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Aldridge SJ, Agrawal U, Murphy S, Millington T, Akbari A, Almaghrabi F, Anand SN, Bedston S, Goudie R, Griffiths R, Joy M, Lowthian E, de Lusignan S, Patterson L, Robertson C, Rudan I, Bradley DT, Lyons RA, Sheikh A, Owen RK. Uptake of COVID-19 vaccinations amongst 3,433,483 children and young people: meta-analysis of UK prospective cohorts. Nat Commun 2024; 15:2363. [PMID: 38491011 PMCID: PMC10943015 DOI: 10.1038/s41467-024-46451-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 02/27/2024] [Indexed: 03/18/2024] Open
Abstract
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).
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Affiliation(s)
- Sarah J Aldridge
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK.
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Siobhán Murphy
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
| | | | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | | | - Sneha N Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Stuart Bedston
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Rosalind Goudie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Rowena Griffiths
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Emily Lowthian
- Department of Education and Childhood Studies, School of Social Sciences, Swansea University, Swansea, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Lynsey Patterson
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
- Public Health Agency, Belfast, UK
| | - Chris Robertson
- Department of Mathematics and Statistics, Strathclyde University, Glasgow, UK and Public Health Scotland, Glasgow, UK
| | - Igor Rudan
- Centre for Global Health, Usher Institute, the University of Edinburgh, Edinburgh, UK
| | - Declan T Bradley
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University, Belfast, UK
- Public Health Agency, Belfast, UK
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Aziz Sheikh
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Rhiannon K Owen
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK.
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2
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Strafford H, Hollinghurst J, Lacey AS, Akbari A, Watkins A, Paterson J, Jennings D, Lyons RA, Powell HR, Kerr MP, Chin RF, Pickrell WO. Health care utilization and mortality for people with epilepsy during COVID-19: A population study. Epilepsia 2024. [PMID: 38441332 DOI: 10.1111/epi.17920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 02/05/2024] [Accepted: 02/05/2024] [Indexed: 03/14/2024]
Abstract
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.
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Affiliation(s)
- Huw Strafford
- Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Joe Hollinghurst
- Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Arron S Lacey
- Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Ashley Akbari
- Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Alan Watkins
- Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | | | | | - Ronan A Lyons
- Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - H Robert Powell
- Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
- Morriston Hospital, Swansea Bay University Health Board, Swansea, UK
| | - Michael P Kerr
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Richard F Chin
- Muir Maxwell Epilepsy Centre, Centre for Clinical Brain Sciences and Department of Child Life and Health, University of Edinburgh, Scotland, UK
- Royal Hospital for Children and Young People, Edinburgh, UK
| | - William O Pickrell
- Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
- Morriston Hospital, Swansea Bay University Health Board, Swansea, UK
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Strafford H, Hollinghurst J, Lacey AS, Akbari A, Watkins A, Paterson J, Jennings D, Lyons RA, Powell HR, Kerr MP, Chin RF, Pickrell WO. Epilepsy and the risk of COVID-19-related hospitalization and death: A population study. Epilepsia 2024. [PMID: 38441374 DOI: 10.1111/epi.17910] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/24/2024] [Accepted: 01/24/2024] [Indexed: 03/14/2024]
Abstract
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.
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Affiliation(s)
- Huw Strafford
- Faculty of Medicine, Health, and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Joe Hollinghurst
- Faculty of Medicine, Health, and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Arron S Lacey
- Faculty of Medicine, Health, and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Ashley Akbari
- Faculty of Medicine, Health, and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Alan Watkins
- Faculty of Medicine, Health, and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | | | | | - Ronan A Lyons
- Faculty of Medicine, Health, and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - H Robert Powell
- Faculty of Medicine, Health, and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
- Morriston Hospital, Swansea Bay University Health Board, Swansea, UK
| | - Michael P Kerr
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Richard F Chin
- Muir Maxwell Epilepsy Centre, Centre for Clinical Brain Sciences and Department of Child Life and Health, University of Edinburgh, Edinburgh, UK
- Royal Hospital for Children and Young People, Edinburgh, UK
| | - William O Pickrell
- Faculty of Medicine, Health, and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
- Morriston Hospital, Swansea Bay University Health Board, Swansea, UK
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4
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Lee SC, DelPozo-Banos M, Friedmann Y, Akbari A, Lyons RA, John A. Widening Excess Mortality During the COVID-19 Pandemic in Individuals Who Self-Harmed. Crisis 2024; 45:154-158. [PMID: 36226352 PMCID: PMC10999850 DOI: 10.1027/0227-5910/a000882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 07/13/2022] [Accepted: 07/17/2022] [Indexed: 11/07/2022]
Abstract
Background: Studies on COVID-19 pandemic-associated changes in mortality following self-harm remain scarce and inconclusive. Aims: To compare mortality risks in individuals who had self-harmed to those for individuals who had not, before and during the COVID-19 pandemic (Waves 1 and 2) in Wales, the United Kingdom, using population-based routinely collected data. Method: We linked whole population health data to all-cause mortality following an episode of self-harm between April 2016 and March 2021. Propensity score matching, Cox regression, and difference-in-differences were applied to compute changes in excess mortality (as ratios of hazard ratios, RHRs) before and during the pandemic for individuals who self-harmed. Results: The difference in mortality for individuals who self-harmed compared to those who did not widened during Wave 1 (RHR = 2.03, 95% CI: 1.04-4.03) and Wave 2 (RHR = 2.19, 95% CI: 1.12-4.29) from before the pandemic. Stratification by sex and age group produced no significant subgroup differences although risk for younger than 65 years group were higher. Limitations: Limitations include small sample size and incomplete data on cause-specific deaths during the pandemic. Conclusion: Our results underscore continuous monitoring of mortality of individuals who self-harm and effective interventions to address any increases in mortality.
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Affiliation(s)
- Sze Chim Lee
- Population Data Science, Swansea
University Medical School, Swansea, UK
| | | | - Yasmin Friedmann
- Population Data Science, Swansea
University Medical School, Swansea, UK
| | - Ashley Akbari
- Population Data Science, Swansea
University Medical School, Swansea, UK
| | - Ronan A. Lyons
- Population Data Science, Swansea
University Medical School, Swansea, UK
| | - Ann John
- Population Data Science, Swansea
University Medical School, Swansea, UK
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5
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Archer L, Relton SD, Akbari A, Best K, Bucknall M, Conroy S, Hattle M, Hollinghurst J, Humphrey S, Lyons RA, Richards S, Walters K, West R, van der Windt D, Riley RD, Clegg A. 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. Age Ageing 2024; 53:afae057. [PMID: 38520142 PMCID: PMC10960070 DOI: 10.1093/ageing/afae057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Indexed: 03/25/2024] Open
Abstract
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.
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Affiliation(s)
- Lucinda Archer
- Institute for Applied Health Research, University of Birmingham, Birmingham, UK
- National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, University of Birmingham, Birmingham, UK
| | - Samuel D Relton
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Kate Best
- Academic Unit for Ageing and Stroke Research, University of Leeds, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | | | - Simon Conroy
- Institute of Cardiovascular Science, University College London, London, UK
| | - Miriam Hattle
- Institute for Applied Health Research, University of Birmingham, Birmingham, UK
- National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, University of Birmingham, Birmingham, UK
| | - Joe Hollinghurst
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Sara Humphrey
- Bradford District and Craven Health and Care Partnership, Bradford, UK
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Suzanne Richards
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Kate Walters
- Primary Care and Population Health, University College London, London, UK
| | - Robert West
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | | | - Richard D Riley
- Institute for Applied Health Research, University of Birmingham, Birmingham, UK
- National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre, University of Birmingham, Birmingham, UK
| | - Andrew Clegg
- Academic Unit for Ageing and Stroke Research, University of Leeds, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
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6
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Mizen A, Thompson DA, Watkins A, Akbari A, Garrett JK, Geary R, Lovell R, Lyons RA, Nieuwenhuijsen M, Parker SC, Rowney FM, Song J, Stratton G, Wheeler BW, White J, White MP, Williams S, Rodgers SE, Fry R. The use of Enhanced Vegetation Index for assessing access to different types of green space in epidemiological studies. J Expo Sci Environ Epidemiol 2024:10.1038/s41370-024-00650-5. [PMID: 38424359 DOI: 10.1038/s41370-024-00650-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 01/24/2024] [Accepted: 01/24/2024] [Indexed: 03/02/2024]
Abstract
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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Affiliation(s)
- Amy Mizen
- Swansea University Medical School, Swansea University, Swansea, UK.
| | | | - Alan Watkins
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Ashley Akbari
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Joanne K Garrett
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Rebecca Geary
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Rebecca Lovell
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Ronan A Lyons
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Mark Nieuwenhuijsen
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Sarah C Parker
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Francis M Rowney
- School of Geography, Earth and Environmental Sciences, University of Plymouth, Plymouth, UK
| | | | - Gareth Stratton
- ASTEM Research Centre, Faculty of Science and Engineering, Swansea University, Swansea, UK
| | - Benedict W Wheeler
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - James White
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK
| | - Mathew P White
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
- Cognitive Science Hub, University of Vienna, Vienna, Austria
| | | | - Sarah E Rodgers
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Richard Fry
- Swansea University Medical School, Swansea University, Swansea, UK
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7
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Pineda-Moncusí M, Allery F, Delmestri A, Bolton T, Nolan J, Thygesen JH, Handy A, Banerjee A, Denaxas S, Tomlinson C, Denniston AK, Sudlow C, Akbari A, Wood A, Collins GS, Petersen I, Coates LC, Khunti K, Prieto-sAlhambra D, Khalid S. Ethnicity data resource in population-wide health records: completeness, coverage and granularity of diversity. Sci Data 2024; 11:221. [PMID: 38388690 PMCID: PMC10883937 DOI: 10.1038/s41597-024-02958-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 01/12/2024] [Indexed: 02/24/2024] Open
Abstract
Intersectional social determinants including ethnicity are vital in health research. We curated a population-wide data resource of self-identified ethnicity data from over 60 million individuals in England primary care, linking it to hospital records. We assessed ethnicity data in terms of completeness, consistency, and granularity and found one in ten individuals do not have ethnicity information recorded in primary care. By linking to hospital records, ethnicity data were completed for 94% of individuals. By reconciling SNOMED-CT concepts and census-level categories into a consistent hierarchy, we organised more than 250 ethnicity sub-groups including and beyond "White", "Black", "Asian", "Mixed" and "Other, and found them to be distributed in proportions similar to the general population. This large observational dataset presents an algorithmic hierarchy to represent self-identified ethnicity data collected across heterogeneous healthcare settings. Accurate and easily accessible ethnicity data can lead to a better understanding of population diversity, which is important to address disparities and influence policy recommendations that can translate into better, fairer health for all.
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Affiliation(s)
- Marta Pineda-Moncusí
- Centre for Statistics in Medicine, Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Freya Allery
- Institute of Health Informatics, 222 Euston Road, London, NW1 2DA, University College London, London, UK
| | - Antonella Delmestri
- Centre for Statistics in Medicine, Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Thomas Bolton
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | - John Nolan
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | - Johan H Thygesen
- Institute of Health Informatics, 222 Euston Road, London, NW1 2DA, University College London, London, UK
| | - Alex Handy
- Institute of Health Informatics, 222 Euston Road, London, NW1 2DA, University College London, London, UK
| | - Amitava Banerjee
- Institute of Health Informatics, 222 Euston Road, London, NW1 2DA, University College London, London, UK
| | - Spiros Denaxas
- Institute of Health Informatics, 222 Euston Road, London, NW1 2DA, University College London, London, UK
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
- University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - Christopher Tomlinson
- Institute of Health Informatics, 222 Euston Road, London, NW1 2DA, University College London, London, UK
- University College London Hospitals Biomedical Research Centre, University College London, London, UK
- UK Research and Innovation Centre for Doctoral Training in AI-enabled Healthcare Systems, University College London, London, UK
| | | | - Cathie Sudlow
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
| | - Angela Wood
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Gary S Collins
- Centre for Statistics in Medicine, Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Irene Petersen
- Department of Primary Care and Population Health, UCL, London, NW3 2PF, UK
- Department of Clinical Epidemiology, Aarhus University, Aarhus N, Aarhus, 8200, Denmark
| | - Laura C Coates
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Daniel Prieto-sAlhambra
- Centre for Statistics in Medicine, Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK
- Department of Medical Informatics, Erasmus MC University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Sara Khalid
- Centre for Statistics in Medicine, Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford, UK.
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Kerr S, Bedston S, Cezard G, Sampri A, Murphy S, Bradley DT, Morrison K, Akbari A, Whiteley W, Sullivan C, Patterson L, Khunti K, Denaxas S, Bolton T, Khan S, Keys A, Weatherill D, Mooney K, Davies J, Ritchie L, McMenamin J, Kee F, Wood A, Lyons RA, Sudlow C, Robertson C, Sheikh A. Undervaccination and severe COVID-19 outcomes: meta-analysis of national cohort studies in England, Northern Ireland, Scotland, and Wales. Lancet 2024; 403:554-566. [PMID: 38237625 DOI: 10.1016/s0140-6736(23)02467-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 10/31/2023] [Accepted: 11/02/2023] [Indexed: 02/12/2024]
Abstract
BACKGROUND Undervaccination (receiving fewer than the recommended number of SARS-CoV-2 vaccine doses) could be associated with increased risk of severe COVID-19 outcomes-ie, COVID-19 hospitalisation or death-compared with full vaccination (receiving the recommended number of SARS-CoV-2 vaccine doses). We sought to determine the factors associated with undervaccination, and to investigate the risk of severe COVID-19 outcomes in people who were undervaccinated in each UK nation and across the UK. METHODS We used anonymised, harmonised electronic health record data with whole population coverage to carry out cohort studies in England, Northern Ireland, Scotland, and Wales. Participants were required to be at least 5 years of age to be included in the cohorts. We estimated adjusted odds ratios for undervaccination as of June 1, 2022. We also estimated adjusted hazard ratios (aHRs) for severe COVID-19 outcomes during the period June 1 to Sept 30, 2022, with undervaccination as a time-dependent exposure. We combined results from nation-specific analyses in a UK-wide fixed-effect meta-analysis. We estimated the reduction in severe COVID-19 outcomes associated with a counterfactual scenario in which everyone in the UK was fully vaccinated on June 1, 2022. FINDINGS The numbers of people undervaccinated on June 1, 2022 were 26 985 570 (45·8%) of 58 967 360 in England, 938 420 (49·8%) of 1 885 670 in Northern Ireland, 1 709 786 (34·2%) of 4 992 498 in Scotland, and 773 850 (32·8%) of 2 358 740 in Wales. People who were younger, from more deprived backgrounds, of non-White ethnicity, or had a lower number of comorbidities were less likely to be fully vaccinated. There was a total of 40 393 severe COVID-19 outcomes in the cohorts, with 14 156 of these in undervaccinated participants. We estimated the reduction in severe COVID-19 outcomes in the UK over 4 months of follow-up associated with a counterfactual scenario in which everyone was fully vaccinated on June 1, 2022 as 210 (95% CI 94-326) in the 5-15 years age group, 1544 (1399-1689) in those aged 16-74 years, and 5426 (5340-5512) in those aged 75 years or older. aHRs for severe COVID-19 outcomes in the meta-analysis for the age group of 75 years or older were 2·70 (2·61-2·78) for one dose fewer than recommended, 3·13 (2·93-3·34) for two fewer, 3·61 (3·13-4·17) for three fewer, and 3·08 (2·89-3·29) for four fewer. INTERPRETATION Rates of undervaccination against COVID-19 ranged from 32·8% to 49·8% across the four UK nations in summer, 2022. Undervaccination was associated with an elevated risk of severe COVID-19 outcomes. FUNDING UK Research and Innovation National Core Studies: Data and Connectivity.
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Davies G, Akbari A, Bailey R, Evans L, Smith K, Goodfellow J, Thomas M, Lutchman Singh K. Cardiac interventions in Wales: A comparison of benefits between NHS Wales specialties. PLoS One 2024; 19:e0297049. [PMID: 38335178 PMCID: PMC10857708 DOI: 10.1371/journal.pone.0297049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 12/24/2023] [Indexed: 02/12/2024] Open
Abstract
OBJECTIVES The study aimed to assess if specialised healthcare service interventions in Wales benefit the population equitably in work commissioned by the Welsh Health Specialised Services Committee (WHSSC). APPROACH The study utilised anonymised individual-level, population-scale, routinely collected electronic health record (EHR) data held in the Secure Anonymised Information Linkage (SAIL) Databank to identify patients resident in Wales receiving specialist cardiac interventions. Measurement was undertaken of associated patient outcomes 2-years before and after the intervention (minus a 6-month clearance period on either side) by measuring events in primary care, hospital attendance, outpatient and emergency department. The analysis controlled for comorbidity (Charlson) and deprivation (Welsh Index of Multiple Deprivation), stratified by admission type (elective or emergency) and membership of top 5% post-intervention costs. Costs were estimated by multiplying events by mean person cost estimates. RESULTS We identified 5,999 percutaneous coronary interventions (PCI) and 1,640 coronary artery bypass graft (CABG) between 2014-06-01 to 2020-02-29. The ratio of emergency to elective interventions was 2.85 for PCI and 1.04 for CABG. In multivariate analysis significant associations were identified for comorbidity (OR = 1.52, CI = (1.01-2.27)), deprivation (OR = 1.34, CI = (1.03-1.76)) and rurality (OR = 0.81, CI = (0.70-0.95)) for PCI interventions, and comorbidity (OR = 1.47, CI = (1.10-1.98)) for CABG. Higher costs post-intervention were associated with increased comorbidity for PCI and CABG in the top 5% cost groups, but for PCI this was not seen outside the top 5%. For PCI, moderate cost increase was associated with increased deprivation, but the picture was more mixed following CABG interventions. For both interventions, lower costs post intervention were seen in rural locations. CONCLUSION We identified and compared health outcomes for selected specialist cardiac interventions amongst patients resident in Wales, with these methods and analyses, providing a template for comparing other cardiac interventions.
