Association Between Surrounding Greenness and Schizophrenia: A Taiwanese Cohort Study

Associations between residential environments and late-onset schizophrenia in UK Biobank: Interaction with genetic risk factor

BACKGROUND

Environment and genes both contribute to schizophrenia. However, the impact of different natural environments surrounding residential addresses on schizophrenia in urban settings remains unknown. This study aimed to investigate the association of urbanisation, measured by residential environments, with late-onset schizophrenia and explore whether genetic risk for schizophrenia modified the associations.

METHODS

We examined the associations between residential environments and late-onset schizophrenia and its interaction with genetic risk factors in UK Biobank, followed from 2006 to 2010 (baseline) to Dec 2021. Residential environments, including greenspace, domestic garden, blue space, and total natural environment, were evaluated using land use coverage percentage. The polygenic risk score (PRS) of schizophrenia was derived using a Bayesian approach and adjusted it against ancestry. Cox proportional hazard regression model was used to assess the associations between per interquartile (IQR) increase of each type of residential environments and late-onset schizophrenia. Interactive effects of PRS and residential environments on late-onset schizophrenia were assessed on both additive and multiplicative scales.

RESULTS

A total of 393,680 participants were included in the analysis, with 844 cases of late-onset schizophrenia being observed after 12.8 years of follow-up. Within 300 m buffer surrounding the residential addresses, per interquartile increase in greenspace (31.5 %) and total natural environment (34.4 %) were both associated with an 11 % (HR = 0.89, 95 % CI 0.80, 0.99) lower risk of late-onset schizophrenia. Domestic garden and blue space did not show significant protective effects on late-onset schizophrenia. A strong dose-response relationship between schizophrenia PRS and schizophrenia was found, while no additive or multiplicative interaction effects were present between residential environments and PRS on late-onset schizophrenia.

CONCLUSION

Residential greenspace and total natural environment may protect against late-onset schizophrenia in older people regardless of genetic risk. These findings shed light on the prevention of schizophrenia and urban planning to optimise ecosystem benefits linked to schizophrenia.

Built environment and schizophrenia re-hospitalization risk in China: A cohort study

BACKGROUND

Built environment exposure, characterized by ubiquity and changeability, has the potential to be the prospective target of public health policy. However, little research has been conducted to explore its impact on schizophrenia. This study aimed to investigate the association between built environmentand and schizophrenia rehospitalization by simultaneously considering substantial built environmental exposures.

METHODS

We recruited eligible schizophrenia patients from Hefei, Anhui Province, China between 2017 and 2019. The main outcome for this study was the time interval until the first recurrent hospital admission occurred within one year after discharge. For each included subject, we estimated the built environment exposures, including population density, walkability, land use mix, green and blue space, public transportation accessibility and road traffic indicator. Lasso (Least Absolute Shrinkage and Selection Operator) analysis was used to select the key variables. Multivariable Cox regression model was applied to obtain hazard ratio (HR) and its corresponding 95% confidence intervals (CI). Further, we also evaluated the joint effects of built environment characteristics on rehospitalization for schizophrenia by Quantile g-computation model.

RESULTS

A total of 1564 hospitalized schizophrenia patients were enrolled, with 347 patients (22.2%) had a rehospitalization within one-year after discharge. Multivariable Cox regression analysis indicated that the re-hospitalization rate for schizophrenia would be higher in areas with a high population density (HR: 1.10, 95%CI: 1.04-1.16). Nonetheless, compared to the reference (Q1), participants who lived in a neighborhood with the highest walkability and NDVI (Normalized Difference Vegetation Index) (Q4) had a 76% and 47% lower risk of re-hospitalization within one year (HR:0.24, 95%CI: 0.13-0.45; and 0.53, 95%CI:0.32-0.85), respectively. Moreover, quantile-based g-computation analyses revealed that increased walkability and green space significantly eliminated the adverse effects of population density increases on schizophrenia patients, with a HR ratio of 0.61 (95%CI:0.48,0.79) per one quartile change at the same time.

CONCLUSION

Our study provides scientific evidence for the significant role of built environment in schizophrenia rehospitalization, suggesting that optimizing the built environment is required in designing and building a healthy city.

Sunshine duration and risks of schizophrenia hospitalizations in main urban area: Do built environments modify the association?

BACKGROUND

Although studies have explored the relationship between sunshine duration and schizophrenia, the evidence was ambiguous. Different built environments may alter the effect of sunlight on schizophrenia, thus the purpose of this study was to investigate the effects of built environments on the sunshine duration-schizophrenia association.

