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

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 (ß = < 0.0001, 95% CI: 0.0000, 0.0000; ß = 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 ß 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.

Visiting nature is associated with lower socioeconomic inequalities in well-being in Wales.

Natural environments can promote well-being through multiple mechanisms. Many studies have investigated relationships between residential green/blue space (GBS) and well-being, fewer explore relationships with actual use of GBS. We used a nationally representative survey, the National Survey for Wales, anonymously linked with spatial GBS data to investigate associations of well-being with both residential GBS and time in nature (N = 7631). Both residential GBS and time spent in nature were associated with subjective well-being. Higher green-ness was associated with lower well-being, counter to hypotheses (predicting the Warwick and Edinburgh Mental Well-Being Scale (WEMWBS): Enhanced vegetation index ß = - 1.84, 95% confidence interval (CI) - 3.63, - 0.05) but time spent in nature was associated with higher well-being (four hours a week in nature vs. none ß = 3.57, 95% CI 3.02, 4.13). There was no clear association between nearest GBS proximity and well-being. In support of the equigenesis theory, time spent in nature was associated with smaller socioeconomic inequalities in well-being. The difference in WEMWBS (possible range 14-70) between those who did and did not live in material deprivation was 7.7 points for those spending no time in nature, and less at 4.5 points for those spending time in nature up to 1 h per week. Facilitating access and making it easier for people to spend time in nature may be one way to reduce socioeconomic inequalities in well-being.

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.

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 outdoorsâ€…× 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.

We investigated whether people who live near or visit green (parks, woodlands) and blue (riversides, beaches) spaces have fewer common mental health disorders (anxiety or depression), and better well-being. We considered whether changes in the amount of green and blue space around the home affected people's mental health. We assessed the availability of local green and blue spaces. Annual exposure and access to local green and blue spaces were extracted from planning and satellite data. We linked these data to anonymised health records of 2,801,483 adults registered with a general practice from 2008 to 2019, and to survey answers about leisure visits to natural environments and well-being. We found: people who lived in greener and bluer areas were less likely to seek help for a common mental health disorder than those in less green or blue areas, with those living in the most deprived areas benefiting the most people who used green and blue spaces for leisure, especially those with the greatest levels of deprivation, had better well-being and were less likely to seek help for common mental health disorders no evidence that changing amounts of green and blue space affected how likely people were to seek help for common mental health disorders; this may be because we found mostly small changes in green and blue space, and we may not have allowed enough time between moving home and recording mental health. We found evidence for relationships between green and blue space and mental health. However, some analyses were restricted due to lack of data on changes in green and blue spaces. An important finding was that people in deprived communities appear to benefit the most. Provision of green and blue spaces could be a strategy to improve the mental health of people living in disadvantaged areas.

COVID-19 mitigation measures in primary schools and association with infection and school staff wellbeing: An observational survey linked with routine data in Wales, UK.

INTRODUCTION: School-based COVID-19 mitigation strategies have greatly impacted the primary school day (children aged 3-11) including: wearing face coverings, two metre distancing, no mixing of children, and no breakfast clubs or extra-curricular activities. This study examines these mitigation measures and association with COVID-19 infection, respiratory infection, and school staff wellbeing between October to December 2020 in Wales, UK. METHODS: A school staff survey captured self-reported COVID-19 mitigation measures in the school, participant anxiety and depression, and open-text responses regarding experiences of teaching and implementing measures. These survey responses were linked to national-scale COVID-19 test results data to examine association of measures in the school and the likelihood of a positive (staff or pupil) COVID-19 case in the school (clustered by school, adjusted for school size and free school meals using logistic regression). Linkage was conducted through the SAIL (Secure Anonymised Information Linkage) Databank. RESULTS: Responses were obtained from 353 participants from 59 primary schools within 15 of 22 local authorities. Having more direct non-household contacts was associated with a higher likelihood of COVID-19 positive case in the school (1-5 contacts compared to none, OR 2.89 (1.01, 8.31)) and a trend to more self-reported cold symptoms. Staff face covering was not associated with a lower odds of school COVID-19 cases (mask vs. no covering OR 2.82 (1.11, 7.14)) and was associated with higher self-reported cold symptoms. School staff reported the impacts of wearing face coverings on teaching, including having to stand closer to pupils and raise their voices to be heard. 67.1% were not able to implement two metre social distancing from pupils. We did not find evidence that maintaining a two metre distance was associated with lower rates of COVID-19 in the school. CONCLUSIONS: Implementing, adhering to and evaluating COVID-19 mitigation guidelines is challenging in primary school settings. Our findings suggest that reducing non-household direct contacts lowers infection rates. There was no evidence that face coverings, two metre social distancing or stopping children mixing was associated with lower odds of COVID-19 or cold infection rates in the school. Primary school staff found teaching challenging during COVID-19 restrictions, especially for younger learners and those with additional learning needs.

Built Environments And Child Health in WalEs and AuStralia (BEACHES): a study protocol.

