Cohort Profile: The Green and Blue Spaces (GBS) and mental health in Wales e-cohort

Thompson, Daniel; Geary, Rebecca; Rowney, Francis M.; Fry, Richard; Watkins, Alan; Wheeler, Benedict W.; Mizen, Amy; Akbari, Ashley; Lyons, Ronan A; Stratton, Gareth; White, James; Rodgers, Sarah

doi:10.1093/ije/dyac080

Cited by 4 publications

(6 citation statements)

References 30 publications

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“…Lack of high-quality, comparable data on green space accessibility, availability and use in epidemiological studies and in the UK Biobank has resulted in little research into the causal mechanisms behind the relationship of exposure to green and blue space and health. [24, 37, 38] The ability to distinguish between types of green spaces, their position in the neighbourhood and their intended use can strengthen evidence-based research and inform public health practice. Outdoor green and blue spaces can be utilised to deliver targeted interventions to promote healthy lifestyles and prevent ill-health.…”

Section: Discussionmentioning

confidence: 99%

The Future is Green. Integrating Green and Blue Space Data from European Urban Atlas into UK Biobank

Geneshka

McClean

Gilbody

et al. 2022

Preprint

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BackgroundGreen and blue spaces can promote good physical and mental health and prevent the development of long-term conditions. Evidence suggests that not all green spaces affect health equally, and that certain types and properties of green spaces are stronger predictors of health than others. However, research into the causal mechanisms is limited in large cohorts due to lack of objective and comparable data on green space type, accessibility, and usage.MethodsWe used data from Urban Atlas to compute measures of urban park accessibility, street trees availability, and total green and blue space availability for 300,000 UK Biobank participants. Exposure metrics were computed using circular buffers with radii of 100 m to 3000 m. Pearson correlation coefficients and other descriptive statistical parameters were used to test agreement between variables and explore the utility of indictors in capturing different types of green spaces.ResultsStrong positive correlations were observed between variables of the same indicator with different buffer sizes. The presence of park and proportion of street tree canopy variables were negatively correlated with amount of total green space variables. This signifies distinct differences in type of green spaces captured by these variables.ConclusionsOverall, five distinct indicators of park accessibility, street trees availability, and total green and blue space availability have been integrated into a large sample of the UK Biobank. Our method is replicable to settings across Europe and facilitates evidence-based research on the roles of different green and blue spaces in health promotion and ill-health prevention.Key MessagesDifferent types of green spaces and their position in the neighbourhood can promote and protect health by mitigating pollution and increasing physical activity and socialisation.We present the methods of constructing and linking data on urban green spaces, street trees and natural vegetation into a large health cohort, the UK Biobank.The ability to distinguish between types of green spaces and their intended use can help inform public health interventions, influence urban policy, and aid urban planning in building sustainable and healthy cities.Our methods are transferable and will allow others to explore the links between environment and health in UK Biobank and other health cohorts.

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Section: Discussionmentioning

confidence: 99%

The Future is Green. Integrating Green and Blue Space Data from European Urban Atlas into UK Biobank

Geneshka

McClean

Gilbody

et al. 2022

Preprint

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“…The cross-sectional work reported in this paper was conducted as part of a wider longitudinal study called the Green-Blue Spaces project [45,50,51] where we developed a national level annual exposure variable for 1.49 million households over 11 years (2008-2019) using satellite derived EVI. Interpreting EVI scores in space and over time in relation to different types of green space was challenging and provoked us to conduct this cross-sectional evaluation to support the interpretation of the impacts of greenspace on mental health and wellbeing.…”

Section: Study Backgroundmentioning

confidence: 99%

“…Topographic vector data processing. We produced a UK-relevant typology to classify green spaces for urban and rural areas (supplementary material Table A, [45]). This addressed the need for typologies that facilitate crossdisciplinary and inter-sectoral work by developing a peer-reviewed typology of green space.…”

Section: Generating Exposure Datamentioning

confidence: 99%

“…However, VIs are a dimensionless measure of green reflectance and therefore may not be linearly associated with 2-dimensional measures of access to green space [43]. Recent studies have begun to acknowledge that there is a difference between greenness and green spaces when defining exposure to green space [11,44,45]. Despite this, there have been few attempts to examine the association between VIs and objective area-based measures of green space [27,46] to contribute to understanding what changes in mean VI values mean to policy makers and planners.…”

Section: Introductionmentioning

confidence: 99%

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The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies

Mizen,

Thompson,

Watkins

et al. 2024

J Expo Sci Environ Epidemiol

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Background Exposure to green space can protect against poor health through a variety of mechanisms. However, there is heterogeneity in methodological approaches to exposure assessments which makes creating effective policy recommendations challenging. Objective Critically evaluate the use of a satellite-derived exposure metric, the Enhanced Vegetation Index (EVI), for assessing access to different types of green space in epidemiological studies. Methods We used Landsat 5–8 (30 m resolution) to calculate average EVI for a 300 m radius surrounding 1.4 million households in Wales, UK for 2018. We calculated two additional measures using topographic vector data to represent access to green spaces within 300 m of household locations. The two topographic vector-based measures were total green space area stratified by type and average private garden size. We used linear regression models to test whether EVI could discriminate between publicly accessible and private green space and Pearson correlation to test associations between EVI and green space types. Results Mean EVI for a 300 m radius surrounding households in Wales was 0.28 (IQR = 0.12). Total green space area and average private garden size were significantly positively associated with corresponding EVI measures (β = < 0.0001, 95% CI: 0.0000, 0.0000; β = 0.0001, 95% CI: 0.0001, 0.0001 respectively). In urban areas, as average garden size increases by 1 m2, EVI increases by 0.0002. Therefore, in urban areas, to see a 0.1 unit increase in EVI index score, garden size would need to increase by 500 m2. The very small β values represent no ‘measurable real-world’ associations. When stratified by type, we observed no strong associations between greenspace and EVI. Impact It is a widely implemented assumption in epidiological studies that an increase in EVI is equivalent to an increase in greenness and/or green space. We used linear regression models to test associations between EVI and potential sources of green reflectance at a neighbourhood level using satellite imagery from 2018. We compared EVI measures with a ‘gold standard’ vector-based dataset that defines publicly accessible and private green spaces. We found that EVI should be interpreted with care as a greater EVI score does not necessarily mean greater access to publicly available green spaces in the hyperlocal environment.

