OBJECTIVE: To examine the associaiton between environmental measures and brain volumes and its potential mediators.
METHODS: This was a prospective study.
METHODS: Our analysis included 34,454 participants (53.4% females) aged 40-73 years at baseline (between 2006 and 2010) from the UK Biobank. Brain volumes were measured using magnetic resonance imaging between 2014 and 2019.
RESULTS: Greater proximity to greenspace buffered at 1000 m at baseline was associated with larger volumes of total brain measured 8.8 years after baseline assessment (standardized β (95% CI) for each 10% increment in coverage: 0.013(0.005,0.020)), grey matter (0.013(0.006,0.020)), and white matter (0.011(0.004,0.017)) after adjustment for covariates and air pollution. The corresponding numbers for natural environment buffered at 1000 m were 0.010 (0.004,0.017), 0.009 (0.004,0.015), and 0.010 (0.004,0.016), respectively. Similar results were observed for greenspace and natural environment buffered at 300 m. The strongest mediator for the association between greenspace buffered at 1000 m and total brain volume was smoking (percentage (95% CI) of total variance explained: 7.9% (5.5-11.4%)) followed by mean sphered cell volume (3.3% (1.8-5.8%)), vitamin D (2.9% (1.6-5.1%)), and creatinine in blood (2.7% (1.6-4.7%)). Significant mediators combined explained 18.5% (13.2-25.3%) of the association with total brain volume and 32.9% (95% CI: 22.3-45.7%) of the association with grey matter volume. The percentage (95% CI) of the association between natural environment and total brain volume explained by significant mediators combined was 20.6% (14.7-28.1%)).
CONCLUSIONS: Higher coverage percentage of greenspace and environment may benefit brain health by promoting healthy lifestyle and improving biomarkers including vitamin D and red blood cell indices.

Exposure to natural environments may benefit child mental wellbeing whilst offering a lever to reduce health inequalities. However, understanding of these relationships is limited by evidence from indirect measures of exposure. We objectively measured children\'s direct use of natural environments-and use in low or high physical activity (PA) states-and associated this with their mental wellbeing. We then examined moderation by sex and household income. Using global positioning system and accelerometry data from children (n = 640), we measured mean daily time in natural environments (\'total use\'), which we stratified by PA level as \'passive use\' (sedentary and light PA) and \'active use\' (moderate and vigorous PA). Logistic regression associated exposures with dichotomised Strengths and Difficulties Questionnaire outcomes (internalising difficulties; externalising difficulties; prosocial behaviour), with interactions to examine moderation. A 10-minute increase in total use was associated with 10.5 % lower risk of abnormal internalising outcomes (OR: 0.895; 95 % CI 0.809, 0.990), and 13.2 % lower risk of abnormal externalising outcomes (OR: 0.868; 95 % CI 0.776, 0.990). This suggests that ∼ 60 min of daily total use was associated with 50 % lower risk of abnormal internalising and externalising outcomes. The relative effects of passive and active use were equal, but their associations were moderated by income independently for specific outcomes. For externalising outcomes, the risk of abnormal scores in lower-income children reduced as passive use increased (P = 0.027) but remained constant for higher-income children. For prosocial outcomes, the likelihood of normal scores increased with active use in lower-income children, but not higher-income children (P = 0.005). Sex did not moderate these associations. The findings suggest that targeted interventions supporting disadvantaged children to use natural environments could help address inequalities in mental wellbeing. Further, the moderated associations with types of use suggest the equigenic effects of natural environments may operate through multiple pathways.

Exploring the influence of green space characteristics and proximity on health via air pollution mitigation, our study analysed data from 1,365 participants across Porto, Nantes, Sofia, and Høje-Taastrup. Utilizing OpenStreetMap and the AID-PRIGSHARE tool, we generated nine green space indicators around residential addresses at 15 distances, ranging from 100m to 1500m. We performed a mediation analysis for these 135 green space variables and revealed significant associations between self-rated air pollution and self-rated health for specific green space characteristics. In our study, indirect positive effects on health via air pollution were mainly associated with green corridors in intermediate Euclidean distances (800-1,000m) and the amount of accessible green spaces in larger network distances (1,400-1,500m). Our results suggest that the amount of connected green spaces measured in intermediate surroundings seems to be a prime green space characteristic that could drive the air pollution mitigation pathway to health.

