Renard Françoise, Devleesschauwer Brecht, Gadeyne Sylvie, Tafforeau Jean, Deboosere Patrick
Department of Public Health and Surveillance, Scientific Institute of Public Health (WIV-ISP), Rue Juliette Wytsmanstraat 14, 1050 Brussels, Belgium.
Interface Demography, Section Social Research, Vrije Universiteit Brussels, Brussels, Belgium.
Arch Public Health. 2017 Oct 16;75:44. doi: 10.1186/s13690-017-0212-x. eCollection 2017.
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.
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.
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.
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.
在比利时,国家层面长期以来一直在描述死亡率方面的社会经济不平等现象。由于比利时是一个联邦制国家,许多卫生政策责任已下放到地区层面,因此卫生指标的地区细分对于政策制定者来说,作为规划和评估的工具,正变得越来越重要。我们分析了比利时人口中全因和特定病因过早死亡的地区教育差异。
纳入2001年人口普查中登记的25 - 64岁出生时具有比利时国籍的居民,并通过与死因数据库的关联对其进行了10年的随访。通过泊松回归探讨了3个社会经济变量(教育、就业和住房)在解释地区死亡率差异中的作用。计算了比利时3个地区按教育水平(EL)划分的年龄标准化死亡率(ASMR)、率差(RD)、率比(RR)和人群归因分数(PAF),并与地区间两两比率进行比较。全球PAF也被分解为主要死因。
在每个教育水平内都观察到了地区健康差距,在比利时人中,布鲁塞尔和瓦隆尼亚的男性ASMR比弗拉芒高出约50%,女性高出约40%。个体社会经济变量仅解释了高达一半的地区差异。布鲁塞尔和瓦隆尼亚的教育不平等也比弗拉芒更大,布鲁塞尔与弗拉芒、瓦隆尼亚与弗拉芒的RD比率分别达到1.8和1.6;相对不平等的地区比率(RR和PAF)较小。在全因和大多数特定过早死亡原因中都观察到了这种模式。对特定病因的PAF进行排序显示,高死亡率和相对不平等相结合的病因中的不平等对健康的影响更大,肺癌和缺血性心脏病在所有地区和两性中均位居前列。排名显示地区差异不大。
在比利时首次按地区研究了教育不平等。在比利时人中,布鲁塞尔的教育不平等较高,其次是瓦隆尼亚和弗拉芒。特定地区的PAF分解,根据其对总体不平等的人群水平影响对病因进行排名,对地区政策制定过程很有用。