TY - JOUR T1 - COVID-19 mortality, excess mortality, deaths per million and infection fatality ratio, Belgium, 9 March 2020 to 28 June 2020 JF - Eurosurveillance Y1 - 2022 A1 - Geert Molenberghs A1 - Christel Faes A1 - Johan Verbeeck A1 - Patrick Deboosere A1 - Steven Abrams A1 - Lander Willem A1 - Jan Aerts A1 - Heidi Theeten A1 - Brecht Devleesschauwer A1 - Natalia Bustos Sierra A1 - Françoise Renard A1 - Sereina Herzog A1 - Patrick Lusyne A1 - Johan Van der Heyden A1 - Herman Van Oyen A1 - Pierre Van Damme A1 - Niel Hens KW - COVID-19 KW - Excess mortality KW - nursing homes AB -

Background

COVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution.

Aim

We examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups.

Methods

The relation between COVID-19-related mortality and excess mortality was evaluated by comparing COVID-19 mortality and the difference between observed and weekly average predictions of all-cause mortality. DPM were evaluated using demographic data of the Belgian population. The number of infections was estimated by a stochastic compartmental model. The IFR was estimated using a delay distribution between infection and death.

Results

In the study period, 9,621 COVID-19-related deaths were reported, which is close to the excess mortality estimated using weekly averages (8,985 deaths). This translates to 837 DPM and an IFR of 1.5% in the general population. Both DPM and IFR increase with age and are substantially larger in the nursing home population.

Discussion

During the first pandemic wave, Belgium had no discrepancy between COVID-19-related mortality and excess mortality. In light of this close agreement, it is useful to consider the DPM and IFR, which are both age, sex, and nursing home population-dependent. Comparison of COVID-19 mortality between countries should rather be based on excess mortality than on COVID-19-related mortality.

VL - 27 CP - 7 M3 - 10.2807/1560-7917.ES.2022.27.7.2002060 ER - TY - RPRT T1 - Health Status Report 2021- De gezondheidstoestand in België Y1 - 2022 A1 - Françoise Renard A1 - Aline Scohy A1 - Robby De Pauw A1 - Jure Jurcevic A1 - Brecht Devleesschauwer KW - Health monitoring KW - Health status PB - Sciensano CY - Brussel, België ER - TY - RPRT T1 - Health Status Report 2021 - L'état de santé en Belgique Y1 - 2022 A1 - Françoise Renard A1 - Aline Scohy A1 - Robby De Pauw A1 - Jure Jurcevic A1 - Brecht Devleesschauwer KW - Health monitoring KW - Health status PB - Sciensano CY - Bruxelles, Belgique ER - TY - RPRT T1 - Health Status Report 2021 - The state of health in Belgium Y1 - 2022 A1 - Françoise Renard A1 - Aline Scohy A1 - Robby De Pauw A1 - Jure Jurcevic A1 - Brecht Devleesschauwer KW - Health monitoring KW - Health status PB - Sciensano CY - Brussels ER - TY - JOUR T1 - Assessing polypharmacy in the older population: Comparison of a self‐reported and prescription based method JF - Pharmacoepidemiology and Drug Safety Y1 - 2021 A1 - Johan Van der Heyden A1 - Finaba Berete A1 - Françoise Renard A1 - Johan Vanoverloop A1 - Brecht Devleesschauwer A1 - Karin De Ridder A1 - Olivier Bruyère KW - Polypharmacy AB -

Purpose

To explore differences in the prevalence and determinants of polypharmacy in the older general population in Belgium between self-reported and prescription based estimates and assess the relative merits of each data source.

Methods

Data were used from participants aged ≥65 years of the Belgian national health survey 2013 (n = 1950). Detailed information was asked on the use of medicines in the past 24 h and linked with prescription data from the Belgian compulsory health insurance (BCHI). Agreement between polypharmacy (use or prescription ≥5 medicines) and excessive polypharmacy (≥10 medicines) between both sources was assessed with kappa statistics. Multinomial logistic regression was used to study determinants of moderate (5–9 medicines) and excessive polypharmacy (≥10 medicines) and over- and underestimation of prescription based compared to self-reported polypharmacy.

Results

Self-reported and prescription based polypharmacy prevalence estimates were respectively 27% and 32%. Overall agreement was moderate, but better in men (kappa 0.60) than in women (0.45). Determinants of moderate polypharmacy did not vary substantially by source of outcome indicator, but restrictions in activities of daily living (ADL), living in an institution and a history of a hospital admission was associated with self-reported based excessive polypharmacy only.

Conclusions

Surveys and prescription data measure polypharmacy from a different perspective, but overall conclusions in terms of prevalence and determinants of polypharmacy do not differ substantially by data source. Linking survey data with prescription data can combine the strengths of both data sources resulting in a better tool to explore polypharmacy at population level.

VL - 30 CP - 12 M3 - 10.1002/pds.5321 ER - TY - Generic T1 - Association between polypharmacy and mortality in the community-dwelling older population: a data linkage study Y1 - 2021 A1 - Johan Van der Heyden A1 - Finaba Berete A1 - Brecht Devleesschauwer A1 - Karin De Ridder A1 - Bruyère, Olivier A1 - Françoise Renard A1 - Rana Charafeddine JF - International Journal of Epidemiology VL - 50 CP - Supplement_1 M3 - 10.1093/ije/dyab168.675 ER - TY - RPRT T1 - Atlas of cause-specific all ages mortality by district in Belgium, 2003-2009. Y1 - 2021 A1 - Aline Scohy A1 - Françoise Renard A1 - Jure Jurcevic PB - Sciensano CY - Brussels ER - TY - RPRT T1 - Atlas of cause-specific all-ages mortality by district in Belgium, 2010- 2017 Y1 - 2021 A1 - Aline Scohy A1 - Françoise Renard A1 - Jure Jurcevic PB - Sciensano CY - Brussels ER - TY - RPRT T1 - Atlas of cause-specific premature mortality (0-74) by districts in Belgium, 2003-2009 Y1 - 2021 A1 - Aline Scohy A1 - Françoise Renard A1 - Jure Jurcevic ER - TY - RPRT T1 - Atlas of cause-specific premature mortality (0-74) by districts in Belgium, 2010-2017 Y1 - 2021 A1 - Aline Scohy A1 - Françoise Renard A1 - Jure Jurcevic PB - Sciensano CY - Brussels ER - TY - JOUR T1 - Establishing an ad hoc COVID-19 mortality surveillance during the first epidemic wave in Belgium, 1 March to 21 June 2020 JF - Eurosurveillance Y1 - 2021 A1 - Françoise Renard A1 - Aline Scohy A1 - Johan Van der Heyden A1 - Ilse Peeters A1 - Sara Dequeker A1 - Eline Vandael A1 - Nina Van Goethem A1 - Dominique Dubourg A1 - Louise De Viron A1 - Anne Kongs A1 - Naïma Hammami A1 - Brecht Devleesschauwer A1 - André Sasse A1 - Javiera Rebolledo A1 - Natalia Bustos Sierra AB -

Background : COVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality.

Aim : To document and assess the COVID-19 mortality surveillance in Belgium.

Methods : We described the content and data flows of the registration and we assessed the situation as of 21 June 2020, 103 days after the first death attributable to COVID-19 in Belgium. We calculated the participation rate, the notification delay, the percentage of error detected, and the results of additional investigations.

Results : The participation rate was 100% for hospitals and 83% for nursing homes. Of all deaths, 85% were recorded within 2 calendar days: 11% within the same day, 41% after 1 day and 33% after 2 days, with a quicker notification in hospitals than in LTCF. Corrections of detected errors reduced the death toll by 5%.

Conclusion : Belgium implemented a rather complete surveillance of COVID-19 mortality, on account of a rapid investment of the hospitals and LTCF. LTCF could build on past experience of previous surveys and surveillance activities. The adoption of an extended definition of ‘COVID-19-related deaths’ in a context of limited testing capacity has provided timely information about the severity of the epidemic.

