The association between prenatal greenspace exposure and Autism spectrum disorder, and the potentially mediating role of air pollution reduction: A population-based birth cohort study

Associations of neighborhood greenspace, and active living environments with autism spectrum disorders: A matched case-control study in Ontario, Canada

BACKGROUND

Increasing evidence links early life residential exposure to natural urban environmental attributes and positive health outcomes in children. However, few studies have focused on their protective effects on the risk of autism spectrum disorder (ASD). The aim of this study was to investigate the associations of neighborhood greenspace, and active living environments during pregnancy with ASD in young children (≤6 years).

METHODS

We conducted a population-based matched case-control study of singleton term births in Ontario, Canada for 2012-2016. The ASD and environmental data was generated using the Ontario Autism Spectrum Profile, the Better Outcomes Registry & Network Ontario, and Canadian Urban Environmental Health Research Consortium. We employed conditional logistic regressions to estimate the odds ratio (OR) between ASD and environmental factors characterizing selected greenspace metrics and neighborhoods conducive to active living (i.e., green view index (GVI), normalized difference vegetation index (NDVI), tree canopy, park proximity and active living environments index (ALE)).

RESULTS

We linked 8643 mother-child pairs, including 1554 cases (18%). NDVI (OR 1.034, 0.944-1.024, per Inter Quartile Range [IQR] = 0.08), GVI (OR 1.025, 95% CI 0.953-1.087, per IQR = 9.45%), tree canopy (OR 0.992, 95% CI 0.903-1.089, per IQR = 6.24%) and the different categories of ALE were not associated with ASD in adjusted models for air pollution. In contrast, living closer to a park was protective (OR 0.888, 0.833-0.948, per 0.06 increase in park proximity index), when adjusted for air pollution.

CONCLUSIONS

This study reported mixed findings showing both null and beneficial effects of green spaces and active living environments on ASD. Further investigations are warranted to elucidate the role of exposure to greenspaces and active living environments on the development of ASD.

Environmental pollution and extreme weather conditions: insights into the effect on mental health

Environmental pollution exposures, including air, soil, water, light, and noise pollution, are critical issues that may implicate adverse mental health outcomes. Extreme weather conditions, such as hurricanes, floods, wildfires, and droughts, may also cause long-term severe concerns. However, the knowledge about possible psychiatric disorders associated with these exposures is currently not well disseminated. In this review, we aim to summarize the current knowledge on the impact of environmental pollution and extreme weather conditions on mental health, focusing on anxiety spectrum disorders, autism spectrum disorders, schizophrenia, and depression. In air pollution studies, increased concentrations of PM2.5, NO2, and SO2 were the most strongly associated with the exacerbation of anxiety, schizophrenia, and depression symptoms. We provide an overview of the suggested underlying pathomechanisms involved. We highlight that the pathogenesis of environmental pollution-related diseases is multifactorial, including increased oxidative stress, systematic inflammation, disruption of the blood-brain barrier, and epigenetic dysregulation. Light pollution and noise pollution were correlated with an increased risk of neurodegenerative disorders, particularly Alzheimer's disease. Moreover, the impact of soil and water pollution is discussed. Such compounds as crude oil, heavy metals, natural gas, agro-chemicals (pesticides, herbicides, and fertilizers), polycyclic or polynuclear aromatic hydrocarbons (PAH), solvents, lead (Pb), and asbestos were associated with detrimental impact on mental health. Extreme weather conditions were linked to depression and anxiety spectrum disorders, namely PTSD. Several policy recommendations and awareness campaigns should be implemented, advocating for the advancement of high-quality urbanization, the mitigation of environmental pollution, and, consequently, the enhancement of residents' mental health.

Greenspace, stress, and health: how is epigenetics involved?

Most expositions of the association between green space and overall health and well-being focus on psychosocial mechanisms. However, discussions of the biological underpinnings of the exposure to green space and health implications are limited. In this paper, we highlight the role epigenetics plays in the manifestation or suppression of stress, in addition to some of the proposed epigenetic mechanisms through which green space mitigates stress. The Health: Epigenetics, Greenspace and Stress (HEGS) model is introduced to explicate this association, and suggestions for research to build the evidence base in this area are discussed.