MATERIALS AND METHODS

Daily schizophrenia hospitalizations data during 2017-2020 in Hefei's main urban area, China, and corresponding meteorological factors as well as ambient pollutants were collected. The impact of sunshine duration on schizophrenia admissions in urban areas was investigated using a generalized additive model combined with a distributed lagged nonlinear model. Additionally, the various modifying effects of different Building Density, Building Height, Normalized Vegetation Index, and Nighttime Light were also explored between sunshine duration and schizophrenia.

RESULTS

We observed that inadequate sunshine duration (<5.3 h) was associated with an increase in schizophrenia hospital admissions, with a maximum relative risk of 1.382 (95 % confidence interval (CI): 1.069-1.786) at 2.9 h. In turn, adequate sunshine duration reduced the risk of schizophrenia hospitalizations. Subgroup analyses indicated females and old patients were particularly vulnerable. In the case of insufficient sunshine duration, significant positive effects were noticed on schizophrenia risk at High-Building Density and High-Nighttime Light. Higher NDVI as well as Building Height were found to be associated with lower risks of schizophrenia.

CONCLUSIONS

Given that sunshine duration in various built environments might lead to distinct effects on schizophrenia hospitalizations. Our findings assist in identifying vulnerable populations that reside in particular areas, thus suggesting policymakers provide advice to mitigate the onset of schizophrenia by allocating healthcare resources rationally and avoiding adverse exposures to vulnerable populations timely.

Multivariate associations between cognition and neighborhood geospatial characteristics in schizophrenia

Cognitive impairment contributes to functional impairment in schizophrenia. Yet, little is known about how environmental characteristics are related to cognition in schizophrenia. By examining how cognition and the environment are intertwined, it may be possible to identify modifiable risk and protective factors that can improve cognitive outcomes in schizophrenia. We aimed to identify multivariate associations between cognition and three geospatial characteristics (built-space density, habitable green spaces, and public spaces for social interaction) within one's immediate neighborhood among individuals with schizophrenia. We recruited participants with schizophrenia from three sites - an urban metropolitan and two towns in southern India. We administered standard cognitive assessments and performed a principal axis factoring to identify episodic memory, cognitive control, and social inference-making factors for use in further analyses. We estimated geospatial characteristics of an individual's neighborhood, i.e., up to 1 km² around the residence, by sourcing data from Google Earth. We performed unconditional and conditional (to examine the effect of clinical covariates) canonical correlation analyses to understand the multivariate relationship between cognition and geospatial characteristics. We analyzed data from 208 participants; the first canonical cognitive variate (higher social inference-making and poorer cognitive control) shared 24% of the variance (r = 0.49; P < 0.001) with the first geospatial variate (lower built density and poorer access to public spaces). Years of education, age at onset, and place of residence significantly modulated this relationship. We observe differential associations of the built environment with social and non-social cognition in schizophrenia, and highlight the clinical and demographic characteristics that shape these associations.

Associations of residential greenness, ambient air pollution, biological sex, and glucocorticoids levels in rural China

AIMS

To evaluate the associations between residential greenness and glucocorticoid levels and whether air pollutants and sex modify the relationship between greenness and glucocorticoid level in Chinese rural adults.

METHODS

We collected cross-sectional survey data from 6055 participants from the Henan Rural cohort. The three-year average residential greenness for participants was assessed using normalized difference vegetation index (NDVI) values from a satellite platform. Liquid chromatography-tandem mass spectrometry was employed to quantify the concentrations of glucocorticoids, which were measured by morning blood draw after at least 8 hr of fasting. A random forest model was employed to obtain the average concentrations of PM₁, PM_2.5, and PM₁₀. A general linear regression model was performed to estimate the associations of NDVI_500-m values with cortisol, 11-deoxycortisol, and cortisone. Furthermore, interaction plots were used to present the interaction effects of particulate matter, sex, and green space on glucocorticoid levels.

RESULTS

After adjusting for multiple variables, an elevated average NDVI_500-m value in the total population was associated with a decrease in cortisol levels (β = -0.063, 95 % confidence interval (CI): - 0.118, - 0.008), and 11-deoxycortisol levels (β = -0.118, 95 % CI: -0.190, -0.047), as well as an increase in cortisone levels (β = 0.130, 95 % CI: 0.079, 0.181). By adding the interaction terms of air pollutants and residential greenness into the regression model, interaction effects between air pollutants and residential greenness were found (cortisol, PM_2.5: P interaction=:0.018; PM₁₀: P interaction=0.016; 11-deoxycortisol, all pollutants: P interaction< 0.001), suggesting that the protective effect of residential greenness on serum glucocorticoids disappeared accompanying with increased concentrations of particulate matter. Moreover, trends towards modification in the association between green space and glucocorticoid levels were also evident by sex, but these did not reach statistical significance (for all glucocorticoids: P interaction> 0.05).

