Chronic Obstructive Pulmonary Disease in Sweden: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy

Life course financial mobility and later-life memory function and decline by gender, and race and ethnicity: an intersectional analysis of the US KHANDLE and STAR cohort studies

BACKGROUND

Intersectionality has rarely been considered in research studies of cognitive ageing. We investigated whether life-course financial mobility is differentially associated with later-life memory function and decline across intersectional identities defined by gender, and race and ethnicity.

METHODS

Data were from two harmonised multiethnic cohorts (the Kaiser Healthy Aging and Diverse Life Experiences cohort and the Study of Healthy Aging in African Americans cohort) in northern California, USA (n=2340). Life-course financial mobility, measured using a combination of self-reported financial capital measures in childhood (from birth to age 16 years) and later adulthood (at the cohort baseline) was defined as consistently high, upwardly mobile, downwardly mobile, or consistently low. We clustered individuals into 32 strata representing intersectional identities defined by life-course financial mobility combined with gender, and race and ethnicity. Verbal episodic memory was assessed using the Spanish and English Neuropsychological Assessment Scales over four waves from 2017 to 2023. Adjusted mixed-effects linear regression models were estimated with and without fixed effects of gender, race and ethnicity, and financial mobility, to evaluate whether the random effects of the intersectional identity strata contributed variance to memory beyond individual fixed effects.

FINDINGS

Mean age was 73·6 years (SD 8·1). Of 2340 individuals, 1460 (62·4%) were women, 880 (37·6%) were men, 388 (16·6%) were Asian, 1136 (48·5%) were Black, 334 (14·3%) were Latinx, and 482 (20·6%) were White. Consistently low and downwardly mobile financial capital were strongly negatively associated with later-life memory at baseline (-0·162 SD units [95% CI -0·273 to -0·051] for consistently low and -0·171 [-0·250 to -0·092] for downwardly mobile), but not rate of change over time. Intersectional identities contributed 0·2% of memory variance after accounting for the fixed effects of gender, race and ethnicity, and financial mobility.

INTERPRETATION

Consistently low and downward life-course financial mobility are associated with lower later-life memory function. Intersectional identities defined by financial mobility in addition to gender, and race and ethnicity, contribute negligible additional variance to later-life memory in this study setting.

FUNDING

US National Institute on Aging, US National Institutes of Health.

Intersectionality and Gender-Based Violence: An Empirical Multi-Level Examination of Prevalence and Frequency in Universities and Research Organizations

This article provides a multilevel intersectional analysis of the prevalence and frequency of gender-based violence within universities and other research organizations in Europe. Results show not only the high prevalence of gender-based violence in this context, but also that in contrast to the prevailing discourse, that gender-based violence is not solely a "women's problem", but also a structural issue impacting diverse identities. Data on frequency show that physical and sexual violence usually occurs as isolated incidents, whereas psychological violence and harassment are often repeated.

Intersectional Inequalities in the Transition to Grandparenthood and Cognitive Functioning: A Longitudinal Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy

OBJECTIVES

In aging societies, more people become vulnerable to experiencing cognitive decline. Simultaneously, the role of grandparenthood is central for older adults and their families. Our study investigates inequalities in the level and trajectories of cognitive functioning among older adults, focusing on possible intersectional effects of social determinants and grandparenthood as a life course transition that may contribute to delaying cognitive decline.

METHODS

Using longitudinal data from the Survey of Health, Aging, and Retirement in Europe, we analyzed a sample of 19,953 individuals aged 50-85 without grandchildren at baseline. We applied multilevel analysis of individual heterogeneity and discriminatory accuracy to investigate variation in cognitive functioning across 48 intersectional strata, defined by sex/gender, migration, education, and occupation. We allowed the impact of becoming a grandparent on cognitive functioning trajectories to vary across strata by including random slopes.

RESULTS

Intersectional strata accounted for 17.43% of the overall variance in cognitive functioning, with most of the stratum-level variation explained by additive effects of the stratum-defining characteristics. Transition to grandparenthood was associated with higher cognitive functioning, showing a stronger effect for women. Stratum-level variation in the grandparenthood effect was modest, especially after accounting for interactions between grandparenthood and the stratum-defining variables.

DISCUSSION

This study highlights the importance of social determinants for understanding heterogeneities in older adults' level of cognitive functioning and its association with the transition to grandparenthood. Cumulative disadvantages negatively affect cognitive functioning, hence adopting an intersectional lens is useful to decompose inequalities and derive tailored interventions to promote equal healthy aging.

Intersectional inequalities in health anxiety: multilevel analysis of individual heterogeneity and discriminatory accuracy in the SOMA.SOC study

Background

Intersectional approaches are needed to disaggregate the complex interaction of social identities contributing to (mental) health disparities. Health anxiety represents an overlooked public mental health issue. Therefore, intersectional inequalities in health anxiety were examined using multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA).

Methods

Analyses are based on cross-sectional data of the adult population living in Germany (N = 2,413). Health anxiety was assessed with the Whiteley Index-7. Applying intersectional MAIHDA, health anxiety in the intersectional strata of gender, history of migration, and income was predicted. Discriminatory accuracy was assessed via the intra-class correlation and the proportional change in variance.

Results

Analyses revealed additive social inequalities in health anxiety with greatest impact of low income but no clear intersectional gradient. Most affected by health anxiety were females who immigrated themselves with low income, males whose parent(s) immigrated with low income, and males who immigrated themselves with medium income.

Conclusion

Intersectional approaches contribute to a more comprehensive understanding of (mental) health disparities. In addition to general efforts to counteract health inequalities, combining universal screening and targeted psychotherapeutic treatment seems promising to specifically reduce inequalities in health anxiety.

Clarifications on the intersectional MAIHDA approach: A conceptual guide and response to Wilkes and Karimi (2024)

Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) has been welcomed as a new gold standard for quantitative evaluation of intersectional inequalities, and it is being rapidly adopted across the health and social sciences. In their commentary "What does the MAIHDA method explain?", Wilkes and Karimi (2024) raise methodological concerns with this approach, leading them to advocate for the continued use of conventional single-level linear regression models with fixed-effects interaction parameters for quantitative intersectional analysis. In this response, we systematically address these concerns, and ultimately find them to be unfounded, arising from a series of subtle but important misunderstandings of the MAIHDA approach and literature. Since readers new to MAIHDA may share confusion on these points, we take this opportunity to provide clarifications. Our response is organized around four important clarifications: (1) At what level are the additive main effect variables defined in intersectional MAIHDA models? (2) Do MAIHDA models have problems with collinearity? (3) Why does the Variance Partitioning Coefficient (VPC) tend to be small, and the Proportional Change in Variance (PCV) tend to be large in MAIHDA? and (4) What are the goals of MAIHDA analysis?

A tutorial for conducting intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)

Intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (I-MAIHDA) is an innovative approach for investigating inequalities, including intersectional inequalities in health, disease, psychosocial, socioeconomic, and other outcomes. I-MAIHDA and related MAIHDA approaches have conceptual and methodological advantages over conventional single-level regression analysis. By enabling the study of inequalities produced by numerous interlocking systems of marginalization and oppression, and by addressing many of the limitations of studying interactions in conventional analyses, intersectional MAIHDA provides a valuable analytical tool in social epidemiology, health psychology, precision medicine and public health, environmental justice, and beyond. The approach allows for estimation of average differences between intersectional strata (stratum inequalities), in-depth exploration of interaction effects, as well as decomposition of the total individual variation (heterogeneity) in individual outcomes within and between strata. Specific advice for conducting and interpreting MAIHDA models has been scattered across a burgeoning literature. We consolidate this knowledge into an accessible conceptual and applied tutorial for studying both continuous and binary individual outcomes. We emphasize I-MAIHDA in our illustration, however this tutorial is also informative for understanding related approaches, such as multicategorical MAIHDA, which has been proposed for use in clinical research and beyond. The tutorial will support readers who wish to perform their own analyses and those interested in expanding their understanding of the approach. To demonstrate the methodology, we provide step-by-step analytical advice and present an illustrative health application using simulated data. We provide the data and syntax to replicate all our analyses.

