Dataset Information

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.

SUBMITTER: Persmark A

PROVIDER: S-EPMC6711500 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Persmark Anna A Wemrell Maria M Zettermark Sofia S Leckie George G Subramanian S V SV Merlo Juan J

PloS one 20190827 8

<h4>Background</h4>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 o ...[more]

PMID: 31454361

Similar Datasets

Project description:BackgroundThe prevalence of teenage pregnancy in Colombia is higher than the worldwide average. The identification of socio-geographical disparities might help to prioritize public health interventions.AimTo describe variation in the probability of teenage maternity across geopolitical departments and socio-geographical intersectional strata in Colombia.MethodsA cross-sectional study based on live birth certificates in Colombia. Teenage maternity was defined as a woman giving birth aged 19 or younger. Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was applied using multilevel Poisson and logistic regression. Two different approaches were used: (1) intersectional: using strata defined by the combination of health insurance, region, area of residency, and ethnicity as the second level (2) geographical: using geopolitical departments as the second level. Null, partial, and full models were obtained. General contextual effect (GCE) based on the variance partition coefficient (VPC) was considered as the measure of disparity. Proportional change in variance (PCV) was used to identify the contribution of each variable to the between-strata variation and to identify whether this variation, if any, was due to additive or interaction effects. Residuals were used to identify strata with potential higher-order interactions.ResultsThe prevalence of teenage mothers in Colombia was 18.30% (95% CI 18.20-18.40). The highest prevalence was observed in Vichada, 25.65% (95% CI: 23.71-27.78), and in the stratum containing mothers with Subsidized/Unaffiliated healthcare insurance, Mestizo, Rural area in the Caribbean region, 29.08% (95% CI 28.55-29.61). The VPC from the null model was 1.70% and 9.16% using the geographical and socio-geographical intersectional approaches, respectively. The higher PCV for the intersectional model was attributed to health insurance. Positive and negative interactions of effects were observed.ConclusionDisparities were observed between intersectional socio-geographical strata but not between geo-political departments. Our results indicate that if resources for prevention are limited, using an intersectional socio-geographical approach would be more effective than focusing on geopolitical departments especially when focusing resources on those groups which show the highest prevalence. MAIHDA could potentially be applied to many other health outcomes where resource decisions must be made.

Project description:Background:While discontinuation of COPD maintenance medication is a known problem, the proportion of patients with discontinuation and its geographical and sociodemographic distribution are so far unknown in Sweden. Therefore, we analyse this question by applying an innovative approach called multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). Patients and Methods:We analysed 49,019 patients categorized into 18 sociodemographic contexts and 21 counties of residence. All patients had a hospital COPD diagnosis and had been on inhaled maintenance medication during the 5 years before the study baseline in 2010. We defined "discontinuation" as the absolute lack of retrieval from a pharmacy of any inhaled maintenance medication during 2011. We performed a cross-classified MAIHDA and obtained the average proportion of discontinuation, as well as county and sociodemographic absolute risks, and compared them with a proposed benchmark value of 10%. We calculated the variance partition coefficient (VPC) and the area under the receiver operating characteristics curve (AUC) to quantify county and sociodemographic differences. To summarize the results, we used a framework with 15 scenarios defined by the size of the differences and the level of achievement in relation to the benchmark value. Results:Around 18% of COPD patients in Sweden discontinued maintenance medication, so the benchmark value was not achieved. There were very small county differences (VPC=0.35%, AUC=0.54). The sociodemographic differences were small (VPC=4.98%, AUC=0.57). Conclusion:Continuity of maintenance medication among COPD patients in Sweden could be improved by reducing the unjustifiably high prevalence of discontinuation. The very small county and small sociodemographic differences should motivate universal interventions across all counties and sociodemographic groups. Geographical analyses should be combined with sociodemographic analyses, and the cross-classified MAIHDA is an appropriate tool to assess health-care quality.

Project description:ObjectivesFrom a reproductive justice framework, we aimed to investigate how a possible association between hormonal contraceptive (HC) and antidepressants use (as a proxy for depression) is distributed across intersectional strata in the population. We aimed to visualise how intersecting power dynamics may operate in combination with HC use to increase or decrease subsequent use of antidepressants. Our main hypothesis was that the previously observed association between HC and antidepressants use would vary between strata, being more pronounced in more oppressed intersectional contexts. For this purpose, we applied an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy approach.DesignObservational prospective cohort study using record linkage of national Swedish registers.SettingThe population of Sweden.ParticipantsAll 915 954 women aged 12-30 residing in Sweden 2010, without a recent pregnancy and alive during the individual 1-year follow-up.Primary outcome measureUse of any antidepressant, meaning being dispensed at least one antidepressant (ATC: N06A) during follow-up.ResultsPreviously mentally healthy HC users had an OR of 1.79 for use of antidepressants compared with non-users, whereas this number was 1.28 for women with previous mental health issues. The highest antidepressant use were uniformly found in strata with previous mental health issues, with highest usage in women aged 24-30 with no immigrant background, low income and HC use (51.4%). The largest difference in antidepressant use between HC users and non-users was found in teenagers, and in adult women of immigrant background with low income. Of the total individual variance in the latent propensity of using antidepressant 9.01% (healthy) and 8.16% (with previous mental health issues) was found at the intersectional stratum level.ConclusionsOur study suggests teenagers and women with immigrant background and low income could be more sensitive to mood effects of HC, a heterogeneity important to consider moving forward.