CONCLUSION

Long-term exposure to green space was negatively correlated with cortisol and 11-deoxycortisol levels, and positively correlated with cortisone levels. There may be sex differences in these associations. Moreover, the protective effect of residential greenness on serum glucocorticoids was altered by high levels of particulate matter.

The association of hypertension and prehypertension with greenness and PM2.5 in urban environment

BACKGROUND

The interplay of air pollution and urban greenness on hypertension (HTN) is not fully understood.

METHODS

We conducted a cross-sectional study to explore the role of greenness and PM_2.5 on HTN for 40,375 adult residents in the New Taipei City, Taiwan. Normalized Difference Vegetation Index (NDVI) defined greenness and land use regression derived exposures of PM_2.5 were used to calculate odds ratios (ORs) of HTN in logistic regression models and common OR of normal to stage 3 HTN in ordinal logistic regression models. Linear regression model was used to evaluate the association between NDVI and blood pressures, including systolic (SBP), diastolic (DBP) and mean (MBP) pressures. The mediation and moderation analysis were used to assess the mediation and moderation effect of PM_2.5 on the association between greenness and SBP.

RESULTS

We found 37.3%, 21.4%, 8.2% and 2.7% of prehypertension and stage 1-3 hypertensions, respectively, for our study participants with annual PM_2.5 exposures of 10.96-43.59 μg/m³ living in an urban environment with NDVI within 500 m buffer ranging from -0.22 to 0.26. The ORs of HTN were 0.744 (95% CI: 0.698-0.793) for NDVI (quartile 4 vs. quartile 1) and 1.048 (1.012-1.085) for each IQR (8.69 μg/m³) increase in PM_2.5, respectively. The common OR of the higher level of 5 categories of BP was 1.1310 (1.241-1.383). With each IQR increase of NDVI (0.03), we found SBP, DBP and MBP were decreased by 0.78 mm Hg (-0.93-0.64), 0.52 mm Hg (-0.62-0.43) and 0.61 mm Hg (-0.71-0.51), respectively, in linear regression models. Stratified analysis found greenness effect was more prominent for people who are younger, female, never smoking, and without chronic diseases. PM_2.5 is moderated rather than mediated the association between greenness and SBP.

CONCLUSIONS

Greenness was associated with lower prevalence of prehypertension and all stages of HTN and this relationship was moderated by PM_2.5.

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.

Residential green space structures are associated with a lower risk of bipolar disorder: A nationwide population-based study in Taiwan

Although many researchers have identified the potential psychological benefits offered by greenness, the association between green space structures and mental disorders is not well understood. The purpose of this study was to identify associations between green space structures and the incidence of bipolar disorder. To this end, we investigated 1,907,776 individuals collected from Taiwan's National Health Insurance Research Database. After a follow-up investigation from 2005 to 2016, among those with no history of bipolar disorder, 20,548 individuals were further found to be diagnosed with bipolar disorder. A geographic information system and landscape index were used to quantify three indices of green space structures: mean patch area (area and edge), mean fractal dimension index (shape), and mean proximity index (proximity). Additionally, greenness indices, the normalized difference vegetation index, and the enhanced vegetation index were used to confirm the association between greenness and incidence of bipolar disorder. These five indices were used to represent the individual's exposure according to the township of the hospital that they most frequently visited with symptoms of the common cold. Spearman's correlation analysis was performed to select variables by considering their collinearity. Subsequently, the frailty model for each index was used to examine the specific associations between those respective indices and the incidence of bipolar disorder by adjusting for related risk factors, such as socioeconomic status, metabolic syndrome, and air pollution. A negative association was identified between the mean patch area and the mean proximity index, and the incidence of bipolar disorder. In contrast, a positive association was found between the mean fractal dimension index and the incidence of bipolar disorder. We observed similar results in sensitivity testing and subgroup analysis. Exposure to green spaces with a larger area, greater proximity, lower complexity, and greener area may reduce the risk of bipolar disorder.

Clinical Ecopsychology: The Mental Health Impacts and Underlying Pathways of the Climate and Environmental Crisis

Humankind is confronted with progressing climate change, pollution, environmental degradation, and/or destruction of the air, soil, water, and ecosystems. The climate and environmental crisis is probably one of the greatest challenges in the history of humankind. It not only poses a serious current and continuing threat to physical health, but is also an existing and growing hazard to the mental health of millions of people worldwide. This synergy of literature provides a current summary of the adverse mental health impacts of the climate and environmental crisis from the perspective of Clinical Psychology. Furthermore, it presents potential underlying processes, including biological, emotional, cognitive, behavioral, and social pathways. The existing data suggest that the climate and environmental crisis not only acts as a direct stressor, but can also exert a detrimental impact on the various pathways, with the potential to amplify an individual's biopsychosocial vulnerability to develop mental ill-health. This is a call for an increased investigation into this emerging research field of Clinical Ecopsychology by clinical psychologists and other researchers.

