Are we really all in this together? The social patterning of mortality during the first wave of the COVID-19 pandemic in Belgium

Gadeyne, Sylvie; Rodriguez-Loureiro, Lucía; Surkyn, Johan; Hemelrijck, Wanda Van; Nusselder, Wilma; Lusyne, Patrick; Vanthomme, Katrien

doi:10.1186/s12939-021-01594-0

Cited by 11 publications

(13 citation statements)

References 31 publications

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“…In the case of Stockholm, the risk of dying from Covid-19 was higher for elderly people living with adults in working age than for those living alone (Brandén et al, 2020). Furthermore, the risk of dying from Covid-19 was higher in men than in women at any age in most countries (Aburto et al, 2021;Ahrenfeldt et al, 2021), including Belgium (Gadeyne et al, 2021). In general, the gender gap increases until the 60-69 age bracket, then gradually decreases to become very small after the age of 80 (Ahrenfeldt et al, 2021).…”

Section: Individual Determinantsmentioning

confidence: 96%

Individual and spatial determinants of mortality during the Covid-19 pandemic: The case of Belgium in 2020

Bourguignon,

Bertrand,

Damiens

et al. 2023

Preprint

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Context. The year 2020 was marked by the Covid-19 pandemic. In Belgium, it led to a doubling in deaths, mainly grouped into two periods. This article aims to compare the relative importance of predictors and individual and spatial determinants of mortality during these two waves to an equivalent non-pandemic period and to identify whether and to what extent the pandemic has altered the sociodemographic patterns of conventional mortality. Methods. The analyses relate to all-cause mortality during the two waves of Covid-19 and their equivalent in 2019. They are based on matching individual and exhaustive data from the Belgian National Register with tax and population census data. A multi-level approach was adopted combining individual and spatial determinants. Results. Mortality patterns during the pandemic are very similar to those observed outside the pandemic. As in 2019, age, sex, and household composition significantly determine the individual risk of dying, with a higher risk of death among the oldest people, men, and residents of collective households. However, their risk of death increases during the Covid period, especially in the 65–79 age group. Spatial information is no more significant in 2020 than in 2019. However, a higher risk of death is observed when the local excess mortality index or the proportions of isolated or disadvantaged people increase. Conclusions. While the Covid pandemic did not fundamentally alter conventional mortality patterns, it did amplify some of the pre-existing differences in mortality.

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Section: Individual Determinantsmentioning

confidence: 96%

Individual and spatial determinants of mortality during the Covid-19 pandemic: The case of Belgium in 2020

Bourguignon,

Bertrand,

Damiens

et al. 2023

Preprint

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“…Furthermore, the risk of dying from Covid-19 was higher in men than in women at any age in most countries (Aburto et al, 2021; Ahrenfeldt et al, 2021), including Belgium (Gadeyne et al, 2021). In general, the gender gap increases until the 60–69 age bracket, then gradually decreases to become very small after the age of 80 (Ahrenfeldt et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Disadvantaged populations are characterised by more widespread risk behaviours (smoking, poor dietary habits), less understanding of and adherence to health and hygiene measures to combat the disease, and limited access to and/or use of good quality healthcare. (Gadeyne et al, 2021). Secondly, socially disadvantaged populations are more frequently found in densely populated neighbourhoods and densely occupied housing, which are additional factors of exposure to the risk of infection and, by extension, mortality (Bambra et al, 2020; Barhoumi et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Decoster et al (2021) showed the existence of a negative income gradient in terms of excess mortality among the elderly in Belgium in the first wave (Decoster et al, 2021). Conversely, Gadeyne et al (2021), using income and level of education as indicators of social inequality, identified the highest levels of excess mortality among the highest-income men aged 25–64 and among middle- and high-income men and women aged 65–84. Bourguignon et al (2022) found excess mortality among all social groups 2 based on an excess mortality index 3 calculated for the two Covid-19 waves in 2020.…”

Section: Introductionmentioning

confidence: 99%

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Individual and spatial determinants of mortality during the Covid-19 pandemic: The case of Belgium in 2020

