Associations between Urban Green Spaces and Health are Dependent on the Analytical Scale and How Urban Green Spaces are Measured

How did COVID-19 case distribution associate with the urban built environment? A community-level exploration in Shanghai focusing on non-linear relationship

Several associations between the built environment and COVID-19 case distribution have been identified in previous studies. However, few studies have explored the non-linear associations between the built environment and COVID-19 at the community level. This study employed the March 2022 Shanghai COVID-19 pandemic as a case study to examine the association between built-environment characteristics and the incidence of COVID-19. A non-linear modeling approach, namely the boosted regression tree model, was used to investigate this relationship. A multi-scale study was conducted at the community level based on buffers of 5-minute, 10-minute, and 15-minute walking distances. The main findings are as follows: (1) Relationships between built environment variables and COVID-19 case distribution vary across scales of analysis at the neighborhood level. (2) Significant non-linear associations exist between built-environment characteristics and COVID-19 case distribution at different scales. Population, housing price, normalized difference vegetation index, Shannon's diversity index, number of bus stops, floor-area ratio, and distance from the city center played important roles at different scales. These non-linear results provide a more refined reference for pandemic responses at different scales from an urban planning perspective and offer useful recommendations for a sustainable COVID-19 post-pandemic response.

A Global Meta-Analysis of the Effects of Greenspaces on COVID-19 Infection and Mortality Rates

The COVID-19 outbreak in 2020 resulted in rapidly rising infection rates with high associated mortality rates. In response, several epidemiological studies aimed to define ways in which the spread and severity of COVID-19 can be curbed. As a result, there is a steady increase in the evidence linking greenspaces and COVID-19 impact. However, the evidence of the benefits of greenspaces or greenness to human wellbeing in the context of COVID-19 is fragmented and sometimes contradictory. This calls for a meta-analysis of existing studies to clarify the matter. Here, we identified 621 studies across the world on the matter, which were then filtered down to 13 relevant studies for meta-analysis, covering Africa, Asia, Europe, and the USA. These studies were meta-analyzed, with the impacts of greenness on COVID-19 infection rate quantified using regression estimates whereas impacts on mortality rates were measured using mortality rate ratios. We found evidence of significant negative correlations between greenness and both COVID-19 infection and mortality rates. We further found that the impacts on COVID-19 infection and related mortality are moderated by year of publication, greenness metrics, sample size, health and political covariates. This clarification has far-reaching implications for policy development toward the establishment and management of green infrastructure for the benefit of human wellbeing.

Utilizing regression model to characterize the impact of urban green space features on the subjective well-being of older adults

Based on the background of rapid global ageing, research exploring urban green spaces and the subjective well-being of urban residents has become one of the key research interests. However, the evidence for assessing the real benefits of urban green spaces on the subjective well-being of older adults by comprehensively examining the features of urban green spaces is limited. We surveyed older urban green space users (n = 536) aged 60 years and older in Nanjing, China, and evaluated the impacts of spatial, green, and grey features of urban green spaces on older people's overall satisfaction with urban green spaces and subjective well-being. The results of the multiple linear regression model showed a strong association between the three types of urban green space features, overall satisfaction with urban green space, and subjective well-being of older adults. The study results indicated that the grey feature of urban green spaces emerged as the most influential factor (p = 0.004) among the three features of urban green spaces in relation to their effect on the subjective well-being of older adults. This implies that it is essential to focus on the importance of grey s of urban green spaces in the planning and design of urban green spaces for older adults' use of different urban green spaces and their sense of well-being. These results contribute to the development of healthy ageing policies and age-friendly urban green space management strategies in rapid ageing countries around the world.

How does multiscale greenspace exposure affect human health? Evidence from urban parks in the central city of Beijing

While the health benefits of exposure to urban greenspace have been widely discussed at different spatial scales, the comprehensive health effects of multiscale greenspace exposure are far from understood. There is a lack of quantified evidence when conducting cost-effective greenspace management practices for promoting human health and well-being. This study proposed a conceptual model that links objective and subjective greenspace exposure metrics at different spatial scales with self-rated health of residents. The model attempted to deconstruct and explore the associations between multiscale greenspace exposure and human health, and a cross-sectional study was conducted to examine the model. Taking urban parks in the central city of Beijing as case study area, the objective greenspace exposure metrics at both the site and subdistrict scales were spatial explicitly assessed, and the subjective exposure metrics and self-rated health status of 1017 respondents were obtained through questionnaire survey and spatial positioning. The results of multiple regression analyses and path analyses suggested that greenspace exposure metrics at both site and subdistrict scales were significantly associated with the respondents' self-rated health status, with the exposure metrics at the site scale being more important than those at the subdistrict scale in affecting human health. The contribution of urban parks to self-rated physical and mental health of respondents varied across spatial scales. Specifically, the aesthetic value of urban parks at site scale contributed the most to mental health by promoting respondents' resting behaviors in urban parks, and the density of urban parks at subdistrict scale had the most significant effects on self-rated physical health by increasing the usage frequency of urban parks. Findings of this study can contribute to understanding the complex associations between urban greenspace and human health from a multiscale perspective, and are also expected to provide quantified information for health-oriented urban greenspace planning and management practices.

Estimating changes in inequality of ecosystem services provided by green exposure: From a human health perspective

Ecosystem services provided by green spaces are closely related to human health, strongly supporting sustainable urban and territorial development. Urbanization has not only resulted in the reduction of green spaces but has also created inequalities in exposure. Inequitable green exposure creates disparities in residents' access to the ecosystem services provided by green spaces and can lead to significant health inequities. In this context, we first categorized green exposures into active and passive types based on their characteristics. Second, utilizing the benefit transfer method and Gini coefficient, we estimated the value and equity of ecosystem services offered by these green exposures around residences at the municipality level in Japan from 2000 to 2020, with a focus on human health implications. Finally, we explored the potential relationship between socioeconomics and ecosystem service inequity. Our findings reveal that: 1) ecosystem service value per capita and equity provided by green exposure are significantly different across municipalities; 2) although most municipalities show an upward trend in per capita ecosystem service value around residences, ecosystem service inequity increases significantly; and 3) ecosystem service inequity is related to the socioeconomic factors of municipalities and could be non-linear. The results of this study suggest that the government should adopt indicators related to the ecosystem services provided by green exposure during urban planning. While focusing on per-capita ecosystem services, they should also consider the equitable distribution of ecosystem services to promote sustainable urban health development.

