exhibit lower SHS levels in main smoking areas or clear behavior change; however, family members expressed receptivity to smoking outdoors. This study established the feasibility of the real-time intervention, laying the groundwork for controlled trials with larger sample sizes. Visual and auditory cues may prompt family members to take immediate action to reduce SHS levels. Dynamic graphs of SHS levels may help families make decisions about specific mitigation approaches. [ABSTRACT FROM AUTHOR]