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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 FamiliesChild 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.

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

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 (βs = −0.15 to −0.11 [varying by ages], p < .05) and fast-food intake (βs = −0.21 to −0.14 [varying by ages], p < .01), and less frequent sedentary behaviors (βs = −0.14 to −0.06 [varying by ages], p < .01), but not with BMIz (βs = −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.

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.

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).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.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.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.

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.

Objectives: This cross-sectional study examines the association between perceived sidewalk conditions and neighborhood participation among older adults in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. Methods: Between 2013–2016, 14,233 REGARDS participants completed a second in-home visit. Using logistic regression, we cross-sectionally examined if perceived severity of sidewalk problems was associated with going into the neighborhood less than once compared to 1–7 times per week. Results: The analytic sample included participants ( N = 9863) with nonmissing data. The likelihood of going into the neighborhood less than one time per week was greater among participants who reported minor (OR = 1.15; 95% CI: 1.00, 1.33), somewhat serious (OR = 1.41; 95% CI: 1.17, 1.70), and very serious (OR = 1.65; 95% CI: 1.38, 1.98) sidewalk problems in their neighborhood compared to those reporting no sidewalk problems, independent of demographic, socioeconomic, and impairment characteristics. Discussion: Perceived sidewalk problems appear to deter neighborhood participation among older adults.

Background Although previous research has highlighted the association between the built environment and individual health, methodological challenges in assessing the built environment remain. In particular, many researchers have demonstrated the high inter-rater reliability of assessing large or objective built environment features and the low inter-rater reliability of assessing small or subjective built environment features using Google Street View. New methods for auditing the built environment must be evaluated to understand if there are alternative tools through which researchers can assess all types of built environment features with high agreement. This paper investigates measures of inter-rater reliability of GigaPan®, a tool that assists with capturing high-definition panoramic images, relative to Google Street View. Methods Street segments (n = 614) in Pittsburgh, Pennsylvania in the United States were randomly selected to audit using GigaPan® and Google Street View. Each audit assessed features related to land use, traffic and safety, and public amenities. Inter-rater reliability statistics, including percent agreement, Cohen’s kappa, and the prevalence-adjusted bias-adjusted kappa (PABAK) were calculated for 106 street segments that were coded by two, different, human auditors. Results Most large-scale, objective features (e.g. bus stop presence or stop sign presence) demonstrated at least substantial inter-rater reliability for both methods, but significant differences emerged across finely detailed features (e.g. trash) and features at segment endpoints (e.g. sidewalk continuity). After adjusting for the effects of bias and prevalence, the inter-rater reliability estimates were consistently higher for almost all built environment features across GigaPan® and Google Street View. Conclusion GigaPan® is a reliable, alternative audit tool to Google Street View for studying the built environment. GigaPan® may be particularly well-suited for built environment projects with study settings in areas where Google Street View imagery is nonexistent or updated infrequently. The potential for enhanced, detailed imagery using GigaPan® will be most beneficial in studies in which current, time sensitive data are needed or microscale built environment features would be challenging to see in Google Street View. Furthermore, to better understand the effects of prevalence and bias in future reliability studies, researchers should consider using PABAK to supplement or expand upon Cohen’s kappa findings.

It is necessary to effectively assess functional mobility for appropriate prosthetic prescription and post-amputation rehabilitation. As part of this process, patients' ability for variable cadence and community ambulation are assessed in-clinic, often through visual assessments and without objective standards. The purpose of this study was to explore the clinical viability of using wearable sensors to characterize the functional mobility of people with lower limb amputation. We collected inertial measurement unit (IMU) and global positioning system (GPS) data over two weeks, from 17 individuals with lower limb amputation and 14 healthy non-amputee controls. We calculated stride-by-stride cadence, walking speed and stride lengths, along with whether they occurred in or out of the home. Self-selected walking speed was also assessed in the lab. Compared to the lab, both groups walked slower and with a lower cadence during their daily lives. There were no differences in cadence variability between groups or between strides taken in and out of the home. Both groups walked faster and with greater stride lengths away from the homes. The results suggest that functional capacity measured in the lab was not necessarily reflected in routine walking during daily life. The walking measures derived in this approach can be used to aid in the prosthetic prescription process or in the assessment of different interventions.