Urban green, blue spaces and their joint effect are associated with lower risk of emotional and behavior problem in children and adolescents, a large population-based study in Guangzhou, China

Extensive research has been conducted on the impact of urban Green and blue spaces (GBS) on mental health. However, there is a dearth of studies examining the potential influence of GBS on Emotion and behavior problems (EBP) in youth populations. This study seeks to address this research gap by examining the association between GBS exposure and EBP in youths, utilizing a large population-based survey. Exposure indicators were derived for each participant, taking into account the 1-m resolution land coverage percentage measurements at their residential and school locations, with buffer sizes of 500m and 800m. The study employed the parent-reported Strengths and Difficulties Questionnaire (SDQ) as a measurement to EBP. To investigate this relationship, a Poisson linear mixed-effects model with comprehensive adjustment was utilized. Stratified analyses were conducted, taking into account demographic variables, while sensitivity analyses were performed to evaluate the reliability of the findings. The primary analysis encompassed a sample of 172,490 individuals, with an average age of 10.2 (standard deviation = 2.99), of whom 55.8% were male. Among young individuals residing within a 500-m radius of residential green spaces (GS), those in the second and third tertiles experienced a 5.0% and 7.6% decrease in the risk of developing total difficulties respectively, compared to those in the first tertile. Exposure to blue spaces (BS) around the residence yielded comparable results, with an AOR of 0.896 (95% CI: 0.866, 0.928) for the second tertile and an AOR of 0.991 (95% CI: 0.879, 0.943) for the third tertile, compared to the first tertile. The decrease in EBPs may also be linked to the joint effect of GS and BS. Young individuals were exposed to GS or BS, as well as the higher level of GS in conjunction with comparable BS, exhibited an inverse correlation with self-reported EBPs.

Geographic uncertainties in external exposome studies: A multi-scale approach to reduce exposure misclassification

BACKGROUND

Many studies on environment-health associations have emphasized that the selected buffer size (i.e., the scale of the geographic context when exposures are assigned at people's address location) may affect estimated effect sizes. However, there is limited methodological progress in addressing these buffer size-related uncertainties.

AIM

We aimed to 1) develop a statistical multi-scale approach to address buffer-related scale effects in cohort studies, and 2) investigate how environment-health associations differ between our multi-scale approach and ad hoc selected buffer sizes.

METHODS

We used lacunarity analyses to determine the largest meaningful buffer size for multiple high-resolution exposure surfaces (i.e., fine particulate matter [PM2.5], noise, and the normalized difference vegetation index [NDVI]). Exposures were linked to 7.7 million Dutch adults at their home addresses. We assigned exposure estimates based on buffers with fine-grained distance increments until the lacunarity-based upper limit was reached. Bayesian Cox model averaging addressed geographic uncertainties in the estimated exposure effect sizes within the exposure-specific upper buffer limits on mortality. Z-tests assessed statistical differences between averaged effect sizes and those obtained through pre-selected 100, 300, 1200, and 1500 m buffers.

RESULTS

The estimated lacunarity curves suggested exposure-specific upper buffer size limits; the largest was for NDVI (960 m), followed by noise (910 m) and PM2.5 (450 m). We recorded 845,229 deaths over eight years of follow-up. Our multi-scale approach indicated that higher values of NDVI were health-protectively associated with mortality risk (hazard ratio [HR]: 0.917, 95 % confidence interval [CI]: 0.886-0.948). Increased noise exposure was associated with an increased risk of mortality (HR: 1.003, 95 % CI: 1.002-1.003), while PM2.5 showed null associations (HR:0.998, 95 % CI: 0.997-1.000). Effect sizes of NDVI and noise differed significantly across the averaged and prespecified buffers (p < 0.05).

CONCLUSIONS

Geographic uncertainties in residential-based exposure assessments may obscure environment-health associations or risk spurious ones. Our multi-scale approach produced more consistent effect estimates and mitigated contextual uncertainties.

Spatially heterogeneous associations between the built environment and objective health outcomes in Japanese cities

The built environment is a structural determinant of health. Here we reveal spatially heterogeneous associations of built environment indicators with objective health outcomes (morbidity) by combining a random forest (RF) approach and a multiscale geographically weighted (MGWR) regression method. Using data from six Japanese cities, we found that the ratio of morbidity has obvious spatial agglomerations. The mixed land-use diversity with 1000 m buffer, distance to hospital, proportion of park area with 300 m buffer, and house price with 2000 m buffer, negatively affect health outcomes at all locations. For most locations, high PM2.5 or high floor area ratio with 2000 m buffer are linked to a high ratio of morbidity. Our findings support the use of such data for long-term urban and health planning. We expect our study to be a starting point for further research on spatially heterogeneous associations of the built environment with comprehensive health outcomes.

Assessment of urban flood susceptibility and role of urban green space (UGS) on flooding susceptibility using GIS-based probabilistic models

With rapid urbanization, the green space in urban areas is replaced with impervious built-up areas, which increases the frequency of urban floods. Kamrup Metropolitan District, Assam, is near the Brahmaputra and is highly prone to urban flooding. The present study aims to develop the urban flood susceptibility index (FSI) and to analyze the role of urban green space (UGS) as a nature-based solution (NBS) for urban flood susceptibility. Two types of flooded urban areas are observed using a two-stage cluster analysis. A GIS-based urban FSI is developed using logistic regression (LR), frequency ratio (FR), Shannon entropy (SE), certainty factor (CF), and weight of evidence (WoE) models, and variation of FSI is assessed for different UGS areas. According to the area under curve (AUC), the performance of all five models falls under the good to excellent class. The average UGS ratio for non-flooded is higher than for flooded areas, and with an increase in the area of UGS, the flooding probability decreases for all the models. The findings of the present study emphasize the importance of UGS and can be used for effective urban flood risk mitigation and management planning.

Resilience and green spaces: Association with stress among contact centre workers in the Philippines

ISSUE ADDRESSED

Philippine contact centres are rife with factors that contribute to work-related stress; health promotion strategies are needed to mitigate the impacts. With a transactional framework with the environment, this study examined the relationship of stress with resilience and the presence of urban green spaces (UGS) in the environment, while accounting for individual characteristics (ie, age, household income, exercise frequency).

