Walk In Environment Research Articles

Associations of neighborhood social cohesion and changes in BMI-The Maastricht Study.

The role of the social environment can facilitate positive health outcomes through active community engagement, normalization of healthy behaviors, and stress buffering. We aim to examine the associations of neighborhood social cohesion with changes in BMI over time. A total of 7641 participants from The Maastricht Study between the ages of 40 and 75 years were analyzed. Weight and height were measured at baseline, and weight was self-reported annually up to 10 years of follow-up (median = 4.7 years). Perceived social cohesion was obtained by questionnaire. Home addresses for each participant were linked to geographic information system data from the Geoscience and Health Cohort Consortium to create neighborhood exposure variables including area level social cohesion, neighborhood walkability, and food environment within a 1000 m Euclidian buffer. Linear regression analyses were performed with BMI adjusted for socioeconomic variables. A mixed model analysis was carried out to examine changes in BMI. Living in the highest quartile area of individually perceived social cohesion was associated with lower BMI (Q4 B: -.53; 95% CI = -.79, -.28) compared to the lowest quartile. Similar findings were discovered using the area level measure (Q4 B: -.97; 95% CI = -1.29, -.65). There was no longitudinal association between social cohesion and BMI. Neighborhood social cohesion was associated with lower BMI classifying it as an obesogenic area characteristic that influences weight, independent of conventional built environment features.

Analyzing Walkability in Hyderabad: A Study of Sakhi Sultan Road

The current study aimed to address the critical issue of climate change and the role of urbanization in exacerbating global warming. Urban sprawl and reliance on automobiles have led to the occurrence of significant urban problems. Therefore, the current study focused on the concept of walkability and its potential to foster sustainable urban neighborhoods. Walkability can be referred to as an effective green transport option that reduces congestion, environmental impact, and energy consumption while promoting healthier lifestyles and social cohesion. Moreover, the study also emphasized the necessity of innovative and strategic design and planning of neighborhood streets to enhance walkability. The research methodology comprised a case study of Sakhi Sultan Road in Hyderabad using field observations and visual analysis to assess the current condition and potential for improvement. The visual analysis identifies various environmental features that influence walkability including aesthetics, functionality, and safety. The findings revealed a mixture of present and absent features across different spots on the street. Additionally, the study also identified multiple issues, such as inadequate maintenance, lack of accessibility features, and encroachments on pedestrian pathways. All these issues highlight a need to improve and enhance walkability. Literature review supports the relationship between walkability and sustainability, citing that walkable environments enhance the quality of life, promote environmental sustainability, and reduce urban issues, such as traffic congestion and pollution. The study concluded with recommendations to address the highlighted issues and enhance the environmental features in order to foster a more walkable and sustainable urban environment.

Neighbourhood walkability and body mass index in children: Evidence from the Millennium Cohort Study in Wales

BackgroundOverweight and obesity in children continues to increase. Yet, the role of active transport, namely walking, in mitigating these trends remains unclear. This study examined the cross-sectional association between walkability and children's Body Mass Index (BMI) and how this varies by socio-economic and lifestyle characteristics. MethodsWe analysed BMI for 14-year-old children living in Wales from the UK Millennium Cohort Study. Children were categorised as healthy weight, overweight or obese using the British 1990 cut-off points. Walkability was assessed using the Wales Active Living Environments (Wal-ALE) database, categorised as 1 (least walkable environments) to 5 (most walkable environments). We applied multinomial logistic regression analysis and adjusted for ethnicity, having a limiting longstanding illness, parental BMI, socio-economic circumstances, and lifestyle characteristics. ResultsChildren were more likely to be obese if they lived in areas classed as more walkable in unadjusted analysis [Relative Risk Ratio (RRR) = 1.72 (95%CI = 1.15–2.58)] and following adjustment for ethnicity, limiting longstanding illness and parental BMI [RRR = 1.83 (95%CI = 1.12–3.00)]). Significant associations remained even after further adjustment for lifestyle characteristics and socio-economic circumstances [RRR = 1.76 (95%CI = 1.05–2.96)]. Further, children were more likely to be obese if their parents were overweight or obese and if they were living in poverty. Children were less likely to be obese if they spent 3 or more days per week in moderate-to-vigorous physical activity (MVPA) and if they ate breakfast every day vs. some days or never. ConclusionFindings demonstrate that walkable environments are not associated with lower rates of obesity in children, indicating that the relationship between the built environment and child health is complex and requires further study.

