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替代加权方法对多重贫困指数与死亡率的关联是否会改变?来自德国的敏感性分析。

Do alternative weighting approaches for an Index of Multiple Deprivation change the association with mortality? A sensitivity analysis from Germany.

机构信息

Institute of Health Economics and Health Care Management, Helmholtz Zentrum München (GmbH), Neuherberg, Germany.

IBE - Institute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Germany.

出版信息

BMJ Open. 2019 Aug 26;9(8):e028553. doi: 10.1136/bmjopen-2018-028553.

Abstract

OBJECTIVES

This study aimed to assess the impact of using different weighting procedures for the German Index of Multiple Deprivation (GIMD) investigating their link to mortality rates.

DESIGN AND SETTING

In addition to the original (normative) weighting of the GIMD domains, four alternative weighting approaches were applied: equal weighting, linear regression, maximization algorithm and factor analysis. Correlation analyses to quantify the association between the differently weighted GIMD versions and mortality based on district-level official data from Germany in 2010 were applied (n=412 districts).

OUTCOME MEASURES

Total mortality (all age groups) and premature mortality (<65 years).

RESULTS

All correlations of the GIMD versions with both total and premature mortality were highly significant (p<0.001). The comparison of these associations using Williams's t-test for paired correlations showed significant differences, which proved to be small in respect to absolute values of Spearman's rho (total mortality: between 0.535 and 0.615; premature mortality: between 0.699 and 0.832).

CONCLUSIONS

The association between area deprivation and mortality proved to be stable, regardless of different weighting of the GIMD domains. The theory-based weighting of the GIMD should be maintained, due to the stability of the GIMD scores and the relationship to mortality.

摘要

目的

本研究旨在评估使用不同加权程序对德国多重剥夺指数(GIMD)进行加权的影响,以研究其与死亡率之间的关系。

设计和设置

除了 GIMD 领域的原始(规范)加权外,还应用了四种替代加权方法:等权重、线性回归、最大化算法和因子分析。应用相关性分析(n=412 个区),根据德国 2010 年的区县级官方数据,对不同加权版本的 GIMD 与死亡率之间的关联进行量化。

结果

所有 GIMD 版本与总死亡率和早逝率(<65 岁)的相关性均高度显著(p<0.001)。使用配对相关的 Williams t 检验对这些关联进行比较,结果显示存在显著差异,但在斯皮尔曼 rho 的绝对值方面差异较小(总死亡率:在 0.535 到 0.615 之间;早逝率:在 0.699 到 0.832 之间)。

结论

无论 GIMD 领域的加权方式如何,区域贫困与死亡率之间的关联都被证明是稳定的。由于 GIMD 得分的稳定性和与死亡率的关系,应该保持基于理论的 GIMD 加权。

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