METHODS

Participants include employees (Stage 1 N = 186; Stage 2 N = 89) from six contact centres in the capital region of the Philippines. A two-stage online survey included standardised instruments to measure stress (10-item Perceived Stress Scale) and resilience (Connor-Davidson Resilience Scale), customised questions to gather demographic information and probe on participants' insights. Google Earth Pro was used for satellite mapping of UGS, followed by on-site ocular inspection.

RESULTS

Participants' average stress level was categorised as high; primary stressors included client demands and workload. The objectively measured percentages of UGS in the study sites' vicinity were categorised as low. Participants found UGS visible after careful observation, and majority were aware of UGS in their workplace vicinity. Resilience, household income and awareness of UGS in the vicinity significantly predicted stress levels.

CONCLUSION

Contact centre workers experienced high stress levels and their workplaces had little accessible UGS. Resilience, household income and awareness of UGS are significant contributors to stress levels. SO WHAT?: Health promotion in Philippine contact centres could consider strategies that include building resilience, enhancing income security and promoting the awareness of UGS within the workplace vicinity.

Association between Low Urban Neighborhood Greenness and Hypertensive Disorders of Pregnancy

OBJECTIVE

Urban neighborhood greenness is associated with greater cardiovascular health in the general population, and with better pregnancy and neonatal outcomes. Hypertension in pregnancy is a leading cause of maternal mortality and long-term cardiovascular morbidity and mortality in women. We sought to examine the association between greenness and hypertensive disorders of pregnancy.

STUDY DESIGN

This study is a secondary analysis of a prospective cohort study of 1,943 women who received prenatal care from December 2013 to December 2016 at a single, urban, and tertiary academic medical center in Philadelphia, PA. Greenness measure was quantified via residential tree canopy cover within circumferential buffers of 100- and 500-meter radii around participants' homes. Associations between greenness and hypertensive disorders of pregnancy (defined as gestational hypertension or preeclampsia) were estimated by using multilevel logistic regression accounting for maternal sociodemographic information (race-ethnicity, insurance status, and age) medical history (diabetes, body mass index, smoking history, and parity), neighborhood deprivation index, and including 1,225 Philadelphia residents for whom key exposure and outcome data were available.

RESULTS

At baseline, the participants' mean (SD) age was 27.5 (5.9) years, (range: 14-44 years). The majority of participants were non-Hispanic Black (857, 70.2%). Participants with less residential tree canopy cover were significantly more likely to have hypertensive disorders of pregnancy. The multivariable-adjusted odds ratio of hypertensive disorders of pregnancy among participants with less than 10% compared with those with greater than 30% tree canopy cover was 2.14 (95% confidence interval [CI]: 1.11-4.15) within 100-meter buffer.

CONCLUSION

In our cohort, greenness was associated with lower hypertensive disorders of pregnancy odds. Our findings add to evidence that greenness may confer health benefits and warrant further investigations in identifying whether there is a causal pathway through which greenness may be protective against hypertensive disorders of pregnancy.

KEY POINTS

· Low residential tree canopy is associated with increased risk of hypertensive disorders of pregnancy. · 100-meter buffers are most sensitive in identifying associations between tree canopy and HDP risk. · The role of greenness against hypertensive disorders of pregnancy should be further studied experimentally.

Association between urban green space and postpartum depression, and the role of physical activity: a retrospective cohort study in Southern California

Background

Little research exists regarding the relationships between green space and postpartum depression (PPD). We aimed to investigate the relationships between PPD and green space exposure, and the mediating role of physical activity (PA).

Methods

Clinical data were obtained from Kaiser Permanente Southern California electronic health records in 2008-2018. PPD ascertainment was based on both diagnostic codes and prescription medications. Maternal residential green space exposures were assessed using street view-based measures and vegetation types (i.e., street tree, low-lying vegetation, and grass), satellite-based measures [i.e., Normalized Difference Vegetation Index (NDVI), land-cover green space, and tree canopy cover], and proximity to the nearest park. Multilevel logistic regression was applied to estimate the association between green space and PPD. A causal mediation analysis was performed to estimate the proportion mediated by PA during pregnancy in the total effects of green space on PPD.

Findings

In total, we included 415,020 participants (30.2 ± 5.8 years) with 43,399 (10.5%) PPD cases. Hispanic mothers accounted for about half of the total population. A reduced risk for PPD was associated with total green space exposure based on street-view measure [500 m buffer, adjusted odds ratio (OR) per interquartile range: 0.98, 95% CI: 0.97-0.99], but not NDVI, land-cover greenness, or proximity to a park. Compared to other types of green space, tree coverage showed stronger protective effects (500 m buffer, OR = 0.98, 95% CI: 0.97-0.99). The proportions of mediation effects attributable to PA during pregnancy ranged from 2.7% to 7.2% across green space indicators.

Interpretation

Street view-based green space and tree coverage were associated with a decreased risk of PPD. The observed association was primarily due to increased tree coverage, rather than low-lying vegetation or grass. Increased PA was a plausible pathway linking green space to lower risk for PPD.

Funding

National Institute of Environmental Health Sciences (NIEHS; R01ES030353).

Valuation of health benefits of green-blue areas for the purpose of ecosystem accounting: a pilot in Flanders, Belgium

In recent years, a vast amount of scientific literature has highlighted the benefits of nearby green space for physical and mental health, but the large variation in scope, methods and indicators used in these studies hampers the assessment of these benefits in the context of natural capital accounting. To our knowledge, this paper is one of the first studies to quantify and value these benefits in the context of natural capital accounting. A method was developed and applied to the Flemish Region in Belgium for 2013 and 2016.

The physical supply and use accounts for health are based on a set of selected dose-effect relationships that quantify the impact of the availability of greenspace on seven specific indicators for physical and mental health, including mortality, cardio-vascular diseases, diabetes and depression. The indicator for green-blue areas is the percentage of green-blue areas in total land use, calculated for 0.5, 1 and 3 km radius from the residence, based on detailed land-use maps (10 m x 10 m) for Flanders, Belgium. The base-line data for mortality and illness are average data for the Flemish Region. These health impacts are weighted using Daly's (disability-adjusted life years) and aggregated. The total health benefits due to the availability of green-blue areas for the total Flemish population was estimated at almost 85,000 DALYs. This is 27% of the estimated total burden of disease in Flanders in 2016 for the seven selected diseases.

