Risk assessment for precise intervention of COVID-19 epidemic based on available big data and spatio-temporal simulation method: Empirical evidence from different public places in Guangzhou, China.

Risk assessment of the intra-city spatio-temporal spreading of COVID-19 is important for providing location-based precise intervention measures, especially when the epidemic occurred in the densely populated and high mobile public places. The individual-based simulation has been proven to be an effective method for the risk assessment. However, the acquisition of individual-level mobility data is limited. This study used publicly available datasets to approximate dynamic intra-city travel flows by a spatio-temporal gravity model. On this basis, an individual-based epidemic model integrating agent-based model with the susceptible-exposed-infectious-removed (SEIR) model was proposed and the intra-city spatio-temporal spreading process of COVID-19 in eleven public places in Guangzhou China were explored. The results indicated that the accuracy of dynamic intra-city travel flows estimated by available big data and gravity model is acceptable. The spatio-temporal simulation method well presented the process of COVID-19 epidemic. Four kinds of spatial-temporal transmission patterns were identified and the pattern was highly dependent on the urban spatial structure and location. It indicated that location-based precise intervention measures should be implemented according to different regions. The approach of this research can be used by policy-makers to make rapid and accurate risk assessments and to implement intervention measures ahead of epidemic outbreaks.

Geographic Ecological Momentary Assessment (GEMA) of environmental noise annoyance: the influence of activity context and the daily acoustic environment.

BACKGROUND: Noise annoyance is considered to be the most widespread and recognized health effect of environmental noise. Previous research is mostly based on the static study of residential environmental noise, but few studies have focused on the effects of noise exposure in different activity contexts on real-time annoyance. The two deficiency are that they neglect the influence of activity context besides residence and fail to reflect the difference of time-scale effect of noise influence. METHODS: Using portable noise and air sensors, GPS-equipped mobile phones, questionnaire survey, and geographic ecological momentary assessment (GEMA), this paper measured the environmental noise and real-time noise annoyance of participants at different activity places. Hierarchical logistic regression models were used to examine the effects of environmental noise on people's real-time annoyance. The paper further considered the influence of the geographic context of the activity places and daily acoustic environment on participants' real-time annoyance. Further, a nonlinear regression model was constructed using Random Forest to further examine the nonlinear relationship between environmental noise and real-time annoyance. RESULTS: The results showed that: (1) the average cumulative equivalent sound level during was 55 dB (A) when the participants responded to the EMA surveys; (2) Only the temperature of activity places had an influence on momentary annoyance and the higher the temperature, the more likely participants were annoyed; (3) Participants with higher perception of noise pollution in residential communities were more likely to be annoyed. However, participants with higher daily exposure to noise were less likely to feel annoyed; (4) The threshold value of the effect of noise on real-time annoyance was 58 dB (A) to 78 dB (A). CONCLUSIONS: These findings can guide the development of urban planning and environmental noise standards and also provide a reference for noise barrier requirements for different activity places.

The association between spatial access to physical activity facilities within home and workplace neighborhoods and time spent on physical activities: evidence from Guangzhou, China.

