From the Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, PA.
Department of Health Management and Policy, Drexel Dornsife School of Public Health, Philadelphia, PA.
Epidemiology. 2025 Jan 1;36(1):119-125. doi: 10.1097/EDE.0000000000001797. Epub 2024 Sep 27.
Place is a critical determinant of health. Recent novel analyses have explored health outcome estimation for small geographies, such as census tracts, as well as health outcome aggregation to geopolitical geographies with accountable political representatives, such as congressional districts. In one such application, combining these approaches, researchers aggregated census tract estimates of life expectancy at the congressional district level to derive local estimates, but such an approach has not been validated.
Here, we compared two sources and approaches to calculating life expectancy data for Pennsylvania congressional districts. We used 2010-2015 census tract life expectancy estimates from the US Small-area Life Expectancy Estimates Project and dasymetric methods to compute population-weighted life expectancy aggregated to the congressional district level. Using georeferenced Vital Statistics data, we aggregated age-specific census tract death and population counts to congressional districts and used abridged life tables to estimate life expectancy. To validate the dasymetric aggregated estimates we compared absolute differences, assessed the correlation, and created Bland-Altman plots to visualize the agreement between the two measures.
We found strong agreement between congressional district estimates of life expectancy at birth derived using the dasymetric Life Expectancy Estimates Project model-based approach and the Vital Statistics direct estimates approach, though life expectancy at older ages (75 years and older) showed weak correlations.
This validation contributes to our understanding of geospatial aggregation methods for novel geographies including congressional districts. Health outcome data aggregated to the congressional district geography can support congressional policymaking aimed at improving population health outcomes.
地点是健康的关键决定因素。最近的新分析探讨了对小地理区域（如普查区）的健康结果估计，以及对具有可问责政治代表的地缘政治区域（如国会选区）的健康结果聚合。在这样的应用中，研究人员结合了这些方法，将普查区的预期寿命估计值汇总到国会选区一级，以得出当地的估计值，但这种方法尚未得到验证。
在这里，我们比较了两种计算宾夕法尼亚州国会选区预期寿命数据的来源和方法。我们使用了 2010-2015 年美国小区域预期寿命估计项目中的普查区预期寿命估计值和 dasymetric 方法，计算出人口加权的预期寿命，并将其汇总到国会选区一级。使用地理参考的人口统计数据，我们将特定年龄的普查区死亡人数和人口计数汇总到国会选区，并使用简化生命表来估计预期寿命。为了验证 dasymetric 汇总估计值，我们比较了绝对差异，评估了相关性，并创建了 Bland-Altman 图来直观地展示两种方法之间的一致性。
我们发现，使用 dasymetric Life Expectancy Estimates Project 基于模型的方法和 Vital Statistics 直接估计方法得出的国会选区出生时预期寿命的估计值之间存在很强的一致性，尽管较老年龄（75 岁及以上）的预期寿命相关性较弱。
这项验证有助于我们了解包括国会选区在内的新地理区域的地理空间聚合方法。汇总到国会选区地理的健康结果数据可以支持旨在改善人口健康结果的国会决策制定。