The monetary accounts are based on a detailed assessment for mortality and morbidity of three different cost components, i.e. avoided medical costs (e.g. hospitalisation) and avoided absenteeism and welfare loss due to suffering and reduced life expectancy. Productivity gains from avoided absenteeism is valued, based on statistics on absenteeism for specific diseases for and labour market data from Belgium and account for 52% of the total monetary value of green spaces. Cost of illness is valued, based on market data and illness specific studies for Belgium or Europe and account for 36% of total values. Welfare gains from increased life expectancy are valued on the basis of European studies for the VOLY (value of a life year lost), based on the simulated exchange value for the willingness-to-pay for increased life expectancy. This accounts for 12% of the total monetary value of green space. The total monetary benefits amount to 464 Euro per inhabitant per year or 3 billion Euro per year for Flanders. This corresponds to 1.3% of the GDP, which reflects the importance of these benefits.

The methodology is incomplete as not all health indicators are covered, mainly due to a lack of dose-effect relationships. The research priority for potential users of the accounts is a better indicator for contact with green space that does differentiate between ecosystems, their quality, accessibility or their use. This requires more systematic health impact studies that take these elements into account, as well as more systematic data on the daily use of green space by citizens. In the meantime, an additional set of condition accounts on these elements can be used, especially to follow changes in quality and use of green-blue areas over time.

Demystifying normalized difference vegetation index (NDVI) for greenness exposure assessments and policy interventions in urban greening

Most nature and health research use the normalized difference vegetation index (NDVI) for measuring greenness exposure. However, little is known about what NDVI measures in terms of vegetation types (e.g., canopy, grass coverage) within certain analysis zones (e.g., 500 m buffer). Additionally, exploration is needed to understand how to interpret changes in average NDVI (e.g., per 0.1 increments) exposure in relation to changes in vegetation amount and types. In this study, we aimed to explore what vegetation types and amounts best explain the average NDVI and how changes in average NDVI values indicate changes in different vegetation coverages. We used spatial modeling to sample mean NDVI and percentages of vegetation for sample locations within the Greater Manchester case study area. We fitted linear, nonlinear, and mixed multivariate and univariate generalized additive models (GAMs) for multiple spatial scales to identify the relationships between NDVI and vegetation amount and types. Our results showed that the relationships between NDVI and individual vegetation types mostly follow nonlinear trends. We found that canopy and shrubs coverage exhibited a greater influence on mean NDVI exposure values than grass coverage at 300 and 500 m indicating that NDVI values are sensitive to certain types and amounts of vegetation within various buffer zones. We also identified increment in mean NDVI exposure values at lower, mid, and high ranges might be associated with varying changes in total greenspace percentage and individual vegetation types. For instance, at 300 m buffer, an increment of mean NDVI in the lower range (e.g., from 0.2 to 0.3) is associated with an about 17% increase in greenspace percentage. Overall, interpreting changes in NDVI values for urban greening interventions would require careful evaluation of the relative changes in types and quantities of vegetation for different buffer zones.

Transformation of Children's Paintings into Public Art to Improve Public Spaces and Enhance People's Happiness

Characteristics of children's paintings have been suggested considered for application in public art since they are known to positively evoke a sense of well-being when people see them. This study aims to understand the impact of artistic features from children's drawings on people's well-being; then analyzing the adaptive design principles of 3D public art featuring children's paintings on people's happiness; and finally, exploring the influence of 3D public art featuring children's paintings on improving public spaces and enhancing people's well-being. The results lead to proposing a conceptual framework for public artworks in public spaces for improving people's happiness. The proposed conceptual framework recommends that, by applying the visual and thinking features of children's paintings to public art, artists can design high-quality artworks suitable for a city, which could improve people's happiness in public spaces. This study recommends further research into how public art can promote public spaces and shape the urban culture. It contributes to enhancing the quality of public art and public spaces, and inspiring a sense of well-being among citizens through the use of appropriate public art. The results are significant because they will help artists to create more high-quality public artworks for urban public spaces in order to evoke people's happiness.

The influence of outdoor play spaces in urban parks on children's social anxiety

Urban green spaces are critical to the healthy development of children's social interactions and activities. However, the relationship between urban green spaces for children's activities and the alleviation of children's social anxiety remains unclear. In this study, we aimed to explore the link between spatial characteristics and social anxiety in children. To explore the coupling relationships among green space, play space, and social anxiety, an assessment of children's play spaces and levels of social anxiety was performed using self-reported data, OpenStreetMap captured the characteristic indicators of urban parks, and the ArcGIS and SPSS softwares were used for the mathematical analysis. The results showed that (1) both the NDVI and 10-min accessibility were significantly negatively related to children's social anxiety; (2) the diversity of service facilities, surfacing materials, and the attractiveness and challenge of the environment were negatively related to children's social anxiety; (3) there were significant differences between activity types and social anxiety. These results provide design references and a theoretical basis for improving the benefits of urban green space on children's health and wellbeing.

Impacts of Urban Blue-Green Space on Residents' Health: A Bibliometric Review

Urban blue-green space (UBGS), as an important component of the urban environment, is found to closely relate to human health. An extensive understanding of the effects of UBGS on human health is necessary for urban planning and intervention schemes towards healthy city development. However, a comprehensive review and discussion of relevant studies using bibliometric methods is still lacking. This paper adopted the bibliometric method and knowledge graph visualization technology to analyze the research on the impact of UBGS on residents' health, including the number of published papers, international influence, and network characteristics of keyword hotspots. The key findings include: (1) The number of articles published between 2001 and 2021 shows an increasing trend. Among the articles collected from WoS and CNKI, 38.74% and 32.65% of the articles focus on physical health, 38.32% and 30.61% on mental health, and 17.06% and 30.61% on public health, respectively. (2) From the analysis of international partnerships, countries with high levels of economic development and urbanization have closer cooperation than other countries. (3) UBGS has proven positive effects on residents' physical, mental, and public health. However, the mediating effects of UBGS on health and the differences in the health effects of UBGS on different ages and social classes are less studied. Therefore, this study proposes several future research directions. First, the mediating effect of UBGS on health impacts should be further examined. Furthermore, the interactive effects of residents' behaviors and the UBGS environment should be emphasized. Moreover, multidisciplinary integration should be strengthened. The coupling mechanism between human behavior and the environment should also be studied in depth with the help of social perception big data, wearable devices, and human-computer interactive simulation. Finally, this study calls for developing health risk monitoring and early warning systems, and integrating health impact assessment into urban planning, so as to improve residents' health and urban sustainability.

