Different Types Of Green Space Research Articles

The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies.

Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging. Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies. We used Landsat 5-8 (30 m resolution) to calculate average EVI for a 300 m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300 m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types. Mean EVI for a 300 m radius surrounding households in Wales was 0.28 (IQR = 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (β = < 0.0001, 95% CI: 0.0000, 0.0000; β = 0.0001, 95% CI: 0.0001, 0.0001 respectively). In urban areas, as average garden size increases by 1 m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500 m2. The very small β values represent no 'measurable real-world' associations. When stratified by type, we observed no strong associations between greenspace and EVI. It is a widely implemented assumption in epidiological studies that an increase in EVI is equivalent to an increase in greenness and/or green space. We used linear regression models to test associations between EVI and potential sources of green reflectance at a neighbourhood level using satellite imagery from 2018. We compared EVI measures with a 'gold standard' vector-based dataset that defines publicly accessible and private green spaces. We found that EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment.

The association between greenery type and gut microbiome in schizophrenia: did all greenspaces play the equivalent role?

In recent years, attention has been focused on the benefit of greenspace on mental health, and it is suggested this link may vary with the type of greenspace. More and more studies have emphasized the influence of the gut microbiome on schizophrenia (SCZ). However, the effects of greenspaces on the gut microbiota in SCZ and the effect of different types of greenspaces on the gut microbiota remain unclear. We aim to examine if there were variations in the effects of various greenspace types on the gut microbiome in SCZ. Besides, we sink to explore important taxonomic compositions associated with different greenspace types. We recruited 243 objects with schizophrenia from Anhui Mental Health Center and collected fecal samples for 16Sr RNA gene sequencing. Three types of greenery coverage were calculated with different circular buffers (800, 1500, and 3000m) corresponding to individual addresses. The association between greenspace and microbiome composition was analyzed with permutational analysis of variance (PERMANOVA). We conducted the linear regression to capture specific gut microbiome taxa associated with greenery coverage. Tree coverage was consistently associated with microbial composition in both 1500m (R2 = 0.007, P = 0.030) and 3000m (R2 = 0.007, P = 0.039). In contrast, there was no association with grass cover in any of the buffer zones. In the regression analysis, higher tree coverage was significantly correlated with the relative abundance of several taxa. Among them, tree coverage was positively associated with increased Bifidobacterium longum (β = 1.069, P = 0.004), which was the dominant composition in the gut microbiota. The relationship between greenspace and gut microbiome in SCZ differed by the type of greenspace. Besides, "tree coverage" may present a dominant effect on the important taxonomic composition. Our findings might provide instructive evidence for the design of urban greenspace to optimize health and well-being in SCZ as well as the whole people.

Associations of neighborhood-level socioeconomic status, accessibility, and quality of green spaces in Finnish urban regions

Ensuring fair access to urban green spaces is a constant challenge for planning in densifying cities. Moreover, the quality of green spaces that determines their usability is often insufficiently considered in accessibility research. We examined residents’ accessibility to different types of green spaces also by neighborhood-level socioeconomic status (SES) in the seven largest urban regions in Finland. We identified eight different green space types, and high and low SES neighborhoods using income, education, and unemployment rate. We calculated network-based accessibility to the different types of green spaces and compared areas with a high and low SES using ANOVA. 90% of the urban residents lived within 300 meters of any green space. However, inclusion of the quality factors decreased accessibility of the green spaces from 34% to 75%. Residents living in high and low SES areas had different quality features in their nearest green spaces. Recreation facilities and routes were closer to low SES areas, whereas areas of high SES were associated with better accessibility to large green areas, and forests. This pattern recurred in most individual cities with varying distance differences. Our results emphasize the importance of considering the quality of green spaces in urban planning.

