Mapping socio-geographical disparities in the occurrence of teenage maternity in Colombia using multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA).

BACKGROUND: The 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. AIM: To describe variation in the probability of teenage maternity across geopolitical departments and socio-geographical intersectional strata in Colombia. METHODS: A 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. RESULTS: The 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. CONCLUSION: Disparities 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.

Multilevel modelling for measuring interaction of effects between multiple categorical variables: An illustrative application using risk factors for preeclampsia.

BACKGROUND: Measuring multiple and higher-order interaction effects between multiple categorical variables proves challenging. OBJECTIVES: To illustrate a multilevel modelling approach to studying complex interactions. METHODS: We apply a two-level random-intercept linear regression to a binary outcome for individuals (level-1) nested within strata (level-2) defined by all observed combinations of multiple categorical exposure variables. As a pedagogic application, we analyse 36 strata defined by five risk factors of preeclampsia (parity, previous preeclampsia, chronic hypertension, multiple pregnancies, body mass index category) among 652,603 women in the Swedish Medical Birth Registry between 2002 and 2010. RESULTS: The absolute risk of preeclampsia was 4% but was predicted to vary from 1% to 44% across strata. The stratum discriminatory accuracy was 30% according to the variance partition coefficient (VPC) and 0.73 according to the area under the receiver operating characteristic curve (AUC). While the risk heterogeneity across strata was primarily due to the main effects of the categories defining the strata, 5% of the variation was attributable to their two- and higher-way interaction effects. One stratum presented a positive interaction, and two strata presented negative interaction. CONCLUSIONS: Multilevel modelling is an innovative tool for identifying and analysing higher-order interaction effects. Further work is needed to explore how this approach can best be applied to making causal inferences.

Mapping sociodemographic and geographical differences in human papillomavirus non-vaccination among young girls in Sweden.

AIMS: Human papillomavirus (HPV) vaccination plays a key role in the prevention of cervical cancer. Yet, disparities in HPV vaccination in Sweden have persisted. Previous research on such disparities has typically focused on singular sociodemographic variables and measures of average risk. Using a multi-categorical approach and drawing on intersectionality theory, this study aimed to provide a more precise mapping of HPV non-vaccination among girls in different sociodemographic groups and geographical areas in Sweden during 2013-2020. METHODS: Using nationwide register data, we conducted a multi-categorical analysis of individual heterogeneity and discriminatory accuracy complemented by a multilevel geographical analysis. We mapped HPV non-vaccination prevalence across 54 strata defined by parental income, education and country of birth, and urban versus rural place of residence. We also disentangled municipal and regional influences on HPV non-vaccination. RESULTS: HPV non-vaccination was more common in groups with a low income, a low education and an immigration background, whereas among those with an immigration background, the association between income, education and HPV non-vaccination was more complex. Geographical differences were found between municipalities. However, the discriminatory accuracy of the sociodemographic and geographical groups was weak, and 50% of the non-vaccination cases were observed in eight strata, of which some are among those with low risk. CONCLUSIONS: Our findings underscore the importance of universal yet tailored approaches, including providing adequate information about HPV vaccination in Swedish and other languages, and of health-care professionals displaying sensitivity to patients' and parents' questions or needs.

Revisiting socio-economic inequalities in sedentary leisure time in Sweden: An intersectional analysis of individual heterogeneity and discriminatory accuracy (AIHDA).

AIMS: Swedish public health reports have repeatedly provided information about socio-economic inequalities in sedentary leisure time, despite that, in the interest of health equity, physical activity should be equally distributed in the population. Such public health reports, however, neither consider the intersection of multiple socio-demographic factors nor the individual heterogeneity around group averages. Drawing on intersectionality theory, this study aimed to revisit previous findings on sedentary leisure time from Swedish public health surveys and demonstrate how the analysis of individual heterogeneity and discriminatory accuracy (AIHDA) can be used for analysing complex health inequalities. METHODS: Using data from Swedish national public health surveys (2004-2015), we applied the AIHDA to define 72 intersectional groups by categories of age, gender, educational achievement, migration status and household composition. We then calculated (a) the absolute and relative risk of sedentary leisure time and (b) the discriminatory accuracy (DA) of the intersectional grouping. RESULTS: The average risk of sedentary leisure time ranged from 5.8% among native-born, highly educated, young women living alone to 41.0% among immigrated young men, living alone, with low education. The risk was higher in strata comprising immigrated people with low education and lower in strata including native-born, highly educated people. However, the DA of the grouping was poor, indicating a substantial overlap of individual risk between groups. CONCLUSIONS: Using the AIHDA and drawing on intersectionality, this study provides an improved mapping of the socio-economic distribution of sedentary leisure time in Sweden, with the poor DA suggesting universal rather than targeted physical activity interventions.