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“…In addition, the cohort dataset is available to external researchers for collaborative research projects. 275 For further details about accessing the cohort, researchers will be able to contact saildatabank.com and Sarah Rodgers (ARCNWC@liverpool.ac.uk) for opportunities to collaborate with the original investigator team.…”

Section: Implications For Future Researchmentioning

confidence: 99%

Green–blue space exposure changes and impact on individual-level well-being and mental health: a population-wide dynamic longitudinal panel study with linked survey data

Geary,

Thompson,

Garrett

et al. 2023

Public Health Res

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Background Cross-sectional evidence suggests that living near green and blue spaces benefits mental health; longitudinal evidence is limited. Objectives To quantify the impact of changes in green and blue spaces on common mental health disorders, well-being and health service use. Design A retrospective, dynamic longitudinal panel study. Setting Wales, UK. Participants An e-cohort comprising 99,682,902 observations of 2,801,483 adults (≥ 16 years) registered with a general practice in Wales (2008–2019). A 5312-strong ‘National Survey for Wales (NSW) subgroup’ was surveyed on well-being and visits to green and blue spaces. Main outcome measures Common mental health disorders, general practice records; subjective well-being, Warwick–Edinburgh Mental Well-being Scale. Data sources Common mental health disorder and use of general practice services were extracted quarterly from the Welsh Longitudinal General Practice Dataset. Annual ambient greenness exposure, enhanced vegetation index and access to green and blue spaces (2018) from planning and satellite data. Data were linked within the Secure Anonymised Information Linkage Databank. Methods Multilevel regression models examined associations between exposure to green and blue spaces and common mental health disorders and use of general practice. For the National Survey for Wales subgroup, generalised linear models examined associations between exposure to green and blue spaces and subjective well-being and common mental health disorders. Results and conclusions Our longitudinal analyses found no evidence that changes in green and blue spaces through time impacted on common mental health disorders. However, time-aggregated exposure to green and blue spaces contrasting differences between people were associated with subsequent common mental health disorders. Similarly, our cross-sectional findings add to growing evidence that residential green and blue spaces and visits are associated with well-being benefits: Greater ambient greenness (+ 1 enhanced vegetation index) was associated with lower likelihood of subsequently seeking care for a common mental health disorder [adjusted odds ratio (AOR) 0.80, 95% confidence interval, (CI) 0.80 to 0.81] and with well-being with a U-shaped relationship [Warwick–Edinburgh Mental Well-being Scale; enhanced vegetation index beta (adjusted) –10.15, 95% CI –17.13 to −3.17; EVI2 beta (quadratic term; adj.) 12.49, 95% CI 3.02 to 21.97]. Those who used green and blue spaces for leisure reported better well-being, with diminishing extra benefit with increasing time (Warwick–Edinburgh Mental Well-being Scale: time outdoors (hours) beta 0.88, 95% CI 0.53 to 1.24, time outdoors2 beta −0.06, 95% CI −0.11 to −0.01) and had 4% lower odds of seeking help for common mental health disorders (AOR 0.96, 95% CI 0.93 to 0.99). Those in urban areas benefited most from greater access to green and blue spaces (AOR 0.89, 95% CI 0.89 to 0.89). Those in material deprivation benefited most from leisure time outdoors (until approximately four hours per week; Warwick–Edinburgh Mental Well-being Scale: time outdoors × in material deprivation: 1.41, 95% CI 0.39 to 2.43; time outdoors2 × in material deprivation −0.18, 95% CI −0.33 to −0.04) although well-being remained generally lower. Limitations Longitudinal analyses were restricted by high baseline levels and limited temporal variation in ambient greenness in Wales. Changes in access to green and blue spaces could not be captured annually due to technical issues with national-level planning datasets. Future work Further analyses could investigate mental health impacts in population subgroups potentially most sensitive to local changes in access to specific types of green and blue spaces. Deriving green and blue spaces changes from planning data is needed to overcome temporal uncertainties. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (Project number 16/07/07) and will be published in full in Public Health Research; Vol. 11, No. 10. Sarah Rodgers is part-funded by the NIHR Applied Research Collaboration North West Coast.

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Cohort Profile: The Green and Blue Spaces (GBS) and mental health in Wales e-cohort

Cited by 4 publications

References 30 publications

The Future is Green. Integrating Green and Blue Space Data from European Urban Atlas into UK Biobank

The Future is Green. Integrating Green and Blue Space Data from European Urban Atlas into UK Biobank

The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies

Green–blue space exposure changes and impact on individual-level well-being and mental health: a population-wide dynamic longitudinal panel study with linked survey data

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