Khoidar Amirus
Department of Public Health, Faculty of Health Sciences, Malahayati University,Bandar LampungCity, Lampung, Postal Code 35152,Indonesia

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Anti-Tuberculosis Drug Resistance Patterns In Patients With Pulmonary Tuberculosis Khoidar Amirus; Syafik Arisandi; Shaharuddin Shaharuddin
Jurnal Ilmiah Kesehatan Masyarakat : Media Komunikasi Komunitas Kesehatan Masyarakat Vol 18 No 2 (2026): JIKM Vol 18, Issue 2, May 2026
Publisher : Public Health Undergraduate Program, Faculty of Health Science, Universitas Pembangunan Nasional Veteran Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52022/jikm.v18i2.826

Abstract

Background: In 2022, Indonesia reported a pulmonary tuberculosis (PTB) incidence rate of 354 per 100,000 population, with an estimated 24,666 cases of drug-resistant pulmonary tuberculosis (DR-TB). Nationally, DR-TB case detection coverage reached 50.8%, with 12,531 patients notified—an increase of 17% from the previous year. Method: This study aimed to examine patterns of Anti-Tuberculosis Drug (ATD) resistance by analyzing internal host-related risk factors using an analytical observational study with a case-control design. The dependent variable was ATD resistance status (resistant and non-resistant). Independent variables included treatment history (new case or previously treated), treatment adherence (adherent or non-adherent), laboratory monitoring (regular or irregular), comorbidities (presence or absence of other diseases), and type of healthcare service unit. Treatment history, laboratory monitoring, and comorbidities were obtained from medical records using checklist forms, while treatment adherence and access to healthcare services were assessed through structured interviews using questionnaires. Data analysis was conducted using chi-square tests and multiple logistic regression. Result: The chi-square tests revealed significant associations for treatment history (p = 0.00, OR = 71.5), adherence (p = 0.00, OR = 7.7), and laboratory monitoring (p = 0.00, OR = 12.0). No significant associations were found for comorbidities (p = 0.655) or service units (p = 0.171). Logistic regression identified treatment history as the primary risk factor for DR-TB (adjusted OR = 47.762), followed by laboratory monitoring (adjusted OR = 5.326). Conclusion: The resulting regression model indicated a predictive probability of 94.9%, suggesting that treatment history and laboratory monitoring are the key factors contributing to ATD resistance among PTB patients.