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The purpose of this study is to identify statistically distinguishable trajectories of childhood body mass index (BMI), an important indicator of developmental status of children, and to provide a summary description of demographic characteristics of children based on these distinctive trajectories. Using data from the Healthy Communities Study (HCS), a large longitudinal dataset with oversamples of Hispanic and Black children across 130 communities in the USA, a group-based trajectory analysis approach was used to estimate trajectories of children based on their BMI-z scores. The three most distinguishable BMI trajectory groups identified for the HCS children show no marked increase or decrease in standardized BMI over an age range of 2 to 11. Approximately 28.5% of children were in a trajectory group with consistently obese BMI-z scores for their sex and age. The patterns of BMI trajectory groups identified for boys and girls are similar, but BMI-z scores for boys tend to be slightly higher than those for girls. These BMI trajectories are characterized by racial/ethnic and socioeconomic status disparities. Hispanic and Black children were more likely to be in the obese trajectory group than White children. Children with parents having less education, or children from low family income level, were more likely to be in the obese trajectory group than counterpart children. The findings suggest that BMI disparities exist from the early years of childhood and persist across childhood, with higher BMI associated with Black and Hispanic children as well as those from low socioeconomic status backgrounds.

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OBJECTIVE: A positive workplace culture of health can have significant benefits for both employees and organizations. The objective of this study was to test the validity and reliability of the Workplace Culture of Health (COH) Scale-Short Form. METHODS: We conducted a confirmatory factor analysis on data collected from a sample of 12,907 employees across 14 organizations. We examined the construct validity of the 14-item short-form version of the Workplace COH scale and assessed its reliability using internal consistency measures. RESULTS: Our confirmatory factor analysis demonstrated that the Workplace COH Scale-Short Form had strong model fit, indicating good construct validity. In addition, we found that all constructs had strong internal consistency reliability. CONCLUSIONS: Findings suggest that the Workplace COH Scale-Short Form is a valid and reliable way to practically assess workplace culture of health from the employee perspective.

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BACKGROUND: There is currently a nationwide effort to bring parks and green spaces within a 10-minute walk of the home. We examined the association between park area within 1 km of a child's residence and self-reported park-specific physical activity (PA) along with accelerometer-derived moderate to vigorous physical activity (MVPA). METHODS: A subsample of K through eighth-grade youth (n = 493) from the Healthy Communities Study reported whether they engaged in park-specific PA during the last 24 hours and wore an accelerometer for up to 7 days. Park area was defined as the percentage of park land in a 1 km Euclidean buffer around the participant's residence, categorized into quintiles. Analysis consisted of logistic and linear regression modeling with interaction effects that controlled for clustering within communities. RESULTS: Regression models estimated greater park-specific PA for participants in the fourth and fifth quintiles of park land. Age, sex, race ethnicity, and family income were unrelated to park-specific PA. Accelerometer analysis indicated that total MVPA was unrelated to park area. Older children (ß = -8.73, P < .001) and girls (ß = -13.44, P < .001) engaged in less MVPA. Seasonality significantly predicted both park-specific PA and total MVPA. CONCLUSION: Increasing park area is likely to improve youth PA patterns, lending support for the 10-minute walk initiative.

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Neighborhood walkability-features of the built environment that promote pedestrian activity-has been associated with greater physical activity and lower body mass index (BMI; calculated as weight (kg)/height (m)2) among neighborhood residents. However, much of the literature has been cross-sectional and only a few cohort studies have assessed neighborhood features throughout follow-up. Using data from the Reasons for Geographic and Racial Differences in Stroke Study (2003-2016) and a neighborhood walkability index (NWI) measured annually during follow-up, we assessed whether the cumulative experience of neighborhood walkability (NWI-years) predicted BMI and waist circumference after approximately 10 years of follow-up, controlling for these anthropometric measures at enrollment. Analyses were adjusted for individual-level sociodemographic covariates and the cumulative experience of neighborhood poverty rate and neighborhood greenspace coverage. Almost a third (29%) of participants changed address at least once during follow-up. The first change of residence, on average, brought the participants to neighborhoods with higher home values and lower NWI scores than their originating neighborhoods. Compared with those having experienced the lowest quartile of cumulative NWI-years, those who experienced the highest quartile had 0.83 lower BMI (95% confidence interval, -1.5, -0.16) and 1.07-cm smaller waist circumference (95% confidence interval, -1.96, -0.19) at follow-up. These analyses provide additional longitudinal evidence that residential neighborhood features that support pedestrian activity are associated with lower adiposity.