Project description:Many studies have demonstrated the existence of simple, unidimensional socioeconomic gradients in body mass index (BMI). However, in the present paper we move beyond such traditional analyses by simultaneously considering multiple demographic and socioeconomic dimensions. Using the Spanish National Health Survey 2011-2012, we apply intersectionality theory and multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to analyze 14,190 adults nested within 108 intersectional strata defined by combining categories of gender, age, income, educational achievement and living situation. We develop two multilevel models to obtain information on stratum-specific BMI averages and the degree of clustering of BMI within strata expressed by the intra-class correlation coefficient (ICC). The first model is a simple variance components analysis that provides a detailed mapping of the BMI disparities in the population and measures the accuracy of stratum membership to predict individual BMI. The second model includes the variables used to define the intersectional strata as a way to identify stratum-specific interactions. The first model suggests moderate but meaningful clustering of individual BMI within the intersectional strata (ICC = 12.4%). Compared with the population average (BMI = 26.07 Kg/m2), the stratum of cohabiting 18-35-year-old females with medium income and high education presents the lowest BMI (-3.7 Kg/m2), while cohabiting 36-64-year-old females with low income and low education show the highest BMI (+2.6 Kg/m2). In the second model, the ICC falls to 1.9%, suggesting the existence of only very small stratum specific interaction effects. We confirm the existence of a socioeconomic gradient in BMI. Compared with traditional analyses, the intersectional MAIHDA approach provides a better mapping of socioeconomic and demographic inequalities in BMI. Because of the moderate clustering, public health policies aiming to reduce BMI in Spain should not solely focus on the intersectional strata with the highest BMI, but should also consider whole population polices.

Project description:ObjectivesIndia bears a significant portion of the global tobacco burden with high prevalence of tobacco use. This study examines the socioeconomic patterning of tobacco use and identifies the changing gender and socioeconomic dynamics in light of the Cigarette Epidemic Model.DesignSecondary analyses of second and third National Family Health Survey (NFHS) data.Setting and participantsData were analysed from 201 219 men and 255 028 women over two survey rounds. OUTCOMES AND METHODS: Outcomes included smoking (cigarettes, bidis and pipes/cigar), chewed tobacco (paan masala, gutkha and others) and dual use, examined by education, wealth, living environment and caste. Standardised prevalence and percentage change were estimated. Pooled multilevel models estimated the effect of socioeconomic covariates on the log odds of tobacco use by gender, along with fixed and random parameters.FindingsAmong men (2005-2006), gradients in smoking by education (illiterates: 44% vs postgraduates: 15%) and chewing (illiterates: 47% vs postgraduates: 19%) were observed. Inverse gradients were also observed by wealth, living environment and caste. Chewed tobacco use by women showed inverse socioeconomic status (SES) gradients comparing the illiterates (7.4%) versus postgraduates (0.33%), and poorest (17%) versus richest (2%) quintiles. However, proportional increases in smoking were higher among more educated (postgraduates (98%) vs high schooling only (17%)) and chewing among richer (richest quintile (49%) vs poorest quintile (35%)). Among women, higher educated showed larger declines for smoking-90% (postgraduates) versus 12% (illiterates). Younger men (15-24 years) showed increasing tobacco use (smoking: 123% and chewing: 112%). Older women (35-49 years) show higher prevalence of smoking (3.2%) compared to younger women (0.3%).ConclusionsIndian tobacco use patterns show significant diversions from the Cigarette Epidemic Model-from gender and socioeconomic perspectives. Separate analysis by type is needed to further understand social determinants of tobacco use in India.

Project description:BackgroundIn 2015, Mexico implemented regulatory changes and an electronic system to improve access to prescription opioids. We aimed to investigate trends in opioid dispensing after the implementation of these changes and assess how opioid dispensing varied geographically and by socioeconomic status.MethodsIn this retrospective analysis of prescription medication surveillance data, we analysed dispensing data for group 1 medications (all opioids, including morphine, methadone, hydromorphone, oxycodone, tapentadol, fentanyl, sufentanil, and remifentanil) obtained from the Federal Commission for the Protection against Sanitary Risk database for 32 states and six large metropolitan areas in Mexico. We calculated crude annual opioid prescriptions per 10 000 people at the national, state, and municipal levels. Adapting methods from the report of the Lancet Commission on Palliative Care and Pain Relief, we calculated the need for palliative opioids by state, and then assessed the observed opioid dispensing rates as a percentage of expected need by geographical socioeconomic status. Within the six major metropolitan areas, we mapped the geocoded location of opioid prescriptions and assessed the association between opioid dispensing and socioeconomic status as well as the association between opioid dispensing and time to US border crossing for areas on the US-Mexico border.FindingsBetween June 25, 2015, and Oct 7, 2019, opioid dispensing rates increased by an average of 13% (95% CI 6·8-19·6) per quarter (3 months). The overall national opioid dispensing rate during the study period was 26·3 prescriptions per 10 000 inhabitants. States with a higher socioeconomic status had higher opioid dispensing rates than states with lower socioeconomic status (rate ratio [RR] 1·88, 95% CI 1·33-2·58, p=0·00016) after controlling for the estimated opioid requirement per state, the presence of methadone clinics, and the presence of tertiary hospitals and cancer centres. The same association between opioid dispensing and socioeconomic status was observed in the metropolitan areas, and in those metropolitan areas on the US-Mexico border a 20% decrease (RR 0·80, 95% CI 0·75-0·86) in opioid dispensation was observed per each SD increase (SD 17·1 min) in travel time to the border.InterpretationMeasures introduced by the Mexican federal Government to increase opioid access for patients with palliative care needs were only marginally successful in raising opioid prescription rates. Opioid access should be improved for patients with palliative care needs who live in geographical areas of lower socioeconomic status.FundingUS National Institutes of Health.

Dataset Information

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

Background

Methods and findings

Conclusions

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets