Background We examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and Black, Asian and Minority Ethnic (BAME) individuals is explained by cardiometabolic, socio-economic or behavioural factors. Methods We studied 4510 UK Biobank participants tested for COVID-19 (positive, n = 1326). Multivariate logistic regression models including age, sex and ethnicity were used to test whether addition of (1) cardiometabolic factors [diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking and body mass index (BMI)]; (2) 25(OH)-vitamin D; (3) poor diet; (4) Townsend deprivation score; (5) housing (home type, overcrowding) or (6) behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status. Results There was over-representation of men and BAME ethnicities in the COVID-19 positive group. BAME individuals had, on average, poorer cardiometabolic profile, lower 25(OH)-vitamin D, greater material deprivation, and were more likely to live in larger households and in flats/apartments. Male sex, BAME ethnicity, higher BMI, higher Townsend deprivation score and household overcrowding were independently associated with significantly greater odds of COVID-19. The pattern of association was consistent for men and women; cardiometabolic, socio-demographic and behavioural factors did not attenuate sex/ethnicity associations. Conclusions In this study, sex and ethnicity differential pattern of COVID-19 was not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels or socio-economic factors. Factors which underlie ethnic differences in COVID-19 may not be easily captured, and so investigation of alternative biological and genetic susceptibilities as well as more comprehensive assessment of the complex economic, social and behavioural differences should be prioritised.
Background: Cardiometabolic morbidity and medications, specifically Angiotensin ConvertingEnzyme inhibitors (ACEi) and Angiotensin Receptor Blockers (ARBs), have been linked with adverse outcomes from coronavirus disease 2019 . This study aims to investigate factors associated with COVID-19 positivity for the first 669 UK Biobank participants; compared with individuals who tested negative, and with the untested, presumed negative, rest of the population. Methods:We studied 1,474 participants from the UK Biobank who had been tested for COVID-19.Given UK testing policy, this implies a hospital setting, suggesting at least moderate to severe symptoms. We considered the following exposures: age, sex, ethnicity, body mass index (BMI), diabetes, hypertension, hypercholesterolaemia, ACEi/ARB use, prior myocardial infarction (MI), and smoking. We undertook comparisons between: 1) COVID-19 positive and COVID-19 tested negative participants; and 2) COVID-19 tested positive and the remaining participants (tested negative plus untested, n=501,837). Logistic regression models were used to investigate univariate and mutually adjusted associations.Results: Among participants tested for COVID-19, non-white ethnicity, male sex, and greater BMI were independently associated with COVID-19 positive result. Non-white ethnicity, male sex, greater BMI, diabetes, hypertension, prior MI, and smoking were independently associated with COVID-19 positivity compared to the remining cohort (test negatives plus untested). However, similar associations were observed when comparing those who tested negative for COVID-19 with the untested cohort;suggesting that these factors associate with general hospitalisation rather than specifically with COVID- 19.Conclusions: Among participants tested for COVID-19 with presumed moderate to severe symptoms in a hospital setting, non-white ethnicity, male sex, and higher BMI are associated with a positive result.
Raisi-Estabragh et al. Renin-Angiotensin System Blockers and COVID-19 Conclusions: Among participants tested for COVID-19 with presumed moderate to severe symptoms in a hospital setting, BAME ethnicity, male sex, and higher BMI are associated with a positive result. Other cardiometabolic morbidities confer increased risk of hospitalization, without specificity for COVID-19. ACE/ARB use did not associate with COVID-19 status.
ObjectiveTo examine associations of birth weight with clinical and imaging indicators of cardiovascular health and evaluate mechanistic pathways in the UK Biobank.MethodsCompeting risk regression was used to estimate associations of birth weight with incident myocardial infarction (MI) and mortality (all-cause, cardiovascular disease, ischaemic heart disease, MI), over 7–12 years of longitudinal follow-up, adjusting for age, sex, deprivation, maternal smoking/hypertension and maternal/paternal diabetes. Mediation analysis was used to evaluate the role of childhood growth, adulthood obesity, cardiometabolic diseases and blood biomarkers in mediating the birth weight–MI relationship. Linear regression was used to estimate associations of birth weight with left ventricular (LV) mass-to-volume ratio, LV stroke volume, global longitudinal strain, LV global function index and left atrial ejection fraction.Results258 787 participants from white ethnicities (61% women, median age 56 (49, 62) years) were studied. Birth weight had a non-linear relationship with incident MI, with a significant inverse association below an optimal threshold of 3.2 kg (subdistribution HR: 1.15 (1.08 to 1.22), p=6.0×10–5) and attenuation to the null above this threshold. The birth weight–MI effect was mediated through hypertension (8.4%), glycated haemoglobin (7.0%), C reactive protein (6.4%), high-density lipoprotein (5.2%) and high cholesterol (4.1%). Birth weight–mortality associations were statistically non-significant after Bonferroni correction. In participants with cardiovascular magnetic resonance (n=19 314), lower birth weight was associated with adverse LV remodelling (greater concentricity, poorer function).ConclusionsLower birth weight was associated with greater risk of incident MI and unhealthy LV phenotypes; effects were partially mediated through cardiometabolic disease and systemic inflammation. These findings support consideration of birth weight in risk prediction and highlight actionable areas for disease prevention.
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