Children and young people's body mass index measures derived from routine data sources: A national data linkage study in Wales.

BACKGROUND: Routine monitoring of Body Mass Index (BMI) in general practice, and via national surveillance programmes, is essential for the identification, prevention, and management of unhealthy childhood weight. We examined and compared the presence and representativeness of children and young people's (CYPs) BMI recorded in two routinely collected administrative datasets: general practice electronic health records (GP-BMI) and the Child Measurement Programme for Wales (CMP-BMI), which measures height and weight in 4-5-year-old school children. We also assessed the feasibility of combining GP-BMI and CMP-BMI data for longitudinal analyses. METHODS: We accessed de-identified population-level GP-BMI data for calendar years 2011 to 2019 for 246,817 CYP, and CMP-BMI measures for 222,772 CYP, held within the Secure Anonymised Information Linkage Databank. We examined the proportion of CYP in Wales with at least one GP-BMI record, its distribution by child socio-demographic characteristics, and trends over time. We compared GP-BMI and CMP-BMI distributions. We quantified the proportion of children with a CMP-BMI measure and a follow-up GP-BMI recorded at an older age and explored the representativeness of these measures. RESULTS: We identified a GP-BMI record in 246,817 (41%) CYP, present in a higher proportion of females (54.2%), infants (20.7%) and adolescents. There was no difference in the deprivation profile of those with a GP-BMI measurement. 31,521 CYP with a CMP-BMI had at least one follow-up GP-BMI; those with a CMP-BMI considered underweight or very overweight were 87% and 70% more likely to have at least one follow-up GP-BMI record respectively compared to those with a healthy weight, as were males and CYP living in the most deprived areas of Wales. CONCLUSIONS: Records of childhood weight status extracted from general practice are not representative of the population and are biased with respect to weight status. Linkage of information from the national programme to GP records has the potential to enhance discussions around healthy weight at the point of care but does not provide a representative estimate of population level weight trajectories, essential to provide insights into factors determining a healthy weight gain across the early life course. A second CMP measurement is required in Wales.

Development and external validation of the eFalls tool: a multivariable prediction model for the risk of ED attendance or hospitalisation with a fall or fracture in older adults.

BACKGROUND: Falls are common in older adults and can devastate personal independence through injury such as fracture and fear of future falls. Methods to identify people for falls prevention interventions are currently limited, with high risks of bias in published prediction models. We have developed and externally validated the eFalls prediction model using routinely collected primary care electronic health records (EHR) to predict risk of emergency department attendance/hospitalisation with fall or fracture within 1 year. METHODS: Data comprised two independent, retrospective cohorts of adults aged ≥65 years: the population of Wales, from the Secure Anonymised Information Linkage Databank (model development); the population of Bradford and Airedale, England, from Connected Bradford (external validation). Predictors included electronic frailty index components, supplemented with variables informed by literature reviews and clinical expertise. Fall/fracture risk was modelled using multivariable logistic regression with a Least Absolute Shrinkage and Selection Operator penalty. Predictive performance was assessed through calibration, discrimination and clinical utility. Apparent, internal-external cross-validation and external validation performance were assessed across general practices and in clinically relevant subgroups. RESULTS: The model's discrimination performance (c-statistic) was 0.72 (95% confidence interval, CI: 0.68 to 0.76) on internal-external cross-validation and 0.82 (95% CI: 0.80 to 0.83) on external validation. Calibration was variable across practices, with some over-prediction in the validation population (calibration-in-the-large, -0.87; 95% CI: -0.96 to -0.78). Clinical utility on external validation was improved after recalibration. CONCLUSION: The eFalls prediction model shows good performance and could support proactive stratification for falls prevention services if appropriately embedded into primary care EHR systems.

Uptake of COVID-19 vaccinations amongst 3,433,483 children and young people: meta-analysis of UK prospective cohorts.