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BACKGROUND: Literature has focused on neighborhood environments and their possible impacts on obesity and obesity-related behaviors. However, few longitudinal studies have examined the effect of neighborhood socioeconomic status (nSES) on childhood obesity. PURPOSE: Investigate the longitudinal association between nSES and obesity and obesity-related unhealthy behaviors. METHODS: We obtained data from the Fragile Families and Child Wellbeing Study (N = 2,072). The main exposure was nSES (measured using an index of five variables representing wealth, income, education, and occupation from the Decennial Census 2000) at ages 3, 5, and 9. The outcome was children's body mass index z-score (BMIz) at ages 5, 9, and 15. Three measures of obesity-related behaviors (i.e., child- or caregiver-reported soda/snack food intake, fast-food intake, and sedentary behaviors) at ages 5, 9, and 15 were included as mediators and outcomes. Cross-lagged path analyses were conducted. RESULTS: Higher nSES at a previous wave was associated with consuming less soda/snack foods (ßs = -0.15 to -0.11 [varying by ages], p < .05) and fast-food intake (ßs = -0.21 to -0.14 [varying by ages], p < .01), and less frequent sedentary behaviors (ßs = -0.14 to -0.06 [varying by ages], p < .01), but not with BMIz (ßs = -0.08 to 0.05 [varying by ages], p > .05). Unhealthy behaviors did not mediate the nSES-BMIz association at alpha .05. CONCLUSION: Health policies need to target low-socioeconomic neighborhoods to shape healthy lifestyles in children. To develop effective interventions, future research needs to examine comprehensive potential mediators like obesity-related parenting skills, home environments, and built and social environments on the risk of childhood obesity and obesity-related behaviors.

Neighborhood environments where children live and grow up have been shown to impact obesity and obesity-related behaviors. However, few longitudinal studies have examined the effect of neighborhood socioeconomic status on childhood obesity risk. We investigated the longitudinal association between neighborhood socioeconomic status and obesity and obesity-related unhealthy behaviors from early childhood to adolescence. Using data from the Fragile Families and Child Wellbeing Study, we conducted a statistical analysis to examine a mechanism by which neighborhood socioeconomic status at ages 3, 5, and 9 impacts childhood obesity and obesity-related unhealthy behaviors (i.e., soda/snack food intake, fast-food intake, and sedentary behaviors) at ages 5, 9, and 15. We observed that living in higher socioeconomic neighborhoods was associated with consuming less soda/snack foods and fast-food intake and engaging in sedentary behaviors less frequently. Neighborhood socioeconomic status was not significantly associated with childhood obesity. Our results indicate that community health policies targeting low socioeconomic neighborhoods are warranted to shape children's healthy lifestyle.

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Decreasing sedentary behavior and increasing light physical activity could promote the maintenance of functional abilities for older adults in assisted living (AL). The purpose of this qualitative study was to gather residents' recommendations about a proposed self-efficacy enhancing intervention to replace sedentary behavior with light physical activity. We interviewed 20 residents (mean age 83.1; 60% women). Topics included their current activities and thoughts about physical activity. We presented the intervention and asked questions to inform its modification. Data were analyzed with content and thematic analysis. Specific recommendations included shorter one-hour sessions and framing the intervention as increasing light physical activity rather than decreasing sedentary behavior. The thematic analysis identified multiple factors that could influence intervention implementation, including motivation to be active, safety concerns, ageist attitudes about physical activity, varying abilities of residents, social influences, and limited opportunities for physical activity. These results will inform physical activity intervention implementation for AL residents.

