Objective: “Nature prescriptions” are increasingly being adopted by health sectors as an adjunct to standard care to attend to health and social needs. We investigated levels of need and interest in nature prescriptions in adults with cardiovascular diseases, psychological distress and concomitants (e.g. physical inactivity, sedentary behaviour, obesity, loneliness, burn-out). Methods: A nationally-representative survey of 3,319 adults across all states and territories of Australia was completed in February 2021 (response 84.0%). Participants were classified across 15 target groups using validated health indicators and surveyed on (1) time and frequency of visits to green and blue spaces (nature spaces), (2) interest in a nature prescription, and (3) potential confounders (e.g. age, income). Analyses were done using weighted logistic regressions. Results: The sample was 50.5% female, 52.0% were aged ≥45 years, 15.2% were living alone and 19.3% were born overseas in non-English-speaking countries. Two-thirds of the sample spent 2 hours or more a week in nature, but these levels were generally lower in target groups (e.g. 57.7% in adults with type 2 diabetes). Most participants (81.9%) were interested in a nature prescription, even among those spending fewer than 2 hours a week in nature (76.4%). For example, 2 hours a week or more in nature was lowest among sedentary adults (36.9%) yet interest in nature prescriptions in this group was still high (74.0%). Lower levels of nature contact in target groups was not explained by differences in access to or preference for local nature spaces. Conclusions: High levels of interest in nature prescriptions amid low levels of nature contact in many target health groups provides impetus for developing randomised trials of interventions that enable people to spend more time in nature. These findings can inform intervention co-design processes with a wide range of community stakeholders, end-users in target health groups, and the health professionals who support them.@en

Overweight and obesity are steadily rising in South Asia, the world’s most populous region. India, a low- and middle-income country in South Asia is experiencing an obesity epidemic. Built environment features may profoundly influence physical activity and counter the risk from overweight and obesity. This cross-sectional study investigated built environment correlates of overweight and obesity among adults (N = 370, 47.2% female, mean age = 37.9 years) in Chennai, India. Participants from low-socioeconomic status households were more likely to be overweight/obese (odds ratio [OR] = 1.8, 95% confidence interval [CI] = 1.1–2.9) than participants from high-socioeconomic status households. Driving to work predicted a three-fold increase in overweight or obesity compared to active commuting (OR = 2.9, 95%CI = 1.3–6.4). Household car ownership was linked with an increased likelihood of overweight or obesity (OR = 1.5, 95%CI = 0.7–3.2). Low walkability neighbourhoods significantly predicted an increase in odds of overweight or obesity (OR = 1.8, 95%CI = 1.1–2.8). By 2030, Indian cities are projected to add 250 million people accompanied by a 9.9% annual motor vehicle growth rate. As car ownership increases across Southern Asia, there is an urgent need to develop interventions to promote physical activity.@en

Introduction: Abundant evidence shows that regular physical activity (PA) is an effective strategy for preventing obesity in people of diverse socioeconomic status (SES) and racial groups. The proportion of PA performed in parks and how this differs by proximate neighborhood SES has not been thoroughly investigated. The present project analyzes online public web data feeds to assess differences in outdoor PA by neighborhood SES in St. Louis, MO, USA. Methods: First, running and walking routes submitted by users of the website MapMyRun.com were downloaded. The website enables participants to plan, map, record, and share their exercise routes and outdoor activities like runs, walks, and hikes in an online database. Next, the routes were visually illustrated using geographic information systems. Thereafter, using park data and 2010 Missouri census poverty data, the odds of running and walking routes traversing a low-SES neighborhood, and traversing a park in a low-SES neighborhood were examined in comparison to the odds of routes traversing higher-SES neighborhoods and higher-SES parks. Results: Results show that a majority of running and walking routes occur in or at least traverse through a park. However, this finding does not hold when comparing low-SES neighborhoods to higher-SES neighborhoods in St. Louis. The odds of running in a park in a low-SES neighborhood were 54% lower than running in a park in a higher-SES neighborhood (OR = 0.46, CI = 0.17–1.23). The odds of walking in a park in a low-SES neighborhood were 17% lower than walking in a park in a higher-SES neighborhood (OR = 0.83, CI = 0.26–2.61). Conclusion: The novel methods of this study include the use of inexpensive, unobtrusive, and publicly available web data feeds to examine PA in parks and differences by neighborhood SES. Emerging technologies like MapMyRun.com present significant advantages to enhance tracking of user-defined PA across large geographic and temporal settings.@en