Assessing the walkability of high-density neighborhoods: Development and reliability of the high-density environment assessment tool (HEAT)

BackgroundWalking is a widespread and multifaceted activity among residents in high-density cities, making assessing the neighborhood walking environments important. Existing tools for assessing walkability in high-density cities primarily focus on the immediate environment of sidewalks. However, an individual's walking behavior is influenced by environmental characteristics across multiple dimensions and scales. Consequently, based on a systematic analysis of the features of high-density cities, this study proposes the High-density Environment Assessment Tool (HEAT). This hybrid approach comprehensively assesses walkability in high-density cities by incorporating variables of neighborhood, segment (sidewalk), and crossing. MethodsThe HEAT consisted of three sections with 108 items. To validate the reliability and applicability, field tests were conducted in two 15-min walkable neighborhoods with different built environment contexts in Chongqing City, China. The neighborhood section was objectively assessed using ArcGIS Software. The segment section and crossing section were audited through systematic on-site observation. Four pairs of trained raters assessed all of the segments (n = 139) and crossings (n = 123) within the two neighborhoods. The inter-rater reliability of the repeated audit data was evaluated by Kappa/Weighted Kappa or Percentage Agreement values. A web-based application was used for data collection and input. ResultsFor the neighborhood section, 21 assessment items were included. For the segment and crossing sections, 87 assessment items were included for the reliability test, and 84 (96.6%) of the items indicated satisfying inter-rater reliability (with Kappa/Weighted Kappa value ≥ 0.4 or high Percentage Agreement). In addition, the audit of each segment and crossing sample was completed in an average of 7.9 and 1.8 min, respectively. ConclusionsThe results indicated that the HEAT was reliable and efficient. The HEAT provided an effective tool for assessing the walkability of the neighborhood built environment in high-density cities, thereby facilitating environmental interventions aimed at promoting walking activities.

A participatory mapping approach to capturing perceived walkability

We present a novel method for capturing citizens’ views on perceived walkability. Peoples’ decisions to use any transport mode are determined by perceived accessibility, thus perceived walkability is vital to the decision to walk for transport. To date, approaches to understanding perceived walkability, such as detailed ‘walkability audit’ instruments, have been difficult to scale and linked only to respondents’ residential locations. In contrast our research uses an online mapping tool designed to rapidly capture vague knowledge about places. Respondents use a map interface to spray-paint the most and least walkable areas across the city of Sydney, Australia, along with defining the area they regularly walk from home and where they would be willing to walk. They also provide free-text input to explain their responses. This approach enables data collection of respondents’ holistic understanding of the walkability of different areas based on the local knowledge and experience of the city. Pilot results together with qualitative analysis of text submitted in response to open ended questions are presented to demonstrate the feasibility, face validity and potential of the method. A comparison with an accessibility-based walkability index, WalkTHERE, for Sydney is shown. Results are broadly aligned, but the perceived walkability results presented highlight the negative environmental quality of walking near high-traffic roads and the positive aspects of natural and water views, which are not captured in this walkability index. Perceived walkable areas around the home were on average similar in overall area to the common standard of 15-minute buffers, but longer in their longest dimension, and have irregular shapes. Detailed methodology for analysis of the online mapping inputs is provided. This method has potential for rapid yet rich data collection, particularly when used together with a walkability model to understand differences which can point to localised problems with walking environment quality.

