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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]

• Recently, cigarette use has declined while cannabis use has increased. • Smoking cannabis produces second- and third-hand emissions that may impact health. • Comparisons of in-home cannabis and tobacco smoking have not been available. • In-home smoking of cannabis was more prevalent than tobacco. • Global cannabis acceptability movements urge research on use patterns & health effects. Early evidence from studies of home smoking policies suggests that in-home cannabis smoking is more often allowed than in-home tobacco smoking, but there are not yet data on whether cannabis is more often smoked in the home compared to tobacco, or whether in-home cannabis and tobacco smoking differs by usage status. Using cross-sectional data from over 100,000 sentinel drug users from 17 countries, we compared cannabis and tobacco smoking in the homes of Global Drug Survey 2019 respondents who currently used cannabis only, tobacco only, both tobacco and cannabis, or neither. Complete data on cannabis and tobacco use and in-home smoking were available for 107,272 adults (average age = 30 ± 12, 34% women, countries with the three highest response rates; Germany = 32%, USA = 10%, New Zealand = 9%). In total, 53.6% and 50.6% of respondents reported past-year cannabis and tobacco smoking in their home respectively. Stratifying respondents into current cannabis-only users, tobacco-only users, dual users, and non-users, past-year in-home cannabis smoking was more prevalent (78.8%) among cannabis-only users than was in-home tobacco smoking (67.9%) among tobacco-only users. Among dual users, past-year in-home cannabis smoking (82.8%; 95%CI = 80%-86%) was higher than in-home tobacco smoking (75.9%; 95%CI = 69%–81%; p < 0.001). In-home cannabis and tobacco smoking was similar among non-users (20.2% and 20.5%, respectively). Past-year in-home cannabis smoking was more prevalent than tobacco smoking in the homes of participants who used cannabis and/or tobacco, supporting our speculation that in-home cannabis smoking might be more socially acceptable than in-home tobacco smoking. [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]

Purpose Of the Research: Early evidence from studies of home smoking policies suggests that in-home cannabis smoking is more often allowed than in-home tobacco smoking, but there are not yet data on whether cannabis is more often smoked in the home compared to tobacco, or whether in-home cannabis and tobacco smoking differs by usage status. Using cross-sectional data from over 100,000 sentinel drug users from 17 countries, we compared cannabis and tobacco smoking in the homes of Global Drug Survey 2019 respondents who currently used cannabis only, tobacco only, both tobacco and cannabis, or neither.Principal Results: Complete data on cannabis and tobacco use and in-home smoking were available for 107,272 adults (average age = 30 ± 12, 34% women, countries with the three highest response rates; Germany = 32%, USA = 10%, New Zealand = 9%). In total, 53.6% and 50.6% of respondents reported past-year cannabis and tobacco smoking in their home respectively. Stratifying respondents into current cannabis-only users, tobacco-only users, dual users, and non-users, past-year in-home cannabis smoking was more prevalent (78.8%) among cannabis-only users than was in-home tobacco smoking (67.9%) among tobacco-only users. Among dual users, past-year in-home cannabis smoking (82.8%; 95%CI = 80%-86%) was higher than in-home tobacco smoking (75.9%; 95%CI = 69%-81%; p < 0.001). In-home cannabis and tobacco smoking was similar among non-users (20.2% and 20.5%, respectively).Major Conclusions: Past-year in-home cannabis smoking was more prevalent than tobacco smoking in the homes of participants who used cannabis and/or tobacco, supporting our speculation that in-home cannabis smoking might be more socially acceptable than in-home tobacco smoking. [ABSTRACT FROM AUTHOR]