Nature interactions and their associations with connection to nature and well‐being varies between different types of green spaces

Abstract Increasing urbanization leads to greater loss of interaction with nature over time in a process described as the extinction of experience. Urban green spaces are some of the most prominent sites where individuals can access and interact with nature in urban areas. There is currently a gap in research around how different types of urban green spaces influence nature interactions, their relationships with human well‐being, and what influences these relationships. Greater knowledge of these connections can aid in the design of green spaces that can increase human well‐being and mitigate the extinction of experience. We conducted a visitor survey in an urban nature site in Israel, which consists of both a garden and protected nature area dominated by natural Mediterranean vegetation. We aimed to understand how visitors interacted with nature at the site and how the interactions differed between the protected nature area and the garden. Both frequency of interactions and number of total interactions were measured. We also investigated the extent to which these interactions associated with nature relatedness (using the NRS scale), well‐being (using overall happiness and psychological well‐being) and the variables that influence nature interactions and well‐being outcomes. Visitors who visited the protected nature area were more likely to interact with nature than those who only visited the garden. Nature interactions were significantly associated with an individual's nature relatedness and their perception of whether the site functioned more similarly to an urban park or a protected nature area. Living nearby was associated with greater attachment to and identity with the site, but also lower frequency of nature interactions. Nature interactions were associated with measures of well‐being, including overall happiness, attachment, identity and reflection, but varied depending on well‐being measures. Interactions with nature, and their benefits, are not equal based on both actual opportunity for interaction and perceptions of green spaces. Incorporating user preferences of urban green spaces for more wild nature that individuals also perceive as wilder may allow for greater interaction. Developing urban nature sites that allow for greater interaction can promote human well‐being associated with interactions and combat extinction of experience. Read the free Plain Language Summary for this article on the Journal blog.

Evaluating the benefits of ecosystem-based urban cooling using a dynamic “on-site” method

Ecosystem-based cooling helps residents cope with the urban heat-island problem. In order to improve the accuracy of traditional heat-island measurements based on comparisons between urban and rural areas, we use an “on-site” method developed with only urban data. The essence of this method is a regression analysis of the relationships among different types of green space and blue space, elevation, vegetation dynamics, and temperature. We then simulate the temperature pattern in a scenario where there is no built-up area (Scenario A), and then in another scenario where there are no ecological spaces (Scenario B). The gap between the actual temperature pattern and the simulated temperature pattern of Scenario A is considered the heat-island effect. Conversely, the gap between the actual temperature pattern and that of Scenario B is considered as the effect of ecosystem-based urban cooling. This method was tested using data from two megacities in China (each had a population of over 10 million people). For Beijing, the average heat-island effect was 4.87 °C and effect of the ecosystem cooling service was 9.07 °C. For Shenzhen, the respective values were 0.8 °C and 2.71 °C. The “on-site” (local small size sampling), “dynamic coefficient”, and “no-positive-coefficient rule” are the three defining characteristics of this method. The application of this method to model ecosystem-based urban cooling can aid urban planning and management in improving the residential thermal environment.

Exploring the Patterns of Recreational Activity among Urban Green Spaces in Poland

The aim of this study was to investigate the relationship between the socio-demographic background, patterns of recreational activity, and their impact on mood regulation strategies used by urban green spaces (UGS) visitors in Poland. In our research approach, we collected data from 376 participants through an online survey. In the next step, we developed structural equation models: one general model and two additional models for men and women. We discovered that both socio-demographic characteristics, as well as the variety of visited green spaces impact people’s mood regulation strategies. In our research approach, latent variable places that consists of different types of green spaces is the key concept that positively affect mood regulation strategies; visiting more places reduces the tendency to decrease mood and increases the tendency to increase mood. Moreover, we identified some important gender similarities and differences. There is causation between the types of leisure activity and the frequency of a leisure activity among men and women. However, in the case of women, the frequency of a leisure activity is positively associated with the tendency to increase mood; in the case of men, the association is negative. The research results provide a deeper insight into of the patterns of green leisure that shape the subjective well-being of urban green space visitors in Poland.

