Development, validation, and transportability of several machine-learned, non-exercise-based VO2max prediction models for older adults.

PURPOSE: There exist few maximal oxygen uptake (VO2max) non-exercise-based prediction equations, fewer using machine learning (ML), and none specifically for older adults. Since direct measurement of VO2max is infeasible in large epidemiologic cohort studies, we sought to develop, validate, compare, and assess the transportability of several ML VO2max prediction algorithms. METHODS: The Baltimore Longitudinal Study of Aging (BLSA) participants with valid VO2max tests were included (n = 1080). Least absolute shrinkage and selection operator, linear- and tree-boosted extreme gradient boosting, random forest, and support vector machine (SVM) algorithms were trained to predict VO2max values. We developed these algorithms for: (a) for the overall BLSA, (b) by sex, (c) using all BLSA variables, and (d) for variables common in aging cohorts. Finally, we quantified the associations between measured and predicted VO2max and mortality. RESULTS: The age was 69.0 ± 10.4 years (mean ± SD) and the measured VO2max was 21.6 ± 5.9 mL/kg/min. Least absolute shrinkage and selection operator, linear- and tree-boosted extreme gradient boosting, random forest, and support vector machine yielded root mean squared errors of 3.4 mL/kg/min, 3.6 mL/kg/min, 3.4 mL/kg/min, 3.6 mL/kg/min, and 3.5 mL/kg/min, respectively. Incremental quartiles of measured VO2max showed an inverse gradient in mortality risk. Predicted VO2max variables yielded similar effect estimates but were not robust to adjustment. CONCLUSION: Measured VO2max is a strong predictor of mortality. Using ML can improve the accuracy of prediction as compared to simpler approaches but estimates of association with mortality remain sensitive to adjustment. Future studies should seek to reproduce these results so that VO2max, an important vital sign, can be more broadly studied as a modifiable target for promoting functional resiliency and healthy aging.

Perception of harm is strongly associated with complete ban on in-home cannabis smoking: a cross-sectional study.

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.

Associations of Abdominal Muscle Density and Area and Incident Cardiovascular Disease, Coronary Heart Disease, and Stroke: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Muscle density is inversely associated with all-cause mortality, but associations with cardiovascular disease (CVD) risk are not well understood. This study evaluated the association between muscle density and muscle area and incident total CVD, coronary heart disease (CHD), and stroke in diverse men and women. METHODS AND RESULTS: Adult participants (N=1869) in the Multi-Ethnic Study of Atherosclerosis Ancillary Body Composition Study underwent computer tomography scans of the L2-L4 region of the abdomen. Muscle was quantified by density (Hounsfield units) and area in cm2. Sex-stratified Cox proportional hazard models assessed associations between incident total CVD, incident CHD, and incident stroke across sex-specific percentiles of muscle area and density, which were entered simultaneously into the model. Mean age for men and women at baseline were 64.1 and 65.1 years, respectively, and median follow-up time was 10.3 years. For men, associations between muscle density and incident CVD were inverse but not significant in fully adjusted models (P trend=0.15). However, there was an inverse association between density and CHD (P trend=0.02; HR, 0.26 for 95th versus 10th percentile), and no association with stroke (P trend=0.78). Conversely, for men, there was a strong positive association between muscle area and incident CVD (HR, 4.19 for 95th versus 10th percentile; P trend<0.001). Associations were stronger for CHD (HR, 6.18 for 95th versus 10th percentile; P trend<0.001), and null for stroke (P trend=0.67). Associations for women were mostly null. CONCLUSIONS: For men, abdominal muscle density is associated with lower CHD risk, whereas greater muscle area is associated with markedly increased risk of CHD.

Prospective Associations of Accelerometer-Measured Machine-Learned Sedentary Behavior With Death Among Older Women: The OPACH Study.

BACKGROUND: Sedentary behavior is a recognized mortality risk factor. The novel and validated convolutional neural network hip accelerometer posture algorithm highly accurately classifies sitting and postural changes compared with accelerometer count cut points. We examined the prospective associations of convolutional neural network hip accelerometer posture-classified total sitting time and mean sitting bout duration with all-cause and cardiovascular disease (CVD) death. METHODS AND RESULTS: Women (n=5856; mean±SD age, 79±7 years; 33% Black women, 17% Hispanic or Latina women, 50% White women) in the Women's Health Initiative Objective Physical Activity and Cardiovascular Health (OPACH) Study wore the ActiGraph GT3X+ for ~7 days from May 2012 to April 2014 and were followed through February 19, 2022 for all-cause and CVD death. The convolutional neural network hip accelerometer posture algorithm classified total sitting time and mean sitting bout duration from GT3X+ output. Over follow-up (median, 8.4 years; range, 0.1-9.9), there were 1733 deaths (632 from CVD). Adjusted Cox regression hazard ratios (HRs) comparing women in the highest total sitting time quartile (>696 min/d) to those in the lowest (<556.0 min/d) were 1.57 (95% CI; 1.35-1.83; P-trend<0.001) for all-cause death and 1.78 (95% CI; 1.36-2.31; P-trend<0.001) for CVD death. HRs comparing women in the longest mean sitting bout duration quartile (>15 minutes) to the shortest (<9.3 minutes) were 1.43 (95% CI; 1.23-1.66; P-trend<0.001) for all-cause death and 1.52 (95% CI; 1.18-1.96; P-trend<0.001) for CVD death. Apparent nonlinear associations for total sitting time suggested higher all-cause death (P nonlinear=0.009) and CVD death (P nonlinear=0.008) risk after ~660 to 700 min/d. CONCLUSIONS: Higher total sitting time and longer mean sitting bout duration are associated with higher all-cause and CVD mortality risk among older women. These data support interventions aimed at reducing both total sitting time and interrupting prolonged sitting.

Low movement, deep-learned sitting patterns, and sedentary behavior in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE).

BACKGROUND/OBJECTIVES: Sedentary behavior (SB) has both movement and postural components, but most SB research has only assessed low movement, especially in children. The purpose of this study was to compare estimates and health associations of SB when derived from a standard accelerometer cut-point, a novel sitting detection technique (CNN Hip Accelerometer Posture for Children; CHAP-Child), and both combined. METHODS: Data were from the International Study of Childhood Obesity, Lifestyle, and the Environment (ISCOLE). Participants were 6103 children (mean ± SD age 10.4 ± 0.56 years) from 12 countries who wore an ActiGraph GT3X+ accelerometer on the right hip for approximately one week. We calculated SB time, mean SB bout duration, and SB breaks using a cut-point (SBmovement), CHAP-Child (SBposture), and both methods combined (SBcombined). Mixed effects regression was used to test associations of SB variables with pediatric obesity variables (waist circumference, body fat percentage, and body mass index z-score). RESULTS: After adjusting for MVPA, SBposture showed several significant obesity associations favoring lower mean SB bout duration (b = 0.251-0.449; all p < 0.001) and higher SB breaks (b = -0.005--0.052; all p < 0.001). Lower total SB was unexpectedly related to greater obesity (b = -0.077--0.649; p from <0.001-0.02). For mean SB bout duration and SB breaks, more associations were observed for SBposture (n = 5) than for SBmovement (n = 3) or SBcombined (n = 1), and tended to have larger magnitude as well. CONCLUSIONS: Using traditional measures of low movement as a surrogate for SB may lead to underestimated or undetected adverse associations between SB and obesity. CHAP-Child allows assessment of sitting posture using hip-worn accelerometers. Ongoing work is needed to understand how low movement and posture are related to one another, as well as their potential health implications.

Psychometric Analysis of the Modified Differential Emotions Scale and the Six-Item Life Orientation Test-Revised in a Cohort of Older Women from the Women's Health Initiative.

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.

Location and home rules of cannabis use - Findings from marijuana use and environmental survey 2020, a nationally representative survey in the United States.

Cannabis combustion and aerosolization may be associated with adverse health for users and nonusers through secondhand and thirdhand exposure. As cannabis regulation becomes more lenient, understanding where cannabis is used and whether homes have rules restricting use is needed. This study aimed to identify locations, presence of other people, and in-home rules of cannabis use in the United States (U.S.). This secondary analysis of 3,464 inhalation-based (smoking, vaping, dabbing) cannabis users in past 12 months drew from a cross-sectional probability-based online panel of 21,903 U.S. adults in early 2020, providing nationally representative estimates. We describe presence of other people and location at most recent use (smoking, vaping, dabbing, respectively). We also describe household restrictions on in-home cannabis smoking by cannabis smokers vs non-smokers, and by presence of children in home. Cannabis smoking, vaping, and dabbing most often occurred at users' own homes (65.7%, 56.8%, and 46.9%, respectively). More than 60% of smoking, vaping, and dabbing occurred with someone else present. About 68% of inhalation-based cannabis users (70% and 55%, smokers and non-smokers, respectively) did not have complete restrictions on in-home cannabis smoking; among them, over a quarter lived with children under 18. In the U.S., inhalation-based cannabis use most commonly occurs at home, with others present and a substantial proportion of users lacking complete in-home cannabis smoking restrictions, raising risks of secondhand and thirdhand smoke exposure. These circumstances demand residential interventions for developing bans on indoor cannabis smoking, especially around vulnerable children.

Accelerometer-measured physical activity and postmenopausal breast cancer incidence in the Women's Health Accelerometry Collaboration.

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.

Accelerometer-measured physical activity and sitting with incident mild cognitive impairment or probable dementia among older women.

INTRODUCTION: Physical activity (PA) is prospectively inversely associated with dementia risk, but few studies examined accelerometer measures of PA and sitting with rigorously-adjudicated mild cognitive impairment (MCI) and dementia risk. METHODS: We examined the associations of accelerometer measures (PA and sitting) with incident MCI/probable dementia in the Women's Health Initiative (n = 1277; mean age = 82 ± 6 years) RESULTS: Over a median follow-up of 4.2 years, 267 MCI/probable dementia cases were identified. Adjusted Cox regression HRs (95% CI) across moderate-to-vigorous PA (MVPA) min/d quartiles were 1.00 (reference), 1.28 (0.90 to 1.81), 0.79 (0.53 to 1.17), and 0.69 (0.45 to 1.06); P-trend = 0.01. Adjusted HRs (95% CI) across steps/d quartiles were 1.00 (reference), 0.73 (0.51 to 1.03), 0.64 (0.43 to 0.94), and 0.38 (0.23 to 0.61); P-trend < 0.001. The HR (95% CI) for each 1-SD increment in MVPA (31 min/d) and steps/d (1865) were 0.79 (0.67 to 0.94) and 0.67 (0.54 to 0.82), respectively. Sitting was not associated with MCI/probable dementia. DISCUSSION: Findings suggest ≥ moderate intensity PA, particularly stepping, associates with lower MCI and dementia risk. HIGHLIGHTS: Few studies have examined accelerometer-measured physical activity, including steps, and sitting with incident ADRD. Moderate-to-vigorous physical activity and steps, but not light physical activity or sitting, were inversely associated with lower ADRD risk. Among older women, at least moderate intensity physical activity may be needed to reduce ADRD risk.

Validation, Recalibration, and Predictive Accuracy of Published V̇O 2max Prediction Equations for Adults Ages 50-96 Yr.