AbstractWe examined the prospective associations of social isolation and loneliness with incident cardiovascular disease (CVD) among aging nonveteran and veteran women, and effect modification by veteran status. Participants with no history of myocardial infarction (MI), stroke, coronary heart disease (CHD), or coronary heart failure from the Women’s Health Initiative Extension Study II self-reported social isolation, loneliness, health behaviors, health status, and veteran status. CVD and CVD subevents were physician adjudicated. Hazard ratios (HR) and 95% confidence intervals (CI) for the Interquartile Range (IQR) in social isolation (IQR = 1) and loneliness (IQR=.33) were calculated using Cox proportional hazard models adjusting for sociodemographic, health behavior, and health status characteristics. Veteran status was tested as an effect modifier. Among 52,442 women (Mean age = 79 ± 6.1; veterans n = 1023; 89.2% non-Hispanic White), 3579 major CVD events occurred over an average 5.8 follow-up years. Compared to nonveterans, veteran women reported higher levels of social isolation (p < .01) and loneliness (p < .01). The CVD HR was 1.07 (95% CI, 1.04–1.10) for the IQR in social isolation and 1.03 (95% CI, 1.10–1.06) for the IQR in loneliness. The HR for the IQR in both social isolation and loneliness was 1.10 (95% CI, 1.05–1.15). Social isolation was associated with CHD (HR = 1.12; 95% CI, 1.03–1.21). The CHD HR for the IQR in social isolation was 1.12 (95% CI, 1.03–1.21). Associations did not differ by veteran status (all p-interactions > 0.08). Findings suggest that the adverse associations of social isolation and loneliness with CVD are similar among veteran and nonveteran women. [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: Positive affect and emotional resources, such as optimism, may play a major role in women's health and promote healthy well-being later in life. However, positive affect and optimism measures have not been psychometrically assessed in older women, despite relations to health. Therefore, the objective of this study was to psychometrically assess measures of positive affect and optimism and test their association with other measures of well-being. Methods: In a Women's Health Initiative subcohort of 58,810 women (mean age [standard deviation] 79.0 [6.1]; 89% White), positive affect and optimism were measured using the modified Differential Emotions Scale (mDES) and Life Orientation Test-Revised (LOT-R), respectively. Reliability was tested using Cronbach's alpha and McDonald's omega. Performance was assessed using item response theory. Factor analysis was used to explore the construct validity of the LOT-R. Convergent and divergent validity with other well-being measures was tested. Results: Results suggest good reliability (mDES: Cronbach's alpha = 0.90 and omega total = 0.92; LOT-R: Cronbach's alpha = 0.79, omega hierarchical = 0.61, and omega total = 0.83). Item response analyses indicate mDES's ability to discriminate across positive affect; LOT-R was skewed toward lower optimism levels. Exploratory factor analyses suggest a two-factor solution for the LOT-R. Significant, but small correlations in expected directions to well-being measures confirmed validity hypotheses. Conclusions: The mDES and LOT-R measured positive affect and optimism with good reliability, item performance, and validity in a large sample of older postmenopausal women, supporting use of these measures to quantify effects of positive affect and optimism-promoting interventions. [ABSTRACT FROM AUTHOR]

Background: Few studies have examined accelerometer‐measured physical activity and incident breast cancer (BC). Thus, this study examined associations between accelerometer‐measured vector magnitude counts per 15 seconds (VM/15s) and average daily minutes of light physical activity (LPA), moderate‐to‐vigorous PA (MVPA), and total PA (TPA) and BC risk among women in the Women's Health Accelerometry Collaboration (WHAC). Methods: The WHAC comprised 21,089 postmenopausal women (15,375 from the Women's Health Study [WHS]; 5714 from the Women's Health Initiative Objective Physical Activity and Cardiovascular Health Study [OPACH]). Women wore an ActiGraph GT3X+ on the hip for ≥4 days and were followed for 7.4 average years to identify physician‐adjudicated in situ (n = 94) or invasive (n = 546) BCs. Multivariable stratified Cox regression estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for tertiles of physical activity measures in association with incident BC overall and by cohort. Effect measure modification was examined by age, race/ethnicity, and body mass index (BMI). Results: In covariate‐adjusted models, the highest (vs. lowest) tertiles of VM/15s, TPA, LPA, and MVPA were associated with BC HRs of 0.80 (95% CI, 0.64–0.99), 0.84 (95% CI, 0.69–1.02), 0.89 (95% CI, 0.73–1.08), and 0.81 (95% CI, 0.64–1.01), respectively. Further adjustment for BMI or physical function attenuated these associations. Associations were more pronounced among OPACH than WHS women for VM/15s, MVPA, and TPA; younger than older women for MVPA; and women with BMI ≥30 than <30 kg/m2 for LPA. Conclusion: Greater levels of accelerometer‐assessed PA were associated with lower BC risk. Associations varied by age and obesity and were not independent of BMI or physical function. In a study of over 20,000 US postmenopausal women, higher levels of accelerometer‐measured physical activity were associated with lower risk of breast cancer. Associations varied by age and obesity and were not independent of body mass index or physical function. [ABSTRACT FROM AUTHOR]

