Dataset Information

Is asthma associated with COVID-19 infection? A UK Biobank analysis.

ABSTRACT:

Background

The relationship between asthma and coronavirus disease 2019 (COVID-19) risk is not clear and may be influenced by level of airway obstruction, asthma medication and known COVID-19 risk factors. We aimed to investigate COVID-19 risk in people with asthma.

Methods

We used UK Biobank data from all participants tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (n=107 412; 17 979 test positive). Questions at baseline defined ever asthma and asthma medications. Baseline forced expiratory volume in 1 s (FEV₁) was categorised into quartiles. Logistic regression modelled relationships between asthma, and asthma categories (age at onset, medications, FEV₁ quartiles), and risk of SARS-CoV-2 positive test. We investigated modification by sex, ethnic group, smoking and body mass index.

Results

There was a reduced risk of a positive test associated with early-onset asthma (<13 years) (OR 0.91, 95% CI 0.84-0.99). This was found for participants with early-onset asthma who were male (OR 0.87, 95% CI 0.78-0.98), nonsmokers (OR 0.87, 95% CI 0.78-0.98), overweight/obese (OR 0.85, 95% CI 0.77-0.93) and non-Black (OR 0.90, 95% CI 0.82-0.98). There was increased risk amongst early-onset individuals with asthma in the highest compared to lowest quartile of lung function (1.44, 1.05-1.72).

Conclusion

Amongst male, nonsmoking, overweight/obese and non-Black participants, having early-onset asthma was associated with lower risk of a SARS-CoV-2 positive test. We found no evidence of a protective effect from asthma medication. Individuals with early-onset asthma of normal weight and with better lung function may have lifestyle differences placing them at higher risk. Further research is needed to elucidate the contribution of asthma pathophysiology and different health-related behaviour, across population groups, to the observed risks.

SUBMITTER: Lodge CJ

PROVIDER: S-EPMC8449950 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description: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 higher 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.

Project description:BackgroundPsychiatric morbidities have been associated with a risk of severe infections through compromised immunity, health behaviours, or both. However, data are scarce on the association between multiple types of pre-pandemic psychiatric disorders and COVID-19. We aimed to assess the association between pre-pandemic psychiatric disorders and the subsequent risk of COVID-19 using UK Biobank.MethodsFor this cohort analysis, we included participants from UK Biobank who were registered in England and excluded individuals who died before Jan 31, 2020, (the start of the COVID-19 outbreak in the UK) or had withdrawn from UK Biobank. Participants diagnosed with a psychiatric disorder before Jan 31 were included in the group of individuals with pre-pandemic psychiatric disorders, whereas participants without a diagnosis before the outbreak were included in the group of individuals without pre-pandemic psychiatric disorders. We used the Public Health England dataset, UK Biobank hospital data, and death registers to collect data on COVID-19 cases. To examine the relationship between pre-pandemic psychiatric disorders and susceptibility to COVID-19, we used logistic regression models to estimate odds ratios (ORs), controlling for multiple confounders and somatic comorbidities. Key outcomes were all COVID-19, COVID-19 specifically diagnosed in inpatient care, and COVID-19-related deaths. ORs were also estimated separately for each psychiatric disorder and on the basis of the number of pre-pandemic psychiatric disorders. As a positive disease control, we repeated analyses for hospitalisation for other infections.FindingsWe included 421 014 UK Biobank participants in our study and assessed their COVID-19 status between Jan 31 and July 26, 2020. 50 809 participants were diagnosed with psychiatric disorders before the outbreak, while 370 205 participants had no psychiatric disorders. The mean age at outbreak was 67·80 years (SD 8·12). We observed an elevated risk of COVID-19 among individuals with pre-pandemic psychiatric disorders compared with that of individuals without such conditions. The fully adjusted ORs were 1·44 (95% CI 1·28-1·62) for All COVID-19 cases, 1·55 (1·34-1·78) for Inpatient COVID-19 cases, and 2·03 (1·59-2·59) for COVID-19-related deaths. We observed excess risk, defined as risk that increased with the number of pre-pandemic psychiatric disorders, across all diagnostic categories of pre-pandemic psychiatric disorders. We also observed an association between psychiatric disorders and elevated risk of hospitalisation due to other infections (OR 1·74, 95% CI 1·58-1·93).InterpretationOur findings suggest that pre-existing psychiatric disorders are associated with an increased risk of COVID-19. These findings underscore the need for surveillance of and care for populations with pre-existing psychiatric disorders during the COVID-19 pandemic.FundingNational Natural Science Foundation of China.

Project description:BackgroundNutritional status influences immunity but its specific association with susceptibility to COVID-19 remains unclear. We examined the association of specific dietary data and incident COVID-19 in the UK Biobank (UKB).MethodsWe considered UKB participants in England with self-reported baseline (2006-2010) data and linked them to Public Health England COVID-19 test results-performed on samples from combined nose/throat swabs, using real time polymerase chain reaction (RT-PCR)-between March and November 2020. Baseline diet factors included breastfed as baby and specific consumption of coffee, tea, oily fish, processed meat, red meat, fruit, and vegetables. Individual COVID-19 exposure was estimated using the UK's average monthly positive case rate per specific geo-populations. Logistic regression estimated the odds of COVID-19 positivity by diet status adjusting for baseline socio-demographic factors, medical history, and other lifestyle factors. Another model was further adjusted for COVID-19 exposure.ResultsEligible UKB participants (n = 37,988) were 40 to 70 years of age at baseline; 17% tested positive for COVID-19 by SAR-CoV-2 PCR. After multivariable adjustment, the odds (95% CI) of COVID-19 positivity was 0.90 (0.83, 0.96) when consuming 2-3 cups of coffee/day (vs. <1 cup/day), 0.88 (0.80, 0.98) when consuming vegetables in the third quartile of servings/day (vs. lowest quartile), 1.14 (1.01, 1.29) when consuming fourth quartile servings of processed meats (vs. lowest quartile), and 0.91 (0.85, 0.98) when having been breastfed (vs. not breastfed). Associations were attenuated when further adjusted for COVID-19 exposure, but patterns of associations remained.ConclusionsIn the UK Biobank, consumption of coffee, vegetables, and being breastfed as a baby were favorably associated with incident COVID-19; intake of processed meat was adversely associated. Although these findings warrant independent confirmation, adherence to certain dietary behaviors may be an additional tool to existing COVID-19 protection guidelines to limit the spread of this virus.