VL - 26 CP - 48 M3 - 10.2807/1560-7917.ES.2021.26.48.2001402 ER - TY - RPRT T1 - Protocol COVID-19 Surveillance in residential institutions - version 5.2 Y1 - 2021 A1 - Sara Dequeker A1 - Katrien Latour A1 - Esma Islamaj A1 - Laura Int Panis A1 - Milena Callies A1 - Lucy Catteau A1 - Boudewijn Catry A1 - Natalia Bustos Sierra A1 - Françoise Renard A1 - Eline Vandael PB - Sciensano CY - Brussels, Belgium ER - TY - RPRT T1 - Protocol COVID-19 surveillance in residentiële instellingen - versie 5.2 Y1 - 2021 A1 - Sara Dequeker A1 - Katrien Latour A1 - Esma Islamaj A1 - Laura Int Panis A1 - Milena Callies A1 - Lucy Catteau A1 - Boudewijn Catry A1 - Natalia Bustos Sierra A1 - Françoise Renard A1 - Eline Vandael ER - TY - RPRT T1 - Protocole surveillance COVID-19 dans les institutions résidentiels - version 5.2 Y1 - 2021 A1 - Sara Dequeker A1 - Katrien Latour A1 - Esma Islamaj A1 - Laura Int Panis A1 - Milena Callies A1 - Lucy Catteau A1 - Boudewijn Catry A1 - Natalia Bustos Sierra A1 - Françoise Renard A1 - Eline Vandael ER - TY - RPRT T1 - Surveillance de la mortalité COVID-19 en Belgique, épidémiologie et méthodologie durant la 1re et 2e vague (mars 2020 - 14 février 2021) Y1 - 2021 A1 - Ilse Peeters A1 - Melissa Vermeulen A1 - Natalia Bustos Sierra A1 - Françoise Renard A1 - Johan Van der Heyden A1 - Aline Scohy A1 - Toon Braeye A1 - Nathalie Bossuyt A1 - Freek Haarhuis A1 - Kristiaan Proesmans A1 - Catharina Vernemmen A1 - Maarten Vanhaverbeke KW - Be-MOMO KW - Coronavirus KW - COVID-19 mortality KW - Surveillance AB -

Ce rapport fournit une analyse épidémiologique des caractéristiques des décès COVID-19 durant la première vague (1er mars 2020 – 21 juin 2020), l’entre-deux vagues (22 juin 2020 – 30 août 2020) et la seconde vague (31 août 2020 – 14 février 2021) de l’épidémie de COVID-19 en Belgique. Il s'agit de la période précédant l'évaluation des effets de la campagne de vaccination nationale qui a débuté au début de l'année 2021. Au total, 21 860 décès COVID-19 se sont produits (43,9 % durant la première vague et 54,7 % durant la seconde). La distribution par sexe est assez équilibrée (49,1 % d’hommes et 50,8 % de femmes). Presque toutes le personnes décédées avaient plus de 64 ans et environ la moitié avaient plus de 84 ans. Les données provenant de patients hospitalisés pour COVID-19 montrent que l’âge, le sexe masculin, et plusieurs comorbidités telles que les maladies cardio-vasculaires et le diabète sont des facteurs de risque de décès. De plus, l’estimation de la létalité COVID-19 en Belgique confirme qu’elle est plus importante pour la population âgée et de sexe masculin.
Au cours de la deuxième vague, plus de décès se sont produits en hôpital (61 %) que dans les maisons de repos et les maisons de repos et de soins (MR/MRS) (38 %). Lors de la
première vague, les proportions étaient quasiment identiques (50 % en hôpital et 49 % en MR/MRS). La capacité des tests a augmenté et son champ s’est élargi au cours du temps, conduisant à une augmentation de la proportion des décès COVID-19 confirmés par test moléculaire (69 % au cours de la première vague et 95 % au cours de la seconde). Les taux de mortalité COVID-19 standardisés pour l’âge (age-standardized mortality rate, ou ASMR) qui tiennent compte de la répartition par âge de la population, montrent que Bruxelles présente l’ASMR le plus élevé pour la période entière et pour la première vague, tandis que la Wallonie présente le taux le plus élevé pour la deuxième vague (provinces de Hainaut et de Liège en tête). Les taux bruts de mortalité COVID-19 pour les résidents des maisons de repos étaient plus élevés en Flandre que dans les autres régions, tant pour la période totale que pour la deuxième vague. 

Le système de surveillance de la mortalité COVID-19 a été mis sur pied au début de l’épidémie pour collecter des données de mortalité COVID-19 à une fréquence journalière.
Ce système a combiné les informations au sujet des décès COVID-19 provenant de trois types de surveillance (surveillance hospitalière, surveillance MR/MRS et notifications aux
inspecteurs de santé des autorités régionales) à travers neuf sources de données. Ces informations incluent la date du décès, la date de naissance, le sexe, la classification de
cas, les types de lieu de décès et de lieu de résidence (par exemple vivre en MR/MRS), le code postal du lieu de décès et du lieu de résidence. Des améliorations continues de la
collecte de données ont conduit à des mises à jour rétrospectives du nombre de décès.  

Les comparaisons internationales et le classement des taux de mortalité COVID-19 sont trompeurs en raison de la grande hétérogénéité des méthodes utilisées (définition de cas, stratégie de tests et de dépistage, méthode de notification, disponibilité d’une surveillance spécifique pour les MR/MRS…). Ces méthodes ont également pu évoluer au cours de l’épidémie au sein d’un même pays. Une meilleure comparaison devrait être possible quand les différents pays auront terminé d’analyser les certificats de décès officiels. La mise sur pied rapide de la surveillance COVID-19 en MR/MRS et l’inclusion des décès de cas possibles de COVID-19 ont néanmoins permis de fournir des données précises sur les décès COVID-19. Cela a permis d’évaluer la gravité de la situation épidémiologique en MR/MRS. La mortalité COVID-19 s’est révélée fortement corrélée avec la surmortalité toutes causes confondues en Belgique. La surmortalité a été un indicateur clé dans l’épidémie de COVID-19 pour valider le fait que la déclaration épidémiologique de la mortalité liée à la COVID-19 a été correctement effectuée durant l’épidémie.

PB - Sciensano CY - Belgium ER - TY - RPRT T1 - Surveillance of COVID-19 mortality in Belgium, epidemiology and methodology during 1st and 2nd wave (March 2020 - 14 February 2021) Y1 - 2021 A1 - Ilse Peeters A1 - Melissa Vermeulen A1 - Natalia Bustos Sierra A1 - Françoise Renard A1 - Johan Van der Heyden A1 - Aline Scohy A1 - Toon Braeye A1 - Nathalie Bossuyt A1 - Freek Haarhuis A1 - Kristiaan Proesmans A1 - Catharina Vernemmen A1 - Maarten Vanhaverbeke KW - Be-MOMO KW - Coronavirus KW - COVID-19 mortality KW - Surveillance AB -

This report provides epidemiological figures about the characteristics of COVID-19 deaths during the first wave (1 March 2020 until 21 June 2020), the inter wave period (22 June until 30 August 2020) and the second wave (31 August 2020 until 14 February 2021) of the COVID-19 epidemic in Belgium. This is the period before the effects of the nationwide vaccination campaign that started early in 2021 could be assessed. In total 21,860 COVID-19 deaths occurred (43.9% in the first wave and 54.7% in the second wave). The COVID-19 mortality surveillance system was implemented at the start of the epidemic to acquire real-time COVID-19 mortality data on a daily basis. The surveillance combined information on COVID-19 related deaths from three surveillances (the hospital surveillance, the nursing home (NH) surveillance and notifications to regional health inspection authorities) through nine data sources. This information included the date of death, date of birth, sex, case classification, type of place of death, type of place of residence (e.g. living in a NH), postal code of the place of death and residence. Continuous improvements as regards the data collection resulted in retrograde adaptations of mortality numbers.

The overall sex distribution was fairly even (49.1% in male and 50.8% in female). Almost all deaths occurred in the age group over 64 years and approximately half of the deaths occurred in the age group over 84 years. Data on hospitalized COVID-19 patients showed that higher age, male sex and several comorbidities such as cardiovascular disease and diabetes were risk factors for mortality. Additionally, the estimated COVID-19 case fatality in Belgium confirmed that it was higher for the elderly and male population. In the second wave, more deaths occurred in hospitals (61%) than in nursing homes for elderly (NHs) (38%). In contrast, during the first wave, this distribution was more equal (50% in hospitals and 49% in NHs). The test capacity increased and the testing strategy broadened over time, leading to an increase in the proportion of laboratory-confirmed COVID-19 cases among deaths (69% and 95% in the first and second waves respectively). COVID-19 age-standardized mortality rates (ASMR), which take into account the age distribution of the population, showed that Brussels presented the highest ASMR for the total period and the first wave, while Wallonia has the highest ASMR for the second wave (more precisely in the provinces of Hainaut and Liège). The crude COVID-19 mortality rates for residents of NHs were higher in Flanders than in the other regions, both for the total period and for the second wave.