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

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.

Antidepressant use in Sweden: an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA).

INTRODUCTION: Antidepressants are among the most commonly prescribed drugs in Sweden. However, we lack detailed knowledge on the socioeconomic and demographic distribution of antidepressant use in the population. To fill this gap, we performed an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy. METHODS: Analysing all Swedish residents older than 10 years (n=8,190,990), we measured the absolute risk of antidepressant use across 144 intersectional strata defined by combinations of age, gender, income, country of birth and psychiatric diagnosis. We calculated the strata-specific absolute risk of antidepressant use in a series of multilevel logistic regression models. By means of the variance partitioning coefficient and the area under the receiver operating characteristic curve, we quantified the discriminatory accuracy of the intersectional contexts (i.e. strata) for discerning those who use antidepressants from those who do not. RESULTS: The absolute risk of antidepressant use ranged between 0.93% and 24.78% among those without a psychiatric diagnosis, and between 21.41% and 77.56% among those with a psychiatric diagnosis. Both the variance partitioning coefficient of 41.88% and the area under the receiver operating characteristic curve of 0.81 were considerable. CONCLUSIONS: Besides overt psychiatric diagnoses, our study shows that antidepressant use is mainly conditioned by age, which might express the embodiment of socioeconomic conditions across the individual life course. Our analysis provides a detailed and highly discriminatory mapping of the heterogeneous distribution of antidepressant use in the Swedish population, which may be useful in public health management.

An intersectional analysis providing more precise information on inequities in self-rated health.

BACKGROUND: Intersectionality theory combined with an analysis of individual heterogeneity and discriminatory accuracy (AIHDA) can facilitate our understanding of health disparities. This enables the application of proportionate universalism for resource allocation in public health. Analyzing self-rated health (SRH) in Sweden, we show how an intersectional perspective allows for a detailed mapping of health inequalities while avoiding simplification and stigmatization based on indiscriminate interpretations of differences between group averages. METHODS: We analyzed participants (n=133,244) in 14 consecutive National Public Health Surveys conducted in Sweden in 2004-2016 and 2018. Applying AIHDA, we investigated the risk of bad SRH across 12 intersectional strata defined by gender, income and migration status, adjusted by age and survey year. We calculated odds ratios (with 95% confidence intervals) to evaluate between-strata differences, using native-born men with high income as the comparison reference. We calculated the area under the receiver operating characteristic curve (AU-ROC) to evaluate the discriminatory accuracy of the intersectional strata for identifying individuals according to their SRH status. RESULTS: The analysis of intersectional strata showed clear average differences in the risk of bad SRH. For instance, the risk was seven times higher for immigrated women with low income (OR 7.00 [95% CI 6.14-7.97]) than for native men with high income. However, the discriminatory accuracy of the intersectional strata was small (AU-ROC=0.67). CONCLUSIONS: The intersectional AIHDA approach provides more precise information on the existence (or the absence) of health inequalities, and can guide public health interventions according to the principle of proportionate universalism. The low discriminatory accuracy of the intersectional strata found in this study warrants universal interventions rather than interventions exclusively focused on strata with a higher average risk of bad SRH.

Optical confinement in the nanocoax: coupling to the fundamental TEM-like mode.

The nanoscale coaxial cable (nanocoax) has demonstrated optical confinement in the visible and the near infrared. We report on a novel nanofabrication process which yields optically addressable, sub-µm diameter, and high aspect ratio metal-insulator-metal nanocoaxes made by atomic layer deposition of Pt and Al2O3. We observe sub-diffraction-limited optical transmission via the fundamental, TEM-like mode by excitation with a radially polarized optical vortex beam. Our experimental results are based on interrogation with a polarimetric imager. Finite element method numerical simulations support these results, and their uniaxial symmetry was exploited to model taper geometries with both an electrically large volume, (15λ)3, and a nanoscopic exit aperture, (λ/200)2.

Individual and Contextual Factors Associated With Hazardous Drinking in Spain: Evidence From a National Population-Based Study.