Bourguignon,

Bertrand,

Damiens

et al. 2023

Preprint

View full text Add to dashboard Cite

Context. The year 2020 was marked by the Covid 19 pandemic. In Belgium, it led to a doubling in deaths, mainly grouped into two periods. This article aims to compare the relative importance of predictors and individual and spatial determinants of mortality during these two waves to an equivalent non-pandemic period and to identify whether and to what extent the pandemic has altered the sociodemographic patterns of conventional mortality. Methods. The analyses relate to all-cause mortality during the two waves of Covid-19 and their equivalent in 2019. They are based on matching individual and exhaustive data from the Belgian National Register with tax and population census data. A multi-level approach was adopted combining individual and spatial determinants. Results. Mortality patterns during the pandemic are very similar to those observed outside the pandemic. As in 2019, age, sex, and household composition significantly determine the individual risk of dying, with a higher risk of death among the oldest people, men, and residents of collective households. However, their risk of death increases during the Covid period, especially in the 65/79 age group. Spatial information is no more significant in 2020 than in 2019. However, a higher risk of death is observed when the local excess mortality index or the proportions of isolated or disadvantaged people increase. Conclusions. While the Covid pandemic did not fundamentally alter conventional mortality patterns, it did amplify some of the pre-existing differences in mortality.

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“…There is emerging evidence that COVID-19 has a socially patterned distribution, with higher risks for exposure, infection, severe illness and death among disadvantaged groups (eg, low-income groups, people with a migrant background) and certain occupations (eg, healthcare workers) 10–14. Currently, the available Belgian research on SE and SD differences builds on COVID-19 incidence on an aggregated level and on all-cause mortality during the first wave at the individual level 10 13 15 16. There has been no detailed investigation, to our knowledge, on SE and SD differences among hospitalised COVID-19 patients in Belgium.…”

Section: Introductionmentioning

confidence: 99%

Social inequalities and long-term health impact of COVID-19 in Belgium: protocol of the HELICON population data linkage

De Pauw,

Van den Borre,

Baeyens

et al. 2023

BMJ Open

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IntroductionData linkage systems have proven to be a powerful tool in support of combating and managing the COVID-19 pandemic. However, the interoperability and the reuse of different data sources may pose a number of technical, administrative and data security challenges.Methods and analysisThis protocol aims to provide a case study for linking highly sensitive individual-level information. We describe the data linkages between health surveillance records and administrative data sources necessary to investigate social health inequalities and the long-term health impact of COVID-19 in Belgium. Data at the national institute for public health, Statistics Belgium and InterMutualistic Agency are used to develop a representative case-cohort study of 1.2 million randomly selected Belgians and 4.5 million Belgians with a confirmed COVID-19 diagnosis (PCR or antigen test), of which 108 211 are COVID-19 hospitalised patients (PCR or antigen test). Yearly updates are scheduled over a period of 4 years. The data set covers inpandemic and postpandemic health information between July 2020 and January 2026, as well as sociodemographic characteristics, socioeconomic indicators, healthcare use and related costs. Two main research questions will be addressed. First, can we identify socioeconomic and sociodemographic risk factors in COVID-19 testing, infection, hospitalisations and mortality? Second, what is the medium-term and long-term health impact of COVID-19 infections and hospitalisations? More specific objectives are (2a) To compare healthcare expenditure during and after a COVID-19 infection or hospitalisation; (2b) To investigate long-term health complications or premature mortality after a COVID-19 infection or hospitalisation; and (2c) To validate the administrative COVID-19 reimbursement nomenclature. The analysis plan includes the calculation of absolute and relative risks using survival analysis methods.Ethics and disseminationThis study involves human participants and was approved by Ghent University hospital ethics committee: reference B.U.N. 1432020000371 and the Belgian Information Security Committee: reference Beraadslaging nr. 22/014 van 11 January 2022, available viahttps://www.ehealth.fgov.be/ehealthplatform/file/view/AX54CWc4Fbc33iE1rY5a?filename=22-014-n034-HELICON-project.pdf. Dissemination activities include peer-reviewed publications, a webinar series and a project website.The pseudonymised data are derived from administrative and health sources. Acquiring informed consent would require extra information on the subjects. The research team is prohibited from gaining additional knowledge on the study subjects by the Belgian Information Security Committee’s interpretation of the Belgian privacy framework.

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Are we really all in this together? The social patterning of mortality during the first wave of the COVID-19 pandemic in Belgium

Cited by 11 publications

References 31 publications

Individual and spatial determinants of mortality during the Covid-19 pandemic: The case of Belgium in 2020

Individual and spatial determinants of mortality during the Covid-19 pandemic: The case of Belgium in 2020

Individual and spatial determinants of mortality during the Covid-19 pandemic: The case of Belgium in 2020

Social inequalities and long-term health impact of COVID-19 in Belgium: protocol of the HELICON population data linkage

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