Spatial uncertainty and environment-health association: An empirical study of osteoporosis among "old residents" in public housing estates across a hilly environment

BACKGROUND

Built environment can influence physical conditions of older adults (e.g. osteoporosis). However, traditional methods using 2-dimensional circular buffer as a spatial structure to measure neighbourhood effect may create bias in health estimation, especially for the hilly and compact environment across low-income neighbourhoods (e.g. public housing estates).

METHODS

We evaluated the environmental influences on self-reported osteoporosis among "old residents" (age≥65) in Hong Kong (n = 2077). Twelve public housing estates across hilly neighbourhoods in Hong Kong were selected as study sites. A cross-validated approach was developed to evaluate four spatial structures (2D circular, 2D service area, 3D circular, 3D service area). To determine problems of spatial uncertainty, we compared odds ratios (OR) and differences in effect sizes from models using different spatial structures. When all adjusted models achieve significant results based on 95% confidence intervals (CI) and with all positive/negative ORs, this study reported to have reached "a result with consistency". Results from the 3D service area were then used to explain the environment-health relationship.

RESULTS

Different spatial structures can yield different results. Particularly, circular buffers overestimated environmental effects on self-reported osteoporosis. Overestimated measures were related to walkability and accessibility but not greenery. Specifically, results from the 3D service area showed that more public space and health facilities within a walkable distance (500 m) from a location of subject's residence were negatively associated with self-reported osteoporosis (adjusted ORs: 0.44 [0.29, 0.66]; 0.94 [0.90, 0.99]). However, more major transport facilities at the immediate distance from residence (200 m) was positively associated with self-reported osteoporosis (adjusted OR: 1.11 [1.01, 1.23]).

CONCLUSIONS

Physical conditions (e.g. osteoporosis) of older adults living in a hilly neighbourhood could be driven by walking behaviours. It is necessary to include local terrain and road network to define a walkable neighbourhood for environment-health estimations to minimize spatial bias.

Residential greenness is associated with disease severity among COVID-19 patients aged over 45 years in Wuhan, China

Evidence regarding environmental factors associated with disease severity of COVID-19 remained scarce. This study aimed to investigate the association of residential greenness exposure with COVID-19 severity applying a retrospective cross-sectional study in Wuhan, China. We included 30,253 COVID-19 cases aged over 45 years from January 1 to February 27, 2020. Residential greenness was quantitatively assessed using normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). A multilevel generalized linear model using Poisson regression was implemented to analyze the association between greenness exposure and disease severity of COVID-19, after adjusting for potential covariates. A linear exposure-response relationship was found between greenness and COVID-19 severity. In the adjusted model, one 0.1 unit increase of NDVI and EVI in the 1000-m buffer radius was significantly associated with a 7.6% (95% confidence interval (CI): 4.0%, 11.1%) and 10.0% (95% CI: 5.1%, 14.7%) reduction of the prevalence of COVID-19 severity, respectively. The effect of residential greenness seemed to be more pronounced among participants with lower population density and economic levels. Air pollutants mediated 0.82~12.08% of the greenness and COVID-19 severity association, particularly to nitrogen dioxide. Sensitivity analyses suggested the robustness of the results. Our findings suggested that residential greenness exposure was beneficial to reduce the prevalence of COVID-19 severity.

Socioeconomic Disparities in Hypertension by Levels of Green Space Availability: A Cross-Sectional Study in Philadelphia, PA

Green spaces have been proposed as equigenic factors, potentially mitigating health disparities. We used data from the 3887 participants residing in Philadelphia who participated in the Public Health Management Corporation’s Southeastern Pennsylvania Household Health Survey in 2014–2015 to assess whether socioeconomic disparities in hypertension are modified by availability of neighborhood-level green spaces. Socioeconomic status (SES) was measured using individual-level education and neighborhood-level median household income. Green space availability was measured using surrounding percent tree canopy cover, mean normalized difference vegetation index (NDVI), and proximity to nearest park. Using logistic regression models adjusted for age, sex, and race/ethnicity, we found that adults with higher educational attainment had significantly lower levels of hypertension (OR = 0.63, 0.57, and 0.36 for high school, some college, and college graduates, respectively, as compared to those with less than high school education), and this pattern was similar for median household income (higher prevalence in lower income areas). We found no significant interaction between education and percent tree canopy cover (p = 0.83), meaning that educational disparities in hypertension were similar across all levels of green space availability. These results held when using mean NDVI or distance to nearest park as availability measures, or when considering neighborhood-level median household income as the socioeconomic measure, although the specific patterns and significance of interactions varied by exposure and modifier. While socioeconomic disparities in hypertension are strong for adults residing in Philadelphia, green spaces did not seem to modify them.

Association of residential greenness with geriatric depression among the elderly covered by long-term care insurance in Shanghai

Residential greenness exposure has been linked to a number of physical and mental disorders. Nevertheless, evidence on the association between greenness and geriatric depression was limited and focused on developed countries. This study was aimed to investigate whether the relationship between residential greenness exposure and geriatric depression exists among the elderly with long-term care insurance (LTCI) in Shanghai, China. In 2018, a total of 1066 LTCI elderly from a cross-sectional survey completed a questionnaire in Shanghai. Residential greenness indicators, including normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI), were calculated from the Landsat 8 imagery data in different buffers (100-m, 300-m, and 500-m). Mediation analysis by perceived social support was conducted to explore potential mechanisms underlying the associations. In the fully adjusted model, one IQR increase of NDVI and SAVI in the 300-m buffer size was associated with an 11.9% (PR: 0.881, 95% CI: 0.795, 0.977) and 14.7% (PR: 0.853, 95% CI: 0.766, 0.949) lower prevalence of geriatric depression, respectively. Stronger association was observed in the elderly with lower education level, living in non-central area, and lower family monthly income. Perceived social support significantly mediated 40.4% of the total effect for NDVI 300-m buffer and 40.3% for SAVI 300-m buffer to the greenness-depression association, respectively. Our results indicate the importance of residential greenness exposure to geriatric depression, especially for the elderly with lower education level, living in non-central area, and lower family monthly income. Perceived social support might mediate the association. Well-designed longitudinal studies are warranted to confirm our findings and investigate the underlying mechanisms.