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BACKGROUND: Features of the physical environment may affect post-stroke recovery, but empirical evidence is limited. This study examines associations between features of the physical environment and post-stroke physical quality of life (PH-QOL). METHODS: The study sample included stroke survivors enrolled in the Caring for Adults Recovering from the Effects of Stroke project, a prospective cohort. Features of the physical environment surrounding participants' home addresses were audited using Google Earth. Audits captured information about crossings (e.g. curb-cuts; range 0-4), street segments (e.g. sidewalks; range 0-17.5), and a route (e.g. parks; range 0-27) near participants' home. Summary scores were categorized into tertials representing "few," "some," and "many" pedestrian-friendly features. Post-stroke PH-QOL was measured by the SF-12 (range 0-100) around 6 to 12-, 18-, 27-, and 36-months post-stroke. Linear mixed models were used to estimate PH-QOL over time. Chained multiple imputation was used to account for missing data. RESULTS: Two hundred and seventy-five participants were eligible, among whom 210 had complete data. Most participants lived in areas with "few" features to promote outdoor mobility. Participants living in environments with "some" crossing features had a 4.90 (95% CI: 2.32, 7.48) higher PH-QOL score across the observation period in comparison to participants living in environments with "few" crossing features. Features of the physical environment along street segments and routes were not associated with post-stroke PH-QOL. CONCLUSION: Crossing features are associated with post-stroke PH-QOL. Modifying features of the physical environment at nearby crossings, such as curb-cuts, may be a promising strategy for increasing PH-QOL.

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Despite several dimensions of area socioeconomic status (SES), past literature has been dominated by the use of area socioeconomic position. We examined the longitudinal effect of three area SES measures (i.e., socioeconomic position, inequality, and segregation) on obesity. Using longitudinal data from the Fragile Families & Child Wellbeing Study (N = 1493), we estimated a linear mixed model to examine the effect of three time-varying area SES measures on time-varying measures of objectively measured body mass index z-score (BMIz) from ages 5 years to 15 years. Findings showed that BMIz increased steadily over time (B = 0.02, 95% CI = 0.02, 0.03). A significant interaction between time and area socioeconomic position indicates that children in areas with higher socioeconomic position had a smaller increase in BMIz than those in low socioeconomic areas (B = - 0.02, 95% CI = - 0.02, - 0.01). A non-linear relationship of area income inequality with BMIz such that BMIz was higher as area income inequality was greater, but the effect diminishes in magnitude with a higher level of area income inequality (linear term: B = 0.07; quadratic term: B = - 0.03). Area income segregation was associated with greater BMIz (B = 0.08, 95% CI = 0.03, 0.12). No time interaction effect was found for area income inequality and segregation. Results highlight a need for community health policy efforts and evidence-based interventions to address childhood obesity issues in low-SES areas.

