Distinct socioeconomic profile of patients hospitalised with severe COVID-19 and prepandemic respiratory infections in Brussels’s deprived areas: a case–control study

OBJECTIVE: Belgium has been hit harder by COVID-19 than other countries in Europe. While clinical risk factors are well studied, socioeconomic risk factors remained underexplored. This study’s objective was to analyse the social and clinical profile of patients hospitalised for COVID-19 during the two waves of 2020, compared with a control population in 2019 in two hospitals located in Brussels’ most deprived area. DESIGN AND METHODS: We did a case–control study by using the minimal clinical data set in two Brussels hospitals. All patients hospitalised for COVID-19 in 2020, divided into two waves (n=3220), were compared with all patients hospitalised for viral pneumonia and respiratory diseases in 2019 (control population n=2950). Multinomial regression models were used to estimate the relative risk ratios of the association between the COVID-19 hospitalised populations (waves 1 and 2) and risk factors (social and clinical) stratified by age. RESULTS: Patients under 65 years of age and hospitalised for COVID-19 presented significantly higher rates (relative rate ratio (95% CI)), especially for the first wave, of obesity 1.6 (1.2–2.2), African nationalities 1.4 (1.0–1.8), lack of health insurance 1.6 (1.3–2.1), living in high-density population areas 1.6 (1.3–2.1) and low incomes 1.7 (1.4–2.1), compared with the control population For patients over 65 years of age, we did not observe significant excess of COVID-19 hospitalisations for any risk factors, except diabetes during for the second wave but we have a significant excess mortality rate than the control population for both waves (p<0.002). CONCLUSIONS: The social and clinical profile of patients hospitalised for COVID-19 compared with a population hospitalised for viral respiratory diseases differed between age groups and waves. For younger patients, risk factors were linked to patients’ precarious situations. This study underlines the role of selected social health determinants and the importance of routinely collecting social data, along with clinical data, particularly among vulnerable populations.