Assessing the role of urban green spaces for human well-being: a systematic review

Human has been evolving in a natural environment over a long time; thus, he is habitual to adapt it. Green spaces are obligatory landscapes in an urban structure that provide a natural environment and accelerate other life events. In contrast, unplanned urbanization, and conversion from green to grey structures have damaged natural environmental resources. Studies through different angles have highlighted the importance of urban green spaces for human well-being but now need to identify their role according to the potential. The demands of urban green spaces may differ with the change of population size, types of grey structure, urban expansion, the altitude of the place, and geographical location. Therefore, this systematic review aims to analyse the significance of urban green spaces for human well-being. The study opted for a systematic process during the selection and organization of studies for this review. After analysing, 46 studies were finalized with the consensus of three review authors. Accordingly, literature was analysed under the central theme of "Urban Green Spaces for Human Well-being." Human Well-being was assessed under six sub-themes; physical, psychological, mental, social, subjective, and environmental well-being. The review concluded that urban green spaces are the primary pillar for a sustainable urban place and human well-being due to highly positive and positive correlations. Moreover, the study did not find any demarcation line between green spaces and grey structures according to any specific need. Therefore, the study suggested that the role of urban green spaces for human well-being should be analysed according to their potential and required optimal ratio under different communities' urban specific environments and social behaviour.

Leisure sedentary time and physical activity are higher in neighbourhoods with denser greenness and better built environments: An analysis of the Canadian Longitudinal Study on Aging

Associations of environmental variables with physical activity and sedentary time using data from the Canadian Longitudinal Study on Aging, and the Canadian Urban Environment Research Consortium (Canadian Active Living Environments (Can-ALE) dataset, and Normalized Difference Vegetation Index (NDVI, greenness) dataset) were assessed. The main outcome variables were physical activity and sedentary time as measured by a modified version of the Physical Activity for Elderly Scale. The sample consisted of adults aged 45 and older (n = 36,580, mean age 62.6±10.2, 51% female). Adjusted ordinal regression models consistently demonstrated that those residing in neighbourhoods in the highest Can-ALE category (most well-connected built environment) reported more physical activity and sedentary time. For example, males aged 75+ in the highest Can-ALE category had 1.9 times higher odds of reporting more physical activity (OR = 1.9, 95%CI = 1.1-3.4) and 1.8 higher odds of reporting more sedentary time (OR = 1.8, 95%CI = 1.0-3.4). Neighbourhoods with higher greenness scores were also associated with higher odds of reporting more physical activity and sedentary time. It appears that an environment characterized by higher Can-ALE and higher greenness may facilitate physical activity, but it also facilitates more leisure sedentary time in older adults; research using device measured total sedentary time, and consideration of the types of sedentary activities being performed is needed. Novelty: ●Middle-aged and older adults living in neighbourhoods with higher Can-ALE scores and more greenness report more physical activity and leisure sedentary time ●Greenness is important for physical activity and sedentary time in middle-aged adults.

An integrated approach to create a spatial database of parks for urban health research

The role of urban parks has gained interest in urban health research. However, there are currently no clear definitions of these urban assets as exposure variable across the literature, which do have implications for the analysis. In this study, we exhibit an approach to design a comprehensive spatial database of urban parks in cities, using the example of Madrid. This approach consisted of the combination of different spatial databases containing information about parks and green spaces in the city of Madrid, and then a spatial processing to keep only those that met the selected criteria for urban park definition: accessible for pedestrians (to have at least one path around or through the area) and with the minimum size suitable (bigger than 0.50ha) for physical activity. This approach can be helpful to design spatial databases that enable conducting epidemiological studies on the relationship between urban parks and population health.

Urban residential tree canopy and perceived stress among pregnant women

OBJECTIVE

To examine the association of urban residential tree canopy cover with perceived stress in a cohort of pregnant women in Philadelphia, PA, and explore whether this association differed among participants with a history of anxiety and depression.

STUDY DESIGN

We performed a secondary analysis of 1294 participants of the Motherhood & Microbiome (M&M) pregnancy cohort who lived in Philadelphia, with first visit perceived stress (Cohen's Perceived Stress Scale, PSS-14), and key covariate data. Tree canopy cover was calculated as percent cover within 100 and 500 m radii buffers around participants' homes. We performed multilevel mixed effects linear regression models, with perceived stress as the dependent variable. The main independent variable was tree canopy coverage. Individual-level covariates included season of last menstrual period, history of depression or anxiety, race/ethnicity, insurance, parity, and age. Census tract neighborhood deprivation index was used to account for area-level socioeconomic confounding variables. We also examined whether a history of anxiety or depression, modified the association between tree canopy coverage and perceived stress.

RESULTS

Most participants were non-Hispanic Black (70.6%, n = 913), on Medicaid or uninsured (60.4%, n = 781), and 15.8% (n = 204) of participants had a prior history of depression or anxiety. We did not detect associations between tree canopy coverage and perceived stress overall. However, we detected effect modification; among participants with a history of depression or anxiety, each standard deviation increase in tree canopy cover was associated with lower PSS-14 in 100 m buffers (β -1.0, 95% CI -1.8, -0.2), but not among participants with no histories of depression or anxiety (β 0.2, 95% CI -0.3, 0.7) (interaction P = 0.007). Results were similar in directionality but not statistically significant within 500 m buffers.

CONCLUSION

Residential tree canopy coverage was associated with reduced perceived stress among urban-dwelling pregnant women with history of anxiety or depression. Future studies of the effects of greenness and other stress-reducing efforts should consider underlying mental health conditions as effect modifiers.

Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure

BACKGROUND

Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on the ground, which is important to elucidate the underlying mechanisms linking green space and health.

OBJECTIVES

This study aimed to evaluate machine learning models that can classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images; and to investigate the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California.