SARS-CoV-2 infection in children and young people (CYP) can lead to life-threatening COVID-19, transmission within households and schools, and the development of long COVID. Using linked health and administrative data, we investigated vaccine uptake among 3,433,483 CYP aged 5-17 years across all UK nations between 4th August 2021 and 31st May 2022. We constructed national cohorts and undertook multi-state modelling and meta-analysis to identify associations between demographic variables and vaccine uptake. We found that uptake of the first COVID-19 vaccine among CYP was low across all four nations compared to other age groups and diminished with subsequent doses. Age and vaccination status of adults living in the same household were identified as important risk factors associated with vaccine uptake in CYP. For example, 5-11 year-olds were less likely to receive their first vaccine compared to 16-17 year-olds (adjusted Hazard Ratio [aHR]: 0.10 (95%CI: 0.06-0.19)), and CYP in unvaccinated households were less likely to receive their first vaccine compared to CYP in partially vaccinated households (aHR: 0.19, 95%CI 0.13-0.29).

Health care utilization and mortality for people with epilepsy during COVID-19: A population study.

OBJECTIVE: This study was undertaken to characterize changes in health care utilization and mortality for people with epilepsy (PWE) during the COVID-19 pandemic. METHODS: We performed a retrospective study using linked, individual-level, population-scale anonymized health data from the Secure Anonymised Information Linkage databank. We identified PWE living in Wales during the study "pandemic period" (January 1, 2020-June 30, 2021) and during a "prepandemic" period (January 1, 2016-December 31, 2019). We compared prepandemic health care utilization, status epilepticus, and mortality rates with corresponding pandemic rates for PWE and people without epilepsy (PWOE). We performed subgroup analyses on children (<18 years old), older people (>65 years old), those with intellectual disability, and those living in the most deprived areas. We used Poisson models to calculate adjusted rate ratios (RRs). RESULTS: We identified 27 279 PWE who had significantly higher rates of hospital (50.3 visits/1000 patient months), emergency department (55.7), and outpatient attendance (172.4) when compared to PWOE (corresponding figures: 25.7, 25.2, and 87.0) in the prepandemic period. Hospital and epilepsy-related hospital admissions, and emergency department and outpatient attendances all reduced significantly for PWE (and all subgroups) during the pandemic period. RRs [95% confidence intervals (CIs)] for pandemic versus prepandemic periods were .70 [.69-.72], .77 [.73-.81], .78 [.77-.79], and .80 [.79-.81]. The corresponding rates also reduced for PWOE. New epilepsy diagnosis rates decreased during the pandemic compared with the prepandemic period (2.3/100 000/month cf. 3.1/100 000/month, RR = .73, 95% CI = .68-.78). Both all-cause deaths and deaths with epilepsy recorded on the death certificate increased for PWE during the pandemic (RR = 1.07, 95% CI = .997-1.145 and RR = 2.44, 95% CI = 2.12-2.81). When removing COVID deaths, RRs were .88 (95% CI = .81-.95) and 1.29 (95% CI = 1.08-1.53). Status epilepticus rates did not change significantly during the pandemic (RR = .95, 95% CI = .78-1.15). SIGNIFICANCE: All-cause non-COVID deaths did not increase but non-COVID deaths associated with epilepsy did increase for PWE during the COVID-19 pandemic. The longer term effects of the decrease in new epilepsy diagnoses and health care utilization and increase in deaths associated with epilepsy need further research.

Epilepsy and the risk of COVID-19-related hospitalization and death: A population study.