Introduction Data on built environment (BE) and physical activity (PA) in low- and middle- income countries is sparse. This study compared BE features, PA levels, and weight status among adults living in neighborhoods stratified by walkability and socio-economic status (SES) in the city of Chennai, India. Methods This cross sectional study design surveyed 370 adults (≥18 years) from four neighborhoods with differing walkability and socio-economic status. Participants were asked to complete a survey on their neighborhood environment, leisure and travel PA, height, weight, and demographic characteristics. One-way analysis of variance tests were used to examine differences across neighborhoods. Results Residents of high-walkability/high-SES neighborhoods reported higher land use mix diversity, land use mix access, street connectivity, aesthetics, and safety from crime. Residential density and walking/bicycling infrastructure were highest in the high-walkability/low-SES neighborhood. Transport PA was the maximum contributor to total PA in low-SES neighborhoods, while residents of high-SES neighborhoods reported greater levels of leisure-time PA. Sitting time and BMI were greater among high-SES participants. Patterns of PA, sedentary time, and weight status varied significantly by neighborhood walkability and SES. Conclusions An understanding of BE correlates of domain-specific PA can support the development of contextually tailored interventions to promote physical activity and reverse the determinants of inactivity occurring through patterns of urbanization and sedentary behaviors in India.@en

Background: Pokémon GO is the most played augmented reality game in history. With more than 44 million players at the peak of its popularity, the game has sparked interest on its effects on the young population’s health. Objective: This pilot study examined motivations to start playing Pokémon GO among a sample of US college students, and how motivations were associated with perceived outcomes of the playing experience and physical activity derived while playing. Methods: In November 2016, we asked a sample of 47 US college students (all Pokémon GO players) to complete online surveys and install an ecological momentary assessment (EMA) tool and step counter on their smartphones. The EMA tool prompted a set of questions on playing behavior and physical activity, 3 times per day (12:00 PM, 7:00 PM, and 10:00 PM), for 7 days. We used a factorial analysis to identify 3 distinctive groups of players based on their motivations to start playing Pokémon GO. We tested differences across motivation groups related to 5 unique outcomes using 1-way analysis of variance. Results: We extracted 3 interpretable factors from the clustering of motivations to start playing Pokémon GO: Pokémon and video game fans (n=26, 55% of the sample), physical activity seekers (n=8, 17%), and curious & social (n=13, 28%). The clusters differed significantly on the enjoyment of different aspects of the game, particularly battling, discovering new places, and meeting new people, as well as differences in agreement that playing improved mood and made them more social. Days when playing Pokémon GO were associated with higher number of steps reported at the end of the day, especially among physical activity seekers, but also for Pokémon and video game fans. All groups perceived traffic as a major threat to playing. Conclusions: Days during which Pokémon GO was played were positively associated with a set of beneficial health behaviors, including higher physical activity levels, more socialization, and better mood. Results, however, depended on personal motivations and expectations when joining the game. These results highlight the importance of taking motivation into account when attempting to extract conclusions from the Pokémon GO phenomenon to enhance future exergames’ designs or health interventions.@en

