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Many western countries used shielding (extended self-isolation) of people presumed to be at high-risk from COVID-19 to protect them and reduce healthcare demand. To investigate the effectiveness of this strategy, we linked family practitioner, prescribing, laboratory, hospital and death records and compared COVID-19 outcomes among shielded and non-shielded individuals in the West of Scotland. Of the 1.3 million population, 27,747 (2.03%) were advised to shield, and 353,085 (26.85%) were classified a priori as moderate risk. COVID-19 testing was more common in the shielded (7.01%) and moderate risk (2.03%) groups, than low risk (0.73%). Referent to low-risk, the shielded group had higher confirmed infections (RR 8.45, 95% 7.44-9.59), case-fatality (RR 5.62, 95% CI 4.47-7.07) and population mortality (RR 57.56, 95% 44.06-75.19). The moderate-risk had intermediate confirmed infections (RR 4.11, 95% CI 3.82-4.42) and population mortality (RR 25.41, 95% CI 20.36-31.71) but, due to their higher prevalence, made the largest contribution to deaths (PAF 75.30%). Age [≥]70 years accounted for 49.55% of deaths. In conclusion, shielding has not been effective at preventing deaths in individuals at high risk. Also, to be effective as a population strategy, shielding criteria would need to be widely expanded to include other criteria, such as the elderly.
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BACKGROUNDIt is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity ([≥]2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. METHODS AND FINDINGSWe studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with [≥]2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and [≥]2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response increased risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI [≥]40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. CONCLUSIONSIncreasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19. Author summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIMultimorbidity is a growing global challenge, but thus far LTC prognostic factors for severe COVID-19 primarily involve single conditions and there is a lack of data on the influence of multimorbidity on the risk of COVID-19. C_LIO_LIAs countries move from the lockdown phase of COVID-19, clinicians need more information about risk stratification to appropriately advise patients with multimorbidity about risk prevention steps. C_LI What did the researchers do and find?O_LIParticipants with multimorbidity ([≥]2 LTCs) had a 48% higher risk of a positive COVID-19 test, those with cardiometabolic multimorbidity had a 77% higher risk, than those without that type of multimorbidity. C_LIO_LIThose from non-white ethnicities with multimorbidity had nearly three times the risk of having COVID-19 infection compared to those of white ethnicity C_LIO_LIPeople with multimorbidity with the highest risk of COVID-19 infection were the most socioeconomically deprived, those with BMI [≥]40 kg/m2, and those with reduced renal function. C_LI What do these findings mean?O_LIIndividuals with [≥]2 LTCs, especially if these are cardiometabolic in nature, should be particularly stringent in adhering to preventive measures, such as physical distancing and hand hygiene. C_LIO_LIOur findings have implications for clinicians, occupational health and employers when considering work-place environments, appropriate advice for patients, and adaptations that might be required to protect such staff, identified here, as higher risk. C_LI
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ObjectivesTo investigate severe COVID-19 risk by occupational group. MethodsBaseline UK Biobank data (2006-10) for England were linked to SARS-CoV-2 test results from Public Health England (16 March to 26 July 2020). Included participants were employed or self-employed at baseline, alive and aged less than 65 years in 2020. Poisson regression models adjusted sequentially for baseline demographic, socioeconomic, work-related, health, and lifestyle-related risk factors to assess risk ratios (RRs) for testing positive in hospital or death due to COVID-19 by three occupational classification schemes (including Standard Occupation Classification 2000). ResultsOf 120,075 participants, 271 had severe COVID-19. Relative to non-essential workers, healthcare workers (RR 7.43, 95% CI:5.52,10.00), social and education workers (RR 1.84, 95% CI:1.21,2.82) and other essential workers (RR=1.60, 95% CI:1.05,2.45) had higher risk of severe COVID-19. Using more detailed groupings, medical support staff (RR 8.70, 95% CI:4.87,15.55), social care (RR 2.46, 95% CI:1.47,4.14) and transport workers (RR= 2.20, 95% CI:1.21,4.00) had highest risk within the broader groups. Compared to white non-essential workers, non-white non-essential workers had a higher risk (RR 3.27, 95% CI: 1.90,5.62) and non-white essential workers had the highest risk (RR 8.34, 95% CI:5.17,13.47). Using SOC2000 major groups, associate professional and technical occupations, personal service occupations and plant and machine operatives had higher risk, compared to managers and senior officials. ConclusionsEssential workers have higher risk of severe COVID-19. These findings underscore the need for national and organizational policies and practices that protect and support workers with elevated risk of severe COVID-19. Trial registration-N/AO_LSTWhat is already known on this topicC_LSTO_LIEssential workers have a higher exposure to the SARS-CoV-2 virus due to the nature of their work. C_LIO_LIIn comparison to non-essential workers, healthcare workers appear to have a higher risk of SARS-CoV-2 infection. C_LI O_LSTWhat this study addsC_LSTO_LIHealthcare workers had a more than seven-fold higher risk of severe COVID-19; those working in social care and transport occupations had a two-fold higher risk. C_LIO_LIAdjusting for potential confounding and mediating variables did not fully account for the differences in the observed risk amongst most occupational groups. C_LIO_LINon-white essential workers had the highest risk of severe COVID-19 infection. C_LI O_LSTHow might this impact on policy or clinical practice in the foreseeable future?C_LSTO_LIOur findings reinforce the need for adequate health and safety arrangements and provision of PPE, particularly in the health and social care sectors, and highlight the need for national and organizational policies and practices that protect and support workers with elevated risk of SARS-CoV-2 infection. C_LI
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BackgroundUnderstanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study. MethodsThe UK Biobank study recruited 40-70 year olds in 2006-2010 from the general population, collecting information about self-defined ethnicity and socioeconomic variables (including area-level socioeconomic deprivation and educational attainment). SARS-CoV-2 test results from Public Health England were linked to baseline UK Biobank data. Poisson regression with robust standard errors was used to assess risk ratios (RRs) between the exposures and dichotomous variables for: being tested, having a positive test and testing positive in hospital. We also investigated whether ethnicity and socioeconomic position were associated with having a positive test amongst those tested. We adjusted for covariates including age, sex, social variables (including healthcare work and household size), behavioural risk factors and baseline health. ResultsAmong 428,225 participants in England, 1,474 had been tested and 669 tested positive between 16 March and 13 April 2020. Black, south Asian and white Irish people were more likely to have confirmed infection (RR 4.01 (95%CI 2.92-5.12); RR 2.11 (95%CI 1.43-3.10); and RR 1.60 (95% CI 1.08-2.38) respectively) and were more likely to be hospital cases compared to the White British. While they were more likely to be tested, they were also more likely to test positive. Adjustment for baseline health and behavioural risk factors led to little change, with only modest attenuation when accounting for socioeconomic variables. Socioeconomic deprivation and having no qualifications were consistently associated with a higher risk of confirmed infection (RR 2.26 (95%CI 1.76-2.90); and RR 1.91 (95%CI 1.53-2.38) respectively). ConclusionsSome minority ethnic groups have a higher risk of confirmed SARS-CoV-2 infection in the UK Biobank study which was not accounted for by differences in socioeconomic conditions, measured baseline health or behavioural risk factors. An urgent response to addressing these elevated risks is required.
