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

PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0220322 ◽  
Author(s):  
Anna Persmark ◽  
Maria Wemrell ◽  
Sofia Zettermark ◽  
George Leckie ◽  
S. V. Subramanian ◽  
...  
Keyword(s):  
Public Health ◽  
Multilevel Analysis ◽  
Socioeconomic Disparities ◽  
Individual Heterogeneity ◽  
Precision Public Health ◽  
Discriminatory Accuracy

scholarly journals Understanding the complexity of socioeconomic disparities in smoking prevalence in Sweden: a cross-sectional study applying intersectionality theory

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e042323
Author(s):  
Sten Axelsson Fisk ◽  
Martin Lindström ◽  
Raquel Perez-Vicente ◽  
Juan Merlo
Keyword(s):  
Public Health ◽  
Smoking Prevalence ◽  
Health Management ◽  
Educational Achievement ◽  
Smoking Habit ◽  
Household Composition ◽  
Socioeconomic Disparities ◽  
Cross Sectional ◽  
Intersectionality Theory ◽  
Discriminatory Accuracy

ObjectivesSocioeconomic disparities in smoking prevalence remain a challenge to public health. The objective of this study was to present a simple methodology that displays intersectional patterns of smoking and quantify heterogeneities within groups to avoid inappropriate and potentially stigmatising conclusions exclusively based on group averages.SettingThis is a cross-sectional observational study based on data from the National Health Surveys for Sweden (2004–2016 and 2018) including 136 301 individuals. We excluded people under 30 years of age, or missing information on education, household composition or smoking habits. The final sample consisted on 110 044 individuals or 80.7% of the original sample.OutcomeApplying intersectional analysis of individual heterogeneity and discriminatory accuracy (AIHDA), we investigated the risk of self-reported smoking across 72 intersectional strata defined by age, gender, educational achievement, migration status and household composition.ResultsThe distribution of smoking habit risk in the population was very heterogeneous. For instance, immigrant men aged 30–44 with low educational achievement that lived alone had a prevalence of smoking of 54% (95% CI 44% to 64%), around nine times higher than native women aged 65–84 with high educational achievement and living with other(s) that had a prevalence of 6% (95% CI 5% to 7%). The discriminatory accuracy of the information was moderate.ConclusionA more detailed, intersectional mapping of the socioeconomic and demographic disparities of smoking can assist in public health management aiming to eliminate this unhealthy habit from the community. Intersectionality theory together with AIHDA provides information that can guide resource allocation according to the concept proportionate universalism.

scholarly journals Socio-economic disparities in the dispensation of antibiotics in Sweden 2016–2017: An intersectional analysis of individual heterogeneity and discriminatory accuracy

2021 ◽  
pp. 140349482098149
Author(s):  
Maria Wemrell ◽  
Cecilia Lenander ◽  
Kristofer Hansson ◽  
Raquel Vicente Perez ◽  
Katarina Hedin ◽  
...  
Keyword(s):  
Public Health ◽  
Antibiotic Use ◽  
Individual Heterogeneity ◽  
Global Public Health ◽  
Swedish Population ◽  
Medical Practitioners ◽  
Demographic Groups ◽  
Discriminatory Accuracy ◽  
Intersectional Analysis ◽  
Socio Economic Variables

Aims: Antimicrobial resistance presents an increasingly serious threat to global public health, which is directly related to how antibiotic medication is used in society. Actions aimed towards the optimised use of antibiotics should be implemented on equal terms and according to the needs of the population. Previous research results on differences in antibiotic use between socio-economic and demographic groups in Sweden are not entirely coherent, and have typically focused on the effects of singular socio-economic variables. Using an intersectional approach, this study provides a more precise analysis of how the dispensation of antibiotic medication was distributed across socio-economic and demographic groups in Sweden in 2016–2017. Methods: Using register data from a nationwide cohort and adopting an intersectional analysis of individual heterogeneity and discriminatory accuracy, we map the dispensation of antibiotics according to age, sex, country of birth and income. Results: While women and high-income earners had the highest antibiotic dispensation prevalence, no large differences in the dispensation of antibiotics were identified between socio-economic groups. Conclusions: Public-health interventions aiming to support the reduced and optimised use of antibiotics should be directed towards the whole Swedish population rather than towards specific groups. Correspondingly, an increased focus on socio-economic or demographic factors is not warranted in interventions aimed at improving antibiotic prescription patterns among medical practitioners.