METHODS

SES variables were obtained from the CalEnviroScreen3.0 dataset. Microsoft Bing Maps images in conjunction with deep learning were used to measure total and types of street view green space, which were compared to normalized difference vegetation index (NDVI) as commonly-used satellite-based green space measure. Generalized linear mixed model was used to examine associations between green space and census tract SES, adjusting for population density and rural/urban status.

RESULTS

The accuracy of the deep learning model was high with 92.5% mean intersection over union. NDVI were moderately correlated with total street view-based green space and tree, and weakly correlated with low-lying vegetation and grass. Total and three types of green space showed significant negative associations with neighborhood SES. The percentage of total green space decreased by 2.62 [95% confidence interval (CI): -3.02, -2.21, p < 0.001] with each interquartile range increase in CalEnviroScreen3.0 score. Disadvantaged communities contained approximately 5% less average street green space than other communities.

CONCLUSION

Street view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian's perspective.

Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure

BACKGROUND

Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on the ground, which is important to elucidate the underlying mechanisms linking green space and health.

OBJECTIVES

This study aimed to evaluate machine learning models that can classify the type of vegetation (i.e., tree, low-lying vegetation, grass) from street view images; and to investigate the associations between street green space and socioeconomic (SES) factors, in Los Angeles County, California.

METHODS

SES variables were obtained from the CalEnviroScreen3.0 dataset. Microsoft Bing Maps images in conjunction with deep learning were used to measure total and types of street view green space, which were compared to normalized difference vegetation index (NDVI) as commonly-used satellite-based green space measure. Generalized linear mixed model was used to examine associations between green space and census tract SES, adjusting for population density and rural/urban status.

RESULTS

The accuracy of the deep learning model was high with 92.5% mean intersection over union. NDVI were moderately correlated with total street view-based green space and tree, and weakly correlated with low-lying vegetation and grass. Total and three types of green space showed significant negative associations with neighborhood SES. The percentage of total green space decreased by 2.62 [95% confidence interval (CI): -3.02, -2.21, p < 0.001] with each interquartile range increase in CalEnviroScreen3.0 score. Disadvantaged communities contained approximately 5% less average street green space than other communities.

CONCLUSION

Street view imagery coupled with deep learning approach can accurately and efficiently measure eye-level street green space and distinguish vegetation types. In Los Angeles County, disadvantaged communities had substantively less street green space. Governments and urban planners need to consider the type and visibility of street green space from pedestrian's perspective.

Relationship between Green and Blue Spaces with Mental and Physical Health: A Systematic Review of Longitudinal Observational Studies

There is growing interest in the ways natural environments influence the development and progression of long-term health conditions. Vegetation and water bodies, also known as green and blue spaces, have the potential to affect health and behaviour through the provision of aesthetic spaces for relaxation, socialisation and physical activity. While research has previously assessed how green and blue spaces affect mental and physical wellbeing, little is known about the relationship between these exposures and health outcomes over time. This systematic review summarised the published evidence from longitudinal observational studies on the relationship between exposure to green and blue space with mental and physical health in adults. Included health outcomes were common mental health conditions, severe mental health conditions and noncommunicable diseases (NCDs). An online bibliographic search of six databases was completed in July 2020. After title, abstract and full-text screening, 44 eligible studies were included in the analysis. Depression, diabetes and obesity were the health conditions most frequently studied in longitudinal relationships. The majority of exposures included indicators of green space availability and urban green space accessibility. Few studies addressed the relationship between blue space and health. The narrative synthesis pointed towards mixed evidence of a protective relationship between exposure to green space and health. There was high heterogeneity in exposure measures and adjustment for confounding between studies. Future policy and research should seek a standardised approach towards measuring green and blue space exposures and employ theoretical grounds for confounder adjustment.

Assessing Emotional Responses to the Spatial Quality of Urban Green Spaces through Self-Report and Face Recognition Measures

Although creating a high-quality urban green space (UGS) is of considerable importance in public health, few studies have used individuals' emotions to evaluate the UGS quality. This study aims to conduct a multidimensional emotional assessment method of UGS from the perspective of spatial quality. Panoramic videos of 15 scenes in the West Lake Scenic Area were displayed to 34 participants. For each scene, 12 attributes regarding spatial quality were quantified, including perceived plant attributes, spatial structure attributes, and experiences of UGS. Then, the Self-Assessment-Manikin (SAM) scale and face recognition model were used to measure people's valence-arousal emotion values. Among all the predictors, the percentages of water and plants were the most predictive indicators of emotional responses measured by SAM scale, while the interpretation rate of the model measured by face recognition was insufficiently high. Concerning gender differences, women experienced a significantly higher valence than men. Higher percentages of water and plants, larger sizes, approximate shape index, and lower canopy densities were often related to positive emotions. Hence, designers must consider all structural attributes of green spaces, as well as enrich visual perception and provide various activities while creating a UGS. In addition, we suggest combining both physiological and psychological methods to assess emotional responses in future studies. Because the face recognition model can provide objective measurement of emotional responses, and the self-report questionnaire is much easier to administer and can be used as a supplement.

A Framework for Fairness Evaluation and Improvement of Urban Green Space: A Case of Wuhan Metropolitan Area in China

Urban green space (UGS) provides a wide range of ecosystem services for human beings. The fairness of UGS distribution has important implications for sustainable urban development and human well-being. However, many current studies on green space fairness are limited to within specific cities, and UGS fairness in rapidly developing metropolitan areas is still largely neglected. This study quantifies the change in green space fairness in the Wuhan metropolitan area from 2000 to 2020 based on a long time series of land cover and population spatial distribution products. We incorporated green space types and population distribution into the fairness evaluation framework, quantified the value of green space ecosystem services available to people through nested buffers, and analyzed the spatial and temporal variation of green space fairness in the study area based on the Gini coefficient of each city. The results show that the supply of green space services in most cities has shown a trend of “decreasing and then increasing” in the past 20 years. The fairness of green space in three cities has shown an improving trend, and the Gini coefficient in four cities is still above 0.50 in 2020. Based on the current green space and related indicators in each city, we propose future greening policies for each city. The methodology and conclusions of this study will help improve future green space planning recommendations in metropolitan areas and urban agglomerations, thus promoting regional public infrastructure coproduction and sharing.