Methodological insights into multilevel analysis of individual heterogeneity and discriminatory accuracy: An empirical examination of the effects of strata configurations on between-stratum variance and of fixed effects across hierarchical levels

This study aims to advance the Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) approach by addressing two key questions. First, it investigates the impact of using increasingly complex combinations of variables to create intersectional strata on between-stratum variance, measured by the variance partitioning coefficients (VPCs). Second, it examines the stability of coefficients for fixed effects across models with an increasing number of hierarchical levels. The analysis is performed using data from a survey of over 42,000 respondents on the prevalence of gender-based violence in European research organisations conducted in 2022. Results indicate that the number of intersectional strata is not significantly related to the proportion of the total variance attributable to the variance between intersectional strata in the MAIHDA approach. Moreover, the coefficients remain relatively stable and consistent across models with increasing complexity, where levels about organisations and countries are added. The analysis concludes that the MAIHDA approach can be flexibly applied for different research purposes, either to better account for structures of power and inequality; or to provide intersectionality-sensitive estimates. The findings underscore the need for researchers to clarify the specific aims of using MAIHDA, whether descriptive or inferential, and highlight the approach's versatility in addressing intersectionality within quantitative research. The study contributes to the literature by offering empirical evidence on the methodological considerations in applying the MAIHDA approach, thereby aiding in its more effective use for intersectional research.

A quantitative approach to the intersectional study of mental health inequalities during the COVID-19 pandemic in UK young adults

PURPOSE

Mental health inequalities across social identities/positions during the COVID-19 pandemic have been mostly reported independently from each other or in a limited way (e.g., at the intersection between age and sex or gender). We aim to provide an inclusive socio-demographic mapping of different mental health measures in the population using quantitative methods that are consistent with an intersectional perspective.

METHODS

Data included 8,588 participants from two British cohorts (born in 1990 and 2000-2002, respectively), collected in February/March 2021 (during the third UK nationwide lockdown). Measures of anxiety and depressive symptomatology, loneliness, and life satisfaction were analysed using Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) models.

RESULTS

We found evidence of large mental health inequalities across intersectional strata. Large proportions of those inequalities were accounted for by the additive effects of the variables used to define the intersections, with some of the largest gaps associated with sexual orientation (with sexual minority groups showing substantially worse outcomes). Additional inequalities were found by cohort/generation, birth sex, racial/ethnic groups, and socioeconomic position. Intersectional effects were observed mostly in intersections defined by combinations of privileged and marginalised social identities/positions (e.g., lower-than-expected life satisfaction in South Asian men in their thirties from a sexual minority and a disadvantaged childhood social class).

CONCLUSION

We found substantial inequalities largely cutting across intersectional strata defined by multiple co-constituting social identities/positions. The large gaps found by sexual orientation extend the existing evidence that sexual minority groups were disproportionately affected by the pandemic. Study implications and limitations are discussed.

Adverse Childhood Experiences and Sexual Orientation: An Intersectional Analysis of Nationally Representative Data

INTRODUCTION

This study compared the prevalence of adverse childhood experiences across intersections of sexual orientation, gender, race/ethnicity, and economic status.

METHODS

Data collected between 1994 and 2018 from 12,519 participants in the National Longitudinal Study of Adolescent to Adult Health were analyzed in 2023 to generate adverse childhood experience prevalence estimates. Unadjusted 1-way ANOVAs and multivariate regressions were performed to compare differences in independent and cumulative adversity measures by sexual orientation, gender, race/ethnicity, and poverty status. A multilevel analysis of individual heterogeneity and discriminatory accuracy was conducted to estimate adversity scores across 24 groups that were stratified by sexual orientation, gender, race/ethnicity, and poverty status.

RESULTS

Adolescents with same-sex attractions and adults who identified with a sexual minority group reported more adverse childhood experiences overall than straight participants, although associations varied by type of adversity. Strikingly, adversity scores were higher among White youth with same-sex attractions than among Black youth with same-sex attractions, among more economically advantaged bisexual adults than among poorer ones, and among poor White participants than among poor Black and Hispanic participants, suggesting that the combination of disadvantaged and marginalized statuses does not necessarily correspond with greater childhood adversity. A multilevel analysis of individual heterogeneity and discriminatory accuracy interaction model showed that sexual orientation and poverty status contributed significant variance to cumulative adversity scores, whereas gender and race/ethnicity did not.

CONCLUSIONS

The results show that disparities in adverse experiences can be more fully and accurately represented when sexual orientation and other social identities are modeled as intersectional configurations. Given that adverse childhood experiences are linked to morbidity and mortality, the findings have salient implications for understanding health disparities that affect population subgroups.

Health inequalities at the intersection of multiple social determinants among under five children residing Nairobi urban slums: An application of multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)

In this analysis we examine through an intersectionality lens how key social determinants of health (SDOH) are associated with health conditions among under-five children (<5y) residing in Nairobi slums, Kenya. We used cross-sectional data collected from Nairobi slums between June and November 2012 to explore how multiple interactions of SDoH shape health inequalities in slums. We applied multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) approach. We constructed intersectional strata for each health condition from combinations of significant SDoH obtained using univariate analyses. We then estimated the intersectional effects of health condition in a series of MAIHDA logistic regression models distinguishing between additive and interaction effects. We quantified discriminatory accuracy (DA) of the intersectional strata by means of the variance partitioning coefficient (VPC) and the area under the receiver operating characteristic curve (AUC-ROC). The total participants were 2,199 <5y, with 120 records (5.5%) dropped because health conditions were recorded as "not applicable". The main outcome variables were three health conditions: 1) whether a child had diarrhea or not, 2) whether a child had fever or not, and 3) whether a child had cough or not in the previous two weeks. We found non-significant intersectional effects for each health condition. The head of household ethnic group was significantly associated with each health condition. We found good DA for diarrhea (VPC = 9.0%, AUC-ROC = 76.6%) an indication of large intersectional effects. However, fever (VPC = 1.9%, AUC-ROC = 66.3%) and cough (VPC = 0.5%, AUC-ROC = 61.8%) had weak DA indicating existence of small intersectional effects. Our study shows pathways for SDoH that affect diarrhea, cough, and fever for <5y living in slums are multiplicative and shared. The findings show that <5y from Luo and Luhya ethnic groups, recent migrants (less than 2 years), and households experiencing CHE are more likely to face worse health outcomes. We recommend relevant stakeholders to develop strategies aimed at identifying these groups for targeted proportionate universalism based on the level of their need.

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.

[Effect of gender equality on mortality from non-communicable diseases]

OBJECTIVE

Relate gender inequalities with the probability of mortality from non-communicable diseases (NCD), in the countries of the world from the year 2000 to 2019, to detect the progress of Target 3.4 of the Sustainable Development Goal 3, to reduce NCD by one third between the ages of 30 and 70 by 2030.

METHOD

Exploratory ecological study on the association between the probability of death from NCD and the gender inequality index (GII) at the global level in 2000, 2015 and 2019. Logistic regression estimation of the risk of not being on track to meet Target 3.4 by 2019 by gender inequality.

RESULTS

The mean probability of death from NCD decreased progressively in all countries. Median 2000/2015/2019: women 20.20/16.58/16; men 26.59/22.45/21.88; total 23.14/20.10/19.23. The risk of not achieving the goal in 2019 is greater in countries with a lower GII than in countries with a higher GII (OR: 2.13; 95% CI: 1.14-3.99; p=0.018), being the higher risk in women (OR: 2.64; 95% CI: 1.40-5.06; p=0.003) than in men (OR: 2.12; 95% CI: 1.44-3.98; p=0.017).

CONCLUSIONS

The risk of deaths from NCD has decreased in both sexes in all countries of the world since the year 2000; but progress is slow, so the greater gender inequality in the countries, there is a greater risk of not achieving the reduction needed to comply with the agreement to reduce mortality from NCD by one third in 2030; this risk being greater in women than in men.

Intersectional analysis of social disparities in type 2 diabetes risk among adults in Germany: results from a nationwide population-based survey

BACKGROUND

Differences in type 2 diabetes risk have been reported for several sociodemographic determinants including sex/gender or socioeconomic status. From an intersectional perspective, it is important to not only consider the role of social dimensions individually, but also their intersections. This allows for a deeper understanding of diabetes risk and preventive needs among diverse population groups.

