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

Abstract

ObjectivesThis 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 settingIn 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 measuresTotal mortality (all age groups) and premature mortality (<65 years).ResultsAll 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).ConclusionsThe 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.

Estimation of the Potentially Avoidable Excess Deaths Associated with Socioeconomic Inequalities in Cancer Survival in Germany

“…The development of the GIMD followed the methods used in the UK to create the widely used Indices of Multiple Deprivation. [ 16 ] More information on the creation and calculation of the GIMD and its regional versions can be found elsewhere [ 17 , 18 , 19 , 20 ]. The index uses data of administrative statistics dating virtually all from 2010 on seven deprivation domains (income, employment, education, municipality revenue, social capital, environment, and security).…”

Spatial accessibility of general inpatient care in Germany: an analysis of surgery, internal medicine and neurology

“…Data on the degree of urbanization were obtained from the municipal directory information system of the German Federal Statistical Office with the following categories (1) densely populated, (2) intermediate density, and (3) thinly populated. We used the German Index of Multiple Deprivation (GIMD) on municipality level as of 2010, an established area deprivation index based on a British method, as a proxy for the population's socioeconomic status 25 . We also calculated simpler measures of spatial accessibility, as described in the introduction section: (1) distance to closest hospital and (2) distance to closest five hospitals in order to compare these simpler measures with the gravity model.…”

A Decade of Disparities in Diabetes Technology Use and HbA1c in Pediatric Type 1 Diabetes: A Transatlantic Comparison

“…This methodology is based on the .40 years of experience of indices to measure deprivation at a local level in the U.K. (25). The GIMD methodology has been previously described (16,26). The German index for the reference year 2010 (GIMD 2010) includes aggregated data for the 412 districts of Germany in seven deprivation domains, each weighted differently: income (25%), employment (25%), education (15%), municipal/district revenue (15%), social capital (10%), environment (5%), and security (5%) (16,26).…”