OBJECTIVE: People with epilepsy (PWE) may be at an increased risk of severe COVID-19. It is important to characterize this risk to inform PWE and for future health and care planning. We assessed whether PWE were at higher risk of being hospitalized with, or dying from, COVID-19. METHODS: We performed a retrospective cohort study using linked, population-scale, anonymized electronic health records from the SAIL (Secure Anonymised Information Linkage) databank. This includes hospital admission and demographic data for the complete Welsh population (3.1 million) and primary care records for 86% of the population. We identified 27 279 PWE living in Wales during the study period (March 1, 2020 to June 30, 2021). Controls were identified using exact 5:1 matching (sex, age, and socioeconomic status). We defined COVID-19 deaths as having International Classification of Diseases, 10th Revision (ICD-10) codes for COVID-19 on death certificates or occurring within 28 days of a positive SARS-CoV-2 polymerase chain reaction (PCR) test. COVID-19 hospitalizations were defined as having a COVID-19 ICD-10 code for the reason for admission or occurring within 28 days of a positive SARS-CoV-2 PCR test. We recorded COVID-19 vaccinations and comorbidities known to increase the risk of COVID-19 hospitalization and death. We used Cox proportional hazard models to calculate hazard ratios. RESULTS: There were 158 (.58%) COVID-19 deaths and 933 (3.4%) COVID-19 hospitalizations in PWE, and 370 (.27%) deaths and 1871 (1.4%) hospitalizations in controls. Hazard ratios for COVID-19 death and hospitalization in PWE compared to controls were 2.15 (95% confidence interval [CI] = 1.78-2.59) and 2.15 (95% CI = 1.94-2.37), respectively. Adjusted hazard ratios (adjusted for comorbidities) for death and hospitalization were 1.32 (95% CI = 1.08-1.62) and 1.60 (95% CI = 1.44-1.78). SIGNIFICANCE: PWE are at increased risk of being hospitalized with, and dying from, COVID-19 when compared to age-, sex-, and deprivation-matched controls, even when adjusting for comorbidities. This may have implications for prioritizing future COVID-19 treatments and vaccinations for PWE.

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.

Risk of severe COVID-19 outcomes after autumn 2022 COVID-19 booster vaccinations: a pooled analysis of national prospective cohort studies involving 7.4 million adults in England, Northern Ireland, Scotland and Wales.

Background: UK COVID-19 vaccination policy has evolved to offering COVID-19 booster doses to individuals at increased risk of severe Illness from COVID-19. Building on our analyses of vaccine effectiveness of first, second and initial booster doses, we aimed to identify individuals at increased risk of severe outcomes (i.e., COVID-19 related hospitalisation or death) post the autumn 2022 booster dose. Methods: We undertook a national population-based cohort analysis across all four UK nations through linked primary care, vaccination, hospitalisation and mortality data. We included individuals who received autumn 2022 booster doses of BNT162b2 (Comirnaty) or mRNA-1273 (Spikevax) during the period September 1, 2022 to December 31, 2022 to investigate the risk of severe COVID-19 outcomes. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) for the association between demographic and clinical factors and severe COVID-19 outcomes after the autumn booster dose. Analyses were adjusted for age, sex, body mass index (BMI), deprivation, urban/rural areas and comorbidities. Stratified analyses were conducted by vaccine type. We then conducted a fixed-effect meta-analysis to combine results across the four UK nations. Findings: Between September 1, 2022 and December 31, 2022, 7,451,890 individuals ≥18 years received an autumn booster dose. 3500 had severe COVID-19 outcomes (2.9 events per 1000 person-years). Being male (male vs female, aHR 1.41 (1.32-1.51)), older adults (≥80 years vs 18-49 years; 10.43 (8.06-13.50)), underweight (BMI <18.5 vs BMI 25.0-29.9; 2.94 (2.51-3.44)), those with comorbidities (≥5 comorbidities vs none; 9.45 (8.15-10.96)) had a higher risk of COVID-19 hospitalisation or death after the autumn booster dose. Those with a larger household size (≥11 people within household vs 2 people; 1.56 (1.23-1.98)) and from more deprived areas (most deprived vs least deprived quintile; 1.35 (1.21-1.51)) had modestly higher risks. We also observed at least a two-fold increase in risk for those with various chronic neurological conditions, including Down's syndrome, immunodeficiency, chronic kidney disease, cancer, chronic respiratory disease, or cardiovascular disease. Interpretation: Males, older individuals, underweight individuals, those with an increasing number of comorbidities, from a larger household or more deprived areas, and those with specific underlying health conditions remained at increased risk of COVID-19 hospitalisation and death after the autumn 2022 vaccine booster dose. There is now a need to focus on these risk groups for investigating immunogenicity and efficacy of further booster doses or therapeutics. Funding: National Core Studies-Immunity, UK Research and Innovation (Medical Research Council and Economic and Social Research Council), Health Data Research UK, the Scottish Government, and the University of Edinburgh.

