Understanding the Differential Impact of Vegetation Measures on Modeling the Association between Vegetation and Psychotic and Non-Psychotic Disorders in Toronto, Canada

Current methodologies of greenspace exposure and mental health research-a scoping review

Introduction

Greenspaces can provide an important resource for human mental health. A growing body of literature investigates the interaction and the influence of diverse greenspace exposures. In order to gain a comprehensive understanding of the complex connection between greenspace and mental health, a variety of perspectives and methodological combinations are needed. The aim of this review is to assess the current methodologies researching greenspace and mental health.

Methods

A scoping review was conducted. Four electronic databases (Pubmed, Embase, PsycInfo, Web of Science) were searched for relevant studies. A wide range of greenspace and mental health keywords were included to provide a comprehensive representation of the body of research. Relevant information on publication characteristics, types of greenspaces, mental health outcomes, and measurements of greenspace exposure and mental health was extracted and assessed.

Results

338 studies were included. The included studies encompassed a multitude of methods, as well as outcomes for both greenspace and mental health. 28 combinations were found between seven categories each for greenspace and mental health assessment. Some pairings such as geoinformation systems for greenspace assessment and questionnaires investigating mental health were used much more frequently than others, implying possible research gaps. Furthermore, we identified problems and inconsistences in reporting of greenspace types and mental health outcomes.

Discussion

The identified methodological variety is a potential for researching the complex connections between greenspace and mental health. Commonly used combinations can provide important insights. However, future research needs to emphasize other perspectives in order to understand how to create living environments with mental health benefits. For this purpose, interdisciplinary research is necessary.

Residential greenness for mitigating impacts of extreme heat events on depression and supporting mental health

Background

Residential green spaces (RGS) are a crucial aspect of urban life, which provide residents with a positive living environment both for mental and physical well-being. However, extreme heat events caused by global warming and local urban heat island effects are threatening the public health of rapidly growing populations. This is especially true for mental health. Depression is a mental illness that can be impacted by extreme heat events, i.e., heatwaves.

Objective

This study aimed to investigate the potential for residential green spaces (RGS) to alleviate depression by reducing heat stress sensitivity during extreme heat events.

Methods

We conducted a literature review using scientometric analysis with CiteSpace to summarize existing research on the relationships between RGS, depression, and heatwaves. We proposed a conceptual framework for the relationship between RGS and depression, and that extreme heat events may be an important contributor to depression.

Results

Our review found that RGS can provide ecosystem services that lower ambient temperatures through evaporative cooling, radiation reflection, humidity regulation, and shading. Different types of RGS, i.e., small green spaces, green roofs, green walls, and street trees, have varying cooling capacities. The mechanisms by which RGS alleviate depression during heatwaves involve green space composition, exposure, physical activity, social contacts, and cohesion. And we proposed a conceptual framework for the relationship between RGS and depression, and that extreme heat events may be an important contributor to depression.

Conclusion

We present a multidimensional RGS evaluation roadmap to inform green space design for reducing depression during heatwaves. Establishing RGS multidimensional evaluation can guide future research on leveraging RGS to build resilience against extreme heat and improve public mental health.

Combining Deep Learning and Multi-Source GIS Methods to Analyze Urban and Greening Changes

Although many authors have observed a degradation in greening cover alongside an increase in the built-up areas, resulting in a deterioration of the essential environmental services for the well-being of ecosystems and society, few studies have measured how greening developed in its full spatiotemporal configuration with urban development using innovative remote sensing (RS) technologies. Focusing on this issue, the authors propose an innovative methodology for the analysis of the urban and greening changes over time by integrating deep learning (DL) technologies to classify and segment the built-up area and the vegetation cover from satellite and aerial images and geographic information system (GIS) techniques. The core of the methodology is a trained and validated U-Net model, which was tested on an urban area in the municipality of Matera (Italy), analyzing the urban and greening changes from 2000 to 2020. The results demonstrate a very good level of accuracy of the U-Net model, a remarkable increment in the built-up area density (8.28%) and a decline in the vegetation cover density (5.13%). The obtained results demonstrate how the proposed method can be used to rapidly and accurately identify useful information about urban and greening spatiotemporal development using innovative RS technologies supporting sustainable development processes.

Age- and Sex-Specific Association Between Vegetation Cover and Mental Health Disorders: Bayesian Spatial Study

BACKGROUND

Despite growing evidence that reduced vegetation cover could be a putative risk factor for mental health disorders, the age- and the sex-specific association between vegetation and mental health disorder cases in urban areas is poorly understood. However, with rapid urbanization across the globe, there is an urgent need to study this association and understand the potential impact of vegetation loss on the mental well-being of urban residents.

OBJECTIVE

This study aims to analyze the spatial association between vegetation cover and the age- and sex-stratified mental health disorder cases in the neighborhoods of Toronto, Canada.

METHODS

We used remote sensing to detect urban vegetation and Bayesian spatial hierarchical modeling to analyze the relationship between vegetation cover and mental health disorder cases. Specifically, an Enhanced Vegetation Index was used to detect urban vegetation, and Bayesian Poisson lognormal models were implemented to study the association between vegetation and mental health disorder cases of males and females in the 0-19, 20-44, 45-64, and ≥65 years age groups, after controlling for marginalization and unmeasured (latent) spatial and nonspatial covariates at the neighborhood level.

RESULTS

The results suggest that even after adjusting for marginalization, there were significant age- and sex-specific effects of vegetation on the prevalence of mental health disorders in Toronto. Mental health disorders were negatively associated with the vegetation cover for males aged 0-19 years (-7.009; 95% CI -13.130 to -0.980) and for both males (-4.544; 95% CI -8.224 to -0.895) and females (-3.513; 95% CI -6.289 to -0.681) aged 20-44 years. However, for older adults in the 45-64 and ≥65 years age groups, only the marginalization covariates were significantly associated with mental health disorder cases. In addition, a substantial influence of the unmeasured (latent) and spatially structured covariates was detected in each model (relative contributions>0.7), suggesting that the variations in area-specific relative risk were mainly spatial in nature.

CONCLUSIONS

As significant and negative associations between vegetation and mental health disorder cases were found for young males and females, investments in urban greenery can help reduce the future burden of mental health disorders in Canada. The findings highlight the urgent need to understand the age-sex dynamics of the interaction between surrounding vegetation and urban dwellers and its subsequent impact on mental well-being.