School greenspace and myopia incidence and burden in Chinese children and adolescents: The Guangzhou children and adolescents cohort study.

Metrics representing exposure to the natural environment are widely used in environmental health-related studies. They are calculated using a variety of different data sources representing greenspace and a range of buffer sizes representing human interaction with the environment. Previous studies have identified issues relating to buffer distance and scaling effects on greenspace exposure assessments when using satellite image-derived metrics. We evaluate the spatial scale sensitivity of three common greenspace metrics (i.e., Normalised Difference Vegetation Index- NDVI, Leaf Area Index- LAI, and Land Use and Land Cover-LULC), using lacunarity analysis, as a scale-dependent measure of heterogeneity based on the principles of fractals. By producing a ‘lacunarity curve’ across multiple spatial scales, we defined the scale-variances for specific greenspace metrics, including the upper scale limit at which the metrics become invariant, approximately 640 m for Sentinel-2 and 480 m for Landsat-8. Each of the greenspace metrics we considered exhibited scale sensitivities, meaning that each is expected to have a different influence on the strength and significance of the statistical associations found between greenspace exposure and health depending on the spatial scale of analysis (e.g., buffer distance). Using lacunarity curves, we produced a novel composite, multi-scale greenspace ‘exposure index’ in which each input scale is weighted according to its relative scale sensitivity. We also created a multi-scale, multi-metric map combining the different vegetation measures while accounting for scale. We found that cumulative exposure gradients across a large urban conurbation are even more marked when using our multi-scale ‘exposure index’ maps compared to traditional approaches. Our multi-scale, composite greenspace ‘exposure index’ mapping techniques are not as vulnerable to scale effects as traditional approaches and can be readily transferred to the analysis of other environmental exposure variables such as air pollution.

Greenspace exposure in the period surrounding pregnancy may influence autism spectrum disorder (ASD) risk in offspring by reducing risk factors or mitigating effects through various pathways. Current research is limited but suggestive. We explored the association between greenspace exposure during pregnancy and ASD risk, assessing potential periods of susceptibility: 3 months preconception; first, second, and third trimester; and 3 months post-birth. We conducted a nested case-control study within the Nurses' Health Study II (NHSII), a US prospective cohort followed up biennially. Cases were children of NHSII participants who were maternally reported to have ASD (n = 245). Controls were randomly selected from the full cohort and frequency matched to cases by birth year (n = 1526). Greenspace exposure was assessed using the satellite-based normalized difference vegetation index (NDVI) measured within 270 m and 1230 m radial buffers of the residential address of participants. Temporally matched, time-linked NDVI was used to calculate greenspace exposure for each potential period of susceptibility. Multivariable adjusted logistic regression models were applied to obtain effect estimates. Greenspace exposure during pregnancy was inversely associated with ASD risk when NDVI was measured within a 270 m radial buffer of the residential address. Specifically, an interquartile range (0.144) increase in NDVI during the first trimester decreased the odds of ASD by 25% (odds ratio=0.75, 95% confidence interval: 0.56, 0.99) in a model adjusting for other time periods of exposure. There was no other 3-month exposure period significantly associated with ASD. Adjusting for PM2.5 did not change results. The analysis of NDVI measured within a 1230 m radial buffer showed weaker and inconsistent associations. This study found that greenspace exposure during pregnancy was inversely associated with ASD, with the first trimester being a critical exposure period. Implications for urban and city design provide compelling reasons to increase research in this field. Ours is the first study to report an inverse association between greenspace exposure during pregnancy and autism spectrum disorder risk in offspring that was specific to the first trimester. An interquartile range increase in satellite-based normalized difference vegetation index exposure (0.114) within a 270 m radial buffer of the residential address decreased the odds of ASD by 25% (odds ratio=0.75, 95% confidence interval: 0.56, 0.99). Future research is warranted to confirm these findings in other populations and explore the pathways by which greenspace may mitigate risk. Implications for urban and city design provide compelling reasons to increase research in this field.