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Affiliation(s)
- Gareth Davies
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales
| | - Rowena Bailey
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales
| | - Lloyd Evans
- NHS Wales Executive, Wales Cardiovascular Network, Cardiff, Wales
| | - Kendal Smith
- Welsh Health Specialised Services Committee, Pontypridd, Wales
| | | | - Michael Thomas
- Hywel Dda University Health Board, Hafan Derwen, Carmarthen, Wales
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Yousefi M, Khoshnevis SJ, Seraj M, Abbasvandi F, Sadeghi P, Khoshnevis Z, Akbari A, Hadi A, Akbari ME. Primary repair with no flaps for lower lip defects (30-80 %) after cancer excision. Asian J Surg 2024; 47:995-998. [PMID: 38160160 DOI: 10.1016/j.asjsur.2023.12.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 07/02/2023] [Accepted: 12/15/2023] [Indexed: 01/03/2024] Open
Abstract
Reconstruction of the lip is a necessary procedure when lip tumors are excised. Although many good techniques have been described, they often have disadvantages such as necrosis and extensive suture lines. In our approach, we aim to minimize the suture line and avoid tissue necrosis for medium-sized lip defects (30-80 %). This is a surgical technique report from a single center. After tumor resection, we made a bilateral 15 mm horizontal skin and mucosa incision from the angles of the lip to the lateral sides. The mucosa and skin were dissected from the underlying muscle, and the muscle was cut approximately 15 mm on each side. The lip defect was then closed and sutured in four layers. Finally, the released mucosa was sutured to the corner of the incised skin. We followed the patients for 36 months and found that their speech intelligibility, sensation, mobility, and aesthetic satisfaction were preserved. The scars were also less pronounced compared to flaps, and there were no signs of edema or drooling. In conclusion, our technique offers many advantages for moderate defects of lower lip tumors. By avoiding the use of flaps, we eliminate the complications associated with flap surgery while achieving aesthetically satisfactory results. However, further evaluation by other surgeons is necessary to fully examine the technique's benefits.
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Affiliation(s)
- M Yousefi
- Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - S J Khoshnevis
- Department of Vascular Surgery, Shahid Beheshti University of Medical Sciences, Shohadaye Tajrish Hospital, Tehran, Iran
| | - M Seraj
- Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - F Abbasvandi
- Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - P Sadeghi
- Plastic Surgery Department, Cleveland, OH, USA
| | - Z Khoshnevis
- School of Architecture and Urban Design, University of Science and Technology, Tehran, Iran
| | - A Akbari
- Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - A Hadi
- Department of Prosthodontics, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - M E Akbari
- Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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11
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Ritchie LA, Harrison SL, Penson PE, Akbari A, Torabi F, Hollinghurst J, Harris D, Oke OB, Akpan A, Halcox JP, Rodgers SE, Lip GYH, Lane DA. Adherence to the Atrial fibrillation Better Care pathway and the risk of adverse health outcomes in older care home residents with atrial fibrillation: a retrospective data linkage study 2003-18. Age Ageing 2024; 53:afae021. [PMID: 38400634 PMCID: PMC10891424 DOI: 10.1093/ageing/afae021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/08/2023] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND The Atrial fibrillation Better Care (ABC) pathway is the gold-standard approach to atrial fibrillation (AF) management, but the effect of implementation on health outcomes in care home residents is unknown. OBJECTIVE To examine associations between ABC pathway adherence and stroke, transient ischaemic attack, cardiovascular hospitalisation, major bleeding, mortality and a composite of all these outcomes in care home residents. METHODS A retrospective cohort study of older care home residents (≥65 years) in Wales with AF was conducted between 1 January 2003 and 31 December 2018 using the Secure Anonymised Information Linkage Databank. Adherence to the ABC pathway was assessed at care home entry using pre-specified definitions. Cox proportional hazard and competing risk models were used to estimate the risk of health outcomes according to ABC adherence. RESULTS From 14,493 residents (median [interquartile range] age 87.0 [82.6-91.2] years, 35.2% male) with AF, 5,531 (38.2%) were ABC pathway adherent. Pathway adherence was not significantly associated with risk of the composite outcome (adjusted hazard ratio, 95% confidence interval [CI]: 1.01 [0.97-1.05]). There was a significant independent association observed between ABC pathway adherence and a reduced risk of myocardial infarction (0.70 [0.50-0.98]), but a higher risk of haemorrhagic stroke (1.59 [1.06-2.39]). ABC pathway adherence was not significantly associated with any other individual health outcomes examined. CONCLUSION An ABC adherent approach in care home residents was not consistently associated with improved health outcomes. Findings should be interpreted with caution owing to difficulties in defining pathway adherence using routinely collected data and an individualised approach is recommended.
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Affiliation(s)
- Leona A Ritchie
- Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK
| | - Stephanie L Harrison
- Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
- Registry of Senior Australians, South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Peter E Penson
- Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, Wales SA2 8PP, UK
| | - Fatemeh Torabi
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, Wales SA2 8PP, UK
| | - Joe Hollinghurst
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, Wales SA2 8PP, UK
| | - Daniel Harris
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, Wales SA2 8PP, UK
- Tritech Institute, Hywel Dda University Health Board, Bynea, Llanelli SA14 9TE, UK
| | - Oluwakayode B Oke
- Department of Renal Medicine, East Kent Hospital NHS Foundation Trust, Ashford TN24 0LZ, UK
| | - Asangaedem Akpan
- Department of Geriatric Medicine, Bunbury Regional Hospital, WA Country Health Service – South West, Bunbury 6230, Australia
- Division of Internal Medicine, University of Western Australia, Perth WA 6009, Australia
- Curtin Medical School, Faculty of Health Sciences, Curtin University, Perth WA 6845, Australia
| | - Julian P Halcox
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, Wales SA2 8PP, UK
| | - Sarah E Rodgers
- Department of Public Health, Policy and Systems, Institute of Population Health, University of Liverpool, Liverpool L69 3GF, UK
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
- Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg DK-9220, Denmark
| | - Deirdre A Lane
- Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
- Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg DK-9220, Denmark
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12
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Bedston S, Almaghrabi F, Patterson L, Agrawal U, Woolford L, Anand SN, Joy M, Crawford A, Goudie R, Byford R, Abbasizanjani H, Smith D, Laidlaw L, Akbari A, Sullivan C, Bradley DT, Lyons RA, de Lusignan S, Hobbs FR, Robertson C, Sheikh SA, Shi T. 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. Lancet Reg Health Eur 2024; 37:100816. [PMID: 38162515 PMCID: PMC10757260 DOI: 10.1016/j.lanepe.2023.100816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/17/2023] [Accepted: 11/29/2023] [Indexed: 01/03/2024]
Abstract
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.
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Affiliation(s)
- Stuart Bedston
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Fatima Almaghrabi
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, Scotland, UK
| | - Lynsey Patterson
- Centre for Public Health, Queen's University Belfast, Belfast, UK
- Public Health Agency, Belfast, UK
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Lana Woolford
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, Scotland, UK
| | - Sneha N. Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Anna Crawford
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, Scotland, UK
| | - Rosalind Goudie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Hoda Abbasizanjani
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Deb Smith
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, Scotland, UK
| | - Lynn Laidlaw
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, Scotland, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | | | - Declan T. Bradley
- Centre for Public Health, Queen's University Belfast, Belfast, UK
- Public Health Agency, Belfast, UK
| | - Ronan A. Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health, and Life Science, Swansea University, Swansea, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - F.D. Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Chris Robertson
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, Scotland, UK
- Public Health Scotland, Glasgow, Scotland, UK
| | - Sir Aziz Sheikh
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, Scotland, UK
| | - Ting Shi
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, Scotland, UK
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13
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Dhafari TB, Pate A, Azadbakht N, Bailey R, Rafferty J, Jalali-Najafabadi F, Martin GP, Hassaine A, Akbari A, Lyons J, Watkins A, Lyons RA, Peek N. A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods. J Clin Epidemiol 2024; 165:111214. [PMID: 37952700 DOI: 10.1016/j.jclinepi.2023.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 10/14/2023] [Accepted: 11/05/2023] [Indexed: 11/14/2023]
Abstract
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.
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Affiliation(s)
- Thamer Ba Dhafari
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Alexander Pate
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Narges Azadbakht
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Rowena Bailey
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - James Rafferty
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Farideh Jalali-Najafabadi
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, M13 9PL Manchester, UK
| | - Glen P Martin
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Abdelaali Hassaine
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Jane Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Alan Watkins
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - Niels Peek
- Division of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, M13 9PL Manchester, UK; NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
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14
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Rafferty J, Lee A, Lyons RA, Akbari A, Peek N, Jalali-najafabadi F, Ba Dhafari T, Lyons J, Watkins A, Bailey R. Using hypergraphs to quantify importance of sets of diseases by healthcare resource utilisation: A retrospective cohort study. PLoS One 2023; 18:e0295300. [PMID: 38100428 PMCID: PMC10723667 DOI: 10.1371/journal.pone.0295300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 11/20/2023] [Indexed: 12/17/2023] Open
Abstract
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.
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Affiliation(s)
- James Rafferty
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Alexandra Lee
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Ronan A. Lyons
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Niels Peek
- Division of Informatics, Imaging and Data Science, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
- Alan Turing Institute, London, United Kingdom
| | - Farideh Jalali-najafabadi
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
| | - Thamer Ba Dhafari
- Division of Informatics, Imaging and Data Science, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Jane Lyons
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Alan Watkins
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Rowena Bailey
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
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15
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Battle C, Hutchings H, Rafferty J, Toghill H, Akbari A, Watkins A. Health care utilization outcomes in patients with blunt chest wall trauma following discharge from the emergency department: A retrospective, observational data-linkage study. J Trauma Acute Care Surg 2023; 95:868-874. [PMID: 37405800 DOI: 10.1097/ta.0000000000004086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/06/2023]
Abstract
BACKGROUND Although much is published reporting clinical outcomes in the patients with blunt chest wall trauma who are admitted to hospital from the ED, less is known about the patients' recovery when they are discharged directly without admission. The aim of this study was to investigate the health care utilization outcomes in adult patients with blunt chest wall trauma, discharged directly from ED in a trauma unit in the United Kingdom. METHODS This was a longitudinal, retrospective, single-center, observational study incorporating analysis of linked datasets, using the Secure Anonymised Information Linkage databank for admissions to a trauma unit in the Wales, between January 1, 2016, and December 31, 2020. All patients 16 years or older with a primary diagnosis of blunt chest wall trauma discharged directly home were included. Data were analyzed using a negative binomial regression model. RESULTS There were 3,205 presentations to the ED included. Mean age was 53 years, 57% were male, with the predominant injury mechanism being a low velocity fall (50%). 93% of the cohort sustained between 0 and 3 rib fractures. Four percent of the cohort were reported to have chronic obstructive pulmonary disease, and 4% using preinjury anticoagulants. On regression analysis, inpatient admissions, outpatient appointments and primary care contacts all significantly increased in the 12-week period postinjury, compared with the 12-week period preinjury (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.33-1.99; p < 0.001; OR, 1.28; 95% CI, 1.14-1.43; p < 0.001; OR, 1.02; 95% CI, 1.01-1.02; p < 0.001, respectively). Risk of health care resource utilization increased significantly with each additional year of age, chronic obstructive pulmonary disease and preinjury anticoagulant use (all p < 0.05). Social deprivation and number of rib fracture did not impact outcomes. CONCLUSION The results of this study demonstrate the need for appropriate signposting and follow-up for patients with blunt chest wall trauma presenting to the ED, not requiring admission to the hospital. LEVEL OF EVIDENCE Prognostic and Epidemiological; Level IV.
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Affiliation(s)
- Ceri Battle
- From the Physiotherapy Department (C.B., H.T.), Morriston Hospital; Swansea Trials Unit (H.H., J.R., A.W.); and Faculty of Medicine, Health and Life Science (A.A.), Swansea University Medical School, Swansea University, Sketty, Swansea, United Kingdom
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16
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Lowthian E, Abbasizanjani H, Bedston S, Akbari A, Cowley L, Fry R, Owen RK, Hollinghurst J, Rudan I, Beggs J, Marchant E, Torabi F, de Lusignan S, Crick T, Moore G, Sheikh A, Lyons RA. Trends in SARS-CoV-2 infection and vaccination in school staff, students and their household members from 2020 to 2022 in Wales, UK: an electronic cohort study. J R Soc Med 2023; 116:413-424. [PMID: 37347268 PMCID: PMC10767617 DOI: 10.1177/01410768231181268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 04/25/2023] [Indexed: 06/23/2023] Open
Abstract
OBJECTIVES We investigated SARS-CoV-2 infection trends, risk of SARS-CoV-2 infection and COVID-19 vaccination uptake among school staff, students and their household members in Wales, UK. DESIGN Seven-day average of SARS-CoV-2 infections and polymerase chain reaction tests per 1000 people daily, cumulative incidence of COVID-19 vaccination uptake and multi-level Poisson models with time-varying covariates. SETTING National electronic cohort between September 2020 and May 2022 when several variants were predominant in the UK (Alpha, Delta and Omicron). PARTICIPANTS School students aged 4 to 10/11 years (primary school and younger middle school, n = 238,163), and 11 to 15/16 years (secondary school and older middle school, n = 182,775), school staff in Wales (n = 47,963) and the household members of students and staff (n = 697,659). MAIN OUTCOME MEASURES SARS-CoV-2 infection and COVID-19 vaccination uptake. RESULTS School students had a sustained period of high infection rates compared with household members after August 2021. Primary schedule vaccination uptake was highest among staff (96.3%) but lower for household members (72.2%), secondary and older middle school students (59.8%), and primary and younger middle school students (3.3%). Multi-level Poisson models showed that vaccination was associated with a lower risk of SARS-CoV-2 infection. The Delta variant posed a greater infection risk for students than the Alpha variant. However, Omicron was a larger risk for staff and household members. CONCLUSIONS Public health bodies should be informed of the protection COVID-19 vaccines afford, with more research being required for younger populations. Furthermore, schools require additional support in managing new, highly transmissible variants. Further research should examine the mechanisms between child deprivation and SARS-CoV-2 infection.
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Affiliation(s)
- Emily Lowthian
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
- Department of Education & Childhood Studies, School of Social Sciences, Faculty of Humanities and Social Sciences, Swansea University, SA2 8PP, UK
| | - Hoda Abbasizanjani
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
| | - Stuart Bedston
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
| | - Laura Cowley
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
| | - Richard Fry
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
| | - Rhiannon K Owen
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
| | - Joe Hollinghurst
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
| | - Igor Rudan
- Centre for Global Health, Usher Institute, The University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Jillian Beggs
- Usher Institute, The University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Emily Marchant
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
- Department of Education & Childhood Studies, School of Social Sciences, Faculty of Humanities and Social Sciences, Swansea University, SA2 8PP, UK
| | - Fatemeh Torabi
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK
| | - Tom Crick
- Department of Education & Childhood Studies, School of Social Sciences, Faculty of Humanities and Social Sciences, Swansea University, SA2 8PP, UK
| | - Graham Moore
- DECIPHer, SPARK, Cardiff University, Cardiff, CF24 4HQ, UK
| | - Aziz Sheikh
- Usher Institute, The University of Edinburgh, Edinburgh, EH8 9AG, UK
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, SA2 8PP, UK
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17
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Jones G, Perry M, Bailey R, Arumugam S, Edwards A, Lench A, Cooper A, Akbari A, Collins B, Harris C, Richardson G, Barry M, Harris P, Fry R, Lyons RA, Cottrell S. Dimensions of equality in uptake of COVID-19 vaccination in Wales, UK: A multivariable linked data population analysis. Vaccine 2023; 41:7333-7341. [PMID: 37932133 DOI: 10.1016/j.vaccine.2023.10.066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/12/2023] [Accepted: 10/26/2023] [Indexed: 11/08/2023]
Abstract
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.
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Affiliation(s)
- Gethin Jones
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Malorie Perry
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University Swansea, SA2 8PP Wales, UK.
| | - Rowena Bailey
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University Swansea, SA2 8PP Wales, UK.
| | - Sudha Arumugam
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University Swansea, SA2 8PP Wales, UK.
| | - Adrian Edwards
- Wales COVID-19 Evidence Centre, PRIME Centre Wales, Division of Population Medicine, School of Medicine, Cardiff University, 8th Floor, Neuadd Meirionnydd, Heath Park, Cardiff CF14 4XN, Wales, UK.
| | - Alex Lench
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Alison Cooper
- Wales COVID-19 Evidence Centre, PRIME Centre Wales, Division of Population Medicine, School of Medicine, Cardiff University, 8th Floor, Neuadd Meirionnydd, Heath Park, Cardiff CF14 4XN, Wales, UK.
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University Swansea, SA2 8PP Wales, UK.
| | - Brendan Collins
- Health and Social Services Group, Health Protection, Welsh Government, Cardiff, UK; Department of Public Health, Policy and Systems, University of Liverpool, UK.
| | - Caroline Harris
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Gill Richardson
- Policy, Research and International Development, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Mai Barry
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Phillippa Harris
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Richard Fry
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University Swansea, SA2 8PP Wales, UK.
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University Swansea, SA2 8PP Wales, UK.
| | - Simon Cottrell
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
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18
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Fagbamigbe AF, Agrawal U, Azcoaga-Lorenzo A, MacKerron B, Özyiğit EB, Alexander DC, Akbari A, Owen RK, Lyons J, Lyons RA, Denaxas S, Kirk P, Miller AC, Harper G, Dezateux C, Brookes A, Richardson S, Nirantharakumar K, Guthrie B, Hughes L, Kadam UT, Khunti K, Abrams KR, McCowan C. Clustering long-term health conditions among 67728 people with multimorbidity using electronic health records in Scotland. PLoS One 2023; 18:e0294666. [PMID: 38019832 PMCID: PMC10686427 DOI: 10.1371/journal.pone.0294666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 11/07/2023] [Indexed: 12/01/2023] Open
Abstract
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.