BACKGROUND: Urban residents from the developing world have increasingly adopted a sedentary lifestyle and spend less time on physical activities (PA). Previous studies on the association between PA facilities and individuals' PA levels are based on the assumption that individuals have opportunities to use PA facilities within neighborhoods all day long, ignoring the fact that their willingness and opportunities to use nearby facilities depend on how much discretionary time (any time when people have a choice what to do) they have. Further, scant attention has been paid to the influence of PA facilities within both residential and workplace neighborhoods in the dense urban context. To address the above research gaps, this study investigated the links between the spatial access to PA facilities within home/workplace neighborhoods and time spent on PA among working adults, focusing on whether results were different when different measures of accessibility were used and whether participants' discretionary time over a week affected their time spent on PA. METHOD: This study used data from a questionnaire survey (n = 1002) in Guangzhou between June and July 2017 and point of interest (POI) data from online mapping resources. Outcome variables included the amount of time spent on physical activity/moderate and vigorous intensity physical activity (PA/MVPA) over the past week. Home/workplace neighborhoods were measured as different distance buffers (500 m circular buffers, 1000 m circular buffers, and 1080 m network buffers) around each respondent's home/workplace. Spatial access to PA facilities was measured using two indicators: the counts of PA facilities and proximity to PA facilities within home/workplace neighborhoods. The amount of discretionary time was calculated based on activity log data of working day/weekend day from the Guangzhou questionnaire survey, and regression models were used to examine relationships between the spatial access of PA facilities, the time spent on PA/MVPA, and the amount of discretionary time, adjusted for covariates. Associations were stratified by gender, age, education, and income. RESULTS: Using different measures of accessibility (the counts of and proximity to PA facilities) generated different results. Specifically, participants spent more time on PA/MVPA when they lived in neighborhoods with more PA facilities and spent more time on MVPA when worked in closer proximity to PA facilities. A larger amount of discretionary time was associated with more time spent on PA/MVPA, but it did not strengthen the relationship between access to PA facilities and PA/MVPA time. In addition, relationships between access to PA facilities and PA levels varied by gender, age, education, and income. CONCLUSION: This study contributes to the knowledge of PA-promoting environments by considering both the home and workplace contexts and by taking into account the temporal attributes of contextual influences. Policymakers and urban planners are advised to take into account the workplace context and the temporal variability of neighborhood influences when allocating public PA facilities and public spaces.

Impact of green space exposure on blood pressure in Guangzhou, China: Mediation by air pollution, mental health, physical activity, and weight status.

Green space exposure has been inversely associated with blood pressure (BP) levels and hypertension risk. However, empirical evidence on the underlying mechanisms are lacking. This study examined the association of green space exposure with BP and hypertension, and assessed the mediating effects by air pollution, mental health, physical activity, and weight status. Survey data from 719 adults, who lived in Guangzhou (China) in 2016, were used. Three area-level green space indicators, including network distance to the nearest park, percentage of green space and Normalized Difference Vegetation Index within a 1 km Euclidean buffer around residence and workplace, were calculated and linked to individual-level BP measurements. Structural equation models were applied to estimate the direct and indirect associations of the various green space indicators on systolic BP (SBP), diastolic BP (DBP), and hypertension, respectively. After adjusting for multiple covariates, longer network distance to green space was directly associated with higher SBP. Compared to the reference group (0-500m), the differences were 0.11 mmHg (95% CI = 0.03 to 0.19, P = 0.006) for 500-1000m, 0.03 mmHg (95% CI = -0.05 to 0.12, P = 0.45) for 1000-1500m, and 0.16 mmHg (95% CI = 0.09 to 0.23, P < 0.001) for >1500m, respectively. The overall and direct associations were significant for all three indicators (distance or density) with or without considering workplace exposure. The association between network distance to green and SBP was partially (18.4%, 95% CI = 0-42.1%) mediated by mental health. There was no statistical evidence that air pollution, physical activity, or weight status mediate the association. Secondary analyses for other indicators and other outcomes showed similar results. Both distance to green space and more green space around residence and workplace were associated with lower BP and lower risk of hypertension in adults living in a Chinese metropolitan. Mental health partly mediated the association.

Building a City with Low Noise Pollution: Exploring the Mental Health Effect Thresholds of Spatiotemporal Environmental Noise Exposure and Urban Planning Solution.