BACKGROUND: Heavy drinking (HD) and binge drinking (BD) exhibit marked differences in their relationships with contextual-level factors imbedded in geographical areas of residence. The objective is to identify sociodemographic factors, both at the individual and at the contextual level, associated with these 2 main hazardous consumption patterns. METHODS: Cross-sectional study using data from the 2011 to 2012 National Health Survey in Spain. The sample included 21,007 individuals ≥15 years of age. HD was defined as an alcohol intake of ≥40 g/d in men and ≥24 g/d in women. BD was defined as the consumption in the previous month of ≥6 alcoholic drinks (men) or ≥5 drinks (women) within 4 to 6 hours. Individual-level variables included sociodemographic factors, urban/rural residence, smoking, and perceived social support. Contextual-level variables covered percentage of population with no schooling, unemployment rate, and hospitality industry-related economic activity, all at the census tract level. We analyzed data using multilevel logistic regression and calculated areas under the curve (AUC). RESULTS: Being male, smoking, high-income, and low perceived social support were associated with both hazardous drinking patterns. Younger individuals were at higher risk for BD but at lower risk for HD. BD was more common among rural than urban dwellers (odds ratios [OR] = 1.35; 95% CI: 1.05 to 1.72), whereas HD was less likely in participants residing in areas with high unemployment rates (OR = 0.62; 95% CI: 0.41 to 0.93). HD was more likely in census tracts with higher levels of hospitality industry activity (OR = 1.74; 95% CI: 1.20 to 2.54). The AUC increased substantially for both HD and BD when the census tract variable was entered in the respective models (reaching 89.5 and 93.3%, respectively). CONCLUSIONS: Except for age, both drinking patterns have similar associations with individual-level variables but disparate links to contextual-level indicators. In both cases, accounting for area of residence substantially increased the ability to discriminate between high-risk drinkers from nonhazardous alcohol consumers.

Does country-level gender equality explain individual risk of intimate partner violence against women? A multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) in the European Union.

BACKGROUND: Gender equality is widely accepted as an important explanatory factor for the occurrence of intimate partner violence (IPV) against women. However, the relationship is not straightforward, as high country-level gender equality is not always associated with lower IPV prevalence. We apply 'multilevel analysis of individual heterogeneity and discriminatory accuracy' (MAIHDA) to (i) quantify the extent to which the country of residence determines individual risk of IPV and (ii) investigate the association between country-level gender equality and individual experience of IPV, and to which extent this association explains the observed between-country differences. METHODS: Using data from the 2012 European Union Agency for Fundamental Rights survey on violence against women we applied MAIHDA to analyse experiences of physical and sexual IPV among 42 000 women living in the EU. We fitted three consecutive models, and calculated specific individual contextual effects (measures of association) as well as the general contextual effects (measures of variance) and the discriminatory accuracy (DA). RESULTS: Our findings show that the relationship between experiences of IPV and country-level gender equality is weak and heterogeneous. The general contextual effect is small and the DA is low, indicating that country boundaries are rather irrelevant for understanding the individual risk of IPV. CONCLUSIONS: Findings from the present study do not imply that that gender equality is unimportant in relation to IPV, but rather that information on country of residence or country-level gender equality does not discriminate very well with regards to individual experiences of IPV in cross-national comparisons.

Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data.

Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster-specific random effects that allow one to partition the total variation in the outcome into between-cluster variation and between-individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time-to-event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time-to-event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between-cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure.

Sociodemographic patterns in pharmacy dispensing of medications for erectile dysfunction in Sweden.

PURPOSE: The purpose of this study is to investigate the relationship between sociodemographic factors and pharmacy dispensing of medications for erectile dysfunction (ED) in the general population of middle-aged and elderly men. By considering a number of medical conditions that could promote or contraindicate use of ED medication, the analysis could help capture prescription patterns that might not be explained by medical needs. METHODS: Individual-level pharmacy dispensing data from 2006 for a population-based cohort of 216,148 men aged 45-79 years in the county Scania, Sweden, were analysed. Multiple logistic regression was applied, and area under the receiver operating characteristic curve (AUC) was calculated to quantify the discriminatory accuracy (DA) of the associations. National trends in pharmacy dispensing of ED medication between 2006 and 2016 were also analysed. RESULTS: Pharmacy dispensing of ED medication increased between 2006 and 2016, particularly among men aged 65-79 years (from 6.8 to 9.2%). Dispensing of ED medication was positively associated with higher socioeconomic position, and divorced and widowed men were more likely to fill a prescription with ED medication than married men. These associations remained after adjusting for medical conditions. The DA of the associations was, however, rather low (AUC = 0.69 among 45-64 year olds and AUC = 0.65 among 65-79 year olds). CONCLUSIONS: Pharmacy dispensing of ED medication seem linked to the individuals socioeconomic position, age and marital status suggesting sociodemographic disparities in the pharmacy dispensing targeting sexual function. However, the low DA of the associations shows the limited capacity of these factors to predict ED medication use at the individual level.

