The 1991-2004 Evolution in Life Expectancy by Educational Level in Belgium Based on Linked Census and Population Register Data

The aim of this study is to determine trends in life expectancy by educational level in Belgium and to present elements of interpretation for the observed evolution. The analysis is based on census data providing information on educational level linked to register data on mortality for the periods 1991–1994 and 2001–2004. Using exhaustive individual linked data allows to avoid selection bias and numerator–denominator bias. The trends reveal a general increase in life expectancy together with a widening social gap. Summary indices of inequality based on life expectancies show, however, a more complex pattern and point to the importance to include the shifts in population composition by educational level in an overall assessment of the evolution of inequality by educational level.L’objectif de l’étude est de déterminer le sens et l’ampleur de l’évolution des inégalités en espérance de vie en Belgique selon le niveau d’instruction. L’analyse part des données des recensements qui fournissent l’information sur le niveau d’instruction. Ces données ont été liées au registre de la population qui fournit l’information sur la mortalité pour les périodes 1991–1994 et 2001–2004. L’utilisation de données exhaustives et d’un enregistrement de la mortalité lié directement aux données du recensement évite des erreurs de sélection et du biais entre numérateur et dénominateur. On peut constater qu’en général l’espérance de vie progresse pour tous les niveaux d’éducation mais que cela va de pair avec un élargissement des inégalités. L’utilisation d’indices d’inégalité montre néanmoins une réalité plus complexe et la nécessité d’inclure l’évolution de la composition de la population par niveau d’éducation dans une évaluation globale de l’évolution des inégalités

Old and new inequalities in educational attainment

This study examines ethnic and class inequalities in educational attainment using the 2001 Belgian Census. It analyses the highest qualifications that the 1973 to 1979 birth cohort obtained in 2001. Variation in attainment levels is explained as a function of gender, ethnic and class origins, and other characteristics of the parental household in 1991. Earlier findings of gross ethnic disadvantage, in particular among Turkish and Moroccan youngsters, were largely replicated when ethnicity is identified by ancestry rather than nationality. Looking across ethnic groups, parental resources in 1991 were very powerful predictors of educational attainment in 2001. In order of importance, parental education, accumulated wealth (as measured by ownership and quality of housing), employment and occupational class explain most educational inequality. Ethnic disadvantage is perpetuated from one generation to the next mainly through mechanisms of class disadvantage. In addition, there is evidence of cumulative ethnic and class disadvantage for Turkish and Moroccan minorities. Finally, the largest unexplained ethnic disadvantage is found for the Turkish minority in Flanders. Not only are they most underrepresented in tertiary education, they are also most at risk of school dropout in secondary education

Spatial disparities at death : age-, sex- and disease-specific mortality in the districts of Belgium at the beginning of the twentieth century

At the beginning of the twentieth century, life expectancy at birth was much lower in Flanders, the northern part of Belgium, than in Wallonia, the southern part of the country. In the literature, this excess mortality is mainly attributed to high levels of infant mortality caused by bad feeding practices and low-quality drinking water. The regional variability of mortality risks at other ages during this period has received less attention. In this article, we reconstruct age-, sex- and disease-specific death rates for the 41 districts of Belgium around the year 1910. To show the mortality variations, we construct maps according to indirect standardised mortality rates that reflect the deviation from the national average. Our spatial analysis shows that there was a clear-cut Flemish-Walloon divide in general mortality only for infants and children under the age of 7. For older children, adolescents, and young and elderly adults, low and high mortality were observed in both regions. For disease-specific mortality, moreover, a geographical pattern was only visible for infants, who consistently had the highest death rates in Flanders. Hence, the spatial disparities in general and disease-specific mortality cannot be simplified according to a Flemish-Walloon divide. Furthermore, we noted large differences among districts belonging to the same province, and in the ranking of the districts by age. In other words, high mortality levels of infants, children, adolescents and adults did not per se appear in the same districts. From adolescent ages onwards, there were also large differences in the ranking of districts by sex- specific mortality. This strongly suggests the importance of sex-specific determinants of health and mortality at these ages

Monitoring health inequalities when the socio-economic composition changes : are the slope and relative indices of inequality appropriate? : results of a simulation study