Urban noise pollution and health hazards have become serious social problems and challenges. Noise prevention and control is the most cost-effective health strategy. However, in urban planning and noise control, reliable evidence is still lacking on individual spatiotemporal environmental noise exposure and its mental health effects. This study used real-time noise exposure data and GPS trackers from 142 volunteers aged 18 to 60 years in Guangzhou, and further analyzed the differences in environmental noise exposure and its mental health impact thresholds under individual spatiotemporal behavior. The results showed that the noise exposure of residents under daily activities has obvious differences in time, space and place. Regarding the threshold relationship between noise exposure and mental health, noise exposure at night, work, personal affairs, travel and sleep activities, as well as at home and work had a threshold effect on residents' mental health. Noise thresholds were 60 dB, 60 dB, and about 34 dB at night, during work or at a workplace, and while sleeping, respectively. The optimal sound environment for personal affairs, traveling, and at home was around 50 dB, 55-70 dB, and 45 dB, respectively. The environmental noise exposure assessment and mental health impact threshold analysis based on the spatial and temporal activities of individuals will provide important reference for government management departments in planning and policy formulation.

The temporality of geographic contexts: Individual environmental exposure has time-related effects on mood.

Research on environmental exposure and its impacts on people's mood has attracted increasing attention. Most studies focus on the spatiality of geographic contexts, but they neglect the influence of temporality in the relationships between environments and mood. To this end, a survey was conducted in January 2019 in Guangzhou, China, and measured data (micro-environments, built environments, EMA records, GPS trajectories, and activity logs) covering a weekday were collected from 125 participants. Then, multiple linear regression models are employed to examine and compare the associations between environments and mood based on three possible types of temporal responses (cumulative response, momentary response, and time-lagged response). The results indicate that there are great differences in environmental mood effects based on different types of temporal responses. Specifically, (i) for three types of temporal responses, exposure to PM2.5 and noise have mood-blunting effects, whereas exposure to green spaces has mood-augmenting effects. (ii) For two types of temporal responses, higher temperature (in winter) may positively influence individual mood based on cumulative and time-lagged response, and higher POI density can positively affect mood based on cumulative and momentary response. (iii) Relative humidity may not have time-related effects on mood. Although all three types of temporal responses are observed in this study, the most significant manifestation is momentary response. These findings not only enrich theoretical research on environmental mood effects and temporality, but also inform the practice of more refined and humanistic urban planning, environmental governance, and public services.

Inside and outside the neighborhood: Short-term and long-term subjective well-being by geographical context.

The value of linking urban environment and subjective well-being (SWB) is now well recognized. But whether the geographical context inside and outside the neighborhood has differential influence on long- and short-term SWB remains unclear. Based on the activity perspective, we used survey data from Guangzhou, China, integrating GPS data, portable environmental sensors data to analyze time-weighted and real-time geographical context inside and outside the neighborhood on long- and short-term SWB. The results show that SWB is not only influenced by the neighborhood environment, but also the geographical context outside the neighborhood. Time-weighted geographical environment inside the neighborhood has a higher impact and explanatory ability on long-term SWB, while real-time geographical environment outside the neighborhood has a higher impact and explanatory ability on short-term SWB. This study provides a new understanding for geographies of SWB through the extension of time and space, and also provides reference for more refined urban planning and governance in the future.

Association between immigrant concentration and mental health service utilization in the United States over time: A geospatial big data analysis.

Immigrants (foreign-born United States [US] citizens) generally have lower utilization of mental health services compared with US-born counterparts, but extant studies have not investigated the disparities in mental health service utilization within immigrant population nationwide over time. Leveraging mobile phone-based visitation data, we estimated the average mental health utilization in contiguous US census tracts in 2019, 2020, and 2021 by employing two novel outcomes: mental health service visits and visit-to-need ratio (i.e., visits per depression diagnosis). We then investigated the tract-level association between immigration concentration and mental health service utilization outcomes using mixed-effects linear regression models that accounted for spatial lag effects, time effects, and covariates. This study reveals spatial and temporal disparities in mental health service visits and visit-to-need ratio among different levels of immigrant concentration across the US, both before and during the pandemic. Tracts with higher concentrations of Latin American immigrants showed significantly lower mental health service utilization visits and visit-to-need ratio, particularly in the US West. Tracts with Asian and European immigrant concentrations experienced a more significant decline in mental health service utilization visits and visit-to-need ratio from 2019 to 2020 than those with Latin American concentrations. Meanwhile, in 2021, tracts with Latin American concentrations had the least recovery in mental health service utilization visits. The study highlights the potential of geospatial big data for mental health research and informs public health interventions.

