Understanding excess mortality during COVID in Belgium: the influence of pre-existing health status and social factors.

Background: This study aims to investigate how pre-existing health status and social background contribute to excess mortality during the COVID-19 crisis in Belgium.

Methods: The study population consists of almost 1.4 million adult members of Solidaris, the second largest health insurance fund in Belgium.

A Nationwide Exploration of Social Inequalities in Cancer Mortality Amidst the COVID-19 Pandemic in Belgium.

Background: The COVID-19 pandemic disrupted global health systems, impacting cancer care and potentially increasing cancer mortality, especially among socioeconomically disadvantaged individuals. We aimed to assess changes in cancer mortality from March 1 to December 31, 2020 relative to the same period in 2019, and to examine potential shifts in cancer mortality's social disparities during the same time frame.

Methods: We used nationwide individually linked cancer mortality data from the Belgian National Register, the Census 2011, and the tax register.

Uncovering the toll of the first three COVID-19 waves: excess mortality and social patterns in Belgium.

Background: This study aims to assess which population groups experienced the heaviest mortality burden during the first three COVID-19 waves in Belgium; and investigate potential changes in social differences in all-cause mortality during the epidemic and compared to the pre-COVID period.

Methods: Exhaustive all-cause mortality information (2015-2021) from the Belgian population register was linked to demographic and socioeconomic census and register data. Annual cohorts consisting of 6.

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.

Background: The 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.

Methods: Two complementary statistical methods were used.

Factors related to the return to work of head and neck cancer patients diagnosed between 2004-2011 in Belgium: a multivariate Fine-Gray regression model analysis.

Background: This study aims to identify the key factors that underlie the return to work (RTW) of head and neck cancer (HNC) patients in Belgium.

Methods: We used data from the EMPCAN database linking data from the Belgian Cancer Registry and the Crossroads Bank for Social Security. We selected HNC patients aged 18-60 at diagnosis who became inactive on the labour market during the follow-up time observed (n = 398).