Relationships between socio-demographic / socio-economic characteristics and neighborhood green space in four Nordic municipalities – results from NORDGREEN

Urban green space governs important ecosystem services including providing health promoting facilities. However, unequal distribution of green space among socio-demographic and socio-economic groups may create environmental injustice among inhabitants and between neighborhoods. This paper reports on access to different types of green space for residents in four Nordic cities. More precisely it explores relationships between socio-demographic and socio-economic characteristics and access to green space at the neighbourhood level. We selected the following green space variables: distance between inhabitants’ dwellings and parks, forest, and cemeteries; percentages and area per inhabitant of parks, forest, and cemeteries; and vegetation cover derived from satellite images and Urban Atlas. These were linked to income, education, age, and percentage of the population born outside their country of residence at a neighbourhood level. The results show that inhabitants in the four Nordic cities have great access to green space, but the percentage of different types of green space, such as forest and parks, varies between the cities and within the cities. We found that most inhabitants have less than 300 m to the nearest green space ranging from 92% in Stavanger (Norway) to 99.2% in Täby (Sweden). We also found differences in access depending on inhabitants' age, education, immigration status, and median income. Espoo (Finland) had the highest total green space coverage (45.3%), while Täby had the highest proportion of park coverage (2.3%). By compensating with green spaces in less affluent areas, and focusing on equal access to green space, planners can contribute to reduce health inequalities in the population.

Types of greenspace and adolescent mental health and well-being in metropolitan London

ABSTRACT The evidence suggests a link between greenspace and adolescent mental health. One limitation is the typically crude measure of greenspace quantity or greenness. We explored the roles of different types of greenspace in the mental health of 10- to 15-year-old adolescents living in London, using data from Understanding Society, a UK household longitudinal study. We used data on 1,879 adolescents from waves 1-8 (2009-2018). As some adolescents had observations at multiple waves, 4,217 observations were included. Mental health and well-being measures were Strengths and Difficulties Questionnaire scores, self-esteem, and happiness. Proportions of green land cover, parks & gardens, natural & semi-natural urban greenspaces, outdoor sports facilities, and total green land use were measured in 500 m around postcodes. We ran linear regressions, stratified by age, adjusted for confounders, and accounting for Understanding Society’s complex sampling design. We did not find consistent results across analyses, but we identified patterns worth exploring further: older adolescents (13-15 years) seemed to ‘benefit’ more from greenspace than younger adolescents (10-12 years); and parks & gardens and outdoor sports facilities seemed to be most ‘beneficial’. Overall, however, no clear conclusions can be drawn, and findings need to be confirmed in future studies.

Associations between COVID-19 risk, multiple environmental exposures, and housing conditions: A study using individual-level GPS-based real-time sensing data

Few studies have used individual-level data to explore the association between COVID-19 risk with multiple environmental exposures and housing conditions. Using individual-level data collected with GPS-tracking smartphones, mobile air-pollutant and noise sensors, an activity-travel diary, and a questionnaire from two typical neighborhoods in a dense and well-developed city (i.e., Hong Kong), this study seeks to examine 1) the associations between multiple environmental exposures (i.e., different types of greenspace, PM2.5, and noise) and housing conditions (i.e., housing types, ownership, and overcrowding) with individuals’ COVID-19 risk both in residential neighborhoods and along daily mobility trajectories; 2) which social groups are disadvantaged in COVID-19 risk through the perspective of the neighborhood effect averaging problem (NEAP). Using separate multiple linear regression and logistical regression models, we found a significant negative association between COVID-19 risk with greenspace (i.e., NDVI) both in residential areas and along people's daily mobility trajectories. Meanwhile, we also found that high open space and recreational land exposure and poor housing conditions were positively associated with COVID-19 risk in high-risk neighborhoods, and noise exposure was positively associated with COVID-19 risk in low-risk neighborhoods. Further, people with work places in high-risk areas and poor housing conditions were disadvantaged in COVID-19 risk.

Neighborhood greenspace and cognition: The cardiovascular health study.