Use of Wearables in Frail Institutionalized Older Adults While Ambulating in Different Environments

(1) Prolonged life expectancy often leads to declining health, reduced physical activity, and dependence, especially in institutionalized elderly. Frailty, obesity, limited functionality, and cognitive impairment are common. Physical activity programs for this demographic can increase weekly energy expenditure and improve frailty. Understanding differences in walking indoors versus outdoors is crucial for tailored programs. This study aimed to compare time, energy expenditure, and perceived exertion in institutionalized elderly walking indoors versus outdoors. It also explored how body mass index and cognitive levels affected these factors. (2) Employing a cross-sectional descriptive observational approach, the study gathered data on height, weight, accelerometers, the modified Borg Scale, the Timed Up and Go test, and the Lobo Cognitive Mini-Exam from a sample of 30 institutionalized older adults. (3) Walking outdoors leads to shorter walking times, higher energy expenditure, and increased perceived effort. Overweight individuals expend more energy in both settings, while cognitive impairment does not significantly impact walking preferences. (4) The study concludes that indoor walking is preferable for frail elderly due to lower perceived exertion, but outdoor walking is recommended for overweight individuals. Cognitive status does not influence the choice of walking environment.

Real-Time Tracking Data and Machine Learning Approaches for Mapping Pedestrian Walking Behavior: A Case Study at the University of Moratuwa.

The growing urban population and traffic congestion underline the importance of building pedestrian-friendly environments to encourage walking as a preferred mode of transportation. However, a major challenge remains, which is the absence of such pedestrian-friendly walking environments. Identifying locations and routes with high pedestrian concentration is critical for improving pedestrian-friendly walking environments. This paper presents a quantitative method to map pedestrian walking behavior by utilizing real-time data from mobile phone sensors, focusing on the University of Moratuwa, Sri Lanka, as a case study. This holistic method integrates new urban data, such as location-based service (LBS) positioning data, and data clustering with unsupervised machine learning techniques. This study focused on the following three criteria for quantifying walking behavior: walking speed, walking time, and walking direction inside the experimental research context. A novel signal processing method has been used to evaluate speed signals, resulting in the identification of 622 speed clusters using K-means clustering techniques during specific morning and evening hours. This project uses mobile GPS signals and machine learning algorithms to track and classify pedestrian walking activity in crucial sites and routes, potentially improving urban walking through mapping.

Determinants of sedentary behavior in community-dwelling older adults with type 2 diabetes based on the behavioral change wheel: a path analysis

BackgroundSedentary behavior (SB) is deeply ingrained in the daily lives of community-dwelling older adults with type 2 diabetes mellitus (T2DM). However, the specific underlying mechanisms of the determinants associated with SB remain elusive. We aimed to explore the determinants of SB based on the behavior change wheel framework as well as a literature review.MethodsThis cross-sectional study recruited 489 community-dwelling older adults with T2DM in Jinan City, Shandong Province, China. Convenience sampling was used to select participants from relevant communities. This study used the Measure of Older Adults’ Sedentary Time-T2DM, the Abbreviated-Neighborhood Environment Walkability Scale, the Social Support Rating Scale, the Lubben Social Network Scale 6, the Subjective Social Norms Questionnaire for Sedentary Behavior, the Functional Activities Questionnaire, the Numerical Rating Scale, the Short Physical Performance Battery, and the Montreal Cognitive Assessment Text to assess the levels of and the determinants of SB. Descriptive statistical analysis and path analysis were conducted to analyze and interpret the data.ResultsPain, cognitive function, social isolation, and social support had direct and indirect effects on SB in community-dwelling older adults with T2DM (total effects: β = 0.426, β = -0.171, β = -0.209, and β = -0.128, respectively), and physical function, walking environment, and social function had direct effects on patients’ SB (total effects: β = -0.180, β = -0.163, and β = 0.127, respectively). All the above pathways were statistically significant (P < 0.05). The path analysis showed that the model had acceptable fit indices: RMSEA = 0.014, χ 2/df = 1.100, GFI = 0.999, AGFI = 0.980, NFI = 0.997, RFI = 0.954, IFI = 1.000, TLI = 0.996, CFI = 1.000.ConclusionCapability (physical function, pain, and cognitive function), opportunity (social isolation, walking environment, and social support), and motivation (social function) were effective predictors of SB in community-dwelling older adults with T2DM. Deeper knowledge regarding these associations may help healthcare providers design targeted intervention strategies to decrease levels of SB in this specific population.

