Differences in mental health inequalities based on university attendance: Intersectional multilevel analyses of individual heterogeneity and discriminatory accuracy

Balloo, Kieran; Hosein, Anesa; Byrom, Nicola; Essau, Cecilia A.

doi:10.1016/j.ssmph.2022.101149

Cited by 7 publications

(3 citation statements)

References 62 publications

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“…Using MAIHDA approach we find evidence of moderate intersectional effects estimates on children's health condition based on social attributes. The PCV values (e.g., 85.90%, 78.42% and 69.77% for cough, fever and ARI, respectively) suggest that some differences in U5y health outcomes can be attributed to intersectional effects [51]. Based on the analyses, we have found that some children in certain intersectional strata are more vulnerable compared to others and therefore need a greater level of interventions compared to other groups despite all coming from an already marginalized population of urban slum dwellers.…”

Section: Discussionmentioning

confidence: 99%

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)

Barua

Kibuchi²,

Aktar³

et al. 2023

PLOS Glob Public Health

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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.

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Section: Discussionmentioning

confidence: 99%

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)

Barua

Kibuchi²,

Aktar³

et al. 2023

PLOS Glob Public Health

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“…Risk factors for mental health accumulate through the life course (Lindstrom et al, 2014) and mental health episodes often have onsets and recoveries, and vary in longevity (Weich & Lewis, 1998). More recent studies have used the cross-sectional intersectional MAIHDA approach to identify intersectional inequalities in mental health, in the UK and elsewhere (Balloo et al, 2022;Evans & Erickson, 2019;Moreno-Agostino, Woodhead, et al, 2023). Meanwhile, a separate literature has explored average life course trajectories in mental health, again in a variety of international contexts.…”

Section: Example: Mental Health Trajectories In the Ukmentioning

confidence: 99%

“…This is a relevant example, given previous literature exploring intersectional inequalities in mental health (e.g. Balloo et al, 2022;Evans & Erickson, 2019;Moreno-Agostino, Woodhead, et al, 2023), and a separate literature exploring (average) life course trajectories in mental health (e.g. Bell, 2014;Beller, 2022;Blanchflower & Oswald, 2008).…”

Section: Introductionmentioning

confidence: 99%

Extending intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to study individual longitudinal trajectories, with application to mental health in the UK

Bell,

Evans,

Holman

et al. 2023

Preprint

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The intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) approach is gaining prominence in health sciences and beyond, as a robust quantitative method for identifying intersectional inequalities in a range of individual outcomes. However, it has so far not been applied to longitudinal data, despite the availability of such data, and growing recognition that intersectional social processes and determinants are not static, unchanging phenomena. Drawing on intersectionality and life-course theories, we develop a longitudinal version of the intersectional MAIHDA approach, allowing the analysis not just of intersectional inequalities in static individual differences, but also of life-course trajectories. We discuss the conceptualisation of intersectional groups in this context: how they are changeable over the life-course, appropriate treatment of generational differences, and relevance of the age-period-cohort identification problem. We illustrate the approach with a study of mental health using United Kingdom Household Longitudinal Study data. The results reveal important differences in trajectories between generations and intersectional strata, and show that trajectories are partly multiplicative but mostly additive in their intersectional inequalities. This article provides an important and much needed methodological contribution, enabling rigorous quantitative, longitudinal, intersectional analyses in social epidemiology and beyond.

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Impact of the Economic Crisis on Body Mass Index in Spain: An Intersectional Multilevel Analysis Using a Socioeconomic and Regional Perspective

Hernández-Yumar¹,

Wemrell²,

Abásolo-Alessón³

et al. 2023

Popul Res Policy Rev

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The Great Recession hit Spain deteriorating the living conditions of many Spanish people, increasing the prevalence of several chronic health issues, including obesity, and affecting health inequalities. We analyse the impact of this economic crisis on body mass index (BMI) disparities in Spain, from two perspectives: the socioeconomic and the territorial, through the application of an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy. We use data from the Spanish National Health Surveys of 2006/2007, 2011/2012 and 2016/2017 to build multilevel linear regression models and estimate BMI averages and components of variance. We find a greater increase in the overall average BMI and a widening of the socioeconomic disparities during the hardest years of the crisis. However, these differences decreased when the economic situation in the country began to improve. Both socioeconomic and geographical information contribute to mapping the distribution of BMI in the population. However, according to the ICC values, considering the regional perspective provides a better understanding of the distribution of the BMI, during the period of economic crisis, in the Spanish population. Therefore, regional policies can play an important role in counteracting obesity in times of crisis.

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Differences in mental health inequalities based on university attendance: Intersectional multilevel analyses of individual heterogeneity and discriminatory accuracy

Cited by 7 publications

References 62 publications

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)

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)

Extending intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) to study individual longitudinal trajectories, with application to mental health in the UK

Impact of the Economic Crisis on Body Mass Index in Spain: An Intersectional Multilevel Analysis Using a Socioeconomic and Regional Perspective

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