International comparison and ranking of COVID-19 crude mortality rates are misleading because of very heterogeneous methods used (e.g. case definition, testing and screening strategy, reporting method, availability of specific surveillance in NHs, etc.). Methods might also have changed during the course of the epidemic within the same country. A better comparison will probably be possible when countries have finished analyzing the official death certificates. The fast initiation of the COVID-19 surveillance in NHs and the inclusion of deaths of possible COVID-19 cases nevertheless allowed Belgium to provide accurate figures on COVID-19 deaths. This helped to assess the seriousness of the epidemiological situation in NHs. COVID-19 mortality was strongly correlated with excess all-cause mortality in Belgium. The excess mortality was a key indicator in the COVID-19 epidemic to validate that the epidemiological reporting of COVID-19-related mortality was correctly conducted during the epidemic

PB - Sciensano CY - Belgium ER - TY - RPRT T1 - Surveillance van COVID-19 gerelateerde mortaliteit in België, epidemiologie en methodologie tijdens 1e en 2e golf (maart 2020 - 14 februari 2021) Y1 - 2021 A1 - Ilse Peeters A1 - Melissa Vermeulen A1 - Natalia Bustos Sierra A1 - Françoise Renard A1 - Johan Van der Heyden A1 - Aline Scohy A1 - Toon Braeye A1 - Nathalie Bossuyt A1 - Freek Haarhuis A1 - Kristiaan Proesmans A1 - Catharina Vernemmen A1 - Maarten Vanhaverbeke KW - Be-MOMO KW - Coronavirus KW - COVID-19 mortality KW - Surveillance AB -

Dit rapport geeft epidemiologische cijfers over de kenmerken van COVID-19-sterfgevallen tijdens de eerste golf (1 maart 2020 tot 21 juni 2020), de intergolf (22 juni tot 30 augustus 2020) en de tweede golf (31 augustus 2020 tot 14 februari 2021) van de COVID-19- epidemie in België. Dit is de periode voordat de effecten van de landelijke vaccinatiecampagne, die begin 2021 van start is gegaan, konden worden beoordeeld. In totaal vielen er tijdens deze periode 21 860 COVID-19 sterfgevallen (43,9% in de eerste golf en 54,7% in de tweede golf).

Het COVID-19 mortaliteitssurveillancesysteem werd aan het begin van de epidemie ingevoerd om dagelijks COVID-19-sterftegegevens te verzamelen. De surveillance combineerde informatie over COVID-19-gerelateerde sterfgevallen uit drie surveillances (de ziekenhuissurveillance, de woonzorgcentra-surveillance en meldingen aan de regionale instanties van gezondheidsinspectie) via negen gegevensbronnen. Deze informatie omvatte de datum van overlijden, de geboortedatum, het geslacht, de gevalsclassificatie, het type plaats van overlijden, het type woonplaats (bv. woonachtig in een woonzorgcentrum), de postcode van de plaats van overlijden en van de woonplaats. Voortdurende verbeteringen met betrekking tot de gegevensverzameling leidden tot retrograde aanpassingen van de sterftecijfers. De verdeling over de geslachten was gelijkmatig (49,1% bij mannen en 50,8% bij vrouwen). Bijna alle overleden personen waren ouder dan 64 jaar en ongeveer de helft was ouder dan 84 jaar.

Uit gegevens over gehospitaliseerde COVID-19-patiënten bleek dat een hogere leeftijd, mannelijk geslacht en verschillende comorbiditeiten zoals hart- en vaatziekten en diabetes risicofactoren voor sterfte waren. Bovendien bevestigde de schatting van de “case fatality ratio” van COVID-19 in België dat de letaliteit hoger was in de oudere populatie en mannen. In de tweede golf waren er meer sterfgevallen in ziekenhuizen (61%) dan in woonzorgcentra voor ouderen (38%). Tijdens de eerste golf was deze verdeling daarentegen gelijkmatiger (50% in ziekenhuizen en 49% in woonzorgcentra). In de loop van de tijd nam de testcapaciteit toe en verbreedde de teststrategie, wat leidde tot een toename van het aandeel van de labo bevestigde COVID-19-gevallen onder de sterfgevallen (69% en 95% in respectievelijk de eerste en tweede golf).

De COVID-19-sterftecijfers na directe leeftijdsstandaardisatie (age-standardized mortality rate, ASMR), die rekening houden met de leeftijdsverdeling van de bevolking, toonden aan dat Brussel de hoogste ASMR vertoonde voor de totale periode en de eerste golf, en Wallonië voor de tweede golf (meer bepaald in de provincies Henegouwen en Luik). De ruwe COVID-19-sterftecijfers voor bewoners van woonzorgcentra lagen zowel voor de totale periode als voor de tweede golf dan weer hoger in Vlaanderen dan in de andere regio’s. 5 Een internationale vergelijking en rangschikking van de ruwe COVID-19-sterftecijfers is misleidend vanwege de zeer uiteenlopende methoden die worden gebruikt (bv. gevalsdefinitie, test- en screeningstrategie, rapportagemethode, beschikbaarheid van specifieke surveillance in woonzorgcentra, enz.). De methoden gebruikt binnen éénzelfde land kunnen ook veranderd zijn in de loop van de epidemie. Een betere vergelijking zal waarschijnlijk mogelijk zijn wanneer de landen klaar zijn met de analyse van de officiële overlijdensakten.

Niettemin stelden de snelle start van de COVID-19-surveillance in woonzorgcentra en het includeren van sterfgevallen bij mogelijke COVID-19-gevallen België in staat nauwkeurige cijfers te verstrekken over de COVID-19-sterfte. Dit hielp om de ernst van de epidemiologische situatie in woonzorgcentra te kunnen inschatten. De gerapporteerde COVID-19-sterfte kwam sterk overeen met de oversterfte ten gevolge van alle oorzaken in België. Deze oversterfte was een belangrijke indicator in de COVID-19- epidemie om te valideren dat de epidemiologische rapportage van COVID-19-gerelateerde sterfte correct gebeurde tijdens de epidemie.

PB - Sciensano CY - Belgium ER - TY - JOUR T1 - All-cause mortality supports the COVID-19 mortality in Belgium and comparison with major fatal events of the last century. JF - Arch Public Health Y1 - 2020 A1 - Natalia Bustos Sierra A1 - Nathalie Bossuyt A1 - Toon Braeye A1 - Mathias Leroy A1 - Isabelle Moyersoen A1 - Ilse Peeters A1 - Aline Scohy A1 - Johan Van der Heyden A1 - Herman Van Oyen A1 - Françoise Renard KW - COVID-19 mortality KW - Excess mortality KW - Surveillance AB -

BACKGROUND: The COVID-19 mortality rate in Belgium has been ranked among the highest in the world. To assess the appropriateness of the country's COVID-19 mortality surveillance, that includes long-term care facilities deaths and deaths in possible cases, the number of COVID-19 deaths was compared with the number of deaths from all-cause mortality. Mortality during the COVID-19 pandemic was also compared with historical mortality rates from the last century including those of the Spanish influenza pandemic.

METHODS: Excess mortality predictions and COVID-19 mortality data were analysed for the period March 10th to June 21st 2020. The number of COVID-19 deaths and the COVID-19 mortality rate per million were calculated for hospitals, nursing homes and other places of death, according to diagnostic status (confirmed/possible infection). To evaluate historical mortality, monthly mortality rates were calculated from January 1900 to June 2020.

RESULTS: Nine thousand five hundred ninety-one COVID-19 deaths and 39,076 deaths from all-causes were recorded, with a correlation of 94% (Spearman's rho, p < 0,01). During the period with statistically significant excess mortality (March 20th to April 28th; total excess mortality 64.7%), 7917 excess deaths were observed among the 20,159 deaths from all-causes. In the same period, 7576 COVID-19 deaths were notified, indicating that 96% of the excess mortality were likely attributable to COVID-19. The inclusion of deaths in nursing homes doubled the COVID-19 mortality rate, while adding deaths in possible cases increased it by 27%. Deaths in laboratory-confirmed cases accounted for 69% of total COVID-19-related deaths and 43% of in-hospital deaths. Although the number of deaths was historically high, the monthly mortality rate was lower in April 2020 compared to the major fatal events of the last century.

CONCLUSIONS: Trends in all-cause mortality during the first wave of the epidemic was a key indicator to validate the Belgium's high COVID-19 mortality figures. A COVID-19 mortality surveillance limited to deaths from hospitalised and selected laboratory-confirmed cases would have underestimated the magnitude of the epidemic. Excess mortality, daily and monthly number of deaths in Belgium were historically high classifying undeniably the first wave of the COVID-19 epidemic as a fatal event.