We examined whether greenspace measures (overall percent greenspace and forest, and number of greenspace types) were associated with clinically adjudicated dementia status. In a sample of non-demented older adults (n=2141, average age=75.3 years) from the Cardiovascular Health and Cognition Study, Cox proportional hazard and logistic regression analyses were used to estimate associations of baseline greenspace with risks of incident dementia and MCI, respectively, while adjusting for demographics, co-morbidities, and other neighborhood factors. We derived quartiles of percent greenness (greenspace), forest (percent tree canopy cover), and tertiles of greenspace diversity (number of greenspace types) for 5-km radial buffers around participant's residences at study entry (1989-1990) from the 1992 National Land Cover Dataset. Dementia status and mild cognitive impairment (MCI) over 10 years was clinically adjudicated. We observed no significant association between overall percent greenspace and risk of mild cognitive impairment or dementia and mostly null results for forest and greenspace diversity. Forest greenspace was associated with lower odds of MCI (OR quartile 4 versus 1: 0.54, 95% CI: 0.29-0.98) and greenspace diversity was associated with lower hazard of incident dementia (HR tertile 2 versus 1: 0.70, 95% CI=0.50-0.99). We found divergent results for different types of greenspace and mild cognitive impairment or dementia. Improved greenspace type and diversity measurement could better characterize the association between greenspace and cognition.

GREENSPACE AND COGNITION: EXPLORING SPECIFIC GREENSPACE MEASURES

Abstract Increased exposure to greenspace is potentially associated with lower risk of Alzheimer’s disease and related disorders (ADRD) through increased physical activity, decreased stress, cleaner air, and social cohesion. Previous studies have primarily used global measures of greenspace, thus specific aspects of different types of greenspaces are overlooked. We assess how different measures of greenspaces associate with global cognitive functioning. We examined data from year 10 of the Pittsburgh site of Health, Aging, and Body Composition Study, a longitudinal cohort study of community-dwelling, Black and White adults aged 70–79 years at baseline. Measures derived from the National Land Cover Database (NLCD) use satellite imaging and include total greenspace, forests, and an index of greenspace diversity. Measures from Google Street View virtual neighborhood audits include dedicated greenspace that promotes physical activity, abandoned buildings, and undeveloped land. We measured global cognitive functioning using the Modified Mini-Mental State Examination (3MS). We conducted cross-sectional linear regression models. Covariates included race, education, and neighborhood socioeconomic status. Age was not included as a covariate because the range was narrow, and results did not vary by age. The sample (n=584) was 82.2 years old on average, 57% female, and 35% Black. Total greenspace (F=0.46, p=0.49), forests, and greenspace diversity, dedicated greenspace for physical activity (F=0.87, p=0.35), undeveloped land (F=1.49, p=0.22), and abandoned buildings (F=3.6, p=0.058) were not associated with 3MS, although the relation with abandoned buildings approached significance. We found no association between greenspaces and ADRD, although specific measures, such as abandoned buildings, may need further investigation.

Green space availability and mental health – results from a cross-sectional study in Northwestern Germany

Abstract Background A relationship between green space and health has been shown in several epidemiological studies. The impact of different types of green space is still relatively unknown. To start filling this gap, we looked at associations between different green space types and health outcomes (depression and mental health). Methods Data are obtained from a cross-sectional study (n = 479). Depression (assessed with PHQ-9) and mental health (assessed with GHQ-28) are dependent variables. Availability of green space in the surrounding neighborhood was assessed as independent variable by the percentage of green space ( &amp;gt; =1ha) within a 250m radius participants residence. Survey data were analyzed using IBM SPSS 26 and Geo data using QGIS 3.18.0. Results N = 479 participants of a cross-sectional study in 2018 provided data (49.4%, n = 240 women; 49.6%, n = 239 men). Participants had a mean age of 57.55 years (SD: 18.80, min-max:18-95), majority (75.2%, n = 360) were married or partnered, had a lower educational qualification than A-levels equivalent (56.8%, n = 272), were not employed (53%, n = 254), had a net household income of at least 3. 000€ per month (40.1%, n = 192) and at least sometimes financial worries (51.4%, n = 246). Green areas without agricultural areas show an association with frequency of depression (B(SE)=0.056(0.024), p = 0.018). This contrasts with green spaces including agricultural areas, where there is no statistically significant association (B(SE)=0.007(0.012), p = 0.564). Discussion We found an association between type of green space and depression. Further studies are needed to establish a grid for assessing characteristics and quality criteria of green spaces. However, it can already be assumed that there is an association between quality of green spaces and psychosocial outcomes.