PURPOSE: Maximal oxygen uptake ( ) is the criterion measure of cardiorespiratory fitness. Lower cardiorespiratory fitness is a strong predictor of poor health outcomes, including all-cause mortality. Because testing is resource intensive, several non-exercise-based V˙O 2max prediction equations have been published. We assess these equations' ability to predict measured V˙O 2max , recalibrate these equations, and quantify the association of measured and predicted V˙O 2max with all-cause mortality. METHODS: Baltimore Longitudinal Study of Aging participants with valid V˙O 2max tests were included ( n = 1080). Using published V˙O 2max prediction equations, we calculated predicted V˙O 2max and present performance metrics before and after recalibration (deriving new regression estimates by regressing measured V˙O 2max 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˙O 2max with mortality. RESULTS: Mean age and V˙O 2max 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˙O 2max relative to the lowest. Predicted V˙O 2max variables yielded similar estimates in unadjusted models but were not robust to adjustment. CONCLUSIONS: Measured V˙O 2max is an extremely strong predictor of all-cause mortality. Several published V˙O 2max prediction equations yielded the following: 1) reasonable performance metrics relative to measured V˙O 2max especially when recalibrated, and 2) all-cause mortality hazard ratios similar to those of measured V˙O 2max , 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˙O 2max .

Associations of Accelerometer-Measured Physical Activity and Sedentary Time With All-Cause Mortality by Genetic Predisposition for Longevity.

The goal of this study was to examine associations between accelerometer-measured physical activity (PA) and sedentary time (ST) with mortality by a genetic risk score (GRS) for longevity. Among 5,446 women, (mean [SD]: age, 78.2 [6.6] years), 1,022 deaths were observed during 33,350 person-years of follow-up. Using multivariable Cox proportional hazards models, higher light PA and moderate to vigorous PA were associated with lower mortality across all GRS for longevity categories (low/medium/high; all ptrend < .001). Higher ST was associated with higher mortality (ptrend across all GRS categories < .001). Interaction tests for PA and ST with the GRS were not statistically significant. Findings support the importance of higher PA and lower ST for reducing mortality risk in older women, regardless of genetic predisposition for longevity.

Association of Social Support with Mild Cognitive Impairment and Dementia Among Older Women: The Women's Health Initiative Memory Study.

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.

Calibration of an Accelerometer Activity Index among Older Women and Its Association with Cardiometabolic Risk Factors.

Purpose: Traditional summary metrics provided by accelerometer device manufacturers, known as counts, are proprietary and manufacturer specific, making them difficult to compare studies using different devices. Alternative summary metrics based on raw accelerometry data have been introduced in recent years. However, they were often not calibrated on ground truth measures of activity-related energy expenditure for direct translation into continuous activity intensity levels. Our purpose is to calibrate, derive, and validate thresholds among women 60 years and older based on a recently proposed transparent raw data based accelerometer activity index (AAI), and to demonstrate its application in association with cardiometabolic risk factors. Methods: We first built calibration equations for estimating metabolic equivalents (METs) continuously using AAI and personal characteristics using internal calibration data (n=199). We then derived AAI cutpoints to classify epochs into sedentary behavior and intensity categories. The AAI cutpoints were applied to 4,655 data units in the main study. We then utilized linear models to investigate associations of AAI sedentary behavior and physical activity intensity with cardiometabolic risk factors. Results: We found that AAI demonstrated great predictive accuracy for METs (R2=0.74). AAI-based physical activity measures were associated in the expected directions with body mass index (BMI), blood glucose, and high density lipoprotein (HDL) cholesterol. Conclusion: The calibration framework for AAI and the cutpoints derived for women older than 60 years can be applied to ongoing epidemiologic studies to more accurately define sedentary behavior and physical activity intensity exposures which could improve accuracy of estimated associations with health outcomes.

In-Home Cannabis Smoking Among a Cannabis-Using Convenience Sample from the Global Drug Survey: With Weighted Estimates for U.S. Respondents.