VL - 78 CP - 1 M3 - 10.1186/s13690-020-00496-x ER - TY - JOUR T1 - Changes in life expectancy and contribution of causes of deaths and age groups in Belgium, 1997-2018 JF - European Journal of Public Health Y1 - 2020 A1 - Aline Scohy A1 - Herman Van Oyen A1 - Françoise Renard VL - 30 CP - Supplement_5 M3 - 10.1093/eurpub/ckaa165.189 ER - TY - RPRT T1 - Enquête de santé 2018 : Services à domicile et d'aide à domicile Y1 - 2020 A1 - Sabine Drieskens A1 - Françoise Renard A1 - Finaba Berete ER - TY - RPRT T1 - Enquête de santé 2018 : Utilisation des services de santé. Résumé des résultats Y1 - 2020 A1 - Finaba Berete A1 - Sabine Drieskens A1 - Johan Van der Heyden A1 - Stefaan Demarest A1 - Rana Charafeddine A1 - Lydia Gisle A1 - Françoise Renard A1 - Aline Scohy A1 - Lize Hermans A1 - Elise Braekman ER - TY - RPRT T1 - Gezondheidsenquête 2018: Gebruik van diensten voor thuiszorg Y1 - 2020 A1 - Sabine Drieskens A1 - Françoise Renard A1 - Finaba Berete ER - TY - RPRT T1 - Gezondheidsenquête 2018: Gebruik van gezondheidsdiensten. Samenvatting van de resultaten Y1 - 2020 A1 - Sabine Drieskens A1 - Finaba Berete A1 - Johan Van der Heyden A1 - Stefaan Demarest A1 - Rana Charafeddine A1 - Lydia Gisle A1 - Françoise Renard A1 - Aline Scohy A1 - Lize Hermans A1 - Elise Braekman ER - TY - JOUR T1 - High impact of COVID-19 in long-term care facilities, suggestion for monitoring in the EU/EEA, May 2020. JF - Euro Surveill Y1 - 2020 A1 - Kostas Danis A1 - Laure Fonteneau A1 - Georges, Scarlett A1 - Daniau, Côme A1 - Sybille Bernard-Stoecklin A1 - Domegan, Lisa A1 - O'Donnell, Joan A1 - Siri Helene Hauge A1 - Sara Dequeker A1 - Eline Vandael A1 - Johan Van der Heyden A1 - Françoise Renard A1 - Natalia Bustos Sierra A1 - Enrico Ricchizzi A1 - Birgitta Schweickert A1 - Nicole Schmidt A1 - Muna Abu Sin A1 - Tim Eckmanns A1 - José-Artur Paiva A1 - Elke Schneider KW - Aged KW - Aged, 80 and over KW - Betacoronavirus KW - Coronavirus KW - Coronavirus Infections KW - COVID-19 KW - Disease Outbreaks KW - Europe KW - Female KW - Humans KW - long-term care KW - Male KW - nursing homes KW - Pandemics KW - Pneumonia, Viral KW - SARS-CoV-2 KW - Vulnerable Populations AB -

Residents in long-term care facilities (LTCF) are a vulnerable population group. Coronavirus disease (COVID-19)-related deaths in LTCF residents represent 30-60% of all COVID-19 deaths in many European countries. This situation demands that countries implement local and national testing, infection prevention and control, and monitoring programmes for COVID-19 in LTCF in order to identify clusters early, decrease the spread within and between facilities and reduce the size and severity of outbreaks.

VL - 25 CP - 22 M3 - 10.2807/1560-7917.ES.2020.25.22.2000956 ER - TY - JOUR T1 - Validity of self-reported mammography uptake in the Belgian health interview survey: selection and reporting bias. JF - Eur J Public Health Y1 - 2020 A1 - Finaba Berete A1 - Johan Van der Heyden A1 - Stefaan Demarest A1 - Rana Charafeddine A1 - Jean Tafforeau A1 - Herman Van Oyen A1 - Bruyère, Olivier A1 - Françoise Renard KW - MAMMOGRAPHY KW - Reimbursement Mechanisms KW - Self-reported AB -

BACKGROUND: The validity of self-reported mammography uptake is often questioned. We assessed the related selection and reporting biases among women aged 50-69 years in the Belgian Health Interview Survey (BHIS) using reimbursement data for mammography stemming from the Belgian Compulsory Health Insurance organizations (BCHI).

METHODS: Individual BHIS 2013 data (n = 1040) were linked to BCHI data 2010-13 (BHIS-BCHI sample). Being reimbursed for mammography within the last 2-years was used as the gold standard. Selection bias was assessed by comparing BHIS estimates reimbursement rates in BHIS-BCHI with similar estimates from the Echantillon Permanent/Permanente Steekproef (EPS), a random sample of BCHI data, while reporting bias was investigated by comparing self-reported versus reimbursement information in the BHIS-BCHI. Reporting bias was further explored through measures of agreement and logistic regression.

RESULTS: Mammography uptake rates based on self-reported information and reimbursement from the BHIS-BCHI were 75.5% and 69.8%, respectively. In the EPS, it was 64.1%. The validity is significantly affected by both selection bias {relative size = 8.93% [95% confidence interval (CI): 3.21-14.64]} and reporting bias [relative size = 8.22% (95% CI: 0.76-15.68)]. Sensitivity was excellent (93.7%), while the specificity was fair (66.4%). The agreement was moderate (kappa = 0.63). Women born in non-EU countries (OR = 2.81, 95% CI: 1.54-5.13), with high household income (OR = 1.27, 95% CI: 1.02-1.60) and those reporting poor perceived health (OR = 1.41, 95% CI: 1.14-1.73) were more likely to inaccurately report their mammography uptake.

CONCLUSIONS: The validity of self-reported mammography uptake in women aged 50-69 years is affected by both selection and reporting bias. Both administrative and survey data are complementary when assessing mammography uptake.

M3 - 10.1093/eurpub/ckaa217 ER - TY - RPRT T1 - Belgian Health Examination Survey 2018 Y1 - 2019 A1 - Johan Van der Heyden A1 - Diem Nguyen A1 - Françoise Renard A1 - Aline Scohy A1 - Stefaan Demarest A1 - Sabine Drieskens A1 - Lydia Gisle ER - TY - RPRT T1 - Belgisch gezondheidsonderzoek 2018 Y1 - 2019 A1 - Johan Van der Heyden A1 - Diem Nguyen A1 - Françoise Renard A1 - Aline Scohy A1 - Stefaan Demarest A1 - Sabine Drieskens A1 - Lydia Gisle ER - TY - JOUR T1 - Contribution of chronic conditions to gender disparities in health expectancies in Belgium, 2001, 2004 and 2008 JF - European Journal of Public Health Y1 - 2019 A1 - Renata T C Yokota A1 - Nusselder, Willma J A1 - Robine, Jean-Marie A1 - Jean Tafforeau A1 - Françoise Renard A1 - Deboosere, Patrick A1 - Herman Van Oyen KW - chronic diseases KW - DISABILITY KW - Gender KW - HEALTH EXPECTANCY KW - inequality KW - trend AB -

Background: We aimed to investigate the contribution of chronic conditions to gender differences in disability- free life expectancy (DFLE) and life expectancy with disability (LED) in Belgium in 2001, 2004 and 2008.

Methods: Data on disability and chronic conditions from participants of the 2001, 2004 and 2008 Health Interview Surveys in Belgium were used to estimate disability prevalence by cause using the attribution method. Disability prevalence was applied to life tables to estimate DFLE and LED using the Sullivan method. Decomposition techniques were used to assess the contribution of mortality and disability and further of causes of death and disability to gender disparities in DFLE and LED.

Results: Higher LE, DFLE and LED were observed for women compared with men in all years studied. A decrease in the gender gap in LE (2001: 5.9; 2004: 5.6; 2008: 5.3) was observed in our cross- sectional approach followed by a decrease in gender differences in DFLE (2001: 1.9; 2004: 1.3; 2008: 0.5) and increase in LED (2001: 4.0; 2004: 4.4; 2008: 4.8). The higher LED in women was attributed to their lower mortality due to lung/larynx/trachea cancer, ischaemic heart diseases, and external causes (2001 and 2004) and higher disability prevalence due to musculoskeletal conditions (2008). Higher DFLE was observed in women owing to their lower mortality from lung/larynx/trachea cancer, ischaemic heart diseases, digestive cancer and chronic re- spiratory diseases.

Conclusion: To promote healthy ageing of populations, priority should be given to reduce the LED disadvantage in women by targeting non-fatal diseases, such as musculoskeletal conditions.

VL - 29 CP - 1 M3 - 10.1093/eurpub/cky105 ER - TY - JOUR T1 - Evolution of educational inequalities in life and health expectancies at 25 years in Belgium between 2001 and 2011: a census-based study JF - Arch Public Health Y1 - 2019 A1 - Françoise Renard A1 - Brecht Devleesschauwer A1 - Herman Van Oyen A1 - Sylvie Gadeyne A1 - Patrick Deboosere KW - Belgium KW - Disability-free life expectancy KW - HEALTH EXPECTANCY KW - Health inequality KW - Life expectancy KW - socio-economic inequality KW - trends AB -

Background: Reducing socio-economic health inequalities is a public health priority, necessitating careful monitoring that should take into account changes in the population composition. We analyzed the evolution of educational inequalities in life expectancy and disability-free life expectancy at age 25 (LE and DFLE) in Belgium between 2001 and 2011.

Methods: The 2001 and 2011 census data were linked with the national register data for a five-year mortality follow up. Disability prevalence estimates from the health interview surveys (2001 to 2013) were used to compute DFLE according to Sullivan's method. LE and DFLE were computed by educational level (EL). Absolute differentials of LE and DFLE were calculated for each EL and for each period, as well as composite inequality indices (CII) of population-level impact of inequality. Changes over the 10-year period were then calculated for each inequality index.

