Accumulating exposure to quality green space over time is posited to influence child health, yet longitudinal studies are scarce. This study aimed to examine the associations between trajectories of perceived green space quality and child health-related outcomes. We used data from 1874 childrenin the B-cohort of the Longitudinal Study of Australian Children who participated in the Child Health Checkpoint module at 11–12 years. Data on caregiver perceived green space quality measured biennially was assessed using discrete trajectory mixture models to group children by contrasting distributions in green space quality over time. Examination of associations between trajectory groups of perceived green space quality and child biomarkers (i.e., albumin-to-creatinine ratio, total, cholesterol, total triglycerides, and glucose), physical health and behavioural assessments (i.e., anthropometric measurements, blood pressure, sedentary behaviour, physical activity, sleep, aerobic work capacity, and general wellbeing), and health care use were assessed using multilevel models, adjusted for sociodemographic variables. Four perceived green space quality trajectories were identified: “decreasing quality from high to moderate”; “increasing quality from low to high”; “consistently high quality”; “consistently low quality”. Compared with consistently low levels of quality green space, adjusted models indicated consistently high-quality green space was associated with lower total triglycerides (β −0.13; 95%CI -0.25, −0.01). Lower odds of hospital admission was observed among children who accumulated quality green space over time (OR 0.45; 95%CI 0.23, 0.87). These associations were observed in boys only in sex-stratified analyses. Moreover, boys accumulating quality green space through time tended to have lower diastolic blood pressure (β −2.76; 95%CI -5.17, −0.35) and girls who experienced loss in quality green space tended to have a higher percentage of body fat (β 2.81; 95%CI 0.43, 5.20). Accumulating quality green space over time is important for various aspects of child health, with contrasting benefits by sex.

Urban Heat Island (UHI) is posing a significant challenge due to growing urbanisations across the world. Green infrastructure (GI) is popularly used for mitigating the impact of UHI, but knowledge on their optimal use is yet evolving. The UHI effect for large cities have received substantial attention previously. However, the corresponding effect is mostly unknown for towns, where appreciable parts of the population live, in Europe and elsewhere. Therefore, we analysed the possible impact of three vegetation types on UHI under numerous scenarios: baseline/current GI cover (BGI); hypothetical scenario without GI cover (HGI-No); three alternative hypothetical scenarios considering maximum green roofs (HGR-Max), grasslands (HG-Max) and trees (HT-Max) using a dispersion model ADMS-Temperature and Humidity model (ADMS-TH), taking a UK town (Guildford) as a case study area. Differences in an ambient temperature between three different landforms (central urban area, an urban park, and suburban residential area) were also explored. Under all scenarios, the night-time (0200 h; local time) showed a higher temperature increase, up to 1.315 °C due to the lowest atmospheric temperature. The highest average temperature perturbation (change in ambient temperature) was 0.563 °C under HGI-No scenario, followed by HG-Max (0.400 °C), BGI (0.343 °C), HGR-Max (0.326 °C) and HT-Max (0.277 °C). Furthermore, the central urban area experienced a 0.371 °C and 0.401 °C higher ambient temperature compared with its nearby suburban residential area and urban park, respectively. The results allow to conclude that temperature perturbations in urban environments are highly dependent on the type of GI, anthropogenic heat sources (buildings and vehicles) and the percentage of land covered by GI. Among all other forms of GI, trees were the best-suited GI which can play a viable role in reducing the UHI. Green roofs can act as an additional mitigation measure for the reduction of UHI at city scale if large areas are covered.

