Precision public health: Mapping socioeconomic disparities in opioid dispensations at Swedish pharmacies by Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)

Abstract

Background In light of the opioid epidemic in the United States, there is growing concern about the use of opioids in Sweden as it may lead to misuse and overuse and, in turn, severe public health problems. However, little is known about the distribution of opioid use across different demographic and socioeconomic dimensions in the Swedish general population. Therefore, we applied an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), to obtain an improved mapping of the risk heterogeneity of and socioeconomic inequalities in opioid prescription receipt. Methods and findings Using data from 6,846,106 residents in Sweden aged 18 and above, we constructed 72 intersectional strata from combinations of gender, age, income, cohabitation status, and presence or absence of psychological distress. We modelled the absolute risk (AR) of opioid prescription receipt in a series of multilevel logistic regression models distinguishing between additive and interaction effects. By means of the Variance Partitioning Coefficient (VPC) and the area under the receiver operating characteristic curve (AUC), we quantified the discriminatory accuracy (DA) of the intersectional strata for discerning those who received opioid prescriptions from those who did not. The AR of opioid prescription receipt ranged from 2.77% (95% CI 2.69–2.86) among low-income men aged 18–34, living alone, without psychological distress, to 28.25% (95% CI 27.95–28.56) among medium-income women aged 65 and older, living alone, with psychological distress. In a model that conflated both additive and interaction effects, the intersectional strata had a fair DA for discerning opioid users from non-users (VPC = 13.2%, AUC = 0.68). However, in the model that decomposed total effects into additive and interaction effects, the VPC was very low (0.42%) indicating the existence of small interaction effects for a number of the intersectional strata. Conclusions The intersectional MAIHDA approach aligns with the aims of precision public health, through improving the evidence base for health policy by increasing understanding of both health inequalities and individual heterogeneity. This approach is particularly relevant for socioeconomically conditioned outcomes such as opioid prescription receipt. We have identified intersections of social position within the Swedish population at greater risk for opioid prescription receipt.

Practice of reporting social characteristics when describing representativeness of epidemiological cohort studies – A rationale for an intersectional perspective

“…Finally, epidemiology has gradually moved past estimating population averages towards mapping heterogeneity of disease burden in a population as well as studying heterogeneity of effects ( Merlo, 2014 , 2018 ). MAIHDA, for example, aids to map heterogeneity of disease frequencies among intersectional strata of a population ( Evans et al, 2018 ; Persmark et al, 2019 ). If epidemiological studies, on the other hand, aim at estimating effect heterogeneity across population subgroups, study designs might need to adapt.…”

Non-response in a national health survey in Germany: An intersectionality-informed multilevel analysis of individual heterogeneity and discriminatory accuracy

“…These intersectional strata were additionally stratified by subjective health, rendering 48 strata (scenario 2). The inclusion of subjective health in this analysis is in line with the concept of intersectionality, since healthy bodies or psychological distress might well be related to social privilege or stigma [36][37][38]. As subjective health might represent a location in social power hierarchies, we would argue that an inclusion in this analysis is warranted.…”

An Intersectional Analysis Providing More Precise Information on Inequities in Self-Rated General Health

“…Further, applying an intersectional perspective means directing interest towards dynamics of power and wealth distribution in society, rather than to levels of risk as attributes of individuals or groups, in the interest of facilitating the amelioration of health inequalities through social change (22,23). Accordingly, the intersectional strata constructed in this study should be considered in terms of social contexts (24) rather than as characteristics of individuals. This can mitigate the risk of excessive biomedical reductionism threatening current precision-based public health (25), while reducing the likelihood of 'blaming the victim' as frequently discussed when investigating socioeconomical differences conceptualized at the individual level.…”