Results: The LE increased in all ELs and both genders, except in the lowest EL for women. The increase was larger in the highest EL, leading in 2011 to 6.07 and 4.58 years for the low-versus-high LE gaps respectively in men and women, compared to 5.19 and 3.76 in 2001, namely 17 and 22% increases. The upwards shift of the EL distribution led to a limited 7% increase of the CII among men but no change in women.The substantial increase of the DFLE in males with high EL (+ 4.5 years) and the decrease of the DFLE in women with low EL, results in a substantial increase of all considered DFLE inequality measures in both genders. In 2011, DFLE gaps were respectively 10.4 and 13.5 years in males and females compared to 6.51 and 9.30 in 2001, representing increases of 61 and 44% for the gaps, and 72 and 20% for the CII.

Conclusion: The LE increased in all ELs, but at a higher pace in highly educated, leading to an increase in the LE gaps in both genders. After accounting for the upwards shift of the educational distribution, the population-level inequality index increased only for men. The DFLE increased only in highly educated men, and decreased in low educated women, leading to large increases of inequalities in both genders. A general plan to tackle health inequality should be set up, with particular efforts to improve the health of the low educated women.

VL - 77 M3 - 10.1186/s13690-019-0330-8 ER - TY - RPRT T1 - Health Status Report 2019: De gezondheidstoestand in België Y1 - 2019 A1 - Françoise Renard A1 - Brecht Devleesschauwer KW - DETERMINANTS KW - Health status KW - inequalities KW - Population health monitoring PB - Sciensano CY - Brussels, Belgium VL - 1 UR - https://www.gezondbelgie.be ER - TY - RPRT T1 - Health Status Report 2019: L’état de santé en Belgique Y1 - 2019 A1 - Françoise Renard A1 - Brecht Devleesschauwer KW - DETERMINANTS KW - Health status KW - inequalities KW - Population health monitoring PB - Sciensano CY - Brussels, Belgium VL - 1 UR - https://www.belgiqueenbonnesante.be ER - TY - JOUR T1 - Monitoring health inequalities when the socio-economic composition changes: are the slope and relative indices of inequality appropriate? Results of a simulation study JF - BMC Public Health Y1 - 2019 A1 - Françoise Renard A1 - Brecht Devleesschauwer A1 - Speybroeck, Niko A1 - Deboosere, Patrick KW - Health inequality KW - Inequality indices KW - Monitoring KW - Relative index of inequality AB -

BACKGROUND: The slope (SII) and relative (RII) indices of inequality are commonly recommended to monitor health inequality policies. As an upwards shift of the educational level distribution (ELD) can be part of those policies, we examine how such a shift affects the SII, the RII and the population attributable fraction (PAF).

METHODS: We simulated 632 distributions of 4 educational levels (ELs) by varying the share (p1 to p4) of each EL, with constant mortality rates (MR) and calculated the corresponding RII, SII and PAF. Second, we decomposed the effect on the three indices of a change affecting both the ELD and the MRs, into the contributions of each component.

RESULTS: RIIs and SIIs sharply increase with p4 at fixed p1 values and evolve as reversed U-curves for p1 changing in complement to p4. The RII reaches a maximum, at much higher p4 values than the SII. PAFs monotonically decrease when p4 increases.

CONCLUSION: If improving the educational attainment is part of a policy, an upwards shift of EL should be assessed as a progress; however the RII, and to a lesser extent the SII, frequently translate an increased EL4 share as a worsening. We warn against the use of SII and RII for monitoring inequality-tackling policies at changing socio-economic structures. Rather, we recommend to complement the assessment of changes in absolute and relative pairwise differentials, with changes in PAF and in the socio-economic group shares.

VL - 19 CP - 1 M3 - 10.1186/s12889-019-6980-1 ER - TY - Generic T1 - Monitoring of non-communicable diseases in Belgium Y1 - 2019 A1 - Brecht Devleesschauwer A1 - L A Abboud A1 - Petronille Bogaert A1 - A Cornez A1 - L Raes A1 - Aline Scohy A1 - Johan Van der Heyden A1 - Françoise Renard JF - European Journal of Public Health VL - 29 CP - Supplement_4 M3 - 10.1093/eurpub/ckz185.120 ER - TY - JOUR T1 - An online health status report to support public health in Belgium JF - European Journal of Public Health Y1 - 2019 A1 - Aline Scohy A1 - Brecht Devleesschauwer A1 - Françoise Renard VL - 29 CP - Supplement_4 M3 - 10.1093/eurpub/ckz186.608 ER - TY - Generic T1 - Assessing polypharmacy in the general older population: comparison of findings from a health survey and health insurance data Y1 - 2018 A1 - Johan Van der Heyden A1 - Françoise Renard A1 - Finaba Berete A1 - Jean Tafforeau A1 - Brecht Devleesschauwer KW - chronic conditions KW - health survey KW - medicine use KW - Polypharmacy JF - European Congress of Epidemiology CY - Lyon, France ER - TY - Generic T1 - Assessing the validity of self reported breast cancer screening coverage in the belgian health interview survey Y1 - 2018 A1 - Finaba Berete A1 - Johan Van der Heyden A1 - Stefaan Demarest A1 - Jean Tafforeau A1 - Herman Van Oyen A1 - Bruyère, Olivier A1 - Françoise Renard KW - breast KW - cancer KW - SCREENING KW - VALIDATION JF - European Congress of Epidemiology CY - Lyon ER - TY - JOUR T1 - Contribution of chronic conditions to gender disparities in health expectancies in Belgium, 2001, 2004 and 2008 JF - European Journal of Public Health Y1 - 2018 A1 - Renata T C Yokota A1 - Nusselder, Willma J A1 - Robine, Jean-Marie A1 - Jean Tafforeau A1 - Françoise Renard A1 - Deboosere, Patrick A1 - Herman Van Oyen KW - causes of death KW - causes of morbidity KW - DISABILITY KW - Gender KW - HEALTH EXPECTANCY KW - inequity KW - Life expectancy AB -

Background

We aimed to investigate the contribution of chronic conditions to gender differences in disability-free life expectancy (DFLE) and life expectancy with disability (LED) in Belgium in 2001, 2004 and 2008.

Methods

Data on disability and chronic conditions from participants of the 2001, 2004 and 2008 Health Interview Surveys in Belgium were used to estimate disability prevalence by cause using the attribution method. Disability prevalence was applied to life tables to estimate DFLE and LED using the Sullivan method. Decomposition techniques were used to assess the contribution of mortality and disability and further of causes of death and disability to gender disparities in DFLE and LED.

Results

Higher LE, DFLE and LED were observed for women compared with men in all years studied. A decrease in the gender gap in LE (2001: 5.9; 2004: 5.6; 2008: 5.3) was observed in our cross-sectional approach followed by a decrease in gender differences in DFLE (2001: 1.9; 2004: 1.3; 2008: 0.5) and increase in LED (2001: 4.0; 2004: 4.4; 2008: 4.8). The higher LED in women was attributed to their lower mortality due to lung/larynx/trachea cancer, ischaemic heart diseases, and external causes (2001 and 2004) and higher disability prevalence due to musculoskeletal conditions (2008). Higher DFLE was observed in women owing to their lower mortality from lung/larynx/trachea cancer, ischaemic heart diseases, digestive cancer and chronic respiratory diseases.

Conclusion

To promote healthy ageing of populations, priority should be given to reduce the LED disadvantage in women by targeting non-fatal diseases, such as musculoskeletal conditions.

M3 - 10.1093/eurpub/cky105 ER - TY - Generic T1 - Contribution of chronic conditions to gender disparities in life expectancy and health expectancies in Belgium, 1997-2013 Y1 - 2017 A1 - Renata Yokota A1 - Nusselder, Wilma A1 - Robine, Jean-Marie A1 - Jean Tafforeau A1 - Françoise Renard A1 - Deboosere, Patrick A1 - Herman Van Oyen JF - WEON 2017 : Epidemiological Methods for Implementation Research ER - TY - JOUR T1 - Educational inequalities in premature mortality by region in the Belgian population in the 2000s JF - Archives of Public Health Y1 - 2017 A1 - Françoise Renard A1 - Brecht Devleesschauwer A1 - Gadeyne, Sylvie A1 - Jean Tafforeau A1 - Deboosere, Patrick KW - Belgium KW - Educational inequalities KW - Health inequalities KW - Premature mortality AB -

Background

In Belgium, socio-economic inequalities in mortality have long been described at country-level. As Belgium is a federal state with many responsibilities in health policies being transferred to the regional levels, regional breakdown of health indicators is becoming increasingly relevant for policy-makers, as a tool for planning and evaluation. We analyzed the educational disparities by region for all-cause and cause-specific premature mortality in the Belgian population.