INTRODUCTION: Childhood obesity and physical inactivity are two of the most significant modifiable risk factors for the prevention of non-communicable diseases (NCDs). Yet, a third of children in Wales and Australia are overweight or obese, and only 20% of UK and Australian children are sufficiently active. The purpose of the Built Environments And Child Health in WalEs and AuStralia (BEACHES) study is to identify and understand how complex and interacting factors in the built environment influence modifiable risk factors for NCDs across childhood. METHODS AND ANALYSIS: This is an observational study using data from five established cohorts from Wales and Australia: (1) Wales Electronic Cohort for Children; (2) Millennium Cohort Study; (3) PLAY Spaces and Environments for Children's Physical Activity study; (4) The ORIGINS Project; and (5) Growing Up in Australia: the Longitudinal Study of Australian Children. The study will incorporate a comprehensive suite of longitudinal quantitative data (surveys, anthropometry, accelerometry, and Geographic Information Systems data) to understand how the built environment influences children's modifiable risk factors for NCDs (body mass index, physical activity, sedentary behaviour and diet). ETHICS AND DISSEMINATION: This study has received the following approvals: University of Western Australia Human Research Ethics Committee (2020/ET000353), Ramsay Human Research Ethics Committee (under review) and Swansea University Information Governance Review Panel (Project ID: 1001). Findings will be reported to the following: (1) funding bodies, research institutes and hospitals supporting the BEACHES project; (2) parents and children; (3) school management teams; (4) existing and new industry partner networks; (5) federal, state and local governments to inform policy; as well as (6) presented at local, national and international conferences; and (7) disseminated by peer-reviewed publications.

Deriving household composition using population-scale electronic health record data-A reproducible methodology.

BACKGROUND: Physical housing and household composition have an important role in the lives of individuals and drive health and social outcomes, and inequalities. Most methods to understand housing composition are based on survey or census data, and there is currently no reproducible methodology for creating population-level household composition measures using linked administrative data. METHODS: Using existing, and more recent enhancements to the address-data linkage methods in the SAIL Databank using Residential Anonymised Linking Fields we linked individuals to properties using the anonymised Welsh Demographic Service data in the SAIL Databank. We defined households, household size, and household composition measures based on adult to child relationships, and age differences between residents to create relative age measures. RESULTS: Two relative age-based algorithms were developed and returned similar results when applied to population and household-level data, describing household composition for 3.1 million individuals within 1.2 million households in Wales. Developed methods describe binary, and count level generational household composition measures. CONCLUSIONS: Improved residential anonymised linkage field methods in SAIL have led to improved property-level data linkage, allowing the design and application of household composition measures that assign individuals to shared residences and allow the description of household composition across Wales. The reproducible methods create longitudinal, household-level composition measures at a population-level using linked administrative data. Such measures are important to help understand more detail about an individual's home and area environment and how that may affect the health and wellbeing of the individual, other residents, and potentially into the wider community.

Staff-pupil SARS-CoV-2 infection pathways in schools in Wales: a population-level linked data approach.

Background: Better understanding of the role that children and school staff play in the transmission of SARS-CoV-2 is essential to guide policy development on controlling infection while minimising disruption to children's education and well-being. Methods: Our national e-cohort (n=464531) study used anonymised linked data for pupils, staff and associated households linked via educational settings in Wales. We estimated the odds of testing positive for SARS-CoV-2 infection for staff and pupils over the period August- December 2020, dependent on measures of recent exposure to known cases linked to their educational settings. Results: The total number of cases in a school was not associated with a subsequent increase in the odds of testing positive (staff OR per case: 0.92, 95% CI 0.85 to 1.00; pupil OR per case: 0.98, 95% CI 0.93 to 1.02). Among pupils, the number of recent cases within the same year group was significantly associated with subsequent increased odds of testing positive (OR per case: 1.12, 95% CI 1.08 to 1.15). These effects were adjusted for a range of demographic covariates, and in particular any known cases within the same household, which had the strongest association with testing positive (staff OR: 39.86, 95% CI 35.01 to 45.38; pupil OR: 9.39, 95% CI 8.94 to 9.88). Conclusions: In a national school cohort, the odds of staff testing positive for SARS-CoV-2 infection were not significantly increased in the 14-day period after case detection in the school. However, pupils were found to be at increased odds, following cases appearing within their own year group, where most of their contacts occur. Strong mitigation measures over the whole of the study period may have reduced wider spread within the school environment.

Real-time spatial health surveillance: Mapping the UK COVID-19 epidemic.

Introduction The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Objectives The primary objective of this study was to develop a real-time geospatial surveillance system to monitor the spread of COVID-19 across the UK. Methods Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. Results We demonstrate that using a combination of crowd-sourced app data and sophisticated geo-statistical techniques it is possible to predict hot spots of COVID-19 at fine geographic scales, nationally. We are also able to produce estimates of their precision, which is an important pre-requisite to an effective control strategy to guard against over-reaction to potentially spurious features of 'best guess' predictions. Conclusion In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data.