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Affiliation(s)
- Adeniyi Francis Fagbamigbe
- School of Medicine, University of St Andrews, St Andrews, United Kingdom
- Department of Epidemiology and Medical Statistics, University of Ibadan, Ibadan, Nigeria
- Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, United Kingdom
- Research Methods and Evaluation Unit, Institute for Health & Wellbeing, Coventry University, Coventry, United Kingdom
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Science, University of Oxford, Oxford, United Kingdom
| | - Amaya Azcoaga-Lorenzo
- School of Medicine, University of St Andrews, St Andrews, United Kingdom
- Hospital Rey Juan Carlos, Instituto de Investigación Sanitaria Fundación Jimenez Diaz, Madrid, Spain
| | - Briana MacKerron
- School of Medicine, University of St Andrews, St Andrews, United Kingdom
| | - Eda Bilici Özyiğit
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, United Kingdom
| | - Daniel C. Alexander
- Centre for Medical Image Computing, Department of Computer Science, UCL, London, United Kingdom
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Rhiannon K. Owen
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Jane Lyons
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Ronan A. Lyons
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Spiros Denaxas
- Institute of Health Informatics, UCL, London, United Kingdom
- British Heart Foundation Data Science Centre, London, United Kingdom
| | - Paul Kirk
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | - Ana Corina Miller
- Centre for Public Health, Institute of Clinical Science, Queen’s University Belfast, Belfast, United Kingdom
| | - Gill Harper
- Clinical Effectiveness Group, Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom
| | - Carol Dezateux
- Clinical Effectiveness Group, Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom
| | - Anthony Brookes
- Department of Genetics & Genome Biology, University of Leicester, Leicester, United Kingdom
| | - Sylvia Richardson
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | | | - Bruce Guthrie
- Advanced Care Research Centre, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Lloyd Hughes
- School of Medicine, University of St Andrews, St Andrews, United Kingdom
| | - Umesh T. Kadam
- Department of Population Health Sciences, University of Leicester, Leicester, United Kingdom
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, United Kingdom
| | - Keith R. Abrams
- Department of Statistics, University of Warwick, Coventry, United Kingdom
| | - Colin McCowan
- School of Medicine, University of St Andrews, St Andrews, United Kingdom
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19
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Sewell B, Farr A, Akbari A, Carson-Stevens A, Dale J, Edwards A, Evans BA, John A, Torabi F, Jolles S, Kingston M, Lyons J, Lyons RA, Porter A, Watkins A, Williams V, Snooks H. The cost of implementing the COVID-19 shielding policy in Wales. BMC Public Health 2023; 23:2342. [PMID: 38008730 PMCID: PMC10680245 DOI: 10.1186/s12889-023-17169-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 11/06/2023] [Indexed: 11/28/2023] Open
Abstract
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.
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Affiliation(s)
- Bernadette Sewell
- Swansea Centre for Health Economics, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK.
| | - Angela Farr
- Swansea Centre for Health Economics, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Ashley Akbari
- Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Andrew Carson-Stevens
- PRIME Centre Wales, Division of Population Medicine, Cardiff University, Heath Park, Cardiff, CF14 4YS, UK
| | - Jeremy Dale
- Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK
| | - Adrian Edwards
- PRIME Centre Wales, Division of Population Medicine, Cardiff University, Heath Park, Cardiff, CF14 4YS, UK
| | - Bridie Angela Evans
- Swansea University Medical School and PRIME Centre Wales, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Ann John
- Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Fatemeh Torabi
- Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Stephen Jolles
- Immunodeficiency Centre for Wales, University Hospital of Wales, Cardiff, CF14 4XW, UK
| | - Mark Kingston
- Swansea University Medical School and PRIME Centre Wales, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Jane Lyons
- Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Ronan A Lyons
- Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Alison Porter
- Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Alan Watkins
- Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Victoria Williams
- Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Helen Snooks
- Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
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20
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Gibson JAG, Dobbs TD, Griffiths R, Song J, Akbari A, Bodger O, Hutchings HA, Lyons RA, John A, Whitaker IS. The association of anxiety disorders and depression with facial scarring: population-based, data linkage, matched cohort analysis of 358 158 patients. BJPsych Open 2023; 9:e212. [PMID: 37964568 PMCID: PMC10753955 DOI: 10.1192/bjo.2023.547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 05/05/2023] [Accepted: 07/18/2023] [Indexed: 11/16/2023] Open
Abstract
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.
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Affiliation(s)
- John A. G. Gibson
- Reconstructive Surgery & Regenerative Medicine Research Centre,
Institute of Life Science, Swansea University Medical School,
UK; and The Welsh Centre for Burns and Plastic Surgery,
Morriston Hospital, UK
| | - Thomas D. Dobbs
- Reconstructive Surgery & Regenerative Medicine Research Centre,
Institute of Life Science, Swansea University Medical School,
UK; and The Welsh Centre for Burns and Plastic Surgery,
Morriston Hospital, UK
| | - Rowena Griffiths
- Population Data Science, Swansea University Medical School, Faculty of
Medicine, Health & Life Science, Swansea University,
UK
| | - Jiao Song
- Population Data Science, Swansea University Medical School, Faculty of
Medicine, Health & Life Science, Swansea University,
UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of
Medicine, Health & Life Science, Swansea University,
UK; and Patient and Population Health and Informatics Research, Swansea
University Medical School, Faculty of Medicine, Health & Life Science,
Swansea University, UK
| | - Owen Bodger
- Patient and Population Health and Informatics Research, Swansea University
Medical School, Faculty of Medicine, Health & Life Science, Swansea
University, UK
| | - Hayley A. Hutchings
- Patient and Population Health and Informatics Research, Swansea University
Medical School, Faculty of Medicine, Health & Life Science, Swansea
University, UK
| | - Ronan A. Lyons
- Population Data Science, Swansea University Medical School, Faculty of
Medicine, Health & Life Science, Swansea University,
UK; and Patient and Population Health and Informatics Research, Swansea
University Medical School, Faculty of Medicine, Health & Life Science,
Swansea University, UK
| | - Ann John
- Population Data Science, Swansea University Medical School, Faculty of
Medicine, Health & Life Science, Swansea University,
UK; and Patient and Population Health and Informatics Research, Swansea
University Medical School, Faculty of Medicine, Health & Life Science,
Swansea University, UK
| | - Iain S. Whitaker
- Reconstructive Surgery & Regenerative Medicine Research Centre,
Institute of Life Science, Swansea University Medical School,
UK; and The Welsh Centre for Burns and Plastic Surgery,
Morriston Hospital, UK
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21
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Tsang RS, Agrawal U, Joy M, Byford R, Robertson C, Anand SN, Hinton W, Mayor N, Kar D, Williams J, Victor W, Akbari A, Bradley DT, Murphy S, O'Reilly D, Owen RK, Chuter A, Beggs J, Howsam G, Sheikh A, Richard Hobbs FD, Lusignan SD. Adverse events after first and second doses of COVID-19 vaccination in England: a national vaccine surveillance platform self-controlled case series study. J R Soc Med 2023:1410768231205430. [PMID: 37921538 DOI: 10.1177/01410768231205430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2023] Open
Abstract
OBJECTIVES To estimate the incidence of adverse events of interest (AEIs) after receiving their first and second doses of coronavirus disease 2019 (COVID-19) vaccinations, and to report the safety profile differences between the different COVID-19 vaccines. DESIGN We used a self-controlled case series design to estimate the relative incidence (RI) of AEIs reported to the Oxford-Royal College of General Practitioners national sentinel network. We compared the AEIs that occurred seven days before and after receiving the COVID-19 vaccinations to background levels between 1 October 2020 and 12 September 2021. SETTING England, UK. PARTICIPANTS Individuals experiencing AEIs after receiving first and second doses of COVID-19 vaccines. MAIN OUTCOME MEASURES AEIs determined based on events reported in clinical trials and in primary care during post-license surveillance. RESULTS A total of 7,952,861 individuals were vaccinated with COVID-19 vaccines within the study period. Among them, 781,200 individuals (9.82%) presented to general practice with 1,482,273 AEIs. Within the first seven days post-vaccination, 4.85% of all the AEIs were reported. There was a 3-7% decrease in the overall RI of AEIs in the seven days after receiving both doses of Pfizer-BioNTech BNT162b2 (RI = 0.93; 95% CI: 0.91-0.94) and 0.96; 95% CI: 0.94-0.98), respectively) and Oxford-AstraZeneca ChAdOx1 (RI = 0.97; 95% CI: 0.95-0.98) for both doses), but a 20% increase after receiving the first dose of Moderna mRNA-1273 (RI = 1.20; 95% CI: 1.00-1.44)). CONCLUSIONS COVID-19 vaccines are associated with a small decrease in the incidence of medically attended AEIs. Sentinel networks could routinely report common AEI rates, which could contribute to reporting vaccine safety.
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Affiliation(s)
- Ruby Sm Tsang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Chris Robertson
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, UK
- Public Health Scotland, Glasgow, G2 6QE, UK
| | - Sneha N Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - William Hinton
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Nikhil Mayor
- Royal Surrey NHS Foundation Trust, Guildford, GU2 7XX, UK
| | - Debasish Kar
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - John Williams
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - William Victor
- Royal College of General Practitioners, London, NW1 2FB, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, SA2 8QA, UK
| | - Declan T Bradley
- Centre for Public Health, Queen's University Belfast, Belfast, BT12 6BA, UK
- Public Health Agency, Belfast, BT2 8BS, UK
| | - Siobhan Murphy
- Centre for Public Health, Queen's University Belfast, Belfast, BT12 6BA, UK
| | - Dermot O'Reilly
- Centre for Public Health, Queen's University Belfast, Belfast, BT12 6BA, UK
| | - Rhiannon K Owen
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, SA2 8QA, UK
| | - Antony Chuter
- BREATHE - The Health Data Research Hub for Respiratory Health, Edinburgh, EH16 4SS, UK
| | - Jillian Beggs
- BREATHE - The Health Data Research Hub for Respiratory Health, Edinburgh, EH16 4SS, UK
| | - Gary Howsam
- Royal College of General Practitioners, London, NW1 2FB, UK
| | - Aziz Sheikh
- Usher Institute, University of Edinburgh, Edinburgh, EH16 4SS, UK
| | - F D Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, OX2 6GG, UK
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, UK
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Lowthian E, Bedston S, Kristensen SM, Akbari A, Fry R, Huxley K, Johnson R, Kim HS, Owen RK, Taylor C, Griffiths L. Maternal Mental Health and Children's Problem Behaviours: A Bi-directional Relationship? Res Child Adolesc Psychopathol 2023; 51:1611-1626. [PMID: 37400731 PMCID: PMC10628040 DOI: 10.1007/s10802-023-01086-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2023] [Indexed: 07/05/2023]
Abstract
Transactional theory and the coercive family process model have illustrated how the parent-child relationship is reciprocal. Emerging research using advanced statistical methods has examined these theories, but further investigations are necessary. In this study, we utilised linked health data on maternal mental health disorders and explored their relationship with child problem behaviours via the Strengths and Difficulties Questionnaire for over 13 years. We accessed data from the Millennium Cohort Study, linked to anonymised individual-level population-scale health and administrative data within the Secure Anonymised Information Linkage (SAIL) Databank. We used Bayesian Structural Equation Modelling, specifically Random-Intercept Cross-Lagged Panel Models, to analyse the relationships between mothers and their children. We then explored these models with the addition of time-invariant covariates. We found that a mother's mental health was strongly associated over time, as were children's problem behaviours. We found mixed evidence for bi-directional relationships, with only emotional problems showing bi-directional associations in mid to late childhood. Only child-to-mother pathways were identified for the overall problem behaviour score and peer problems; no associations were found for conduct problems or hyperactivity. All models had strong between-effects and clear socioeconomic and sex differences. We encourage the use of whole family-based support for mental health and problem behaviours, and recommend that socioeconomic, sex and wider differences should be considered as factors in tailoring family-based interventions and support.
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Affiliation(s)
- Emily Lowthian
- Population Data Science, Swansea University Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales.
- Department of Education and Childhood Studies, School of Social Sciences, Swansea University, Swansea, SA2 8PP, Wales.
| | - Stuart Bedston
- Population Data Science, Swansea University Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales
| | | | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales
| | - Richard Fry
- Population Data Science, Swansea University Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales
| | - Katy Huxley
- School of Social Sciences, Population Data Science, Swansea University Medical School, Swansea University, Wales, UK
| | - Rhodri Johnson
- Population Data Science, Swansea University Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales
| | - Hyun Sue Kim
- Virginia Tech Carilion School of Medicine, 2 Riverside Circle, Roanoke, VA, 24016, United States
| | - Rhiannon K Owen
- Population Data Science, Swansea University Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales
| | - Chris Taylor
- School of Social Sciences, Population Data Science, Swansea University Medical School, Swansea University, Wales, UK
| | - Lucy Griffiths
- Population Data Science, Swansea University Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales
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23
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Fonferko-Shadrach B, Lacey AS, Strafford H, Jones C, Baker M, Powell R, Akbari A, Lyons RA, Ford D, Thompson S, Jones KH, Chung SK, Pickrell WO, Rees MI. Genetic influences on epilepsy outcomes: A whole-exome sequencing and health care records data linkage study. Epilepsia 2023; 64:3099-3108. [PMID: 37643892 DOI: 10.1111/epi.17766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 08/31/2023]
Abstract
OBJECTIVE This study was undertaken to develop a novel pathway linking genetic data with routinely collected data for people with epilepsy, and to analyze the influence of rare, deleterious genetic variants on epilepsy outcomes. METHODS We linked whole-exome sequencing (WES) data with routinely collected primary and secondary care data and natural language processing (NLP)-derived seizure frequency information for people with epilepsy within the Secure Anonymised Information Linkage Databank. The study participants were adults who had consented to participate in the Swansea Neurology Biobank, Wales, between 2016 and 2018. DNA sequencing was carried out as part of the Epi25 collaboration. For each individual, we calculated the total number and cumulative burden of rare and predicted deleterious genetic variants and the total of rare and deleterious variants in epilepsy and drug metabolism genes. We compared these measures with the following outcomes: (1) no unscheduled hospital admissions versus unscheduled admissions for epilepsy, (2) antiseizure medication (ASM) monotherapy versus polytherapy, and (3) at least 1 year of seizure freedom versus <1 year of seizure freedom. RESULTS We linked genetic data for 107 individuals with epilepsy (52% female) to electronic health records. Twenty-six percent had unscheduled hospital admissions, and 70% were prescribed ASM polytherapy. Seizure frequency information was linked for 100 individuals, and 10 were seizure-free. There was no significant difference between the outcome groups in terms of the exome-wide and gene-based burden of rare and deleterious genetic variants. SIGNIFICANCE We successfully uploaded, annotated, and linked genetic sequence data and NLP-derived seizure frequency data to anonymized health care records in this proof-of-concept study. We did not detect a genetic influence on real-world epilepsy outcomes, but our study was limited by a small sample size. Future studies will require larger (WES) data to establish genetic variant contribution to epilepsy outcomes.
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Affiliation(s)
| | - Arron S Lacey
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
| | - Huw Strafford
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
| | - Carys Jones
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
| | - Mark Baker
- Swansea Bay University Health Board, Swansea, UK
| | - Robert Powell
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
- Swansea Bay University Health Board, Swansea, UK
| | - Ashley Akbari
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
| | - Ronan A Lyons
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
| | - David Ford
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
| | - Simon Thompson
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
| | - Kerina H Jones
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
| | - Seo-Kyung Chung
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
- Brain & Mind Centre, University of Sydney, Camperdown, New South Wales, Australia
- Kids Research, Children's Hospital at Westmead, Sydney, New South Wales, Australia
| | - William O Pickrell
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
- Swansea Bay University Health Board, Swansea, UK
| | - Mark I Rees
- Faculty of Medicine, Health, & Life Science, Swansea University Medical School, Swansea, UK
- Faculty of Medicine & Health, University of Sydney, Camperdown, New South Wales, Australia
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24
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Melis G, Bedston S, Akbari A, Bennett D, Lee A, Lowthian E, Schlüter D, Taylor-Robinson D. Impact of socio-economic conditions and perinatal factors on risk of becoming a child looked after: a whole population cohort study using routinely collected data in Wales. Public Health 2023; 224:215-223. [PMID: 37856904 DOI: 10.1016/j.puhe.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 08/23/2023] [Accepted: 09/01/2023] [Indexed: 10/21/2023]
Abstract
OBJECTIVES Between 1997 and 2021, the number of children looked after (CLA) in Wales, UK, increased steadily, with stark inequalities. We aimed to assess how deprivation and maternal and child perinatal characteristics influence the risk of becoming CLA in Wales. STUDY DESIGN We constructed a prospective longitudinal cohort of children born in Wales between April 2006 and March 2021 (n = 395,610) using linked administrative records. METHODS Survival models examined the risk of CLA from birth by small-area deprivation and maternal and child perinatal characteristics. Population attributable fractions quantify the potential impact of action on modifiable risk factors. RESULTS Children from the most deprived fifth of the population were 3.4 times more likely to enter care than those in the least deprived (demographic adjusted hazard ratios [aHRs] 3.40, 95% confidence interval [CI] 3.08, 3.74). Maternal mental health problems in pregnancy (fully aHR, 2.03, 95% CI 1.88, 2.19) and behavioural factors, such as smoking (aHR 2.46, 95% CI 2.34-2.60), alcohol problems (aHR 2.35, 95% CI 1.70-3.23) and substance use in pregnancy (aHR 5.72, 95% CI 5.03-6.51), as well as child congenital anomalies (aHR 1.46, 95% CI 1.16-1.84), low birth weight (aHR 1.28, 95% CI 1.17, 1.39) and preterm birth (aHR 1.16, 95% CI 1.06, 1.26), were associated with higher risk of CLA status. The risk of CLA in the population may be reduced by 35% (95% CI 0.33, 0.38) if children in the two most deprived fifths of the population experienced the conditions of those in the least deprived. CONCLUSIONS Deprivation and perinatal maternal health are important modifiable risk factors for children becoming CLA. Our analysis provides insight into the mechanisms of intergenerational transfer of disadvantage in a vulnerable section of the child population and identifies targets for public health action.