Methods

Residents with Belgian nationality at birth registered in the census 2001 aged 25–64 were included, and followed up for 10 years though a linkage with the cause-of-death database. The role of 3 socio-economic variables (education, employment and housing) in explaining the regional mortality difference was explored through a Poisson regression. Age-standardised mortality rates (ASMRs) by educational level (EL), rate differences (RD), rate ratios (RR), and population attributable fractions (PAF) were computed in the 3 regions of Belgium and compared with pairwise regional ratios. The global PAFs were also decomposed into the main causes of death.

Results

Regional health gaps are observed within each EL, with ASMRs in Brussels and Wallonia exceeding those of Flanders by about 50% in males and 40% in females among Belgian. Individual SE variables only explained up to half of the regional differences. Educational inequalities were also larger in Brussels and Wallonia than in Flanders, with RDs ratios reaching 1.8 and 1.6 for Brussels versus Flanders, and Wallonia versus Flanders respectively; regional ratios in relative inequalities (RRs and PAFs) were smaller. This pattern was observed for all-cause and most specific causes of premature mortality. Ranking the cause-specific PAFs revealed a higher health impact of inequalities in causes combining high mortality rate and relative inequality, with lung cancer and ischemic heart disease on top for all regions and both sexes. The ranking showed few regional differences.

Conclusions

For the first time in Belgium, educational inequalities were studied by region. Among the Belgian, educational inequalities were higher in Brussels, followed by Wallonia and Flanders. The region-specific PAF decomposition, leading to a ranking of causes according to their population-level impact on overall inequality, is useful for regional policy-making processes.

VL - 75 CP - 44 M3 - 10.1186/s13690-017-0212-x ER - TY - JOUR T1 - Estimating the prevalence of diabetes mellitus and thyroid disorders using medication data in Flanders, Belgium. JF - Eur J Public Health Y1 - 2017 A1 - Vaes, Bert A1 - Ruelens, Catherine A1 - Saikali, Samuel A1 - Smets, Alexander A1 - Henrard, Séverine A1 - Françoise Renard A1 - van den Akker, Marjan A1 - Van Pottelbergh, Gijs A1 - Goderis, Geert A1 - Johan Van der Heyden AB -

Background: Various methods exist to estimate disease prevalences. The aim of this study was to determine whether dispensed, self-reported and prescribed medication data could be used to estimate the prevalence of diabetes mellitus and thyroid disorders. Second, these pharmaco-epidemiological estimates were compared with prevalences based on self-reported diagnoses and doctor-registered diagnoses.

Methods: Data on medication for diabetes and thyroid disorders were obtained from three different sources in Flanders (Belgium) for 2008: a purely administrative database containing data on dispensed medication, the Belgian National Health Interview Survey for self-reported medication and diagnoses, and a patient record database for prescribed medication and doctor-registered diagnoses. Prevalences were estimated based on medication data and compared with each other. Cross-tabulations of dispensed medication and self-reported diagnoses, and prescribed medication and doctor-registered diagnoses, were investigated.

Results: Prevalences based on dispensed medication were the highest (4.39 and 2.98% for diabetes and thyroid disorders, respectively). The lowest prevalences were found using prescribed medication (2.39 and 1.72%, respectively). Cross-tabulating dispensed medication and self-reported diagnoses yielded a moderate to high sensitivity for diabetes (90.4%) and thyroid disorders (77.5%), while prescribed medication showed a low sensitivity for doctor-registered diagnoses (56.5 and 43.6%, respectively). The specificity remained above 99% in all cases.

Conclusions: This study was the first to perform cross-tabulations for disease prevalence estimates between different databases and within (sub)populations. Purely administrative database was shown to be a reliable source to estimate disease prevalence based on dispensed medication. Prevalence estimates based on prescribed or self-reported medication were shown to have important limitations.

U1 - http://www.ncbi.nlm.nih.gov/pubmed/29016831?dopt=Abstract M3 - 10.1093/eurpub/ckx106 ER - TY - Generic T1 - Registration of treatment demands for substance use disorders in Belgium : Why are some clients registered anonymously? Y1 - 2017 A1 - Jérôme Antoine A1 - Françoise Renard JF - Lisbon Addictions 2017 ER - TY - JOUR T1 - Trends in educational inequalities in premature mortality in Belgium between the 1990s and the 2000s: the contribution of specific causes of deaths. JF - J Epidemiol Community Health Y1 - 2017 A1 - Françoise Renard A1 - Gadeyne, Sylvie A1 - Brecht Devleesschauwer A1 - Jean Tafforeau A1 - Deboosere, Patrick AB -

BACKGROUND: Reducing socioeconomic inequalities in mortality, a key public health objective may be supported by a careful monitoring and assessment of the contributions of specific causes of death to the global inequality.

METHODS: The 1991 and 2001 Belgian censuses were linked with cause-of-death data, each yielding a study population of over 5 million individuals aged 25-64, followed up for 5 years. Age-standardised mortality rates (ASMR) were computed by educational level (EL) and cause. Inequalities were measured through rate differences (RDs), rate ratios (RRs) and population attributable fractions (PAFs). We analysed changes in educational inequalities between the 1990s and the 2000s, and decomposed the PAF into the main causes of death.

RESULTS: All-cause and avoidable ASMR decreased in all ELs and both sexes. Lung cancer, ischaemic heart disease (IHD), chronic obstructive pulmonary disease (COPD) and suicide in men, and IHD, stroke, lung cancer and COPD in women had the highest impact on population mortality. RDs decreased in men but increased in women. RRs and PAFs increased in both sexes, albeit more in women. In men, the impact of lung cancer and COPD inequalities on population mortality decreased while that of suicide and IHD increased. In women, the impact of all causes except IHD increased.

CONCLUSION: Absolute inequalities decreased in men while increasing in women; relative inequalities increased in both sexes. The PAFs decomposition revealed that targeting mortality inequalities from lung cancer, IHD, COPD in both sexes, suicide in men and stroke in women would have the largest impact at population level.

VL - 71 CP - 4 U1 - http://www.ncbi.nlm.nih.gov/pubmed/27885048?dopt=Abstract M3 - 10.1136/jech-2016-208370 ER - TY - Generic T1 - Worse or better ? The challenge of measuring inequality changes in premature mortality in Belgium Y1 - 2016 A1 - Françoise Renard A1 - Gadeyne, Sylvie A1 - Brecht Devleesschauwer A1 - Jean Tafforeau A1 - Patrick De Boosere KW - Health inequalities KW - mortality KW - Premature mortality JF - European Public Health Association conference CY - Vienna ER - TY - Generic T1 - A design to improve the comparability of area maps: the exemple of the premature mortality in Belgium Y1 - 2015 A1 - Françoise Renard KW - a KW - Area KW - Belgium KW - COMPARABILITY KW - conference KW - Design KW - epidemiology KW - improve KW - map KW - method KW - methods KW - mortality KW - premature KW - Premature mortality JF - Methods in Epidemiology Conference CY - Leuven CP - ? U1 - 38005 U2 - ? ER - TY - JOUR T1 - La mortalité prématurée par cancer chez l'adulte en Belgique: principales causes et évolution de 1993-1994 à 2008-2009 JF - Onco Y1 - 2015 A1 - Françoise Renard KW - Belgique KW - Belgium KW - cancer KW - cause KW - causes KW - de KW - EN KW - ET KW - mortalité KW - mortality KW - PAR KW - Premature mortality KW - trend VL - 9 CP - 9 U1 - 38003 ER - TY - JOUR T1 - Mapping the cause-specific premature mortality reveals large between-districts disparity in Belgium, 2003-2009 JF - Archives of Public Health Y1 - 2015 A1 - Françoise Renard A1 - Deboosere,P. A1 - Jean Tafforeau KW - a KW - age KW - ALL KW - association KW - at KW - Belgium KW - cause specific KW - cause-specific KW - Class KW - Clustering KW - conditions KW - conference KW - Correlation KW - Correlations KW - data KW - Design KW - Discussion KW - disparities KW - distribution KW - district KW - Ecological KW - ECONOMIC KW - European KW - Expectancy KW - Flanders KW - Flemish KW - Geographical KW - Geographical-distribution KW - health KW - Health indicator KW - HEALTH POLICIES KW - HEALTH POLICY KW - Heterogeneity KW - Impact KW - Income KW - Income inequality KW - Indicator KW - inequalities KW - inequality KW - intervention KW - interventions KW - IS KW - LEVEL KW - Life KW - Life expectancy KW - Male KW - males KW - mapping KW - method KW - methods KW - mortality KW - Mortality rate KW - Mortality rates KW - Mortality-rates KW - observed KW - ON KW - Paper KW - pattern KW - PATTERNS KW - period KW - POISSON KW - Poisson regression KW - POLICIES KW - POLICY KW - POPULATION KW - premature KW - Premature mortality KW - PROGRESSION KW - public KW - public health KW - Public-health KW - RATES KW - Ratio KW - Ratios KW - region KW - regional KW - regression KW - Research KW - result KW - results KW - scale KW - Socio economic KW - Socio-economic KW - Socioeconomic KW - Statistics KW - Still KW - Test KW - unemployment AB - Background: Belgium has a well-known regional pattern in life expectancy with higher life expectancy in the northern Flemish region. The aim of this paper is to analyse in how far this pattern is reproduced in premature mortality (1-<75 yr) in males, a health indicator sensitive to both health policy interventions and socio-economic conditions. Methods: Data on mortality, population and unemployment are provided by Statistics Belgium. We used maps to explore the geographical patterns of premature mortality, and look at the ecological association with socio-economic characteristics at the district level: age-adjusted premature mortality rates in males were computed and mapped at district level for the periods 1993-1997 and 2005-2009. Rates are grouped into classes with a geometrical progression of 1.1 and are represented with a diverging scale of colours. The disparity between districts was measured with the decile ratio (P90/P10). The association with the geographical distribution of unemployment was examined both visually and tested with a Poisson regression.Results: The clear geographical pattern with lower premature mortality rates in the North (Flanders) is confirmed. The highest premature mortality rates are observed in the South-West districts. The pattern is persistent over the 2 periods, with more heterogeneity in the 2005-2009 period, the between-district decile ratios being 1.56 and 1.75 respectively in the 1 VL - 73 CP - 13 U1 - 38004 M3 - http://dx.doi.org/10.1186/s13690-015-0060-5 ER - TY - JOUR T1 - Premature mortality in Belgium in 1993-2009: leading causes, regional disparities and 15 years change. JF - Arch Public Health Y1 - 2014 A1 - Françoise Renard A1 - Jean Tafforeau A1 - Deboosere, Patrick AB -