Background: Physical activity (PA) provides important health benefits to children, and a large percentage of children’s PA occurs at home. The purpose of this study was to examine the associations between psychosocial, home, and neighborhood environmental factors and children’s reported PA at home and in the neighborhood, during the transition from elementary to high school. Methods: A total of 555 participants (44% boys) were recruited in grade 5 and followed through grades 6, 7, and 9. Children self-reported PA in 3 locations—at home, in the neighborhood, and on the street. Children reported parent support and neighborhood environment, parents reported PA equipment, and a windshield survey assessed incivilities and outside PA equipment. Longitudinal Poisson models evaluated the relationships between environmental variables and 3 self-reported PA variables, adjusting for gender, race/ethnicity, and parent education. Results: Parent support and PA equipment were significant positive predictors of home PA. Child’s perceived environment (positive) and incivilities (negative) were significant predictors of neighborhood PA. Parental support, perceived environment, and outside PA equipment were positive significant predictors of street PA. Conclusions: This study supports the need for both family and community/neighborhood PA interventions that encourage parents to support child PA and for communities to reduce incivilities.

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 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

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 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. CLINICALTRIAL ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788 INTERNATIONAL REGISTERED REPORT RR2-10.2196/29561

This paper describes environmental exposures of adult participants in the Moving to Opportunity for Fair Housing (MTO) experiment over a four to seven year period from baseline to the interim evaluation. The MTO experiment randomized participants living in public housing or private assisted housing at baseline into experimental and control groups and provided a housing voucher for experimental group participants to move to neighborhoods with less than 10 percent of the population below the poverty line. However, few studies have examined how this move affected exposures to health promoting environments. We used data on residential locations of MTO participants and archival data on the built and food environment to construct environmental exposure variables. MTO participants in the experimental and Section 8 groups lived in neighborhoods with higher food prices, less high intensity development and more open space relative to the control group. The findings suggest that housing policies can have potential health consequences by altering health-related environmental exposures.

BackgroundFew studies have examined the moderating role of neighbourhood environments on the relation between psychosocial factors and physical activity, and results of these studies are mixed. This study examined this relationship in 636 fifth to seventh graders from South Carolina, USA.MethodsFrom 2010 to 2013, children and their parent/guardian completed annual self-reported surveys assessing psychosocial factors, and children wore accelerometers for 1 week each year. Neighbourhood environments were classified as supportive or non-supportive for physical activity (PA) based on in-person audits of facilities near children’s homes and windshield surveys of children’s streets. Growth curve analyses were completed to assess the moderating effect of the neighbourhood physical activity environment (NPAE) on the relation between psychosocial factors and total physical activity (TPA) over time.ResultsSignificant interactions on TPA were found for (1) time, NPAE and parent-reported parent support for PA; (2) time, NPAE and child-reported equipment in the home; (3) child-reported parental support for PA and time; (4) child-reported parental support for PA and NPAE; (5) PA self-schema and time and (6) child-reported parental encouragement and time. Parental support and a supportive NPAE were important for TPA, especially as children transitioned to middle school, whereas home equipment and a supportive NPAE were important for fifth graders’ TPA.ConclusionConsistent with the socioecological model, PA behaviour was dependent on interacting effects across levels of influence. Generally, both a supportive NPAE and positive psychosocial factors were needed to support TPA. Factors influencing PA across multiple levels should be addressed in PA interventions.

BackgroundThere have been mixed findings regarding the relationship between walkability and level of physical activity in adults.MethodsParticipants from The REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort (N=7561) were used to examine the association between Walk Score and physical activity measured via accelerometry. The subsample included geographically diverse adults, who identified as black or white, and were over the age of 45. Linear regression was used to examine the direct effects, as well as the interaction, of Walk Score by sex, age and race.ResultsThe majority of participants lived in a ‘Very Car-Dependent’ location (N=4115). Only 527 lived in a location that was ‘Very Walkable/Walker’s Paradise’. Living in a location with a Walk Score of ‘Very Car-Dependent’ compared with ‘Very Walkable/Walker’s Paradise’ was associated with 19% (0.81; 95% CI 0.73 to 0.90) lower predicted minutes of moderate to vigorous physical activity per day, after adjustment for covariates. There was no evidence of statistically significant interactions between Walk Score and sex, age or race (p>0.05).ConclusionAccumulated daily time in moderate to vigorous physical activity was higher for participants living in neighbourhoods designated as ‘Very Walkable/Walker’s Paradise’. This effect was not moderated by sex, age or race of participants.