Introduction: Secondhand and thirdhand tobacco smoke exposure most often occur at home, but little is known about occurrences of in-home cannabis smoking. We ascertained in-home cannabis smoking reported by all cannabis-using (i.e., used in the last 12 months) respondents to the Global Drug Survey (GDS; international-GDS sample), and among U.S. cannabis-using respondents (US-GDS sample). Materials and Methods: We used data collected November 2019-January 2020 for the 2020 GDS, an annual anonymous, cross-sectional survey; respondents were 16+ years old, from 191 countries. We estimated any and daily in-home cannabis smoking in the last 30 days among international-GDS respondents (n=63,797), using mixed effects logistic regression. US-GDS respondents (n=6,580) were weighted to the covariate distribution of the nationally representative 2018 National Survey on Drug Use and Health cannabis-using sample, using inverse odds probability weighting, to make estimates more generalizable to the U.S. cannabis-using population. Results: For the international-GDS cannabis-using respondents, any in-home cannabis smoking was reported by 63.9% of men, 61.9% of women, and 68.6% of nonbinary people; and by age (<25 years old=62.7%, 25-34 years old=65.0%, and 35+ years old=62.8%). Daily in-home cannabis smoking was highest among nonbinary (28.7%) and respondents 35+ years of age (28.0%). For the weighted US-GDS cannabis-using respondents, any in-home cannabis smoking was reported by 49.8% of males and 61.2% of females; and by age (<25 years old=62.6%, 25-34 years old=41.8%, 35+ years old=57.9%). Weighted daily in-home smoking was 23.2% among males and 37.1% among females; by age (<25 years old=34.8%, 25-34 years old=27.8%, and 35+ years old=21.6%). Conclusions: There was high daily cannabis smoking in homes of international-GDS and US-GDS respondents who used cannabis in the last 12 months. In part, due to cannabis legalization, the number of users worldwide has increased over the past decade. Criminal stigma historically associated with cannabis continues to drive those users indoors. In this context, our findings support further investigation of cannabis use behavior to understand how often people are exposed to secondhand and thirdhand cannabis smoke and the consequences of that exposure.

CHAP-child: an open source method for estimating sit-to-stand transitions and sedentary bout patterns from hip accelerometers among children.

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.

Association of compassion and empathy with prosocial health behaviors and attitudes in a pandemic.

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.

Relationship of Social Connectedness With Decreasing Physical Activity During the COVID-19 Pandemic Among Older Women Participating in the Women's Health Initiative Study.

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.

Sedentary Behavior and Atrial Fibrillation in Older Women: The OPACH Study.

Background Sedentary behavior is associated with cardiovascular disease, but its association with incident atrial fibrillation is not well studied. Our aim was to measure the association between objectively measured sedentary behavior and incident atrial fibrillation. Methods and Results Sedentary behavior was measured by a triaxial accelerometer worn on a belt for 1 week. Incident atrial fibrillation was ascertained from Medicare claims. The associations between total sedentary time (or patterns of sedentary behavior) and incident atrial fibrillation were assessed using Cox proportional hazards models adjusted for demographic and clinical covariates. Among 2675 participants (mean age, 78.2 years), there were 268 (10.0%) cases of incident atrial fibrillation at a rate of 31 cases per 1000 person-years. Greater total sedentary time was associated with a higher risk of incident atrial fibrillation after adjustment for age, race and ethnicity, body mass index, education, smoking history, hypertension, diabetes, stroke, heart disease, and other chronic conditions (quartile 4 versus quartile 1: hazard ratio, 1.20, [95% CI, 0.81-1.78]; P for trend=0.05). After adjusting for physical function and self-rated health, this was no longer statistically significant. Both longer mean sedentary bout duration and more continuous sedentary periods (versus frequent breaks in sedentary time) were also associated with higher risks of incident atrial fibrillation, but these associations were also attenuated with serial adjustment. Conclusions Total sedentary time and prolonged patterns of sedentary accumulation were associated with a higher risk of atrial fibrillation in this prospective study of community-dwelling older women, but these associations were attenuated by adjustment for physical function and self-reported health. This suggests that associations between sedentary behavior and atrial fibrillation may be attributable to global measures of overall function and health.

Evaluation of Social Isolation, Loneliness, and Cardiovascular Disease Among Older Women in the US.