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Importance: The amount and intensity of physical activity required to prevent stroke are yet to be fully determined because of previous reliance on self-reporting measures. Furthermore, the association between objectively measured time spent being sedentary as an independent risk factor for stroke is unknown. Objective: To investigate the associations of accelerometer-measured sedentary time and physical activity of varying intensity and duration with the risk of incident stroke. Design, Setting, and Participants: This cohort study involved participants who were enrolled in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study from February 5, 2003, to October 30, 2007. Accelerometer data were collected from 7607 Black and White adults 45 years or older in the contiguous US between May 12, 2009, and January 5, 2013. Data on other races and ethnicities were not collected for scientific and clinical reasons. By design, Black adults and residents of the southeastern US stroke belt and stroke buckle were oversampled. Data were analyzed from May 5, 2020, to November 11, 2021. Exposures: Sedentary time, light-intensity physical activity (LIPA), and moderate- to vigorous-intensity physical activity (MVPA) were measured using a hip-mounted accelerometer worn for 7 consecutive days and stratified by tertile for the analyses. Main Outcomes and Measures: Incident stroke. Results: Among 7607 participants, the mean (SD) age was 63.4 (8.5) years; 4145 participants (54.5%) were female, 2407 (31.6%) were Black, and 5200 (68.4%) were White. A total of 2523 participants (33.2%) resided in the stroke belt, and 1638 (21.5%) resided in the stroke buckle. Over a mean (SD) of 7.4 (2.5) years of follow-up, 286 incident stroke cases (244 ischemic [85.3%]) occurred. The fully adjusted hazard ratios (HRs) for incident stroke in the highest tertile compared with the lowest tertile were 0.74 (95% CI, 0.53-1.04; P = .08) for LIPA and 0.57 (95% CI, 0.38-0.84; P = .004) for MVPA. Higher sedentary time was associated with a 44% greater risk of incident stroke (HR, 1.44; 95% CI, 0.99-2.07; P = .04). When comparing the highest with the lowest tertile, mean sedentary bout duration was associated with a significantly greater risk of incident stroke (HR, 1.53; 95% CI, 1.10-2.12; P = .008). After adjustment for sedentary time, the highest tertile of unbouted MVPA (shorter bouts [1-9 minutes]) was associated with a significantly lower risk of incident stroke compared with the lowest tertile (HR, 0.62; 95% CI, 0.41-0.94; P = .02); however, bouted MVPA (longer bouts [at least 10 minutes]) was not (HR, 0.78; 95% CI, 0.53-1.15; P = .17). When expressed as continuous variables, sedentary time was positively associated with incident stroke risk (HR per 1-hour/day increase in sedentary time: 1.14; 95% CI, 1.02-1.28; P = .02), and LIPA was negatively associated with incident stroke risk (HR per 1-hour/day increase in LIPA: 0.86; 95% CI, 0.77-0.97; P = .02). Conclusions and Relevance: In this cohort study, objectively measured LIPA, MVPA, and sedentary time were significantly and independently associated with incident stroke risk. Longer sedentary bout duration was also independently associated with an increased risk of incident stroke. These findings suggest that replacing sedentary time with LIPA, or even very short bouts of MVPA, may lower stroke risk, supporting the concept of moving more and sitting less as a beneficial stroke risk reduction strategy among adults.

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Stroke survivors face unique challenges in the outdoor environment when returning to their home community following a stroke. Challenges include navigating uneven terrain, social stigma, and adapting to changes in functioning. Outdoor environments may serve as potential points of intervention to promote independence and participation post stroke. This study aimed to understand lived post-stroke experience in the outdoor environment as it pertains to independent mobility. METHODS: Qualitative semi-structured interviews were conducted with 20 stroke survivors (8 males, 12 females; mean age 64.2 years: range 45 years-90 years). Participants were eligible if they were over the age of 45, could communicate in English, lived outside a nursing home, able to walk safely outdoors, were a minimum of six-months post stroke, and had no severe cognitive impairment. Interviews with participants were tape recorded, audio files were transcribed verbatim, codes were created and applied to transcripts, and themes were generated using interpretative phenomenological analysis. RESULTS: Post-stroke experiences in the outdoor environment were multidimensional. Three themes emerged from the stroke survivors' description of personal experiences in the outdoor environment. These themes included feelings of vigilance, employing adaptation strategies, and management of dynamic relations between the self and context. DISCUSSION: The findings highlight the post-stroke experience traversing the outdoor environment. Investing in the public outdoor environment to remove barriers and install facilitators could reduce feelings of apprehension and hypervigilance while walking in the outdoor environment. Future research is needed to evaluate the role of environmental interventions on hypervigilance in the outdoor environment post stroke.

