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1.
PLoS Med ; 19(2): e1003904, 2022 02.
Article in English | MEDLINE | ID: covidwho-1686090

ABSTRACT

BACKGROUND: Deaths in the first year of the Coronavirus Disease 2019 (COVID-19) pandemic in England and Wales were unevenly distributed socioeconomically and geographically. However, the full scale of inequalities may have been underestimated to date, as most measures of excess mortality do not adequately account for varying age profiles of deaths between social groups. We measured years of life lost (YLL) attributable to the pandemic, directly or indirectly, comparing mortality across geographic and socioeconomic groups. METHODS AND FINDINGS: We used national mortality registers in England and Wales, from 27 December 2014 until 25 December 2020, covering 3,265,937 deaths. YLLs (main outcome) were calculated using 2019 single year sex-specific life tables for England and Wales. Interrupted time-series analyses, with panel time-series models, were used to estimate expected YLL by sex, geographical region, and deprivation quintile between 7 March 2020 and 25 December 2020 by cause: direct deaths (COVID-19 and other respiratory diseases), cardiovascular disease and diabetes, cancer, and other indirect deaths (all other causes). Excess YLL during the pandemic period were calculated by subtracting observed from expected values. Additional analyses focused on excess deaths for region and deprivation strata, by age-group. Between 7 March 2020 and 25 December 2020, there were an estimated 763,550 (95% CI: 696,826 to 830,273) excess YLL in England and Wales, equivalent to a 15% (95% CI: 14 to 16) increase in YLL compared to the equivalent time period in 2019. There was a strong deprivation gradient in all-cause excess YLL, with rates per 100,000 population ranging from 916 (95% CI: 820 to 1,012) for the least deprived quintile to 1,645 (95% CI: 1,472 to 1,819) for the most deprived. The differences in excess YLL between deprivation quintiles were greatest in younger age groups; for all-cause deaths, a mean of 9.1 years per death (95% CI: 8.2 to 10.0) were lost in the least deprived quintile, compared to 10.8 (95% CI: 10.0 to 11.6) in the most deprived; for COVID-19 and other respiratory deaths, a mean of 8.9 years per death (95% CI: 8.7 to 9.1) were lost in the least deprived quintile, compared to 11.2 (95% CI: 11.0 to 11.5) in the most deprived. For all-cause mortality, estimated deaths in the most deprived compared to the most affluent areas were much higher in younger age groups, but similar for those aged 85 or over. There was marked variability in both all-cause and direct excess YLL by region, with the highest rates in the North West. Limitations include the quasi-experimental nature of the research design and the requirement for accurate and timely recording. CONCLUSIONS: In this study, we observed strong socioeconomic and geographical health inequalities in YLL, during the first calendar year of the COVID-19 pandemic. These were in line with long-standing existing inequalities in England and Wales, with the most deprived areas reporting the largest numbers in potential YLL.


Subject(s)
COVID-19/mortality , Adult , Aged , Cardiovascular Diseases/mortality , Cause of Death , Diabetes Mellitus/mortality , England/epidemiology , Female , Health Status Disparities , Humans , Interrupted Time Series Analysis , Life Expectancy , Male , Middle Aged , Neoplasms/mortality , Residence Characteristics , Respiratory Tract Diseases/mortality , Socioeconomic Factors , Wales/epidemiology
2.
BMJ Qual Saf ; 2021 Oct 12.
Article in English | MEDLINE | ID: covidwho-1467705

ABSTRACT

OBJECTIVE: To compare rates of performing National Institute for Health and Care Excellence-recommended health checks and prescribing in people with type 2 diabetes (T2D), before and after the first COVID-19 peak in March 2020, and to assess whether trends varied by age, sex, ethnicity and deprivation. METHODS: We studied 618 161 people with T2D followed between March and December 2020 from 1744 UK general practices registered with the Clinical Practice Research Datalink. We focused on six health checks: haemoglobin A1c, serum creatinine, cholesterol, urinary albumin excretion, blood pressure and body mass index assessment. Regression models compared observed rates in April 2020 and between March and December 2020 with trend-adjusted expected rates derived from 10-year historical data. RESULTS: In April 2020, in English practices, rates of performing health checks were reduced by 76%-88% when compared with 10-year historical trends, with older people from deprived areas experiencing the greatest reductions. Between May and December 2020, the reduced rates recovered gradually but overall remained 28%-47% lower, with similar findings in other UK nations. Extrapolated to the UK population, there were ~7.4 million fewer care processes undertaken March-December 2020. In England, rates for new medication fell during April with reductions varying from 10% (95% CI: 4% to 16%) for antiplatelet agents to 60% (95% CI: 58% to 62%) for antidiabetic medications. Overall, between March and December 2020, the rate of prescribing new diabetes medications fell by 19% (95% CI: 15% to 22%) and new antihypertensive medication prescribing fell by 22% (95% CI: 18% to 26%), but prescribing of new lipid-lowering or antiplatelet therapy was unchanged. Similar trends were observed across the UK, except for a reduction in new lipid-lowering therapy prescribing in the other UK nations (reduction: 16% (95% CI: 10% to 21%)). Extrapolated to the UK population, between March and December 2020, there were ~31 800 fewer people with T2D prescribed a new type of diabetes medication and ~14 600 fewer prescribed a new type of antihypertensive medication. CONCLUSIONS: Over the coming months, healthcare services will need to manage this backlog of testing and prescribing. We recommend effective communications to ensure patient engagement with diabetes services, monitoring and opportunities for prescribing, and when appropriate use of home monitoring, remote consultations and other innovations in care.