Build environment, race, and walking behavior: A multiscale analysis

Hispanics have a documented higher risk of obesity than other ethnic minorities. Walking can reduce the risk of obesity and promote healthy living. However, walking behavior varies with race/ethnicity, and Hispanics’ walking behavior is less understood. This study compared the walking behaviors of Hispanic and non-Hispanic White residents in Salt Lake County (SLCo), Utah, at the personal and block group levels, based on data from the Utah Household Travel Survey (UHS), which covered 2800 households and 176 Hispanic individuals in SLCo, including their travel trips and socioeconomic status. Trip-level data from the UHS were aggregated into personal and block group levels based on trip ends for multiscale analysis. Our statistical analysis suggested that Hispanics’ walking frequency and density were significantly lower than those of non-Hispanic Whites. According to the personal-level model, education generally contributed to ethnic disparities in walking, but higher education did not increase Hispanics’ walking frequency. The block-group-level model showed that non-Hispanic Whites’ walking behavior was highly sensitive to the built environment. We also found positive impacts of worship accessibility on walking density, which might be unique to non-Hispanic White neighborhoods in SLCo. Built environment factors influenced Hispanics’ walking behavior less than that of non-Hispanic Whites, and the primary determinants included car ownership, driving license, and accessibility of public transit. The research outcomes of this study could provide implications for designing strategies to promote walkability based on ethnic disparities. This also encourages further investigations into the equity of walkable environments for different racial/ethnic populations as an environmental injustice issue.

Physical independence and related factors among older adults: a systematic review and meta-analysis

Background: Adopting a physically active lifestyle is advocated as a strategy to prevent loss of physical independence and support healthy aging. This study aimed to evaluate the physical independence and related factors among older adults. Materials and methods: This systematic review and meta-analysis was conducted through electronic databases such as Scopus, PubMed, Web of Science, Iranmedex, and Scientific Information Database from the earliest to 1 April 2022. Two researchers independently extracted information from the studies and evaluated the quality of the studies. The analysis was conducted using CMA program version 3, and each study’s importance was determined based on its inverse variance. Results: Five thousand seven hundred thirty-three older adults participated in this review in six studies. All evaluated studies had high quality. The mean score of physical independence in older adults was 20.07 (SE=0.76) out of 24 (95% CI: 18.58–21.56; I2 =98.573%; P&lt;0.001). Physical activity is very important for physical independence and reduces the risk of physical dependence in older adults. Other factors, such as sex, BMI, age, abnormal performance, timed performance, sufficiently active, muscle function, handgrip strength, lower extremity function, lower body strength, maximal isometric knee extension power, lung function, aerobic endurance, sedentary time, agility, and the prevalence of arthritis, had a significant relationship with physical independence in older adults. Conclusion: Older adults demonstrate favourable levels of physical independence. Notably, physical activity emerges as a significant determinant positively associated with such independence. Thus, policymakers and administrators are encouraged to strategize the creation of conducive environments for walking and exercise among older adults.

Artificial Neural Network Accuracy Optimization Using Transfer Function Methods on Various Human Gait Walking Environments

A bionic leg with ergonomic functionality can increase the user’s independence. However, an ergonomic bionic leg can be challenged to be developed. One of its challenges is related to functionality, where the bionic leg motor can be rugged to adapt to the user. One of the solutions for the bionic leg challenge is the application of a motor driver controlled by the user’s muscle signal. EMG signal can be utilized as the user’s signal source. The EMG signal is then fed back into the motor device. EMG signals obtained during a natural walking environment can result in smooth and natural movement. This study classifies EMG signals into 8 classes: a controlled walking environment (treadmill walking with various speeds) and a natural walking environment (ground walking, upstairs and downstairs walking). This research aims to optimize the ANN method using transfer function variations. The best method will be used to train EMG-driven motors for future studies related to bionic legs. The best ANN parameter in this research using Levenberg-Marquardt backpropagation as a training algorithm with transfer function pairing of the exponential function: Hyperbolic tangent sigmoid transfer function and SoftMax transfer function with 98.8% accuracy and 0.036 MSE value. The best method from the experiment and ANN classification can be used as a training method for a bionic leg in future research.

