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

Persmark, Anna LU ; Wemrell, Maria LU ; Zettermark, Sofia LU ; Leckie, George LU ; Subramanian, S. V. and Merlo, Juan LU (2019) In PLoS ONE p.1-21
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... (More)
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.
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author
organization
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type
Contribution to journal
publication status
published
subject
in
PLoS ONE
pages
1 - 21
publisher
Public Library of Science
ISSN
1932-6203
DOI
10.1371/journal.pone.0220322
language
English
LU publication?
yes
id
6b4ce6e4-80bb-4a42-ad5f-c9b1d51f2ae8
date added to LUP
2019-08-15 15:46:03
date last changed
2019-09-07 02:17:41
@article{6b4ce6e4-80bb-4a42-ad5f-c9b1d51f2ae8,
  abstract     = {Background<br/>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. <br/><br/>Methods and Findings<br/>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. <br/>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. <br/><br/>Conclusions<br/>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. <br/>},
  author       = {Persmark, Anna and Wemrell, Maria and Zettermark, Sofia and Leckie, George and Subramanian, S. V. and Merlo, Juan},
  issn         = {1932-6203},
  language     = {eng},
  month        = {08},
  pages        = {1--21},
  publisher    = {Public Library of Science},
  series       = {PLoS ONE},
  title        = {Precision public health: mapping socioeconomic disparities in opioid dispensations at Swedish pharmacies by Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)},
  url          = {http://dx.doi.org/10.1371/journal.pone.0220322},
  year         = {2019},
}