UNASSIGNED: Epidemiological studies commonly use residential addresses at birth to estimate exposures throughout pregnancy, ignoring residential mobility. Lack of consideration for residential mobility during pregnancy might lead to exposure misclassification that should be addressed in environmental epidemiology.
UNASSIGNED: We investigated potential exposure misclassification from estimating exposure during pregnancy by residence at delivery utilizing a prospective cohort of pregnant women in New York, United States (n = 1899; 2016-2019). We calculated exposure during pregnancy corresponding to each address for fine particles (PM2.5), temperature, and greenness (Enhanced Vegetation Index [EVI]).
UNASSIGNED: Twenty-two percent of participants moved at least once during pregnancy; 82.3% of movers changed residences during the second or third trimesters. Participants with better health, lower parity, and higher socioeconomic status were more likely to move. Exposures based on address at delivery rather than residential history overestimated exposure for PM2.5 (exposure error: range -5.7 to 4.6 µg/m3, average -0.6 µg/m3) and EVI (range -0.305 to 0.307, average -0.013), but not temperature. Overestimations were significantly larger for mothers with higher socioeconomic status. Our findings indicate that the error for prenatal exposure can occur when residential mobility is not considered and is disproportional by maternal characteristics.
UNASSIGNED: Epidemiological studies should consider residential mobility in exposure assessments based on geolocation when possible, and results based on mother\'s residence at birth should be interpreted with understanding of potential differential exposure misclassification.

BACKGROUND: Previous investigations have reported that individuals living in greener neighborhoods have better cardiovascular health. It is unclear whether the effects reported at large geographic scales persist when examined at an intra-neighborhood level. The effects of greenness have not been thoroughly examined using high-resolution metrics of greenness exposure, and how they vary with spatial scales of assessment or participant characteristics.
METHODS: We conducted a cross-sectional assessment of associations between blood pressure and multiple high-resolution measures of residential area greenness in spatially concentrated HEAL Study cohort of the Green Heart Project. We employed generalized linear models, accounting for individual-level covariates, to examine associations between different high-resolution measures of greenness and blood pressure among 667 participants in a 4 sq. mile contiguous neighborhood area in Louisville, KY.
RESULTS: In adjusted models, we observed significant inverse associations between residential greenness, measured by leaf area index (LAI), and systolic blood pressure (SBP) within 150-250 m and 500 m of homes, but not for Normalized Difference Vegetation Index (NDVI) or grass cover. Weaker associations were also found with diastolic blood pressure (DBP). Significant positive associations were observed between LAI and SBP among participants who reported being female, White, without obesity, non-exercisers, non-smokers, younger age, of lower income, and who had high nearby roadway traffic. We found few significant associations between grass cover and SBP, but an inverse association in those with obesity, but positive associations for those without obesity.
CONCLUSIONS: We found that leaf surface area of trees around participants home is strongly associated with lower blood pressure, with little association with grass cover. These effects varied with participant characteristics and spatial scales. More research is needed to test causative links between greenspace types and cardiovascular health and to develop population-, typology-, and place-based evidence to inform greening interventions.

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.
CONCLUSIONS: 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.

BACKGROUND: Cohort studies linking greenspace exposure to a lower risk of obesity-related cancer (ORC) are scarce. Existing evidence on site-specific cancers has predominantly relied on non-specific greenspace measures, including vegetation indices. We examined the associations of total greenspace, private residential gardens, and other greenspace types with the risk of being diagnosed with overall and site-specific ORC.
METHODS: We used data from the participants in the UK Biobank recruited between 2006 and 2010 and censored until December 31, 2016. We defined greenspace variables using Ordnance Survey MasterMap™ greenspace categories. The incidence of ORC was ascertained through data linkage to cancer registries. Hazard ratios (HRs) and 95 % confidence intervals (CIs) were estimated using Cox proportional hazard models and adjusted for covariates. We conducted mediation and modification analysis by physical activity, serum 25-hydroxyvitamin D [25(OH)D], and particulate matter air pollution with an aerodynamic diameter ≤ 2.5 (PM2.5) and nitrogen dioxide (NO2), as well as subgroup analysis by covariates.
RESULTS: Among 279,326 participants, 9550 developed ORC over a median follow-up period of 7.82 years. An increase in private residential gardens within a 100 m buffer was associated with a decreased risk of overall ORC (HR:0.92; 95 % CI: 0.88, 0.96), breast cancer (HR: 0.91; 95 % CI: 0.84, 0.98), and uterine cancer (HR:0.80; 95 % CI: 0.67, 0.96). There was no association between other greenspace types and ORC, except for uterine cancer. The association for ORC was partly mediated by NO2 and modified by physical activity levels, 25(OH)D, PM2.5, and NO2, and sociodemographic factors, including sex and neighbourhood socioeconomic status.
CONCLUSIONS: Increased exposure to private residential gardens may lower the risk of being diagnosed with obesity-related cancer, particularly breast and uterine cancer. Future studies might move beyond considering greenspace quantity to explore functional types of greenspace exposure that should be prioritized for targeted health intervention and cancer prevention.