Long-Term Residential Environment Exposure and Subjective Wellbeing in Later Life in Guangzhou, China: Moderated by Residential Mobility History.

With rapid global urbanization, the importance of understanding relationships between the changing environment and wellbeing is being increasingly recognized. However, there is still a lack of understanding of how long-term residential environment exposure affects subjective wellbeing under the dual changes of geographical environment and residential location. Based on a survey of the elderly (people over 60 years old) in Guangzhou, China, this study analyzes the effect of long-term residential environment exposure over 25 years on subjective wellbeing in later life in the context of residential mobility. The study found that subjective wellbeing in later life is not only related to the current residential environment but also the cumulative exposure to the long-term residential environment. The relationship between long-term residential environment exposure and subjective wellbeing in later life tends to be stable with the increase of cumulative time, especially the cumulative years over 15 years. Considering the importance of residential mobility history, the study further analyzes the moderating effects of relocation frequency and residential location. Relocation frequency can strengthen the positive effect of residential environment on subjective wellbeing and weaken the negative effect of residential environment on subjective wellbeing, which confirms the existence of residential self-selection. In addition, the direction of effect of residential environment on residents who move between living in the urban center and the periphery is consistent with that of residents who have always lived in the urban center, while the effects of the residential environment on residents who have always lived in the urban center and those who have always lived in the urban periphery are related in different directions. The conclusion of this study can provide guidance for individuals' residential choice and governance of the urban environment to improve wellbeing.

The spatially heterogeneous and double-edged effect of the built environment on commuting distance: Home-based and work-based perspectives.

Rich literature has examined the impact of the built environment on commuting distance. Linear models assume that the influence of the built environment is spatially homogeneous. However, given the spatial heterogeneity of urban space, conclusions might be different or even be contrary. The influence of the built environment might also be different by home and work locations. To explore the spatially heterogeneous effect of the built environment from both home-based and work-based perspectives, this study applied large-scale cellular cellphone data in Guangzhou, China. Commuting was measured by decay parameters of probabilistic distributions of commuting distances. Geographically weighted regression models were applied to examine the spatially heterogeneous effect, differentiated by home-based and work-based perspectives. Results confirmed that the impact of the built environment on commuting distance is spatially heterogeneous. The urban space is classified into clusters of central areas, inner suburbs, and outer suburbs. Results also revealed the double-edged effect of the built environment. Residential population, recreation facilities, and mixed development are residence-attractive factors that increase the home-based commuting distance and decrease the work-based commuting distance. Work population and transport facilities are work-attractive factors that decrease home-based commuting distance and increase work-based commuting distance. The results further provide evidence to support area-based policies in urban planning practice.

Social Group Differences in Influencing Factors for Chinese Urban Residents' Subjective Well-Being: From the Perspective of Social Stratification.

With the great pressure of modern social life, the problem of residents' subjective well-being has attracted scholars' attention. Against the background of institutional transformation, China has a special social stratification structure. The socio-economic resources and living needs of different social classes are different, resulting in differences in the level of subjective well-being and the influencing factors for this. Taking Guangzhou as an example, based on the data of a household survey conducted in 2016, this paper obtains the social hierarchical structure through two-step clustering, and explores the differences between influencing factors for subjective well-being using multiple linear regression models. The clustering results divided Guangzhou urban residents into four classes: retirees, white-collar workers outside the system, manual workers and white-collar workers inside the system. The subjective well-being of white-collar workers inside the system and manual workers is high. The subjective well-being of white-collar workers outside the system is below the average value, and retirees have poor subjective well-being. The results of the regression analysis show that the subjective well-being of all social classes could be improved by active participation in fitness exercises, harmonious neighborhood relationships and a central residential location. Health-related factors such as physical health, sleeping time and density of neighborhood medical facilities, have a significant impact on manual workers' subjective well-being. An increase in the density of neighborhood leisure facilities could help to improve the subjective well-being of white-collar workers outside the system. However, this would inhibit the subjective well-being of white-collar workers within the system. By revealing the differences in influencing factors for different social groups' subjective well-being, the research conclusions could provide a reference for the formulation of targeted policies and measures to improve residents' subjective well-being in urban China.