Earth Observation Data Supporting Non-Communicable Disease Research: A Review

A disease is non-communicable when it is not transferred from one person to another. Typical examples include all types of cancer, diabetes, stroke, or allergies, as well as mental diseases. Non-communicable diseases have at least two things in common—environmental impact and chronicity. These diseases are often associated with reduced quality of life, a higher rate of premature deaths, and negative impacts on a countries’ economy due to healthcare costs and missing work force. Additionally, they affect the individual’s immune system, which increases susceptibility toward communicable diseases, such as the flu or other viral and bacterial infections. Thus, mitigating the effects of non-communicable diseases is one of the most pressing issues of modern medicine, healthcare, and governments in general. Apart from the predisposition toward such diseases (the genome), their occurrence is associated with environmental parameters that people are exposed to (the exposome). Exposure to stressors such as bad air or water quality, noise, extreme heat, or an overall unnatural surrounding all impact the susceptibility to non-communicable diseases. In the identification of such environmental parameters, geoinformation products derived from Earth Observation data acquired by satellites play an increasingly important role. In this paper, we present a review on the joint use of Earth Observation data and public health data for research on non-communicable diseases. We analyzed 146 articles from peer-reviewed journals (Impact Factor ≥ 2) from all over the world that included Earth Observation data and public health data for their assessments. Our results show that this field of synergistic geohealth analyses is still relatively young, with most studies published within the last five years and within national boundaries. While the contribution of Earth Observation, and especially remote sensing-derived geoinformation products on land surface dynamics is on the rise, there is still a huge potential for transdisciplinary integration into studies. We see the necessity for future research and advocate for the increased incorporation of thematically profound remote sensing products with high spatial and temporal resolution into the mapping of exposomes and thus the vulnerability and resilience assessment of a population regarding non-communicable diseases.

Effects of surrounding environment on incidence of end stage renal disease

The rising prevalence and incidence of end-stage renal disease (ESRD) have been noted around the world. However, no study has been conducted to examine the effect of surrounding environment on incidence of ESRD. This study assessed the associations of exposure to PM2.5 level and surrounding green spaces, separately, with incidence of ESRD in Taiwan. Demographic and clinical data used in this study was retrieved from the National Health Insurance Research Database from 2003 to 2012. PM2.5 data collected from the Environmental Protection Administration of Taiwan and a hybrid land-use regression model was used to approximate long-term exposure to PM2.5. Percentage of exposure to surrounding green spaces was used to determine individual exposure level. Cox proportional hazards models with a generalized estimating equation were applied to investigate the effect of surrounding environment on incidence of ESRD. The results showed significant positive association between exposure to PM2.5 level and incidence of ESRD; but inverse association between exposure to surrounding green spaces and incidence of ESRD (adjusted hazard ratio (AHR) = 1.08, 95% CI: 1.00-1.15 for exposure to PM2.5 level; AHR = 0.90, 95%CI: 0.84-0.98 for surrounding green spaces). Together, the findings from this study have added suggestive evidence on the adverse effect of exposure to PM2.5 level and the beneficial effect of exposure to surrounding green spaces on the incidence of ESRD in a general population in Taiwan.

Association Between Childhood Green Space, Genetic Liability, and the Incidence of Schizophrenia

Childhood exposure to green space has previously been associated with lower risk of developing schizophrenia later in life. It is unclear whether this association is mediated by genetic liability or whether the 2 risk factors work additively. Here, we investigate possible gene-environment associations with the hazard ratio (HR) of schizophrenia by combining (1) an estimate of childhood exposure to residential-level green space based on the normalized difference vegetation index (NDVI) from Landsat satellite images, with (2) genetic liability estimates based on polygenic risk scores for 19 746 genotyped individuals from the Danish iPSYCH sample. We used information from the Danish registers of health, residential address, and socioeconomic status to adjust HR estimates for established confounders, ie, parents' socioeconomic status, and family history of mental illness. The adjusted HRs show that growing up surrounded by the highest compared to the lowest decile of NDVI was associated with a 0.52-fold (95% confidence interval [CI]: 0.40 to 0.66) lower schizophrenia risk, and children with the highest polygenic risk score had a 1.24-fold (95% CI: 1.18 to 1.30) higher schizophrenia risk. We found that NDVI explained 1.45% (95% CI: 1.07 to 1.90) of the variance on the liability scale, while polygenic risk score for schizophrenia explained 1.01% (95% CI: 0.77 to 1.46). Together they explained 2.40% (95% CI: 1.99 to 3.07) with no indication of a gene-environment interaction (P = .29). Our results suggest that risk of schizophrenia is associated additively with green space exposure and genetic liability, and provide no support for an environment-gene interaction between NDVI and schizophrenia.