METHODS

As an intersectionality-informed approach, multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was used in a population-based sample of adults without known diabetes in Germany from the cross-sectional survey "Disease knowledge and information needs- Diabetes mellitus (2017)". Diabetes risk was assessed by the German Diabetes Risk Score (GDRS, range 0-122 points), estimating the individual risk of developing type 2 diabetes within the next 5 years based on established self-reported risk factors. Nesting individuals in 12 intersectional strata defined by combining sex/gender, educational level, and history of migration, we calculated measures to quantify the extent to which individual differences in diabetes risk were explained at strata level, and how much this was due to additive or multiplicative intersectional effects of social determinants.

RESULTS

Drawing on data of 2,253 participants, we found good discriminatory accuracy of intersectional strata (variance partition coefficient = 14.00% in the simple intersectional model). Model-predicted GDRS means varied between 29.97 (corresponding to a "low risk" of < 2%) in women with high educational level and a history of migration, and 52.73 ("still low risk" of 2-5%) in men with low educational level without a history of migration. Variance in GDRS between strata was mainly explained by additive effects of social determinants (proportional change in variance to intersectional interaction model = 77.95%) with being male and having low educational level being associated with higher GDRS. There was no evidence of multiplicative effects in individual strata.

CONCLUSIONS

Type 2 diabetes risk differed between intersectional strata and can to some extent be explained at strata level. The role of intersectional effects was minor and needs to be further investigated. Findings suggest a need for specific preventive measures targeted at large groups with increased diabetes risk, such as men and persons with low educational level.

Intersecting gender identity and racial/ethnic inequities in eating disorder risk factors, symptoms, and diagnosis among U.S. college students: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy

INTRODUCTION

There are documented inequities in eating disorders (EDs) by gender and race/ethnicity, yet, little is known about population-level prevalence of ED risk factors, symptoms, and diagnosis at the intersection of diverse gender and racial/ethnic identities.

METHODS

Data from the Healthy Minds Study 2015-2019 (N = 251,310 U.S. university students) were used in a multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). Participants were nested in 35 intersectional strata given by all combinations of 5 gender and 7 racial/ethnic categories. Multilevel logistic models with participants at level 1 and intersectional strata at level 2 were used to estimate stratum-specific predicted prevalence estimates for self-reported thin-ideal internalization, ED symptoms, and ED diagnosis. The variance partition coefficient (VPC) was calculated to quantify the contextual effect of the strata.

RESULTS

There was considerable heterogeneity in the predicted prevalence of our ED outcomes across the strata (e.g., .3%-18.3% for ED diagnoses). There were large disparities in all three outcomes, with transgender participants of color having a higher predicted prevalence than expected based on the additive effects of gender and race/ethnicity. Moderation by race/ethnicity was also apparent, such that racial/ethnic disparities were wider within the cisgender groups relative to the transgender groups. VPCs indicated that ~10% of the total variance in ED outcomes was due to intersectionality between gender and race/ethnicity, over and above variance due to individual-level differences.

CONCLUSION

Findings suggest that gender and racial/ethnic disparities in EDs are interrelated, underscoring the need to develop preventive interventions centering health equity.

PUBLIC SIGNIFICANCE

Despite evidence that sexism, racism, and cissexism (i.e., anti-transgender prejudice) can impact EDs risk, little research examines the social patterning of EDs at the intersection of diverse gender and racial/ethnic identities. Using data from a sample of 250,000 U.S. university students, this study found that gender and racial/ethnic disparities in eating disorder risk are interrelated, highlighting the need to develop health equity centered preventive interventions.

Overcoming combination fatigue: Addressing high-dimensional effect measure modification and interaction in clinical, biomedical, and epidemiologic research using multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)

Growing interest in precision medicine, gene-environment interactions, health equity, expanding diversity in research, and the generalizability results, requires researchers to evaluate how the effects of treatments or exposures differ across numerous subgroups. Evaluating combination complexity, in the form of effect measure modification and interaction, is therefore a common study aim in the biomedical, clinical, and epidemiologic sciences. There is also substantial interest in expanding the combinations of factors analyzed to include complex treatment protocols (e.g., multiple study arms or factorial randomization), comorbid medical conditions or risk factors, and sociodemographic and other subgroup identifiers. However, expanding the number of subgroup category combinations creates combination fatigue problems, including concerns over small sample size, reduced power, multiple testing, spurious results, and design and analytic complexity. Creative new approaches for managing combination fatigue and evaluating high-dimensional effect measure modification and interaction are needed. Intersectional MAIHDA (multilevel analysis of individual heterogeneity and discriminatory accuracy) has already attracted substantial interest in social epidemiology, and has been hailed as the new gold standard for investigating health inequities across complex intersections of social identity. Leveraging the inherent advantages of multilevel models, a more general multicategorical MAIHDA can be used to study statistical interactions and predict effects across high-dimensional combinations of conditions, with important advantages over alternative approaches. Though it has primarily been used thus far as an analytic approach, MAIHDA should also be used as a framework for study design. In this article, I introduce MAIHDA to the broader health sciences research community, discuss its advantages over conventional approaches, and provide an overview of potential applications in clinical, biomedical, and epidemiologic research.

An Intersectional Approach to Quantifying the Impact of Geographic Remoteness and Health Disparities on Quality-Adjusted Life Expectancy: Application to Australia

OBJECTIVES

An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) is a novel method for exploring the interaction between sociodemographic characteristics that affect health outcomes. This study explores the interaction between geographic remoteness and socioeconomic status on health outcomes in Australia from an intersectional perspective.

METHODS

Data from a cross-sectional survey were matched with data from the Australian Bureau of Statistics and the Australian Institute of Health and Welfare. To explore the effect of health-related quality of life on life expectancy, quality-adjusted life expectancy (QALE) was estimated through applying utility values derived from the EQ-5D-5L to life table data from the Australian Bureau of Statistics. The effect of geographic remoteness on QALE was quantified using multivariable linear regression. An intersectional MAIHDA was performed to explore differences in mean QALE across strata formed by intersections of age, sex, and Socioeconomic Indexes for Areas score.

RESULTS

Based on multivariable linear modeling, QALE declined significantly with increasing remoteness (inner regional, -1.0 years [undiscounted]; remote/very remote, -3.3 years [undiscounted]) (P < .001). In contrast, life expectancy was only significantly different between participants in remote/very remote areas and major cities (β-coefficient, -2.4; 95% CI -4.4 to -0.4; P = .016). No intersectional interaction effects between strata on QALE were found in the MAIHDA.

CONCLUSIONS

QALE has considerable value as a metric for exploring disparities in health outcomes. Given that no intersectional interactions were identified, our findings support broad interventions that target the underlying social determinants of health appropriately reduce disparities versus interventions targeting intersectional interactions.

Socioeconomic disparities in attention deficit hyperactivity disorder (ADHD) in Sweden: An intersectional ecological niches analysis of individual heterogeneity and discriminatory accuracy (IEN-AIHDA)

We aimed (i) to gain a better understanding of the demographic and socioeconomical distribution of ADHD risk in Sweden; and (ii) to contribute to the critical discussion on medicalization, i.e., the tendency to define and treat behavioural and social problems as medical entities. For this purpose, we analysed the risk of suffering from ADHD in the whole Swedish population aged between 5 and 60 years, across 96 different strata defined by combining categories of gender, age, income, and country of birth. The stratified analysis evidenced considerable risk heterogeneity, with prevalence values ranging from 0.03% in high income immigrant women aged 50-59, to 6.18% in middle income immigrant boys aged 10-14. Our study questions the established idea that behavioural difficulties conceptualized as ADHD should be primarily perceived as a neurological abnormality. Rather, our findings suggest that there is a strong sociological component behind how some individuals become impaired and subject to medicalization.

Intersectional Prevalence of Suicide Ideation, Plan, and Attempt Based on Gender, Sexual Orientation, Race and Ethnicity, and Rurality

Importance

Suicidal thoughts and behaviors (STBs) are major public health problems, and some social groups experience disproportionate STB burden. Studies assessing STB inequities for single identities (eg, gender or sexual orientation) cannot evaluate intersectional differences and do not reflect that the causes of inequities are due to structural-level (vs individual-level) processes.