Exposure to greenness during pregnancy and the first three years after birth and autism spectrum disorder: A matched case-control study in shanghai, China

Causes of autism spectrum disorder (ASD) have not been fully understood. Previous studies have linked environmental factors with ASD. However, evidence for the greenness-ASD association is limited, especially in China. To fill this gap, we conducted a matched case-control study to examine the association between greenness and ASD in China. Participants in this study were 84,934 children aged 3-12 years in Shanghai, China, selected using a multi-stage cluster sampling method. ASD cases were firstly screened by questionnaires completed by both children's parents and teachers, and were then confirmed by clinical examinations. Further, 10 healthy controls were randomly selected to match each ASD case by age and sex. The final analyses included 146 ASD cases and 1460 healthy controls. Participants' exposure to greenness before and after birth was assessed by normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from NASA's Earth Observing System according to their residential locations. We used conditional logistic regression to examine the ASD-greenness association. Per interquartile range (IQR) increase in EVI500m and NDVI500m during the year before birth were associated with lower risks of ASD with adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of 0.96 (95%CI: 0.946, 0.975, IQR = 0.074) and 0.937 (95%CI: 0.915, 0.959, IQR = 0.101). Exposure to greenness during the first 3 years after birth was also significantly associated with lower risk of ASD [IQR ORs for EVI500m and NDVI500m were 0.935 (95%CI: 0.91, 0.962, IQR = 0.06) and 0.897 (95%CI: 0.861, 0.935, IQR = 0.09), respectively]. Air pollution showed mediation effects on thegreenness-ASD association. Greenness was observed to have stronger beneficial effects on children without historical diseases and term birth. More greenness exposure before and after birth were significantly associated with lower risks of ASD in children. Our results highlight the importance of greenness in urban planning.

Environmental Influences on Individuals with Autistic Spectrum Disorders with Special Emphasis on Seasonality: An Overview

This paper offers an in-depth exploration of the intricate relationship between environmental factors and autism spectrum disorder (ASD), with a special emphasis on seasonality. It reviews existing research, providing a comprehensive summary of findings and highlighting the multifaceted dimensions of several environmental factors influencing the etiology of ASD. The discussion encompasses various elements, including birth months, maternal health, dietary choices, and vitamin D deficiency, delving into the intricate interplay of seasonality with environmental influences such as viral infections and solar radiation. The present study raises essential questions regarding the timing of environmental influences and the factors contributing to the rising prevalence of ASD. Ultimately, it underscores the need for future epidemiological research to incorporate more extensive investigations of environmental risk factors and employ advanced statistical analyses. This comprehensive overview contributes to a deeper understanding of how environmental factors, particularly seasonality, may be linked to the occurrence of ASD and its increasing prevalence, recognizing the multifaceted and diverse nature of these interactions.

Reduction in the use of green spaces during the COVID-19 pandemic and its impact on mental health

Our study examined the use of green spaces before and during the pandemic in a large cohort of Italian twins and evaluated its impact on measures of mental health (depressive, anxiety, stress symptoms). Twins were analysed as individuals and as pairs. A twin design approach was applied to minimize confounding by genetic and shared environmental factors. Questionnaires from 2,473 twins enrolled in the Italian Twin Registry were screened. Reduced green space use was associated with significantly higher levels of depression, anxiety and distress. Being a woman, residing in urban areas, and having a high perceived risk of the outbreak resulted in a higher likelihood to modify green space use, with a negative impact on mental health.