5.
Lancet Reg Health Eur ; 7: 100144, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1260817

ABSTRACT

BACKGROUND: Excess deaths during the COVID-19 pandemic compared with those expected from historical trends have been unequally distributed, both geographically and socioeconomically. Not all excess deaths have been directly related to COVID-19 infection. We investigated geographical and socioeconomic patterns in excess deaths for major groups of underlying causes during the pandemic. METHODS: Weekly mortality data from 27/12/2014 to 2/10/2020 for England and Wales were obtained from the Office of National Statistics. Negative binomial regressions were used to model death counts based on pre-pandemic trends for deaths caused directly by COVID-19 (and other respiratory causes) and those caused indirectly by it (cardiovascular disease or diabetes, cancers, and all other indirect causes) over the first 30 weeks of the pandemic (7/3/2020-2/10/2020). FINDINGS: There were 62,321 (95% CI: 58,849 to 65,793) excess deaths in England and Wales in the first 30 weeks of the pandemic. Of these, 46,221 (95% CI: 45,439 to 47,003) were attributable to respiratory causes, including COVID-19, and 16,100 (95% CI: 13,410 to 18,790) to other causes. Rates of all-cause excess mortality ranged from 78 per 100,000 in the South West of England and in Wales to 130 per 100,000 in the West Midlands; and from 93 per 100,000 in the most affluent fifth of areas to 124 per 100,000 in the most deprived. The most deprived areas had the highest rates of death attributable to COVID-19 and other indirect deaths, but there was no socioeconomic gradient for excess deaths from cardiovascular disease/diabetes and cancer. INTERPRETATION: During the first 30 weeks of the COVID-19 pandemic there was significant geographic and socioeconomic variation in excess deaths for respiratory causes, but not for cardiovascular disease, diabetes and cancer. Pandemic recovery plans, including vaccination programmes, should take account of individual characteristics including health, socioeconomic status and place of residence. FUNDING: None.

6.
Thorax ; 76(6): 601-606, 2021 06.
Article in English | MEDLINE | ID: covidwho-1203985

ABSTRACT

INTRODUCTION: Shift work is associated with lung disease and infections. We therefore investigated the impact of shift work on significant COVID-19 illness. METHODS: 501 000 UK Biobank participants were linked to secondary care SARS-CoV-2 PCR results from Public Health England. Healthcare worker occupational testing and those without an occupational history were excluded from analysis. RESULTS: Multivariate logistic regression (age, sex, ethnicity and deprivation index) revealed that irregular shift work (OR 2.42, 95% CI 1.92 to 3.05), permanent shift work (OR 2.5, 95% CI 1.95 to 3.19), day shift work (OR 2.01, 95% CI 1.55 to 2.6), irregular night shift work (OR 3.04, 95% CI 2.37 to 3.9) and permanent night shift work (OR 2.49, 95% CI 1.67 to 3.7) were all associated with positive COVID-19 tests compared with participants that did not perform shift work. This relationship persisted after adding sleep duration, chronotype, premorbid disease, body mass index, alcohol and smoking to the model. The effects of workplace were controlled for in three ways: (1) by adding in work factors (proximity to a colleague combined with estimated disease exposure) to the multivariate model or (2) comparing participants within each job sector (non-essential, essential and healthcare) and (3) comparing shift work and non-shift working colleagues. In all cases, shift work was significantly associated with COVID-19. In 2017, 120 307 UK Biobank participants had their occupational history reprofiled. Using this updated occupational data shift work remained associated with COVID-19 (OR 4.48 (95% CI 1.8 to 11.18). CONCLUSIONS: Shift work is associated with a higher likelihood of in-hospital COVID-19 positivity. This risk could potentially be mitigated via additional workplace precautions or vaccination.


