The objective of this analysis is to identify the prevalence of depressive symptoms and its predictors in the national cohort of people living with HIV (PLHIV) in Pakistan. This is a secondary data analysis of the National Stigma Index Study 2.0. We screened PLHIV in the Stigma Index study for depressive symptoms using the Urdu version of the Patient Health Questionnaire (PHQ)-9. We used stepwise multiple linear regression to identify predictors of depressive symptoms. We also explored the moderating effect of stigma faced by PLHIVs while accessing HIV health services on depressive symptoms. Data was analyzed using the Statistical Package for Social Sciences Version 26 and PROCESS MACRO Version 4.2. A total of 1,497 PLHIV participated in the original study. Based on the PHQ-9 depressive symptom categories, 39.89% had no depressive symptoms, 24.42% had mild depressive symptoms, 16.89% had moderate depressive symptoms, 10.17% had moderately severe depressive symptoms, and 8.61% had severe depressive symptoms. Results of multiple linear regression show that being worried to meet basic life needs such as food and shelter in last 12 months (2.188, 95% Confidence interval 3.98-5.68, p < .01), female sex (3.599, 95% CI 2.703-4.49, p < .01), substance use (31.33, 95% CI 2.379-3.88, p < .01), being employed (-1.627, 95% CI -2.36 to -.88, p < .01), being recruited through limited chain referral as opposed to recruitment from HIV service delivery sites (-2.147, 95% CI -3.41 to -.88, p< .01), and doing sex work (1.143, 95% CI .225-2.061, p < .01) were significant predictors of depressive symptoms. There is a high prevalence of depressive symptoms among PLHIV in Pakistan. Inability to meet basic life needs, female sex, substance use, employment, and facing stigma in the healthcare setting were predictors of depression. There is a need of socioeconomic empowerment, stigma reduction in healthcare settings, and a robust screening program for depressive symptoms for PLHIV community in the country.
Copyright: © 2024 Ali et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.