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Affiliation(s)
- G Melis
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK; NHS England, National Disease Registration Service, UK.
| | - S Bedston
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - A Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - D Bennett
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - A Lee
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - E Lowthian
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK; Department of Education & Childhood Studies, School of Social Sciences, Swansea University, Swansea, UK
| | - D Schlüter
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - D Taylor-Robinson
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
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25
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Geary RS, Thompson DA, Garrett JK, Mizen A, Rowney FM, Song J, White MP, Lovell R, Watkins A, Lyons RA, Williams S, Stratton G, Akbari A, Parker SC, Nieuwenhuijsen MJ, White J, Wheeler BW, Fry R, Tsimpida D, Rodgers SE. 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. Public Health Res (Southampt) 2023; 11:1-176. [PMID: 37929711 DOI: 10.3310/lqpt9410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023] Open
Abstract
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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Affiliation(s)
- Rebecca S Geary
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | | | - Joanne K Garrett
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Amy Mizen
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Francis M Rowney
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Jiao Song
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Mathew P White
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Rebecca Lovell
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Alan Watkins
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Ronan A Lyons
- Department of Health Data Science, Swansea University, Swansea, UK
| | | | | | - Ashley Akbari
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Sarah C Parker
- Department of Health Data Science, Swansea University, Swansea, UK
| | | | - James White
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK
| | - Benedict W Wheeler
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Richard Fry
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Dialechti Tsimpida
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Sarah E Rodgers
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
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26
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Geary RS, Thompson D, Mizen A, Akbari A, Garrett JK, Rowney FM, Watkins A, Lyons RA, Stratton G, Lovell R, Nieuwenhuijsen M, Parker SC, Song J, Tsimpida D, White J, White MP, Williams S, Wheeler BW, Fry R, Rodgers SE. 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. Lancet Planet Health 2023; 7:e809-e818. [PMID: 37821160 DOI: 10.1016/s2542-5196(23)00212-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 07/27/2023] [Accepted: 08/25/2023] [Indexed: 10/13/2023]
Abstract
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.
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Affiliation(s)
- Rebecca S Geary
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Daniel Thompson
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Amy Mizen
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Ashley Akbari
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Joanne K Garrett
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Francis M Rowney
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Alan Watkins
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Ronan A Lyons
- Department of Health Data Science, Swansea University, Swansea, UK
| | | | - Rebecca Lovell
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | | | - Sarah C Parker
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Jiao Song
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Dialechti Tsimpida
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - James White
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK
| | - Mathew P White
- Cognitive Science Hub, University of Vienna, Vienna, Austria
| | | | - Benedict W Wheeler
- European Centre for Environment and Human Health, University of Exeter Medical School, University of Exeter, Truro, UK
| | - Richard Fry
- Department of Health Data Science, Swansea University, Swansea, UK
| | - Sarah E Rodgers
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
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27
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Mhereeg M, Jones H, Kennedy J, Seaborne M, Parker M, Kennedy N, Akbari A, Zuccolo L, Azcoaga-Lorenzo A, Davies A, Nirantharakumar K, Brophy S. COVID-19 vaccination in pregnancy: the impact of multimorbidity and smoking status on vaccine hesitancy, a cohort study of 25,111 women in Wales, UK. BMC Infect Dis 2023; 23:594. [PMID: 37697235 PMCID: PMC10496238 DOI: 10.1186/s12879-023-08555-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 08/22/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Multimorbidity, smoking status, and pregnancy are identified as three risk factors associated with more severe outcomes following a SARS-CoV-2 infection, thus vaccination uptake is crucial for pregnant women living with multimorbidity and a history of smoking. This study aimed to examine the impact of multimorbidity, smoking status, and demographics (age, ethnic group, area of deprivation) on vaccine hesitancy among pregnant women in Wales using electronic health records (EHR) linkage. METHODS This cohort study utilised routinely collected, individual-level, anonymised population-scale linked data within the Secure Anonymised Information Linkage (SAIL) Databank. Pregnant women were identified from 13th April 2021 to 31st December 2021. Survival analysis was employed to examine and compare the length of time to vaccination uptake in pregnancy by considering multimorbidity, smoking status, as well as depression, diabetes, asthma, and cardiovascular conditions independently. The study also assessed the variation in uptake by multimorbidity, smoking status, and demographics, both jointly and separately for the independent conditions, using hazard ratios (HR) derived from the Cox regression model. RESULTS Within the population cohort, 8,203 (32.7%) received at least one dose of the COVID-19 vaccine during pregnancy, with 8,572 (34.1%) remaining unvaccinated throughout the follow-up period, and 8,336 (33.2%) receiving the vaccine postpartum. Women aged 30 years or older were more likely to have the vaccine in pregnancy. Those who had depression were slightly but significantly more likely to have the vaccine compared to those without depression (HR = 1.08, 95% CI 1.03 to 1.14, p = 0.002). Women living with multimorbidity were 1.12 times more likely to have the vaccine compared to those living without multimorbidity (HR = 1.12, 95% CI 1.04 to 1.19, p = 0.001). Vaccine uptakes were significantly lower among both current smokers and former smokers compared to never smokers (HR = 0.87, 95% CI 0.81 to 0.94, p < 0.001 and HR = 0.92, 95% CI 0.85 to 0.98, p = 0.015 respectively). Uptake was also lower among those living in the most deprived areas compared to those living in the most affluent areas (HR = 0.89, 95% CI 0.83 to 0.96, p = 0.002). CONCLUSION Younger women, living without multimorbidity, current and former smokers, and those living in the more deprived areas are less likely to have the vaccine, thus, a targeted approach to vaccinations may be required for these groups. Pregnant individuals living with multimorbidity exhibit a slight but statistically significant reduction in vaccine hesitancy towards COVID-19 during pregnancy.
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Affiliation(s)
- Mohamed Mhereeg
- National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK.
- Data Lab, National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK.
| | - Hope Jones
- National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
| | - Jonathan Kennedy
- National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
- Data Lab, National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
| | - Mike Seaborne
- National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
- Data Lab, National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
| | - Michael Parker
- National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
- Data Lab, National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
| | - Natasha Kennedy
- National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
- Health Data Research UK, Swansea University Medical School, Swansea, UK
| | - Ashley Akbari
- Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
| | - Luisa Zuccolo
- Health Data Science Centre, Fondazione Human Technopole, Milan, Italy
| | - Amaya Azcoaga-Lorenzo
- School of Medicine, University of St Andrews, Scotland, UK
- Hospital Rey Juan Carlos, University of St Andrews, Instituto de Investigación Sanitaria Fundación Jimenez Diaz. Madrid, Madrid, Spain
| | - Alisha Davies
- Research and Evaluation Division, Public Health Wales, Wales, UK
| | | | - Sinead Brophy
- National Centre for Population Health and Wellbeing Research, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea, Wales, UK
- Health Data Research UK, Swansea University Medical School, Swansea, UK
- Administrative Data Research Wales, Swansea University Medical School, Swansea, UK
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28
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Lyons J, Akbari A, Abrams KR, Azcoaga Lorenzo A, Ba Dhafari T, Chess J, Denaxas S, Fry R, Gale CP, Gallacher J, Griffiths LJ, Guthrie B, Hall M, Jalali-najafabadi F, John A, MacRae C, McCowan C, Peek N, O’Reilly D, Rafferty J, Lyons RA, Owen RK. Trajectories in chronic disease accrual and mortality across the lifespan in Wales, UK (2005-2019), by area deprivation profile: linked electronic health records cohort study on 965,905 individuals. Lancet Reg Health Eur 2023; 32:100687. [PMID: 37520147 PMCID: PMC10372901 DOI: 10.1016/j.lanepe.2023.100687] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 06/27/2023] [Accepted: 06/29/2023] [Indexed: 08/01/2023]
Abstract
Background Understanding and quantifying the differences in disease development in different socioeconomic groups of people across the lifespan is important for planning healthcare and preventive services. The study aimed to measure chronic disease accrual, and examine the differences in time to individual morbidities, multimorbidity, and mortality between socioeconomic groups in Wales, UK. Methods Population-wide electronic linked cohort study, following Welsh residents for up to 20 years (2000-2019). Chronic disease diagnoses were obtained from general practice and hospitalisation records using the CALIBER disease phenotype register. Multi-state models were used to examine trajectories of accrual of 132 diseases and mortality, adjusted for sex, age and area-level deprivation. Restricted mean survival time was calculated to measure time spent free of chronic disease(s) or mortality between socioeconomic groups. Findings In total, 965,905 individuals aged 5-104 were included, from a possible 2.9 m individuals following a 5-year clearance period, with an average follow-up of 13.2 years (12.7 million person-years). Some 673,189 (69.7%) individuals developed at least one chronic disease or died within the study period. From ages 10 years upwards, the individuals living in the most deprived areas consistently experienced reduced time between health states, demonstrating accelerated transitions to first and subsequent morbidities and death compared to their demographic equivalent living in the least deprived areas. The largest difference were observed in 10 and 20 year old males developing multimorbidity (-0.45 years (99% CI: -0.45, -0.44)) and in 70 year old males dying after developing multimorbidity (-1.98 years (99% CI: -2.01, -1.95)). Interpretation This study adds to the existing literature on health inequalities by demonstrating that individuals living in more deprived areas consistently experience accelerated time to diagnosis of chronic disease and death across all ages, accounting for competing risks. Funding UK Medical Research Council, Health Data Research UK, and Administrative Data Research Wales.
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Affiliation(s)
- Jane Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
| | - Keith R. Abrams
- Department of Statistics, University of Warwick, Coventry, UK
- Centre for Health Economics, University of York, York, UK
| | - Amaya Azcoaga Lorenzo
- Instituto Investigación Sanitaria Fundación Jimenez Diaz, Madrid, Spain
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Thamer Ba Dhafari
- Division of Informatics, Imaging and Data Science, School of Health Sciences, University of Manchester, Manchester, UK
| | - James Chess
- Swansea Bay Health Board, Morriston Hospital, Swansea, Wales, UK
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
| | - Richard Fry
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
| | | | - John Gallacher
- Dementias Platform UK, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Lucy J. Griffiths
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
| | - Bruce Guthrie
- Advanced Care Research Centre, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Marlous Hall
- Leeds Institute of Cardiovascular and Metabolic Medicine and Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
| | - Farideh Jalali-najafabadi
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Ann John
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
| | - Clare MacRae
- Advanced Care Research Centre, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Colin McCowan
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Niels Peek
- Division of Informatics, Imaging and Data Science, School of Health Sciences, University of Manchester, Manchester, UK
| | - Dermot O’Reilly
- School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, UK
| | - James Rafferty
- Swansea Trials Unit, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
| | - Ronan A. Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
| | - Rhiannon K. Owen
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK
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29
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Snooks H, Watkins A, Lyons J, Akbari A, Bailey R, Bethell L, Carson-Stevens A, Dale J, Edwards A, Emery H, Evans BA, Jolles S, John A, Kingston M, Porter A, Sewell B, Williams V, Lyons RA. Corrigendum to "Did the UK's public health shielding policy protect the clinically extremely vulnerable during the COVID-19 pandemic in wales? Results of EVITE immunity, a linked data retrospective study" [Public Health 218 (2023) 12-20]. Public Health 2023; 222:229. [PMID: 37463828 PMCID: PMC11021201 DOI: 10.1016/j.puhe.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Affiliation(s)
- H Snooks
- Swansea University, Medical School, ILS 2, Singleton Park, SA2 8PP, Swansea, UK.
| | - A Watkins
- Swansea University, Medical School, ILS 2, Singleton Park, SA2 8PP, Swansea, UK
| | - J Lyons
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, SA2 8PP, Swansea, UK
| | - A Akbari
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, SA2 8PP, Swansea, UK
| | - R Bailey
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, SA2 8PP, Swansea, UK
| | - L Bethell
- Swansea University, Medical School, ILS 2, Singleton Park, SA2 8PP, Swansea, UK
| | - A Carson-Stevens
- Cardiff University, Division of Population Medicine, University Hospital of Wales, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK
| | - J Dale
- The University of Warwick, Medical School, Coventry CV4 7AL, UK
| | - A Edwards
- Cardiff University, Division of Population Medicine, University Hospital of Wales, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK
| | - H Emery
- Swansea University, Medical School, ILS 2, Singleton Park, SA2 8PP, Swansea, UK
| | - B A Evans
- Swansea University, Medical School, ILS 2, Singleton Park, SA2 8PP, Swansea, UK
| | - S Jolles
- Immunodeficiency Centre for Wales, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK
| | - A John
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, SA2 8PP, Swansea, UK
| | - M Kingston
- Swansea University, Medical School, ILS 2, Singleton Park, SA2 8PP, Swansea, UK
| | - A Porter
- Swansea University, Medical School, ILS 2, Singleton Park, SA2 8PP, Swansea, UK
| | - B Sewell
- Swansea University, School of Health and Social Care, Vivian Tower, Singleton Park, SA2 8PP, Swansea, UK
| | - V Williams
- Swansea University, Medical School, ILS 2, Singleton Park, SA2 8PP, Swansea, UK
| | - R A Lyons
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, SA2 8PP, Swansea, UK
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30
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Han J, Rolles M, Torabi F, Griffiths R, Bedston S, Akbari A, Burnett B, Lyons J, Greene G, Thomas R, Long T, Arnold C, Huws DW, Lawler M, Lyons RA. The impact of the COVID-19 pandemic on community prescription of opioid and antineuropathic analgesics for cancer patients in Wales, UK. Support Care Cancer 2023; 31:531. [PMID: 37606853 PMCID: PMC10444652 DOI: 10.1007/s00520-023-07944-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 07/12/2023] [Indexed: 08/23/2023]
Abstract
PURPOSE Public health measures instituted at the onset of the COVID-19 pandemic in the UK in 2020 had profound effects on the cancer patient pathway. We hypothesise that this may have affected analgesic prescriptions for cancer patients in primary care. METHODS A whole-nation retrospective, observational study of opioid and antineuropathic analgesics prescribed in primary care for two cohorts of cancer patients in Wales, using linked anonymised data to evaluate the impact of the pandemic and variation between different demographic backgrounds. RESULTS We found a significant increase in strong opioid prescriptions during the pandemic for patients within their first 12 months of diagnosis with a common cancer (incidence rate ratio (IRR) 1.15, 95% CI: 1.12-1.18, p < 0.001 for strong opioids) and significant increases in strong opioid and antineuropathic prescriptions for patients in the last 3 months prior to a cancer-related death (IRR = 1.06, 95% CI: 1.04-1.07, p < 0.001 for strong opioids; IRR = 1.11, 95% CI: 1.08-1.14, p < 0.001 for antineuropathics). A spike in opioid prescriptions for patients diagnosed in Q2 2020 and those who died in Q2 2020 was observed and interpreted as stockpiling. More analgesics were prescribed in more deprived quintiles. This differential was less pronounced in patients towards the end of life, which we attribute to closer professional supervision. CONCLUSIONS We demonstrate significant changes to community analgesic prescriptions for cancer patients related to the UK pandemic and illustrate prescription patterns linked to patients' demographic background.
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Affiliation(s)
- Jun Han
- Population Data Science, Swansea University Medical School, Swansea, UK
- DATA-CAN, the UK's Health Data Research Hub for Cancer, London, UK
| | - Martin Rolles
- Population Data Science, Swansea University Medical School, Swansea, UK.
- South West Wales Cancer Centre, Swansea Bay University Health Board, Swansea, UK.
| | - Fatemeh Torabi
- Population Data Science, Swansea University Medical School, Swansea, UK
| | - Rowena Griffiths
- Population Data Science, Swansea University Medical School, Swansea, UK
| | - Stuart Bedston
- Population Data Science, Swansea University Medical School, Swansea, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea, UK
- DATA-CAN, the UK's Health Data Research Hub for Cancer, London, UK
| | - Bruce Burnett
- Population Data Science, Swansea University Medical School, Swansea, UK
| | - Jane Lyons
- Population Data Science, Swansea University Medical School, Swansea, UK
| | - Giles Greene
- Welsh Cancer Intelligence and Surveillance Unit, Public Health Wales, Cardiff, UK
| | - Rebecca Thomas
- Observatory and Cancer Analysis Team, Public Health Wales, Cardiff, UK
| | - Tamsin Long
- Observatory and Cancer Analysis Team, Public Health Wales, Cardiff, UK
| | - Cathy Arnold
- DATA-CAN, the UK's Health Data Research Hub for Cancer, London, UK
- Data Services, University of Leeds, Leeds, UK
| | - Dyfed Wyn Huws
- Welsh Cancer Intelligence and Surveillance Unit, Public Health Wales, Cardiff, UK
| | - Mark Lawler
- DATA-CAN, the UK's Health Data Research Hub for Cancer, London, UK
- Patrick G Johnston Centre for Cancer Research, Queens University Belfast, Belfast, UK
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Swansea, UK
- DATA-CAN, the UK's Health Data Research Hub for Cancer, London, UK
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31
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Porter A, Akbari A, Carson-Stevens A, Dale J, Dixon L, Edwards A, Evans B, Griffiths L, John A, Jolles S, Kingston MR, Lyons R, Morgan J, Sewell B, Whiffen A, Williams VA, Snooks H. Rationale for the shielding policy for clinically vulnerable people in the UK during the COVID-19 pandemic: a qualitative study. BMJ Open 2023; 13:e073464. [PMID: 37541747 PMCID: PMC10407356 DOI: 10.1136/bmjopen-2023-073464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 07/19/2023] [Indexed: 08/06/2023] Open
Abstract
INTRODUCTION Shielding aimed to protect those predicted to be at highest risk from COVID-19 and was uniquely implemented in the UK during the first year of the pandemic from March 2020. As the first stage in the EVITE Immunity evaluation (Effects of shielding for vulnerable people during COVID-19 pandemic on health outcomes, costs and immunity, including those with cancer:quasi-experimental evaluation), we generated a logic model to describe the programme theory underlying the shielding intervention. DESIGN AND PARTICIPANTS We reviewed published documentation on shielding to develop an initial draft of the logic model. We then discussed this draft during interviews with 13 key stakeholders involved in putting shielding into effect in Wales and England. Interviews were recorded, transcribed and analysed thematically to inform a final draft of the logic model. RESULTS The shielding intervention was a complex one, introduced at pace by multiple agencies working together. We identified three core components: agreement on clinical criteria; development of the list of people appropriate for shielding; and communication of shielding advice. In addition, there was a support programme, available as required to shielding people, including food parcels, financial support and social support. The predicted mechanism of change was that people would isolate themselves and so avoid infection, with the primary intended outcome being reduction in mortality in the shielding group. Unintended impacts included negative impact on mental and physical health and well-being. Details of the intervention varied slightly across the home nations of the UK and were subject to minor revisions during the time the intervention was in place. CONCLUSIONS Shielding was a largely untested strategy, aiming to mitigate risk by placing a responsibility on individuals to protect themselves. The model of its rationale, components and outcomes (intended and unintended) will inform evaluation of the impact of shielding and help us to understand its effect and limitations.
