How well do street view images predict crime rates in London? A comparison with social and macro-level environmental features

BackgroundChildrens’ outdoor active play is an important part of their development. Play behaviour can be predicted by a variety of physical and social environmental features. Some of these features are difficult to measure with traditional data sources.MethodsThis study investigated the viability of a machine learning method using Google Street View images for measurement of these environmental features. Models to measure natural features, pedestrian traffic, vehicle traffic, bicycle traffic, traffic signals, and sidewalks were developed in one city and tested in another.ResultsThe models performed well for features that are time invariant, but poorly for features that change over time, especially when tested outside of the context where they were initially trained.ConclusionThis method provides a potential automated data source for the development of prediction models for a variety of physical and social environment features using publicly accessible street view images.

IntroductionOur objective was to identify social and physical environmental factors associated with current cigarette smoking among adults by metropolitan county in the United States.MethodsWe linked cigarette smoking data from the 2012 Behavioral Risk Factor Surveillance System (BRFSS) Selected Metropolitan Area Risk Trends (SMART) data set to 7 social and physical environmental characteristics: county type (metropolitan designation), primary care physician density, income inequality, percentage of the population that was a racial/ethnic minority, violent crime rate, education, and percentage of county residents with low income and no health insurance, all obtained from several county data sets. Spatial regression and hierarchical logistic regression modeling were performed.ResultsResults showed that metropolitan counties with a high proportion of non-Hispanic white adults (P < .001), lower education levels (high school graduate or less) (P < .001), and high violent crime rates (P < .001) had a higher adult cigarette smoking prevalence than other metropolitan counties. Spatial models showed 63.3% of the variability in county cigarette smoking prevalence was explained by these 3 factors as well as county type (based on population size of the of metropolitan area), primary care physician density, and percentage of county residents with low income and no health insurance. At an individual level, results showed that as the density (population) of primary care physicians increased in a county, the odds of being a current smoker decreased (OR, 0.980; P = .02).ConclusionWe found a significant association between adult cigarette smoking and county social and physical environmental factors. These place-based factors, especially social environmental characteristics, may reveal tobacco-related disparities to be considered when developing strategies to reduce tobacco use.

Physical and Social Environment Relationship With Sleep Health and Disorders

ObjectivesWe aimed to examine the associations of both objectively assessed and perceived physical and social neighborhood characteristics with happiness in European adults. In addition, we aimed to study how these associations differed among subgroups.MethodsParticipants (N = 6037) of the cross-sectional SPOTLIGHT survey reported on their level of happiness using a 5-point Likert scale, and on perceived physical and social environmental neighborhood characteristics. Objective physical environmental characteristics were assessed using a Google Street View-based neighborhood audit. Associations of 14 physical and social environmental characteristics with happiness were analyzed using multivariable multinomial regression analyses with clustered standard errors.ResultsLiving in neighborhoods with higher levels of aesthetics and more water and green space was associated with being very happy. Individuals who perceived their neighborhood to be safer, more functional and more aesthetic were more likely to be very happy. The associations of functionality and aesthetics with happiness were strongest in the Ghent region (Belgium), the Randstad (the Netherlands) and Greater London (United Kingdom). Perceived absence of air pollution was only associated with higher levels of happiness in more highly educated participants. Individuals with a larger social network, more social cohesion and who trusted their neighbors were more likely to be very happy. The association between social networks and happiness was somewhat stronger in men than in women. In general, the associations between environmental characteristics and happiness had similar directions and sizes across socio-economic and socio-demographic subgroups.ConclusionsThis European study provided evidence that both objectively assessed and perceived physical and social characteristics of the neighborhood environment are associated with the happiness of its residents.