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INTRODUCTION: Post-stroke physical activity has widespread health benefits. Environmental exposures may shape post-stroke physical activity behavior. This study investigates the relationships between environmental exposures and post-stroke physical activity. METHODS: Stroke survivors (n=374) from a cohort of Black and White adults with post-stroke accelerometer data (2009-2013) were eligible for this study. Participants' home addresses were linked with secondary data to capture environmental characteristics, including annual density of neighborhood resources (e.g., parks, physical activity facilities, and intellectual stimulation destinations), 2010 neighborhood SES, 2010 neighborhood crime, and daily information on extremely cold days. Post-stroke light physical activity and moderate-to-vigorous physical activity were captured using accelerometers over a 7-day period. Linear regression and 2-part/hurdle models were used to estimate the relationship between the density of neighborhood resources with light physical activity and with moderate-to-vigorous physical activity, respectively. Analyses were conducted in 2021. RESULTS: A 10% increase in the number of extremely cold days was associated with 6.37 fewer minutes of daily light physical activity (95% CI= -11.37, -1.37). A 1-SD increase in neighborhood SES was associated with greater odds (OR=1.10, 95% CI=1.02, 1.19) of doing any moderate-to-vigorous physical activity. Among participants obtaining any moderate-to-vigorous physical activity, a 1-unit (count/km2) increase in destinations for intellectual stimulation was associated with 0.99 (95% CI=0.02, 1.97) more minutes of daily moderate-to-vigorous physical activity. All other environmental exposures were not associated with post-stroke light physical activity or moderate-to-vigorous physical activity. CONCLUSIONS: Environmental exposures may facilitate physical activity participation among stroke survivors. This study found that weather, neighborhood SES, and proximity to destinations for intellectual stimulation were associated with physical activity over and above individual factors.

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BACKGROUND: Studies have shown neighborhood walkability is associated with obesity. To advance this research, study designs involving longer follow-up, broader geographic regions, appropriate neighborhood characterization, assessment of exposure length and severity, and consideration of stayers and movers are needed. Using a cohort spanning the conterminous United States, this study examines the longitudinal relationship between a network buffer-derived, duration-weighted neighborhood walkability measure and two adiposity-related outcomes. METHODS: This study included 12,846 Black/African American and White adults in the REasons for Geographic And Racial Differences in Stroke study. Body mass index (BMI) and waist circumference (WC) were assessed at baseline and up to 13.3 years later (M (SD) = 9.4 (1.0) years). BMI and WC were dichotomized. Walk Score® was duration-weighted based on time at each address and categorized as Very Car-Dependent, Car-Dependent, Somewhat Walkable, Very Walkable, and Walker's Paradise. Unadjusted and adjusted logistic regression models tested each neighborhood walkability-adiposity association. Adjusted models controlled for demographics, health factors, neighborhood socioeconomic status, follow-up time, and either baseline BMI or baseline WC. Adjusted models also tested for interactions. Post-estimation Wald tests examined whether categorical variables had coefficients jointly equal to zero. Orthogonal polynomial contrasts tested for a linear trend in the neighborhood walkability-adiposity relationships. RESULTS: The odds of being overweight/obese at follow-up were lower for residents with duration-weighted Walk Score® values in the Walker's Paradise range and residents with values in the Very Walkable range compared to residents with values in the Very Car-Dependent range. Residents with duration-weighted Walk Score® values classified as Very Walkable had significantly lower odds of having a moderate-to-high risk WC at follow-up relative to those in the Very Car-Dependent range. For both outcomes, the effects were small but meaningful. The negative linear trend was significant for BMI but not WC. CONCLUSION: People with cumulative neighborhood walkability scores in the Walker's Paradise range were less likely to be overweight/obese independent of other factors, while people with scores in the Very Walkable range were less likely to be overweight/obese and less likely to have a moderate-to-high risk WC. Addressing neighborhood walkability is one approach to combating obesity.

