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

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Persmark, AnnaLund University,Lunds universitet,Socialepidemiologi,Forskargrupper vid Lunds universitet,Social Epidemiology,Lund University Research Groups,Lund University, Sweden (author)

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

Article/chapterEnglish2019

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2019-08-27
Public Library of Science (PLoS),2019

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LIBRIS-ID:oai:lup.lub.lu.se:6b4ce6e4-80bb-4a42-ad5f-c9b1d51f2ae8
https://lup.lub.lu.se/record/6b4ce6e4-80bb-4a42-ad5f-c9b1d51f2ae8URI
https://doi.org/10.1371/journal.pone.0220322DOI
https://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-117371URI

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Language:English
Summary in:English

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BackgroundIn 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 FindingsUsing 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. ConclusionsThe 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.

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Wemrell, MariaLund University,Lunds universitet,Socialepidemiologi,Forskargrupper vid Lunds universitet,Genusvetenskapliga institutionen,Samhällsvetenskapliga institutioner och centrumbildningar,Samhällsvetenskapliga fakulteten,Social Epidemiology,Lund University Research Groups,Department of Gender Studies,Departments of Administrative, Economic and Social Sciences,Faculty of Social Sciences,Lund University, Sweden(Swepub:lnu)maweai (author)
Zettermark, SofiaLund University,Lunds universitet,Socialepidemiologi,Forskargrupper vid Lunds universitet,Social Epidemiology,Lund University Research Groups,Lund University, Sweden(Swepub:lu)med-szr (author)
Leckie, GeorgeLund University,Lunds universitet,Socialepidemiologi,Forskargrupper vid Lunds universitet,Social Epidemiology,Lund University Research Groups,Lund University, Sweden; University of Bristol, UK(Swepub:lu)ge8681le (author)
Subramanian, S. V.Harvard University,Harvard T.H. Chan School of Public Health, USA (author)
Merlo, JuanLund University,Lunds universitet,Socialepidemiologi,Forskargrupper vid Lunds universitet,Social Epidemiology,Lund University Research Groups,Lund University, Sweden;Region Skåne; Sweden(Swepub:lu)smi-jme (author)
SocialepidemiologiForskargrupper vid Lunds universitet (creator_code:org_t)

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In:PLoS ONE: Public Library of Science (PLoS), s. 1-211932-6203

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By the author/editor: Persmark, Anna; Wemrell, Maria; Zettermark, Sofi ...; Leckie, George; Subramanian, S. ...; Merlo, Juan

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