Parent and child perceived neighborhood safety predicts child health outcomes such as sleep quality, asthma, physical activity, and psychological distress. Although previous studies identify environmental predictors of parent perceived safety, little is known about predictors of child perceived safety. This study aims to identify the social and physical environmental neighborhood features that predict child and parent perceived neighborhood safety and, simultaneously, to assess the association between child and parent perceptions. Data were from the QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort, an ongoing study of Caucasian children (aged 8-10 years) with a parental history of obesity, and their biological parents from Québec, Canada. Measures of social and physical neighborhood features were collected using a spatial data infrastructure and in-person audits. Structural equation modeling was used to test direct and indirect associations between neighborhood features, child and parent perceived safety. Results suggest that among children (N = 494), trees and lighting were positively associated with perceived neighborhood safety, whereas a high proportion of visible minorities was associated with poorer perceived safety. Parents' perceptions of safety were more strongly tied to indicators of disorder and a lack of community involvement, and to traffic. Child perceived safety was partly explained by parent perceived safety, suggesting moderate concordance between perceptions. Although associated with each other, parent and child perceived safety seemed to be determined by distinct environmental features. Though this study focused on determinants of child and parent perceived safety, future research investigating the impact of neighborhood safety on child health should consider both child and parent perspectives.

The current study examines the relationship between the features of physical and social environments and neighborhood crime in a large Korean city. We utilized the 112 Crime Calls Data from May 1, 2018 to April 30, 2019, aggregated at the ¼-mile egohood level. We estimated a series of negative binomial regression models to test the effects of social and physical environmental features on crime rates. Furthermore, we examine potential moderating effects between the measures of physical and social environments. The results indicate that incorporating the physical and social environmental features based on the theoretical framework of criminal opportunities and social disorganization can be useful for understanding the spatial patterns of crime in Korean context.

Smart prevention: A new approach to primary and secondary cancer prevention in smart and connected communities

City features related to obesity in preschool children: a cross-sectional analysis of 159 cities in six Latin American countries

Age-friendly cities and environments: an investigation of the living environment of older people in England based on the MRC Cognitive Function and Ageing Study II

BackgroundSuicide is a serious worldwide public health concern, and South Korea has shown the highest suicide rate among Organisation for Economic Co-operation and Development (OECD) countries since 2003. Nevertheless, most previous Korean studies on suicide had limitations in investigating various social environment factors using long-term nationwide data. Thus, this study examined how various social environment characteristics are related to the suicide rate at the district-level, using nationwide longitudinal data over 11 years.MethodsWe used the district-level age-standardized suicide rate and a total of 12 annual social environment characteristics that represented socioeconomic, demographic, urbanicity, general health behaviors, and other environmental characteristics from 229 administrative districts in South Korea. A Bayesian hierarchical model with integrated Laplace approximations (INLA) was used to examine the spatiotemporal association between the rate of suicide and the social environment indicators selected for the study.ResultsIn the total population, the indicators “% of population aged 65 and older eligible for the basic pension”, “% vacant houses in the area”, “% divorce”, “% single elderly households”, “% detached houses”, “% current smokers”, and “% of population with obesity” showed positive associations with the suicide rate. In contrast, “% of people who regularly participated in religious activities” showed negative associations with suicide rate. The associations between these social environment characteristics and suicide rate were generally more statistically significant in males and more urbanized areas, than in females and less urbanized areas; however, associations differed amongst age groups, depending on the social environment characteristic variable under study.ConclusionsThis study investigated the complex role of social environments on suicide rate in South Korea and revealed that higher suicide rates were associated with lower values of socioeconomic status, physical exercise, and religious activities, and with higher social isolation and smoking practice. Our results can be used in the development of targeted suicide prevention policies.

Little is known about the association between environmental features and the risk of Alzheimer’s dementia (AD). This study aims to investigate the association of physical and social environments with the incidence of AD. We identified 12,401 newly diagnosed AD cases aged ≥65 years in 2010, with the same no. of matched controls from National Health Insurance claims in Taiwan. Environmental data were collected from government statistics including three physical environments and three social environments. Multilevel logistic regression was conducted to calculate the odds ratios (OR) of AD in association with environmental features at the township level. Results showed that living in the areas with higher availability of playgrounds and sport venues was associated with a 3% decreased odds of AD (95% CI = 0.96–0.99), while higher density of elderly living alone was associated with a 5% increased odds of AD (95% CI = 1.01–1.11), after controlling for individual and other environmental factors. In further examination by urbanization level, the above relationships were found only in rural areas but not in urban areas. This study provides evidence that specific physical and social environmental features have different impacts on the risk of AD.