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

Reversing the Malthusian paradigm on retirement age

Résumé La démographie a toujours influencé la pensée politique. La décision récente d’aug­menter l’âge à la pension dans beaucoup de pays développés est inspirée par l’évo­lution importante de la composition par âge de la population. Mais il y a en réalité peu d’arguments pour augmenter l’âge à la retraite si l’on tient compte de l’ensem­ble des données démographiques et économiques. Une interprétation souvent trop simpliste et même parfois erronée d’indicateurs démographiques contribue à cette démarche. L’utilisation systématique d’indicateurs démographiques dans la discussion sur la viabilité du système des pensions et de la sécurité sociale est selon nous souvent inspirée par la théorie de l’économie de l’offre. Un aspect crucial est le fait que la croissance de la productivité est ignorée ou minimisée. À cet égard, la discussion actuelle présente une profonde similitude avec l’approche Malthusienne de la population. Abstract Demography always influenced political thinking. The recent decision to increase the age of retirement in many high-income countries is driven by a dramatic chan­ge in the age composition of the population. We argue that there is in fact no need to increase the age of retirement and that many aspects of the current evolution both in demography and in economy are overlooked. Moreover, some demographic indicators such as life expectancy or the dependency ratio are often interpreted in a simplistic and erroneous way. The systematic use of demographic indicators to discuss the sustainability of the pension system and of the social security system is in our view often inspired by the supply-side way of economic thinking. A crucial aspect is that productivity increase is ignored or minimalized in the discussion. In this regard the discussion has many similarities with the Malthusian approach of the population question

Contribution of chronic conditions to the disability burden across smoking categories in middle-aged adults, Belgium

Introduction : Smoking is considered the single most important preventable cause of morbidity and mortality worldwide, contributing to increased incidence and severity of disabling conditions. The aim of this study was to assess the contribution of chronic conditions to the disability burden across smoking categories in middle-aged adults in Belgium. Methods : Data from 10,224 individuals aged 40 to 60 years who participated in the 1997, 2001, 2004, or 2008 Health Interview Surveys in Belgium were used. Smoking status was defined as never, former (cessation >= 2 years), former (cessation = 20 cigarettes/day). To attribute disability to chronic conditions, binomial additive hazards models were fitted separately for each smoking category adjusted for gender, except for former (cessation <2 years) and occasional light smokers due to the small sample size. Results : An increasing trend in the disability prevalence was observed across smoking categories in men (never = 4.8%, former (cessation >= 2 years) = 5.8%, daily light = 7.8%, daily heavy = 10.7%) and women (never = 7.6%, former (cessation >= 2 years) = 8.0%, daily light = 10.2%, daily heavy = 12.0%). Musculoskeletal conditions showed a substantial contribution to the disability burden in men and women across all smoking categories. Other important contributors were depression and cardiovascular diseases in never smokers; depression, chronic respiratory diseases, and diabetes in former smokers (cessation >= 2 years); chronic respiratory diseases, cancer, and cardiovascular diseases in daily light smokers; cardiovascular diseases and chronic respiratory diseases in men and depression and diabetes in women daily heavy smokers. Conclusions : Beyond the well-known effect of smoking on mortality, our findings showed an increasing trend of the disability prevalence and different contributors to the disability burden across smoking categories. This information can be useful from a public health perspective to define strategies to reduce disability in Belgium

Educational inequalities in premature mortality by region in the Belgian population in the 2000s

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

Evolution of educational inequalities in life and health expectancies at 25 years in Belgium between 2001 and 2011 : a census-based study

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 (LE25 and DFLE25) 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. LE25 and DFLE25 were computed by educational level (EL). Absolute differentials of LE25 and DFLE25 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 LE25 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 LE25 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 DFLE25 in males with high EL (+4.5 years) and the decrease of the DFLE25 in women with low EL, results in a substantial increase of all considered DFLE25 inequality measures in both genders. In 2011, DFLE25 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 LE25 increased in all ELs, but at a higher pace in highly educated, leading to an increase in the LE25 gaps in both genders. After accounting for the upwards shift of the educational distribution, the population-level inequality index increased only for men. The DFLE25 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

Data inventory of health inequalities among adolescents and young adults in the Brussels-Capital Region