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Affiliation(s)
- Alison Porter
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Ashley Akbari
- Swansea University Medical School, Swansea University, Swansea, UK
| | | | - Jeremy Dale
- Warwick Medical School, University of Warwick, Coventry, UK
| | - Lucy Dixon
- Public Contributor, SUPER group, Swansea, UK
| | | | - Bridie Evans
- Swansea University Medical School, Swansea University, Swansea, UK
| | | | - Ann John
- Swansea University Medical School, Swansea University, Swansea, UK
| | | | | | - Ronan Lyons
- Swansea University Medical School, Swansea University, Swansea, UK
| | | | - Bernadette Sewell
- College of Human and Health Sciences, Swansea University, Swansea, UK
| | - Anthony Whiffen
- Administrative Data Research Unit, Welsh Government, Cardiff, UK
| | | | - Helen Snooks
- Swansea University Medical School, Swansea University, Swansea, UK
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32
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Schnier C, McCarthy A, Morales DR, Akbari A, Sofat R, Dale C, Takhar R, Mamas MA, Khunti K, Zaccardi F, Sudlow CL, Wilkinson T. Antipsychotic drug prescribing and mortality in people with dementia before and during the COVID-19 pandemic: a retrospective cohort study in Wales, UK. Lancet Healthy Longev 2023; 4:e421-e430. [PMID: 37543047 DOI: 10.1016/s2666-7568(23)00105-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/03/2023] [Accepted: 06/05/2023] [Indexed: 08/07/2023] Open
Abstract
BACKGROUND Concerns have been raised that antipsychotic drug prescribing, which has been associated with increased mortality in people with dementia, might have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of SARS-CoV-2. We used multisource, routinely collected health-care data from Wales, UK to investigate prescribing and mortality variations in people with dementia before and during the COVID-19 pandemic. METHODS In this retrospective cohort study, we used individual-level, anonymised, population-scale linked health data to identify adults aged 60 years and older with a diagnosis of dementia in Wales, UK. We used the CVD-COVID-UK initiative to access Welsh routinely collected electronic health record data from the Secure Anonymised Information Linkage (SAIL) Databank. Patients who were alive and registered with a SAIL general practice on Jan 1, 2016, and who received a dementia diagnosis before the age of 60 years and before or during the study period were included. We explored antipsychotic drug prescribing rate changes over 67 months, between Jan 1, 2016, and Aug 1, 2021, overall and stratified by age and dementia subtype. We used time-series analyses to examine all-cause and myocardial infarction and stroke mortality over the study period and identified the leading causes of death in people with dementia between Jan 1, 2020, and Aug 1, 2021. FINDINGS Of 3 106 690 participants in SAIL between Jan 1, 2016 and Aug 1, 2021, 57 396 people (35 148 [61·2%] women and 22 248 [38·8%] men) met inclusion criteria for this study and contributed 101 428 person-years of follow-up. Of the 57 396 people with dementia, 11 929 (20·8%) were prescribed an antipsychotic drug at any point during follow-up. Accounting for seasonality, antipsychotic drug prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 prescriptions per 10 000 person-months in March, 2019, to 1305 per 10 000 person-months in September, 2020. All-cause mortality and stroke mortality increased throughout 2020, while myocardial infarction mortality declined. From Jan 1, 2020, to Aug 1, 2021, 1286 (17·1%) of 7508 participants who died had COVID-19 recorded as the underlying cause of death. INTERPRETATION During the COVID-19 pandemic, antipsychotic drug prescribing in people with dementia in the UK increased slightly; however, it is unlikely that this was solely related to the pandemic and this increase was unlikely to be a major factor in the substantial increase in mortality during 2020. The long-term increase in antipsychotic drug prescribing in younger people and in those with Alzheimer's disease warrants further investigation using resources with access to more granular clinical data. Although deprescribing antipsychotic medications remains an essential aspect of dementia care, the results of this study suggest that changes in prescribing and deprescribing practices as a result of the COVID-19 pandemic are not required. FUNDING British Heart Foundation (via the British Heart Foundation Data Science Centre led by Health Data Research UK), and the Scottish Neurological Research Fund.
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Affiliation(s)
- Christian Schnier
- The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Aoife McCarthy
- Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, Dundee, UK; Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Ashley Akbari
- Swansea University Medical School, Swansea University, Swansea, UK
| | - Reecha Sofat
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK; British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | - Caroline Dale
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - Rohan Takhar
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - Mamas A Mamas
- Keele Cardiovascular Research Group, Keele University, Stoke-on-Trent, UK
| | - Kamlesh Khunti
- Diabetes Research Centre and Real World Evidence Unit, University of Leicester, Leicester, UK
| | - Francesco Zaccardi
- Diabetes Research Centre and Real World Evidence Unit, University of Leicester, Leicester, UK
| | - Cathie Lm Sudlow
- Usher Institute, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences UK, University of Edinburgh, Edinburgh, UK; British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | - Tim Wilkinson
- Centre for Clinical Brain Sciences UK, University of Edinburgh, Edinburgh, UK; Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
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33
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Goedegebuur J, Abbel D, Accassat S, Achterberg WP, Akbari A, Arfuch VM, Baddeley E, Bax JJ, Becker D, Bergmeijer B, Bertoletti L, Blom JW, Calvetti A, Cannegieter SC, Castro L, Chavannes NH, Coma-Auli N, Couffignal C, Edwards A, Edwards M, Enggaard H, Font C, Gava A, Geersing GJ, Geijteman ECT, Greenley S, Gregory C, Gussekloo J, Hoffmann I, Højen AA, van den Hout WB, Huisman MV, Jacobsen S, Jagosh J, Johnson MJ, Jørgensen L, Juffermans CCM, Kempers EK, Konstantinides S, Kroder AF, Kruip MJHA, Lafaie L, Langendoen JW, Larsen TB, Lifford K, van der Linden YM, Mahé I, Maiorana L, Maraveyas A, Martens ESL, Mayeur D, van Mens TE, Mohr K, Mooijaart SP, Murtagh FEM, Nelson A, Nielsen PB, Ording AG, Ørskov M, Pearson M, Poenou G, Portielje JEA, Raczkiewicz D, Rasmussen K, Trinks-Roerdink E, Schippers I, Seddon K, Sexton K, Sivell S, Skjøth F, Søgaard M, Szmit S, Trompet S, Vassal P, Visser C, van Vliet LM, Wilson E, Klok FA, Noble SIR. Towards optimal use of antithrombotic therapy of people with cancer at the end of life: A research protocol for the development and implementation of the SERENITY shared decision support tool. Thromb Res 2023; 228:54-60. [PMID: 37276718 DOI: 10.1016/j.thromres.2023.05.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/02/2023] [Accepted: 05/05/2023] [Indexed: 06/07/2023]
Abstract
BACKGROUND Even though antithrombotic therapy has probably little or even negative effects on the well-being of people with cancer during their last year of life, deprescribing antithrombotic therapy at the end of life is rare in practice. It is often continued until death, possibly resulting in excess bleeding, an increased disease burden and higher healthcare costs. METHODS The SERENITY consortium comprises researchers and clinicians from eight European countries with specialties in different clinical fields, epidemiology and psychology. SERENITY will use a comprehensive approach combining a realist review, flash mob research, epidemiological studies, and qualitative interviews. The results of these studies will be used in a Delphi process to reach a consensus on the optimal design of the shared decision support tool. Next, the shared decision support tool will be tested in a randomised controlled trial. A targeted implementation and dissemination plan will be developed to enable the use of the SERENITY tool across Europe, as well as its incorporation in clinical guidelines and policies. The entire project is funded by Horizon Europe. RESULTS SERENITY will develop an information-driven shared decision support tool that will facilitate treatment decisions regarding the appropriate use of antithrombotic therapy in people with cancer at the end of life. CONCLUSIONS We aim to develop an intervention that guides the appropriate use of antithrombotic therapy, prevents bleeding complications, and saves healthcare costs. Hopefully, usage of the tool leads to enhanced empowerment and improved quality of life and treatment satisfaction of people with advanced cancer and their care givers.
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Affiliation(s)
- J Goedegebuur
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - D Abbel
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands; Department of Medicine - Internal Medicine and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - S Accassat
- Department of Vascular and Therapeutical Medicine, University Hospital of Saint-Etienne, Saint-Étienne, France
| | - W P Achterberg
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - A Akbari
- Swansea University, Swansea, Wales, United Kingdom
| | - V M Arfuch
- Department of Medical Oncology, Hospital Clinic Barcelona, Clinical Institute of Haematological and Oncological Diseases (ICMHO), IDIBAPS, Barcelona, Spain
| | - E Baddeley
- Cardiff University, Cardiff, United Kingdom
| | - J J Bax
- Department of Medicine - Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - D Becker
- University Medical Center Mainz, Mainz, Germany
| | | | - L Bertoletti
- Department of Vascular and Therapeutical Medicine, Jean Monnet University, University Hospital of Saint-Étienne, Saint-Étienne, France
| | - J W Blom
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - A Calvetti
- Assistance Publique-Hopitaux de Paris, Paris, France
| | - S C Cannegieter
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - L Castro
- Vall d'Hebron Research Institute, Barcelona, Spain
| | - N H Chavannes
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - N Coma-Auli
- Department of Medical Oncology, Hospital Clinic Barcelona, Clinical Institute of Haematological and Oncological Diseases (ICMHO), IDIBAPS, Barcelona, Spain
| | - C Couffignal
- Hôpital Louis Mourier, APHP, Assistance Publique-Hopitaux de Paris, Paris, France
| | - A Edwards
- Cardiff University, Cardiff, United Kingdom
| | - M Edwards
- Cardiff University, Cardiff, United Kingdom
| | - H Enggaard
- Aalborg University Hospital, Aalborg, Denmark
| | - C Font
- Department of Medical Oncology, Hospital Clinic Barcelona, Clinical Institute of Haematological and Oncological Diseases (ICMHO), IDIBAPS, Barcelona, Spain
| | - A Gava
- Societa per l'Assistenza al Malato Oncologico Terminale Onlus (S.A.M.O.T.) Ragusa Onlus, Ragusa, Italy
| | - G J Geersing
- Julius Center for Health Sciences and Primary Care, Department of General Practice, University Medical Center Utrecht, Utrecht, the Netherlands
| | - E C T Geijteman
- Department of Medical Oncology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - S Greenley
- Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, United Kingdom
| | - C Gregory
- Cardiff University, Cardiff, United Kingdom
| | - J Gussekloo
- Department of Medicine - Internal Medicine and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - I Hoffmann
- Hôpital Bichat, APHP, Assistance Publique-Hopitaux de Paris, Paris, France
| | - A A Højen
- Aalborg University Hospital, Aalborg, Denmark
| | - W B van den Hout
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - M V Huisman
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
| | - S Jacobsen
- Aalborg University Hospital, Aalborg, Denmark
| | - J Jagosh
- Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, United Kingdom
| | - M J Johnson
- Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, United Kingdom
| | - L Jørgensen
- Aalborg University Hospital, Aalborg, Denmark
| | - C C M Juffermans
- Centre of Expertise in Palliative Care, Leiden University Medical Center, Leiden, the Netherlands
| | - E K Kempers
- Department of Hematology, Erasmus MC, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - A F Kroder
- Todaytomorrow, Rotterdam, the Netherlands
| | - M J H A Kruip
- Department of Hematology, Erasmus MC, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - L Lafaie
- Department of Geriatrics and Gerontology, Jean Monnet University, University Hospital of Saint-Étienne, Saint-Étienne, France
| | | | - T B Larsen
- Aalborg University Hospital, Aalborg, Denmark
| | - K Lifford
- Cardiff University, Cardiff, United Kingdom
| | - Y M van der Linden
- Centre of Expertise in Palliative Care, Leiden University Medical Center, Leiden, the Netherlands; Netherlands Comprehensive Cancer Organization, Utrecht, the Netherlands
| | - I Mahé
- Department of Innovative Therapies in Haemostasis, Hôpital Louis Mourier, APHP, Paris, France
| | - L Maiorana
- Societa per l'Assistenza al Malato Oncologico Terminale Onlus (S.A.M.O.T.) Ragusa Onlus, Ragusa, Italy
| | - A Maraveyas
- Clinical Sciences Centre Hull York Medical School University of Hull, Hull, United Kingdom
| | - E S L Martens
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
| | - D Mayeur
- Centre Georges-François Leclerc, Dijon, France
| | - T E van Mens
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
| | - K Mohr
- University Medical Center Mainz, Mainz, Germany
| | - S P Mooijaart
- Department of Medicine - Internal Medicine and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - F E M Murtagh
- Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, United Kingdom
| | - A Nelson
- Cardiff University, Cardiff, United Kingdom
| | - P B Nielsen
- Aalborg University Hospital, Aalborg, Denmark
| | - A G Ording
- Aalborg University Hospital, Aalborg, Denmark
| | - M Ørskov
- Aalborg University Hospital, Aalborg, Denmark
| | - M Pearson
- Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, United Kingdom
| | - G Poenou
- Department of Vascular and Therapeutical Medicine, Jean Monnet University, University Hospital of Saint-Étienne, Saint-Étienne, France
| | - J E A Portielje
- Department of Medicine - Internal medicine and Medical Oncology, Leiden University Medical Center, Leiden, the Netherlands
| | - D Raczkiewicz
- Department of Medical Statistics, School of Public Health, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - K Rasmussen
- Aalborg University Hospital, Aalborg, Denmark
| | - E Trinks-Roerdink
- Julius Center for Health Sciences and Primary Care, Department of General Practice, University Medical Center Utrecht, Utrecht, the Netherlands
| | | | - K Seddon
- Wales Cancer Research Centre, Cardiff, UK
| | - K Sexton
- Cardiff University, Cardiff, United Kingdom
| | - S Sivell
- Cardiff University, Cardiff, United Kingdom
| | - F Skjøth
- Aalborg University Hospital, Aalborg, Denmark
| | - M Søgaard
- Aalborg University Hospital, Aalborg, Denmark
| | - S Szmit
- Department of Cardio-Oncology, Centre of Postgraduate Medical Education, Warsaw, Poland
| | - S Trompet
- Department of Medicine - Internal Medicine and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - P Vassal
- Department of Vascular and Therapeutical Medicine, University Hospital of Saint-Etienne, Saint-Étienne, France
| | - C Visser
- Department of Hematology, Erasmus MC, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - L M van Vliet
- Department of Health, Medicine and Neuropsychology, Leiden University, Leiden, the Netherlands
| | - E Wilson
- Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, United Kingdom
| | - F A Klok
- Department of Medicine - Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands.
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Bosworth ML, Schofield R, Ayoubkhani D, Charlton L, Nafilyan V, Khunti K, Zaccardi F, Gillies C, Akbari A, Knight M, Wood R, Hardelid P, Zuccolo L, Harrison C. Vaccine effectiveness for prevention of covid-19 related hospital admission during pregnancy in England during the alpha and delta variant dominant periods of the SARS-CoV-2 pandemic: population based cohort study. BMJ Med 2023; 2:e000403. [PMID: 37564827 PMCID: PMC10410807 DOI: 10.1136/bmjmed-2022-000403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 05/18/2023] [Indexed: 08/12/2023]
Abstract
Objective To estimate vaccine effectiveness for preventing covid-19 related hospital admission in individuals first infected with the SARS-CoV-2 virus during pregnancy compared with those of reproductive age who were not pregnant when first infected with the virus. Design Population based cohort study. Setting Office for National Statistics Public Health Data Asset linked dataset, providing national linked census and administrative data in England, 8 December 2020 to 31 August 2021. Participants 815 477 females aged 18-45 years (mean age 30.4 years) who had documented evidence of a first SARS-CoV-2 infection in the NHS Test and Trace or Hospital Episode Statistics data. Main outcome measures Hospital admission where covid-19 was recorded as the primary diagnosis. Cox proportional hazards models, adjusted for calendar time of infection, sociodemographic factors, and pre-existing health conditions related to uptake of the covid-19 vaccine and risk of severe covid-19 outcomes, were used to estimate vaccine effectiveness as the complement of the hazard ratio for hospital admission for covid-19. Results Compared with pregnant individuals who were not vaccinated, the adjusted rate of hospital admission for covid-19 was 77% (95% confidence interval 70% to 82%) lower for pregnant individuals who had received one dose and 83% (76% to 89%) lower for those who had received two doses of vaccine. These estimates were similar to those found in the non-pregnant group: 79% (77% to 81%) for one dose and 83% (82% to 85%) for two doses of vaccine. Among those who were vaccinated >90 days before infection, having two doses of vaccine was associated with a greater reduction in risk than one dose. Conclusions Covid-19 vaccination was associated with reduced rates of hospital admission in pregnant individuals infected with the SARS-CoV-2 virus, and the reduction in risk was similar to that in non-pregnant individuals. Waning of vaccine effectiveness occurred more quickly after one than after two doses of vaccine.