This article reviews evidence relating social environment characteristics to patterns of neuroendocrine regulation. To date, although there has been considerable interest in the effects of social ties and support on health and longevity, less attention has been given to the effects of such social environment characteristics on actual physiologic parameters. Animal and human studies from 1960s to the present are reviewed for evidence linking social environment characteristics to patterns of hypothalamic-pituitary-adrenal (HPA) axis, sympathetic nervous system (SNS), and cardiovascular activity. Community and laboratory-based studies document that characteristics of the social environment influence patterns of neuroendocrine reactivity. These effects seem to be highly sensitive to aspects of the social environment such as relative social status, the relative stability of the social ordering and, importantly, the quality of social relationships. Although supportive social relationships are often associated with attenuated patterns of HPA and SNS activation, the converse also seems to be true as nonsupportive social interactions are frequently associated with enhanced reactivity. Available evidence regarding links between social environment characteristics and neuroendocrine regulation documents a link between the social and biological realms that may have important consequences for health and longevity. The data provide support for the hypothesis that observed associations between social ties and health and longevity result, at least partially, from the positive influence of such social environment characteristics in reducing neuroendocrine reactivity. The evidence regarding nonsupportive or hostile social relationships highlights the importance of taking a broader view of the potential health effects of the social environment, one that encompasses the potential for both positive and negative effects.

Humans start new friendships and social connections throughout their lives and such relationships foster mental and physical well-being. While friendship initiation may depend on alignment of subtle and complex personal variables, here we investigated whether it also depends on basic features of social environments. In a preregistered online study (n = 783) using a novel social-affiliation seeking paradigm, we found people were more likely to send friend requests as the density of friendship opportunities decreased and frequency of success increased. Further, we found task-related measures, like overall friend requests, were correlated with mental health dimensions like social thriving and anhedonia. Next, in an ultra-high-field fMRI study (n = 24), we found that both fundamental features of social environments--opportunity density and frequency of success--affected neural activity across a network of regions linked to foraging including dorsal raphe nucleus, substantia nigra, and anterior insula. Thus, humans consider the background statistics of an environment while making social decisions and these decisions are linked to activity in cortico-subcortical circuits mediating the influence of environmental statistics on other aspects of behavior. Moreover, individual differences in how environmental features influence social behavior are associated with variation in mental health dimensions, offering key insights into interindividual variability in social functioning.

Safety seat belt usage has been a great interest to the transportation community. Understanding factors that influence driver’s decision of wearing a safety seat belt or not is essential in determining ways to enhance safety seat belt usage rate. A modeling approach is made to observe the trend of seat belt usage in Mumbai city and to understand the effect of vehicle type, ownership type, driver’s sociodemographic, and environmental characteristics on safety seat belt usage in Mumbai City. Data were collected by roadside observational surveys at various locations in Mumbai during the years 2015 through 2018. The time series model estimate confirms declining trend of drivers not wearing safety seat belt. When vehicles are disaggregated into different build types, buses are found to be associated with no use of safety seat belt as compared to other type of vehicles, and even male drivers follow the same trend in the city. By using random parameter logit model unobserved heterogeneity was captured among individuals. Findings can be used by policymakers to develop intervention strategies to increase seat belt usage in Mumbai and other cities having similar traffic characteristics and social environment features.

BackgroundPhysical and social environments may influence cognition health in older adults. However, evidence regarding physical and social environments linked to dementia is lacking, especially in Asia. This study aims to explore the influence of physical and social environments on the incidence of dementia through a population-based case-control design in Taiwan.MethodsWe identified 26,206 incident cases with dementia aged≧65 years in 2010, with the same no. of controls from National Health Insurance claims. Environmental measures were collected from government statistics including three physical environments and three social environments. Multilevel logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CI) of the association between dementia incidence and the environmental measures at the township level.ResultsWe observed a significant reduction of 12% in the odds ratios of dementia in areas with higher availability of playgrounds and sport venues (OR 0.88, 95% CI 0.81–0.95), after controlling for individual and other environmental characteristics. Community center availability was also significantly associated with an 8% decreased odds for dementia (OR 0.92, 95% CI 0.87–0.99), but the association was not significant after further consideration of individual-level characteristics. Although higher odds of dementia were found in areas with high median annual family income (OR 1.14, 95% CI 1.04–1.25), such a significant relationship did not appear in the full model.ConclusionsOur study suggests that specific physical and social environmental features have different influences on the risk of dementia. Public health interventions may consider these environmental aspects for preventing dementia incidence.