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NOₓ) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (¹⁵N and ¹⁸O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NOₓ. The capacity of urban trees for NOₓ removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m⁻² a⁻¹ across administrative regions, indicating that 1304 tons of NOₓ could be potentially removed by urban trees in 2019. Our finding qualified the potential NOₓ removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

Metabolic syndrome is an important risk factor for non-communicable diseases, particularly type 2 diabetes, coronary heart disease, and stroke. Long-term exposure to greenspace could be protective of metabolic syndrome, but evidence for such an association is lacking. Accordingly, we investigated the association between long-term exposure to greenspace and risk of metabolic syndrome.The present longitudinal study was based on data from four clinical examinations between 1997 and 2013 in 6076 participants of the Whitehall II study, UK (aged 45–69 years at baseline). Long-term exposure to greenspace was assessed by satellite-based indices of greenspace including Normalized Difference Vegetation Index (NDVI) and Vegetation Continuous Field (VCF) averaged across buffers of 500 and 1000 m surrounding the participants’ residential location at each follow-up. The ascertainment of metabolic syndrome was based on the World Health Organization (WHO) definition. Hazard ratios for metabolic syndrome were estimated using Cox proportional hazards regression models, controlling for age, sex, ethnicity, lifestyle factors, and socioeconomic status.Higher residential surrounding greenspace was associated with lower risk of metabolic syndrome. An interquartile range increase in NDVI and VCF in the 500 m buffer was associated with 13% (95% confidence interval (CI): 1%, 23%) and 14% (95% CI: 5%, 22%) lower risk of metabolic syndrome, respectively. Greater exposure to greenspace was also associated with each individual component of metabolic syndrome, including a lower risk of high levels of fasting glucose, large waist circumference, high triglyceride levels, low HDL cholesterol, and hypertension. The association between residential surrounding greenspace and metabolic syndrome may have been mediated by physical activity and exposure to air pollution.The findings of the present study suggest that middle-aged and older adults living in greener neighbourhoods are at lower risk of metabolic syndrome than those living in neighbourhoods with less greenspace.

A limited but emerging body of evidence is suggestive for a beneficial association between contact with green spaces and glucose homeostasis in adults; however, such an evidence for children is scarce. We evaluated the association between time spent in green spaces and fasting blood glucose (FBG) levels and impaired fasting glucose (IFG, FBG≥110 mg/dL) in a population-based multicentric sample of 3844 Iranian schoolchildren aged 7–18 years (2015). Participants were instructed to report the average hours per week spent in green spaces separately during each season and in each type of green space (parks, woods/other natural green spaces, and private gardens/agricultural field) for a 12-month period preceding the interview. We developed linear and logistic mixed effects models with centre as random effect to evaluate the association of time spent in green spaces (separately for each type as well as all types together) with FBG and IFG, respectively, controlled for a wide range of covariates including household indicators of socioeconomic status. We observed inverse associations between time spent in green spaces, especially in natural green spaces, and FBG levels. Specifically, 1.83 h increase in the total time spent in green spaces was associated with −0.5 mg/dl (95% confidence intervals: −0.9, −0.1) change in FBG levels. We also observed reduced risk of IFG associated with time spent in green spaces; however, the association was statistically significant only for the time spent in natural green spaces. There were suggestions for stronger associations for those residing in urban areas and those from lower socioeconomic status groups; however, the interaction terms for socioeconomic status and urbanity were not statistically significant. Further longitudinal studies are required to replicate our findings in other settings with different climates and population susceptibilities.

The aim of this study was to investigate the key landscape structures of migratory bird habitats that affect abundance of migratory birds to promote resilient coastal green infrastructure planning on the Yellow Sea coast. We classified coastal areas into four watersheds of South Korea and conducted multivariate regression analysis between migratory bird populations and landscape structures including total class area (CA), patch area distribution (MN), patch density (PD), and edge density (ED). At the national level, sandbank MN, sandbank CA, water ED, and grasslands were derived as key landscape structures affecting the abundance of migratory birds. At the watershed level, key landscape structures were determined as follows: Urban area_MN for the Han River watershed, rice paddy MN for the Asan watershed, rice paddy CA for Saemangeum, and grassland MN for the Youngsan River watershed. Considering the multifunctionality, redundancy, and connectivity of the resilience strategy, we provide specific coastal infrastructure planning recommendations at the national and watershed scales.