Exploring green gentrification in 28 global North cities: the role of urban parks and other types of greenspaces

Although cities globally are increasingly mobilizing re-naturing projects to address diverse urban socio-environmental and health challenges, there is mounting evidence that these interventions may also be linked to the phenomenon known as green gentrification. However, to date the empirical evidence on the relationship between greenspaces and gentrification regarding associations with different greenspace types remains scarce. This study focused on 28 mid-sized cities in North America and Western Europe. We assessed improved access to different types of greenspace (i.e. total area of parks, gardens, nature preserves, recreational areas or greenways [i] added before the 2000s or [ii] added before the 2010s) and gentrification processes (including [i] gentrification for the 2000s; [ii] gentrification for the 2010s; [iii] gentrification throughout the decades of the 2000s and 2010s) in each small geographical unit of each city. To estimate the associations, we developed a Bayesian hierarchical spatial model for each city and gentrification time period (i.e. a maximum of three models per city). More than half of our models showed that parks—together with other factors such as proximity to the city center—are positively associated with gentrification processes, particularly in the US context, except in historically Black disinvested postindustrial cities with lots of vacant land. We also find than in half of our models newly designated nature preserves are negatively associated with gentrification processes, particularly when considering gentrification throughout the 2000s and the 2010s and in the US. Meanwhile, for new gardens, recreational spaces and greenways, our research shows mixed results (some positive, some negative and some no effect associations). Considering the environmental and health benefits of urban re-naturing projects, cities should keep investing in improving park access while simultaneously implementing anti-displacement and inclusive green policies.

Green spaces, especially nearby forest, may reduce the SARS-CoV-2 infection rate: A nationwide study in the United States

The coronavirus pandemic is an ongoing global crisis that has profoundly harmed public health. Although studies found exposure to green spaces can provide multiple health benefits, the relationship between exposure to green spaces and the SARS-CoV-2 infection rate is unclear. This is a critical knowledge gap for research and practice. In this study, we examined the relationship between total green space, seven types of green space, and a year of SARS-CoV-2 infection data across 3,108 counties in the contiguous United States, after controlling for spatial autocorrelation and multiple types of covariates. First, we examined the association between total green space and SARS-CoV-2 infection rate. Next, we examined the association between different types of green space and SARS-CoV-2 infection rate. Then, we examined forest–infection rate association across five time periods and five urbanicity levels. Lastly, we examined the association between infection rate and population-weighted exposure to forest at varying buffer distances (100 m to 4 km). We found that total green space was negative associated with the SARS-CoV-2 infection rate. Furthermore, two forest variables (forest outside park and forest inside park) had the strongest negative association with the infection rate, while open space variables had mixed associations with the infection rate. Forest outside park was more effective than forest inside park. The optimal buffer distances associated with lowest infection rate are within 1,200 m for forest outside park and within 600 m for forest inside park. Altogether, the findings suggest that green spaces, especially nearby forest, may significantly mitigate risk of SARS-CoV-2 infection.

