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瑞典的慢性阻塞性肺疾病:个体异质性与判别准确性的交叉多层次分析

Chronic Obstructive Pulmonary Disease in Sweden: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy.

作者信息

Axelsson Fisk Sten, Mulinari Shai, Wemrell Maria, Leckie George, Perez Vicente Raquel, Merlo Juan

机构信息

Unit for Social Epidemiology, Faculty of Medicine, Lund University, Sweden.

Centre for Multilevel Modelling, University of Bristol, UK.

出版信息

SSM Popul Health. 2018 Mar 20;4:334-346. doi: 10.1016/j.ssmph.2018.03.005. eCollection 2018 Apr.

Abstract

Socioeconomic, ethnic and gender disparities in Chronic Obstructive Pulmonary Disease (COPD) risk are well established but no studies have applied multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) within an intersectional framework to study this outcome. We study individuals at the first level of analysis and combinations of multiple social and demographic categorizations (i.e., intersectional strata) at the second level of analysis. Here we used MAIHDA to assess to what extent individual differences in the propensity of developing COPD are at the intersectional strata level. We also used MAIHDA to determine the degree of similarity in COPD incidence of individuals in the same intersectional stratum. This leads to an improved understanding of risk heterogeneity and of the social dynamics driving socioeconomic and demographic disparities in COPD incidence. Using data from 2,445,501 residents in Sweden aged 45-65, we constructed 96 intersectional strata combining categories of age, gender, income, education, civil- and migration status. The incidences of COPD ranged from 0.02% for young, native males with high income and high education who cohabited to 0.98% for older native females with low income and low education who lived alone. We calculated the intra-class correlation coefficient (ICC) that informs on the discriminatory accuracy of the categorizations. In a model that conflated additive and interaction effects, the ICC was good (20.0%). In contrast, in a model that measured only interaction effects, the ICC was poor (1.1%) suggesting that most of the observed differences in COPD incidence across strata are due to the main effects of the categories used to construct the intersectional matrix while only a minor share of the differences are attributable to intersectional interactions. We found conclusive interaction effects. The intersectional MAIHDA approach offers improved information to guide public health policies in COPD prevention, and such policies should adopt an intersectional perspective.

摘要

慢性阻塞性肺疾病(COPD)风险中的社会经济、种族和性别差异已得到充分证实,但尚无研究在交叉性框架内应用个体异质性和判别准确性的多层次分析(MAIHDA)来研究这一结果。我们在分析的第一层次研究个体,并在分析的第二层次研究多个社会和人口分类的组合(即交叉阶层)。在这里,我们使用MAIHDA来评估在交叉阶层层面上,个体患COPD倾向的差异程度。我们还使用MAIHDA来确定同一交叉阶层个体中COPD发病率的相似程度。这有助于更好地理解风险异质性以及驱动COPD发病率社会经济和人口差异的社会动态。利用瑞典2445501名45至65岁居民的数据,我们构建了96个交叉阶层,将年龄、性别、收入、教育程度、婚姻和移民状况等类别进行了组合。COPD的发病率从高收入、高学历且同居的年轻本土男性的0.02%到低收入、低学历且独居的老年本土女性的0.98%不等。我们计算了组内相关系数(ICC),以了解分类的判别准确性。在一个将加性效应和交互效应合并的模型中,ICC良好(20.0%)。相比之下,在一个仅测量交互效应的模型中,ICC较差(1.1%),这表明各阶层间观察到的COPD发病率差异大多归因于用于构建交叉矩阵的类别的主效应,而只有一小部分差异可归因于交叉交互作用。我们发现了确凿的交互效应。交叉性MAIHDA方法为指导COPD预防的公共卫生政策提供了更完善的信息,此类政策应采用交叉性视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f98f/5976844/67169b689e86/gr1.jpg

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