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      Evaluating access to health and care services during lockdown by the COVID-19 survey in five UK national longitudinal studies


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          Access to health services and adequate care is influenced by sex, ethnicity, socioeconomic position (SEP) and the burden of comorbidities. Our study aimed to assess whether the COVID-19 pandemic further deepened these already existing health inequalities.


          Cross-sectional study.


          Data were collected from five longitudinal age-homogenous British cohorts (born in 2000-2002, 1989-1990, 1970, 1958 and 1946).


          A web survey was sent to the cohorts. Anybody who responded to the survey was included, resulting in 14 891 eligible participants.

          Main outcomes measured

          The survey provided data on cancelled surgical or medical appointments, and the number of care hours received in a week during the first UK COVID-19 national lockdown.


          Using binary or ordered logistic regression, we evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. Adjustment was made for study design, non-response weights, psychological distress, presence of children or adolescents in the household, COVID-19 infection, key worker status, and whether participants had received a shielding letter. Meta-analyses were performed across the cohorts, and meta-regression was used to evaluate the effect of age as a moderator.


          Women (OR 1.40, 95% CI 1.27 to 1.55) and those with a chronic illness (OR 1.84, 95% CI 1.65 to 2.05) experienced significantly more cancellations during lockdown (all p<0.0001). Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown (both OR≈2.00, all p<0.002). SEP was not associated with cancellation or care hours. Age was not independently associated with either outcome in the meta-regression.


          The UK government’s lockdown approach during the COVID-19 pandemic appears to have deepened existing health inequalities, impacting predominantly women, ethnic minorities and those with chronic illnesses. Public health authorities need to implement urgent policies to ensure equitable access to health and care for all in preparation for a fourthwave.

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          Most cited references37

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          Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials

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            The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study

            Summary Background Since a national lockdown was introduced across the UK in March, 2020, in response to the COVID-19 pandemic, cancer screening has been suspended, routine diagnostic work deferred, and only urgent symptomatic cases prioritised for diagnostic intervention. In this study, we estimated the impact of delays in diagnosis on cancer survival outcomes in four major tumour types. Methods In this national population-based modelling study, we used linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15–84 years, diagnosed with breast, colorectal, and oesophageal cancer between Jan 1, 2010, and Dec 31, 2010, with follow-up data until Dec 31, 2014, and diagnosed with lung cancer between Jan 1, 2012, and Dec 31, 2012, with follow-up data until Dec 31, 2015. We use a routes-to-diagnosis framework to estimate the impact of diagnostic delays over a 12-month period from the commencement of physical distancing measures, on March 16, 2020, up to 1, 3, and 5 years after diagnosis. To model the subsequent impact of diagnostic delays on survival, we reallocated patients who were on screening and routine referral pathways to urgent and emergency pathways that are associated with more advanced stage of disease at diagnosis. We considered three reallocation scenarios representing the best to worst case scenarios and reflect actual changes in the diagnostic pathway being seen in the NHS, as of March 16, 2020, and estimated the impact on net survival at 1, 3, and 5 years after diagnosis to calculate the additional deaths that can be attributed to cancer, and the total years of life lost (YLLs) compared with pre-pandemic data. Findings We collected data for 32 583 patients with breast cancer, 24 975 with colorectal cancer, 6744 with oesophageal cancer, and 29 305 with lung cancer. Across the three different scenarios, compared with pre-pandemic figures, we estimate a 7·9–9·6% increase in the number of deaths due to breast cancer up to year 5 after diagnosis, corresponding to between 281 (95% CI 266–295) and 344 (329–358) additional deaths. For colorectal cancer, we estimate 1445 (1392–1591) to 1563 (1534–1592) additional deaths, a 15·3–16·6% increase; for lung cancer, 1235 (1220–1254) to 1372 (1343–1401) additional deaths, a 4·8–5·3% increase; and for oesophageal cancer, 330 (324–335) to 342 (336–348) additional deaths, 5·8–6·0% increase up to 5 years after diagnosis. For these four tumour types, these data correspond with 3291–3621 additional deaths across the scenarios within 5 years. The total additional YLLs across these cancers is estimated to be 59 204–63 229 years. Interpretation Substantial increases in the number of avoidable cancer deaths in England are to be expected as a result of diagnostic delays due to the COVID-19 pandemic in the UK. Urgent policy interventions are necessary, particularly the need to manage the backlog within routine diagnostic services to mitigate the expected impact of the COVID-19 pandemic on patients with cancer. Funding UK Research and Innovation Economic and Social Research Council.
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              Ethnicity and clinical outcomes in COVID-19: A systematic review and meta-analysis