Nonlinear Effects of the Neighborhood Environments on Residents' Mental Health.

In the context of rapid urbanization and the "Healthy China" strategy, neighborhood environments play an important role in improving mental health among urban residents. While an increasing number of studies have explored the linear relationships between neighborhood environments and mental health, much remains to be revealed about the nonlinear health effects of neighborhood environments, the thresholds of various environmental factors, and the optimal environmental exposure levels for residents. To fill these gaps, this paper collected survey data from 1003 adult residents in Guangzhou, China, and measured the built and social environments within the neighborhoods. The random forest model was then employed to examine the nonlinear effects of neighborhood environments on mental health, evaluate the importance of each environmental variable, as well as identify the thresholds and optimal levels of various environmental factors. The results indicated that there are differences in the importance of diverse neighborhood environmental factors affecting mental health, and the more critical environmental factors included greenness, neighborhood communication, and fitness facility density. The nonlinear effects were shown to be universal and varied among neighborhood environmental factors, which could be classified into two categories: (i) higher exposure levels of some environmental factors (e.g., greenness, neighborhood communication, and neighborhood safety) were associated with better mental health; (ii) appropriate exposure levels of some environmental factors (e.g., medical, fitness, and entertainment facilities, and public transport stations) had positive effects on mental health, whereas a much higher or lower exposure level exerted a negative impact. Additionally, this study identified the exact thresholds and optimal exposure levels of neighborhood environmental factors, such as the threshold (22.00%) and optimal exposure level (>22.00%) of greenness and the threshold (3.80 number/km2) and optimal exposure level (3.80 number/km2) of fitness facility density.

Assessing personal travel exposure to on-road PM2.5 using cellphone positioning data and mobile sensors.

PM2.5 pollution imposes substantial health risks on urban residents. Previous studies mainly focused on assessing peoples' exposures at static locations, such as homes or workplaces. There has been a scarcity of research that quantifies the dynamic PM2.5 exposures of people when they travel in cities. To address this gap, we use cellphone positioning data and PM2.5 concentration data collected from smart sensors along roads in Guangzhou, China, to assess personal travel exposure to on-road PM2.5. First, we extract the trips of cellphone users from their trajectories and use the shortest path algorithm to calculate their travel routes on the road network. Second, the travel exposure of each user is estimated by associating their movement patterns with PM2.5 concentrations on roads. The result shows that most users' average travel exposures per hour fall within the range of 20 ug/m3 to 75 ug/m3. Travel exposure varies across users, and 54.0% of users experience low travel exposure throughout the day, 25.5% of users experience high travel exposure in the evening, and 20.5% of users experience high travel exposure in the afternoon. Furthermore, the impacts of on-road PM2.5 on urban populations are uneven across roads. More attention should be given to roads with high PM2.5 concentrations and traffic flows in each period, such as Huan Shi Middle Road in the morning, Inner Ring Road in the afternoon, and Xinjiao Middle Road in the evening. The findings in this study can contribute to a more in-depth understanding of the relationship between air pollution and the travel activities of urban populations.

Associations between Objective and Subjective Housing Status with Individual Mental Health in Guangzhou, China.

