Methods: Recurrent AMI was identified by the Beijing Monitoring System for Cardiovascular Diseases through the end of 2019 for patients discharged with AMI between 2007 and 2017. Cox proportional hazards models were performed to estimate associations between neighborhood disorder and AMI recurrence.
Results: Of 66,238 AMI patients, 11,872 had a recurrent event, and 3117 died from AMI during a median followup of 5.92 years. After covariate adjustment, AMI patients living in the high tertile of neighborhood disorder had a higher recurrence risk (hazard ratio [HR] 1.08, 95 % confidence interval [CI], 1.03–1.14) compared with those in the low tertile. A stronger association was noted for fatal recurrent AMI (HR 1.21, 95 % CI 1.10–1.34). The association was mainly observed in females (HR 1.04, 95 % CI: 1.02 to 1.06).
Conclusions: Serious neighborhood disorder may contribute to higher recurrence risk, particularly fatal recurrence, among AMI patients. Policies to eliminate neighborhood disorders may play an important role in the secondary prevention of cardiovascular disease.
Online paper: https://www.tandfonline.com/doi/full/10.1080/24694452.2022.2114417
Data and Code: https://data.mendeley.com/datasets/d3d4h5bvss/1
To date, most studies have assessed individual exposure to neighborhood physical disorder (NPD) through the static residence-based approach, which ignores elements of human mobility and may lead to inaccurate estimates. This study assessed individual exposure to neighborhood physical disorder through the mobility-based approach using wearable cameras. The use of this approach allowed us to leverage innovative tools to accurately assess exposure to NPD in individuals’ activities in space-time. We assessed the volunteers’ exposure to neighborhood physical disorder by manually auditing pictures taken by wearable cameras on an online browserbased assessment platform. The results illustrated that wearable cameras can clearly capture the exposure while volunteers were engaged in travel behaviors. We also compared the proposed approach (mobility-based, using wearable cameras to take photos) with other approaches (with consideration of travel behaviors to varying degrees, using street view images) to demonstrate that wearable cameras can record individual exposure to neighborhood physical disorder accurately and conveniently, and the assessment results might be significantly different from those obtained by other approaches. Thus, the proposed approach is of great significance.
Based on scoping review and field research, we build a quantitative checklist for physical disorder and a standard handbook for auditing that includes the characteristics of Chinese urban landscapes. Via the self-developed virtual audit online system, the validity of the checklist and the off-site audit method is verified through small-scale manual audit, and a sample library of disordered street view images is constructed. Model training and optimization are carried out applying Faster R-CNN, SSD object detection algorithm and SegNet segmentation algorithm. We finally select the optimal deep learning model for each physical disorder factor (with F2-score above 80%).
With street view image data for multiple years, we further applied this model to carry out an empirical study on the street space within the Fifth Ring Road in Beijing and estimated physical disorder levels throughout the city, providing evidence for understanding the characteristics of urban physical disorder in China. The deep learning results show that although the overall urban spatial quality of the city is moderate, physical disorder is still common and spread to varying degrees in Beijing urban area, where ratio of the points with disorder has reached 69.8% among the 71,165 street view points. Also, disordered areas performed concentrated in the north within the Second
Ring Road. Stores with poor signboards, garbage/litter on street and graffiti/illegal advertisement are the main factors of disorder that affect the quality of urban space in Beijing, leaving a negative impact on the vitality of the space. For the multiyear scenario, the overall street space quality tends to improve (50.4% of street view points have witnessed the decreasing or even disappearing of disorder, while 16.1% remained basically the same). For areas within the Second Ring Road and Chang'an Avenue and the extension area, the space quality has improved significantly, indicating the certain effects of the urban space renovation. This study also sorted out various intervention methods in the urban street design guidelines at home and abroad, proposed sustainable strategies for specific disorder factors which significantly improved the space quality.
Under the call of the construction and quality improvement of urban space, the current uneven quality of the space caused by extensive urban development is worthy of attention, given the lack of maintenance of the old city core, the brown filed and vacant land, as well as the decay of the urban environment that is common in many cities. Drawing on a concept from sociology, this phenomenon of poor space quality and chaotic space order is defined as a physical disorder of urban space. With a new method of off-site built environment audits based on street view images, this study measures and evaluates the physical disorder of urban space within Beijing's Fifth Ring Road area. It finds that varying degrees of physical disorder is spread in this area, where the disorder has reached 50.1% among the 70,436 street points. The unkempt façades of buildings and roads lacking maintenance were the main factors of disorder that affect the quality of urban space in Beijing, leaving a negative impact on the vitality of the space. This study also carries out spatial intervention experiments that target specific disorder factors and can significantly improve the space. The large scale measurement of public spaces of poor quality or even disordered space provides an important basis for refined management and intervention of cities in the future.
In recent years, space quality and design of streets have received increasing attention. In the field of public health, the insufficient quality of urban spatial characteristics or even disorder have been proved to directly or indirectly affect the physical and mental health of individuals, implying high-risk influence on individual behavior and delivering negative health outcomes. The improvement of micro-scale spatial features is beneficial to enhancing the activity-friendliness of public space and shaping positive psychological perceptions, thereby promoting public health. Focusing on the core goal of creating high-quality urban street space, this study takes the street space of the public space as the research object, and pays attention to the phenomenon of insufficient local space quality. Based on the current quality and significant characteristics of street space quality in China, it sorts out relevant design strategies in various street design guidelines for cities at home and abroad, and proposes design response strategies for different space quality factors, so as to explore the practical points to solve the problem of poor street space quality or physical disorder in Chinese cities, to pave a way for public health-oriented environmental maintenance, improvement and organic renewal, and to further serve the refined urban space management and design.
With improvements and optimization in the field of urban construction and people's pursuit of a higher quality of life, spatial quality has become an important aspect of urban research. However, rapid developments in the Chinese economy in recent years have caused disordered local urban space. In this study, area within the second ring of Hefei City was used as the research object, and multi-source data (e.g., street view images) were applied as carriers. On this basis, the physical disorder phenomenon, the relationship between different street types and the degree of physical disorder in Hefei City were explored through technical methods such as virtual built-environment audit. For area within the second ring road of Hefei City, the results revealed as following: (1) for the overall spatial quality, the degree of physical disorder was 35.11%; (2) among the spatial features explored, the commercial elements along the street presented the highest disorder degree; and (3) the quality of the space along the streets of land servicing commercial-industry facilities (Class B) was the worst, while the quality along the streets of logistics and storage land (Class W) was the best. Based on physical disorder theory, this study quantitatively measured the quality of street space. In practice, these findings provide important insights toward improving the urban management of cities in the future. In theory, they address the limitations of current research into physical disorder in China's urban space.