Introduction Interventions to promote physical activity in children should be informed by knowledge of the factors that influence physical activity behavior during critical developmental transitions. The purpose of this study is to identify, from a comprehensive, multidomain set of factors, those that are associated with change in objectively measured physical activity in children as they transition from elementary to middle school. Methods The study used a prospective cohort design, with children observed in fifth, sixth, and seventh grades. Growth curve analyses were used to examine associations between exposure variables measured at baseline and children's physical activity across three observations. A total of 828 children, aged 10.6 (SD=0.5) years at baseline provided physical activity data in fifth grade and at one or both follow-ups. Exposure variables assessed child characteristics, parent characteristics, home characteristics, social factors, school environment, and community characteristics. Physical activity was measured via accelerometry. Data were collected in two school districts in South Carolina in 2010–2013 and analyzed in 2017. Results Variables measured within the child, parent/home, and community domains were positively associated with children's physical activity as they transitioned from fifth to seventh grade. These included parent encouragement of physical activity, parental support for physical activity, child sports participation, parent's report of the child's physical activity level, the child's time spent outdoors, social spaces for physical activity in the community, and the number of physical activity facilities that were proximal to the child's home. Conclusions Interventions designed to increase children's physical activity should include strategies that target multiple domains of influence.

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.

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., Highlights • Approximately 9% of REGARDS participants did not have a LexisNexis address history available. • Of participants with both REGARDS and LexisNexis addresses available, 93% of these addresses matched. • Agreement between REGARDS and LexisNexis address varied by socio-demographics—potentially biasing environmental exposures. • Compared to LexisNexis, REGARDS addresses may be valuable in detecting interactions contributing to stroke disparities.

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 P 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.

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.To investigate the associations of accelerometer-measured sedentary time and physical activity of varying intensity and duration with the risk of incident stroke.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.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.Incident stroke.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).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.

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.

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.

Objective: Research demonstrates mastery motivational climates are effective in increasing children’s physical activity (PA) and fundamental movement skills (FMS). In this study, we evaluated the effects of different types of mastery climate physical education (PE) lessons on PA and FMS. Methods: Participants in this 10-week randomized trial (N = 45, mean age = 9.0±0.5years, 48.9% boys) were randomly assigned to one of 3 mastery climate PE lessons: (1) FMS, (2) PA, or (3) FMS + PA. We conducted one-way ANCOVAs to determine differences between lessons on percentage of time spent in PA levels and changes in FMS scores. Results: There was a statistically significant effect of lesson type on moderate-to-vigorous PA (MVPA; F(2,40) = 7.730, p 2, 38 = 3.431, p =.043) and total FMS score (F2, 38 = 4.993, p =.027). Post hoc analyses revealed children receiving the FMS lesson had significantly higher MVPA levels compared to other lessons and higher VPA levels compared to the PA lesson (all ps

(1) Background: Few studies have examined the relationship between neighborhood socioeconomic deprivation (SED) and weight-related outcomes in youth, controlling for weight-related behaviors. Hence, the purpose of this study was to examine the association between neighborhood SED, weight status, and fat mass in a diverse sample of youth, before and after controlling for physical activity and diet. (2) Methods: The sample included 828 youth from the Transitions and Activity Changes in Kids study. Neighborhood SED was expressed as an index score at the census tract of residence. Height, weight, and body composition were measured and used to calculate fat mass index (FMI) and weight status. Moderate-to-vigorous physical activity (MVPA) and sedentary behavior (min/h) were measured via accelerometry. Diet quality was assessed via the Block Food Screener for Kids. Multilevel regression models were employed to examine these relationships. (3) Results: Neighborhood SED was significantly associated with FMI and weight status before and after controlling for MVPA, sedentary behavior, and diet. Notably, youth residing in the most deprived neighborhoods had significantly higher FMI and were 30% more likely to be overweight/obese (OR = 1.30, 95% CI = 1.03&ndash, 1.65). (4) Conclusions: Greater neighborhood SED was consistently and significantly associated with higher fat mass index and increased likelihood of overweight/obesity among youth.

