Author
Listed:
- Chakrapani, Venkatesan
- Scheim, Ayden I.
- Tsai, Alexander C.
- Shunmugam, Murali
- Sivasubramanian, Murugesan
Abstract
Sexual and gender minority (SGM) populations in India experience substantial psychosocial health burdens, which are likely patterned by intersecting axes of marginalized identities and positions within them. To characterize these intersectional inequalities and inform equitable intervention design, we investigated how psychosocial problems vary across combinations of SGM subgroup, sex work engagement, and socioeconomic status. We analyzed baseline data from the S3 Cohort Study of 799 men who have sex with men (MSM) and 630 transgender women in India. We employed intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (I-MAIHDA) using a Bayesian approach for six binary outcomes. Participants were nested within 16 social strata defined by SGM subgroup, sex work engagement, and socioeconomic status. We quantified between-stratum inequality (Variance Partition Coefficient, VPC), additive vs. interactive patterns (Proportional Change in Variance, PCV), and the discriminatory accuracy of intersectional strata in predicting outcomes (Area Under the Receiver Operating Characteristic Curve, AUC). All psychosocial problems were more prevalent among transgender women than MSM. Between-stratum inequality was strongest for depression (VPC = 9.0%; AUC = 0.66), followed by anxiety (VPC = 6.4%; AUC = 0.65), sexual violence victimization (VPC = 5.9%; AUC = 0.63), drug use (VPC = 5.5%; AUC = 0.62) and alcohol use (VPC = 4.7%; AUC = 0.62). For anxiety, problematic alcohol use, drug use, and sexual violence victimization, inequalities were driven predominantly by additive effects (PCV ∼ 62 to 96%). Depression showed primarily interactive effects (PCV = 43.5%; AUC = 0.66). Transgender women with indigenous identities who had low socioeconomic status and who engaged in sex work comprised the most marginalized stratum, with high adverse outcome prevalence. Health inequalities among SGM individuals are outcome-specific. Anxiety, problematic alcohol use, drug use and violence victimization outcomes follow cumulative disadvantage models with good discriminatory accuracy, while depression demonstrates interactive patterns, requiring targeted interventions.
Suggested Citation
Chakrapani, Venkatesan & Scheim, Ayden I. & Tsai, Alexander C. & Shunmugam, Murali & Sivasubramanian, Murugesan, 2026.
"Psychosocial problems, sexual violence victimization, and substance use among sexual and gender minorities in India: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (I-MAIHDA),"
Social Science & Medicine, Elsevier, vol. 403(C).
Handle:
RePEc:eee:socmed:v:403:y:2026:i:c:s0277953626004685
DOI: 10.1016/j.socscimed.2026.119392
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:403:y:2026:i:c:s0277953626004685. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.