TB Research

Co-Occurring Risk Factors for Tuberculosis Preventive Treatment Non-Adherence Among People Living With HIV in Ethiopia: A Latent Class Analysis.

Edao Sinba Etu, Jet Fransen, Biftu Geda, Kemal Ahmed Kuti, Anteneh Fikrie, Mark Spigt

Tropical medicine & international health : TM & IH · 2026-05

Abstract

OBJECTIVE: Non-adherence to tuberculosis preventive treatment (TPT) among people living with HIV (PLHIV) is a critical issue in Ethiopia and other Sub-Saharan African countries, where both TB and HIV burdens are high. To reduce TPT non-adherence among PLHIV, it is crucial to identify those at risk and implement targeted interventions. Therefore, the main objective is to identify subgroups based on co-occurring risk factors for non-adherence and examine their association with TPT adherence.

METHODS: A cross-sectional study was conducted at selected health centres and hospitals in West Arsi, Ethiopia. Data from 390 PLHIV were collected through structured questionnaires administered via face-to-face interviews. Latent class analysis (LCA) was used to identify distinct subgroups, defined by risk factors for non-adherence, among PLHIV. Maximum Likelihood adjustment method was used to predict adherence outcome based on the identified latent classes.

RESULTS: The overall prevalence rate of adherence in PLHIV was 60%. Two distinct latent classes emerged (prevalence rate noted): a "Lower risk of non-adherence" class (63%), and a "Higher risk of non-adherence" class (37%). PLHIV in the "Higher risk of non-adherence" class endorsed higher probabilities of each of the considered risk factors, particularly regarding perceiving the relationship with the healthcare provider and distance to the health facility as barriers, and were nearly twice as likely to be non-adherent compared to those in the "Lower risk of non-adherence" class.

CONCLUSIONS: The findings emphasize the importance of considering co-occurring risk factors for non-adherence and tailoring interventions accordingly. This study suggests specific practical implications: for example, screening tools assessing non-adherence risk, health providers training programs and strengthening of community-based primary care.