BACKGROUND : Life expectancy at birth (LEB), one of the main indicators of human longevity, has often been used to characterise the health status of a population. Understanding its relationships with the deprivation is key to develop policies and evaluate interventions that are aimed at reducing health inequalities. However, methodological challenges in the analysis of LEB data arise from the fact that different Government agencies often provide spatially aggregated information on LEB and the index of multiple deprivation (IMD) at different spatial scales. Our objective is to develop a geostatistical framework that, unlike existing methods of inference, allows to carry out spatially continuous prediction while dealing with spatial misalignment of the areal-level data. METHODS : We developed a model-based geostatistical approach for the joint analysis of LEB and IMD, when these are available over different partitions of the study region. We model the spatial correlation in LEB and IMD across the areal units using inter-point distances based on a regular grid covering the whole of the study area. The advantages and strengths of the new methodology are illustrated through an analysis of LEB and IMD data from the Liverpool district council. RESULTS : We found that the effect of IMD on LEB is stronger in males than in females, explaining about 63.35% of the spatial variation in LEB in the former group and 38.92% in the latter. We also estimate that LEB is about 8.5 years lower between the most and least deprived area of Liverpool for men, and 7.1 years for women. Finally, we find that LEB, both in males and females, is at least 80% likely to be above the England wide average only in some areas falling in the electoral wards of Childwall, Woolton and Church. CONCLUSION : The novel model-based geostatistical framework provides a feasible solution to the spatial misalignment problem. More importantly, the proposed methodology has the following advantages over existing methods used model LEB: (1) it can deliver spatially continuous inferences using spatially aggregated data; (2) it can be applied to any form of misalignment with information provided at a range of spatial scales, from areal-level to pixel-level.

中文翻译：

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处理空间失调问题以建模剥夺与预期寿命之间的关系：一种基于模型的地统计方法。

背景：出生时的预期寿命（LEB）是人类寿命的主要指标之一，经常被用来表征人群的健康状况。了解其与贫困的关系对于制定旨在减少健康不平等的政策和评估干预措施至关重要。但是，对LEB数据进行分析的方法学挑战来自以下事实：不同的政府机构经常在不同的空间规模上提供LEB的空间汇总信息和多重剥夺指数（IMD）。我们的目标是开发一个地统计框架，与现有的推理方法不同，该框架允许在处理面积级别数据的空间不齐的同时进行空间连续的预测。方法 ：当研究区域的不同分区中可用时，我们为LEB和IMD的联合分析开发了基于模型的地统计方法。我们基于覆盖整个研究区域的规则网格，使用点间距离对LEB和IMD跨区域单位的空间相关性进行建模。通过对利物浦区议会的LEB和IMD数据进行分析，说明了新方法的优势和优势。结果：我们发现，IMD对LEB的影响在男性中比在女性中强，解释了前者中LEB的空间变异约为63.35％，后者是38.92％。我们还估计，在利物浦最贫困和最贫困的地区，男性的LEB降低了约8.5年，而女性则为7.1年。最后，我们发现LEB，无论是男性还是女性，仅在Childwall，Woolton和Church的选举区中的某些地区，该比例至少有80％可能高于英格兰平均水平。结论：基于模型的新型地统计框架为空间失准问题提供了可行的解决方案。更重要的是，与LEB模型所使用的现有方法相比，所提出的方法具有以下优点：（1）它可以使用空间汇总数据来传递空间连续的推论；（2）它可以应用于从面积级别到像素级别的一系列空间尺度上提供的信息的任何不对齐形式。基于模型的新型地统计框架为空间失调问题提供了可行的解决方案。更重要的是，与LEB模型所使用的现有方法相比，所提出的方法具有以下优点：（1）它可以使用空间汇总数据来传递空间连续的推论；（2）它可以应用于从面积级别到像素级别的一系列空间尺度上提供的信息的任何不对齐形式。基于模型的新型地统计框架为空间失调问题提供了可行的解决方案。更重要的是，与LEB模型所使用的现有方法相比，所提出的方法具有以下优点：（1）它可以使用空间汇总数据来传递空间连续的推论；（2）它可以应用于从面积级别到像素级别的一系列空间尺度上提供的信息的任何不对齐形式。