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

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.

Keywords: CI, Credible Interval; DA, Discriminatory Accuracy; Equity in health; ICC, Intra Class Correlation; Incidence of Chronic Obstructive Pulmonary Disease; Individual heterogeneity; Intersectionality; MAIHDA, Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy; Multilevel analysis; Respiratory epidemiology; Socioeconomic determinants of health.

Fig. 1

Flow diagram showing the selection of the study population.

Fig. 2

Predicted incidence of Chronic Obstructive Pulmonary Disease in 2011 for people aged 45–65 residing in Sweden on Dec 31st 2010, by intersectional strata. Predictions are based on model 1 multilevel regression analysis with individuals at the first level and intersectional strata at the second level. Main effects and interactive effects are conflated. Intersectional strata were calculated by categories of age, gender, income based on tertiles in the whole population aged 45–65 years, education, civil status and country of birth. Intersectional strata are ordered according to their rank, strata with lowest rank to the left. For identification of the different intersectional strata, see Table 2, Table A1Table A1.

Fig. 3

Incidence of Chronic Obstructive Pulmonary Disease during 2011 for people aged 45–65 residing in Sweden on Dec 31^st 2010, by intersectional strata. Point estimates of predicted incidences based on model 3. Black circles indicate the incidence according to predictions based on the total effect (intersectional effects and main effects) while white circles indicate the incidence according to predictions based on main effects only. The differences between black and white circle depict the interaction effects. Intersectional strata were calculated by categories of age, gender, income based on tertiles in the whole population aged 45–65 years, education, living alone and immigration status. To identify the different intersectional strata, see Table 3 and Table A2 (Appendix).

Fig. 4

Intersectional interaction effects on incidence of Chronic Obstructive Pulmonary Disease during 2011 for people aged 45–65 residing in Sweden on Dec 31^st 2010, by intersectional strata. Point estimates of the incidences attributable to intersectional interaction and their 95% CIs based on model 3. Interaction effects are calculated as the incidence according to the total effect (intersectional effects and main effects) minus incidence according to main effect only, for each intersectional stratum. Intersectional strata were calculated by categories of age, gender, income based on tertiles in the whole population aged 45–65 years, education, living alone and immigration status. Intersectional strata are ordered according to their intersectional interaction effect. To identify the different intersectional strata, see Table 3 and Table A2 (Appendix).