Associations between green space, air pollution and birthweight in Sydney Metropolitan Area, Australia

Growing number of evidence have reported that exposure to air pollution was associated with unfavourable birth outcomes while increased exposure to green spaces was associated with better birth outcomes. However, the effect of interactions between air pollution and green spaces on pregnancy outcomes remain unclear. Using the data on all the live births recorded in Sydney between 2016 January and 2017 December, we built up multilevel linear and logistic regression models with random intercepts for statistical area level 2 (SA2) to examine the association between residential levels of air pollution (NO2, PM2.5, SO2 and O3) and pregnancy outcomes including birthweight, low birthweight, and preterm birth. This was followed by assessment of potential effect modification by green space quantity by fitting 2-way interaction term between each air pollutants and green space quantity separately. Furthermore, building on the 2-way interaction term, we explored 3-way interactions by adding area level socio-economic status and population density. Higher levels of PM2.5, NO2 and SO2 were statistically significantly associated with decrease in birthweights (p < 0.05) in the adjusted models. We observed statistically significantly association between the lower risks of preterm birth and higher levels of NO2 in the adjusted models (p < 0.05). However, none of the other air pollutants were statistically significantly associated with the odds of low birthweight and preterm birth. In the adjusted models, green space quantity was statistically significantly associated with reduced odds of preterm birth (p < 0.05). The results for birthweights were in the same direction (p < 0.05) however, some of these associations did not remain statistically significant after adjusting the models for air pollution. In general, no associations were found for low birthweight. Statistically significant 2-way interactions between green space quantity and NO2, PM2.5 and SO2 levels indicated that association between moderate levels of NO2, PM2.5 and birthweight weakened in the greener areas (>20 %) especially in the affluent and densely populated areas while the effect of SO2 did not differ consistently across green space levels with benefit of exposure to the greenest areas (>40 %) was evident, yet not statistically significant. Our findings suggest that increasing green spaces in cities may help supporting a healthy start in life by decreasing harms of moderate levels of air pollution. Replication in different contexts and consideration of potentially contrasting results with different types of green space is warranted.

Evaluation of urban green space landscape planning scheme based on PSO-BP neural network model

The evaluation simulation of urban green space landscape planning scheme based on PSO-BP neural network model is carried out in this paper. PSO-BP neural network can combine the principle of landscape ecology, integrate more evaluation indicators of ecology and urban development into the urban green space landscape planning scheme, and simply understand and predict human behavior, so as to make a more comprehensive evaluation and prediction of the urban green space landscape planning scheme. It not only has superior memory storage and learning ability, but also can simply understand and predict human behavior, so that more influencing factors that cannot be added in the past can be considered in the scheme evaluation and analysis, and the evaluation of urban green space landscape planning scheme is more comprehensive, scientific and reasonable. Experiments show that PSO-BP neural network has smaller error and better generalization ability than BP neural network. PSO-BP neural network rating model can analyze its more reasonable proportion according to the relationship between different types of green space and indicators, and give corresponding adjustment suggestions, which has guiding significance for the modification and adjustment of urban green space landscape planning scheme.

Valuing access to urban greenspace using non-linear distance decay in hedonic property pricing

Modelling walking distance enables the observation of non-linearities in hedonic property pricing of accessibility to greenspace. We test a penalized spline spatial error model (PS-SEM), which has two distinctive features. First, the PS-SEM controls for the presence of a spatially autocorrelated error term. Second, the PS-SEM allows for continuous non-linear distance decay of the property price premium as a function of walking distance to greenspaces. As a result, compared with traditional spatial econometric methods, the PS-SEM has the advantage that data determines the functional form of the distance decay of the implicit price for greenspace accessibility. Our PS-SEM results from Oslo, Norway, suggest that the implicit price for greenspace access is highly non-linear in walking distance, with the functional form varying for different types of greenspaces. Our results caution against using simple linear distances and assumptions of log or stepwise buffer-based distance decay in property prices relative to pedestrian network distance to urban amenities. The observed heterogeneity in the implicit property prices for walking distance to greenspace also provides a general caution against using non-spatial hedonic pricing models when aggregating values of greenspace amenities for policy analysis or urban ecosystem accounting purposes.