Navigating the Challenges Encountered While Dual-task Walking in Real-life Environment by Elderly with Type 2 Diabetes Mellitus

Abstract Background and Objectives: Real-life walking environment comprises various attentionally demanding activities that require intact dual-tasking ability. Dual-task cost is higher in older adults with type 2 diabetes mellitus (T2DM) while walking due to the alterations in cognition and gait. However, contextual variations in the familial, social, and environmental conditions also influence walking in real-life environments. There is a scarcity of literature exploring the challenges linked with contextual variations while dual-task walking in real-life environments for older adults with T2DM. Hence, this study aims to identify barriers and facilitators to dual-task walking in real-life environments for T2DM elderly. Methods: The study used a phenomenological approach and interviewed older adults with and without T2DM using a semi-structured interview guide. It comprised open-ended questions on walking difficulties in a real-life environment. Results: Four themes were identified which comprised individual, social, environmental, and policy-level factors influencing walking. Role transitions within the family, fear, infrastructural impediments, and overprotectiveness of family members were identified as barriers whereas health literacy, positive outlook, occupational demands, and devout engagement in religious participation were identified as facilitators to walking in the elderly. The participants expressed several policy-level challenges, and emphasis was made on outdoor modifications and the need for community programs. Conclusion: The findings of this study provide insights into various constructs close to real-life walking environment that needs to be included in dual-task cost evaluation tools and several measures that can be taken at the familial and policy levels to increase the community mobility of older adults with T2DM.

Utilizing Space Syntax Techniques to Understand the Relationship Between Spatial Configuration and Walkability in Urban Neighborhoods (Case Study: Valiasr Neighborhood, Tehran)

The numerous benefits of walking, as one of the healthiest, simplest, and most cost-effective modes of transportation, have prompted many urban researchers to identify influential factors in pedestrian-oriented urbanism. These efforts aim to transform urban areas, including neighborhoods, into conducive environments for walking, thereby realizing related benefits such as sustainable development. Extensive research has confirmed the role of the built environment in attracting and distributing pedestrian movement, with a significant portion highlighting the relationship between urban configuration and walkability. This study aims to determine the role of urban configuration components in enhancing walkability at the neighborhood scale, selecting the Valiasr neighborhood in Tehran due to its location in the city’s commercial center with a high volume of pedestrian traffic. For this purpose, after identifying spatial configuration components related to walkability – including accessibility, connectivity, and spatial arrangement components – key streets in the neighborhood's spatial configuration were identified using an initial analysis of spatial arrangement variables, followed by a survey of pedestrian volumes on selected streets. The evaluation of configuration components led to design recommendations in two layout patterns – grid and parallel block. The relationship between urban configuration and walkability, utilizing space syntax techniques, was identified after analyzing spatial arrangement variables in three different scenarios (existing condition and two proposed alternatives). The results indicate that accessibility components have the most significant impact on walkability in the Valiasr neighborhood. Following this, connectivity components were identified as influential in promoting pedestrian-oriented urbanism. Regarding spatial arrangement components, a comparison with prior research confirms that spatial elements do not operate independently of mixed-use and access to services and facilities. Instead, they play a role not in the formation of movement but in facilitating and directing it.