Background Improving the neighborhood environment may help address chronic disease and mortality. To identify neighborhood features that are predictors of health, objective assessments of the environment are used. Multiple studies have reported on cross-sectional assessments of health-related neighborhood features using direct observation. As study designs expand to better understand causation and predictors of change, there is a need to test whether direct observation methods are adequate for longitudinal assessment. To our knowledge, this is the first study to report on the reliability of repeated measurements of the neighborhood environment, and their stability, over time. Methods The Pittsburgh Hill/Homewood Research on Neighborhood Change and Health (PHRESH) study conducted longitudinal assessments in two low-income, African American neighborhoods at three waves (years 2012, 2015, 2017). The PHRESH audit tool is a modification of earlier validated tools, with an emphasis on environment features relevant for physical activity, sleep, and obesogenic behaviors. Trained data-collector pairs conducted direct observations of a 25% sample of street segments in each neighborhood. At each wave, we audited a sub-sample of street segments twice and assessed reliability using percentage inter-observer agreement and krippendorf’s alpha statistics. Stability of these items was assessed as exhibiting moderate or high agreement at every time point. Results Across waves, a majority (81%) of the items consistently demonstrated moderate to high agreement except for items such as public/communal space, amount of shade, sidewalk features, number of traffic lanes, garden/flower bed/planter, art/statue/monument, amount of trash, and physical disorder. The list of items with poor agreement includes features that are easy to miss (e.g. flower bed/planter), hard to assess from outside (e.g. public/communal space), or may change quickly (e.g. amount of trash). Conclusion In this paper, we have described implementation methods, reliability results and lessons learned to inform future studies of change. We found the use of consistent methods allowed us to conduct reliable, replicable longitudinal assessments of the environment. Items that did not exhibit stability are less useful for detecting real change over time. Overall, the PHRESH direct observation tool is an effective and practical instrument to detect change in the neighborhood environment.

ObjectiveTo summarize overall patterns of the impact of neighborhood socioeconomic status (nSES) on stroke incidence and uncover potential gaps in the literature, we conducted a systematic review of studies examining the association between nSES and stroke incidence, independent of individual SES.MethodsFour electronic databases and reference lists of included articles were searched, and corresponding authors were contacted to locate additional studies. A keyword search strategy included the 3 broad domains of neighborhood, SES, and stroke. Eight studies met our inclusion criteria (e.g., nSES as an exposure, individual SES as a covariate, and stroke incidence as an outcome). We coded study methodology and findings across the 8 studies.ResultsThe results provide evidence for the overall nSES and stroke incidence association in Sweden and Japan, but not within the United States. Findings were inconclusive when examining the nSES-stroke incidence association stratified by race. We found evidence for the mediating role of biological factors in the nSES-stroke incidence association.ConclusionsHigher neighborhood disadvantage was found to be associated with higher stroke risk, but it was not significant in all the studies. The relationship between nSES and stroke risk within different racial groups in the United States was inconclusive. Inconsistencies may be driven by differences in covariate adjustment (e.g., individual-level sociodemographic characteristics and neighborhood-level racial composition). Additional research is needed to investigate potential intermediate and modifiable factors of the association between nSES and stroke incidence, which could serve as intervention points.

Background: The prevalence of childhood obesity is higher in economically and socially deprived areas. Higher levels of physical activity reduce the risk of excessive weight gain in youth, and research has focused on environmental factors associated with children’s physical activity, though the term “physical activity desert” has not come into wide use. Methods: This exploratory study operationalized the term “physical activity desert” and tested the hypothesis that children living in physical activity deserts would be less physically active than children who do not. A cross-sectional study design was applied with 992 fifth-grade students who had provided objectively measured physical activity data. Five of 12 possible elements of the built environment were selected as descriptors of physical activity deserts, including no commercial facilities, no parks, low play spaces, no cohesion, and the presence of incivilities. Results: Univariate and multivariate analyses showed that only the absence of parks was associated with less physical activity in children. Conclusion: Children living in a “no park” zone were less active than their counterparts who lived near a park. This study contributes preliminary conceptual and operational definitions of “physical activity desert.” Future studies of physical activity deserts should be undertaken in larger and more diverse samples.