Prospective study design and data analysis in UK Biobank.

Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.

A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods.

OBJECTIVES: Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns. STUDY DESIGN AND SETTING: We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns. RESULTS: Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation. CONCLUSION: The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.

Using hypergraphs to quantify importance of sets of diseases by healthcare resource utilisation: A retrospective cohort study.

Rates of Multimorbidity (also called Multiple Long Term Conditions, MLTC) are increasing in many developed nations. People with multimorbidity experience poorer outcomes and require more healthcare intervention. Grouping of conditions by health service utilisation is poorly researched. The study population consisted of a cohort of people living in Wales, UK aged 20 years or older in 2000 who were followed up until the end of 2017. Multimorbidity clusters by prevalence and healthcare resource use (HRU) were modelled using hypergraphs, mathematical objects relating diseases via links which can connect any number of diseases, thus capturing information about sets of diseases of any size. The cohort included 2,178,938 people. The most prevalent diseases were hypertension (13.3%), diabetes (6.9%), depression (6.7%) and chronic obstructive pulmonary disease (5.9%). The most important sets of diseases when considering prevalence generally contained a small number of diseases, while the most important sets of diseases when considering HRU were sets containing many diseases. The most important set of diseases taking prevalence and HRU into account was diabetes & hypertension and this combined measure of importance featured hypertension most often in the most important sets of diseases. We have used a single approach to find the most important sets of diseases based on co-occurrence and HRU measures, demonstrating the flexibility of the hypergraph approach. Hypertension, the most important single disease, is silent, underdiagnosed and increases the risk of life threatening co-morbidities. Co-occurrence of endocrine and cardiovascular diseases was common in the most important sets. Combining measures of prevalence with HRU provides insights which would be helpful for those planning and delivering services.

Impact of an injury hospital admission on childhood academic performance: a Welsh population-based data linkage study.

BACKGROUND: While injuries can impact on children's educational achievements (with threats to their development and employment prospects), these risks are poorly quantified. This population-based longitudinal study investigated the impact of an injury-related hospital admission on Welsh children's academic performance. METHODS: The Secure Anonymised Information Linkage databank, 55 587 children residing in Wales from 2006 to 2016 who had an injury hospital admission (58.2% males; 16.8% born in most deprived Wales area; 80.1% one injury hospital admission) were linked to data from the Wales Electronic Cohort for Children. The primary outcome was the Core Subject Indicator reflecting educational achievement at key stages 2 (school years 3-6), 3 (school years 7-9) and 4 (school years 10-11). Covariates in models included demographic, birth, injury and school characteristics. RESULTS: Educational achievement of children was negatively associated with: pedestrian injuries (adjusted risk ratio, (95% CIs)) (0.87, (0.83 to 0.92)), cyclist (0.96, (0.94 to 0.99)), high fall (0.96, (0.94 to 0.97)), fire/flames/smoke (0.85, (0.73 to 0.99)), cutting/piercing object (0.96, (0.93 to 0.99)), intentional self-harm (0.86, (0.82 to 0.91)), minor traumatic brain injury (0.92, (0.86 to 0.99)), contusion/open wound (0.93, (0.91 to 0.95)), fracture of vertebral column (0.78, (0.64 to 0.95)), fracture of femur (0.88, (0.84 to 0.93)), internal abdomen/pelvic haemorrhage (0.82, (0.69 to 0.97)), superficial injury (0.94, (0.92 to 0.97)), young maternal age (<18 years: 0.91, (0.88 to 0.94); 19-24 years: 0.94, (0.93 to 0.96)); area based socioeconomic status (0.98, (0.97 to 0.98)); moving to a more deprived area (0.95, (0.93 to 0.97)); requiring special educational needs (0.46, (0.44 to 0.47)). Positive associations were: being female (1.04, (1.03 to 1.06)); larger pupil school sizes and maternal age 30+ years. CONCLUSION: This study highlights the importance on a child's education of preventing injuries and implementing intervention programmes that support injured children. Greater attention is needed on equity-focused educational support and social policies addressing needs of children at risk of underachievement, including those from families experiencing poverty. VIBES-JUNIOR STUDY PROTOCOL: http://dx.doi.org/10.1136/bmjopen-2018-024755.