Unraveling the Dynamic Relationship between Neighborhood Deprivation and Walkability over Time: A Machine Learning Approach

Unraveling the Dynamic Relationship between Neighborhood Deprivation and Walkability over Time: A Machine Learning Approach

Spatial Image-Based Walkability Evaluation Using Regression Model

Spatial Image-Based Walkability Evaluation Using Regression Model

Impacts of Streetscape Features on Individual Social Capital: Applying Korea’s Neighborhood Data to Street View Images to Improve Lives of the Socially Vulnerable

Neighborhood social vulnerability is a dimension of vulnerability that influences society’s response to external factors, encompassing various social factors tied to socioeconomic and demographic attributes at the neighborhood level. While previous studies have explored the associations between vulnerable neighborhoods and stressors like environmental hazards, understanding of their impact on residents’ social capital remains limited. Moreover, the role of built environments in mitigating these effects is uncertain. This study investigates the impact of neighborhood social vulnerability, alongside streetscape features, on individual social capital in Seoul, South Korea. Using a stratified random sampling method, we surveyed 1000 Seoul residents, assessing their social capital and demographics. In particular, six questionnaires based on a four-point Likert scale were used to measure the individual level of social capital: two questions for social networks, three questions for social participation, and one question for sense of community. Additionally, we employed a deep learning-based model to analyze Google Street View images for detailed streetscape features. Our analysis, utilizing multiple and ordinal logistic regression models, reveals that walkable environments and neighborhood prosperity, indicated by factors like income, education, and street greenery, are linked to higher social capital. Moreover, less urbanized areas with lower land prices and greater openness to the sky also show positive associations. These findings underscore the potential of improving streetscape features to mitigate the negative impacts of neighborhood vulnerability, particularly in neighborhoods where low-income and less-educated residents are concentrated, offering insights for urban planners and community leaders.

Different smartphone tasks and traffic complexity affect pedestrian awareness of co-existing road objects and cerebral oxygenation during shared space walking

Distraction, primarily owing to the widespread use of cell phones and mobile devices while walking, is a contributing factor to pedestrian injuries. Pedestrians distracted by smartphones exhibit decreased situational awareness, influenced by the nature of concurrent tasks. However, little is known about the neural correlations between smartphone use and pedestrian responses to safety–critical events in a walking environment. This study recruited 30 young adults to investigate pedestrians’ ability to selectively respond to road objects while using smartphones (texting and reading) while walking in an immersive virtual environment system. The level of traffic complexity for the road conditions was manipulated by varying the number of safety–critical road objects coexisting in the environment at any given time and the number of required responses to the number of objects. During each 7-min task condition, cerebral oxygenation was measured using functional near-infrared spectroscopy. Furthermore, smartphone task performance, response times to road objects, and perceived workload were also measured. The participants exhibited reduced texting speed and reading performance when responding sequentially to coexisting road objects. Compared with other road conditions, those requiring two responses to four objects resulted in an increased workload and longer object response times. Participants perceived a higher workload in conditions involving tasks with smartphones than those without smartphones. More importantly, increased concentrations of oxygenated hemoglobin in the prefrontal cortex were observed when participants were concurrently performing smartphone and pedestrian tasks. Compared to smartphone reading, smartphone texting induced greater cerebral oxygenation in the bilateral frontopolar cortex. These results suggest that continuously texting while walking may demand additional cognitive resources for executive function. The findings of this study represent an initial step towards elucidating the cognitive mechanisms underlying attentional impairments experienced during smartphone distraction and working towards a viable solution to mitigate pedestrian risk.

Social cohesion and associations with sedentary time, physical activity and dietary quality in The Maastricht Study

IntroWe aim to investigate the relationship between social cohesion and sedentary behavior (SB), total physical activity (PA), moderate-to-vigorous PA (MVPA), and dietary quality. Additionally, we assess whether these associations are independent of neighborhood walkability and the food environment. MethodsA total of 7641 participants from The Maastricht Study in the Netherlands between the ages of 40 and 75 years were analyzed. Neighborhood social cohesion was obtained by participant questionnaire completed at baseline and measured by the Dutch Livability meter. Home addresses were linked to geographic information system (GIS) data from the Geoscience and Health Cohort Consortium (GECCO) to create neighborhood exposures of walkability and food environment. A thigh worn accelerometer collected data to measure sedentary time, total daily PA, and MVPA. Dietary quality was measured with a food frequency questionnaire. Multivariate linear regression analyses were adjusted for age, sex, socioeconomic position, neighborhood walkability, and food environment. ResultsThose living in the highest quartile area of perceived social cohesion had statistically significant lower levels of SB (Q4 B: -13.04; 95% CI = −20.23, −5.85), higher total PA (Q4 B: 4.39; 95% CI = 1.69, 7.10), and higher MVPA (Q4 B: 2.57; 95% CI = 0.83, 4.31) and better diet quality (Q4 B: 1.12; 95% CI = 0.24, 2.01) compared to the lowest quartile independent of walkability and food environment. Similar results were found using the Livability meter. ConclusionWe discovered neighborhood social cohesion as an important obesogenic determinant that should be considered in policymaking to encourage higher levels of PA and higher diet quality.