Objective

To examine differences in STB prevalence at the intersection of gender, sexual orientation, race and ethnicity, and rurality.

Design, Setting, and Participants

This cross-sectional study used adult data from the 2015-2019 National Survey on Drug Use and Health (NSDUH), a population-based sample of noninstitutionalized US civilians. Data were analyzed from July 2022 to March 2023.

Main Outcomes and Measures

Outcomes included past-year suicide ideation, plan, and attempt, each assessed with a single question developed for the NSDUH. Intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) models were estimated, in which participants were nested within social strata defined by all combinations of gender, sexual orientation, race and ethnicity, and rurality; outcome prevalence estimates were obtained for each social stratum. Social strata were conceptualized as proxies for exposure to structural forms of discrimination that contribute to health advantages or disadvantages (eg, sexism, racism).

Results

The analytic sample included 189 800 adults, of whom 46.5% were men; 53.5%, women; 4.8%, bisexual; 93.0%, heterosexual; 2.2%, lesbian or gay; 18.8%, Hispanic; 13.9%, non-Hispanic Black; and 67.2%, non-Hispanic White. A total of 44.6% were from large metropolitan counties; 35.5%, small metropolitan counties; and 19.9%, nonmetropolitan counties. There was a complex social patterning of STB prevalence that varied across social strata and was indicative of a disproportionate STB burden among multiply marginalized participants. Specifically, the highest estimated STB prevalence was observed among Hispanic (suicide ideation: 18.1%; 95% credible interval [CrI], 13.5%-24.3%) and non-Hispanic Black (suicide plan: 7.9% [95% CrI, 4.5%-12.1%]; suicide attempt: 3.3% [95% CrI, 1.4%-6.2%]) bisexual women in nonmetropolitan counties.

Conclusions and Relevance

In this cross-sectional study, intersectional exploratory analyses revealed that STB prevalence was highest among social strata including multiply marginalized individuals (eg, Hispanic and non-Hispanic Black bisexual women) residing in more rural counties. The findings suggest that considering and intervening in both individual-level (eg, psychiatric disorders) and structural-level (eg, structural discrimination) processes may enhance suicide prevention and equity efforts.

Geographical and sociodemographic differences in statin dispensation after acute myocardial infarction in Sweden: a register-based prospective cohort study applying analysis of individual heterogeneity and discriminatory accuracy (AIHDA) for basic comparisons of healthcare quality

BACKGROUND

In Sweden, as in many other countries, official monitoring of healthcare quality is mostly focused on geographical disparities in relation to a desirable benchmark. However, current evaluations could be improved by considering: (1) The intersection of other relevant axes of inequity like age, sex, income and migration status; and (2) The existence of individual heterogeneity around averages. Therefore, using an established quality indicator (ie, dispensation of statins after acute myocardial infarction, AMI), we valuate both geographical and sociodemographic inequalities and illustrate how the analysis of individual heterogeneity and discriminatory accuracy (AIHDA) enhances such evaluations.

POPULATION AND METHODS

We applied AIHDA and calculated the area under the receiver operating characteristics curve (AUC) of regional and sociodemographic differences in the statin dispensations of 35 044 patients from 21 Swedish regions and 24 sociodemographic strata who were discharged from the hospital with an AMI diagnosis between January 2011 and December 2013. Following the Swedish National Board of Health and Welfare, we used a benchmark value of 90%.

RESULTS

Dispensation of stains after AMI in Sweden did not reach the desired target of 90%. Regional differences were absent/very small (AUC=0.537) while sociodemographic differences were small (AUC=0.618). Women, especially those with immigrant background and older than 65 years, have the lowest proportions of statin dispensations after AMI.

CONCLUSIONS

As the AUC statistics are small, interventions trying to achieve the benchmark value should be universal. However, special emphasis should nevertheless be directed towards women, especially older women with immigrant backgrounds.

Socioeconomic conditions and children's mental health and quality of life during the COVID-19 pandemic: An intersectional analysis

BACKGROUND

Children and adolescents are highly vulnerable to the impact of sustained stressors during developmentally sensitive times. We investigated how demographic characteristics intersect with socioeconomic dimensions to shape the social patterning of quality of life and mental health in children and adolescents, two years into the COVID-19 pandemic.

METHODS

We used data from the prospective SEROCoV-KIDS cohort study of children and adolescents living in Geneva (Switzerland, 2022). We conducted an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy by nesting participants within 48 social strata defined by intersecting sex, age, immigrant background, parental education and financial hardship in Bayesian multilevel logistic models for poor health-related quality of life (HRQoL, measured with PedsQL) and mental health difficulties (measured with the Strengths and Difficulties Questionnaire).

RESULTS

Among participants aged 2-17 years, 240/2096 (11.5%, 95%CI 10.1-12.9) had poor HRQoL and 105/2135 (4.9%, 95%CI 4.0-5.9) had mental health difficulties. The predicted proportion of poor HRQoL ranged from 3.4% for 6-11 years old Swiss girls with highly educated parents and no financial hardship to 34.6% for 12-17 years old non-Swiss girls with highly educated parents and financial hardship. Intersectional strata involving adolescents and financial hardship showed substantially worse HRQoL than their counterparts. Between-stratum variations in the predicted frequency of mental health difficulties were limited (range 4.4%-6.5%).

CONCLUSIONS

We found considerable differences in adverse outcomes across social strata. Our results suggest that, post-pandemic, interventions to address social inequities in HRQoL should focus on specific intersectional strata involving adolescents and families experiencing financial hardship, while those aiming to improve mental health should target all children and adolescents.

Intersectional inequalities in the transition to grandparenthood and cognitive functioning: A longitudinal Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)

Objectives

With aging societies, more people become vulnerable to experiencing cognitive decline. While normal aging is associated with a deterioration in certain cognitive abilities, little is known about how social determinants intersect to create late-life cognitive functioning inequalities. Simultaneously, the role of grandparenthood is central for older adults and their families. There are indications that social determinants intersect to modulate the effect of the transition to grandparenthood, but further evidence is needed. Our study investigates the relation of transition to grandparenthood with cognitive functioning and explores differences across intersectional strata.

Methods

Using longitudinal data from the Survey of Health, Ageing and Retirement in Europe, we analyzed a sample of 19,953 individuals aged 50-85 without grandchildren at the baseline. We applied Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy to investigate cognitive functioning differences across 48 intersectional strata, defined by sex/gender, migration, education, and occupation. We allowed the impact of becoming a grandparent to vary across strata by including random slopes.

Results

Intersectional strata accounted for 17.43% of the overall variance in cognitive functioning, with most of the stratum-level variation explained by additive effects of the stratum-defining characteristics. Transition to grandparenthood was associated with higher cognitive functioning, with a stronger effect for women. Stratum-level variation in the grandparenthood effect was modest.

Discussion

This study highlights the importance of social determinants for understanding heterogeneities in the association of transition to grandparenthood with cognitive functioning. Adopting an intersectional lens is useful to decompose inequalities and derive tailored interventions to promote equal healthy aging.

The intersections of socioeconomic position, gender, race/ethnicity and nationality in relation to oral conditions among American adults

OBJECTIVE

The objective of the study was to evaluate how gender, socioeconomic position (SEP), race/ethnicity and nationality intersect to structure social inequalities in adult oral health among American adults.

METHODS

Data from adults aged 20 years or over who participated in the National Health and Nutrition Examination Survey (NHANES) 2009-2018 were analysed. The outcomes were poor self-rated oral health and edentulism among all adults (n = 24 541 and 21 446 participants, respectively) and untreated caries and periodontitis among dentate adults (n = 16 483 and 9829 participants, respectively). A multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was conducted for each outcome, by nesting individuals within 48 intersectional strata defined as combinations of gender, SEP, race/ethnicity and nationality. Intersectional measures included the variance partition coefficient (VPC), the proportional change in variance (PCV) and predicted excess probability due to interaction.