Background: Social support may be a modifiable risk factor for cognitive impairment. However, few long-term, large prospective studies have examined associations of various forms of social support with incident mild cognitive impairment (MCI) and dementia. Objective: To examine associations of perceived social support with incident MCI and dementia among community-dwelling older women. Methods: This prospective cohort study included 6,670 women from the Women's Health Initiative Memory Study who were cognitively unimpaired at enrollment. We used Cox proportional hazards models to assess associations between perceived social support with incident MCI, dementia, or either MCI/dementia during an average 10.7 (SD = 6.1)-year follow-up. Modelling was repeated for emotional/information support, affection support, tangible support, and positive social interaction subscales of social support. Results: Among 6,670 women (average age = 70 years [SD = 3.8]; 97.0% non-Hispanic/Latina; 89.8% White), greater perceived social support was associated with lower risk of MCI/dementia after adjustment for age, ethnicity, race, hormone therapy, education, income, diabetes, hypertension, and body mass index (Tertile [T]3 versus T1: HR = 0.85, 95% CI 0.74–0.99; ptrend = 0.08). Associations were significant for emotional/information support (T3 versus T1: HR = 0.84, 95% CI 0.72–0.97; ptrend = 0.04) and positive social interaction (T3 versus T1: HR = 0.85, 95% CI 0.73–0.99; ptrend = 0.06) subscales. Associations were attenuated and not significant after adjustment for depressive symptom severity. Objective: Perceived social support, emotional/information support, and positive social interaction were associated with incident MCI/dementia among older women. Results were not significant after adjustment for depressive symptom severity. Improving social support may reduce risk of MCI and dementia in older women. [ABSTRACT FROM AUTHOR]

Psychological well-being is linked to healthy aging in older women, but associations with health behaviors are not well understood. Our study aims to evaluate the relationships between objectively-measured physical behavior (including physical activity and sedentary behavior) with optimism and positive affect in a diverse sample of older women. Our cross-sectional study of 4168 American women (aged 63–99) with accelerometer-measured physical behavior from the Objective Physical Activity and Cardiovascular Health Study assessed associations using multiple linear regression. Effect modification by age, race and ethnicity, social support, and number of chronic conditions was examined as well. In unadjusted models, positive associations for physical activity and negative associations for sedentary behaviors were generally linear for optimism and positive affect. In adjusted models, every one-hour increment in weekly moderate-vigorous physical activity was associated with higher optimism by 0.4 score points [Revised 6-item Life Orientation Test, 95% CI = 0.2, 0.6] and positive affect by 0.6 score points [modified Differential Emotions Scale, 95% CI = 0.2, 0.9]. One-hour increments in light physical activity were associated with higher positive affect [0.2 score points; 95% CI = 0.03, 0.33] while one-hour increments in sedentary behavior patterns were associated with lower positive affect [-0.1 score points; 95% CI = − 0.10, − 0.02). Effect modification by age, race and ethnicity, social support, and number of chronic conditions was not observed. In conclusion, associations between physical behavior with optimism and positive affect were modest but suggest greater activity and less sedentary time are associated with greater psychological well-being in older women. [ABSTRACT FROM AUTHOR]

Background: Aging is generally accompanied by decreasing physical activity (PA), which is associated with a decline in many health parameters, leading to recommendations for older adults to increase or at least maintain PA.Methods: We determined relationships between social connectedness and decreasing or increasing PA levels during the coronavirus disease 2019 pandemic among 41 443 participants of the Women's Health Initiative Extension Study. Outcomes of logistic regression models were decreasing PA activity (reference: maintaining or increasing) and increasing PA activity (reference: maintaining or decreasing). The main predictor was social connectedness as a combined variable: not living alone (reference: living alone) and communicating with others outside the home more than once/week (reference: once/week or less). We adjusted for age, race, ethnicity, body mass index, physical function level, and education.Results: Compared with participants who were not socially connected, socially connected participants had lower odds of decreasing PA (adjusted odds ratio 0.91, 95% confidence interval 0.87-0.95). Odds of increasing PA (vs decreasing or maintaining PA) were not significantly different among socially connected and not socially connected participants. Associations between social connectedness and decreasing PA did not significantly differ by age (<85 vs ≥85 years), race/ethnicity (non-Hispanic White vs other races/ethnicity), education (college vs 75).Conclusion: Social connectedness was associated with lower odds of decreasing PA among older women during the pandemic. These findings could inform the development of future interventions to help older women avoid decreasing PA. [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]