Associations between green space and preterm birth: Windows of susceptibility and interaction with air pollution

BACKGROUND & AIM: Along with other environmental exposures, both neighbourhood walkability, and greenspace exposure and access have been linked to many diverse health benefits. Previous work has examined the spatial relationship of built and natural environments according to levels of neighbourhood deprivation; however, less is known about how these relationships may vary when different greenspace metrics are used. This work examines how normalized differences vegetation index (NDVI), tree canopy cover, green land cover, and park count metrics relate to walkability, and how these neighbourhood characteristics associate with both social and material deprivation. METHODS: Greenspace exposure was measured using NDVI, tree canopy cover, and green land cover, while park access was quantified by the number of designated public parks within 1000m and 400m network buffers for each six-digit postal-code centroid in Metro Vancouver, Canada. Local area deprivation was measured using the 2016 Material and Social Deprivation Index (MSDI). Pearson’s correlation coefficients were calculated to compare these neighbourhood characteristics. RESULTS: Walkability was positively associated with social deprivation (1000m r = 0.48; 400m r = 0.48, p < .01), while walkability has a weak inverse relationship with material deprivation (1000m r = -0.21, p < .01). Tree canopy was negatively related to both social (1000m r = -0.23, 400m r = -0.23, p < .01) and material deprivation (1000m r = -0.24, 400m r = -0.23, p < .01). In contrast, the relationship between park count and both deprivation measures was weak. CONCLUSION: In this study, areas with greater social and material deprivation tend to have less greenspace, but not necessarily less park access. The identification of neighbourhoods with higher material deprivation, low walkability, and low greenspace, may be prioritized by urban planners and decision makers as possible locations for additional greenspace allocation. KEYWORDS: greenspace, walkability, social deprivation, material deprivation

Understanding Modifiable Risk Factors for the Development of Myopia

Arthritis is a common health issue among middle-aged and older adults, significantly impacting their quality of life. While previous studies have explored various risk factors for arthritis, the relationship between green space exposure and arthritis risk remains underexplored. This study aims to investigate the correlation between green space exposure, as measured by the Normalized Difference Vegetation Index (NDVI), and arthritis risk among middle-aged and older adults in China using a cross-sectional approach. Data for the present study were extracted from the 2015 wave of the China Health and Retirement Longitudinal Study (CHARLS), focusing specifically on middle-aged and older adults aged 45 years and above. Greenness exposure was quantified using the NDVI. Generalized linear models were used to assess the association between NDVI and arthritis. Climatic variables (relative humidity, precipitation) and metabolic equivalents were evaluated as correlates and potential mediators of this relationship. The study included a total of 7,985 participants, of whom 3,519 had arthritis and 4,466 did not. In the fully adjusted model, NDVI showed a positive correlation with arthritis. Specifically, the odds ratio (OR) of arthritis for each interquartile range (IQR) increase in NDVI was 1.14 (95% CI: 1.02–1.27). Additionally, annual precipitation, annual relative humidity, and metabolic equivalents all showed positive associations with arthritis prevalence. Further mediation analysis indicated that annual precipitation significantly mediated the relationship between NDVI and arthritis, with a proportion mediated of 5.31%. Higher NDVI was associated with a higher prevalence of arthritis, and annual precipitation partly explained this association. The findings suggest that environmental factors, including greenery and climate, may be considered in future strategies aimed at understanding and addressing joint disease burdens. The study was approved by the Institutional Review Board of Peking University (Code: IRB00001052-11015) and conducted in accordance with the Declaration of Helsinki, with written informed consent obtained from all participants. • Based on CHARLS 2015 data, a per IQR increase in NDVI was associated with a 14% higher prevalence of arthritis. • Mediation analysis indicated that annual precipitation partially accounted for the observed association between NDVI and arthritis prevalence. • Regions with higher levels of green space may consider integrating environmental factors, such as greenery and climate, into joint disease prevention and management strategies.