Country of residence, gender equality and victim blaming attitudes about partner violence: a multilevel analysis in EU.

Background: Intimate partner violence against women (IPVAW) is a global and preventable public health problem. Public attitudes, such as victim-blaming, are important for our understanding of differences in the occurrence of IPVAW, as they contribute to its justification. In this paper, we focus on victim-blaming attitudes regarding IPVAW within the EU and we apply multilevel analyses to identify contextual determinants of victim-blaming attitudes. We investigate both the general contextual effect of the country and the specific association between country level of gender equality and individual victim-blaming attitudes, as well as to what extend a possible general contextual effect was explained by county level gender equality. Methods: We analyzed data from 26 800 respondents from 27 member states of the European Union who responded to a survey on public perceptions of domestic violence. We applied multilevel logistic regression analysis and measures of variance (intra-class correlation (ICC)) were calculated, as well as the discriminatory accuracy by calculating the area under the receiver operator characteristic curve. Results: Over and above individual characteristics, about 15% of the individual variance in the propensity for having victim-blaming attitudes was found at the country level, and country level of gender equality did not affect the general contextual effect (i.e. ICC) of the country on individual victim-blaming attitudes. Conclusion: The present study shows that there are important between-country differences in victim-blaming attitudes that cannot be explained by differences in individual-level demographics or in gender equality at the country level. More research on attitudes towards IPVAW is needed.

Intermediate and advanced topics in multilevel logistic regression analysis.

Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis.

Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster-specific random effects which allow one to partition the total individual variance into between-cluster variation and between-individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time-to-event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., 'frailty') Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Absolute rather than relative income is a better socioeconomic predictor of chronic obstructive pulmonary disease in Swedish adults.

BACKGROUND: While psychosocial theory claims that socioeconomic status (SES), acting through social comparisons, has an important influence on susceptibility to disease, materialistic theory says that socioeconomic position (SEP) and related access to material resources matter more. However, the relative role of SEP versus SES in chronic obstructive pulmonary disease (COPD) risk has still not been examined. METHOD: We investigated the association between SES/SEP and COPD risk among 667 094 older adults, aged 55 to 60, residing in Sweden between 2006 and 2011. Absolute income in five groups by population quintiles depicted SEP and relative income expressed as quintile groups within each absolute income group represented SES. We performed sex-stratified logistic regression models to estimate odds ratios and the area under the receiver operator curve (AUC) to compare the discriminatory accuracy of SES and SEP in relation to COPD. RESULTS: Even though both absolute (SEP) and relative income (SES) were associated with COPD risk, only absolute income (SEP) presented a clear gradient, so the poorest had a three-fold higher COPD risk than the richest individuals. While the AUC for a model including only age was 0.54 and 0.55 when including relative income (SES), it increased to 0.65 when accounting for absolute income (SEP). SEP rather than SES demonstrated a consistent association with COPD. CONCLUSIONS: Our study supports the materialistic theory. Access to material resources seems more relevant to COPD risk than the consequences of low relative income.

A GPS-Based Methodology to Analyze Environment-Health Associations at the Trip Level: Case-Crossover Analyses of Built Environments and Walking.

Environmental health studies have examined associations between context and health with individuals as statistical units. However, investigators have been unable to investigate momentary exposures, and such studies are often vulnerable to confounding from, for example, individual-level preferences. We present a Global Positioning System (GPS)-based methodology for segmenting individuals' observation periods into visits to places and trips, enabling novel life-segment investigations and case-crossover analysis for improved inferences. We analyzed relationships between built environments and walking in trips. Participants were tracked for 7 days with GPS receivers and accelerometers and surveyed with a Web-based mapping application about their transport modes during each trip (Residential Environment and Coronary Heart Disease (RECORD) GPS Study, France, 2012-2013; 6,313 trips made by 227 participants). Contextual factors were assessed around residences and the trips' origins and destinations. Conditional logistic regression modeling was used to estimate associations between environmental factors and walking or accelerometry-assessed steps taken in trips. In case-crossover analysis, the probability of walking during a trip was 1.37 (95% confidence interval: 1.23, 1.61) times higher when trip origin was in the fourth (vs. first) quartile of service density and 1.47 (95% confidence interval: 1.23, 1.68) times higher when trip destination was in the fourth (vs. first) quartile of service density. Green spaces at the origin and destination of trips were also associated with within-individual, trip-to-trip variations in walking. Our proposed approach using GPS and Web-based surveys enables novel life-segment epidemiologic investigations.

