Chronic Obstructive Pulmonary Disease in Sweden: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy.
Chronic Obstructive Pulmonary Disease in Sweden: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy.
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DOI：
10.1016/j.ssmph.2018.03.005
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发表时间：
2018-04
期刊：
影响因子：
--
通讯作者：
Merlo J
中科院分区：
文献类型：
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作者：
Axelsson Fisk S;Mulinari S;Wemrell M;Leckie G;Perez Vicente R;Merlo J
慢性阻塞性肺疾病（COPD）风险的社会经济，种族和性别差异是公认的，但没有研究应用个体异质性和判别准确性（MAIHDA）的交叉框架内的多层次分析来研究这一结果。我们在第一级分析和多种社会和人口分类的组合（即，交叉地层）在第二级分析中。在这里，我们使用MAIHDA来评估在交叉分层水平上发生COPD倾向的个体差异程度。我们还使用MAIHDA来确定同一交叉层中个体COPD发病率的相似程度。这导致了对风险异质性和推动COPD发病率的社会经济和人口统计学差异的社会动力学的更好理解。使用瑞典2，445，501名45-65岁居民的数据，我们构建了96个交叉阶层，结合年龄，性别，收入，教育，公民和移民身份。COPD的发病率范围从0.02%的年轻，本地男性，高收入和高教育谁同居，0.98%的老年本地女性，低收入和低教育谁独自生活。我们计算了类内相关系数（ICC），它反映了分类的区分准确性。在合并加性和互作效应的模型中，ICC良好（20.0%）。相比之下，在仅测量相互作用效应的模型中，ICC较差（1.1%），表明观察到的各分层COPD发病率的大部分差异是由于用于构建交叉矩阵的类别的主要效应，而只有一小部分差异可归因于交叉相互作用。我们发现了决定性的相互作用效应。交叉MAIHDA方法提供了更好的信息，以指导COPD预防的公共卫生政策，这些政策应采用交叉视角。我们使用个体异质性和判别准确性的多水平分析。交叉分层之间的COPD发病率存在明显差异。交叉性改善了COPD发病率社会经济差异的映射。预防措施应基于交叉分析而不是传统分析。
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. We use multilevel analysis of individual heterogeneity and discriminatory accuracy. There is a clear difference in COPD incidence between intersectional strata. Intersectionality improves mapping of socioeconomic differences in COPD incidence. Preventive measures should be based on intersectional rather than classic analyses.