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BACKGROUND: The COVID-19 pandemic triggered a seismic shift in education to web-based learning. With nearly 20 million students enrolled in colleges across the United States, the long-simmering mental health crisis in college students was likely further exacerbated by the pandemic. OBJECTIVE: This study leveraged mobile health (mHealth) technology and sought to (1) characterize self-reported outcomes of physical, mental, and social health by COVID-19 status; (2) assess physical activity through consumer-grade wearable sensors (Fitbit); and (3) identify risk factors associated with COVID-19 positivity in a population of college students prior to release of the vaccine. METHODS: After completing a baseline assessment (ie, at Time 0 [T0]) of demographics, mental, and social health constructs through the Roadmap 2.0 app, participants were instructed to use the app freely, wear the Fitbit, and complete subsequent assessments at T1, T2, and T3, followed by a COVID-19 assessment of history and timing of COVID-19 testing and diagnosis (T4: ~14 days after T3). Continuous measures were described using mean (SD) values, while categorical measures were summarized as n (%) values. Formal comparisons were made on the basis of COVID-19 status. The multivariate model was determined by entering all statistically significant variables (P<.05) in univariable associations at once and then removing one variable at a time through backward selection until the optimal model was obtained. RESULTS: During the fall 2020 semester, 1997 participants consented, enrolled, and met criteria for data analyses. There was a high prevalence of anxiety, as assessed by the State Trait Anxiety Index, with moderate and severe levels in 465 (24%) and 970 (49%) students, respectively. Approximately one-third of students reported having a mental health disorder (n=656, 33%). The average daily steps recorded in this student population was approximately 6500 (mean 6474, SD 3371). Neither reported mental health nor step count were significant based on COVID-19 status (P=.52). Our analyses revealed significant associations of COVID-19 positivity with the use of marijuana and alcohol (P=.02 and P=.046, respectively) and with lower belief in public health measures (P=.003). In addition, graduate students were less likely and those with ≥20 roommates were more likely to report a COVID-19 diagnosis (P=.009). CONCLUSIONS: Mental health problems were common in this student population. Several factors, including substance use, were associated with the risk of COVID-19. These data highlight important areas for further attention, such as prioritizing innovative strategies that address health and well-being, considering the potential long-term effects of COVID-19 on college students. TRIAL REGISTRATION: ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/29561.

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Background and Purpose: We examined differences in the volume and pattern of physical activity (PA) and sedentary behavior between adults with and without stroke. Methods: We studied cohort members with an adjudicated or self-reported stroke (n=401) and age-, sex-, race-, region of residence-, and body mass index-matched participants without a history of stroke (n=1203) from the REGARDS study (Reasons for Geographic and Racial Differences in Stroke). Sedentary behavior (total volume and bouts), light-intensity PA, and moderate-to-vigorous-intensity PA were objectively measured for 7 days via hip-worn accelerometer. Results: Sedentary time (790.5±80.4 versus 752.4±81.9 min/d) and mean sedentary bout duration (15.7±12.6 versus 11.9±8.1 min/d) were higher and PA (light-intensity PA: 160.5±74.6 versus 192.9±73.5 min/d and moderate-to-vigorous-intensity PA: 9.0±11.9 versus 14.7±17.0 min/d) lower for stroke survivors compared with controls (P<0.001). Stroke survivors also accrued fewer activity breaks (65.5±21.9 versus 73.31±18.9 breaks/d) that were shorter (2.4±0.7 versus 2.7±0.8 minutes) and lower in intensity (188.4±60.8 versus 217.9±72.2 counts per minute) than controls (P<0.001). Conclusions: Stroke survivors accrued a lower volume of PA, higher volume of sedentary time, and exhibited accrual patterns of more prolonged sedentary bouts and shorter, lower intensity activity breaks compared with persons without stroke.