RESULTS

Substantial social inequalities in the prevalence of oral conditions among adults were found, which were characterized by high between-stratum heterogeneity and outcome specificity. The VPCs of the simple intersectional model showed that 9.4%-12.7% of the total variance in the presentation of oral conditions was attributed to between-stratum differences. In addition, the PCVs from the simple intersectional model to the intersectional interaction model showed that 84.1%-97.1% of the stratum-level variance in the presentation of oral conditions was attributed to the additive effects of gender, SEP, race/ethnicity and nationality. The point estimates of the predictions for some intersectional strata were suggestive of an intersectional interaction effect. However, the 95% credible intervals were very wide and the estimations inconclusive.

CONCLUSIONS

This analysis highlights the value of the intersectionality framework to understand heterogeneity in social inequalities in oral health. These inequalities were mainly due to the additive effect of the social identities defining the intersectional strata, with no evidence of interaction effects.

Educational Inequalities at the Intersection of Multiple Social Categories: An Introduction and Systematic Review of the Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) Approach

Intersectional approaches have become increasingly important for explaining educational inequalities because they help to improve our understanding of how individual experiences are shaped by simultaneous membership in multiple social categories that are associated with interconnected systems of power, privilege, and oppression. For years, there has been a call in psychological and educational research for quantitative approaches that can account for the intersection of multiple social categories. The present paper introduces the Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) approach, a novel intersectional approach from epidemiology, to study educational inequalities. The MAIHDA approach uses a multilevel model as the statistical framework to define intersectional strata that represent individuals’ membership in multiple social categories. By partitioning the variance within and between intersectional strata, the MAIHDA approach allows identifying intersectional effects at the strata level as well as obtaining information on the discriminatory accuracy of these strata for predicting individual educational outcomes. Compared to conventional quantitative intersectional approaches, MAIHDA analyses have several advantages, including better scalability for higher dimensions, model parsimony, and precision-weighted estimates of strata with small sample sizes. We provide a systematic review of its past application and illustrate its use by analyzing inequalities in reading achievement across 40 unique intersectional strata (combining the social categories of gender, immigrant background, parental education, and parental occupational status) using data from 15-year-old students in Germany (N = 5451). We conclude that the MAIHDA approach is a valuable intersectional tool to study inequalities in educational contexts.

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.

The effects of social determinants on children's health outcomes in Bangladesh slums through an intersectionality lens: An application of multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)

Empirical evidence suggests that the health outcomes of children living in slums are poorer than those living in non-slums and other urban areas. Improving health especially among children under five years old (U5y) living in slums, requires a better understanding of the social determinants of health (SDoH) that drive their health outcomes. Therefore, we aim to investigate how SDoH collectively affects health outcomes of U5y living in Bangladesh slums through an intersectionality lens. We used data from the most recent national Urban Health Survey (UHS) 2013 covering urban populations in Dhaka, Chittagong, Khulna, Rajshahi, Barisal, Sylhet, and Rangpur divisions. We applied multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to estimate the Discriminatory Accuracy (DA) of the intersectional effects estimates using Variance Partition Coefficient (VPC) and the Area Under the Receiver Operating Characteristic Curve (AUC-ROC). We also assessed the Proportional Change in Variance (PCV) to calculate intersectional effects. We considered three health outcomes: cough, fever, and acute respiratory infections (ARI) in U5y.We found a low DA for cough (VPC = 0.77%, AUC-ROC = 61.90%), fever (VPC = 0.87%, AUC-ROC = 61.89%) and ARI (VPC = 1.32%, AUC-ROC = 66.36%) of intersectional strata suggesting that SDoH considered do not collectively differentiate U5y with a health outcome from those with and without a health outcome. The PCV for cough (85.90%), fever (78.42%) and ARI (69.77%) indicates the existence of moderate intersectional effects. We also found that SDoH factors such as slum location, mother's employment, age of household head, and household's garbage disposal system are associated with U5y health outcomes. The variables used in this analysis have low ability to distinguish between those with and without health outcomes. However, the existence of moderate intersectional effect estimates indicates that U5y in some social groups have worse health outcomes compared to others. Therefore, policymakers need to consider different social groups when designing intervention policies aimed to improve U5y health outcomes in Bangladesh slums.

Structural Racism as an Environmental Justice Issue: A Multilevel Analysis of the State Racism Index and Environmental Health Risk from Air Toxics

Communities of color and poor neighborhoods are disproportionately exposed to more air pollution-a pattern known as environmental injustices. Environmental injustices increase susceptibility to negative health outcomes among residents in affected communities. The structural mechanisms distributing environmental injustices in the USA are understudied. Bridging the literatures on the social determinants of health and environmental justice highlights the importance of the environmental conditions for health inequalities and sheds light on the institutional mechanisms driving environmental health inequalities. Employing a critical quantitative methods approach, we use data from an innovative state racism index to argue that systematic racialized inequalities in areas from housing to employment increase outdoor airborne environmental health risks in neighborhoods. Results of a multilevel analysis in over 65,000 census tracts demonstrate that tracts in states with higher levels of state-level Black-white gaps report greater environmental health risk exposure to outdoor air pollution. The state racism index explains four-to-ten percent of county- and state-level variation in carcinogenic risk and noncarcinogenic respiratory system risks from outdoor air toxics. The findings suggest that the disproportional exposure across communities is tied to systematic inequalities in environmental regulation and other structural elements such as housing and incarceration. Structural racism is an environmental justice issue.

Intersecting identities and adolescent depression: Patterns of depressed mood and anhedonia in the past decade

BACKGROUND

Research suggests adolescent depression is increasing and certain adolescents may be uniquely vulnerable. However, limited conceptualizations of identity and time, as well as the reliance on unitary conceptualizations of depression, inhibits a nuanced perspective on these trends. In response, we examined how adolescent depressive symptoms, depressed mood, and anhedonia, vary across intersecting identities over time.

METHODS

Secondary data analysis on the National Survey on Drug Use and Health between 2009 and 2017 was conducted. In total 145,499 nationally representative adolescents (ages 12-17) completed a diagnostic assessment for depression. Lifetime and past year reports of depressive symptoms, depressed mood, and anhedonia were treated as separate variables. A novel, mixed-level model in which participants were nested within identity (defined by one's age, gender, race/ethnicity, poverty level) and time was used to test our aims.

RESULTS

Overall, the relation between depression outcomes and identity did not vary over time (p > .01). Further, identity's impact on depression was approximately ten-fold that of temporal effects. Multiracial, late adolescent, female adolescents were at particular risk. Findings concerning depressed mood and anhedonia were similar across analyses.

LIMITATIONS

All facets of identity (e.g., sexual identity) were not included in the model and a unidimensional measure of poverty may have underestimated its depressogenic influence.

CONCLUSION

Adolescent depression outcomes are mostly consistent across criterial symptom subtypes and time, but vary as a function of identity. Prevention protocols that highlight mechanisms of risk tethered to social identity, and include salient experiences of females, late adolescents, and multiracial youth in particular, need to be prioritized in mental health initiatives.

A capital-based approach to better understand health inequalities: Theoretical and empirical explorations

Background

The persistence of health inequalities may be driven by differences in education and income, but also by other economic and non-economic factors. Our aim was to explore how the association between single-dimensional health and socioeconomic status (SES) changes when including health-related person capital, economic capital, social capital, cultural capital and attractiveness and personality capital.

Methods

We used a capital-based approach to understand health inequalities. It presumes intertwined relationships between broadly measured health ('health-related person capital') and embodied resources ('attractiveness and personality capital') on the one hand, and ESC capital, i.e., economic, social, and cultural resources on the other. We used cross-sectional data on 152,592 participants from the Dutch Lifelines cohort study and estimated correlations using partial least squares structural equation modelling.

Results

The correlation between SES and health-related person capital (r = 0.15) was stronger than the correlations between SES and single-dimensional health (physical and mental health; r = 0.12 and r = 0.04, respectively). ESC capital, combining economic, social and cultural capital, showed a correlation of 0.34 with health-related person capital. This was stronger than the correlation between health-related person capital and economic capital alone (r = 0.19). Lastly, the correlation between health-related person capital and ESC capital increased when health related, attractiveness and personality resources were combined into a single person capital construct (from r = 0.34 to r = 0.49).

Conclusions

This exploratory study shows the empirical interconnectedness of various types of resources, and their potential role in the persistence of health inequalities. Our findings corroborate the idea of considering health as a multidimensional concept, and to extend conventional SES indicators to a broader measurement of economic and non-economic resources.