BACKGROUND: Reducing premature mortality is a crucial public health objective. After a long gap in the publication of Belgian mortality statistics, this paper presents the leading causes and the regional disparities in premature mortality in 2008-2009 and the changes since 1993.

METHODS: All deaths occurring in the periods 1993-1999 and 2003-2009, in people aged 1-74 residing in Belgium were included. The cause of death and population data for Belgium were provided by Statistics Belgium , while data for international comparisons were extracted from the WHO mortality database. Age-adjusted mortality rates and Person Year of Life Lost (PYLL) were calculated. The Rate Ratios were computed for regional and international comparisons, using the region or country with the lowest rate as reference; statistical significance was tested assuming a Poisson distribution of the number of deaths.

RESULTS: The burden of premature mortality is much higher in men than in women (respectively 42% and 24% of the total number of deaths). The 2008-9 burden of premature mortality in Belgium reaches 6410 and 3440 PYLL per 100,000, respectively in males and females, ranking 4th and 3rd worst within the EU15. The disparities between Belgian regions are substantial: for overall premature mortality, respective excess of 40% and 20% among males, 30% and 20% among females are observed in Wallonia and Brussels as compared to Flanders. Also in cause specific mortality, Wallonia experiences a clear disadvantage compared to Flanders. Brussels shows an intermediate level for natural causes, but ranks differently for external causes, with less road accidents and suicide and more non-transport accidents than in the other regions. Age-adjusted premature mortality rates decreased by 29% among men and by 22% among women over a period of 15 years. Among men, circulatory diseases death rates decreased the fastest (-43.4%), followed by the neoplasms (-26.6%), the other natural causes (-21.0%) and the external causes (-20.8%). The larger decrease in single cause is observed for stomach cancer (-48.4%), road accident (-44%), genital organs (-40.4%) and lung (-34.6%) cancers. On the opposite, liver cancer death rate increased by 16%. Among female, the most remarkable feature is the 50.2% increase in the lung cancer death rate. For most other causes, the decline is slightly weaker than in men.

CONCLUSION: Despite a steady decrease over time, international comparisons of the premature mortality burden highlight the room for improvement in Belgium. The disadvantage in Wallonia and to some extent in Brussels suggest the role of socio-economic factors; well- designed health policies could contribute to reduce the regional disparities. The increase in female lung cancer mortality is worrying.

VL - 72 CP - 1 M3 - 10.1186/2049-3258-72-34 ER - TY - JOUR T1 - Premature mortality in Belgium in 1993-2009: leading causes, regional disparities and 15 years change JF - Archives of Public Health Y1 - 2014 A1 - Françoise Renard A1 - Jean Tafforeau A1 - Deboosere, Patrick KW - Belgium KW - Cause of Death KW - mortality KW - prematute mortality AB -

Background

Reducing premature mortality is a crucial public health objective. After a long gap in the publication of Belgian mortality statistics, this paper presents the leading causes and the regional disparities in premature mortality in 2008–2009 and the changes since 1993.

Methods

All deaths occurring in the periods 1993–1999 and 2003–2009, in people aged 1–74 residing in Belgium were included.

The cause of death and population data for Belgium were provided by Statistics Belgium , while data for international comparisons were extracted from the WHO mortality database.

Age-adjusted mortality rates and Person Year of Life Lost (PYLL) were calculated. The Rate Ratios were computed for regional and international comparisons, using the region or country with the lowest rate as reference; statistical significance was tested assuming a Poisson distribution of the number of deaths.

Results

The burden of premature mortality is much higher in men than in women (respectively 42% and 24% of the total number of deaths). The 2008–9 burden of premature mortality in Belgium reaches 6410 and 3440 PYLL per 100,000, respectively in males and females, ranking 4th and 3rd worst within the EU15. The disparities between Belgian regions are substantial: for overall premature mortality, respective excess of 40% and 20% among males, 30% and 20% among females are observed in Wallonia and Brussels as compared to Flanders. Also in cause specific mortality, Wallonia experiences a clear disadvantage compared to Flanders. Brussels shows an intermediate level for natural causes, but ranks differently for external causes, with less road accidents and suicide and more non-transport accidents than in the other regions.

Age-adjusted premature mortality rates decreased by 29% among men and by 22% among women over a period of 15 years. Among men, circulatory diseases death rates decreased the fastest (-43.4%), followed by the neoplasms (-26.6%), the other natural causes (-21.0%) and the external causes (-20.8%). The larger decrease in single cause is observed for stomach cancer (-48.4%), road accident (-44%), genital organs (-40.4%) and lung (-34.6%) cancers. On the opposite, liver cancer death rate increased by 16%.

Among female, the most remarkable feature is the 50.2% increase in the lung cancer death rate. For most other causes, the decline is slightly weaker than in men.

Conclusion

Despite a steady decrease over time, international comparisons of the premature mortality burden highlight the room for improvement in Belgium. The disadvantage in Wallonia and to some extent in Brussels suggest the role of socio-economic factors; well- designed health policies could contribute to reduce the regional disparities. The increase in female lung cancer mortality is worrying.

VL - 72 CP - 1 M3 - 10.1186/2049-3258-72-34 ER - TY - JOUR T1 - Using multiple measures to assess changes in social inequalities for breast cancer screening JF - The European Journal of Public Health Y1 - 2014 A1 - Françoise Renard A1 - Stefaan Demarest A1 - Herman Van Oyen A1 - J. Tafforeau KW - breast KW - cancer KW - Health inequalities KW - SCREENING AB -

Objectives: To identify changes in social inequalities for mammograms uptake in Belgium over the period 1997–2008 using multiple indices, and to assess the contribution of the national breast cancer screening programme in these changes. Methods: Data were obtained from four waves of the Belgian Health Interview Survey. The socio-economic position was defined by the educational level. Inequalities were measured both with pairwise measures comparing extreme educational groups (prevalence difference and prevalence ratio), and with indices measuring the total inequality impact at population level: the Population Attributable Fraction (PAF), the Relative Index of Inequality (RII) and the Slope Index of Inequality (SII). Results: All indices show a substantial decrease in inequalities in mammographic uptake between 1997 and 2008. For the indices of total impact (PAF, RII, SII), the change occurred between the first two waves (1997 and 2001) and stabilized afterwards, while for pairwise indices the evolution continued over the whole period. Conclusion: Using multiple indices of inequality is necessary for a more complete understanding of the changes: total impact inequality indices should always complement simple pairwise measures. The inequalities in mammograms uptake, as measured with total impact indices, only decreased before the start of the national screening programme.