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BACKGROUND: Epidemiological studies utilize residential histories to assess environmental exposure risk. The validity from using commercially-sourced residential histories within national longitudinal studies remains unclear. Our study assessed predictors of non-agreement between baseline addresses from the commercially-sourced LexisNexis database and participants in the national longitudinal study, REasons for Geographic and Racial Differences in Stroke (REGARDS). Additionally, we assessed differences in stroke risk by neighborhood socioeconomic score (nSES) based on participant reported address compared to nSES from LexisNexis/REGARDS matched baseline address. METHODS: From January 2003-October 2007, REGARDS enrolled 30,239 black and white adults aged 45 and older within the continental United States and collected their baseline address. ArcGIS Desktop 10.5.1 with ESRI 2016 Business Analyst Data was used to geocode baseline addresses from LexisNexis and REGARDS. Logistic regression was used to estimate the likelihood that LexisNexis address matched REGARDS baseline address for each participant. Survival analysis was used to estimate association between nSES and incident stroke. RESULTS: Approximately 91% of REGARDS participants had a LexisNexis address. Of these geocoded addresses, 93% of REGARDS baseline addresses matched LexisNexis addresses. Odds of agreement between LexisNexis and REGARDS was higher for older-aged participants (OR = 1.02 per year, 95% CI: 1.01, 1.02), blacks compared to whites (OR = 1.16, 95% CI: 1.05, 1.29), females compared to males (OR = 1.15, 95% CI: 1.04, 1.26), participants with an income of $34k-74k compared to an income less than $20k (OR = 1.62, 95% CI: 1.39, 1.89). Odds of agreement were lower for residents in Midwest compared to residents in the south (OR = 0.82, 95% CI: 0.73, 0.94). No significant differences in nSES-stroke associations were observed between REGARDS only and LexisNexis/REGARDS matched addresses; however, differences in interactions were observed. CONCLUSION: Agreement between LexisNexis and REGARDS addresses varied by sociodemographic groups, potentially introducing bias in studies reliant on LexisNexis alone for residential address data.

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Objectives: Socialization predicts cognitive aging outcomes. Neighborhoods may facilitate socially engaged aging and thus shape cognition. We investigated places where older adults socialized and whether availability of these sites was associated with cognitive outcomes. Methods: Qualitative analysis of interviews and ethnography with 125 older adults (mean age 71 years) in Minneapolis identified where participants socialized outside of home. This informed quantitative analysis of a national sample of 21,151 older Americans (mean age at baseline 67 years) from the Reasons for Geographic and Racial Differences in Stroke study. Multilevel generalized additive models described associations between access to key social places and cognitive function and decline. Results: Qualitative analysis identified eateries, senior centers, and civic groups as key places to socialize. We identified significant positive associations between kernel density of senior centers, civic/social organizations, and cognitive function. Discussion: Specific neighborhood social infrastructures may support cognitive health among older adults aging in place.

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BACKGROUND: Understanding how and where children accumulate their physical activity (PA) and sedentary minutes throughout the day has important implications for behavioral interventions. PURPOSE: The purpose of this study was to examine the duration and intensity of habitual PA and sedentary time (SED) at and away from school among preadolescent children. METHODS: Data from twenty-one children ages 7-11 (57% girls; 57% non-white; 24% overweight/obese) were included in this analysis. Proportion of time spent in PA, SED, and SED bouts were examined on school days (in-school and out-of-school) and non-school days via accelerometry. RESULTS: When comparing school time with non-school time on school days, children accumulated a higher proportion of light PA while in-school [49.3% (i.e. 5 minutes 18 seconds) vs. 39.6% (i.e. 3 hours 53 minutes), p=0.01]. While at school, the proportion of time spent in SED was less [46.3% (i.e. 3 hours 7 minutes) vs. 56.3% (i.e. 5 hours 32 minutes), p=0.01] and fewer children spent time engaged in prolonged sitting compared to out-of-school [uninterrupted SED for 30 minutes 52.4% (i.e. 11 children) vs. 85.7% (i.e. 18 children), p=0.02]. DISCUSSION: These findings suggest children are proportionately most active and least sedentary when at school, yet children only accumulated approximately 18 minutes of moderate-to-vigorous PA in this environment. TRANSLATION TO HEALTH EDUCATION PRACTICE: These preliminary findings can help to inform physical activity programming designed to promote life-long physical activity behaviors in children.