Higher greenspace exposure is associated with a decreased risk of childhood asthma in Shanghai – A megacity in China

Muscle strength is closely related to chronic noncommunicable diseases; specifically, a decline in handgrip strength (HS) is predominant globally. Exposure to green space-built environment components used for health intervention-reportedly decreases the risk of certain diseases and all-cause mortality. However, evidence in this area is limited. We aimed to explore the association between green space exposure and muscle strength and ascertain the combined effect of physical activity and green space exposure on muscle strength. Data from 128,759 participants (aged 20-79 years) were obtained using a complex stratified multistage probability cluster sampling design. The green space was assessed as normalized difference vegetation index (NDVI) data for a 500-m buffer zone based on the geolocation information of sampling sites. We used a questionnaire to investigate transportation, occupation, physical activity, leisure-time exercise behaviors, and sedentary time within a usual week of the preceding year. The outcome was low relative HS, defined as HS-to-body weight ratio, and the percentage of men and women with relative HS in the lower third. We defined adequate physical activity as 150 min of moderate-intensity or 75 min of vigorous physical activity per week and calculated the weighted proportion of participants with insufficient physical activity. Categorical variables of NDVI and physical activity were used as exposure variables and their interrelationship was evaluated in a generalized linear mixed model (GLMM) to estimate the odds ratios (ORs) and 95% confidence intervals (95% CI). We measured interaction on an additive or multiplicative scale using a GLMM to test the interaction between green space exposure and physical activity. All analyses were performed for the total sample and subgroups (urban and rural). The high NDVI group had a lower risk of low relative HS than the low NDVI group (OR [95% CI]: 0.92 [0.88-0.95]). The sufficient physical activity group had a lower risk of low relative HS than the insufficient physical activity group (OR [95% CI]: 0.85 [0.81-0.88]). There was an interactive effect on the additive scale (relative excess risk owing to interaction: 0.29, 95% CI 0.22-0.36, p < 0.001) between green space exposure and physical activity. High NDVI and adequate physical activity were protective factors against low relative HS in Chinese adults. Increasing green space exposure and physical activity together may have a greater potentiating effect on muscle strength improvement than these two protective factors individually. Green spaces should be incorporated into city design or built environments.

Green space may be associated with obesity outcomes in children by promoting physical activity and reducing stress. However, previous studies have mostly used a single measure of green space and body mass index (BMI) as the sole indicator of adiposity. To examine associations of the satellite-based normalized difference vegetation index (NDVI) and street-view imagery-based green space metrics with comprehensive adiposity measures in children. The Project Viva cohort study observed participants from mid-childhood (mean [SD] age, 8.0 [0.8] years) and early adolescence (mean [SD] age, 13.3 [1.0] years) through late adolescence (mean [SD] age, 17.8 [0.7] years) between January 1, 2007, and December 31, 2021. This analysis included children with data on green space and adiposity measures. Data were analyzed from January 1 to June 30, 2024. Green space metrics (ie, percentage of trees, grass, and other green space) using street-view imagery and deep learning algorithms along with the NDVI were linked with participants' home addresses during mid-childhood and early adolescence. Body mass index (calculated as weight in kilograms divided by height in meters squared) and waist circumference z scores were calculated from anthropometric measurements during early and late adolescence. The total fat mass index (FMI; calculated as fat mass in kilograms divided by height in meters squared) and trunk FMI were obtained using dual-energy x-ray absorptiometry. Separate linear regression models adjusted for a child's age, sex, individual and neighborhood socioeconomic status, and population density estimated prospective associations of the NDVI and street-view green space (in mid-childhood or early adolescence) with 4 adiposity measures (in early or late adolescence). The sample included 843 children (mean [SD] age at mid-childhood, 7.9 [0.8] years; 423 girls [50.2%]) at baseline. After adjustment for confounders, a higher NDVI (per 1-SD increase) within 270 m in early adolescence was associated with lower z scores for BMI (-0.16 [95% CI, -0.27 to -0.04]) and waist circumference (-0.13 [95% CI, -0.23 to -0.03]), as well as a lower total FMI (-0.62 [95% CI, -1.02 to -0.23]) and trunk FMI (-0.33 [95% CI, -0.55 to -0.12]) in late adolescence. Higher percentages of street-view other green space (flowers, plants, and fields), but not street-view trees and grass, within 500 m in early adolescence were associated with lower BMI z scores (-0.09 [95% CI, -0.18 to -0.01) in late adolescence. The NDVI and street-view green space exposure at mid-childhood were not associated with adiposity measures in early adolescence. This cohort study of US children suggests that higher levels of satellite-based NDVI greenness and percentages of street-level green space components (flowers, plants, and fields) were associated with lower adiposity. The findings support the exploration of increasing residential green space levels and adding specific green space components as an urban planning and public health intervention strategy to combat the prevalence of childhood obesity in the US.