Few studies assess built environment correlates of active commuting in low-and-middle-income countries (LMICs), but the different context could yield distinct findings. Policies and investments to promote active commuting remain under-developed in LMICs like India, which grapples with traffic congestion, lack of activity-supportive infrastructure, poor enforcement of traffic rules and regulations, air pollution, and overcrowding. This cross-sectional study investigated associations between home neighborhood environment characteristics and active commuting in Chennai, India. Adults (N = 370, 47.2% female, mean age = 37.9 years) were recruited from 155 wards in the metropolitan area of Chennai in southern India between January and June 2015. Participants self-reported their usual mode of commute to work, with responses recoded into three categories: (1) multi-modal or active commuting (walking and bicycling; n = 56); (2) public transit (n = 52); and (3) private transport (n = 111). Environmental attributes around participants’ homes were assessed using the Neighborhood Environment Walkability Scale for India (NEWS-India). Associations between environmental characteristics and likelihood of active commuting and public transit use were modeled using logistic regression with private transport (driving alone or carpool) as the reference category, adjusting for age, gender, and household car ownership. Consistent with other international studies, participants living in neighborhoods with a mix of land uses and a transit stop within a 10-minute walk from home were more likely to use active commuting (both p < 0.01). Land-use mix was significantly associated with the use of public transit compared to private transport (adjusted odds ratio (aOR) = 5.2, p = 0.002). Contrary to findings in high-income countries, the odds of active commuting were reduced with improved safety from crime (aOR = 0.2, p = 0.003), aesthetics (aOR = 0.2, p = 0.05), and street connectivity (aOR = 0.2, p = 0.003). Different environmental attributes were associated with active commuting, suggesting that these relationships are complex and may distinctly differ from those in high-income countries. Unexpected inverse associations of perceived safety from crime and aesthetics with active commuting emphasize the need for high-quality epidemiologic studies with greater context specificity in the study of physical activity in LMICs. Findings have public health implications for India and suggest that caution should be taken when translating evidence across countries.@en

Dietary behaviors are associated with obesity, and may be influenced by the environment. The objective of the current work was to investigate whether perceptions of built environment factors related to eating in the residential neighborhood will have different, independent associations with BMI and dietary behaviors than perceived built environment factors in the worksite neighborhood. In 2012–2013, a cross-sectional telephone-survey of Missouri adults (n = 2015) assessed perceptions of home and workplace built environment factors related to eating, dietary behaviors, and height and weight. Logistic regression models explored associations between perceived neighborhood built environment variables, diet, and obesity. The only variable associated with any of the outcomes explored in the fully adjusted models was the home neighborhood composite scale. None of the work environment variables were significantly associated with any of the health/behavior outcomes after adjustment. Few associations were found after adjustment for personal and job-related characteristics, and none were identified with the workplace neighborhood environment. While few home environment associations were found after adjustment, and none were identified with the perceived workplace neighborhood environment, the current study adds to the limited literature looking at associations between the perceived neighborhood around the workplace neighborhood and the perceived neighborhood around the home and dietary behaviors and obesity in adults. Future studies are needed to determine whether relationships between these environments and behavior exist, and if so, if they are causal and warrant intervention attempts. @en

Evidence correlates physical activity, psychological restoration, and social health to proximity to parks and sites of recreation. The purpose of this study was to identify perceived constraints to park use in low-income communities facing significant health disparities, but with proximate access to underutilized parks. The authors used a series of focus groups with families, teens, and older adults in neighborhoods with similar demographic distribution and parks over 125 acres in size. Constraints to park use varied across age groups as well as across social ecological levels, with perceived constraints to individuals, user groups, communities, and society. Policies and interventions aimed at increasing park use must specifically address constraints across social ecological levels to be successful.@en

Background Promoting the use of public transit and active transport (walking and cycling) instead of car driving is an appealing strategy to increase overall physical activity. Purpose To quantify the combined associations between self-reported home and worksite neighborhood environments, worksite support and policies, and employees’ commuting modes. Method Between 2012 and 2013, participants residing in four Missouri metropolitan areas were interviewed via telephone (n=1338) and provided information on socio-demographic characteristics, home and worksite neighborhoods, and worksite support and policies. Commuting mode was self-reported and categorized into car driving, public transit, and active commuting. Commuting distance was calculated using geographic information systems. Commuters providing completed data were included in the analysis. Multivariate logistic regression models were used to examine the correlates of using public transit and active commuting. Result The majority of participants reported commuting by driving (88.9%); only 4.9% used public transit and 6.2% used active modes. After multivariate adjustment, having transit stops within 10–15 min walking distance from home (p=0.05) and using worksite incentive for public transit (p<0.001) were associated with commuting by public transit. Commuting distance (p<0.001) was negatively associated with active commuting. Having free or low cost recreation facilities around the worksite (p=0.04) and using bike facilities to lock bikes at the worksite (p<0.001) were associated with active commuting. Conclusion Both environment features and worksite supports and policies are associated with the choice of commuting mode. Future studies should use longitudinal designs to investigate the potential of promoting alternative commuting modes through worksite efforts that support sustainable commuting behaviors as well as the potential of built environment improvements. @en