Résumé Cet article analyse différentes sources de données quant à leur potentiel à étudier et suivre les inégalités de santé parmi les adolescents et les jeunes adultes dans la Région de Bruxelles-Capitale (RBC). Les données du recensement et d’enquêtes sont évaluées quant à leur disponibilité, leur aptitude à se prêter à une analyse sta­tistique, la quantité d’information portant sur des indicateurs-clés, comme la position socio-économique (PSE), l’état de santé, des comportements de santé ou des risques, et les soins de santé. Les certificats de décès couplés avec les données du recensement et l’Enquête de Santé par Interview (HIS) ont été identifiés comme les meilleures sources de données et sont discutées en détail. Les certificats de décès sont couplés aux recensements de 1991 et 2001, ce qui en fait un important outil de monitoring. Le lien entre ces deux bases de données nous permet de suivre la mortalité par cause dans la population jeune de RBC. De plus, le recensement de 2001 fournit de l’information sur le niveau de santé auto-évalué pour l’ensemble de la population. L’information sur les variables de PSE, la structure familiale, l’his­torique des migrations et la nationalité d’origine sont disponibles et permettent la comparaison de la santé perçue et de la mortalité entre différents sous-groupes, en tenant compte de l’impact spécifique de plusieurs déterminants sociaux. Cependant, le monitoring des inégalités de santé parmi les adolescents et les jeunes adul­tes ciblé uniquement sur la mortalité et la santé perçue ne suffit pas à en décrire toutes les facettes. D’autres données sont disponibles pour compléter l’information des bases de données couplées, par exemple celles de la HIS&nbsp;; nous avons analysé la représentativité et les non-réponses dans les données de la HIS (1997, 2001, 2004, 2008) afin d’identifier son potentiel et ses limites pour l’étude des 15-34 ans. Les avantages de cette enquête sont&nbsp;: la taille suffisante de l’échantillon pour le RBC, la représentativité des 15-34 ans pour la plupart des caractéristiques démographi­ques, une information détaillée sur les comportements de santé, la santé mentale et la consommation de soins, ainsi que sur des déterminants sociaux. Il existe aussi certaines limites&nbsp;: comme dans toute enquête se pose le problème des non-répon­dants, et spécifiquement pour cette enquête, le taux de non-réponses au volet auto-rempli du questionnaire est important et sélectif. De plus, certains modules n’ont pas été utilisés à chaque vague de l’enquête, ce qui limite l’utilisation de don­nées groupées pour certains modules. Summary In this paper, various data sources are analysed in terms of their potential for the study and monitoring of health inequalities among adolescents and young adults in the Brussels-Capital Region (BCR). Routine, census and survey data sources are eva­luated as to their accessibility, their suitability for use in statistical analysis, and the amount of information they can yield on key indicators such as socioeconomic po­sition (SEP), health outcomes, intermediate factors (i.e. health and risk behaviours), and health care. Death certificates linked to census data and the Belgian Health In­terview Survey (BHIS) are identified as the most suitable data sources and are discussed in detail. The linkage of death certificates to the 1991 and 2001 censuses re­sulted in an important tool for health monitoring because the continuity between these two datasets allows for the tracking of cause-specific mortality rates among the BCR’s young population. Additionally, the 2001 census data include information on self-rated health for the entire population. Data on SEP variables, living arran­gement indicators and other sociodemographic variables such as migration history and nationality of origin are available, allowing for comparisons between subgroups of self-rated health and mortality and taking into account the specific impact of a number of social determinants. However, it is insufficient to rely solely on cause-specific mortality and self-rated health for the monitoring of health inequalities among young people as this is too narrow an approach to produce a complete picture of the situation. Other data complementing the information obtained through the linking of datasets are available, such as that collected by the HIS. Re­presentativeness and nonresponse within HIS data (1997, 2001, 2004, 2008) are analysed in order to identify the opportunities and limitations of the HIS for the study of young people. The benefits of this survey are its sample size, sufficiently large for the BCR, the representativeness of 15-to-34-year-olds with regard to most demographic characteristics, and the in-depth information it provides on health be­haviour, mental health and medical consumption, as well as on social determinants of health. This dataset also has its limitations: as with any survey, there is the problem of nonresponse, and in this specific case, the dropout rate for the self-adminis­tered questionnaire is substantial and selective. Also, not all of the modules were employed every survey year, thus restricting the usefulness of pooled data to only some of the modules

