Our primary care database covered a large inner city region that closely matched the normal catchment area for the hospital while at the same time enabling individual-level assessment of factors such as comorbidities and deprivation. In the present study, the use of a case-control design allowed us to compare in detail the characteristics of admitted patients with a representative sample of the source population and thereby minimise selection bias. Finally, using multiple imputation to impute missing values of comorbidity and IMD variables (<5%), fully adjusted hazard ratios for in-hospital mortality were as follows: Black 0.83 (0.62–1.09), Asian 1.55 (0.98–2.45) and Mixed/Other ethnicity 0.67 (0.42–1.07). The findings in this subset were similar to those of the main analysis (Supplemental Fig. To examine potential bias due to left truncation, we performed a sensitivity analysis in patients ≥65 years of age ( n = 928, 67% White, 22% Black, 5% Asian, 7% Mixed/Other ethnicity). Since the age at hospitalisation was, on average, younger for patients from minority ethnic groups than White patients, the age-specific hazard of death could be different for these groups. Sensitivity analyses in this subset (to examine potential bias due to differential left-censoring) revealed similar findings to the main analysis with respect to mortality (Supplemental Fig. These individuals had higher rates of hypertension and diabetes than patients without a symptom-onset record. Symptom-onset prior to admission was self-reported in 73.2% patients, including a greater proportion of Black and Minority Ethnic than White individuals (Supplemental Table 6). Sensitivity analyses adjusting for BMI in the subset of patients with BMI available produced results similar to those in the main analysis (Supplemental Fig. Number of comorbidities (excluding obesity) An increased OR for admission was observed for both Black African and Black Caribbean groups in disaggregated analyses (Supplemental Table 3).īMI was categorised as underweight (<18.5 kg/m2), normal (18.5–24.9 kg/m2 ), overweight (25–29.9 kg/m2 ), and obese (≥30 kg/m2 ). BMI contributed to a small proportion of ethnicity-associated admission risk (Supplemental Fig. Similar results were obtained in analyses adjusting for BMI, in the subset of individuals with BMI data available. There was no increase in admission risk associated with Asian ethnicity albeit the proportion of Asian patients in our study was small (5.6% cases, 7.8% controls, predominantly non-East Asian). In fully adjusted models including all comorbidities and deprivation quintile, there was modest attenuation of the association between Black or Mixed/Other ethnicity and risk of admission, with the OR still 2.2 to 2.7-fold higher for these groups ( Fig. 2). All comorbidities assessed were also associated with greater odds of admission, with the highest OR observed for cardiometabolic comorbidities, including hypertension (4.2 ) and diabetes (3.7 ). In analyses adjusting for the matching variables (age and sex) only, Black and Mixed/Other ethnicity were associated with higher odds of admission compared to White ethnicity ( Fig. 2) (OR for Black ethnicity 3.1, Mixed/Other 3.0 both p<0.001). Table 1 Characteristics of COVID-19 cases and matched population controls. For BMI, the most recent value within 6 months (median 27 days ) of admission (for hospital cases) or data extraction (primary care) was used. Demographic and clinical variables, identified a priori as potential risk factors for severe COVID-19, included: age, sex, body mass index (BMI), cardiometabolic comorbidities (hypertension, coronary heart disease, heart failure, previous stroke or transient ischaemic attack, diabetes, chronic kidney disease ), asthma and chronic obstructive pulmonary disease (COPD). Patients with missing ethnicity data were excluded. These were reduced into four groups: White (British, Irish, Gypsy, any other White), Black (African, Caribbean, any other Black), Asian (Indian, Pakistani, Bangladeshi, Chinese, any other Asian), and Mixed/Other. The Lancet Regional Health – Western Pacific.The Lancet Regional Health – Southeast Asia.The Lancet Gastroenterology & Hepatology.
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