La mortalité des plus de 15 ans en Belgique : les disparités régionales en 1985-1987

Duchêne, Josianne; Thiltgès, E.

doi:10.3406/espos.1993.1556

Cited by 5 publications

(3 citation statements)

References 1 publication

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“…individuals) into groups or clusters, minimizing the intra-group differences among units and maximizing the inter-group differences. For example, Duchêne and Thiltgès (1993) have clustered the 43 regional sub-divisions (‘arrondissements’) of Belgium into 4 groups with common characteristics of mortality over age 15 in order to examine regional disparities in adult mortality. Clustering could be especially useful in the analysis of big data, such as census microdata, where the very large number of individuals could be grouped into a much smaller number of units, in which individuals share common characteristics, that are more convenient to analyse.…”

Section: Machine-learning and Artificial Intelligencementioning

confidence: 99%

Big data analytics. A demographer’s perspective

Wunsch

2024

Bulletin of Sociological Methodology/Bulletin de Méthodologie S

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In the past few years, several demographers have pointed out the need to consider big data in population studies. Some are in favour of data-driven approaches, as statistical algorithms could discover novel patterns in the data. This paper examines some of the methods, both old and new, that have been developed for detecting patterns and associations in the data. It concludes with a discussion on how big data and big data analytics can contribute to improving the explanatory power of models in the social sciences and in demography in particular.

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Section: Machine-learning and Artificial Intelligencementioning

confidence: 99%

Big data analytics. A demographer’s perspective

Wunsch

2024

Bulletin of Sociological Methodology/Bulletin de Méthodologie S

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“…Substantive spatial variation in all‐cause and cause‐specific mortality has been documented in various contexts, which may represent regional variation in risk factors, regional variation in the composition of the resident population (e.g., in terms of socio‐economic position), and selective internal migration between regions in terms of health status (Keenan et al, 2021; Wilson et al, 2020). In Belgium, substantive spatial variation at both the regional and district level has been documented for all‐cause as well as cause‐specific mortality (Deboosere & Fiszman, 2009; Deboosere & Gadeyne, 2002; Duchene & Thiltgès, 1993; Eggerickx et al, 2018; Grimmeau et al, 2015). Controlling for composition in terms of socio‐economic status, pronounced regional variation persists in Belgium with lower mortality in Flemish districts than Walloon districts, and Brussels taking an intermediate position (Eggerickx et al, 2018; Grimmeau et al, 2015).…”

Section: Spatial Variation In Mortalitymentioning

confidence: 99%

Spatial variation of migrant‐native mortality differentials by duration of residence in Belgium: A story of partial convergence

Neels

Wood

Surkyn

et al. 2021

Population Space and Place

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Previous studies have repeatedly shown that all‐cause mortality is subject to spatial variation within countries and that acculturation of migrant mortality to native patterns occurs gradually with increasing duration of residence. This suggests that spatial variation in mortality is likely to differ between migrants and natives and that the migrant mortality advantage may be subject to strong variation between local settings. Using longitudinal microdata from the Belgian census, the population register, and the tax registers for 2011–2015, this article contributes to our understanding of migrant‐native mortality differentials by considering subnational spatial variation in the mortality advantage, settlement patterns of migrant groups, and varying degrees of acculturation by duration of residence. Consistent with the health selection hypothesis and the migration as a rapid health transition hypothesis, spatial variation in all‐cause mortality is limited among migrants with durations of residence under 30 years, resulting in strong variation of the mortality advantage between districts. Partial convergence to the spatial pattern of natives emerges among first generation migrants with durations of residence exceeding 30 years, as well as the intermediate and second generation. In Belgium, the country‐level mortality advantage can be partially accounted for by the settlement pattern of the migrant population in districts characterised by high native mortality and large migrant‐native differentials in all‐cause mortality.

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“…There has been no shortage of previous analyses of Belgian mortality differentials. However, most of these have focussed on the total mortality in the population, either as a whole or subdivided by sex (see, e. g. Van Houte-Minet, Wunsch, 1978;Poulain et al, 1984;Decroly, Grimmeau, 1991;Lagasse et al, 1990;Duchêne, Thiltgès, 1993;Joosens, Kesteloot, 1996;Van Oyen et al 2002;Bossuyt et al, 2004;Eggericx, Sanderson, 2007;Grimmeau et al, 2012a;Renard et al, 2015;Van Hemelrijck et al, 2017). The results of these analyses are remarkably consistent:…”

Section: Belgian Mortalitymentioning

confidence: 99%

Estimating local mortality tables for small areas: An application using Belgian sub-arrondissements

Anson

2018

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Standardised mortality ratios (SMR) may give a good estimate of the relative level of mortality in a local area, and its relation to local social conditions, but if we wish to understand changes in the age distribution of mortality as mortality declines, we need an estimate of the local mortality curve. Such fine detail can be elusive when examining small populations for which the number of people in each age group is small, the number of deaths minuscule, and estimation errors are large. A possible solution to this problem is to estimate age-specific mortality rates simultaneously for all the subunits of a particular country, using the reported number of deaths, by age and sex, for each unit as the input data. The national mortality rates then serve as a model from which local deviations, by age and sex, are estimated, on the basis of overall mortality (SMR) and local social conditions. We demonstrate this approach using data from 87 sub-national units in Belgium to construct local-level life tables, using a multilevel model with the local sex- and age-specific cells as units, nested within sex-age groups and regional units at the second level. The results indicate that life expectancy is closely related to SMR, but the specific shape of the mortality curve, in particular the range over which mid-life mortality is low and the age at which mortality begins to rise into senescence, varies by level of mortality and social conditions.

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La mortalité des plus de 15 ans en Belgique : les disparités régionales en 1985-1987

Cited by 5 publications

References 1 publication

Big data analytics. A demographer’s perspective

Big data analytics. A demographer’s perspective

Spatial variation of migrant‐native mortality differentials by duration of residence in Belgium: A story of partial convergence

Estimating local mortality tables for small areas: An application using Belgian sub-arrondissements

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