Importance: Social isolation and loneliness are increasing public health concerns and have been associated with increased risk of cardiovascular disease (CVD) among older adults. Objective: To examine the associations of social isolation and loneliness with incident CVD in a large cohort of postmenopausal women and whether social support moderated these associations. Design, Setting, and Participants: This prospective cohort study, conducted from March 2011 through March 2019, included community-living US women aged 65 to 99 years from the Women's Health Initiative Extension Study II who had no history of myocardial infarction, stroke, or coronary heart disease. Exposures: Social isolation and loneliness were ascertained using validated questionnaires. Main Outcomes and Measures: The main outcome was major CVD, which was physician adjudicated using medical records and included coronary heart disease, stroke, and death from CVD. Continuous scores of social isolation and loneliness were analyzed. Hazard ratios (HRs) and 95% CIs for CVD were calculated for women with high social isolation and loneliness scores (midpoint of the upper half of the distribution) vs those with low scores (midpoint of the lower half of the distribution) using multivariable Cox proportional hazards regression models adjusting for age, race and ethnicity, educational level, and depression and then adding relevant health behavior and health status variables. Questionnaire-assessed social support was tested as a potential effect modifier. Results: Among 57 825 women (mean [SD] age, 79.0 [6.1] years; 89.1% White), 1599 major CVD events occurred over 186 762 person-years. The HR for the association of high vs low social isolation scores with CVD was 1.18 (95% CI, 1.13-1.23), and the HR for the association of high vs low loneliness scores with CVD was 1.14 (95% CI, 1.10-1.18). The HRs after additional adjustment for health behaviors and health status were 1.08 (95% CI, 1.03-1.12; 8.0% higher risk) for social isolation and 1.05 (95% CI, 1.01-1.09; 5.0% higher risk) for loneliness. Women with both high social isolation and high loneliness scores had a 13.0% to 27.0% higher risk of incident CVD than did women with low social isolation and low loneliness scores. Social support was not a significant effect modifier of the associations (social isolation × social support: r, -0.18; P = .86; loneliness × social support: r, 0.78; P = .48). Conclusions and Relevance: In this cohort study, social isolation and loneliness were independently associated with modestly higher risk of CVD among postmenopausal women in the US, and women with both social isolation and loneliness had greater CVD risk than did those with either exposure alone. The findings suggest that these prevalent psychosocial processes merit increased attention for prevention of CVD in older women, particularly in the era of COVID-19.

Accelerometer-Derived Daily Life Movement Classified by Machine Learning and Incidence of Cardiovascular Disease in Older Women: The OPACH Study.

Background Current physical activity guidelines focus on volume and intensity for CVD prevention rather than common behaviors responsible for movement, including those for daily living activities. We examined the associations of a machine-learned, accelerometer-measured behavior termed daily life movement (DLM) with incident CVD. Methods and Results Older women (n=5416; mean age, 79±7 years; 33% Black, 17% Hispanic) in the Women's Health Initiative OPACH (Objective Physical Activity and Cardiovascular Health) study without prior CVD wore ActiGraph GT3X+ accelerometers for up to 7 days from May 2012 to April 2014 and were followed for physician-adjudicated incident CVD through February 28th, 2020 (n=616 events). DLM was defined as standing and moving in a confined space such as performing housework or gardening. Cox models estimated hazard ratios (HR) and 95% CI, adjusting for age, race and ethnicity, education, alcohol use, smoking, multimorbidity, self-rated health, and physical function. Restricted cubic splines examined the linearity of the DLM-CVD dose-response association. We examined effect modification by age, body mass index, Reynolds Risk Score, and race and ethnicity. Adjusted HR (95% CIs) across DLM quartiles were: 1.00 (reference), 0.68 (0.55-0.84), 0.70 (0.56-0.87), and 0.57 (0.45-0.74); p-trend<0.001. The HR (95% CI) for each 1-hour increment in DLM was 0.86 (0.80-0.92) with evidence of a linear dose-response association (p non-linear>0.09). There was no evidence of effect modification by age, body mass index, Reynolds Risk Score, or race and ethnicity. Conclusions Higher DLM was independently associated with a lower risk of CVD in older women. Describing the beneficial associations of physical activity in terms of common behaviors could help older adults accumulate physical activity.