How to promote residents’ use of green space: An empirically grounded agent-based modeling approach

One focus of those responsible for making urban policies has been the improvement of green space effectiveness, including environmental plans and eco-city initiatives. In the evaluation of policy effectiveness, residents’ needs, values and preferences are critical but often overlooked. This study proposes an agent-based model (ABM) for simulating the effectiveness of policy measures on residents’ decision making with regard to the use of green space. Using a residential questionnaire survey conducted in Shanghai, China, we model individual decision making with artificial neural networks that account for the heterogeneous characteristics and imperfect rationality in the decision-making process, and compare three policy scenarios in local green space provision. The results of the model illustrate the unequal effectiveness of green space policies among different social groups and different types of green space (i.e., urban parks, neighborhood parks, and community gardens), and the sensitivity analysis suggests the key factors in different stages of green space provision. Based on the results, we argue that tailored policies are needed in order to meet residents’ heterogeneous needs; in fact, relatively “soft” policies, particularly those that promote social interaction and participation, play a significant role in the appeal of green space use. Finally, policy suggestions are provided for the optimization of green space provision.

Green Space and Mental Health outcomes: a cross-sectional survey as a starting point to bridge Green Areas' features to the post-pandemic needs

Abstract Background Green space has been associated with health and mental health. Given the high prevalence of mental disorders and costs of worldwide mental ill health and the concurrent rise in mental disorders during the pandemic, there is a need of a better understanding of the impact of different types of green space on mental health. The aim of this study was to assess the impact of characteristics of green space on mental health in a population in a rural area of Germany. Methods We conducted a cross-sectional survey based on face-to-face on an online assessment instrument. The instrument consisted of sociodemographic questions (assessing age, gender, income, education), mental health related question (PHQ - 9). Green space was dichotomized into green space with agrarian features and green space without agrarian features and subsequently geocoded using ATkis TN. Results In total n = 484 persons participated (female: 240 (49, 6%), male: N = 239 (49, 9%), n= missing). Mean age was 58,17 years (SD: 18,83) with an age range of 19-96 years. Depression symptoms showed n = 122 (54.9%) persons. Green space without agrarian features was associated with lower symptom levels of depression (Beta: 0.045, SE: 0.023, p = 0.015). However, green space with agrarian features was not related to depression. Discussion Characteristics of green spaces are associated with better mental health; however, the clear definition of quality green space needs further elaboration. The sample is a rural sample and results need further validation in an urban sample. Outlook: In the post-pandemic era green space itself seems to have no impact on mental health, however quality green space does. These results need further validation in multinational studies.

Associations between green space, air pollution and birthweight in Sydney Metropolitan Area, Australia

BACKGROUND AND AIM: Low birthweight is one of the most common pregnancy complications. Previous studies have shown that while higher quantities of green space are associated with higher birthweights, exposure to ambient air pollution is associated with lower birthweights. These results might be related since green space is theorized to buffer air pollution harms; however, evidence of interactions between these exposures on birthweight remains inadequate. Therefore, aim of this study was to investigate how the association between air pollution (NO2, PM2.5, SO2 and O3) term birthweight is affected by quantity of green space. METHODS: 79,430 births recorded in Sydney in 2016 and 2017 were included in the analysis. Multilevel linear regression with random intercepts for statistical area level 2 (SA2) were developed to assess association between air pollutants and birthweight. Furthermore, interaction terms between air pollutants and green space quantity were fitted in the model to examine potential effect modification. RESULTS:Higher PM2.5, NO2 and SO2 was associated with lower birthweight, while increase in O3 exposure was associated with higher birthweight (all p0.05). Higher green space quantity was associated with lower birthweight (p0.05). Interactions between green space quantity and NO2 and PM2.5 were identified (p0.05), indicating that increasing green space may help to mitigate harms of moderate levels of NO2 and PM2.5 on birthweight. CONCLUSIONS:Improving access to green spaces in cities may help support a healthy start in life by mitigating harms from certain air pollutants. Replication in different contexts and consideration of potentially contrasting results with different types of green space should be further investigated. KEYWORDS: Green space, Birth outcomes, air pollution