IntroductionData supports that motor skills are an underlying mechanism that influence physical activity along with perceived motor and physical competence, but the relationship between motor skills and physical activity during the early years is unclear. The goal of this study, Promoting Activity and Trajectories of Health (PATH) for Children, is to examine and compare the immediate (pre-test to post-test) and sustained (3-year follow-up) effect of an intervention on motor performance, physical activity and perceived physical competence to a control condition (ie, standard practice) in preschool-age children.Methods and analysisThe PATH study is a two-cohort, randomised cluster clinical trial. 300 children between the ages of>3.5 to 5 years of age will be randomised to the motor skill intervention (n=153) or control (n=147) condition. Each assessment involves a measure of motor skill performance; product and process, seven consecutive days of physical activity monitoring and perceived physical competence. These measures will be assessed before and after the intervention (pre-test to post-test) and then each academic year across 3 years, grades kindergarten, first grade and second grade (3-year follow-up). To assess the clustered longitudinal effect of the intervention on outcome measures, random-effects models (eg, mixed model regression, growth curve modelling and structural equation modelling) will be used. The PATH study addresses gaps in paediatric exercise science research. Findings hold the potential to help shape public health and educational policies and interventions that support healthy development and active living during the early years.Ethics and disseminationEthical approval for this study was obtained through the Health Sciences and Behavioral Sciences Institutional Review Board, University of Michigan (HUM00133319). The PATH study is funded by the National Institutes of Health. Findings will be disseminated via print, online media, dissemination events and practitioner and/or research journals.Trial registration numberNHLBI ClinicalTrials.gov Identifier,NCT03189862. Registered 17 August 2017,https://clinicaltrials.gov/ct2/show/NCT03189862

Introduction: Neighborhood economic conditions are important predictors of incident stroke. Neighborhood economic conditions can be characterized differently but studies have not identified which characterizations are most predictive of incident stroke. Previous work has suggested that the income distribution within the population may be more relevant for chronic disease than the absolute value of median income of the population. This project aims to estimate the effects of neighborhood income and neighborhood income inequality on incidence stroke. Hypothesis: Neighborhood income inequality and absolute neighborhood income will predict incident stroke above and beyond demographic characteristics and individual socioeconomic status. Methods: We used data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, a national longitudinal study of black and white older adults (N=29,443). Baseline median household income and the Gini coefficient of income inequality at the Census Tract level were obtained from the 2000 decennial census. Both variables were standardized to have a mean of 0 and a standard deviation of 1; z-score of median household income was multiplied by -1 (representing neighborhood income deprivation) to allow for comparability. Using Cox Proportional Hazards analysis we examined the risk of stroke associated with these exposures in separate models. Model 1 was unadjusted, Model 2 was adjusted for demographic characteristics (age, race, sex, marital status), and Model 3 was adjusted for individual socioeconomic characteristics (household income and education). Results: Within Model 1, neighborhood income deprivation (HR: 1.18; 95% CI 1.11-1.24) and neighborhood income inequality (HR: 1.10; 95% CI: 1.05-1.16) were both significantly associated with risk of stroke. The association persisted in Model 2: neighborhood income deprivation (HR: 1.13; 95% CI 1.07-1.20) and neighborhood income inequality (HR: 1.06; 95% CI: 1.00-1.11). Within Model 3, neighborhood income deprivation maintained its positive association (HR: 1.06; 95% CI 1.00-1.13), while neighborhood income inequality was no longer predictive of stroke risk (HR:1.04; 95% CI 0.99-1.10). Conclusions: Neighborhood income deprivation and neighborhood income inequality were similar predictors of incident stroke. The effect of absolute economic resources in a Census Tract was slightly larger than the relative economic standards within a Census Tract. There is a need to investigate other characterizations of neighborhood economic conditions, such as residential income segregation. The findings from this project suggest that there are multiple policy levels that can be used to decrease incident stroke, through decreasing income inequality and improving the absolute economic conditions of deprived neighborhoods.