BACKGROUND &amp;#x26; AIM: Access and exposure to greenspace has been shown to promote mental and physical health; however, not all studies have found these benefits, with some studies reporting no association and others reporting associations with adverse health outcomes. It has been suggested that the use of diverse greenspace metrics, the varied quality of these metrics, and the specific methods used to quantify exposure or access, may contribute to these inconsistent findings. This project sought to compare the results of using different metrics in Metro Vancouver, Canada. METHODS: Greenspace metrics were calculated from the centroid of each 6-digit postal code. Average buffer normalized differences vegetation index (NDVI), green landcover, tree canopy cover, and park count were calculated using circular and network buffers, at both 400m and 1000m. Pearson’s correlation coefficients were calculated to compare the results for each metric and method. RESULTS: The number of parks was only weakly positively correlated with each of the other three greenspace metrics for 1000m circular buffers (NDVI r = 0.12; green land cover r = 0.07; tree canopy r = 0.14, p &amp;#x3c; .01). For 1000m network buffers (NDVI r = -0.34; green landcover r = -0.12; tree canopy r = 0.05, p &amp;#x3c; .01) two of the correlations became negative. Circular and network buffer were most highly correlated for the tree canopy (1000m r = 0.92; 400m r = 0.86, p &amp;#x3c; .01), whereas park count had the weakest correlation (1000m r = 0.66; 400m r = 0.66, p &amp;#x3c; .01). CONCLUSIONS: The associations between greenspace metrics vary. Selection of buffering method may be particularly influential when using park count data. These findings support the importance of intentional selection of greenspace metric and measurement method in environmental epidemiological research. KEYWORDS: greenspace metrics, NDVI, tree canopy cover, parks, network buffers, and circular buffers

BackgroundExposure to natural vegetation (ie, “greenspace”) is related to beneficial outcomes, including higher positive and lower negative affect, in individuals with and those without mental health concerns. Researchers have yet to examine dynamic associations between greenspace exposure and affect within individuals over time. Smartphone-based ecological momentary assessment (EMA) and passive sensors (eg, GPS, microphone) allow for frequent sampling of data that may reveal potential moment-to-moment mechanisms through which greenspace exposure impacts mental health.ObjectiveIn this study, we examined associations between greenspace exposure and affect (both self-reported and inferred through speech) in people with and those without schizophrenia spectrum disorder (SSD) at the daily level using smartphones.MethodsTwenty people with SSD and 14 healthy controls reported on their current affect 3 times per day over 7 days using smartphone-based EMA. Affect expressed through speech was labeled from ambient audio data collected via the phone’s microphone using Linguistic Inquiry and Word Count (LIWC). Greenspace exposure, defined as the normalized difference vegetation index (NDVI), was quantified based on continuous geo-location data collected from the phone’s GPS.ResultsOverall, people with SSD used significantly more positive affect words (P=.04) and fewer anger words (P=.04) than controls. Groups did not significantly differ in mean EMA-reported positive or negative affect, LIWC total word count, or NDVI exposure. Greater greenspace exposure showed small to moderate associations with lower EMA-reported negative affect across groups. In controls, greenspace exposure on a given day was associated with significantly lower EMA-reported anxiety on that day (b=–0.40, P=.03, 95% CI –0.76 to –0.04) but significantly higher use of negative affect words (b=0.66, P<.001, 95% CI 0.29-1.04). There were no significant associations between greenspace exposure and affect at the daily level among participants with SSD.ConclusionsOur findings speak to the utility of passive and active smartphone assessments for identifying potential mechanisms through which greenspace exposure influences mental health. We identified preliminary evidence that greenspace exposure could be associated with improved mental health by reducing experiences of negative affect. Future directions will focus on furthering our understanding of the relationship between greenspace exposure and affect on individuals with and those without SSD.

