ArticleArchives of public health = Archives belges de sante publique2024
Unravelling demographic and socioeconomic patterns of COVID-19 death and other causes of death: results of an individual-level analysis of exhaustive cause of death data in Belgium, 2020.
Article in Archives of public health = Archives belges de sante publique, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The trial behind it
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Who cites it
3 citing papers in PubMed.
- Post-acute organ complications within one year following COVID-19 hospitalization and related socioeconomic inequalities.Nature communications · 2026Article
- Post-acute healthcare expenditure following COVID-19 hospitalization and associated social inequalities in Belgium: a matched cohort study.BMC health services research · 2026Article
- Sociodemographic patterns of COVID-19 mortality: the 2020 Japanese census-linked mortality database.The Lancet regional health. Western Pacific · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundThe COVID-19 pandemic led to significant excess mortality in 2020 in Belgium. By using microlevel cause-specific mortality data for the total adult population in Belgium in 2020, three outcomes were considered in this study aiming at predicting sociodemographic (SD) and socioeconomic (SE) patterns of (1) COVID-19 specific death compared to survival; (2) all other causes of death (OCOD) compared to survival; and (3) COVID-19 specific death compared to all OCOD.
methodsTwo complementary statistical methods were used. First, multivariable logistic regression models providing odds ratios and 95% confidence intervals were fitted for the three study outcomes. In addition, we computed conditional inference tree (CIT) algorithms, a non-parametric class of classification trees, to identify and rank by significance level the strongest predictors of the three study outcomes.
resultsOlder individuals, males, individuals living in collectivities, first-generation migrants, and deprived SE groups experienced higher odds of dying from COVID-19 compared to survival; living in collectivities was identified by the CIT as the strongest predictor followed by age and sex. Education emerged as one of the strongest predictors for individuals not living in collectivities. Overall, similar patterns were observed for all OCOD except for first- and second-generation migrants having lower odds of all OCOD compared to survival; age group was identified by the CIT as the strongest predictor. Older individuals, males, individuals living in collectivities, first- and second-generation migrants, and individuals with lower levels of education had higher odds of COVID-19 death compared to all OCOD; living in collectivities was identified by the CIT as the strongest predictor followed by age, sex, and migration background. Education and income emerged as among the strongest predictors among individuals not living in collectivities.
conclusionsThis study identified important SD and SE disparities in COVID-19 mortality, with living in collectivities highlighted as the strongest predictor. This underlines the importance of implementing preventive measures, particularly within the most vulnerable populations, in infectious disease pandemic preparedness to reduce virus circulation and the resulting lethality.
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Registered trials
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