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Background A lack of physical activity and overconsumption of energy dense food is associated with overweight and obesity. The neighbourhood environment may stimulate or hinder the development and/or maintenance of a healthy lifestyle. To improve research on the obesogenicity of neighbourhood environments, reliable, valid and convenient assessment methods of potential obesogenic characteristics of neighbourhood environments are needed. This study examines the reliability and validity of the SPOTLIGHT-Virtual Audit Tool (S-VAT), which uses remote sensing techniques (Street View feature in Google Earth) for desk-based assessment of environmental obesogenicity. Methods A total of 128 street segments in four Dutch urban neighbourhoods – heterogeneous in socio-economic status and residential density – were assessed using the S-VAT. Environmental characteristics were categorised as walking related items, cycling related items, public transport, aesthetics, land use-mix, grocery stores, food outlets and physical activity facilities. To assess concordance of inter- and intra-observer reliability of the Street View feature in Google Earth, and validity scores with real life audits, percentage agreement and Cohen's Kappa (k) were calculated. Results Intra-observer reliability was high and ranged from 91.7% agreement (k = 0.654) to 100% agreement (k = 1.000) with an overall agreement of 96.4% (k = 0.848). Inter-observer reliability results ranged from substantial agreement 78.6% (k = 0.440) to high agreement, 99.2% (k = 0.579), with an overall agreement of 91.5% (k = 0.595). Criterion validity was substantial to high for most of the categories ranging from 87.3% agreement (k = 0.539) to 99.9% agreement (k = 0.887) with an overall score of 95.6% agreement (k = 0.747). Conclusion These study results suggest that the S-VAT is a highly reliable and valid remote sensing tool to assess potential obesogenic environmental characteristics.

Active commuting to school increases children's daily physical activity. The built environment is associated with children's physical activity levels in cross-sectional studies. This study examined the role of the built environment on the outcomes of a \"walking school bus\" study. Geographical information systems was used to map out and compare the built environments around schools participating in a pilot walking school bus randomised controlled trial, as well as along school routes. Multi-level modelling was used to determine the built environment attributes associated with the outcomes of active commuting to school and accelerometer-determined moderate-to-vigorous physical activity (MPVA). There were no differences in the surrounding built environments of control (n = 4) and intervention (n = 4) schools participating in the walking school bus study. Among school walking routes, park space was inversely associated with active commuting to school (β = -0.008, SE = 0.004, P = 0.03), while mixed-land use was positively associated with daily MPVA (β = 60.0, SE = 24.3, P = 0.02). There was effect modification such that high traffic volume and high street connectivity were associated with greater moderate-to-vigorous physical activity. The results of this study suggest that the built environment may play a role in active school commuting outcomes and daily physical activity.

Background Urban green open space is a valuable resource for physical activities of urban inhabitants and has the potential to reduce chronic illness and improve health. Research on the relationships between green open space and physical activity is incomplete and limited in China. Thus, the study examines how the urban green open space contributes to physical activity. Methods A questionnaire was designed based on the social ecology theory to investigate the physical activity of 513 residents in urban green open space. We use the time and frequency of residents exercising in urban green space to measure physical activity, and use the factor analysis to synthesize a large number of original factors (i.e., infrastructure, safety, accessibility, landscape quality, and space environment) into relatively few composite indicators. Based on the collected data of the cross-sectional population, the Order Probit regression model was constructed to analyze how urban green open space affects the residents’ physical activity from the perspective of social ecology. Results ① in community factors: accessibility is significantly positive correlation with residents’ physical activity, and there is no significant correlation between safety and physical activity; ②in natural factors: space environment and landscape quality are not significantly correlated with residents’ physical activity; ③ in built environmental factors: infrastructures, the area of green space, the size of open space, and entertainment facilities are significantly correlated to residents’ activity. Basketball courts, volleyball courts, swimming pools, and sports equipment will promote physical activity; ④ apart from the attributes of green open space, other factors are significantly correlated to physical activity in the green open space, e.g. having a companion. Conclusions Urban green open space plays an important role in promoting physical activity especially among the women and the old, and improving the attributes (such as accessibility, infrastructures, the area of green space, the size of open space and entertainment facilities) of the urban green open space and trying to set up group sports proper to play with companion (like “square dancing” and “Tai Chi”) can promote Chinese residents’ physical activity so as to improve public health. The results are significant to facilitate environment health.