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Affiliation(s)
| | | | - Daniel Ayoubkhani
- Office for National Statistics, Newport, UK
- Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
| | | | - Vahé Nafilyan
- Office for National Statistics, Newport, UK
- London School of Hygiene and Tropical Medicine, London, UK
| | - Kamlesh Khunti
- Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Francesco Zaccardi
- Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Clare Gillies
- Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Marian Knight
- National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rachael Wood
- Public Health Scotland, Edinburgh, UK
- The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
| | - Pia Hardelid
- NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Luisa Zuccolo
- Health Data Science Centre, Fondazione Human Technopole, Milan, Italy
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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Owen RK, Lyons J, Akbari A, Guthrie B, Agrawal U, Alexander DC, Azcoaga-Lorenzo A, Brookes AJ, Denaxas S, Dezateux C, Fagbamigbe AF, Harper G, Kirk PDW, Özyiğit EB, Richardson S, Staniszewska S, McCowan C, Lyons RA, Abrams KR. Effect on life expectancy of temporal sequence in a multimorbidity cluster of psychosis, diabetes, and congestive heart failure among 1·7 million individuals in Wales with 20-year follow-up: a retrospective cohort study using linked data. Lancet Public Health 2023; 8:e535-e545. [PMID: 37393092 DOI: 10.1016/s2468-2667(23)00098-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 04/28/2023] [Accepted: 05/02/2023] [Indexed: 07/03/2023]
Abstract
BACKGROUND To inform targeted public health strategies, it is crucial to understand how coexisting diseases develop over time and their associated impacts on patient outcomes and health-care resources. This study aimed to examine how psychosis, diabetes, and congestive heart failure, in a cluster of physical-mental health multimorbidity, develop and coexist over time, and to assess the associated effects of different temporal sequences of these diseases on life expectancy in Wales. METHODS In this retrospective cohort study, we used population-scale, individual-level, anonymised, linked, demographic, administrative, and electronic health record data from the Wales Multimorbidity e-Cohort. We included data on all individuals aged 25 years and older who were living in Wales on Jan 1, 2000 (the start of follow-up), with follow-up continuing until Dec 31, 2019, first break in Welsh residency, or death. Multistate models were applied to these data to model trajectories of disease in multimorbidity and their associated effect on all-cause mortality, accounting for competing risks. Life expectancy was calculated as the restricted mean survival time (bound by the maximum follow-up of 20 years) for each of the transitions from the health states to death. Cox regression models were used to estimate baseline hazards for transitions between health states, adjusted for sex, age, and area-level deprivation (Welsh Index of Multiple Deprivation [WIMD] quintile). FINDINGS Our analyses included data for 1 675 585 individuals (811 393 [48·4%] men and 864 192 [51·6%] women) with a median age of 51·0 years (IQR 37·0-65·0) at cohort entry. The order of disease acquisition in cases of multimorbidity had an important and complex association with patient life expectancy. Individuals who developed diabetes, psychosis, and congestive heart failure, in that order (DPC), had reduced life expectancy compared with people who developed the same three conditions in a different order: for a 50-year-old man in the third quintile of the WIMD (on which we based our main analyses to allow comparability), DPC was associated with a loss in life expectancy of 13·23 years (SD 0·80) compared with the general otherwise healthy or otherwise diseased population. Congestive heart failure as a single condition was associated with mean a loss in life expectancy of 12·38 years (0·00), and with a loss of 12·95 years (0·06) when preceded by psychosis and 13·45 years (0·13) when followed by psychosis. Findings were robust in people of older ages, more deprived populations, and women, except that the trajectory of psychosis, congestive heart failure, and diabetes was associated with higher mortality in women than men. Within 5 years of an initial diagnosis of diabetes, the risk of developing psychosis or congestive heart failure, or both, was increased. INTERPRETATION The order in which individuals develop psychosis, diabetes, and congestive heart failure as combinations of conditions can substantially affect life expectancy. Multistate models offer a flexible framework to assess temporal sequences of diseases and allow identification of periods of increased risk of developing subsequent conditions and death. FUNDING Health Data Research UK.
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Affiliation(s)
- Rhiannon K Owen
- Population Data Science, Health Data Research, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK.
| | - Jane Lyons
- Population Data Science, Health Data Research, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK
| | - Ashley Akbari
- Population Data Science, Health Data Research, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK
| | - Bruce Guthrie
- Advanced Care Research Centre, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, Faculty of Engineering Sciences, University College London, London, UK
| | - Amaya Azcoaga-Lorenzo
- School of Medicine, University of St Andrews, St Andrews, UK; Hospital Rey Juan Carlos, Instituto de Investigación Sanitaria Fundación Jimenez Diaz, Madrid, Spain
| | | | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
| | - Carol Dezateux
- Clinical Effectiveness Group, Wolfson Institute of Population Health, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | - Gill Harper
- Clinical Effectiveness Group, Wolfson Institute of Population Health, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Paul D W Kirk
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK
| | - Eda Bilici Özyiğit
- Centre for Medical Image Computing, Department of Computer Science, Faculty of Engineering Sciences, University College London, London, UK
| | | | - Sophie Staniszewska
- Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
| | - Colin McCowan
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Ronan A Lyons
- Population Data Science, Health Data Research, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK
| | - Keith R Abrams
- Department of Statistics, University of Warwick, Coventry, UK; Centre for Health Economics, University of York, York, UK
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Garrett JK, Rowney FM, White MP, Lovell R, Fry RJ, Akbari A, Geary R, Lyons RA, Mizen A, Nieuwenhuijsen M, Parker C, Song J, Stratton G, Thompson DA, Watkins A, White J, Williams SA, Rodgers SE, Wheeler BW. Visiting nature is associated with lower socioeconomic inequalities in well-being in Wales. Sci Rep 2023; 13:9684. [PMID: 37322030 PMCID: PMC10272170 DOI: 10.1038/s41598-023-35427-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 05/17/2023] [Indexed: 06/17/2023] Open
Abstract
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 β = - 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 β = 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.
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Affiliation(s)
- Joanne K Garrett
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK.
| | - Francis M Rowney
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK
- School of Geography, Earth and Environmental Sciences, University of Plymouth, Plymouth, UK
| | - Mathew P White
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK
- Cognitive Science HUB, University of Vienna, Vienna, Austria
| | - Rebecca Lovell
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK
| | - Rich J Fry
- Department of Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Ashley Akbari
- Department of Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Rebecca Geary
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Ronan A Lyons
- Department of Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Amy Mizen
- Department of Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Mark Nieuwenhuijsen
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Chrissie Parker
- Department of Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | | | - Gareth Stratton
- Faculty of Science and Engineering, ASTEM Research Centre, Swansea University, Swansea, UK
| | - Daniel A Thompson
- Department of Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Alan Watkins
- Department of Population Data Science, Faculty of Medicine, Health and Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - James White
- Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK
| | | | - Sarah E Rodgers
- Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
| | - Benedict W Wheeler
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK
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Cannings-John R, Schoenbuchner S, Jones H, Lugg-Widger FV, Akbari A, Brookes-Howell L, Hood K, John A, Thomas DR, Prout H, Robling M. Impact of the COVID-19 pandemic on domiciliary care workers in Wales, UK: a data linkage cohort study using the SAIL Databank. BMJ Open 2023; 13:e070637. [PMID: 37263685 DOI: 10.1136/bmjopen-2022-070637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/03/2023] Open
Abstract
OBJECTIVES To quantify population health risks for domiciliary care workers (DCWs) in Wales, UK, working during the COVID-19 pandemic. DESIGN A population-level retrospective study linking occupational registration data to anonymised electronic health records maintained by the Secure Anonymised Information Linkage Databank in a privacy-protecting trusted research environment. SETTING Registered DCW population in Wales. PARTICIPANTS Records for all linked DCWs from 1 March 2020 to 30 November 2021. PRIMARY AND SECONDARY OUTCOME MEASURES Our primary outcome was confirmed COVID-19 infection; secondary outcomes included contacts for suspected COVID-19, mental health including self-harm, fit notes, respiratory infections not necessarily recorded as COVID-19, deaths involving COVID-19 and all-cause mortality. RESULTS Confirmed and suspected COVID-19 infection rates increased over the study period to 24% by 30 November 2021. Confirmed COVID-19 varied by sex (males: 19% vs females: 24%) and age (>55 years: 19% vs <35 years: 26%) and were higher for care workers employed by local authority social services departments compared with the private sector (27% and 23%, respectively). 34% of DCWs required support for a mental health condition, with mental health-related prescribing increasing in frequency when compared with the prepandemic period. Events for self-harm increased from 0.2% to 0.4% over the study period as did the issuing of fit notes. There was no evidence to suggest a miscoding of COVID-19 infection with non-COVID-19 respiratory conditions. COVID-19-related and all-cause mortality were no greater than for the general population aged 15-64 years in Wales (0.1% and 0.034%, respectively). A comparable DCW workforce in Scotland and England would result in a comparable rate of COVID-19 infection, while the younger workforce in Northern Ireland may result in a greater infection rate. CONCLUSIONS While initial concerns about excess mortality are alleviated, the substantial pre-existing and increased mental health burden for DCWs will require investment to provide long-term support to the sector's workforce.
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Affiliation(s)
| | | | - Hywel Jones
- Division of Population Medicine, Cardiff University, Cardiff, UK
| | | | - Ashley Akbari
- Faculty of Medicine, Health & Life Science, Swansea University Medical School, Swansea, UK
| | | | - Kerenza Hood
- Centre for Trials Research, Cardiff University, Cardiff, UK
| | - Ann John
- Health Data Research UK | Administrative Data Research Wales, Swansea University, Swansea, UK
- DECIPHer-Centre for Development, Evaluation, Complexity and Implementation in Public Health Improvement, Cardiff University, Cardiff, UK
| | - Daniel Rh Thomas
- Communicable Disease Surveillance Centre, Public Health Wales, Cardiff, UK
- Cardiff Metropolitan University, Cardiff, UK
| | - Hayley Prout
- Centre for Trials Research, Cardiff University, Cardiff, UK
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Lyons J, Nafilyan V, Akbari A, Bedston S, Harrison E, Hayward A, Hippisley-Cox J, Kee F, Khunti K, Rahman S, Sheikh A, Torabi F, Lyons RA. An external validation of the QCOVID3 risk prediction algorithm for risk of hospitalisation and death from COVID-19: An observational, prospective cohort study of 1.66m vaccinated adults in Wales, UK. PLoS One 2023; 18:e0285979. [PMID: 37200350 PMCID: PMC10194890 DOI: 10.1371/journal.pone.0285979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 05/07/2023] [Indexed: 05/20/2023] Open
Abstract
INTRODUCTION At the start of the COVID-19 pandemic there was an urgent need to identify individuals at highest risk of severe outcomes, such as hospitalisation and death following infection. The QCOVID risk prediction algorithms emerged as key tools in facilitating this which were further developed during the second wave of the COVID-19 pandemic to identify groups of people at highest risk of severe COVID-19 related outcomes following one or two doses of vaccine. OBJECTIVES To externally validate the QCOVID3 algorithm based on primary and secondary care records for Wales, UK. METHODS We conducted an observational, prospective cohort based on electronic health care records for 1.66m vaccinated adults living in Wales on 8th December 2020, with follow-up until 15th June 2021. Follow-up started from day 14 post vaccination to allow the full effect of the vaccine. RESULTS The scores produced by the QCOVID3 risk algorithm showed high levels of discrimination for both COVID-19 related deaths and hospital admissions and good calibration (Harrell C statistic: ≥ 0.828). CONCLUSION This validation of the updated QCOVID3 risk algorithms in the adult vaccinated Welsh population has shown that the algorithms are valid for use in the Welsh population, and applicable on a population independent of the original study, which has not been previously reported. This study provides further evidence that the QCOVID algorithms can help inform public health risk management on the ongoing surveillance and intervention to manage COVID-19 related risks.
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Affiliation(s)
- Jane Lyons
- Faculty of Medicine, Health & Life Science, Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Vahé Nafilyan
- Office of National Statistics, Newport, United Kingdom
| | - Ashley Akbari
- Faculty of Medicine, Health & Life Science, Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Stuart Bedston
- Faculty of Medicine, Health & Life Science, Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Ewen Harrison
- Usher Institute, Centre for Medical Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew Hayward
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Julia Hippisley-Cox
- Nuffield Department, Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Frank Kee
- School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, United Kingdom
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, United Kingdom
| | - Shamim Rahman
- Department of Health and Social Care, Mental Health and Disabilities Analysis, London, United Kingdom
| | - Aziz Sheikh
- Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Fatemeh Torabi
- Faculty of Medicine, Health & Life Science, Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Ronan A. Lyons
- Faculty of Medicine, Health & Life Science, Population Data Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
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Strafford H, Lacey AS, Hollinghurst J, Akbari A, Watkins A, Paterson J, Jennings D, Lyons RA, Powell HR, Kerr MP, Chin RW, Pickrell WO. COVID-19 vaccination uptake in people with epilepsy in wales. Seizure 2023; 108:49-52. [PMID: 37080124 PMCID: PMC10076248 DOI: 10.1016/j.seizure.2023.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 04/03/2023] [Accepted: 04/05/2023] [Indexed: 04/09/2023] Open
Abstract
PURPOSE People with epilepsy (PWE) are at increased risk of severe COVID-19. Assessing COVID-19 vaccine uptake is therefore important. We compared COVID-19 vaccination uptake for PWE in Wales with a matched control cohort. METHODS We performed a retrospective, population, cohort study using linked, anonymised, Welsh electronic health records within the Secure Anonymised Information Linkage (SAIL) Databank (Welsh population=3.1 million).We identified PWE in Wales between 1st March 2020 and 31st December 2021 and created a control cohort using exact 5:1 matching (sex, age and socioeconomic status). We recorded 1st, 2nd and booster COVID-19 vaccinations. RESULTS There were 25,404 adults with epilepsy (127,020 controls). 23,454 (92.3%) had a first vaccination, 22,826 (89.9%) a second, and 17,797 (70.1%) a booster. Comparative figures for controls were: 112,334 (87.8%), 109,057 (85.2%) and 79,980 (62.4%).PWE had higher vaccination rates in all age, sex and socioeconomic subgroups apart from booster uptake in older subgroups. Vaccination rates were higher in older subgroups, women and less deprived areas for both cohorts. People with intellectual disability and epilepsy had higher vaccination rates when compared with controls with intellectual disability. CONCLUSIONS COVID-19 vaccination uptake for PWE in Wales was higher than that for a matched control group.
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Affiliation(s)
- H Strafford
- Neurology Research Group, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales SA2 8PP, UK.
| | - A S Lacey
- Neurology Research Group, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales SA2 8PP, UK
| | - J Hollinghurst
- Neurology Research Group, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales SA2 8PP, UK
| | - A Akbari
- Neurology Research Group, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales SA2 8PP, UK
| | - A Watkins
- Neurology Research Group, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales SA2 8PP, UK
| | - J Paterson
- Epilepsy Action, New Anstey House, Gate Way Drive, Yeadon, Leeds, England, UK
| | - D Jennings
- Epilepsy Action, New Anstey House, Gate Way Drive, Yeadon, Leeds, England, UK
| | - R A Lyons
- Neurology Research Group, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales SA2 8PP, UK
| | - H R Powell
- Neurology Research Group, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales SA2 8PP, UK; Morriston Hospital, Swansea Bay University Health Board, Swansea, Wales, UK
| | - M P Kerr
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, Wales, UK
| | - R W Chin
- Muir Maxwell Epilepsy Centre, Centre for Clinical Brain Sciences and Department of Child Life and Health, The University of Edinburgh, Scotland, UK; Royal Hospital for Children and Young People, Edinburgh, Scotland, UK
| | - W O Pickrell
- Neurology Research Group, Swansea University Medical School, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, Wales SA2 8PP, UK; Morriston Hospital, Swansea Bay University Health Board, Swansea, Wales, UK
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Harris DE, Torabi F, Mallory D, Akbari A, Thayer D, Wang T, Grundy S, Gravenor M, Alikhan R, Lister S, Halcox J. SAIL study of stroke, systemic embolism and bleeding outcomes with warfarin anticoagulation in non-valvular atrial fibrillation (S 4-BOW-AF). Eur Heart J Open 2023; 3:oead037. [PMID: 37143610 PMCID: PMC10153743 DOI: 10.1093/ehjopen/oead037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 03/29/2023] [Accepted: 04/12/2023] [Indexed: 05/06/2023]
Abstract
Aims In patients with non-valvular atrial fibrillation (NVAF) prescribed warfarin, the association between guideline defined international normalised ratio (INR) control and adverse outcomes in unknown. We aimed to (i) determine stroke and systemic embolism (SSE) and bleeding events in NVAF patients prescribed warfarin; and (ii) estimate the increased risk of these adverse events associated with poor INR control in this population. Methods and results Individual-level population-scale linked patient data were used to investigate the association between INR control and both SSE and bleeding events using (i) the National Institute for Health and Care Excellence (NICE) criteria of poor INR control [time in therapeutic range (TTR) <65%, two INRs <1.5 or two INRs >5 in a 6-month period or any INR >8]. A total of 35 891 patients were included for SSE and 35 035 for bleeding outcome analyses. Mean CHA2DS2-VASc score was 3.5 (SD = 1.7), and the mean follow up was 4.3 years for both analyses. Mean TTR was 71.9%, with 34% of time spent in poor INR control according to NICE criteria.SSE and bleeding event rates (per 100 patient years) were 1.01 (95%CI 0.95-1.08) and 3.4 (95%CI 3.3-3.5), respectively, during adequate INR control, rising to 1.82 (95%CI 1.70-1.94) and 4.8 (95% CI 4.6-5.0) during poor INR control.Poor INR control was independently associated with increased risk of both SSE [HR = 1.69 (95%CI = 1.54-1.86), P < 0.001] and bleeding [HR = 1.40 (95%CI 1.33-1.48), P < 0.001] in Cox-multivariable models. Conclusion Guideline-defined poor INR control is associated with significantly higher SSE and bleeding event rates, independent of recognised risk factors for stroke or bleeding.