Floods are threats to ecosystems that are caused by natural disasters such as typhoons and heavy rain, and to respond to these threats, resilience needs to be improved. In this study, the response of the social-ecological system of Haeundae-gu (Busan, Republic of Korea) to disasters is analyzed by using a causal loop diagram, and a resilience improvement plan is presented by simulating the disaster resilience using green infrastructure through the System Resilience Dynamics Model. First, the resilience values are highest when green infrastructure is applied at the maximum applicable ratio (30%) compared with no application. Second, in the public and private areas of Haeundae-gu, resilience according to green roof scenario was higher until approximately 8 h after the beginning of rainfall, but then the resilience according to infiltration storage facility scenario was higher. In the transportation and industrial areas, the overall resilience according to infiltration storage facility scenario was higher than the resilience according to porous pavement scenario. This study demonstrates that a resilience improvement plan based on simulation can support decision making to respond to disasters such as typhoons.

The presence of urban greenspace may lead to reduced personal exposure to air pollution via several mechanisms, for example, increased dispersion of airborne particulates; however, there is a lack of real-time evidence across different urban contexts. Study participants were 79 adolescents with asthma who lived in Delhi, India and were recruited to the Delhi Air Pollution and Health Effects (DAPHNE) study. Participants were monitored continuously for exposure to PM₂.₅ (particulate matter with an aerodynamic diameter of less than 2.5 μm) for 48 h. We isolated normal day-to-day walking journeys (n = 199) from the personal monitoring dataset and assessed the relationship between greenspace and personal PM₂.₅ using different spatial scales of the mean Normalised Difference Vegetation Index (NDVI), mean tree cover (TC), and proportion of surrounding green land use (GLU) and parks or forests (PF). The journeys had a mean duration of 12.7 (range 5, 53) min and mean PM₂.₅ personal exposure of 133.9 (standard deviation = 114.8) μg/m³. The within-trip analysis showed weak inverse associations between greenspace markers and PM₂.₅ concentrations only in the spring/summer/monsoon season, with statistically significant associations for TC at the 25 and 50 m buffers in adjusted models. Between-trip analysis also indicated inverse associations for NDVI and TC, but suggested positive associations for GLU and PF in the spring/summer/monsoon season; no overall patterns of association were evident in the autumn/winter season. Associations between greenspace and personal PM₂.₅ during walking trips in Delhi varied across metrics, spatial scales, and season, but were most consistent for TC. These mixed findings may partly relate to journeys being dominated by walking along roads and small effects on PM₂.₅ of small pockets of greenspace. Larger areas of greenspace may, however, give rise to observable spatial effects on PM₂.₅, which vary by season.

An increasing body of evidence has linked greenspace and various health outcomes in children and adolescents, but the conclusions were inconsistent. For this review, we comprehensively summarized the measurement methods of greenspace, resultant health outcomes, and potential mechanisms from epidemiological studies in children and adolescents (aged ≤19 years). We searched for studies published and indexed in MEDLINE and EMBASE (via Ovid) up to April 11, 2022. There were a total of 9,291 studies identified with 140 articles from 28 countries finally assessed and included in this systematic review. Over 70% of the studies were conducted in highly urbanised countries/regions, but very limited research has been done in low-and middle-income countries and none in Africa. Measures of greenspace varied. Various health outcomes were reported, including protective effects of greenspace exposure on aspects of obesity/overweight, myopia, lung health, circulatory health, cognitive function, and general health in children and adolescents. The associations between greenspace exposure and other health outcomes were inconsistent, especially for respiratory health studies. We pooled odds ratios (OR) using random-effects meta-analysis for health outcomes of asthma (OR = 0.94, 95%CI: 0.84 to 1.06), allergic rhinitis (OR = 0.95; 95% CI: 0.73 to 1.25), and obesity/overweight (OR = 0.91, 95%CI: 0.84 to 0.98) with per 0.1 unit increase in normalized difference in vegetation index (NDVI). These associations have important implications for the assessment and management of urban environment and health in children and adolescents.

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.