The association of anxiety disorders and depression with facial scarring: population-based, data linkage, matched cohort analysis of 358 158 patients.

BACKGROUND: Estimates suggest that 1 in 100 people in the UK live with facial scarring. Despite this incidence, psychological support is limited. AIMS: The aim of this study was to strengthen the case for improving such support by determining the incidence and risk factors for anxiety and depression disorders in patients with facial scarring. METHOD: A matched cohort study was performed. Patients were identified via secondary care data sources, using clinical codes for conditions resulting in facial scarring. A diagnosis of anxiety or depression was determined by linkage with the patient's primary care general practice data. Incidence was calculated per 1000 person-years at risk (PYAR). Logistic regression was used to determine risk factors. RESULTS: Between 2009 and 2018, 179 079 patients met the study criteria and were identified as having a facial scar, and matched to 179 079 controls. The incidence of anxiety in the facial scarring group was 10.05 per 1000 PYAR compared with 7.48 per 1000 PYAR for controls. The incidence of depression in the facial scarring group was 16.28 per 1000 PYAR compared with 9.56 per 1000 PYAR for controls. Age at the time of scarring, previous history of anxiety or depression, female gender, socioeconomic status and classification of scarring increased the risk of both anxiety disorders and depression. CONCLUSIONS: There is a high burden of anxiety disorders and depression in this patient group. Risk of these mental health disorders is very much determined by factors apparent at the time of injury, supporting the need for psychological support.

Clustering long-term health conditions among 67728 people with multimorbidity using electronic health records in Scotland.

There is still limited understanding of how chronic conditions co-occur in patients with multimorbidity and what are the consequences for patients and the health care system. Most reported clusters of conditions have not considered the demographic characteristics of these patients during the clustering process. The study used data for all registered patients that were resident in Fife or Tayside, Scotland and aged 25 years or more on 1st January 2000 and who were followed up until 31st December 2018. We used linked demographic information, and secondary care electronic health records from 1st January 2000. Individuals with at least two of the 31 Elixhauser Comorbidity Index conditions were identified as having multimorbidity. Market basket analysis was used to cluster the conditions for the whole population and then repeatedly stratified by age, sex and deprivation. 318,235 individuals were included in the analysis, with 67,728 (21·3%) having multimorbidity. We identified five distinct clusters of conditions in the population with multimorbidity: alcohol misuse, cancer, obesity, renal failure, and heart failure. Clusters of long-term conditions differed by age, sex and socioeconomic deprivation, with some clusters not present for specific strata and others including additional conditions. These findings highlight the importance of considering demographic factors during both clustering analysis and intervention planning for individuals with multiple long-term conditions. By taking these factors into account, the healthcare system may be better equipped to develop tailored interventions that address the needs of complex patients.

The cost of implementing the COVID-19 shielding policy in Wales.

BACKGROUND: The EVITE Immunity study investigated the effects of shielding Clinically Extremely Vulnerable (CEV) people during the COVID-19 pandemic on health outcomes and healthcare costs in Wales, United Kingdom, to help prepare for future pandemics. Shielding was intended to protect those at highest risk of serious harm from COVID-19. We report the cost of implementing shielding in Wales. METHODS: The number of people shielding was extracted from the Secure Anonymised Information Linkage Databank. Resources supporting shielding between March and June 2020 were mapped using published reports, web pages, freedom of information requests to Welsh Government and personal communications (e.g. with the office of the Chief Medical Officer for Wales). RESULTS: At the beginning of shielding, 117,415 people were on the shielding list. The total additional cost to support those advised to stay home during the initial 14 weeks of the pandemic was £13,307,654 (£113 per person shielded). This included the new resources required to compile the shielding list, inform CEV people of the shielding intervention and provide medicine and food deliveries. The list was adjusted weekly over the 3-month period (130,000 people identified by June 2020). Therefore the cost per person shielded lies between £102 and £113 per person. CONCLUSION: This is the first evaluation of the cost of the measures put in place to support those identified to shield in Wales. However, no data on opportunity cost was available. The true costs of shielding including its budget impact and opportunity costs need to be investigated to decide whether shielding is a worthwhile policy for future health emergencies.

