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Built and natural environments may provide opportunities for physical activity. However, studies are limited by primarily using residential addresses to define exposure and ...self-report to measure physical activity. We quantified associations between global positioning systems (GPS)-based activity space measures of environmental exposure and accelerometer-based physical activity.
Using a nationwide sample of working female adults (N = 354), we obtained seven days of GPS and accelerometry data. We created Daily Path Area activity spaces using GPS data and linked these activity spaces to spatial datasets on walkability (EPA Smart Location Database at the Census block group level) and greenness (satellite vegetation at 250 m resolution). We utilized generalized additive models to examine nonlinear associations between activity space exposures and accelerometer-derived physical activity outcomes adjusted for demographic characteristics, socioeconomic factors, and self-rated health.
Higher activity space walkability was associated with higher levels of moderate-vigorous physical activity, and higher activity space greenness was associated with greater numbers of steps per week. No strong relationships were observed for sedentary behavior or light physical activity. Highest levels of moderate-vigorous physical activity were observed for participants with both high walkability and high greenness in their activity spaces.
This study contributes evidence that higher levels of physical activity occur in environments with more dense, diverse, and well-connected built environments, and with higher amounts of vegetation. These data suggest that urban planners, landscape architects, and policy makers should implement and evaluate environmental interventions to encourage higher levels of physical activity.
University students are exposed to many stressors, necessitating opportunities for restoration. Research has indicated that actual experiences in nearby green spaces are associated with restorative ...psychological and physiological health benefits. However, the perception of greenness and restorativeness of environments might also impact health outcomes. Can green campus spaces provide restorative potential to university students? Do students perceive the greenness and restorative benefits? To explore these questions, students at three universities (convenience sample) were surveyed with items on perceived greenness of campus, perceived restorativeness of campus, and the World Health Organization Quality-of-Life Scale. Results indicate that those with higher perceived campus greenness report greater quality of life, a pathway significantly and partially mediated by perceived campus restorativeness. Future research should help identify effective ways in which university green spaces can be developed as health resources for students.
Evidence is mounting on the association between the built environment and physical activity (PA) with a call for intervention research. A broader approach which recognizes the role of supportive ...environments that can make healthy choices easier is required. A systematic review was undertaken to assess the effectiveness of interventions to encourage PA in urban green space. Five databases were searched independently by two reviewers using search terms relating to 'physical activity', 'urban green space' and 'intervention' in July 2014. Eligibility criteria included: (i) intervention to encourage PA in urban green space which involved either a physical change to the urban green space or a PA intervention to promote use of urban green space or a combination of both; and (ii) primary outcome of PA. Of the 2405 studies identified, 12 were included. There was some evidence (4/9 studies showed positive effect) to support built environment only interventions for encouraging use and increasing PA in urban green space. There was more promising evidence (3/3 studies showed positive effect) to support PAprograms or PA programs combined with a physical change to the built environment, for increasing urban green space use and PA of users. Recommendations for future research include the need for longer term follow-up post-intervention, adequate control groups, sufficiently powered studies, and consideration of the social environment, which was identified as a significantly under-utilized resource in this area. Interventions that involve the use of PA programs combined with a physical change to the built environment are likely to have a positive effect on PA. Robust evaluations of such interventions are urgently required. The findings provide a platform to inform the design, implementation and evaluation of future urban green space and PAintervention research.
•Short text topic modeling identifies Twitter opinions related to urban parks.•Urban parks continue to be valued for physical activity during the pandemic.•A decrease in conversations about general ...activities in urban parks during the pandemic.•Concerns about social distancing in urban parks have been a trending topic on Twitter.•The potential for monitoring attitudes and values about parks through Twitter data.