Housing is an important social determinant of mental health. However, few studies simultaneously measure the objective housing status (i.e., housing tenure, living space, housing conditions, and housing stability) and subjective housing status (i.e., housing satisfaction) as well as examine their effects on people's mental health (i.e., stress, anxiety, and depression). Thus, using a sample size of 1003 participants by two-stage random sampling survey in Guangzhou, China, this study applies multivariate ordinary least square regression models to comprehensively explore and compare the associations between objective and subjective housing status with mental health, and then analyze the moderating effects of subjective housing status on the relationships between objective housing status and mental health. The findings suggest that there are significant differences in people's mental health based on different housing status. The subjective housing status can better explain the variances in mental health than objective housing status. Also, subjective housing status may partly mitigate the adverse impacts of objective housing disadvantages on some aspects of an individual's mental health. Therefore, housing improvement policies and public health initiatives should be designed based on a comprehensive account of objective and subjective housing characteristics as well as their influences on specific aspects of mental health.

Optimizing Spatial Allocation of COVID-19 Vaccine by Agent-Based Spatiotemporal Simulations.

Optimizing allocation of vaccine, a highly scarce resource, is an urgent and critical issue during fighting against on-going COVID-19 epidemic. Prior studies suggested that vaccine should be prioritized by age and risk groups, but few of them have considered the spatial prioritization strategy. This study aims to examine the spatial heterogeneity of COVID-19 transmission in the city naturally, and optimize vaccine distribution strategies considering spatial prioritization. We proposed an integrated spatial model of agent-based model and SEIR (susceptible-exposed-infected-recovered). It simulated spatiotemporal process of COVID-19 transmission in a realistic urban context. Individual movements were represented by trajectories of 8,146 randomly sampled mobile phone users on December 28, 2016 in Guangzhou, China, 90% of whom aged 18-60. Simulations were conducted under seven scenarios. Scenarios 1 and 2 examined natural spreading process of COVID-19 and its final state of herd immunity. Scenarios 3-6 applied four vaccination strategies (random strategy, age strategy, space strategy, and space & age strategy), and identified the optimal vaccine strategy. Scenario 7 assessed the most appropriate vaccine coverage. The results demonstrates herd immunity is heterogeneously distributed in space, thus, vaccine intervention strategies should be spatialized. Among four strategies, space & age strategy is substantially most efficient, with 7.7% fewer in attack rate and 44 days longer than random strategy under 20% vaccine uptake. Space & age strategy requires 30%-40% vaccine coverage to control the epidemic, while the coverage for a random strategy is 60%-70% as a comparison. The application of our research would greatly improves the effectiveness of the vaccine usability.

How Does Crime-Specific Victimization Impact Fear of Crime in Urban China? The Role of Neighborhood Characteristics.

Past research has failed to find consistent relationships between criminal victimization and fear of crime. Except for neighborhood disorder and crime rate, few studies have examined whether other neighborhood conditions matter the victimization-fear relationship. Using survey data in Guangzhou neighborhoods, the present analysis employs multinomial logistic regression models to examine whether neighborhood characteristics moderate the relationship between violent victimization and fear of violence, and between burglary victimization and fear of burglary, separately. Some aspects of the neighborhood environment do differentially influence victims' and non-victims' fear levels. Besides verifying the interaction effect of neighborhood disorder and victimization, the present study finds that neighborhood policing alleviates the harmful effect of violent victimization on fear, while collective efficacy fosters the harmful effect of burglary victimization on fear. This paper underscores the significance of the social context of urban China in explaining the interplay of neighborhood characteristics and victimization on fear of crime.

Assessing individual environmental exposure derived from the spatiotemporal behavior context and its impacts on mental health.