Physically Constructed and Socially Shaped: Sociomaterial Environment and Walking for Transportation in Later Life

The predictive power of three intersecting environmental dimensions (built structures, social infrastructure, and social capital) on late-life walking was investigated, conceptually based on the ecological framework of place, which posits that a living environment is simultaneously a physical place, a social place, and a set of social bonds. Multilevel models were used to examine the extent to which environments, defined as interactions of the social and material environmental dimensions, reliably predicted walking for transportation among U.S. adults aged 60 years or older in the 2015 National Health Interview Survey (n = 11,180). Random intercepts representing 221 environments showed an intraclass correlation of 21%, indicating high levels of between-environment variance in walking. Social infrastructure had the highest predictive power for walking, followed by material structures and social capital. Synergistic interventions that incorporate the intersecting nature of the sociomaterial environment may be most effective in promoting physical activity in later life.

Effects of social determinants on children's health in informal settlements in Bangladesh and Kenya through an intersectionality lens: a study protocol

INTRODUCTION

Several studies have shown that residents of urban informal settlements/slums are usually excluded and marginalised from formal social systems and structures of power leading to disproportionally worse health outcomes compared to other urban dwellers. To promote health equity for slum dwellers, requires an understanding of how their lived realities shape inequities especially for young children 0-4 years old (ie, under-fives) who tend to have a higher mortality compared with non-slum children. In these proposed studies, we aim to examine how key Social Determinants of Health (SDoH) factors at child and household levels combine to affect under-five health conditions, who live in slums in Bangladesh and Kenya through an intersectionality lens.

METHODS AND ANALYSIS

The protocol describes how we will analyse data from the Nairobi Cross-sectional Slum Survey (NCSS 2012) for Kenya and the Urban Health Survey (UHS 2013) for Bangladesh to explore how SDoH influence under-five health outcomes in slums within an intersectionality framework. The NCSS 2012 and UHS 2013 samples will consist of 2199 and 3173 under-fives, respectively. We will apply Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy approach. Some of SDoH characteristics to be considered will include those of children, head of household, mothers and social structure characteristics of household. The primary outcomes will be whether a child had diarrhoea, cough, fever and acute respiratory infection (ARI) 2 weeks preceding surveys.

ETHICS AND DISSEMINATION

The results will be disseminated in international peer-reviewed journals and presented in events organised by the Accountability and Responsiveness in Informal Settlements for Equity consortium and international conferences. Ethical approval was not required for these studies. Access to the NCSS 2012 has been given by Africa Population and Health Center and UHS 2013 is freely available.

Human papillomavirus vaccination disparities among U.S. college students: An intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA)

We investigated how gender identity, sexual orientation, and race/ethnicity intersect to shape the social epidemiology of HPV vaccination initiation among U.S. college students. Cross-sectional survey data were from the National College Health Assessment (Fall, 2019-Spring, 2020; N = 65,047). We conducted an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy by nesting participants within 36 social strata defined using gender identity, sexual orientation, and race/ethnicity. Bayesian multilevel logistic regression models with random intercepts for social strata were fit for HPV vaccination initiation. Intersectional models adjusted for the additive main effects to isolate intersectional interactions, controlling for age and geographic region. Social strata that included cisgender men, transgender women, and non-binary assigned-male-at-birth individuals and strata that included racial/ethnic minorities had a significantly lower likelihood of HPV vaccination initiation relative to strata including cisgender women and non-Hispanic White individuals, respectively, while strata including lesbian/gay and bisexual/pansexual/queer individuals had a significantly higher likelihood of HPV vaccination initiation relative to strata including heterosexual individuals. We also observed substantial between-stratum inequities in the predicted prevalence of HPV vaccination initiation, with estimates ranging from 59.2% for heterosexual, racial/ethnic minority, cisgender men to 87.1% for bisexual/pansexual/queer, racial/ethnic minority, non-binary assigned-female-at-birth individuals. That being said, the majority of the observed between-stratum variance was driven by additive rather than intersectional interaction effects and the discriminatory accuracy of intersectional stratification with respect to predicting HPV vaccination initiation was low. Collectively, our findings point to a need for more universal guidelines and clinician recommendations that promote HPV vaccine uptake for all adolescents, regardless of race/ethnicity, gender identity, sex-assigned-at-birth, or sexual orientation; however, utilizing an intersectional lens will ensure that resulting public health interventions address inequities and center the needs and experiences of multiply marginalized adolescents.

Decomposing intersectional inequalities in subjective physical and mental health by sex, gendered practices and immigration status in a representative panel study from Germany

BACKGROUND

The mapping of immigration-related health inequalities remains challenging, since immigrant populations constitute a heterogenous socially constructed group whose health experiences differ by social determinants of health. In spite of the increasing awareness that population mobility and its effects on health are highly gendered, an explicit gender perspective in epidemiology is often lacking or limited.

METHODS

To map inequalities in self-reported physical and mental health in Germany at the intersections of sex, gendered practices and immigration status, we used data from the German Socioeconomic Panel (SOEP) and applied an intercategorical intersectional approach conducting multilevel linear regression models. We differentiated between sex (male/female) as reported in the survey and gendered social practices, quantified through a gender score (on a femininity-masculinity continuum).

RESULTS

We included 20,897 participants in our analyses. We saw an intersectional gradient for physical and mental health. Compared to the reference group, i.e. non-immigrant males with masculine gendered practices, physical and mental health steadily decreased in the intersectional groups that did not embody one or more of these social positions. The highest decreases in health were observed in the intersectional group of immigrant females with feminine gendered practices for physical health (-1,36; 95% CI [-2,09; -0,64]) and among non-immigrant females with feminine practices for mental health (-2,51; 95% CI [-3,01; -2,01]).

CONCLUSIONS

Patterns of physical and mental health vary along the intersectional axes of sex, gendered practices and immigration status. These findings highlight the relevance of intersections in describing population health statuses and emphasise the need to take them into account when designing public health policies aiming at effectively reducing health inequalities.

Conceptualizing, Contextualizing, and Operationalizing Race in Quantitative Health Sciences Research

Differences in health outcomes across racial groups are among the most commonly reported findings in health disparities research. Often, these studies do not explicitly connect observed disparities to mechanisms of systemic racism that drive adverse health outcomes among racialized and other marginalized groups in the United States. Without this connection, investigators inadvertently support harmful narratives of biologic essentialism or cultural inferiority that pathologize racial identities and inhibit health equity. This paper outlines pitfalls in the conceptualization, contextualization, and operationalization of race in quantitative population health research and provides recommendations on how to appropriately engage in scientific inquiry aimed at understanding racial health inequities. Race should not be used as a measure of biologic difference, but rather as a proxy for exposure to systemic racism. Future studies should go beyond this proxy use and directly measure racism and its health impacts.VISUAL ABSTRACTAppeared as Annals "Online First" article.

Complicating Narratives of Sexual Minority Mental Health: An Intersectional Analysis of Frequent Mental Distress at the Intersection of Sexual Orientation, Gender Identity, and Race/Ethnicity

Purpose: Research indicates that sexual minority populations experience mental health inequities. However, few studies have examined mental health outcomes in sexual minority populations while including intersecting dimensions of social identity. This study had two objectives: (1) to quantify the prevalence of frequent mental distress among U.S. adults across intersecting social identity categories and (2) to evaluate the contribution of intersectional interactions to observed inequities. Methods: Using data from the Behavioral Risk Factor Surveillance System 2014-2019 (N = 1,024,261), we performed an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (I-MAIHDA). Participants were nested in 45 intersectional groups defined by combining 3 sexual orientation (gay/lesbian, bisexual, and heterosexual), 5 gender identity (transgender women, transgender men, gender nonconforming, cisgender women, and cisgender men), and 3 racial/ethnic (non-Hispanic Black, Hispanic/Latinx, and non-Hispanic White) categories. We estimated the predicted probability of frequent mental distress for each stratum. We then calculated the variance partition coefficient (VPC) and proportional change in variance (PCV). Results: We found that multiply marginalized groups tended to have the highest prevalence of frequent mental distress. Groups with racial/ethnic minority individuals were equally represented among low- and high-prevalence groups. The VPC indicated that slightly over 10% of observed variance in prevalence was attributable to group-level differences, while the PCV revealed that a small but meaningful amount of observed heterogeneity in prevalence was due to intersectional interactions between the dimensions of social identity. Conclusion: I-MAIHDA is a promising method for examining the patterning of sexual orientation-based mental health inequities at the population level.