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Objective.The ActiGraph is commonly used for measuring sedentary behavior (SB), but the best data processing technique is not established for sedentary adults with chronic illness. The purpose of this study was to process ActiGraph vertical axis and vector magnitude data with multiple combinations of filters, non-wear algorithm lengths, and cut-points and to compare ActiGraph estimates to activPAL-measured sedentary time in sedentary adults with chronic obstructive pulmonary disease (COPD).Approach.This study was a secondary analysis of adults ≥50 years (N = 59; mean age: 69.4 years;N = 31 males) with COPD. Participants woreActiGraph GT9XandactivPAL3for 7 d. ActiGraph vertical axis and vector magnitude data were processed using combinations of filters (normal, low frequency extension (LFE)), non-wear algorithm lengths (60, 90, 120 min), and cut-points for SB previously validated in older adults (two for vertical axis and three for vector magnitude data). The Bland-Altman method was used to assess concordance between sedentary time measured with 30 ActiGraph techniques and activPAL-measured sedentary time.Main results. Agreement between the two devices was moderate to strong for all techniques; concordance correlations ranged from 0.614 to 0.838. Limits of agreement were wide. The best overall technique was vector magnitude data with LFE filter, 120 min non-wear algorithm, and <40 counts/15 s SB cut-point (concordance correlation 0.838; mean difference -11.7 min d-1).Significance. This analysis supports the use of ActiGraph vector magnitude data and LFE filter in adults with COPD, but also demonstrates that other techniques may be acceptable with appropriate cut-points. These results can guide ActiGraph data processing decisions.

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Sedentary behavior contributes to health decline and frailty in older adults, especially the oldest old. The purpose of this systematic review was to synthesize evidence describing the volume of device-measured sedentary behavior and factors that influence sedentary behavior in community-dwelling adults aged 80 and older. Four electronic databases were searched in August 2018; the search was updated in September 2019 and December 2020. Twenty-one articles representing 16 unique datasets from six countries met inclusion criteria. Various devices and data processing methods were used to measure sedentary behavior; the most common device was the ActiGraph accelerometer. Sedentary time during the waking day ranged from 7.6 to 13.4 h/day. Studies using similar measurement methods (hip-worn ActiGraph with uniaxial cut-point <100 counts per minute) had a weighted mean of 10.6 h/day. Subgroup analyses revealed that male gender and age ≥85 may contribute to increased sedentary behavior. Only seven individual articles examined factors that influence sedentary behavior in the 80 and older age group; older age, male gender, non-Hispanic white race/ethnicity, social disadvantage, and declining cognitive function (in men) were associated with increased sedentary behavior. In conclusion, the oldest old are highly sedentary and little is known about factors that influence their sedentary behavior.

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Physical exercise benefits cognitive functioning and can protect against neurodegeneration. Neighborhood environments may be pivotal to physically active aging, and thus help shape older adults' cognitive function. This mixed-methods study investigated where older adults exercised outside the home, and whether availability of these neighborhood sites was associated with cognitive function. We thematically analyzed qualitative data from semi-structured interviews in 2015 with 125 older adults (mean age = 71) in the Minneapolis (MN) metropolitan area. Results identified nearby public parks, fitness/sports amenities, and walkable destinations as motivators for recreational exercise and active transit among participants. These findings informed quantitative analysis of the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a national sample of older Black and white Americans (n = 21,151; mean age at assessment = 67; data collected 2006-2017). We used generalized additive multilevel models to examine whether neighborhood features that qualitative participants identified as encouraging physical activity were associated with elevated levels of cognitive function. Results indicated that residing in neighborhoods with greater availability of local parks, access to recreational amenities, and business density was associated with higher levels of cognitive function. We found no evidence to suggest a significant association between availability of these neighborhood resources and rate of cognitive decline. This study identifies specific neighborhood active aging infrastructure that may support cognitive function among older adults aging in place.

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