We found that age, male sex and Black ethnicity were strongly associated with COVID-19 death as previously reported [5, 6] and were highly explanatory of COVID-19 death. In addition, comorbidities (cardiovascular disease, hypertension, diabetes and autoimmune disease), history of oral steroids and being a healthcare worker, current smoker or former drinker at enrolment were independently associated with COVID-19 death. Age, male sex, Black ethnicity, cardiovascular disease, hypertension, diabetes, and history of oral steroid use were also highly selected in LASSO models, as were cystatin C and income. Of these, ethnicity, hypertension, and history of steroid use specifically associated with the risk of COVID-19 but not non-COVID-19 death in the same population and during the same period. These variables yielded only incremental improvements over age, sex and ethnicity in the prediction of COVID mortality.
We examined effects of various classes of drugs (steroids, RAAS inhibitors, statins) on risk of COVID-19 death. History of oral steroid use at enrolment was consistently associated with risk of COVID-19 death after multiple adjustment and in LASSO stability selection. These findings might result from the long-term immunosuppressant effects of systemic steroids or the associated risk of diabetes ; alternatively, they might be acting as a marker for severity of underlying disease such as autoimmune or respiratory disease. However, it has been shown that systemic steroids are an effective treatment for severe COVID-19, including reducing risk of COVID-19 mortality for those requiring oxygen therapy .
ACEi and ARBs have been postulated to increase risk of severe / fatal COVID-19 due to, among other possible mechanisms, upregulation of transmembrane ACE2 receptor expression (the cell entry site for the SARS-CoV-2 virus) . In the present study, however, while history of ACEi and ARB use were positively associated with risk of COVID-19 death in univariate analysis, these associations did not survive multiple adjustment. This is in keeping with other reports showing no effect of these drugs on COVID-19 mortality [20, 21].
The role of statins in COVID-19 remains unclear. Positive effects have been proposed, for example through anti-inflammatory, anti-thrombotic or immunomodulatory mechanisms, as well as negative effects such as on kidney function or increased diabetes risk [24, 38, 39]. Here, statin therapy was positively associated with risk of COVID-19 death in univariate analysis but not after multiple adjustment, nor was it selected in LASSO stability analyses. It seems likely that the univariate association with statin therapy is confounded by comorbidities such as cardiovascular disease, where statins are used for prevention and treatment.
We found healthcare workers to be at increased risk of COVID-19 death even after adjustment for other covariates. These findings are consistent with results from national mortality statistics , which show elevated risk of COVID-19 mortality among healthcare workers (especially men) in comparison to that of the general population, accounting for age and sex. This may reflect a higher risk of infection among healthcare workers than in the general population .
A number of lifestyle and environmental factors have been suggested to affect risk of COVID-19 death. Among these, smoking has been suggested to reduce risk of infection but increase risk of severe or fatal COVID-19 post infection [15, 42]. In the present study, current smoking on enrolment was positively associated with risk of COVID-19 death. Meanwhile, respiratory disease was associated with COVID-19 mortality only in univariate analysis. The respiratory disease findings may partly be explained by inclusion of smoking in adjusted analyses. However, neither smoking nor respiratory disease were highly selected by LASSO models (< 50%), suggesting they were not key factors driving COVID-19 mortality despite SARS-CoV-2 virus being primarily a respiratory pathogen.
Environmental exposure to air pollutants  and low vitamin D levels have both been proposed to increase risk of COVID-19 death  but we found little support for these associations. While vitamin D was associated with decreased COVID-19 mortality risk in univariate analysis, this did not survive multiple adjustment nor was vitamin D selected by LASSO stability analysis; these findings are consistent with lack of association between vitamin D levels and positive testing for SARS-CoV-2 virus in previous analyses of UK Biobank . For air pollutants, while we observed a small effect of particulate pollution on risk of COVID-19 death in univariate analyses, this was attenuated upon adjustment for other covariates.
Cystatin C was positively associated with COVID-19 mortality in univariate analysis and was highly selected by the LASSO models but did not survive multiple adjustment. Cystatin C has been implicated in severe COVID-19  but, to our knowledge, this is the first report of it being associated with risk of COVID-19 death. It is a marker of kidney function and inflammatory state and may capture features of comorbidities, such as cardiovascular disease, that were independently associated with COVID-19 mortality in our data .
Our work has a number of limitations. First, although UK Biobank includes over 500,000 participants, numbers of COVID-19 deaths were modest compared to national studies of mortality and hospitalised cases. Nonetheless, unlike such studies, our work combines (i) COVID-19 and non-COVID-19 mortality data linked to UK Biobank data, (ii) individual demographic, social, biological, health risk, medical and environmental factors collected at enrolment, and (iii) detailed information on premorbid conditions. While baseline characteristics of the cohort were obtained over ten years prior to the period of the epidemic, they may have changed in the interim. However, for the intervening period, we were able to identify morbid events through linkage to hospitalisation data, giving updated information on comorbidities. UK Biobank has a 5.5% response rate, giving a selected population that is not fully representative of the UK population . However, it has been reported that within-cohort risk factor associations with mortality in UK Biobank appear generalisable. Data from the latest release of UK Biobank include COVID-19 deaths up to the end of September 2020, and therefore do not capture the second wave of the epidemic in the UK. Given the bimodal nature of the pattern of COVID-19 mortality in the UK so far, timing of the occurrence of COVID-19 deaths will need to be taken into account in future analyses, for example, using survival regression models.
The use of multivariable regression and variable selection approaches enabled us to model correlation across predictors in relation to mortality and identify sets of variables jointly contributing to risk of COVID-19 death. These methods aim to capture the complex interrelationships between covariates, although are dependent on parametric assumptions underlying (generalised) linear models. In addition, given these are observational data, we cannot rule out residual confounding. However, comparing our findings for COVID-19 versus non-COVID-19 mortality during the same period lends further plausibility to the specificity of the COVID-19 mortality associations.
In conclusion, our study of the ongoing COVID-19 epidemic as it affected UK Biobank participants has identified age, male sex and Black ethnicity as key explanatory factors for COVID-19 death. Among other covariates, some were consistently associated with and moderately explanatory of COVID-19 mortality. Comorbidities including cardiovascular disease, hypertension, diabetes and autoimmune disease as well as oral steroid use at enrolment were independently associated with increased COVID-19 mortality risk. In particular, Black ethnicity, oral steroids and hypertension were associated with COVID-19 but did not explain non-COVID-19 mortality in this population. Our results indicate that previously reported associations with COVID-19 mortality involving the use of RAAS inhibitors, statins, current smoking, vitamin D levels and air pollutants may, at least partially, be explained by factors we have identified. Further follow-up of UK Biobank with linkage to primary and secondary care as well as future mortality data will help delineate the long-term sequelae of COVID-19.