Since school and business closures due to the evolving COVID-19 outbreak, urban parks have been a popular destination, offering spaces for daily fitness activities and an escape from the home environment. There is a need for evidence for parks and recreation departments and agencies to base decisions when adapting policies in response to the rapid change in demand and preferences during the pandemic. The application of social media data analytic techniques permits a qualitative and quantitative big-data approach to gain unobtrusive and prompt insights on how parks are valued. This study investigates how public values associated with NYC parks has shifted between pre- COVID (i.e., from March 2019 to February 2020) and post- COVID (i.e., from March 2020 to February 2021) through a social media microblogging platform –Twitter. A topic modeling technique for short text identified common traits of the changes in Twitter topics regarding impressions and values associated with the parks over two years. While the NYC lockdown resulted in much fewer social activities in parks, some parks continued to be valued for physical activity and nature contact during the pandemic. Concerns about people not keeping physical distance arose in parks where frequent human interactions and crowding seemed to cause a higher probability of the coronavirus transmission. This study demonstrates social media data could be used to capture park values and be specific per park. Results could inform park management during disruptions when use is altered and the needs of the public may be changing.
Physical inactivity is a risk factor for cancer that may be influenced by environmental factors. Indeed, dense and well-connected built environments and environments with natural vegetation may ...create opportunities for higher routine physical activity. However, studies have focused primarily on residential environments to define exposure and self-reported methods to estimate physical activity. This study explores the momentary association between minute-level global positioning systems (GPS)-based greenness exposure and time-matched objectively measured physical activity.
Adult women were recruited from sites across the United States. Participants wore a GPS device and accelerometer on the hip for 7 days to assess location and physical activity at minute-level epochs. GPS records were linked to 250 m resolution satellite-based vegetation data and Census Block Group-level U.S. Environmental Protection Agency (EPA) Smart Location Database walkability data. Minute-level generalized additive mixed models were conducted to test for associations between GPS measures and accelerometer count data, accounting for repeated measures within participant and allowing for deviations from linearity using splines.
Among 360 adult women (mean age of 55.3 ± 10.2 years), we observed positive nonlinear relationships between physical activity and both greenness and walkability. In exploratory analyses, the relationships between environmental factors and physical activity were strongest among those who were white, had higher incomes, and who were middle-aged.
Our results indicate that higher levels of physical activity occurred in areas with higher greenness and higher walkability.
Findings suggest that planning and design policies should focus on these environments to optimize opportunities for physical activity.
Uncertainty in the relevant spatial context may drive heterogeneity in findings on the built environment and energy balance. To estimate the effect of this uncertainty, we conducted a sensitivity ...analysis defining intersection and business densities and counts within different buffer sizes and shapes on associations with self-reported walking and body mass index. Linear regression results indicated that the scale and shape of buffers influenced study results and may partly explain the inconsistent findings in the built environment and energy balance literature.
•Findings in research on the built environment and energy balance are inconsistent.•Uncertainty on the context relevant to energy balance drives this inconsistency.•We constructed built environment measures of varying buffer sizes and shapes.•We modeled the effect of these measures on self-reported walking and BMI.•Effect sizes and statistical significance varied by buffer size and shape.
Physical activity and time spent outdoors may be important non-pharmacological approaches to improve sleep quality and duration (or sleep patterns) but there is little empirical research evaluating ...the two simultaneously. The current study assesses the role of physical activity and time outdoors in predicting sleep health by using objective measurement of the three variables. A convenience sample of 360 adult women (mean age = 55.38 ±9.89 years; mean body mass index = 27.74 ±6.12) was recruited from different regions of the U.S. Participants wore a Global Positioning System device and ActiGraph GT3X+ accelerometers on the hip for 7 days and on the wrist for 7 days and 7 nights to assess total time and time of day spent outdoors, total minutes in moderate-to-vigorous physical activity per day, and 4 measures of sleep health, respectively. A generalized mixed-effects model was used to assess temporal associations between moderate-to-vigorous physical activity, outdoor time, and sleep at the daily level (days = 1931) within individuals. There was a significant interaction (p = 0.04) between moderate-to-vigorous physical activity and time spent outdoors in predicting total sleep time but not for predicting sleep efficiency. Increasing time outdoors in the afternoon (versus morning) predicted lower sleep efficiency, but had no effect on total sleep time. Time spent outdoors and the time of day spent outdoors may be important moderators in assessing the relation between physical activity and sleep. More research is needed in larger populations using experimental designs.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Information on the relationship between diabetes prevalence and built environment attributes could allow public health programs to better target populations at risk for diabetes. This study sought to ...determine the spatial prevalence of diabetes in the United States and how this distribution is associated with the geography of common diabetes correlates.