Background Following recruitment of a private sector company, an 8 week lunchtime walking intervention was implemented to examine the effect of the intervention on modifiable cardiovascular disease risk factors, and further to see if walking environment had any further effect on the cardiovascular disease risk factors. Methods For phase 1 of the study participants were divided into three groups, two lunchtime walking intervention groups to walk around either an urban or natural environment twice a week during their lunch break over an 8 week period. The third group was a waiting-list control who would be invited to join the walking groups after phase 1. In phase 2 all participants were encouraged to walk during their lunch break on self-selecting routes. Health checks were completed at baseline, end of phase 1 and end of phase 2 in order to measure the impact of the intervention on cardiovascular disease risk. The primary outcome variables of heart rate and heart rate variability were measured to assess autonomic function associated with cardiovascular disease. Secondary outcome variables (Body mass index, blood pressure, fitness, autonomic response to a stressor) related to cardiovascular disease were also measured. The efficacy of the intervention in increasing physical activity was objectively monitored throughout the 8-weeks using an accelerometer device. Discussion The results of this study will help in developing interventions with low researcher input with high participant output that may be implemented in the workplace. If effective, this study will highlight the contribution that natural environments can make in the reduction of modifiable cardiovascular disease risk factors within the workplace.

The urban street network is one of the most permanent features of cities. Once laid down, the pattern of streets determines urban form and the level of sprawl for decades to come. We present a high-resolution time series of urban sprawl, as measured through street network connectivity, in the United States from 1920 to 2012. Sprawl started well before private car ownership was dominant and grew steadily until the mid-1990s. Over the last two decades, however, new streets have become significantly more connected and grid-like; the peak in street-network sprawl in the United States occurred in ∼1994. By one measure of connectivity, the mean nodal degree of intersections, sprawl fell by ∼9% between 1994 and 2012. We analyze spatial variation in these changes and demonstrate the persistence of sprawl. Places that were built with a low-connectivity street network tend to stay that way, even as the network expands. We also find suggestive evidence that local government policies impact sprawl, as the largest increases in connectivity have occurred in places with policies to promote gridded streets and similar New Urbanist design principles. We provide for public use a county-level version of our street-network sprawl dataset comprising a time series of nearly 100 y.

Objectives. We evaluated the effects of providing new high-quality, traffic-free routes for walking and cycling on overall levels of walking, cycling, and physical activity. Methods. 1796 adult residents in 3 UK municipalities completed postal questionnaires at baseline (2010) and 1-year follow-up (2011), after the construction of the new infrastructure. 1465 adults completed questionnaires at baseline and 2-year follow-up (2012). Transport network distance from home to infrastructure defined intervention exposure and provided a basis for controlled comparisons. Results. Living nearer the infrastructure did not predict changes in activity levels at 1-year follow-up but did predict increases in activity at 2 years relative to those living farther away (15.3 additional minutes/week walking and cycling per km nearer; 12.5 additional minutes/week of total physical activity). The effects were larger among participants with no car. Conclusions. These new local routes may mainly have displaced walking or cycling trips in the short term but generated new trips in the longer term, particularly among those unable to access more distant destinations by car. These findings support the potential for walking and cycling infrastructure to promote physical activity.

Urbanization is a potential threat to mental health and well-being. Cross-sectional evidence suggests that living closer to urban green spaces, such as parks, is associated with lower mental distress. However, earlier research was unable to control for time-invariant heterogeneity (e.g., personality) and focused on indicators of poor psychological health. The current research advances the field by using panel data from over 10,000 individuals to explore the relation between urban green space and well-being (indexed by ratings of life satisfaction) and between urban green space and mental distress (indexed by General Health Questionnaire scores) for the same people over time. Controlling for individual and regional covariates, we found that, on average, individuals have both lower mental distress and higher well-being when living in urban areas with more green space. Although effects at the individual level were small, the potential cumulative benefit at the community level highlights the importance of policies to protect and promote urban green spaces for well-being.