BACKGROUND: The current understandings of the relationship between air pollution (AP), greenspace exposure and Parkinson\'s Disease (PD) remain inconclusive.
METHODS: We engaged 441,462 participants from the UK Biobank who were not diagnosed with PD. Utilizing Cox proportional hazard regression model, relationships between AP [nitrogen dioxide (NO2), and nitrogen oxides (NOX), particulate matter < 2.5 μm in aerodynamic diameter(PM2.5), coarse particulate matter between 2.5 μm and 10 μm in aerodynamic diameter(PM2.5-10), particulate matter < 10 μm in aerodynamic diameter(PM10)], greenspace exposure, and PD risk were determined independently. Our analyses comprised three models, adjusted for covariates, and affirmed through six sensitivity analyses to bolster the robustness of our findings. Moreover, mediation analysis was deployed to discern the mediating effect of AP between greenspaces and PD.
RESULTS: During a median follow-up of 12.23 years (5,574,293 person-years), there were 3,293 PD events. Each interquartile (IQR) increment in NO2 and PM10 concentrations were associated with 10% and 8% increase in PD onset risk, while the increases in NOX, PM2.5 and PM2.5-10 were not associated with PD risk. Additionally, greenspace may safeguard by reducing NO2 and PM10 levels, with the effect mediated by NO2 and PM10 in greenspace-PD relationship.
CONCLUSIONS: Our findings indicate that an IQR increase in ambient NO2 and PM10 concentrations was associated with risk of PD development, while other pollutants (NOX, PM2.5 and PM2.5-10) were not associated with PD risk. Firstly, we find that augmented exposure to greenspace was associated with the lower PD risk by reducing NO2 and PM10 levels.

UNASSIGNED: Sudden death accounts for approximately 10% of deaths among working-age adults and is associated with poor air quality. Objectives: To identify high-risk groups and potential modifiers and mediators of risk, we explored previously established associations between fine particulate matter (PM2.5) and sudden death stratified by potential risk factors.
UNASSIGNED: Sudden death victims in Wake County, NC, from 1 March 2013 to 28 February 2015 were identified by screening Emergency Medical Systems reports and adjudicated (n = 399). Daily PM2.5 concentrations for Wake County from the Air Quality Data Mart were linked to event and control periods. Potential modifiers included greenspace metrics, clinical conditions, left ventricular hypertrophy (LVH), and neutrophil-to-lymphocyte ratio (NLR). Using a case-crossover design, conditional logistic regression estimated the OR (95%CI) for sudden death for a 5 μg/m3 increase in PM2.5 with a 1-day lag, adjusted for temperature and humidity, across risk factor strata.
UNASSIGNED: Individuals having LVH or an NLR above 2.5 had PM2.5 associations of greater magnitude than those without [with LVH OR: 1.90 (1.04, 3.50); NLR > 2.5: 1.25 (0.89, 1.76)]. PM2.5 was generally less impactful for individuals living in areas with higher levels of greenspace.
UNASSIGNED: LVH and inflammation may be the final step in the causal pathway whereby poor air quality and traditional risk factors trigger arrhythmia or myocardial ischemia and sudden death. The combination of statistical evidence with clinical knowledge can inform medical providers of underlying risks for their patients generally, while our findings here may help guide interventions to mitigate the incidence of sudden death.

UNASSIGNED: PM2.5, NO2, and O3 contribute to the development of adverse pregnancy complications. While studies have investigated the independent effects of these exposures, literature on their combined effects is limited. Our objective was to study the multipollutant effects of PM2.5, NO2, and O3 on maternal systemic C-reactive protein (CRP) levels.
UNASSIGNED: We used data from 1170 pregnant women enrolled in the Maternal-Infant Research on Environmental Chemicals Study (MIREC) study in Canada. Air pollution exposures were assigned to each participant based on residential location. CRP was measured in third-trimester blood samples. We fit multipollutant linear regression models and evaluated the effects of air pollutant mixtures (14-day averages) using repeated-holdout Weighted Quantile Sum (WQS) regression and by calculating the Air Quality Health Index (AQHI).
UNASSIGNED: In multipollutant models adjusting for NO2, O3, and green space, each interquartile range (IQR) increase in 14-day average PM2.5 (IQR: 6.9 µg/m3) was associated with 27.1% (95% confidence interval [CI] = 6.2, 50.7) higher CRP. In air pollution mixture models adjusting for green space, each IQR increase in AQHI was associated with 37.7% (95% CI = 13.9, 66.5) higher CRP; and an IQR increase in the WQS index was associated with 78.6% (95% CI = 29.7, 146.0) higher CRP.
UNASSIGNED: PM2.5 has the strongest relationship of the individual pollutants examined with maternal blood CRP concentrations. Mixtures incorporating all three pollutants, assessed using the AQHI and WQS index, showed stronger relationships with CRP compared with individual pollutants and illustrate the importance of conducting multipollutant analyses.