Associations of park features with park use and park-based physical activity in an urban environment in Asia: A cross-sectional study

Park use is associated with health, yet our understanding of park features related to their use is limited. Singapore's parks were audited for 30 micro-features, then geospatial analysis characterized micro-features scores for parks nearest to participants' homes. Adults (3,435) reported their park use and park-based physical activity. Using linear regression models, we found living near a park with higher micro-features scores was associated with more time in parks and park-based physical activity. Specific micro-features were associated with more park time (wildlife areas, water features, forested areas, unpaved trails (2–2.6 h/month, p < 0.05)) and with physical activity in parks (water features, forested areas, large playground, open green spaces (1.8–2.2 h/month, p < 0.05)). These findings could inform parks planning to support population-health.     

Using aggregated mobile phone location data to compare the realised foodscapes of different socio-economic groups.

The foodscape (the built food environment) is considered one of the driving factors of the higher burden of obesity and chronic disease observed in low socio-economic status (SES) groups. Traditional data collection methods struggle to accurately capture actual access and exposure to the foodscape (realised foodscape). We assess the use of anonymised mobile phone location data (location data) in foodscape studies by applying them to a case study in Perth, Western Australia to test the hypothesis that lower SES groups have poorer realised foodscapes than high SES groups. Kernel density estimation was used to calculate realised foodscapes of different SES groups and home foodscape typologies, which were compared to home foodscapes of the different groups. The location data enabled us to measure realised foodscapes of multiple groups over an extended period and at the city scale. Low SES groups had poor availability of food outlets, including unhealthy outlets, in their home and realised foodscapes and may be more susceptible to a poor home foodscape because of low mobility.     

困境家庭环境与儿童健康机会不平等研究--来自全国7省调查分析

儿童健康是健康中国建设的基础,是我国社会可持续发展的重要保障。家庭是儿童健康成长的重要环境。文章基于相互作用的家庭环境系统框架,依据2018年在我国7省份进行的“困境家庭儿童健康状况”专项调查数据,使用基于有序多分类回归的夏普里值(Shapley)分解,详细考察了家庭环境因素导致困境家庭儿童健康机会不平等及其相对贡献。结果发现:家庭环境是导致困境家庭儿童心理健康机会不平等的主要因素。从各个家庭环境因素的相对贡献来看:家庭关系是影响困境家庭儿童自评健康和儿童认知机会不平等的主要原因,而影响困境家庭儿童心理健康机会不平等的主要因素则是家庭经济状况。对于普通家庭儿童来说,各家庭环境因素对儿童获得健康的影响相对均衡。最后,文章就改善困境家庭儿童各维度健康的机会差异等问题进行了讨论。     

One health disparities and COVID-19

 The global impact of the COVID-19 pandemic has disproportionately affected some communities and populations more than others. We propose that an interdisciplinary framework of ‘One Health Disparities’ advances understanding of the social and systemic issues that drive COVID-19 in vulnerable populations. One Health Disparities integrates the social environment with One Health perspectives on the interconnectedness of human, animal, and environmental health. To apply this framework, we consider One Health Disparities that emerge in three key components of disease transmission: exposure, susceptibility, and disease expression. Exposure disparities arise through variation in contact with COVID-19’s causative agent, SARS-CoV-2. Disparities in susceptibility and disease expression also exist; these are driven by biological and social factors, such as diabetes and obesity, and through variation in access to healthcare. We close by considering how One Health Disparities informs understanding of spillback into new animal reservoirs, and what this might mean for further human health disparities.Lay summaryOne Health focuses on interconnections between human, animal, and environmental health. We propose that social environments are also important to One Health and help illuminate disparities in the coronavirus pandemic, including its origins, transmission and susceptibility among humans, and spillback to other species. We call this framework One Health Disparities.     

Web Data Mining: Validity of Data from Google Earth for Food Retail Evaluation

To overcome the challenge of obtaining accurate data on community food retail, we developed an innovative tool to automatically capture food retail data from Google Earth (GE). The proposed method is relevant to non-commercial use or scholarly purposes. We aimed to test the validity of web sources data for the assessment of community food retail environment by comparison to ground-truth observations (gold standard). A secondary aim was to test whether validity differs by type of food outlet and socioeconomic status (SES). The study area included a sample of 300 census tracts stratified by SES in two of the largest cities in Brazil, Rio de Janeiro and Belo Horizonte. The GE web service was used to develop a tool for automatic acquisition of food retail data through the generation of a regular grid of points. To test its validity, this data was compared with the ground-truth data. Compared to the 856 outlets identified in 285 census tracts by the ground-truth method, the GE interface identified 731 outlets. In both cities, the GE interface scored moderate to excellent compared to the ground-truth data across all of the validity measures: sensitivity, specificity, positive predictive value, negative predictive value and accuracy (ranging from 66.3 to 100%). The validity did not differ by SES strata. Supermarkets, convenience stores and restaurants yielded better results than other store types. To our knowledge, this research is the first to investigate using GE as a tool to capture community food retail data. Our results suggest that the GE interface could be used to measure the community food environment. Validity was satisfactory for different SES areas and types of outlets.     

