Centre of Studies in Geography and Spatial Planning (CEGOT), Department of Geography and Tourism, University of Coimbra, 3004-530, Coimbra, Portugal.
Faculty of Health, Medicine and Life Sciences (FHML), Care and Public Health Research Institute (CAPHRI), Department of Health, Ethics and Society, Maastricht University, Maastricht, The Netherlands.
Popul Health Metr. 2019 Aug 7;17(1):11. doi: 10.1186/s12963-019-0188-6.
The ability to measure regional health inequalities across Europe and to build adequate population health indices depends significantly on the availability of reliable and comparable data at the regional level. Within the scope of the EU-funded project EURO-HEALTHY, a Population Health Index (PHI) was built. This model aggregates 39 indicators considered relevant by experts and stakeholders to evaluate and monitor population health on the regional level within the European Union (269 regions). The aim of this research was to assess the data availability for those indicators. As a subsequent aim, an adequate protocol to overcome issues arising from missing data will be presented, as well as key messages for both national and European statistical authorities meant to improve data collection on population health.
The methodology for the study includes three consecutive phases: (i) assessing the data availability for the respective indicators at the regional level for the last year available (ii) applying a protocol for missing data and completing the database and (iii) developing a scoring system ranging from 0 (no data available; worst) to 1 (all data available; best) to evaluate the availability of data by indicator and EU region.
Although the missing data on the set of the PHI indicators was significant, the mean availability score for the EURO-HEALTHY PHI indicators is 0.8 and the regional availability score is 0.7, which reveal the strength of the indicators as well as the data completeness protocol for missing data.
This study provides a comprehensive data availability assessment for population health indicators from multiple areas of concern, at the EU regional level. The results highlight that the data completeness protocol and availability scores are suitable tools to apply on any indicator's data source mapping. It also raises awareness to the urgent need for sub-national data in several domains and for closing the data gaps between and within countries. This will require policies clearly focused on improving equity between regions and a coordinated effort from the producers of data (the EU28 national statistics offices and EUROSTAT) and the stakeholders who design policies at EU, regional and local level.
衡量欧洲各地的区域健康不平等，并构建适当的人口健康指数，在很大程度上取决于在区域层面上是否能获得可靠和可比的数据。在欧盟资助的项目 EURO-HEALTHY 范围内，构建了一个人口健康指数（PHI）。该模型汇总了 39 个指标，这些指标是专家和利益攸关方认为与评估和监测欧盟范围内的区域人口健康相关的指标（269 个地区）。本研究的目的是评估这些指标的数据可用性。作为后续目标，将提出一种解决缺失数据问题的适当方案，并为国家和欧洲统计当局提供重要信息，以改善人口健康数据的收集。
该研究的方法包括三个连续阶段：（一）评估上一年度可获得的各区域层面相关指标的数据可用性；（二）应用缺失数据方案并完成数据库；（三）开发评分系统，范围从 0（无数据可用；最差）到 1（所有数据可用；最好），以评估指标和欧盟区域的数据可用性。
尽管 PHI 指标集中的缺失数据较多，但 EURO-HEALTHY PHI 指标的平均可用性评分为 0.8，欧盟区域的平均可用性评分为 0.7，这反映了指标的优势以及缺失数据的完整性协议。
本研究对欧盟区域多个关注领域的人口健康指标进行了全面的数据可用性评估。研究结果突出表明，数据完整性协议和可用性评分是适用于任何指标数据源映射的工具。它还使人们意识到在多个领域需要地方数据，并需要缩小国家之间和国家内部的数据差距。这将需要政策明确侧重于改善地区间的公平性，并需要数据提供者（欧盟 28 个国家统计局和欧盟统计局）和在欧盟、地区和地方各级制定政策的利益攸关方进行协调努力。