scholarly journals Understanding the complexity of socioeconomic disparities in type 2 diabetes risk: a study of 4.3 million people in Sweden

2019 ◽  
Vol 7 (1) ◽  
pp. e000749 ◽  
Author(s):  
Maria Wemrell ◽  
Louise Bennet ◽  
Juan Merlo
Keyword(s):  
Public Health ◽  
Type 2 Diabetes ◽  
Low Income ◽  
Educational Achievement ◽  
Absolute Risk ◽  
Diabetes Risk ◽  
Socioeconomic Disparities ◽  
Heterogeneous Distribution ◽  
Discriminatory Accuracy

ObjectiveInvestigating demographic and socioeconomic factors as intersecting rather than as separate dimensions may improve our understanding of the heterogeneous distribution of type 2 diabetes in the population. However, this complexity has scarcely been investigated and we still do not know the accuracy of these factors for predicting type 2 diabetes. Improved understanding of the demographic and socioeconomic disparities predicting type 2 diabetes risk in the population would contribute to more precise and effective public health interventions.Research design and methodsWe analyzed the risk of type 2 diabetes among 4 334 030 individuals aged 40–84 years who by 2010 had resided in Sweden for at least 5 years. We stratified the study population into 120 strata defined by categories of age, gender, income, education, and immigration status. We calculated measures of absolute risk (prevalence) and relative risk (prevalence ratio), and quantified the discriminatory accuracy of the information for predicting type 2 diabetes in the population.ResultsThe distribution of type 2 diabetes risk in the population was highly heterogeneous. For instance, immigrated men aged 70–79 years with low educational achievement and low income had a risk around 32 times higher than native women aged 40–49 years with high income and high educational achievement (ie, 17.6% vs 0.5%). The discriminatory accuracy of the information was acceptable.ConclusionA more detailed, intersectional mapping of socioeconomic and demographic distribution of type 2 diabetes can assist in public health management aiming to reduce the prevalence of the disease.

scholarly journals Cross-classified Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to evaluate hospital performance: the case of hospital differences in patient survival after acute myocardial infarction

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e036130
Author(s):  
Merida Rodriguez-Lopez ◽  
Juan Merlo ◽  
Raquel Perez-Vicente ◽  
Peter Austin ◽  
George Leckie
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Multilevel Analysis ◽  
Area Under The Curve ◽  
Hospital Performance ◽  
Individual Heterogeneity ◽  
Secondary Outcome ◽  
Discriminatory Accuracy ◽  
Hospital Variation ◽  
Novel Approach

ObjectiveTo describe a novel strategy, Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to evaluate hospital performance, by analysing differences in 30-day mortality after a first-ever acute myocardial infarction (AMI) in Sweden.DesignCross-classified study.Setting68 Swedish hospitals.Participants43 247 patients admitted between 2007 and 2009, with a first-ever AMI.Primary and secondary outcome measuresWe evaluate hospital performance by analysing differences in 30-day mortality after a first-ever AMI using a cross-classified multilevel analysis. We classified the patients into 10 categories according to a risk score (RS) for 30-day mortality and created 680 strata defined by combining hospital and RS categories.ResultsIn the cross-classified multilevel analysis the overall RS adjusted hospital 30-day mortality in Sweden was 4.78% and the between-hospital variation was very small (variance partition coefficient (VPC)=0.70%, area under the curve (AUC)=0.54). The benchmark value was therefore achieved by all hospitals. However, as expected, there were large differences between the RS categories (VPC=34.13%, AUC=0.77)ConclusionsMAIHDA is a useful tool to evaluate hospital performance. The benefit of this novel approach to adjusting for patient RS is that it allowed one to estimate separate VPCs and AUC statistics to simultaneously evaluate the influence of RS categories and hospital differences on mortality. At the time of our analysis, all hospitals in Sweden were performing homogeneously well. That is, the benchmark target for 30-day mortality was fully achieved and there were not relevant hospital differences. Therefore, possible quality interventions should be universal and oriented to maintain the high hospital quality of care.

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