How does the environment in and around the home affect social care and health outcomes for older people? A national longitudinal dynamic cohort study.

BACKGROUND: Reducing the burden of falls and fall-related admissions to hospital and care homes is an important policy area because falls cause significant injury leading to a reduced quality of life. We investigated the effect of the environment around people's homes on the risk of falls for older people in Wales. METHODS: In this longitudinal cohort study, we created a dynamic national e-cohort of individuals aged 60 years or older living in Wales between Jan 1, 2010, and Dec 31, 2019. Using the Secure Anonymised Information Linkage Databank, we linked routinely collected, anonymised health-data on general practitioner (GP) appointments; hospital and emergency admissions; and longitudinal individual-level demographic data to metrics detailing the built environment and deprivation as determined by the Welsh Index of Multiple Deprivation. Using adjusted cox regression models, we assessed how the risk of a fall changed with sex, age, deprivation quintile, urban or rural classification, household occupancy, care status, frailty, dementia diagnosis, and built environment metrics. Built environments of urban and rural areas are very different, so we stratified our analysis by urbanicity to compare these associations in each setting. FINDINGS: We analysed 5 536 444 person-years of data from 931 830 individuals (sex: 51·5% female, 48·5% male; age: 69·2% aged 60-64 years, 12·3% aged 65-69 years, 13·3% aged 70-79 years, 4·4% aged 80-89 years, and 0·7% aged ≥90 years). 154 060 (16·5%) had a fall between joining the cohort and Dec 31, 2019. Men had a lower risk of falling than women (adjusted hazard ratio [aHR] 0·736 [0·729-0·742]), and the risk increased with age compared with individuals aged 60-64 years (1·395 [1·378-1·412] for 65-69 years, 1·892 [1·871-1·913] for 70-79 years, 2·668 [2·623-2·713] for 80-89 years, 3·196 [3·063-3·335] for ≥90 years) and with frailty compared with fit individuals (1·609 [1·593-1·624] for mild frailty, 2·263 [2·234-2·293] for moderate frailty, and 2·833 [2·770-2·897] for severe frailty). Those living in rural areas were less likely to fall than those in urban areas (0·711 [0·702-0·720]). All p values were less than 0·0001. INTERPRETATION: Although preliminary, these results corroborate current knowledge that as we age and become frailer, the risk of falling increases. The effect of urbanicity on risk of fall suggests that the built environment could be associated with fall risk. We only detected falls that caused emergency or hospital admission, leading to potential selection bias. Nevertheless, this research could help guide policy to reduce the incidence of injuries caused by falls in older people. FUNDING: Health and Care Research Wales.

Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis.

Vaccination has proven to be effective at preventing severe outcomes of COVID-19 infection, and uptake in the population has been high in Wales. However, there is a risk that high-level vaccination coverage statistics may mask hidden inequalities in under-served populations, many of whom may be at increased risk of severe outcomes of COVID-19 infection. The study population included 1,436,229 individuals aged 18 years and over, alive and residence in Wales as at 31st July 2022, and excluded immunosuppressed or care home residents. We compared people who had received one or more vaccinations to those with no vaccination using linked data from nine datasets within the Secure Anonymised Information Linkage (SAIL) databank. Multivariable analysis was undertaken to determine the impact of a range of sociodemographic characteristics on vaccination uptake, including ethnicity, country of birth, severe mental illness, homelessness and substance use. We found that overall uptake of first dose of COVID-19 vaccination was high in Wales (92.1 %), with the highest among those aged 80 years and over and females. Those aged under 40 years, household composition (aOR 0.38 95 %CI 0.35-0.41 for 10+ size household compared to two adult household) and being born outside the UK (aOR 0.44 95 %CI 0.43-0.46) had the strongest negative associations with vaccination uptake. This was followed by a history of substance misuse (aOR 0.45 95 %CI 0.44-0.46). Despite high-level population coverage in Wales, significant inequalities remain across several underserved groups. Factors associated with vaccination uptake should not be considered in isolation, to avoid drawing incorrect conclusions. Ensuring equitable access to vaccination is essential to protecting under-served groups from COVID-19 and further work needs to be done to address these gaps in coverage, with focus on tailored vaccination pathways and advocacy, using trusted partners and communities.