Potential of Standard Perinatal Data for Measuring Violation of Birth Integrity

Background: Measuring the phenomenon of violation of birth integrity (vBI) (e.g., obstetric violence) relies in part on the availability and content of maternity care providers' data. The population coverage and linkage possibilities that these data provide make for a yet untapped potential. Although vBI is a complex phenomenon best measured with dedicated instruments, we argue that maternity care providers' data could contribute to enhance our knowledge of the manifestations and frequency of vBI, and allow for analyses across different sub-groups of the population. Looking into the German standardized perinatal data, we investigate which variables are relevant to vBI-related research, and how complete their reporting is.

Methods: First, we analyse state-of-the-art frameworks and recommendations, and, for each vBI-related domain, we search for and list corresponding variables in the perinatal data which could contribute to a better understanding of vBI issues. Second, we use an example and analyse the content of perinatal data obtained between 2013 and 2016 in the context of the BaBi birth cohort study set in Bielefeld, Germany. We use descriptive statistics to assess the completeness of the data.

Results: The vBI-related variables can be classified in three main categories: discrimination based on specific patient socio-demographic attributes (e.g., height and weight to calculate BMI before pregnancy, foreign origin), indication for medical interventions (i.e., medicalization-related variables: indication for cesarean sections and induction), and supportive care, in particular the mobilization dimension (e.g., continuous fetal heartbeat monitoring). The data analyses included 876 births, of which 601 were vaginal birth. We found poor reporting on demographic variables in terms of completeness. Medicalization and mobilization variables are better documented, although limited in scope.

Conclusions: Putting more emphasis on the completeness of standardized data could increase their potential for vBI-related research. Perinatal data alone are insufficient to assess vBI, but a broader, theory-informed discussion of indicators to be included in standardized datasets would contribute to capturing the different aspects of integrity violation in a more systematic way and expand the evidence-base on different types of vBI.

Social capital, the miniaturization of community, traditionalism and mortality: A population-based prospective cohort study in southern Sweden

Objectives

To investigate associations between social capital, miniaturization of community and traditionalism and all-cause, cardiovascular (CVD), cancer and other causes mortality.

Study design

Prospective cohort study.

Methods

The 2008 public health survey in Scania in the southernmost part of Sweden was conducted with a postal questionnaire posted to a stratified random sample aged 18–80. The response rate was 54.1%. The baseline survey was linked to 8.3-year prospective public death register data. Analyses were conducted with survival analyses, adjusting for relevant factors.

Results

Among women 37.9% had low social participation and 37.8% low trust. Among men 40.9% had low social participation and 35.7% low trust. Low social capital (low social participation/low trust) and traditionalism (low social participation/high trust) have significantly higher total and cardiovascular mortality among women and men combined and among men, but not among women in the final models. The results for women are not significant in the full models for all-cause, CVD, cancer and all other causes mortality. Miniturization of community (high social participation/low trust) displays no statistically significant associations in the adjusted models. Social participation and trust, respectively, and total mortality show consistent Schoenfeld residuals over 8.3 years.

Conclusions

The associations between low social capital, traditionalism and mortality are stronger for men than for women, and may be partly mediated by health-related behaviors.

•

Combinations of cognitive (trust) and structural (social participation) social capital were analyzed.

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Traditionalism and low social capital are associated higher all-cause and CVD mortality among men.

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High social participation/low trust combination does not differ mortality from high social capital combination.

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It may be possible to analyze social capital using intersectional statistical aproaches.

The Intersections of Ethnicity, Nativity Status and Socioeconomic Position in Relation to Periodontal Status: A Cross-Sectional Study in London, England

The role of migration as a social determinant of periodontitis has been overlooked. Intersectionality theory could help understand how immigration status interacts with other social determinants of health to engender inequalities in periodontitis. The objective of the present study was to evaluate whether ethnicity, nativity status and socioeconomic position intersect to structure social inequalities in periodontal status. Data from 1936 adults in a deprived and multi-ethnic area of London were analysed. The numbers of teeth with probing depth and clinical attachment loss were determined from clinical examinations. A matrix with 51 intersectional strata, defined according to ethnicity, nativity status and education, was created. A cross-classified multilevel analysis, with participants clustered within intersectional social strata, was performed to assess the extent to which individual differences in periodontal measures were at the intersectional strata level. A complex pattern of social inequalities in periodontal status was found, which was characterised by high heterogeneity between strata and outcome-specificity. The variance partition coefficient of the simple intersectional model, which conflated additive and interaction effects, indicated that 3-5% of the observed variation in periodontal measures was due to between-stratum differences. Moreover, the percentual change in variance from the simple intersectional to the intersectional interaction model indicated that 73-74% of the stratum-level variance in periodontal measures was attributed to the additive effects of ethnicity, nativity status and education. This study found modest evidence of intersectionality among ethnicity, nativity status and education in relation to periodontal status.

Population heterogeneity in associations between hormonal contraception and antidepressant use in Sweden: a prospective cohort study applying intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)

OBJECTIVES

From 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.

DESIGN

Observational prospective cohort study using record linkage of national Swedish registers.

SETTING

The population of Sweden.

PARTICIPANTS

All 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 MEASURE

Use of any antidepressant, meaning being dispensed at least one antidepressant (ATC: N06A) during follow-up.

RESULTS

Previously 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.

CONCLUSIONS

Our 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.

Challenging categorical thinking: A mixed methods approach to explaining health inequalities

"Categorical thinking" in social science research has been widely criticised by feminist scholars for conceptualising social categories as natural, de-contextualised, and internally homogeneous. This paper develops and applies a mixed-methods approach to the study of health inequalities, using social categories meaningfully in order to challenge categorical thinking. The approach is demonstrated through a case study of socio-economic (SES) inequalities in maternal healthcare access in Zambia. This paper's approach responds to the research agenda set by intersectional social epidemiologists by considering potential heterogeneity within categories, but also by exploring the context-specific meaning of categories, examining explanations at multiple levels, and interpreting results according to mutually constitutive social processes. The study finds that meso-level institutions, "health service environments", explain a large share of SES inequalities in maternal healthcare access. Women's work, marital status, and levels of "autonomy" have heterogeneous implications for healthcare access across SES categories. Disadvantaged categories and their reproductive behaviours are stigmatised as 'backwards', in contrast to advantaged categories and their behaviours, which are associated with 'modernity' and 'development'. Challenging categorical thinking has important implications for social justice and health, by rejecting framings of a specific category as problematic or non-compliant, highlighting the possibility of change, and emphasising the political and structural nature of progress.

Disparities in adverse childhood experiences by race/ethnicity, gender, and economic status: Intersectional analysis of a nationally representative sample

BACKGROUND

Adverse childhood experiences (ACEs) are disturbingly common and consequential. Priority should be given to identifying populations that bear a disproportionate share of the burden of ACEs, but such disparities have received limited attention to date.

OBJECTIVE

This study analyzes data from the National Longitudinal Study of Adolescent to Adult Health, a nationally representative sample in the U.S., to explore variation in ACEs by race/ethnicity, economic status, and gender.

METHODS

In addition to using conventional statistical methods to generate unadjusted and adjusted estimates, we conduct an intercategorical intersectional analysis of variation in ACEs using multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA).

RESULTS

Descriptively, we find that ACEs are more prevalent overall among the poor than the non-poor, among most racial/ethnic minority groups than non-Hispanic Whites, and among females than males. However, multivariate regression results indicate that gender is not a robust correlate of cumulative adversity and that economic status moderates racial/ethnic differences. MAIHDA models further expose heterogeneity in aggregate ACE scores between intersectional strata representing unique combinations of gender, race/ethnicity, and economic status.

CONCLUSIONS

The MAIHDA results confirm that conclusions based on unadjusted group differences may be spurious. While most variance in ACE scores is explained by additive main effects, accounting for intersections among social categories generates a more complex portrait of inequality. We compare our work to prior studies and discuss potential explanations for and implications of these findings for research on disparities.