              Background Patients from ethnic minority groups are disproportionately affected by Coronavirus disease (COVID-19). We performed a systematic review and meta-analysis to explore the relationship between ethnicity and clinical outcomes in COVID-19. Methods Databases (MEDLINE, EMBASE, PROSPERO, Cochrane library and MedRxiv) were searched up to 31st August 2020, for studies reporting COVID-19 data disaggregated by ethnicity. Outcomes were: risk of infection; intensive therapy unit (ITU) admission and death. PROSPERO ID: 180654. Findings 18,728,893 patients from 50 studies were included; 26 were peer-reviewed; 42 were from the United States of America and 8 from the United Kingdom. Individuals from Black and Asian ethnicities had a higher risk of COVID-19 infection compared to White individuals. This was consistent in both the main analysis (pooled adjusted RR for Black: 2.02, 95% CI 1.67–2.44; pooled adjusted RR for Asian: 1.50, 95% CI 1.24–1.83) and sensitivity analyses examining peer-reviewed studies only (pooled adjusted RR for Black: 1.85, 95%CI: 1.46–2.35; pooled adjusted RR for Asian: 1.51, 95% CI 1.22–1.88). Individuals of Asian ethnicity may also be at higher risk of ITU admission (pooled adjusted RR 1.97 95% CI 1.34–2.89) (but no studies had yet been peer-reviewed) and death (pooled adjusted RR/HR 1.22 [0.99–1.50]). Interpretation Individuals of Black and Asian ethnicity are at increased risk of COVID-19 infection compared to White individuals; Asians may be at higher risk of ITU admission and death. These findings are of critical public health importance in informing interventions to reduce morbidity and mortality amongst ethnic minority groups.

                Author and article information

                BMJ Open
                BMJ Open
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                18 March 2021
                18 March 2021
                : 11
                : 3
                : e045813
                [1 ]departmentSchool of Medicine , University College London , London, UK
                [2 ]departmentUCL MRC Unit for Lifelong Health and Ageing , University College London , London, UK
                [3 ]departmentInstitute of Cardiovascular Science , University College London , London, UK
                [4 ]departmentCardiac Imaging Department , Barts Heart Center , London, UK
                [5 ]departmentCenter for Longitudinal Studies, Department of Social Science , University College London , London, UK
                [6 ]departmentDepartment of Economics and UCL Social Research Institute , University College London , London, UK
                [7 ]departmentCenter for Inherited Heart Muscle Conditions, Cardiology Department , The Royal Free Hospital , London, UK
                Author notes
                [Correspondence to ] Dr Gaby Captur; gabriella.captur@ 123456ucl.ac.uk
                Author information
                © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/.

                : 13 October 2020
                : 04 February 2021
                : 01 March 2021
                Funded by: Economic and Social Research Council (ESRC);
                Award ID: ES/M001660/1
                Funded by: FundRef http://dx.doi.org/10.13039/501100000274, British Heart Foundation;
                Award ID: SP/20/2/34841
                Funded by: FundRef http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: grant MC_UU_00019/1
                Original research
                Custom metadata

                epidemiology,quality in health care,public health
                epidemiology, quality in health care, public health


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