Pokemon GO and its ability to get people moving highlights new beginnings for gamification of health and social life of urban spaces with implications for people–space interaction.@en

Physical inactivity is the fourth leading risk factor for global mortality, with most of these deaths occurring in low and middle-income countries (LMICs) like India. Research from developed countries has consistently demonstrated associations between built environment features and physical activity levels of populations. The development of culturally sensitive and reliable measures of the built environment is a necessary first step for accurate analysis of environmental correlates of physical activity in LMICs. This study systematically adapted the Neighborhood Environment Walkability Scale (NEWS) for India and evaluated aspects of test-retest reliability of the adapted version among Indian adults. Cultural adaptation of the NEWS was conducted by Indian and international experts. Semi-structured interviews were conducted with local residents and key informants in the city of Chennai, India. At baseline, participants (N = 370; female = 47.2%) from Chennai completed the adapted NEWS-India surveys on perceived residential density, land use mix-diversity, land use mix-access, street connectivity, infrastructure and safety for walking and cycling, aesthetics, traffic safety, and safety from crime. NEWS-India was administered for a second time to consenting participants (N = 62; female = 53.2%) with a gap of 2–3 weeks between successive administrations. Qualitative findings demonstrated that built environment barriers and constraints to active commuting and physical activity behaviors intersected with social ecological systems. The adapted NEWS subscales had moderate to high test-retest reliability (ICC range 0.48–0.99). The NEWS-India demonstrated acceptable measurement properties among Indian adults and may be a useful tool for evaluation of built environment attributes in India. Further adaptation and evaluation in rural and suburban settings in India is essential to create a version that could be used throughout India.@en

The Archive of Many Outdoor Scenes has captured 400 million images. Many of these cameras and images are of street intersections, a subset of which has experienced built environment improvements during the past seven years. We identified six cameras in Washington, DC, and uploaded 120 images from each before a built environment change (2007) and after (2010) to the crowdsourcing website Amazon Mechanical Turk (n=1,440). Five unique MTurk workers annotated each image, counting the number of pedestrians, cyclists, and vehicles. Two trained Research Assistants completed the same tasks. Reliability and validity statistics of MTurk workers revealed substantial agreement in annotating captured images of pedestrians and vehicles. Using the mean annotation of four MTurk workers proved most parsimonious for valid results. Crowdsourcing was shown to be a reliable and valid workforce for annotating images of outdoor human behavior.@en

Introduction: Fewer than 50% of adults and 40% of youth meet US CDC guidelines for physical activity (PA) with the built environment (BE) a culprit for limited PA. A challenge in evaluating policy and BE change is the forethought to capture a priori PA behaviors and the ability to eliminate bias in post-change environments. The present objective was to analyze existing public data feeds to quantify effectiveness of BE interventions. The Archive of Many Outdoor Scenes (AMOS) has collected 135 million images of outdoor environments from 12,000 webcams since 2006. Many of these environments have experienced BE change. Methods: One example of BE change is the addition of protected bike lanes and a bike share program in Washington, DC. We selected an AMOS webcam that captured this change. AMOS captures a photograph from each webcam every half hour. AMOS captured the 120 webcam photographs between 0700 and 1900 during the first work week of June 2009 and the 120 photographs from the same week in 2010. We used the Amazon Mechanical Turk (MTurk) website to crowd-source the image annotation. MTurk workers were paid US$0.01 to mark each pedestrian, cyclist and vehicle in a photograph. Each image was coded 5 unique times (n=1200). The data, counts of transportation mode, was downloaded to SPSS for analysis. Results: The number of cyclists per scene increased four-fold between 2009 and 2010 (F=36.72, p=0.002). There was no significant increase in pedestrians between the two years, however there was a significant increase in number of vehicles per scene (F=16.81, p<0.001). Discussion: This novel research presents unobtrusive surveillance of PA policy and BE intervention effectiveness. Washington, DC, added bike lanes during 2009 and the use of webcam data allowed for a pre- and post-bike lane analysis of travel. The addition of the bike lane is associated with a significant four-fold increase in number of cyclist per scene. The number of vehicles per scene also increased. A portion of this increase may be associated with compressed lanes due to lane removal for the bike lane, thus increasing vehicles per remaining lane. Captured public webcam scenes and MTurks offer an inexpensive (US$12.00), discreet means to evaluate effectiveness of BE policy change and interventions. This abstract presents an initial effort. We continue to test methodology with additional scenes, including parks, school playgrounds, and safe routes to schools, and are working to automate the MTurk process. @en