Eating-related pathology at the intersection of gender identity and expression, sexual orientation, and weight status: An intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) of the Growing Up Today Study cohorts

The objective of this study was to investigate how gender identity, the overwhelmingly prioritized dimension of social identity/position in eating-related pathology research, intersects with gender expression, sexual orientation, and weight status to structure the social patterning of eating disorders and disordered eating behaviors among young people in the U.S. Data were drawn from the 2010/2011 Growing Up Today Study (GUTS; N = 11,090-13,307). We conducted an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) by nesting participants within social strata defined by intersecting gender identity, gender expression, sexual orientation, and weight status categories in a series of multilevel logistic models for four outcomes (past-year purging, overeating, and binge eating; lifetime eating disorder diagnosis). To illustrate the advantages of intersectional MAIHDA, we compared the results to those from unitary and conventional intersectional analyses. The intersectional MAIHDA revealed a complex social patterning of eating-related pathology characterized by heterogeneity and outcome-specificity. Several multiply marginalized strata (e.g., those including gender nonconforming, sexual minority, and/or larger-bodied girls/women) had disproportionately elevated prevalence, although all estimates were driven by additive effects. Notably, these patterns were obscured within the unitary and conventional intersectional analyses. Future epidemiologic research on eating-related pathology should continue to adopt an intersectional approach through the use of appropriate methodologies.

Intersectional inequalities in mental health across multiple dimensions of inequality in the Swedish adult population

Intersectionality has recently gained traction in health inequality research emphasizing multiple intersecting dimensions of inequality as opposed to the traditional unidimensional approaches. In this study inequalities in mental health were estimated across intersections of gender, income, education, occupation, country of birth, and sexual orientation. The outcomes and inequalities of intersectional strata were disentangled analogously to the possibilities described by intersectionality theory; as a result of either of the two inequality dimensions, as a result of the sum the dimensions, or as a unique outcome not equaling the sum. Furthermore the study examined the discriminatory accuracy of the six inequality dimensions as well as the intersectional space comprising 64 strata. The study population (N = 52,743) consists of a yearly random sample of the Swedish population 26-84 years between 2010 and 2015, from The Health on Equal Terms survey. Mental health was measured through a self-administered General Health Questionnaire (GHQ)-12, and sociodemographics through survey and linked register data. Intersectional inequalities in mental health were estimated for all pairwise combinations of inequality dimensions by joint inequalities, excess intersectional inequalities and referent inequalities. The findings of the study found that the sum of dimensions contributed to the overall (joint) inequality in mental health rather than a reinforced adverse effect of multiple disadvantages or the contribution by a single dimension. Nevertheless, the dimension of income was found to be the most important in terms of relative contribution. The discriminatory accuracy was low indicating that policy action targeting mental health should be universal rather than focusing on particular groups. The results highlight the unpredictable inequality patterns revealed by an intersectional approach, even for a single health outcome and within one country, and illustrate the need for empirical investigations into the actual population patterns in health that appear in the intersections of multiple disadvantages.

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.

Intersectionality in quantitative research: A systematic review of its emergence and applications of theory and methods

BACKGROUND

Intersectionality is a theoretical framework rooted in the premise that human experience is jointly shaped by multiple social positions (e.g. race, gender), and cannot be adequately understood by considering social positions independently. Used widely in qualitative studies, its uptake in quantitative research has been more recent.

OBJECTIVES

To characterize quantitative research applications of intersectionality from 1989 to mid-2020, to evaluate basic integration of theoretical frameworks, and to identify innovative methods that could be applied to health research.

METHODS

Adhering to PRISMA guidelines, we conducted a systematic review of peer-reviewed articles indexed within Scopus, Medline, ProQuest Political Science and Public Administration, and PsycINFO. Original English-language quantitative or mixed-methods research or methods papers that explicitly applied intersectionality theoretical frameworks were included. Experimental studies on perception/stereotyping and measures development or validation studies were excluded. We extracted data related to publication, study design, quantitative methods, and application of intersectionality.

RESULTS

707 articles (671 applied studies, 25 methods-only papers, 11 methods plus application) met inclusion criteria. Articles were published in journals across a range of disciplines, most commonly psychology, sociology, and medical/life sciences; 40.8% studied a health-related outcome. Results supported concerns among intersectionality scholars that core theoretical tenets are often lost or misinterpreted in quantitative research; about one in four applied articles (26.9%) failed to define intersectionality, while one in six (17.5%) included intersectional position components not reflective of social power. Quantitative methods were simplistic (most often regression with interactions, cross-classified variables, or stratification) and were often misapplied or misinterpreted. Several novel methods were identified.

CONCLUSIONS

Intersectionality is frequently misunderstood when bridging theory into quantitative methodology. Further work is required to (1) ensure researchers understand key features that define quantitative intersectionality analyses, (2) improve reporting practices for intersectional analyses, and (3) develop and adapt quantitative methods.

Multimorbidity in Finnish and Swedish speaking Finns; association with daily habits and socioeconomic status - Nordic EpiLung cross-sectional study

Multimorbidity is an emerging public health priority. This study aims to assess the role of lifestyle and socioeconomic status in the prevalence of multimorbidity and chronic diseases by using two language groups that are part of the same genetic subgroup but differ by daily habits. We conducted a cross-sectional survey in 2016 with randomly selected population sample with 4173 responders (52.3%) aged 20-69 years in Western Finland. We included 3864 Finnish participants with Swedish (28.1%) or Finnish (71.9%) as a native language. We used a questionnaire to assess participants' chronic diseases and lifestyle. We determined multimorbidity as a disease count ≥ 2. Finnish speakers were more likely to have a diagnosis of COPD, heart failure, diabetes, reflux disease, chronic kidney failure, and painful conditions than Swedish speakers. The prevalence of multimorbidity was higher for Finnish speakers in the age group of 60-69 years (41.0% vs. 32.0%, p = 0.018) than Swedish speakers. A higher proportion of Finnish speakers smoked, were obese, inactive, and had lower socioeconomic status compared to Swedish speakers. All these factors, in addition to age and female sex, were significant risk factors for multimorbidity. Prevalence of multimorbidity was different in two language groups living in the same area and was associated with differences in lifestyle factors such as smoking, physical inactivity and obesity.

Complex sociodemographic inequalities in consultations for low back pain: lessons from multilevel intersectional analysis

Supplemental Digital Content is Available in the Text.

We found substantial individual heterogeneity in consultation for low back pain that could not be explained by combination of age, sex, education, income, and nativity.

Sociodemographic inequalities in the occurrence of low back pain (LBP) are well-studied. This study aimed to examine complex sociodemographic inequalities in the risk of LBP consultation in the population from a socioeconomical intersectional perspective. Using register data, we identified 458,852 individuals aged 35 to 75 years residing in Skåne in 2013, with no previous LBP consultation since 2006. We created 108 strata using categories of age, sex, education, income, and nativity. With individuals nested within strata, we modelled the absolute risk of LBP consultation during 2014 in a series of multilevel logistic regression models. We quantified discriminatory accuracy (DA) of these variables by computing the variance partition coefficient and area under the receiver operating characteristic curve (AUC). We identified 13,657 (3.0%) people with an LBP consultation. The absolute risk ranged from 2.1% (95% credible interval: 1.9%-2.3%) among young native men with high education and high income to 4.8% (4.3%-5.5%) among young foreign-born women with medium education and low income (2.3-fold relative difference). Discriminatory accuracy of intersectional strata was very low (variance partition coefficient 1.1% (0.7-1.6); and AUC 0.56 [0.55-0.56]). Sex (35.6%) and nativity (19.2%) had the largest contributions in explaining the initially small between-strata variation in risk of LBP. The low DA of the intersectional strata indicates the existence of limited intersectional inequalities in LBP consultation. Therefore, interventions to reduce LBP risk should be universal rather than targeted to specific socioeconomic groups with a higher average risk. Before planning targeted intervention, other risk factors with higher DA need to be identified.

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.

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

OBJECTIVES

Socioeconomic 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.

SETTING

This 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.

OUTCOME

Applying 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.

RESULTS

The 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.

CONCLUSION

A 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.

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.