VL - 24 CP - 2 M3 - 10.1093/eurpub/ckt116 ER - TY - JOUR T1 - The Belgian Health System Performance Report 2012: Snapshot of results and recommendations to policy makers JF - Health Policy Y1 - 2013 A1 - Vrijens,F. A1 - Françoise Renard A1 - Jonckheer,P. A1 - Van den Heede,K. A1 - Desomer,A. A1 - Van de Voorde,C. A1 - Walckiers,D. A1 - Dubois,C. A1 - Camberlin,C. A1 - Vlayen,J. A1 - Herman Van Oyen A1 - C. Léonard A1 - Meeus,P. KW - 2012 KW - abstract KW - accessibility KW - ALL KW - AS KW - Belgian KW - Belgium KW - Benchmarking KW - care KW - conceptual framework KW - Countries KW - Efficiency KW - end of life KW - End-of-life KW - equity KW - Evolution KW - health KW - health promotion KW - Health status KW - health system KW - Health-status KW - Indicator KW - Indicators KW - IS KW - IT KW - Long-term KW - ON KW - Output KW - performance KW - performance indicators KW - POLICIES KW - POLICY KW - promotion KW - Quality KW - quality of care KW - recommendation KW - Recommendations KW - report KW - result KW - results KW - status KW - sustainability KW - System KW - time KW - values AB - Abstract Following the commitments of the Tallinn Charter, Belgium publishes the second report on the performance of its health system. A set of 74 measurable indicators is analysed, and results are interpreted following the five dimensions of the conceptual framework: accessibility, quality of care, efficiency, sustainability and equity. All domains of care are covered (preventive, curative, long-term and end-of-life care), as well as health status and health promotion. For all indicators, national/regional values are presented with their evolution over time. Benchmarking to results of other EU-15 countries is also systematic. The policy recommendations represent the most important output of the report VL - 112 CP - 1-2 U1 - 36130 M3 - http://dx.doi.org/10.1016/j.healthpol.2013.06.010 ER - TY - RPRT T1 - La performance du système de santé belge. Rapport 2012 Y1 - 2013 A1 - Vrijens,F. A1 - Françoise Renard A1 - Jonckheer,P. A1 - Van den Heede,K. A1 - Desomer,A. A1 - Van de Voorde,C. A1 - Walckiers,D. A1 - Dubois,C. A1 - Camberlain,C. A1 - Vlayen,J. A1 - Herman Van Oyen A1 - C. Léonard A1 - Meeus,P. KW - 2012 KW - Belge KW - Belgium KW - de KW - EVALUATION KW - FR_CV KW - Health indicators KW - Health systems KW - performance KW - rapport KW - santé PB - KCE CY - Brussels VL - 196b U1 - 36427 ER - TY - JOUR T1 - Using multiple inequality indices to assess changes in social inequalities for breast cancer screening in Belgium JF - Eur J Publ Health Y1 - 2013 A1 - Françoise Renard A1 - Stefaan Demarest A1 - Herman Van Oyen A1 - Jean Tafforeau KW - 2001 KW - 2008 KW - ALL KW - AS KW - at KW - Attributable KW - Belgian KW - Belgium KW - breast KW - breast cancer KW - breast cancer screening KW - Breast-cancer KW - cancer KW - cancer screening KW - Change KW - Changes KW - comparing KW - contribution KW - data KW - Educational level KW - Educational-level KW - Evolution KW - Fraction KW - Group KW - health KW - Health inequalities KW - health interview survey KW - HIS KW - identify KW - Impact KW - index KW - inequalities KW - inequality KW - Interview KW - Interview survey KW - IS KW - LEVEL KW - mammographic KW - measure KW - measures KW - measuring KW - method KW - methods KW - Multiple KW - national KW - national screening KW - objectives KW - PAF KW - period KW - POPULATION KW - prevalence KW - programme KW - Ratio KW - relative KW - Relative index of inequality KW - result KW - results KW - RII KW - SCREENING KW - slope index KW - SOCIAL KW - Social inequalities KW - Social inequality KW - Socio economic KW - Socio-economic KW - Socioeconomic KW - Socioeconomic position KW - survey KW - uptake AB - Objectives: To identify changes in social inequalities for mammograms uptake in Belgium over the period1997-2008 using multiple indices, and to assess the contribution of the national breast cancer screeningprogramme in these changes. Methods: Data were obtained from four waves of the Belgian Health InterviewSurvey. The socio-economic position was defined by the educational level. Inequalities were measured both withpairwise measures comparing extreme educational groups (prevalence difference and prevalence ratio), and withindices measuring the total inequality impact at population level: the Population Attributable Fraction (PAF), theRelative Index of Inequality (RII) and the Slope Index of Inequality (SII). Results: All indices show a substantialdecrease in inequalities in mammographic uptake between 1997 and 2008. For the indices of total impact (PAF, RII,SII), the change occurred between the first two waves (1997 and 2001) and stabilized afterwards, while forpairwise indices the evolution continued over the whole period. Conclusion: Using multiple indices ofinequality is necessary for a more complete understanding of the changes: total impact inequality indicesshould always complement simple pairwise measures. The inequalities in mammograms uptake, as measuredwith total impact indices, only decreased before the start of the national screening programme VL - 24 CP - 2 U1 - 35764 M3 - http://dx.doi.org/ ER - TY - Generic T1 - Evolution of social inequalities after the introduction of a breast cancer screening program. Conference Proceeding of the 5th International Congres of Epidemiology of Adelf-Epiter, Brusselss 2012 Y1 - 2012 A1 - Françoise Renard A1 - Stefaan Demarest A1 - Jean Tafforeau KW - 2001 KW - 2008 KW - 2012 KW - Absolute KW - Aged KW - ALL KW - AS KW - association KW - at KW - Belgium KW - breast KW - breast cancer KW - breast cancer screening KW - Breast-cancer KW - cancer KW - cancer screening KW - Categories KW - Change KW - Changes KW - conference KW - Coverage KW - data KW - differences KW - Discussion KW - Educational level KW - Educational-level KW - epidemiology KW - Evolution KW - Fraction KW - FR_CV KW - Gini coefficient KW - Group KW - health KW - Health inequalities KW - health interview survey KW - health interview surveys KW - Improvement KW - Income KW - Increase KW - inequalities KW - inequality KW - International KW - Interview KW - Interview survey KW - IQ KW - IT KW - Less KW - LEVEL KW - levels KW - linear regression KW - mammographic KW - mammographic screening KW - measure KW - measures KW - method KW - methods KW - national KW - national screening KW - objectives KW - observed KW - ODDS RATIO KW - PAF KW - period KW - prevalence KW - PROGRAM KW - proxies KW - Proxy KW - RATES KW - Ratio KW - Reduction KW - regression KW - relative KW - result KW - results KW - RII KW - RR KW - SCREENING KW - SCREENING PROGRAM KW - self reported KW - Self-reported KW - SES KW - SOCIAL KW - Social inequalities KW - Social inequality KW - Socio economic KW - socio economic inequalities KW - Socio economic status KW - Socio-economic KW - socio-economic inequality KW - Socio-economic status KW - Socioeconomic KW - Socioeconomic inequalities KW - Socioeconomic status KW - status KW - study KW - survey KW - surveys KW - TESTING KW - time KW - trend KW - trends KW - WOMEN KW - work AB - Introduction: Opportunistic breast cancer screening associated with a better coverage for highest socio-economic status (SES) existed in Belgium before the introduction of a national screening program in 2001-2002. This work examined the changes in the mammographic coverage by SES and the changes in SE-inequalities since 1997.Methods: Data were obtained from the Health Interview Surveys (1997-2001-2004-2008). The mammographic coverage rate was computed for women aged 50-69. Educational levels (EL) were used as proxies for SES. SE-inequality for mammographic coverage was estimated with absolute and relative disparity measures (absolute differences and ratio of the lowest versus highest EL-prevalence), regression indices (the SII and RII), and the Population-Attributable Fraction (PAF). The evolution over time of the indices was measured by testing for the differences between the first and the last survey year, and by fitting a weighted linear regression.Results: In each EL a substantial increase in the coverage was observed over time. The relative increase of prevalence (absolute increase in prevalence between 2 years divided by the prevalence in the first year) between 1997 and 2008 was larger in the 2 less educated groups (respectively + 62.8% and +92.75% increase from initial value) than in the more educated groups (+ 33% and +19%). All inequality indices reflected a change towards less inequality: the absolute prevalence difference (lowest vs highest) decreased with 55% (p=0.13), the RR of being screened (lowest vs highest) increased with 40% (p=0.07) , the PAF decreased with 72% (p<0.01) , the RII increased with 76% (p=0.07) and the SII decreased with 52% (p=0.13). However, for most of the indices, no linear trend in SE-inequalities could be observed: only between 1997 and 2001 these inequalities seem to have been reducedDiscussion and Conclusions: Since 1997, the prevalence rates of mammographic coverage increased for every EL. At the beginning of the study period - before the introduction of the screening program - a reduction of SE-inequality could be observed. The figures reflect little improvement since its introduction. JF - NA T3 - Revue Epidémiologique et Santé Publique PB - ADELF (Association des Epidémiologistes de Langue Française) congress CY - Brussels VL - 60S CP - NA U1 - 33561 U2 - NA ER - TY - RPRT T1 - Enquête de Santé par Examen Belge 2018 Y1 - 0 A1 - Johan Van der Heyden A1 - Diem Nguyen A1 - Françoise Renard A1 - Aline Scohy A1 - Stefaan Demarest A1 - Sabine Drieskens A1 - Lydia Gisle ER -