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Affiliation(s)
| | | | - Daniel Mallory
- Population Data Science, Swansea University, Singleton Park, Swansea, SA28PP, UK
| | - Ashley Akbari
- Population Data Science, Swansea University, Singleton Park, Swansea, SA28PP, UK
| | - Daniel Thayer
- Population Data Science, Swansea University, Singleton Park, Swansea, SA28PP, UK
| | - Ting Wang
- Population Data Science, Swansea University, Singleton Park, Swansea, SA28PP, UK
| | - Sarah Grundy
- Medical Department, Bristol-Myers Squibb ltd, ARC Uxbridge, Sanderson Road, Denham, UB8 1DH, UK
| | - Mike Gravenor
- Population Data Science, Swansea University, Singleton Park, Swansea, SA28PP, UK
| | - Raza Alikhan
- Thrombosis Centre, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK
| | - Steven Lister
- Department of Health Economics, Bristol-Myers Squibb ltd, ARC Uxbridge, Sanderson Road, Denham, UB8 1DH, UK
| | - Julian Halcox
- Population Data Science, Swansea University, Singleton Park, Swansea, SA28PP, UK
- Cardiology Department, Swansea Bay University Health Board, Sketty Lane, Swansea, SA28QA, UK
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41
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Snooks H, Watkins A, Lyons J, Akbari A, Bailey R, Bethell L, Carson-Stevens A, Edwards A, Emery H, Evans BA, Jolles S, John A, Kingston M, Porter A, Sewell B, Williams V, Lyons RA. Did the UK's public health shielding policy protect the clinically extremely vulnerable during the COVID-19 pandemic in Wales? Results of EVITE Immunity, a linked data retrospective study. Public Health 2023; 218:12-20. [PMID: 36933354 PMCID: PMC9928733 DOI: 10.1016/j.puhe.2023.02.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 02/03/2023] [Accepted: 02/07/2023] [Indexed: 02/17/2023]
Abstract
INTRODUCTION The UK shielding policy intended to protect people at the highest risk of harm from COVID-19 infection. We aimed to describe intervention effects in Wales at 1 year. METHODS Retrospective comparison of linked demographic and clinical data for cohorts comprising people identified for shielding from 23 March to 21 May 2020; and the rest of the population. Health records were extracted with event dates between 23 March 2020 and 22 March 2021 for the comparator cohort and from the date of inclusion until 1 year later for the shielded cohort. RESULTS The shielded cohort included 117,415 people, with 3,086,385 in the comparator cohort. The largest clinical categories in the shielded cohort were severe respiratory condition (35.5%), immunosuppressive therapy (25.9%) and cancer (18.6%). People in the shielded cohort were more likely to be female, aged ≥50 years, living in relatively deprived areas, care home residents and frail. The proportion of people tested for COVID-19 was higher in the shielded cohort (odds ratio [OR] 1.616; 95% confidence interval [CI] 1.597-1.637), with lower positivity rate incident rate ratios 0.716 (95% CI 0.697-0.736). The known infection rate was higher in the shielded cohort (5.9% vs 5.7%). People in the shielded cohort were more likely to die (OR 3.683; 95% CI: 3.583-3.786), have a critical care admission (OR 3.339; 95% CI: 3.111-3.583), hospital emergency admission (OR 2.883; 95% CI: 2.837-2.930), emergency department attendance (OR 1.893; 95% CI: 1.867-1.919) and common mental disorder (OR 1.762; 95% CI: 1.735-1.789). CONCLUSION Deaths and healthcare utilisation were higher amongst shielded people than the general population, as would be expected in the sicker population. Differences in testing rates, deprivation and pre-existing health are potential confounders; however, lack of clear impact on infection rates raises questions about the success of shielding and indicates that further research is required to fully evaluate this national policy intervention.
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Affiliation(s)
- H Snooks
- Swansea University, Medical School, ILS 2, Singleton Park, Swansea, SA2 8PP, UK.
| | - A Watkins
- Swansea University, Medical School, ILS 2, Singleton Park, Swansea, SA2 8PP, UK.
| | - J Lyons
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, Swansea, SA2 8PP, UK.
| | - A Akbari
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, Swansea, SA2 8PP, UK.
| | - R Bailey
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, Swansea, SA2 8PP, UK.
| | - L Bethell
- Swansea University, Medical School, ILS 2, Singleton Park, Swansea, SA2 8PP, UK.
| | - A Carson-Stevens
- Cardiff University, Division of Population Medicine, Neuadd Meirionnydd, University Hospital of Wales, Heath Park, Cardiff, CF14 4YS, UK.
| | - A Edwards
- Cardiff University, Division of Population Medicine, Neuadd Meirionnydd, University Hospital of Wales, Heath Park, Cardiff, CF14 4YS, UK.
| | - H Emery
- Swansea University, Medical School, ILS 2, Singleton Park, Swansea, SA2 8PP, UK.
| | - B A Evans
- Swansea University, Medical School, ILS 2, Singleton Park, Swansea, SA2 8PP, UK.
| | - S Jolles
- Immunodeficiency Centre for Wales, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK.
| | - A John
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, Swansea, SA2 8PP, UK.
| | - M Kingston
- Swansea University, Medical School, ILS 2, Singleton Park, Swansea, SA2 8PP, UK.
| | - A Porter
- Swansea University, Medical School, ILS 2, Singleton Park, Swansea, SA2 8PP, UK.
| | - B Sewell
- Swansea University, School of Health and Social Care, Vivian Tower, Singleton Park, Swansea, SA2 8PP, UK.
| | - V Williams
- Swansea University, Medical School, ILS 2, Singleton Park, Swansea, SA2 8PP, UK.
| | - R A Lyons
- Population Data Science, Swansea University, Medical School, Data Science Building, Singleton Park, Swansea, SA2 8PP, UK.
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42
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Ellins EA, Wareham K, Harris DE, Hanney M, Akbari A, Gilmore M, Barry JP, Phillips CJ, Gravenor MB, Halcox JP. Incident atrial fibrillation and adverse clinical outcomes during extended follow-up of participants recruited to the remote heart rhythm sampling using the AliveCor heart monitor to screen for atrial fibrillation: the REHEARSE-AF study. Eur Heart J Open 2023; 3:oead047. [PMID: 37205320 PMCID: PMC10187779 DOI: 10.1093/ehjopen/oead047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 04/25/2023] [Accepted: 05/02/2023] [Indexed: 05/21/2023]
Abstract
Aims Atrial fibrillation (AF) is an important risk factor for stroke, which is commonly asymptomatic, particularly in older patients, and often undetected until cardiovascular events occur. Development of novel technology has helped to improve detection of AF. However, the longer-term benefit of systematic electrocardiogram (ECG) screening on cardiovascular outcomes is unclear. Methods and results In the original REHEARSE-AF study, patients were randomized to twice-weekly portable electrocardiogram (iECG) assessment or routine care. After discontinuing the trial portable iECG assessment, electronic health record data sources provided longer-term follow-up analysis. Cox regression was used to provide unadjusted and adjusted hazard ratios (HR) [95% confidence intervals (CI)] for clinical diagnosis, events, and anticoagulant prescriptions during the follow-up period. Over the median 4.2-year follow-up, although a greater number of patients were diagnosed with AF in the original iECG group (43 vs. 31), this was not significant (HR 1.37, 95% CI 0.86-2.19). No differences were seen in the number of strokes/systemic embolisms or deaths between the two groups (HR 0.92, 95% CI 0.54-1.54; HR 1.07, 95% CI 0.66-1.73). Findings were similar when restricted to those with CHADS-VASc ≥ 4. Conclusion A 1-year period of home-based, twice-weekly screening for AF increased diagnoses of AF for the screening period but did not lead to increased diagnoses of AF or a reduction in cardiovascular-related events or all-cause death over a median of 4.2 years, even in those at highest risk of AF. These results suggest that benefits of regular ECG screening over a 1-year period are not maintained after cessation of the screening protocol.
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Affiliation(s)
| | - Kathie Wareham
- Faculty of Medicine, Health & Life Science, Swansea University Medical School, Singleton, Swansea SA2 8PP, UK
| | - Daniel E Harris
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
- Titech Institute, Hywel Dda University Health Board, Llanelli, UK
| | - Matthew Hanney
- Faculty of Medicine, Health & Life Science, Swansea University Medical School, Singleton, Swansea SA2 8PP, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Mark Gilmore
- Cardiology, Princess of Wales Hospital, Bridgend, UK
| | - James P Barry
- Regional Cardiac Centre, Morriston Hospital, Swansea, UK
| | - Ceri J Phillips
- Swansea University College of Health and Human Sciences, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - Michael B Gravenor
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
| | - Julian P Halcox
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Singleton Park, Swansea, SA2 8PP, UK
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Qi C, Osborne T, Bailey R, Cooper A, Hollinghurst JP, Akbari A, Crowder R, Peters H, Law RJ, Lewis R, Smith D, Edwards A, Lyons RA. Impact of COVID-19 pandemic on incidence of long-term conditions in Wales: a population data linkage study using primary and secondary care health records. Br J Gen Pract 2023; 73:e332-e339. [PMID: 37105743 PMCID: PMC9997656 DOI: 10.3399/bjgp.2022.0353] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 11/25/2022] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic has directly and indirectly had an impact on health service provision owing to surges and sustained pressures on the system. The effects of these pressures on the management of long-term or chronic conditions are not fully understood. AIM To explore the effects of COVID-19 on the recorded incidence of 17 long-term conditions. DESIGN AND SETTING This was an observational retrospective population data linkage study on the population of Wales using primary and secondary care data within the Secure Anonymised Information Linkage (SAIL) Databank. METHOD Monthly rates of new diagnosis between 2000 and 2021 are presented for each long-term condition. Incidence rates post-2020 were compared with expected rates predicted using time series modelling of pre-2020 trends. The proportion of annual incidence is presented by sociodemographic factors: age, sex, social deprivation, ethnicity, frailty, and learning disability. RESULTS A total of 5 476 012 diagnoses from 2 257 992 individuals are included. Incidence rates from 2020 to 2021 were lower than mean expected rates across all conditions. The largest relative deficit in incidence was in chronic obstructive pulmonary disease corresponding to 343 (95% confidence interval = 230 to 456) undiagnosed patients per 100 000 population, followed by depression, type 2 diabetes, hypertension, anxiety disorders, and asthma. A GP practice of 10 000 patients might have over 400 undiagnosed long-term conditions. No notable differences between sociodemographic profiles of post- and pre-2020 incidences were observed. CONCLUSION There is a potential backlog of undiagnosed patients with multiple long-term conditions. Resources are required to tackle anticipated workload as part of COVID-19 recovery, particularly in primary care.
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Affiliation(s)
- Cathy Qi
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea
| | - Tim Osborne
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea
| | - Rowena Bailey
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea
| | - Alison Cooper
- Wales COVID-19 Evidence Centre, Division of Population Medicine, Cardiff University, Cardiff
| | - Joe P Hollinghurst
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea
| | - Ruth Crowder
- Directorate of Primary Care and Mental Health, Health and Social Services Group, Welsh Government, Cardiff
| | - Holly Peters
- Centre for Medical Education, Cardiff University, Cardiff
| | - Rebecca-Jane Law
- Technical Advisory Cell, Health and Social Services Group, Welsh Government, Cardiff
| | - Ruth Lewis
- North Wales Centre for Primary Care Research, PRIME Centre Wales, Bangor University, Bangor
| | - Deb Smith
- Wales COVID-19 Evidence Centre, Division of Population Medicine, Cardiff University, Cardiff
| | - Adrian Edwards
- Wales COVID-19 Evidence Centre, Division of Population Medicine, Cardiff University, Cardiff
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea
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Harris C, Cottrell S, Perry M, Meaden R, Davey R, Elliott M, Cushen R, Jones G, Youlden H, Meredith N, Jones R, Thomas S, Akbari A, Lyons RA, Johnson C. A pilot intervention to improve uptake and equality of childhood influenza vaccination in an area of Wales, through the introduction of a mixed delivery model including nursery school immunisation sessions. Vaccine 2023; 41:2990-2995. [PMID: 37037705 DOI: 10.1016/j.vaccine.2023.03.075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 04/12/2023]
Abstract
The schools-based influenza vaccination programme has seen consistently high uptake in Wales, however coverage in pre-school two and three-year olds is lower. One health board area (Cwm Taf University Health Board (UHB)) developed an intervention to offer live attenuated influenza vaccine (LAIV) for three-year olds attending nursery schools alongside the existing general practice (GP) programme. During the pilot, sessions were delivered by health visitors, working with school nurses. The mixed delivery model led to vaccination data being recorded in two separate data systems. To evaluate the impact of the pilot on overall vaccine uptake, data linkage was carried out within the Secure Anonymised Information Linkage (SAIL) Databank. Overall influenza vaccine uptake was calculated for each health board in Wales for two and three-year olds for the 2015-16, 2016-17, and 2017-18 influenza programmes. Uptake in two-year olds in Cwm Taf UHB and also uptake in three-year olds in other health boards in Wales were the comparison groups. Uptake of influenza vaccine in the 2015-16 (pre-intervention) period was 41.0% for three-year olds in Cwm Taf UHB. Following the intervention, coverage increased to 70.7% and 71.5% for 2016-17 and 2017-18 respectively. The same increases in uptake were not seen in two-year olds in Cwm Taf UHB or in three-year olds in non-intervention health boards. In Cwm Taf UHB resident three-year olds in 2015-16 there was an inequality gap in the uptake of 17.4 percentage points between the most and least deprived areas. Uptake increased across all deprivation quintiles in 2016-17 and 2017-18; and the inequality gap decreased to 10.3 and 13.4 percentage points respectively. Influenza vaccination uptake and equality of uptake in three-year olds can be improved by adopting a mixed delivery model across nursery school based immunisation sessions with the additional option of influenza vaccination at GPs.
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Affiliation(s)
- Caroline Harris
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Simon Cottrell
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Malorie Perry
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK.
| | - Rhian Meaden
- Cwm Taf Morgannwg University Health Board, Keir Hardie University Health Park, Aberdare Road, Merthyr Tydfil CF48 1BZ, UK.
| | - Rhianydd Davey
- Cwm Taf Morgannwg University Health Board, Keir Hardie University Health Park, Aberdare Road, Merthyr Tydfil CF48 1BZ, UK.
| | - Megan Elliott
- Cwm Taf Morgannwg Public Health Team, Glanrhyd Hospital, Tondu Road, Bridgend CF31 4LN, UK.
| | - Rebecca Cushen
- Cwm Taf Morgannwg Public Health Team, Glanrhyd Hospital, Tondu Road, Bridgend CF31 4LN, UK.
| | - Gareth Jones
- Cwm Taf Morgannwg University Health Board, Keir Hardie University Health Park, Aberdare Road, Merthyr Tydfil CF48 1BZ, UK.
| | - Hawys Youlden
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Nicola Meredith
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Rosemary Jones
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
| | - Sara Thomas
- Cwm Taf Morgannwg University Health Board, Keir Hardie University Health Park, Aberdare Road, Merthyr Tydfil CF48 1BZ, UK.
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK.
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales, UK.
| | - Christopher Johnson
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, Wales, UK.
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Jones M, Hill T, Coupland C, Kendrick D, Akbari A, Rodgers S, Watson MC, Tyrrell E, Merrill S, Martin A, Orton E. Cost-effectiveness of England's national 'Safe At Home' scheme for reducing hospital admissions for unintentional injury in children aged under 5. Inj Prev 2023; 29:158-165. [PMID: 36600567 DOI: 10.1136/ip-2022-044698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 11/06/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Injuries in children aged under 5 years most commonly occur in the home and disproportionately affect those living in the most disadvantaged communities. The 'Safe at Home' (SAH) national home safety equipment scheme, which ran in England between 2009 and 2011, has been shown to reduce injury-related hospital admissions, but there is little evidence of cost-effectiveness. MATERIALS AND METHODS Cost-effectiveness analysis from a health and local government perspective. Measures were the incremental cost-effectiveness ratio per hospital admission averted (ICER) and cost-offset ratio (COR), comparing SAH expenditure to savings in admission expenditure. The study period was split into three periods: T1 (years 0-2, implementation); T2 (years 3-4) and T3 (years 5-6). Analyses were conducted for T2 versus T1 and T3 versus T1. RESULTS Total cost of SAH was £9 518 066. 202 223 hospital admissions in the children occurred during T1-3, costing £3 320 000. Comparing T3 to T1 SAH reduced admission expenditure by £924 per month per local authority and monthly admission rates by 0.5 per local authority per month compared with control areas. ICER per admission averted was £4209 for T3 versus T1, with a COR of £0.29, suggesting that 29p was returned in savings on admission expenditure for every pound spent on SAH. CONCLUSION SAH was effective at reducing hospital admissions due to injury and did result in some cost recovery when taking into admissions only. Further analysis of its cost-effectiveness, including emergency healthcare, primary care attendances and wider societal costs, is likely to improve the return on investment further.
