Geographical Inequalities in Mortality by Age and Gender in Italy, 2002-2019: Insights from a Spatial Extension of the Lee-Carter Model.

IF 1.1 Q3 DEMOGRAPHY
Spatial Demography Pub Date : 2026-01-01 Epub Date: 2026-05-01 DOI:10.1007/s40980-026-00161-x
Francesca Fiori, Andrea Riebler, Sara Martino
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引用次数: 0

Abstract

Italy reports some of the lowest levels of mortality in the developed world. Recent evidence, however, suggests that even in low-mortality countries improvements may be slowing and regional inequalities widening. This study contributes new empirical evidence to the debate by analysing mortality data by single year of age for males and females across 107 provinces in Italy from 2002 to 2019. We extend the widely used Lee-Carter model to include spatially varying age-specific effects, and further specify it to capture space-age-time interactions. The model is estimated in a Bayesian framework using the inlabru package, which builds on INLA (Integrated Nested Laplace Approximation) for non-linear models and facilitates the use of smoothing priors. This approach borrows strength across provinces and years, mitigating random fluctuations in small-area death counts. Results demonstrate the value of such a granular approach, highlighting the existence of an uneven geography of mortality despite overall national improvements. Mortality disadvantage is concentrated in parts of the Centre-South and North-West, while the Centre-North and North-East fare relatively better. These geographical differences have widened since 2010, with clear age- and gender-specific patterns, being more pronounced at younger adult ages for men and at older adult ages for women. Future work may involve refining the analysis to mortality by cause of death or socioeconomic status, informing more targeted public health policies to address mortality disparities across Italy's provinces.

2002-2019年意大利年龄和性别死亡率的地理不平等:来自李-卡特模型空间扩展的见解
意大利是发达国家中死亡率最低的国家之一。然而,最近的证据表明,即使在低死亡率国家,改善的速度也可能放缓,区域不平等现象也可能扩大。本研究通过分析2002年至2019年意大利107个省份按年龄划分的男性和女性死亡率数据,为这场辩论提供了新的经验证据。我们扩展了广泛使用的Lee-Carter模型,以包括空间变化的年龄特异性效应,并进一步指定它以捕获空间-年龄-时间相互作用。该模型使用inlabru包在贝叶斯框架中进行估计,inlabru包建立在非线性模型的INLA(集成嵌套拉普拉斯近似)基础上,便于平滑先验的使用。这种方法具有跨省跨年的优势,减轻了小地区死亡人数的随机波动。结果证明了这种细粒度方法的价值,突出了尽管国家总体上有所改善,但死亡率地理分布不平衡的存在。死亡率劣势集中在中南部和西北部的部分地区,而中北部和东北部的情况相对较好。自2010年以来,这些地域差异有所扩大,具有明显的年龄和性别特征,在男性较年轻和女性较年长时更为明显。未来的工作可能涉及改进按死因或社会经济地位分列的死亡率分析,为更有针对性的公共卫生政策提供信息,以解决意大利各省之间的死亡率差异。
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来源期刊
Spatial Demography
Spatial Demography DEMOGRAPHY-
自引率
0.00%
发文量
12
期刊介绍: Spatial Demography focuses on understanding the spatial and spatiotemporal dimension of demographic processes.  More specifically, the journal is interested in submissions that include the innovative use and adoption of spatial concepts, geospatial data, spatial technologies, and spatial analytic methods that further our understanding of demographic and policy-related related questions. The journal publishes both substantive and methodological papers from across the discipline of demography and its related fields (including economics, geography, sociology, anthropology, environmental science) and in applications ranging from local to global scale. In addition to research articles the journal will consider for publication review essays, book reviews, and reports/reviews on data, software, and instructional resources.
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