Public transportation systems are an essential component of major cities. The widespread use of smart cards for automated fare collection in these systems offers a unique opportunity to understand passenger behavior at a massive scale. In this study, we use network-wide data obtained from smart cards in the London transport system to predict future traffic volumes, and to estimate the effects of disruptions due to unplanned closures of stations or lines. Disruptions, or shocks, force passengers to make different decisions concerning which stations to enter or exit. We describe how these changes in passenger behavior lead to possible overcrowding and model how stations will be affected by given disruptions. This information can then be used to mitigate the effects of these shocks because transport authorities may prepare in advance alternative solutions such as additional buses near the most affected stations. We describe statistical methods that leverage the large amount of smart-card data collected under the natural state of the system, where no shocks take place, as variables that are indicative of behavior under disruptions. We find that features extracted from the natural regime data can be successfully exploited to describe different disruption regimes, and that our framework can be used as a general tool for any similar complex transportation system. Significance We propose a new approach to analyzing massive transportation systems that leverages traffic information about individual travelers. The goals of the analysis are to quantify the effects of shocks in the system, such as line and station closures, and to predict traffic volumes. We conduct an in-depth statistical analysis of the Transport for London railway traffic system. The proposed methodology is unique in the way that past disruptions are used to predict unseen scenarios, by relying on simple physical assumptions of passenger flow and a system-wide model for origin–destination movement. The method is scalable, more accurate than blackbox approaches, and generalizable to other complex transportation systems. It therefore offers important insights to inform policies on urban transportation.

Insufficient physical activity (PA) is the fourth major risk factor for many non-communicable diseases and premature mortality worldwide. Features of the built environment (BE) play a considerable role in determining population PA behaviors. The majority of evidence for PA-BE relationships comes from high-income countries and may not be generalizable to low- and middle-income countries (LMICs). We aim to systematically review the literature and assess the associations between perceived and/or objective BE characteristics and PA domains in LMICs. This review adopted a systematic search strategy for English language articles published between January 2000 and June 2019 from four electronic databases-Medline, Embase, Web of Science and PubMed-adhering to the PRISMA guidelines. Studies addressing the associations between self-reported and/or objective BE and PA were only included if they were conducted in LMICs, according to the World Bank classification list. Articles investigating PA-BE relationships across any age groups were included, and all study designs were eligible, except for qualitative studies and reviews. Thirty-three studies were included for evidence synthesis. Cross-sectional studies were the most prevailing study design (97%), revealing a notable gap in longitudinal PA-BE research in LMICs. A majority of the BE factors were not associated with different PA domains while others (e.g., density, proximity to services, aesthetics) exhibited an inconsistent association. Land-use mix diversity was positively associated with transport PA and the presence of recreation facilities resulted in an increase in PA during leisure-time. Increased safety from crime at night consistently increased total PA and walking levels. Research exploring the associations between BE attributes and PA behaviors in LMICs appears to be limited and is primarily cross-sectional. Longitudinal research studies with objective measures are needed for inferring well-grounded PA-BE causal relationships and informing the design of evidence-based environmental interventions for increasing PA levels in LMICs.

Background Increasing global urbanisation has resulted in a greater proportion of the world's population becoming exposed to risk factors unique to urban areas, and understanding these effects on public health is essential. The aim of this study was to examine the association between access to green space and mental health among adult twin pairs. Methods We used a multilevel random intercept model of same-sex twin pairs (4338 individuals) from the community-based University of Washington Twin Registry to analyse the association between access to green space, as measured by the Normalised Difference Vegetation Index and self-reported depression, stress, and anxiety. The main parameter of interest was the within-pair effect for identical (monozygotic, MZ) twins because it was not subject to confounding by genetic or shared childhood environment factors. Models were adjusted for income, physical activity, neighbourhood deprivation and population density. Results When treating twins as individuals and not as members of a twin pair, green space was significantly inversely associated with each mental health outcome. The association with depression remained significant in the within-pair MZ univariate and adjusted models; however, there was no within-pair MZ effect for stress or anxiety among the models adjusted for income and physical activity. Conclusions These results suggest that greater access to green space is associated with less depression, but provide less evidence for effects on stress or anxiety. Understanding the mechanisms linking neighbourhood characteristics to mental health has important public health implications. Future studies should combine twin designs and longitudinal data to strengthen causal inference.