Background Physical inactivity has been associated with obesity and related chronic diseases. Understanding built environment (BE) influences on specific domains of physical activity (PA) around homes and workplaces is important for public health interventions to increase population PA. Purpose To examine the association of home and workplace BE features with PA occurring across specific life domains (work, leisure, and travel). Methods Between 2012 and 2013, telephone interviews were conducted with participants in four Missouri metropolitan areas. Questions included sociodemographic characteristics, home and workplace supports for PA, and dietary behaviors. Data analysis was conducted in 2013; logistic regression was used to examine associations between BE features and domain-specific PA. Results In home neighborhoods, seven of 12 BE features (availability of fruits and vegetables, presence of shops and stores, bike facilities, recreation facilities, crime rate, seeing others active, and interesting things) were associated with leisure PA. The global average score of home neighborhood BE features was associated with greater odds of travel PA (AOR=1.99, 95% CI=1.46, 2.72); leisure PA (AOR=1.84, 95% CI=1.44, 2.34); and total PA (AOR=1.41, 95% CI=1.04, 1.92). Associations between workplace neighborhoods’ BE features and workplace PA were small but in the expected direction. Conclusions This study offers empirical evidence on BE supports for domain-specific PA. Findings suggest that diverse, attractive, and walkable neighborhoods around workplaces support walking, bicycling, and use of public transit. Public health practitioners, researchers, and worksite leaders could benefit by utilizing worksite domains and measures from this study for future BE assessments.@en

Evidence correlates physical activity, psychological restoration, and social health to proximity to parks and sites of recreation. The purpose of this study was to identify perceived constraints to park use in low-income communities facing significant health disparities, with access to underutilized parks. We used a series of focus groups with families, teens, and older adults in neighborhoods with similar demographic distribution and access to parks over 125 acres in size. Constraints to park use varied across age groups as well as across social ecological levels, with perceived constraints to individuals, user groups, communities, and society. Policies and interventions aimed at increasing park use must specifically address barriers across social ecological levels to be successful.@en

India is currently facing a non-communicable disease epidemic. Physical activity (PA) is a preventative factor for non-communicable diseases. Understanding the role of the built environment (BE) to facilitate or constrain PA is essential for public health interventions to increase population PA. The objective of this study was to understand BEs associations with PA occurring in two major life domains or life areas—travel and leisure—in urban India. Between December 2014 and April 2015, in-person surveys were conducted with participants (N = 370; female = 47.2%) in Chennai, India. Perceived BE characteristics regarding residential density, land use mix-diversity, land use mix-access, street connectivity, infrastructure for walking and bicycling, aesthetics, traffic safety, and safety from crime were measured using the adapted Neighborhood Environment Walkability Scale-India (NEWS-India). Self-reported PA was measured the International Physical Activity Questionnaire. High residential density was associated with greater odds of travel PA (aOR = 1.9, 95% CI = 1.2, 3.2). Land use mix-diversity was positively related to travel PA (aOR = 2.1, 95%CI = 1.2, 3.6), but not associated with leisure or total PA. The aggregate NEWS-India score predicted a two-fold increase in odds of travel PA (aOR = 1.9, 95% CI = 1.1, 3.1) and a 40% decrease in odds of leisure PA (aOR = 0.6, 95% CI = 0.4, 1.0). However, the association of the aggregated score with leisure PA was not significant. Results suggest that relationships between BE and PA in low-and-middle income countries may be context-specific, and may differ markedly from higher income countries. Findings have public health implications for India suggesting that caution should be taken when translating evidence across countries. @en