Spatial clusters of daily tobacco consumption before and after a smoke-free policy implementation

This study assessed the spatial dependence of daily tobacco consumption and how it is spatially impacted by individual and neighborhood socioeconomic determinants, and tobacco consumption facilities before and after a smoke-free implementation.Individual data was obtained from the Bus Santé, a cross-sectional survey in Geneva. Spatial clusters of high and low tobacco consumption were assessed using Getis-Ord Gi*.Daily tobacco consumption was not randomly clustered in Geneva and may be impacted by tobacco consumption facilities independently of socioeconomic factors and a smoking ban. Spatial analysis should be considered to highlight the impact of smoke-free policies and guide public health interventions.     

How can an agent-based model explore the impact of interventions on children's physical activity in an urban environment?

Insufficient physical activity (PA) among most children and adolescents is a global problem that is undermining the realisation of numerous developmental and health benefits. The aim of this study was to explore the potential impact of interventions on PA by using an agent-based model (ABM) simulating children's daily activities in an urban environment. Three domains for interventions were explored: outdoor play, school physical education and active travel. Simulated interventions increased children's average daily moderate-to-vigorous PA by 2–13 min and reduced the percentage of children not meeting PA guidelines, from 34% to 10%–29%, depending on the intervention. Promotion of active travel and outdoor play benefited more those in a higher socio-economic position. Agents' interactions suggested that: encouraging activity in diverse groups will reduce percentage of the least active in the population; and initiating outdoor events in neighbourhoods can generate an enhancing effect on children's engagement in PA. The ABM provided measurable outcomes for interventions that are difficult to estimate using reductionist methods. We suggest that ABMs should be used more commonly to explore the complexity of the social-environmental PA system.     

The superspreading places of COVID-19 and the associated built-environment and socio-demographic features: A study using a spatial network framework and individual-level activity data

Previous studies observed that most COVID-19 infections were transmitted by a few individuals at a few high-risk places (e.g., bars or social gathering venues). These individuals, often called superspreaders, transmit the virus to an unexpectedly large number of people. Further, a small number of superspreading places (SSPs) where this occurred account for a large number of COVID-19 transmissions. In this study, we propose a spatial network framework for identifying the SSPs that disproportionately spread COVID-19. Using individual-level activity data of the confirmed cases in Hong Kong, we first identify the high-risk places in the first four COVID-19 waves using the space-time kernel density method (STKDE). Then, we identify the SSPs among these high-risk places by constructing spatial networks that integrate the flow intensity of the confirmed cases. We also examine what built-environment and socio-demographic features would make a high-risk place to more likely become an SSP in different waves of COVID-19 by using regression models. The results indicate that some places had very high transmission risk and suffered from repeated COVID-19 outbreaks over the four waves, and some of these high-risk places were SSPs where most (about 80%) of the COVID-19 transmission occurred due to their intense spatial interactions with other places. Further, we find that high-risk places with dense urban renewal buildings and high median monthly household rent-to-income ratio have higher odds of being SSPs. The results also imply that the associations between built-environment and socio-demographic features with the high-risk places and SSPs are dynamic over time. The implications for better policymaking during the COVID-19 pandemic are discussed.     

A relational approach to evaluate food environments finds that the proximate food environment matters for those who use it

Using a relational approach, this study investigates whether shopping close to home moderates the relationship between the proximate food environment and diet. To address this question, we develop the proximate food retail quality (PFRQ) score, an inverse-distance weighted measure of all food retailers within a resident's neighborhood that incorporates audit data of each food retailer. This study relies on data collected through 24-h dietary recalls and psychosocial surveys administered to 449 adults in two socioeconomically matched neighborhoods. Food retailer audits collected data on the availability, price, and quality of healthful foods. Seventy-one percent of study participants report conducting at least 50% of their food shopping within approximately one mile of their home. Household income and education are associated with likelihood to shop close to home, while access to a personal vehicle is not. Finally, results suggest that, for residents who shop primarily close to home, a one unit increase in proximate food retail environment score is associated with a 17.2-point increase in HEI-2010 score, a measure of overall diet quality that ranges from zero to 100. This study suggests that the food environment matters for those who use it and that a low-quality proximate food environment can amplify individual disadvantage.     

Re-grounding the concept of liminality by foregrounding spatial aspects in experiences of cancer care

Liminality captures the passing stages in transitioning from one sociocultural status to another. As its spatial dimension remains under-examined, we analyse this in experiences of people affected by cancer. We review liminality in cancer-related literature and juxtapose this with empirical material. Analysing interview data (with eight patients) and participant-made photos highlights why places may be experienced differently throughout a period of illness and how places of diagnosis and care ‘stretch’ across locations. We conclude that exploring liminality's spatial dimension has implications for people ‘living beyond’ cancer, advances sociological understandings of (cancer) illness, and may inform healthcare facility design.