The population of Brussels: a demographic overview

The Brussels-Capital Region is comprised of 19 municipalities and has a surface area of 161.4 km². The region is the core of a much broader morphological agglomeration made up of 36 municipalities with a total population of more than one and a half million inhabitants. The official population of the Brussels-Capital Region totalled 1 048 491 inhabitants on 1st January 2008 and is the youngest in the country with an average age of 37.8 years recorded in 2006. The demographic development of Brussels has always been strongly dominated by migration over the past one and half centuries and this is not different today. The capital city has experienced a rise in population over the past few years and, just like all large European cities, the population composition is highly influenced by internationalisation. The last census (socio-economic survey of 2001) enabled the nationality of origin to be taken into account. According to this criterion, Brussels had 45 different nationalities with at least 1 000 inhabitants. The composition has diversified further since then and there has been an increase in inhabitants from European Union countries. The region is characterised by a clear spatial differentiation between the poorer districts, mixed neighbourhoods and the affluent areas of the city. The underlying structure of this spatial segregation according to socio-economic status has deep-seated historical roots and a high level of inertia. However, the arrival of new inhabitants, large construction sites within a number of districts, speculation and increasing property prices are slowly changing the composition of the population within some districts. A short description of the most important demographic trends that will affect the composition of the city in the coming decades is given below.La Région de Bruxelles-Capitale comprend 19 communes sur une superficie de 161,4 km². La Région constitue le noyau d’une agglomération morphologique bien plus vaste qui compte 36 communes au total et une population de plus d’un million et demi d’habitants. Au 1er janvier 2008, les chiffres officiels de la population de la Région de Bruxelles-Capitale atteignaient 1 048 491 habitants. La population bruxelloise est la plus jeune du pays, avec une moyenne d’âge de 37,8 ans en 2006. Au cours du siècle et demi passé, le développement démographique de Bruxelles est resté fortement dominé par les migrations. Ce phénomène ne se dément pas aujourd’hui. La capitale a vu sa population s’accroître au cours des dernières années et, comme pour toutes les grandes villes d’Europe, sa composition s’internationaliser fortement. Le dernier recensement (enquête socio-économique de 2001) permet de tenir compte de la nationalité d’origine de la population. Suivant ce critère, Bruxelles ne comptait pas moins de 45 nationalités différentes avec au moins 1 000 habitants. Depuis lors, la composition s’est encore diversifiée et la population originaire des pays de l’Union européenne a augmenté. La Région se caractérise par une nette différenciation spatiale entre les quartiers pauvres, les quartiers mixtes et les quartiers aisés. La structure de base de cette ségrégation spatiale selon le statut socio-économique a des racines historiques anciennes et est frappée d’une inertie certaine. Toutefois, l’arrivée de nouveaux habitants, la réalisation de grands travaux dans un certain nombre de quartiers, la spéculation immobilière et l’augmentation des prix du logement modifient petit à petit la composition de la population de certains quartiers. Nous esquissons ci-dessous les principales tendances démographiques qui influenceront la composition de la ville dans les décennies à venir.Het Brussels Hoofdstedelijk Gewest omvat 19 gemeenten op een oppervlakte van 161,4 km2. Het gewest vormt de kern van een veel bredere morfologische agglomeratie die in het totaal 36 gemeenten telt en een totale bevolking van meer dan anderhalf miljoen inwoners. Het officieel bevolkingsaantal van het Brussels Hoofdstedelijk Gewest bedroeg op 1 januari 2008 1 048 491 inwoners. De Brusselse bevolking is de jongste van het land met een gemiddelde leeftijd van 37,8 jaar in 2006. De demografische ontwikkeling van Brussel is in de afgelopen anderhalve eeuw altijd sterk gedomineerd geweest door migratie. Dit is vandaag niet anders. De laatste jaren heeft de hoofdstad een bevolkingsgroei gekend en zoals alle grote Europese steden is de samenstelling van de bevolking sterk beïnvloed door internationalisering. De laatste volkstelling (socio-economische enquête van 2001) laat toe om rekening te houden met de nationaliteit van oorsprong. Volgens dit criterium telde Brussel 45 verschillende nationaliteitsgroepen met minstens 1 000 bewoners. Sindsdien is de samenstelling verder gediversifieerd en is er een toename van de bevolking afkomstig uit landen van de Europese Unie. Het Gewest is gekenmerkt door een duidelijke ruimtelijke differentiatie tussen de armere wijken, gemengde buurten en de welvarende stadsdelen. De basisstructuur van die ruimtelijke segregatie naar sociaal-economische status heeft diepe historische wortels en kent een vrij grote inertie. Maar de komst van nieuwe bewoners, grote bouwwerven in een aantal wijken, speculatie en stijgende woonprijzen veranderen stilaan de bevolkingssamenstelling in sommige wijken. We overlopen hieronder kort de belangrijkste demografische tendensen die de samenstelling van de stad in de nabije decennia mee zullen bepalen