Testosterone prescribing in the population-a short social epidemiological analysis in Sweden.

PURPOSE: In recent years, there has been an increased interest for use of pharmaceutical testosterone among elderly men. However, it is still scarcely studied if this use is conditioned by socioeconomic factors in the general population of elderly men. METHODS: Using individual-level data from a population-based cohort of men aged 65-84 years in the County Scania, Sweden, we analysed testosterone use in 2006 in relation to demographic and socioeconomic factors by means of multiple logistic regression. We also analysed national data at the ecological level to investigate trends in prescribing between 2006 and 2014. RESULTS: The prevalence of testosterone use in Sweden among 65- to 84-year-old men increased by 83%, from 3.3 per 1000 men in 2006 to 6.0 in 2014. Testosterone use was more than twice as common in men in the highest income quintile compared with those in the lowest (0.68% versus 0.25%, odds ratio 2.69 and 95% confidence interval 1.80-4.02). Besides in the high-income group, testosterone use was highest in 65- to 69-year-old men, divorced men and, specially, in men with a previous hospital diagnose of hypogonadism. CONCLUSIONS: Our findings show socioeconomic inequities in prescription of testosterone. This is a short analysis based on limited data, but because information on this topic is scarce, our analysis adds a relevant piece of evidence and highlights the need for further research.

Ethnic differences in asthma treatment among Swedish adolescents: A multilevel analysis of individual heterogeneity.

AIMS: Adolescents with immigrant or ethnic minority background suffering from asthma receive on average less appropriate anti-asthmatic medication (AAM) than the majority population. However, those findings are based on analyses of differences between group averages which prevents our understanding of individual heterogeneity around the averages. Taking into account individual socioeconomic factors and medical needs, we performed multilevel analysis in order to evaluate if maternal country of birth (MCOB) accurately identifies adolescents with inappropriate AAM use. METHODS: Using the Swedish Medical Birth Register, we identified all singleton children born between 1988 and 1991 who were residing in the country until they turned 17 and had complete information on the study variables. We applied a two-level multilevel logistic regression analysis with 62 MCOBs at the second and 755,894 children at the first level. Adjusting for socioeconomic and medical factors using a risk score, and including the socioeconomic characteristics of the MCOBs, we obtained both measures of association (odds ratio (OR)) and measures of variance (Intra-class correlation (ICC)). RESULTS: Comparing with adolescents born from Swedish mothers, all other children had a lower AAM use, especially those whose mothers were from upper-middle- and low-income countries (OR = 0.47, 95% confidence interval: 0.35-0.61). However, the ICC was low (i.e., ICC ≈ 3%) for both preventive and relief AAM. CONCLUSIONS: MCOB was associated to adolescent use of AAM. However, the small ICC indicates that MCOB is an inaccurate categorization for identifying inappropriate use of AAM among Swedish adolescents.

Appropriate assessment of ethnic differences in adolescent use of psychotropic medication: multilevel analysis of discriminatory accuracy.

OBJECTIVE: In the present study, we used a multilevel approach to investigate the role of maternal country of birth (MCOB) in predicting adolescent use of psychotropic medication in Sweden. DESIGN: Using the Swedish Medical Birth Register we identified all 428,314 adolescents born between 1987 and 1990 and who were residing in Sweden in the year they turned 18. We applied multilevel logistic regression analysis with adolescents (level 1) nested within MCOBs (level 2). Measures of association (odds ratio) and measures of variance (intra-class correlation (ICC)) were calculated, as well as the discriminatory accuracy by calculating the area under the Receiver Operator Characteristic (AU-ROC) curve. RESULTS: In comparison with adolescents with Swedish-born mothers, adolescents with mothers born in upper-middle, lower-middle and low-income countries were less likely to use psychotropic medication. However, the variance between MCOBs was small (ICC = 2.5 in the final model) relative to the variation within MCOBs. This was confirmed by an AU-ROC value of 0.598. CONCLUSIONS: Even though we found associations between MCOB and adolescent use of psychotropic medication, the small ICC and AU-ROC indicate that MCOB appears to be an inaccurate context for discriminating adolescent use of psychotropic medication in Sweden.