Data from the Centers for Disease Control and Prevention and the US Census Bureau were integrated to perform geographically weighted regression at the county level on the following variables: percentage nonwhite population, percentage Hispanic population, education level, percentage unemployed, percentage living below the federal poverty level, population density, percentage obese, percentage physically inactive, percentage population that cycles or walks to work, and percentage neighborhood food deserts.
We found significant spatial clustering of county-level diabetes prevalence in the United States; however, diabetes prevalence was inconsistently correlated with significant predictors. Percentage living below the federal poverty level and percentage nonwhite population were associated with diabetes in some regions. The percentage of population cycling or walking to work was the only significant built environment-related variable correlated with diabetes, and this association varied in magnitude across the nation.
Sociodemographic and built environment-related variables correlated with diabetes prevalence in some regions of the United States. The variation in magnitude and direction of these relationships highlights the need to understand local context in the prevention and maintenance of diabetes. Geographically weighted regression shows promise for public health research in detecting variations in associations between health behaviors, outcomes, and predictors across geographic space.
This study compared marginal and conditional modeling approaches for identifying individual, park and neighborhood park use predictors. Data were derived from the ParkIndex study, which occurred in ...128 block groups in Brooklyn (New York), Seattle (Washington), Raleigh (North Carolina), and Greenville (South Carolina). Survey respondents (n = 320) indicated parks within one half-mile of their block group used within the past month. Parks (n = 263) were audited using the Community Park Audit Tool. Measures were collected at the individual (park visitation, physical activity, sociodemographic characteristics), park (distance, quality, size), and block group (park count, population density, age structure, racial composition, walkability) levels. Generalized linear mixed models and generalized estimating equations were used. Ten-fold cross validation compared predictive performance of models. Conditional and marginal models identified common park use predictors: participant race, participant education, distance to parks, park quality, and population >65yrs. Additionally, the conditional mode identified park size as a park use predictor. The conditional model exhibited superior predictive value compared to the marginal model, and they exhibited similar generalizability. Future research should consider conditional and marginal approaches for analyzing health behavior data and employ cross-validation techniques to identify instances where marginal models display superior or comparable performance.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The popularity of the augmented reality smartphone game, Pokémon GO, prompted multiple possibilities regarding its utilization as a mechanism to increase physical activity (PA) levels among young ...adults. A better comprehension of the gameplay characteristics may aid researchers and game developers in the implementation/design of interventions and games which provide the greatest chances at promoting health. A sample of 74 US college students were asked to complete a pre and post online survey and to install an Ecological Momentary Assessment (EMA) tool and a step counter on their smartphones. The EMA tool prompted a set of questions on playing behavior and PA three times per day (12pm, 7pm, 10pm) for seven days. Linear mixed effects regression models were used to address the relationship between gameplay characteristics (time of play, play context, playing environment, social play) and PA at each time of the day. Playing Pokémon GO was associated with higher PA when playing occurred during weekdays and during daytime and also among those who played while being active (i.e., walking). During weekends, this association was only found in the morning or late in the evening (after 7pm). Accumulating three or more active playing episodes per day was associated with an increase of 1526 daily steps. Pokémon GO has uneven effects on player's PA. However, under the right circumstances such as the time of day during which playing occurs, or where the playing takes place, Pokémon GO can become a useful tool for health promotion among young adults.
•The link between Pokémon GO and physical activity was tested using EMA and smartphone step counters.•Small associations were found between playing time and increased PA.•Associations were stronger on weekdays and before 7pm.•Playing 3 times a day while being active was associated with more steps at the end of the day.•Playing environment and conditions of play are also affecting physical activity.
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