Introduction: Prior studies have investigated the relationship between neighborhood income and incident hypertension but have lacked participant-level details or studied specific subpopulations. We assessed the relationship between neighborhood income and incident hypertension accounting for individual level factors in the racially and geographically diverse REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Hypothesis: Low neighborhood income is associated with increased hypertension incidence. Methods: REGARDS recruited 30,239 white and black adults aged ≥45y from the contiguous US in 2003-7 with follow-up between 2013-6. We excluded individuals with baseline hypertension (≥130/80 mm Hg or using antihypertension medications, n=22,325), missing follow-up (n=3,365) and not residing at the same address for ≥5 years (n=1,075). Neighborhood income was measured within 1 and 5 km buffers around the participant’s home using a spatial overlay of census tract-level median household income, and then classified into tertiles. We used Poisson regression to calculate risk ratio for incident hypertension adjusting for demographic, socioeconomic, and health habit factors. Results: Among the 3,474 individuals (58% women, 24% black, mean age 62y), 1,499 individuals (43%) developed hypertension. After adjusting for individual-level risk factors, the incident rate ratio of hypertension for individuals living in low-income neighborhoods was 1.16 (95% CI 1.04, 1.31) and middle-income was 1.12 (95% CI 1.01, 1.25) as compared to high income, when neighborhood was defined as a 1 km buffer. The result was similar but not significant in middle-income for the 5 km buffer neighborhoods (Table 1). There were no significant interactions with age, gender, or race (p-interaction > 0.1). Conclusions: In REGARDS, neighborhood income was associated with incident hypertension. Understanding the specific social and environmental inequities associated with hypertension will require further study.

Numerous studies have focused on the role of neighborhood socioeconomic status in childhood obesity and physical activity, but few studies have examined the effect of neighborhood socioeconomic changes over time and the interaction between family and neighborhood SES on childhood obesity and physical activity. This study measured neighborhood socioeconomic histories between 2000 and 2010 and examined the associations between neighborhood socioeconomic histories and childhood obesity, as well as physical activity. The moderating role of family poverty status was also examined. Using the Healthy Communities Study (2013–2015), we measured obesity indicators (objectively measured body mass index z-score and waist circumference) and a physical activity indicator (self-reported moderate-to-vigorous physical activity) for a cohort of 4114 children. Multilevel linear regression models were used to examine the associations between neighborhood socioeconomic histories between 2000 and 2009–2013 and body-mass index z-score, waist circumference, and moderate-to-vigorous physical activity. Results showed that higher-income children in consistently high socioeconomic neighborhoods had lower measured BMIz and WC and engaged in more moderate-to-vigorous physical activity than higher-income children in consistently low socioeconomic neighborhoods. Additionally, low-income children in consistently moderate socioeconomic neighborhoods reported a lower level of moderate-to-vigorous physical activity than low-income children in consistently low socioeconomic neighborhoods. The findings indicate that considering both family and neighborhood socioeconomic status may help elucidate the underlying differences in childhood obesity and physical activity levels by socioeconomic status. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11524-020-00427-9) contains supplementary material, which is available to authorized users.

Background: Improving the neighborhood environment may help address chronic disease and mortality. To identify neighborhood features that are predictors of health, objective assessments of the environment are used. Multiple studies have reported on cross-sectional assessments of health-related neighborhood features using direct observation. As study designs expand to better understand causation and predictors of change, there is a need to test whether direct observation methods are adequate for longitudinal assessment. To our knowledge, this is the first study to report on repeated direct observations of the neighborhood environment. Methods : The Pittsburgh Hill/Homewood Research on Neighborhood Change and Health (PHRESH) study conducted longitudinal assessments in two low-income, African American neighborhoods at three waves (years 2012, 2015, 2017). The PHRESH audit tool is a modification of earlier validated tools, with an emphasis on environment features relevant for physical activity, sleep, and obesogenic behaviors. Trained data-collector pairs conducted direct observations of a 25% sample of street segments in each neighborhood. At each wave, we audited a sub-sample of street segments twice and assessed reliability using percentage inter-observer agreement and krippendorf’s alpha statistics. Stability of these items was assessed as exhibiting moderate or high agreement at every time point. Results : Across waves, a majority (81%) of the items consistently demonstrated moderate to high agreement except for items such as public/communal space, amount of shade, sidewalk features, number of traffic lanes, garden/flower bed/planter, art/statue/monument, amount of trash, and physical disorder. The list of items with poor agreement includes features that are easy to miss (e.g. flower bed/planter), hard to assess from outside (e.g. public/communal space), or may change quickly (e.g. amount of trash). Conclusion: In this paper, we have described implementation methods, reliability results and lessons learned to inform future studies of change. We found the use of consistent methods allowed us to conduct reliable, replicable longitudinal assessments of the environment. Items that did not exhibit stability are less useful for detecting real change over time. Overall, the SSA direct observation tool is an effective and practical instrument to detect change in the neighborhood environment.