Research on the associations between environmental exposures and mental health has attracted considerable attention. Most studies to date have mainly estimated environmental health effects based on static geographic contexts (e.g., residential neighborhoods, administrative units), ignoring the dynamic nature of individual spatiotemporal behavior, which may lead to unreliable results. To address this limitation, this study collects survey data from 1003 adults in Guangzhou, China. Then, it delineates dynamic geographic context to capture individual daily activity and travel and assesses individual exposure to environmental factors derived from the home buffer (HB) and the time-weighted activity and travel buffer (TATB). Finally, multiple linear regression models are used in this paper to examine and compare the relationships between individual environmental exposure and mental health based on the HB and TATB. The results of this study indicate that there are great differences in individual environmental exposure levels based on the HB and TATB. The explanatory power of the environmental factors obtained from the TATB on mental health is greater than that derived from the HB. Specifically, exposures to some environmental factors (i.e., green space coverage, blue space coverage, fitness facility density, and recreational facility density) derived from the TATB have mental health-promoting effects, while exposures to the other environmental factors (i.e., public transit station density) have mental health-constraining effects. These findings enrich our knowledge of spatiotemporal behavior and the effects of the dynamic contextual environment on mental health, as well as provide valuable implications for urban planning and public health service.

Assessing the Impact of Street-View Greenery on Fear of Neighborhood Crime in Guangzhou, China.

Previous literature has examined the relationship between the amount of green space and perceived safety in urban areas, but little is known about the effect of street-view neighborhood greenery on perceived neighborhood safety. Using a deep learning approach, we derived greenery from a massive set of street view images in central Guangzhou. We further tested the relationships and mechanisms between street-view greenery and fear of crime in the neighborhood. Results demonstrated that a higher level of neighborhood street-view greenery was associated with a lower fear of crime, and its relationship was mediated by perceived physical incivilities. While increasing street greenery of the micro-environment may reduce fear of crime, this paper also suggests that social factors should be considered when designing ameliorative programs.

Relationship between Long-Term Residential Green Exposure and Individuals' Mental Health: Moderated by Income Differences and Residential Location in Urban China.

Environmental health effects during urbanization have attracted much attention. However, knowledge is lacking on the relationship between long-term cumulative residential environment and health effects on individuals during rapid transformations in urban physical and social space. Taking Guangzhou, China, as a case example, this study analyzed the relationship between long-term exposure to green environments and residents' mental health under urban spatial restructuring. Based on a household survey in 2016, 820 residents who have lived in Guangzhou for more than 15 years were used as the sample. High-resolution remote sensing images were used to assess the long-term green exposure of residents. The results indicate that long-term green exposure in residential areas had a negative correlation with residents' mental health (p < 0.05), and the correlation was strongest for the cumulative green environment in the last five years. However, this significant effect was moderated by income and residential location. Green exposure had a positive relationship with mental health for low income groups, and a negative relationship for middle and high income groups. In addition, residents living farther away from the city center were likely to have fewer green environmental health benefits. Residential relocation in a rapidly urbanizing and transforming China has led to the continuous differentiation of residential green environments among different income groups, which has also caused different mental health effects from green exposure. It provides empirical evidence and theoretical support for policymakers to improve the urban environment and reduce environmental health disparities by considering social differences and residential location.

A comparative analysis of the impacts of objective versus subjective neighborhood environment on physical, mental, and social health.

Research on the relationship between neighborhood context and health outcome has attracted notable attention. However, few studies examine and compare the associations between the objective and subjective neighborhood environment and different dimensions of health. To this end, high-resolution remote sensing images and points-of-interest (POIs) data collected in Guangzhou, China, are used together with questionnaire survey data to measure the objective and subjective characteristics of the neighborhood environment. The sample includes 1029 adults selected from 34 communities in Guangzhou, China. Hierarchical linear modeling is then employed to analyze the associations between the objective and subjective neighborhood environment and three dimensions of health (physical health, mental health, and social health), as well as compare the relative strengths of and moderating mechanisms between these associations. The results indicate that significant variations in health outcomes are observed among neighborhoods, which can be explained by both personal attributes and the neighborhood environment. Although objective and subjective measures of the neighborhood environment are both linked to the three dimensions of health, physical health and social health are influenced more by objective measures, while mental health is affected more by subjective measures. Further, subjective measures have positive moderating effects on the relationship between objective measures and mental health but do not have significant moderating effects on the relationships between objective measures and physical and social health.