Residential open space and the perception of health benefits: How much is the public willing to pay?

Emerging evidence suggests that residential open space (ROS) is beneficial for multiple health outcomes for urban residents. However, the general public's understanding of and demand for the health benefits related to ROS have not been widely explored. This study aims to examine the impact of residents' socioeconomic status and perceptions of landscape health benefits on their willingness to pay (WTP) for ROS and to evaluate the perceived monetary value of different residential landscape elements. An online survey with 1348 respondents was conducted between August 2020 and October 2021 in China using a contingent valuation (CV) method. Respondents perceived the landscape benefits related to mental health to be higher than those related to physical and social health. The perception of landscape health benefits positively affected WTP and the WTP value of ROS. Residents' monthly income was a significant influencing factor for WTP and the latter's value. For individuals with positive WTP, the average annual WTP for ROS was CNY 68.98 (USD 10.81), while for all the respondents, the estimated mean annual WTP for ROS was CNY 91.75 (USD 14.38). Moreover, the estimated WTP for plants was the highest, whereas the WTP for activity spaces was estimated as the lowest. These findings may improve city planners' and community managers' understanding of the perceived value of residential landscapes among the public and help them make effective decisions to build healthy communities.

Predicting the effect of street environment on residents' mood states in large urban areas using machine learning and street view images.

BACKGROUND: Researchers have demonstrated that the built environment is associated with mental health outcomes. However, evidence concerning the effects of street environments on mood in fast-growing Asian cities is scarce. Traditional questionnaires and interview methods are labor intensive and time consuming and pose challenges for accurately and efficiently evaluating the impact of urban-scale street environments on mood. OBJECTIVE: This study aims to use street view images and machine learning methods to model the impact of street environments on mood states in a large urban area in Guangzhou, China, and to assess the effect of different street view elements on mood. METHODS: A total of 199,754 street view images of Guangzhou were captured from Tencent Street View, and street elements were extracted by pyramid scene parsing network. Data on six mood state indicators (motivated, happy, positive-social emotion, focused, relaxed, and depressed) were collected from 1590 participants via an online platform called Assessing the Effects of Street Views on Mood. A machine learning approach was proposed to predict the effects of street environment on mood in large urban areas in Guangzhou. A series of statistical analyses including stepwise regression, ridge regression, and lasso regression were conducted to assess the effects of street view elements on mood. RESULTS: Streets in urban fringe areas were more likely to produce motivated, happy, relaxed, and focused feelings in residents than those in city center areas. Conversely, areas in the city center, a high-density built environment, were more likely to produce depressive feelings. Street view elements have different effects on the six mood states. "Road" is a robust indicator positively correlated with the "motivated" indicator and negatively correlated with the "depressed" indicator. "Sky" is negatively associated with "positive-social emotion" and "depressed" but positively associated with "motivated". "Building" is a negative predictor for the "focused" and "happy" indicator but is positively related to the "depressed" indicator, while "vegetation" and "terrain" are the variables most robustly and positively correlated with all positive moods. CONCLUSION: Our findings can help urban designers identify crucial areas of the city for optimization, and they have practical implications for urban planners seeking to build urban environments that foster better mental health.

Factors Affecting Perceived Health Benefits and Use Behaviors in Urban Green Spaces During the COVID-19 Pandemic in Southern China Megacities.

Background: The COVID-19 pandemic has alienated people from urban green spaces (UGSs) that have various health outcomes for humans. However, little is known about the influential factors of perceived health benefits and use behaviors in UGSs during the COVID-19 pandemic. This study aims to explore the key factors that influence perceived health benefits and use behaviors in UGSs and to assess the mediating role of place attachment in relationships during the COVID-19 pandemic in Chinese megacities. Methods: We conducted an online questionnaire survey from December 2020 to March 2021 in Guangzhou and Shenzhen, China. Six multiple regression models were constructed to investigate the main factors by which UGSs influence citizens' perceived health benefits and use behaviors. Four mediation models were established using the structural equation modeling (SEM) method to explore the mediating effect of place attachment. Results: A total of 628 questionnaires were included in the analysis. The results revealed that some UGS components (green space access, maintenance, and soundscape) significantly affected perceived health benefits for citizens (physical, mental, and social health) during the COVID-19 pandemic. Conversely, use behaviors (frequency of visits, duration of visits, and activity intensity) were mainly affected by the sociodemographic context but less affected by UGS components. In addition, UGS components were found to significantly predict place attachment, which in turn influenced the perceived health benefits, frequency, and duration of visits. Conclusions: This study distinguished the key factors that affect perceived health benefits and use behaviors during the COVID-19 pandemic: green space access, maintenance, soundscape, and sociodemographic characteristics. Place attachment still needs to be considered when discussing how to encourage citizens to visit UGSs during the pandemic. These findings provide implications for policymakers and landscape planners regarding design and management measures for UGSs that are conducive to coping with pandemics.

Impact of Perception of Green Space for Health Promotion on Willingness to Use Parks and Actual Use among Young Urban Residents.

Promoting the use of green space is a fundamental way to improve physical and mental health and to enhance the quality of life of urban residents. In response to increasing demand for green space in cities, the impact of perception of green space for health promotion on willingness to use parks and actual use among young urban residents was investigated in this study. A total of 1135 young residents (ages 18-35) in three cities in China were surveyed by online questionnaire. A group of multiple regression models was constructed to investigate the influencing perception factors of participants' willingness to use parks and actual use. The results revealed that the young residents' perception of green space components for health promotion (green space access, types, sizes, plants, water, sensory features, microclimate environments and amenity facilities) had a greater effect on their willingness to use parks and to promote health, while it was less influential with respect to their actual park use behavior (frequency and duration). Among these variables, green space access is a critical concern for willingness to use toward parks. The disparities of perception of green space for health promotion effect on willingness to use a park and actual use provide a better understanding of the psychological factors affecting park use among young residents. The findings also provided some implications for public health policymakers, urban planners and landscape architects in designing parks to encourage visitation by young people.

Serial Mediation of Environmental Preference and Place Attachment in the Relationship between Perceived Street Walkability and Mood of the Elderly.

Urban streets are important public spaces for daily activities that play a crucial role in promoting health in the elderly. The purpose of this study was to investigate the association between perceived street walkability and mood in the elderly, and specifically, the mediating effect of environmental preference and place attachment. We surveyed a total of 269 elderly residents from six streets in Guangzhou, China. We collected assessments of the street environments, environmental preferences, place attachment, and mood status from the elderly. A serial multiple mediator model was constructed using the structural equation modeling method. The results showed that the perceived street walkability was sequentially associated first with an increased level of place attachment (ß = 0.798, SE = 0.358, p < 0.000) and then environmental preference (ß = 0.191, SE = 0.033, p = 0.038), which was in turn related to improvement of positive mood in the elderly (ß = 0.595 SE = 0.341, p < 0.000). Environmental preference alone was found to be significantly associated with positive mood (ß = 0.595, SE = 0.341, p < 0.000), while no significant effect of place attachment was found when considered individually (ß = -0.075, SE = 0.089, p = 0.395). These findings provide a greater understanding of the possible mechanism through which street environment impacts mood in the elderly. Therefore, when promoting the emotional experience of the elderly, we might consider not only physical environment factors but also psychological conditions in street environments.