Subject(s)
COVID-19/epidemiology , Hospitalization/statistics & numerical data , Pneumonia, Viral/epidemiology , Shift Work Schedule , Adult , Aged , COVID-19/prevention & control , Disease Susceptibility , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/virology , Risk Factors , United Kingdom/epidemiology
7.
Acta Diabetol ; 58(2): 231-237, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-871475

ABSTRACT

AIMS: People with type 1 diabetes (T1D) face the daily task of implementing self-management strategies to achieve their glycaemic goals. The UK COVID-19 lockdown has had an impact on day-to-day behaviour, which may affect diabetes self-management and outcomes. We assessed whether sensor-based outcomes pre- and during lockdown periods were different in a cohort of glucose sensor users with T1D. METHODS: Data were collected from Freestyle Libre (FSL) or Dexcom G6 sensor users who remotely shared their data with the diabetes clinic web platform. Sensor metrics according to international consensus were analysed and compared between pre-lockdown period and 2 and 3 weeks into lockdown (periods 1 and 2). RESULTS: Two hundred and sixty-nine T1D patients (baseline HbA1c 57 ± 14 mmol/mol) were identified as FSL (n = 190) or Dexcom G6 (n = 79) users. In patients with sensor use > 70% (N = 223), compared to pre-lockdown period percentage TIR 3.9-10 mM (TIR) significantly increased during period 1 (59.6 ± 18.2 vs. 57.5 ± 17.2%, p = 0.002) and period 2 (59.3 ± 18.3 vs. 57.5 ± 17.2%, p = 0.035). The proportion of patients achieving TIR ≥ 70% increased from 23.3% pre-lockdown to 27.8% in period 1 and 30.5% in period 2. A higher proportion also achieved the recommended time below and above range, and coefficient of variation in periods 1 and 2. Dexcom G6 users had significantly lower % time below range (< 3.9 mM) compared to FSL users during both lockdown periods (period 1: Dexcom G6 vs. FSL: 1.8% vs. 4%; period 2: 1.4% vs. 4%, p < 0.005 for both periods). CONCLUSION: Sensor-based glycaemic outcomes in people with T1D in the current cohort improved during COVID-19 lockdown, which may be associated with positive changes in self-management strategies. Further work is required to evaluate long-term sustainability and support.


Subject(s)
Blood Glucose/analysis , COVID-19/epidemiology , Diabetes Mellitus, Type 1/blood , Quarantine , Remote Sensing Technology/instrumentation , Telemedicine , Adult , Blood Glucose/metabolism , Blood Glucose Self-Monitoring/instrumentation , Blood Glucose Self-Monitoring/methods , Clinical Audit , Communicable Disease Control/methods , Computer Systems , Diabetes Mellitus, Type 1/drug therapy , Diabetes Mellitus, Type 1/epidemiology , England/epidemiology , Female , Health Services Accessibility/organization & administration , Health Services Accessibility/standards , Hospitals, Teaching , Humans , Insulin/administration & dosage , Insulin Infusion Systems , Male , Middle Aged , Pandemics , Remote Sensing Technology/standards , Retrospective Studies , SARS-CoV-2/physiology , Telemedicine/instrumentation , Telemedicine/organization & administration , Telemedicine/standards
8.
Eur J Endocrinol ; 183(2): G67-G77, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-665892

ABSTRACT

The COVID-19 pandemic is a major international emergency leading to unprecedented medical, economic and societal challenges. Countries around the globe are facing challenges with diabetes care and are similarly adapting care delivery, with local cultural nuances. People with diabetes suffer disproportionately from acute COVID-19 with higher rates of serious complications and death. In-patient services need specialist support to appropriately manage glycaemia in people with known and undiagnosed diabetes presenting with COVID-19. Due to the restrictions imposed by the pandemic, people with diabetes may suffer longer-term harm caused by inadequate clinical support and less frequent monitoring of their condition and diabetes-related complications. Outpatient management need to be reorganised to maintain remote advice and support services, focusing on proactive care for the highest risk, and using telehealth and digital services for consultations, self-management and remote monitoring, where appropriate. Stratification of patients for face-to-face or remote follow-up should be based on a balanced risk assessment. Public health and national organisations have generally responded rapidly with guidance on care management, but the pandemic has created a tension around prioritisation of communicable vs non-communicable disease. Resulting challenges in clinical decision-making are compounded by a reduced clinical workforce. For many years, increasing diabetes mellitus incidence has been mirrored by rising preventable morbidity and mortality due to complications, yet innovation in service delivery has been slow. While the current focus is on limiting the terrible harm caused by the pandemic, it is possible that a positive lasting legacy of COVID-19 might include accelerated innovation in chronic disease management.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Diabetes Mellitus/epidemiology , Diabetes Mellitus/therapy , Pneumonia, Viral/epidemiology , Pneumonia, Viral/therapy , Therapies, Investigational/trends , COVID-19 , Coronavirus Infections/diagnosis , Diabetes Mellitus/diagnosis , Endocrinology/methods , Endocrinology/trends , Humans , Pandemics , Pneumonia, Viral/diagnosis , SARS-CoV-2 , Telemedicine/methods , Telemedicine/trends , Therapies, Investigational/methods , United Kingdom/epidemiology
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