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A simple multilevel approach for analysing geographical inequalities in public health reports: The case of municipality differences in obesity

机译:一种简单的多级方法,用于分析公共卫生报告中的地理不平等:肥胖的自治市差异

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摘要

The epidemiological analysis of geographical inequalities in individual outcomes is a fundamental theme in public health research. However, many traditional studies focus on analysing area differences in averages outcomes, disregarding individual variation around such averages. In doing so, these studies may produce misleading information and lead researchers to draw incorrect conclusions. Analysing individual and municipality differences in body mass index (BMI) and overweight/obesity status, we apply an analytical approach based on the multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). This analytical approach may be viewed as a reorganization of existing multilevel modelling concepts in order to provide a systematic approach to simultaneously considering both differences between area averages and individual heterogeneity around those averages. In doing so, MAIHDA provides an improved approach to the quantification and understanding of geographical inequalities as compared with traditional approaches.
机译:个人成果中地理不平等的流行病学分析是公共卫生研究的基本主题。然而,许多传统研究侧重于分析平均结果的区域差异,忽视这些平均值周围的个体变化。在这样做时,这些研究可能会产生误导性信息和引导研究人员,以吸引错误的结论。分析体重指数(BMI)和超重/肥胖状态的个人和市政差异,我们基于个体异质性和鉴别精度(Maihda)的多级分析来应用分析方法。该分析方法可以被视为现有多级建模概念的重组,以便提供系统的方法,同时考虑区域平均值与这些平均值周围的各个异质性之间的差异。在这样做时,Maihda与传统方法相比,提供了对地理不平等的量化和理解的改进方法。

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