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.

Impact of individual, household, and area characteristics on health and social care outcomes for people with multimorbidity: Protocol for a multilevel analysis.

BACKGROUND: Multimorbidity is one of the greatest challenges facing health and social care systems globally. It is associated with high rates of health service use, adverse healthcare events, and premature death. Despite its importance, little is known about the effects of contextual determinants such as household and area characteristics on health and care outcomes for people with multimorbidity. This study protocol presents a plan for the examination of associations between individual, household, and area characteristics with important health and social care outcomes. METHODS: The study will use a cross-section of data from the SAIL Databank on 01 January 2019 and include all people alive and registered with a Welsh GP. The cohort will be stratified according to the presence or absence of multimorbidity, defined as two or more long-term conditions. Multilevel models will be used to examine covariates measured for individuals, households, and areas to account for social processes operating at different levels. The intra-class correlation coefficient will be calculated to determine the strength of association at each level of the hierarchy. Model outcomes will be any emergency department attendance, emergency hospital or care home admission, or mortality, within the study follow-up period. DISCUSSION: Household and area characteristics might act as protective or risk factors for health and care outcomes for people with multimorbidity, in which case results of the analyses can be used to guide clinical and policy responses for effective targeting of limited resources.

Ambient greenness, access to local green spaces, and subsequent mental health: a 10-year longitudinal dynamic panel study of 2·3 million adults in Wales.

BACKGROUND: Living in greener areas, or close to green and blue spaces (GBS; eg, parks, lakes, or beaches), is associated with better mental health, but longitudinal evidence when GBS exposures precede outcomes is less available. We aimed to analyse the effect of living in or moving to areas with more green space or better access to GBS on subsequent adult mental health over time, while explicitly considering health inequalities. METHODS: A cohort of the people in Wales, UK (≥16 years; n=2 341 591) was constructed from electronic health record data sources from Jan 1, 2008 to Oct 31, 2019, comprising 19 141 896 person-years of follow-up. Household ambient greenness (Enhanced Vegetation Index [EVI]), access to GBS (counts, distance to nearest), and common mental health disorders (CMD, based on a validated algorithm combining current diagnoses or symptoms of anxiety or depression [treated or untreated in the preceding 1-year period], or treatment of historical diagnoses from before the current cohort [up to 8 years previously, to 2000], where diagnosis preceded treatment) were record-linked. Cumulative exposure values were created for each adult, censoring for CMD, migration out of Wales, death, or end of cohort. Exposure and CMD associations were evaluated using multivariate logistic regression, stratified by area-level deprivation. FINDINGS: After adjustment, exposure to greater ambient greenness over time (+0·1 increased EVI on a 0-1 scale) was associated with lower odds of subsequent CMD (adjusted odds ratio 0·80, 95% CI 0·80-0·81), where CMD was based on a combination of current diagnoses or symptoms (treated or untreated in the preceding 1-year period), or treatments. Ten percentile points more access to GBS was associated with lower odds of a later CMD (0·93, 0·93-0·93). Every additional 360 m to the nearest GBS was associated with higher odds of CMD (1·05, 1·04-1·05). We found that positive effects of GBS on mental health appeared to be greater in more deprived quintiles. INTERPRETATION: Ambient exposure is associated with the greatest reduced risk of CMD, particularly for those who live in deprived communities. These findings support authorities responsible for GBS, who are attempting to engage planners and policy makers, to ensure GBS meets residents' needs. FUNDING: National Institute for Health and Care Research Public Health Research programme.