BACKGROUND AND AIM Early life exposure to greenspace is associated with health benefits on childhood development, but the pathways of this relationship are not completely understood. This study aimed to evaluate early life exposure to different greenspace metrics on the development on autism spectrum disorder (ASD) and whether these associations are mediated by reductions in ambient air pollution. METHODS This case-control study included 1,801 ASD cases and 9002 controls less than 5 years of age identified from 2012 to 2017 using health administrative databases in the province of Ontario, Canada. Greenspace metrics were estimated using the Normalized Difference Vegetation Index (NDVI), Green View Index (GVI) and percent tree canopy coverage using values within 250 m of participants' residential postal codes at birth. Conditional logistic regression was used to investigate associations between greenspace exposure and ASD while adjusting for maternal age, parity, maternal comorbidities, substance use (i.e. smoking and alcohol), socioeconomic status and urbanicity. We estimated the mediation effects of nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) using causal mediation analyses. RESULTS In the adjusted model, we found that one interquartile range (IQR) increase in percentage tree canopy was associated with a 6% reduction in the odds of ASD (Odds ratio = 0.94; 95% CI: 0.90, 0.98). No associations were found for NDVI and GVI in relation to ASD. We found that 81.8% (77.6 – 85.9), 20.1% (16.6 – 23.6) and 13.6% (11.1 – 16.0) of the association between tree canopy exposure and ASD was mediated through reductions in NO2, PM2.5, and O3, respectively. CONCLUSIONS Early life exposure to greenspace might reduce the risk of ASD through reductions in ambient air pollution, in particular traffic pollution from NO2. Our findings may provide support to communities on the potential health benefits of greenspaces.

The association between allergic respiratory diseases, such as asthma and allergic rhinitis (AR), and green space (GS) remains controversial. Our study aimed to summarize and synthesize the association between individual GS exposure and the incidence of asthma/AR. We systematically summarized the qualitative relationship between GS exposure and asthma and AR. The pooled odds ratio (OR) with 95% confidence intervals (CIs) was used to estimate the effect of the Normalized Difference Vegetation Index (NDVI) on asthma and AR. A total of 21 studies were included for systematic review, and 8 of them underwent meta-analysis. In the meta-analysis of current asthma, the 0 < radius ≤ 100m group, 100 < radius ≤ 300m group, and 500 < radius ≤ 1000m group presented weak negative associations between the NDVI and current asthma. For ever asthma, slight positive associations existed in the 0 < radius ≤ 100m group and 300 < radius ≤ 500m group. In addition, the NDVI might slightly reduce the risk of AR in radius of 100m and 500m. Our findings suggest that the effects of GS exposure on asthma and AR were not significant. Differences in GS measurements, disease diagnoses and adjusted confounders across studies may have an impact on the results. Subsequent studies should consider potential confounding factors and use more accurate GS exposure measurements to better understand the impact of GS exposure on respiratory disease in the population.

Green space exposure and blood DNA methylation at birth and in childhood – A multi-cohort study

Sensitive months for green spaces' impact on macrosomia and interaction with air pollutants: A birth cohort study.