Examining the joint effects of heatwaves, air pollution, and green space on the risk of preterm birth in California

BACKGROUND

Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy.

OBJECTIVES

To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB.

METHODS

California birth certificate records for singleton births (2005-2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB.

RESULTS

In total, 1,967,300 births were included in this study. For PM2.5, PM10 and O3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e., shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves.

CONCLUSION

This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.

Cross-sectional association of residential greenness exposure with activities of daily living disability among urban elderly in Shanghai

AIM

Residential greenness exposure is associated with many health outcomes, including obesity, cardiovascular disease, and mental disorders. However, few studies have assessed the effects of greenness exposure on activities of daily living (ADL). This study evaluated the relationship between greenness and ADL among elderly residents with long-term care insurance (LTCI) in Shanghai, China.

METHODS

We conducted a cross-sectional survey using stratified random sampling among elderly residents with LTCI in six districts of Shanghai in August 2018. We quantitatively assessed residential greenness using satellite-derived normalized difference vegetation index (NDVI) values with 250-, 500-, and 1000-m buffers around each participant's residential address. We calculated the walk score to assess neighborhood walkability. Physical function was assessed using basic ADL (BADL) and instrumental ADL (IADL). We performed binary logistic regression and restricted cubic splines with R software.

RESULTS

The study participants were 1067 adults with a mean age of 82.40 years (standard deviation, 7.68 years). The mean NDVI value was 0.311. In the fully adjusted model, being in the highest-tertile NDVI_500-m had a significant protective effect on BADL mild to none disability (odds ratio, 2.143; 95% confidence interval, 1.489-3.084) compared with participants in the lowest-tertile NDVI_500-m. Restricted cubic spline showed a non-linearity association between NDVI values and BADL and IADL mild to none disability.

CONCLUSIONS

Our results indicate the importance of residential greenness exposure to physical function-especially for BADL disability. Well-designed longitudinal studies are needed to confirm our findings and investigate the underlying mechanisms.

Residential exposure to natural outdoor environments and general health among older adults in Shanghai, China

Background

Exposure to natural outdoor environments (NOE) has been shown to be beneficial to older adults’ health and functioning, yet this assertion has rarely been tested in China. We investigated the relationships between exposure to NOE and older adults’ self-rated health in Shanghai, China and examined whether these relationships varied by sex, age, education and hukou status.

Method

This cross-sectional study used micro-data sample of the 2010 Shanghai population census, including 7962 older adults nested within 3345 neighbourhoods. Self-rated health was the outcome variable. Four NOE exposure indicators were calculated for each neighbourhood: the amount of surrounding greenness/blueness and proximity to large green/blue spaces. Multilevel logistic regression was employed to explore the association between natural outdoor environment exposure and self-rated health, adjusting for individual-level and neighbourhood-level covariates. Stratified analyses were used to examine variations by sex, age, education and hukou status.

Results

Older adults living in neighbourhoods with higher surrounding greenness and higher proximity to both green spaces and blue spaces were more likely to report good health. Residential surrounding blueness was not significantly related to self-rated health. Females, those aged 60–69 years, those who had elementary school or junior high school education and those with non-local hukou benefit more from residential surrounding greenness, and those aged 70–79 years and who had elementary school or junior high school education benefit more from residential proximity to blue spaces.

Conclusions

Higher residential greenness and proximity to both green spaces and blue spaces were associated with better self-rated health, particularly for females, younger older adults, the low educated and non-local hukou holders. Our findings suggest that urban green spaces and urban blue spaces have different effects on health among Chinese older adults and that the assessment of exposure matters to the investigation of NOE-health relationships.

Greening Blocks: A Conceptual Typology of Practical Design Interventions to Integrate Health and Climate Resilience Co-Benefits

It is increasingly evident that exposure to green landscape elements benefits human health. Urban green space in cities is also recognized as a crucial adaptation response to changes in climate and its subsequent effects. The exploration of conceptual and practical intersections between human health, green spaces, and climate action is needed. Evidence-based guidance is needed for stakeholders, practitioners, designers, and citizens in order to assess and manage urban green spaces that maximize co-benefits for both human health and climate resilience. This paper proposes interventions that provide strategic green space enhancement at the neighborhood and block scale. We propose eight tangible green space interventions and associated metrics to integrate climate resilience and population health co-benefits into urban green space design and planning: View from within, Plant entrances, Bring nature nearby, Retain the mature, Generate diversity, Create refuge, Connect experiences, and Optimize green infrastructure. These interventions represent a hierarchy of functional design concepts that respond to experiential qualities and physical/psychological dimensions of health, and which enhance resilience at a range of social scales from the individual to the neighborhood. The interventions also reveal additional research needs in green space design, particularly in neighborhood-level contexts.

Community greenness and neurobehavioral health in children and adolescents

BACKGROUND

Neighborhood greenness appears to be beneficial to human health. However, there are few studies on the relationship between greenness of children's residential communities and their neurobehavioral health.

OBJECTIVE

In this cross-sectional study, we examined the association between neighborhood greenness of children's residential area and their neurobehavioral health.

METHODS

We used a population-representative sample of school children (n = 1817) from 2012 and 2013 in South Korea. Parents or guardians of children completed the Child Behavior Checklist (CBCL) to assess their children's neurobehavioral health. As a measurement for greenness, the modified soil-adjusted vegetation index (MSAVI) at a 30-m resolution was retrieved from the Landsat satellite data operated by NASA. The MSAVI values were categorized into tertiles (low, moderate, high greenness) and each child was assigned the mean MSAVI within a 1.6-km radius of residence. We applied survey regressions of the CBCL transformed scores on the 3 levels of greenness, controlling for age, sex, physical activity, monthly family income, exposure to second-hand smoke, exposure to NO₂, and blood lead level.

RESULTS

High greenness was associated with a lower Total CBCL score compared to low greenness (-2.33, 95% CI, -4.10 to -0.56). Externalizing Behavior showed a slightly stronger association with greenness than did Internalizing Behavior. The inverse relationship with greenness was strongest for Attention Problems (-1.32; 95% CI: -2.58, -0.06). The magnitudes of the association were strongest when the buffer distance was 1600 m.

CONCLUSIONS

Greenness of residential neighborhood was associated with lower problematic behavior scores in children, especially aggressive behaviors and attention problems.