Associations of perceived built environment characteristics using NEWS questionnaires with all-cause mortality and major cardiovascular diseases: The prospective urban rural epidemiology (PURE)-China study

BackgroundDespite increased literature focusing on the role of the built environment (BE) in health, few cohort studies have quantitatively analyzed neighborhood walkability environment in relation to the risk of death and cardiovascular disease (CVD). This longitudinal study aimed at evaluating the association between perceived BE attributeswith mortality and major CVD based on the Prospective Urban Rural Epidemiology study in China (PURE-China). MethodsThe PURE-China study recruited 47,931 participants aged 35–70 years from 12 provinces of China between 2005 and 2009. The perceived BE information, including land use, street, aesthetics, and safety, was collected using the neighborhood environment walkability scale (NEWS) questionnaire, with higher scores indicating a more favorable rating. Two primary outcomes are all-cause mortality and major CVD event. The Cox frailty model with random intercepts was used to assess the association between the perceived total BE/subscales score and outcomes. ResultsOf 32,163 participants included in this study, 19,253 (59.9 %) were women, and the mean (SD) age was 51.0 (9.5) years. After a median follow-up period of 11.7 years (IQR 9.4 – 12.2), we observed that one standard deviation higher of combined BE scores was related to a lower risk of all-cause mortality (HR = 0.85; 95 %CI, 0.80–0.90), and major CVD events (HR = 0.95; 95 %CI, 0.90–0.99). The subscales of perceived BE were related to a lower risk, although a few were not significant. Land use mix-diversity and safety from crime were the two most significant subscales. Stronger risks were observed among urban and female participants. ConclusionFavorable perceived BE characteristics were linked with a lower risk of all-cause mortality and major CVD events in Chinese population, especially in urban areas and females. Our findings can be used by policymakers to take action to mitigate the adverse effect of poor community conditions on health, such as improving local amenities and transport connectivity, providing building paths for walking, running and cycling.

Design Strategies to Improve Metro Transit Station Walking Environments: Five Stations in Chongqing, China

While transit-oriented development (TOD) has been widely adopted in urban design alongside the expansion of urban metro transit, the creation of pedestrian-friendly environments has often been overlooked during implementation. This has resulted in a lower walking advantage around metro transit stations. To address this issue and encourage walking and public transport use in metro transit station areas, this study undertook a quantitative comparative analysis of the pedestrian environment in five Chongqing metro transit station areas. The analysis focused on three key dimensions: “comprehensive evaluation”, “basic scale”, and “structural quality”. The comprehensive evaluation considered factors such as the pedestrian catchment area ratio, POI kernel density distribution, and crowd agglomeration. The basic scale dimension comprised floor area ratio, building density, pedestrian road density, and the quantity of station entrances and exits. Finally, structural quality factors included land use type mixing degree, POI function mixing degree, intersection connectivity, median street length, pedestrian route directness, and green view index. Based on these analyses, this study proposes a series of pedestrian environment design strategies including land use and transportation. The strategies for land use advocate for “developing compact and diverse land use”, “strengthening attraction of station center”, “positioning large projects on the edge”, “restricting private transportation capabilities”. The strategies for transportation consist of “increasing pedestrian road density”, “traffic calming organization”, “subdivision of road types”, and “three-dimensional pedestrian traffic system”. These strategies aim to create a more humanized and environmentally friendly pedestrian environment, proactively rise to the challenge of climate change, thereby cultivating sustainable urban development.