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Affiliation(s)
- Matthew Jones
- Unit of Lifespan and Population Health, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, UK
| | - Trevor Hill
- Unit of Lifespan and Population Health, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, UK
| | - Carol Coupland
- Unit of Lifespan and Population Health, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, UK
| | - Denise Kendrick
- Unit of Lifespan and Population Health, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, UK
| | - Ashley Akbari
- Faculty of Medicine, Health, & Life Science, University of Wales Swansea, Swansea, UK
| | - Sarah Rodgers
- Department of Public Health, Policy & Systems, University of Liverpool, Liverpool, UK
| | | | - Edward Tyrrell
- Unit of Lifespan and Population Health, University of Nottingham, Nottingham, UK
| | - Sheila Merrill
- Royal Society for the Prevention of Accidents (RoSPA), Edgbaston, UK
| | - Ashley Martin
- Royal Society for the Prevention of Accidents (RoSPA), Edgbaston, UK
| | - Elizabeth Orton
- Unit of Lifespan and Population Health, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, UK
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Bright D, Hillier S, Song J, Huws DW, Greene G, Hodgson K, Akbari A, Griffiths R, Davies AR, Gjini A. Inequalities in colorectal cancer screening uptake in Wales: an examination of the impact of the temporary suspension of the screening programme during the COVID-19 pandemic. BMC Public Health 2023; 23:546. [PMID: 36949447 PMCID: PMC10031708 DOI: 10.1186/s12889-023-15345-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 02/28/2023] [Indexed: 03/24/2023] Open
Abstract
BACKGROUND Response to the early stages of the COVID-19 pandemic resulted in the temporary disruption of cancer screening in the UK, and strong public messaging to stay safe and to protect NHS capacity. Following reintroduction in services, we explored the impact on inequalities in uptake of the Bowel Screening Wales (BSW) programme to identify groups who may benefit from tailored interventions. METHODS Records within the BSW were linked to electronic health records (EHR) and administrative data within the Secured Anonymised Information Linkage (SAIL) Databank. Ethnic group was obtained from a linked data method available within SAIL. We examined uptake for the first 3 months of invitations (August to October) following the reintroduction of BSW programme in 2020, compared to the same period in the preceding 3 years. Uptake was measured across a 6 month follow-up period. Logistic models were conducted to analyse variations in uptake by sex, age group, income deprivation quintile, urban/rural location, ethnic group, and clinically extremely vulnerable (CEV) status in each period; and to compare uptake within sociodemographic groups between different periods. RESULTS Uptake during August to October 2020 (period 2020/21; 60.4%) declined compared to the same period in 2019/20 (62.7%) but remained above the 60% Welsh standard. Variation by sex, age, income deprivation, and ethnic groups was observed in all periods studied. Compared to the pre-pandemic period in 2019/20, uptake declined for most demographic groups, except for older individuals (70-74 years) and those in the most income deprived group. Uptake continues to be lower in males, younger individuals, people living in the most income deprived areas and those of Asian and unknown ethnic backgrounds. CONCLUSION Our findings are encouraging with overall uptake achieving the 60% Welsh standard during the first three months after the programme restarted in 2020 despite the disruption. Inequalities did not worsen after the programme resumed activities but variations in CRC screening in Wales associated with sex, age, deprivation and ethnic group remain. This needs to be considered in targeting strategies to improve uptake and informed choice in CRC screening to avoid exacerbating disparities in CRC outcomes as screening services recover from the pandemic.
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Affiliation(s)
- Diana Bright
- Research and Evaluation Division, Knowledge and Research Directorate, Public Health Data, Public Health Wales, Floor 5, Number 2 Capital Quarter, Tyndall Street, Cardiff, CF10 4BZ, UK.
| | - Sharon Hillier
- Health Protection and Screening Services Directorate. Public Health Wales, Cardiff, Wales
| | - Jiao Song
- Communicable Disease Surveillance Centre. Public Health Wales, Cardiff, Wales
| | - Dyfed W Huws
- Research and Evaluation Division, Knowledge and Research Directorate, Public Health Data, Public Health Wales, Floor 5, Number 2 Capital Quarter, Tyndall Street, Cardiff, CF10 4BZ, UK
- Population Data Science, Faculty of Medicine, Health & Life Science, Swansea University Medical School, Swansea University, Swansea, Wales
| | - Giles Greene
- Research and Evaluation Division, Knowledge and Research Directorate, Public Health Data, Public Health Wales, Floor 5, Number 2 Capital Quarter, Tyndall Street, Cardiff, CF10 4BZ, UK
| | - Karen Hodgson
- Research and Evaluation Division, Knowledge and Research Directorate, Public Health Data, Public Health Wales, Floor 5, Number 2 Capital Quarter, Tyndall Street, Cardiff, CF10 4BZ, UK
| | - Ashley Akbari
- Population Data Science, Faculty of Medicine, Health & Life Science, Swansea University Medical School, Swansea University, Swansea, Wales
| | - Rowena Griffiths
- Population Data Science, Faculty of Medicine, Health & Life Science, Swansea University Medical School, Swansea University, Swansea, Wales
| | - Alisha R Davies
- Research and Evaluation Division, Knowledge and Research Directorate, Public Health Data, Public Health Wales, Floor 5, Number 2 Capital Quarter, Tyndall Street, Cardiff, CF10 4BZ, UK
| | - Ardiana Gjini
- Health Protection and Screening Services Directorate. Public Health Wales, Cardiff, Wales
- Cardiff University, Cardiff, UK
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47
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Lench A, Perry M, Johnson RD, Fry R, Richardson G, Lyons RA, Akbari A, Edwards A, Collins B, Joseph-Williams N, Cooper A, Cottrell S. Household Composition and Inequalities in COVID-19 Vaccination in Wales, UK. Vaccines (Basel) 2023; 11:604. [PMID: 36992188 PMCID: PMC10055803 DOI: 10.3390/vaccines11030604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 02/22/2023] [Accepted: 03/05/2023] [Indexed: 03/09/2023] Open
Abstract
The uptake of COVID-19 vaccination in Wales is high at a population level but many inequalities exist. Household composition may be an important factor in COVID-19 vaccination uptake due to the practical, social, and psychological implications associated with different living arrangements. In this study, the role of household composition in the uptake of COVID-19 vaccination in Wales was examined with the aim of identifying areas for intervention to address inequalities. Records within the Wales Immunisation System (WIS) COVID-19 vaccination register were linked to the Welsh Demographic Service Dataset (WDSD; a population register for Wales) held within the Secure Anonymised Information Linkage (SAIL) databank. Eight household types were defined based on household size, the presence or absence of children, and the presence of single or multiple generations. Uptake of the second dose of any COVID-19 vaccine was analysed using logistic regression. Gender, age group, health board, rural/urban residential classification, ethnic group, and deprivation quintile were included as covariates for multivariable regression. Compared to two-adult households, all other household types were associated with lower uptake. The most significantly reduced uptake was observed for large, multigenerational, adult group households (aOR 0.45, 95%CI 0.43-0.46). Comparing multivariable regression with and without incorporation of household composition as a variable produced significant differences in odds of vaccination for health board, age group, and ethnic group categories. These results indicate that household composition is an important factor for the uptake of COVID-19 vaccination and consideration of differences in household composition is necessary to mitigate vaccination inequalities.
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Affiliation(s)
- Alex Lench
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, UK
- Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea SA2 8PP, UK
| | - Malorie Perry
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, UK
- Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea SA2 8PP, UK
| | - Rhodri D. Johnson
- Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea SA2 8PP, UK
| | - Richard Fry
- Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea SA2 8PP, UK
| | - Gill Richardson
- Policy, Research and International Development, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, UK
| | - Ronan A. Lyons
- Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea SA2 8PP, UK
| | - Ashley Akbari
- Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea SA2 8PP, UK
| | - Adrian Edwards
- Wales COVID-19 Evidence Centre, PRIME Centre Wales, Division of Population Medicine, School of Medicine, Cardiff University, 8th floor, Neuadd Meirionnydd, Heath Park, Cardiff CF14 4XN, UK
| | - Brendan Collins
- Health and Social Services Group, Finance Directorate, Welsh Government, Cardiff CF10 3NQ, UK
| | - Natalie Joseph-Williams
- Wales COVID-19 Evidence Centre, PRIME Centre Wales, Division of Population Medicine, School of Medicine, Cardiff University, 8th floor, Neuadd Meirionnydd, Heath Park, Cardiff CF14 4XN, UK
| | - Alison Cooper
- Wales COVID-19 Evidence Centre, PRIME Centre Wales, Division of Population Medicine, School of Medicine, Cardiff University, 8th floor, Neuadd Meirionnydd, Heath Park, Cardiff CF14 4XN, UK
| | - Simon Cottrell
- Vaccine Preventable Disease Programme and Communicable Disease Surveillance Centre, Public Health Wales, 2 Capital Quarter, Tyndall Street, Cardiff CF10 4BZ, UK
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48
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Ibrahim N, Jovic M, Ali S, Williams N, Gibson JAG, Griffiths R, Dobbs TD, Akbari A, Lyons RA, Hutchings HA, Whitaker IS. The epidemiology, healthcare and societal burden of basal cell carcinoma in Wales 2000-2018: a retrospective nationwide analysis. Br J Dermatol 2023; 188:380-389. [PMID: 36715329 DOI: 10.1093/bjd/ljac090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/30/2022] [Accepted: 11/05/2022] [Indexed: 01/31/2023]
Abstract
BACKGROUND Basal cell carcinoma (BCC) represents the most commonly occurring cancer worldwide within the white population. Reports predict 298 308 cases of BCC in the UK by 2025, at a cost of £265-366 million to the National Health Service (NHS). Despite the morbidity, societal and healthcare pressures brought about by BCC, routinely collected healthcare data and global registration remain limited. OBJECTIVES To calculate the incidence of BCC in Wales between 2000 and 2018 and to establish the related healthcare utilization and estimated cost of care. METHODS The Secure Anonymised Information Linkage (SAIL) databank is one of the largest and most robust health and social care data repositories in the UK. Cancer registry data were linked to routinely collected healthcare databases between 2000 and 2018. Pathological data from Swansea Bay University Health Board (SBUHB) were used for internal validation. RESULTS A total of 61 404 histologically proven BCCs were identified within the SAIL Databank during the study period. The European age-standardized incidence for BCC in 2018 was 224.6 per 100 000 person-years. Based on validated regional data, a 45% greater incidence was noted within SBUHB pathology vs. matched regions within SAIL between 2016 and 2018. A negative association between deprivation and incidence was noted with a higher incidence in the least socially deprived and rural dwellers. Approximately 2% travelled 25-50 miles for dermatological services compared with 37% for plastic surgery. Estimated NHS costs of surgically managed lesions for 2002-2019 equated to £119.2-164.4 million. CONCLUSIONS Robust epidemiological data that are internationally comparable and representative are scarce for nonmelanoma skin cancer. The rising global incidence coupled with struggling healthcare systems in the post-COVID-19 recovery period serve to intensify the societal and healthcare impact. This study is the first to demonstrate the incidence of BCC in Wales and is one of a small number in the UK using internally validated large cohort datasets. Furthermore, our findings demonstrate one of the highest published incidences within the UK and Europe.
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Affiliation(s)
- Nader Ibrahim
- Reconstructive Surgery & Regenerative Medicine Research Centre (ReconRegen) Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,The Welsh Centre for Burns & Plastic Surgery, Morriston Hospital, Swansea, UK
| | - Matthew Jovic
- Reconstructive Surgery & Regenerative Medicine Research Centre (ReconRegen) Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,Population Data Science, Health Data Research UK and
| | - Stephen Ali
- Reconstructive Surgery & Regenerative Medicine Research Centre (ReconRegen) Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,The Welsh Centre for Burns & Plastic Surgery, Morriston Hospital, Swansea, UK
| | - Namor Williams
- Department of Pathology, Singleton Hospital, Swansea Bay University Health Board, Swansea, UK
| | - John A G Gibson
- Reconstructive Surgery & Regenerative Medicine Research Centre (ReconRegen) Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,The Welsh Centre for Burns & Plastic Surgery, Morriston Hospital, Swansea, UK
| | - Rowena Griffiths
- Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,Population Data Science, Health Data Research UK and
| | - Thomas D Dobbs
- Reconstructive Surgery & Regenerative Medicine Research Centre (ReconRegen) Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,The Welsh Centre for Burns & Plastic Surgery, Morriston Hospital, Swansea, UK
| | - Ashley Akbari
- Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,Population Data Science, Health Data Research UK and.,Administrative Data Research Wales, Swansea University, Swansea, UK
| | - Ronan A Lyons
- Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,Population Data Science, Health Data Research UK and.,Administrative Data Research Wales, Swansea University, Swansea, UK
| | - Hayley A Hutchings
- Swansea University Medical School, Institute of Life Sciences, Swansea, UK
| | - Iain S Whitaker
- Reconstructive Surgery & Regenerative Medicine Research Centre (ReconRegen) Swansea University Medical School, Institute of Life Sciences, Swansea, UK.,The Welsh Centre for Burns & Plastic Surgery, Morriston Hospital, Swansea, UK
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49
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Bedston S, Lowthian E, Jarvis CI, Akbari A, Beggs J, Bradley D, de Lusignan S, Griffiths R, Herbert L, Hobbs R, Kerr S, Lyons J, Midgley W, Owen RK, Quint JK, Tsang R, Torabi F, Sheikh A, Lyons RA. COVID-19 booster vaccination uptake and infection breakthrough amongst health care workers in Wales: A national prospective cohort study. Vaccine 2023; 41:1378-1389. [PMID: 36669966 PMCID: PMC9837216 DOI: 10.1016/j.vaccine.2023.01.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/10/2023] [Accepted: 01/11/2023] [Indexed: 01/15/2023]
Abstract
BACKGROUND From September 2021, Health Care Workers (HCWs) in Wales began receiving a COVID-19 booster vaccination. This is the first dose beyond the primary vaccination schedule. Given the emergence of new variants, vaccine waning vaccine, and increasing vaccination hesitancy, there is a need to understand booster vaccine uptake and subsequent breakthrough in this high-risk population. METHODS We conducted a prospective, national-scale, observational cohort study of HCWs in Wales using anonymised, linked data from the SAIL Databank. We analysed uptake of COVID-19 booster vaccinations from September 2021 to February 2022, with comparisons against uptake of the initial primary vaccination schedule. We also analysed booster breakthrough, in the form of PCR-confirmed SARS-Cov-2 infection, comparing to the second primary dose. Cox proportional hazard models were used to estimate associations for vaccination uptake and breakthrough regarding staff roles, socio-demographics, household composition, and other factors. RESULTS We derived a cohort of 73,030 HCWs living in Wales (78% female, 60% 18-49 years old). Uptake was quickest amongst HCWs aged 60 + years old (aHR 2.54, 95%CI 2.45-2.63), compared with those aged 18-29. Asian HCWs had quicker uptake (aHR 1.18, 95%CI 1.14-1.22), whilst Black HCWs had slower uptake (aHR 0.67, 95%CI 0.61-0.74), compared to white HCWs. HCWs residing in the least deprived areas were slightly quicker to have received a booster dose (aHR 1.12, 95%CI 1.09-1.16), compared with those in the most deprived areas. Strongest associations with breakthrough infections were found for those living with children (aHR 1.52, 95%CI 1.41-1.63), compared to two-adult only households. HCWs aged 60 + years old were less likely to get breakthrough infections, compared to those aged 18-29 (aHR 0.42, 95%CI 0.38-0.47). CONCLUSION Vaccination uptake was consistently lower among black HCWs, as well as those from deprived areas. Whilst breakthrough infections were highest in households with children.
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Affiliation(s)
- Stuart Bedston
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
| | - Emily Lowthian
- Department of Education and Childhood Studies, School of Social Sciences, Swansea University, UK.
| | | | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
| | | | - Declan Bradley
- Centre for Public Health, Queen's University Belfast, Belfast, UK. And Public Health Agency, Belfast, UK.
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
| | - Rowena Griffiths
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
| | - Laura Herbert
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
| | - Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
| | - Steven Kerr
- Usher Institute, The University of Edinburgh, Edinburgh, UK.
| | - Jane Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
| | - William Midgley
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
| | - Rhiannon K Owen
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
| | - Jennifer K Quint
- National Heart & Lung Institute, Faculty of Medicine, Imperial College London, UK.
| | - Ruby Tsang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
| | - Fatemeh Torabi
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
| | - Aziz Sheikh
- Usher Institute and HDR UK BREATHE Hub, University of Edinburgh, UK.
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, UK.
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50
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Kerr S, Bedston S, Bradley DT, Joy M, Lowthian E, Mulholland RM, Akbari A, Hobbs FDR, Katikireddi SV, de Lusignan S, Rudan I, Torabi F, Tsang RSM, Lyons RA, Robertson C, Sheikh A. Waning of first- and second-dose ChAdOx1 and BNT162b2 COVID-19 vaccinations: a pooled target trial study of 12.9 million individuals in England, Northern Ireland, Scotland and Wales. Int J Epidemiol 2023; 52:22-31. [PMID: 36272418 PMCID: PMC9620314 DOI: 10.1093/ije/dyac199] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 09/30/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Several SARS-CoV-2 vaccines have been shown to provide protection against COVID-19 hospitalization and death. However, some evidence suggests that notable waning in effectiveness against these outcomes occurs within months of vaccination. We undertook a pooled analysis across the four nations of the UK to investigate waning in vaccine effectiveness (VE) and relative vaccine effectiveness (rVE) against severe COVID-19 outcomes. METHODS We carried out a target trial design for first/second doses of ChAdOx1(Oxford-AstraZeneca) and BNT162b2 (Pfizer-BioNTech) with a composite outcome of COVID-19 hospitalization or death over the period 8 December 2020 to 30 June 2021. Exposure groups were matched by age, local authority area and propensity for vaccination. We pooled event counts across the four UK nations. RESULTS For Doses 1 and 2 of ChAdOx1 and Dose 1 of BNT162b2, VE/rVE reached zero by approximately Days 60-80 and then went negative. By Day 70, VE/rVE was -25% (95% CI: -80 to 14) and 10% (95% CI: -32 to 39) for Doses 1 and 2 of ChAdOx1, respectively, and 42% (95% CI: 9 to 64) and 53% (95% CI: 26 to 70) for Doses 1 and 2 of BNT162b2, respectively. rVE for Dose 2 of BNT162b2 remained above zero throughout and reached 46% (95% CI: 13 to 67) after 98 days of follow-up. CONCLUSIONS We found strong evidence of waning in VE/rVE for Doses 1 and 2 of ChAdOx1, as well as Dose 1 of BNT162b2. This evidence may be used to inform policies on timings of additional doses of vaccine.
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Affiliation(s)
- Steven Kerr
- Centre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, UK
| | - Stuart Bedston
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Declan T Bradley
- School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, UK
- Public Health Agency, Belfast, UK
| | - Mark Joy
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Emily Lowthian
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
- Department of Education and Childhood Studies, Swansea University, Swansea, UK
| | - Rachel M Mulholland
- Centre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - F D Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Igor Rudan
- Centre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, UK
| | - Fatemeh Torabi
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Ruby S M Tsang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Chris Robertson
- Public Health Scotland, Glasgow, UK
- Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK
| | - Aziz Sheikh
- Centre for Medical Informatics, Usher Institute, The University of Edinburgh, Edinburgh, UK
- BREATHE—The Health Data Research Hub for Respiratory Health, The University of Edinburgh, Edinburgh, UK
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