Association between greenspace and cancer: evidence from a systematic review and meta-analysis of multiple large cohort studies

Cancer is a chronic disease that seriously endangers human health, and studies on its association with greenspace have been published. We aimed to systematically review the epidemiological evidence and obtain the best available evidence. PubMed, Web of Science, Embase, and Cochrane Library were used as search databases, the time limit was September 12, 2022, and the cited articles were manually supplemented. Two researchers independently performed literature screening and data extraction. We performed a meta-analysis of data using a normalized difference vegetation index (NDVI) as the greenspace measure, providing hazard ratio (HR) and corresponding 95% CI. After standardization of the data, we used a random effects model for pooling. We also assessed the risk of bias for each study and the quality of each evidence body. We identified 10,108 items and included 14 studies from 11 institutions in eight countries. All studies had a low risk of bias. Quantitative analysis of 13 studies found a beneficial association of greenspace with the mortality of lung cancer (pooled HR [95% CI]=0.965 [0.947, 0.983]) and prostate cancer (HR [95% CI]=0.939 [0.898, 0.980]) based on 0.1-unit NDVI increment and a potential beneficial association with the incidence of prostate, lung, and breast cancer. Greenspace had opposite associations with cancer mortality for urban and rural populations. Indirect comparisons did not find statistically significant differences in the effects of greenspace on different cancer outcomes. The evidence body assessment was considered to be "very low." This review indicated potential beneficial associations between greenspace for lung, prostate, and breast cancer outcomes. However, there was a lack of mediation analysis to explore the underlying mechanism of a causal association. Meanwhile, the interstudy heterogeneity was large. Therefore, future studies should consider more accurate exposure assessment and more comprehensive covariate coverage, while focusing on mediating analysis. PROSPERO: CRD42022361068.

The importance of data splitting in combined NOx concentration modelling

The polluted air breathed every day by those living in large conurbations poses a significant risk to their health. Through effective modelling (prediction) of concentrations of pollutants and identification of the factors influencing them, it should be possible to obtain advance information on dangers and to plan and implement measures to reduce them. This work describes two different modelling approaches: based on the NO_x concentration of the previous hour (C&RT models); and based on meteorological factors, traffic flow, and past (up to two previous hours) NO_x and NO₂ concentrations (CA models). For each approach, three alternative machine learning methods were applied: artificial neutral network (ANN), random forest (RF), and support vector regression (SVR). The best fits were obtained for the models using ANN and RF (MAPE values in the range 18.3-18.5 %). Poorer fits were found for the SVR models (MAPE equal to 23.4 % for the C&RT approach and 29.3 % for CA). No significant preferences were identified between the C&RT and CA approaches (based on various goodness-of-fit measures). The choice should be determined by the purposes for which the forecast is to be used.

Green space, air pollution and gestational diabetes mellitus: A retrospective cohort study in central China

Emerging evidence suggests residential surrounding green space is beneficial for human health. The association between green space and GDM showed inconsistent results, and potential effect modification of green space with air pollution is still unclear. This study aims to evaluate the association between green space and GDM, and further explore potential interaction and medication effects. Participants were recruited from a retrospective cohort study between 2015 and 2020 in Henan, China. Residential green space based on normalized difference vegetation index (NDVI) and air pollution exposure were estimated using spatial-statistical models. Multivariate logistic regression was applied to evaluate the association between per 0.1 unit increase in NDVI with 4 buffer sizes (250 m, 500 m, 1000 m, 2000 m) and GDM. We examined potential interaction of green space and air pollutants on GDM. Mediating effects of air pollution associated with green space exposure on GDM were also investigated by causal mediation analyses. A total of 46,665 eligible pregnant women were identified. There were 4092 (8.8 %) women diagnosed with GDM according to the IADPSG criteria. We found that per 0.1-unit increment in NDVI250 m, NDVI500 m, NDVI1000 m and NDVI2000 m in second trimester were associated with the decreased risk of GDM, with adjusted OR of 0.921(95 %CI: 0.890-0.953), 0.922 (95 %CI: 0.891-0.953), 0.921 (95 %CI: 0.892-0.952) and 0.921 (95 %CI: 0.892-0.951), respectively. We identified significant interactions between second trimester PM2.5 and O3 exposure and NDVI for GDM (Pinteraction < 0.001). The causal mediation analysis showed that PM2.5 mediated approximately 2.5-5.5 % of the association between green space and GDM, while the estimated mediating effect of O3 was approximately 30.1-38.5 %. In conclusion, our study indicates that residential green space was associated with a reduced risk of GDM, particularly second trimester. Green space may benefit to GDM partly mediated by a reduction in PM2.5 and O3.