Prevalence and Factors Associated with Non-adherence to Antituberculosis Medications in Dar es salaam, Tanzania

Prevalence and Factors Associated with Non-adherence to Antituberculosis Medications in Dar es salaam, Tanzania | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence and Factors Associated with Non-adherence to Antituberculosis Medications in Dar es salaam, Tanzania Tresphory Zumba, Candida Moshiro, Sabina Mugusi, Lulu Fundikira, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6857120/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract Background Non-adherence to tuberculosis (TB) medication is a significant public health problem, associated with poor treatment outcomes such as drug resistance, relapse, increased economic burden, morbidity and mortality. Ensuring adherence to TB medication is key for treatment success. To effectively promote adherence, it is important to have a clear understanding of the factors associated with non-adherence. Objective The study aimed to determine the prevalence and factors associated with non-adherence to medications among TB patients attending a Regional Referral Hospital in Dar es Salaam. Methodology: A cross-sectional study was conducted at the TB clinic of this hospital. A total of 362 participants were selected using a systematic random sampling method. Data were collected through face-to-face interviews. Informed consent was obtained from each respondent prior to data collection. Non-adherence to TB medications was measured by using a validated tool with four questions. Factors independently associated with non-adherence were determined using multivariable modified Poisson regression analysis. Results The median age of study participants was 38 years (interquartile range: 30–46 years). The majority, 267 (73.8%) were aged between 18–45 years. Most participants, 246 (68%), were male. The prevalence of non-adherence to TB medications was 14.4%. In the multivariable modified Poisson regression model, non-adherence to TB medications was associated with methadone use (adjusted prevalence ratio (aPR) = 3.04; 95% CI: 1.69–5.46) and spending 1–2 hours at the hospital (aPR = 4.44; 95% CI: 1.16–16.97). A strong healthcare worker-patient relationship was associated with lower odds of non-adherence (aPR = 0.41; 95% CI: 0.25–0.67). Conclusions In this study, non-adherence to TB medications among current TB patients was low. Very bad to good relationship with HCWs was associated with good adherence to TB medications while methadone use, and spending 1–2 hours at the hospital were significantly associated with non-adherence to TB medications. Clinical trial number: Not applicable. Adherence Non-adherence to TB medication Tuberculosis Background Tuberculosis (TB) is the 13th leading cause of death and the second leading infectious killer worldwide, after COVID-19 ( 1 ). Majority of people affected by TB live in low- and middle-income countries ( 1 ). In 2020, approximately 1.5 million people died from TB disease globally ( 1 ). In 2022, about 10 million people worldwide, fell ill with TB, including 5.6 million men, 3.3 million women, and 1.1 million children ( 1 ). According to a 2016 report by the World Health Organization (WHO), South Africa and Nigeria were the most affected countries in Africa ( 2 ). A 2022 report from the Centers for Disease Control and Prevention (CDC) indicated that in Tanzania, about 36% of TB patients were undiagnosed and untreated due to stigma and discrimination within the society ( 3 ). Tuberculosis treatment necessitates six consecutive months of uninterrupted medication to ensure effectiveness. The TB medications are important in decreasing the rate of TB disease transmission, reducing morbidity, mortality and disability ( 4 ). It has been reported that approximately 85% of the patients who develop TB disease can be completely cured by using TB medications for six months ( 5 ). To optimize TB treatment outcomes and enhance medication adherence, thereby preventing drug resistance, treatment failure, and relapse, the WHO introduced the directly observed treatment (DOT) strategy in 1998 in order to ensure effective treatment, follow-up, and monitoring of patients ( 4 , 6 ). Also, in order to improve medication adherence for TB patients, Patient Centered TB Treatment (PCT) was introduced in Tanzania in 2006. As a result, more than 75% of TB patients are now monitored and supervised at the community level. Individuals undergoing TB treatment are afforded the choice of DOT administered by healthcare professionals within a clinical setting or by trained non-medical personnel within their respective communities ( 7 ). However, it has been shown from a study done in Dar es Salaam in 2016 that, patients on home-based DOTS were more likely to experience poor treatment outcomes and higher mortality rates, despite demonstrating good adherence to treatment ( 8 ). In contrast, patients supervised through facility-based DOTS were less likely to die ( 8 ). However, DOT and PCT methods are not currently used and this may impact adherence to medications for TB patients ( 4 ). According to WHO, medication adherence refers to “the extent to which a person’s behavior-taking medication, following a diet, or executing lifestyle changes, corresponds with agreed recommendations from health care provider” ( 9 ). Adherence to TB medication is crucial for treatment success, while non-adherence is associated with adverse outcomes such as increased mortality, morbidity and relapse ( 10 ). Non-adherence to TB medications remains a significant obstacle facing TB control programs, hindering both prevention and treatment efforts. Patients who take less than 95% of their prescribed TB medications are considered non-adherent ( 11 ). Poor medication adherence has a clear link with multi-drug resistant tuberculosis (MDR-TB) and about 28% of all MDR-TB cases in Tanzania come from Dar es Salaam region ( 12 ). Apart from that, if TB is not well treated and controlled, it imposes a considerable economic burden on individuals and the community. A study conducted in Dar es Salaam revealed over 53% of TB patients borrowed money, some even sold personal assets, to afford treatment ( 13 ). Non-adherence to tuberculosis medication is influenced by a complex interplay of factors, including patient-related issues such as alcohol consumption and side effects, as well as health system challenges, particularly prevalent in Sub-Saharan Africa. Despite the availability of free TB medications in Tanzania, the country remains among those with a high TB burden, further complicated by HIV co-infection. With a national non-adherence rate of 16.9%, achieving the global goal of ending the TB epidemic by 2030 requires improved diagnosis, management, and patient education on medication adherence. While existing research has explored contributing factors, a more nuanced understanding of the specific determinants of non-adherence within the local context of a Regional Referral Hospital is essential. Therefore, this study aimed to determine the prevalence and factors associated with non-adherence to TB medications among patients receiving care at this facility. Methodology Study design This study employed an analytical cross-sectional design, utilizing quantitative methods to collect and analyze data. Participants We randomly interviewed a total of 362 participants above 18 years old from a Regional Referral Hospital (RRH) in Dar es Salaam. Data collection methods Data were collected at the TB clinic of the RRH for a period of 8 weeks, from March to April 2023. Information was collected simultaneously from each participant to investigate the association between exposure to risk factors and the outcomes of interest. Participants selection was random. The interview was pretested on 20 TB participants at another RRH, with similar characteristics as the index hospital, to ensure the validity and reliability. Feedback from the pretest was incorporated to improve the questionnaire ( 14 ). Following their clinic visit, participants were invited to a private room for a face-to-face interview, conducted with N95 mask protection. Participants were invited to participate after they had been seen by the health care workers at the TB clinic. Before the interview, fieldworkers provided a study briefing, and voluntary verbal and written informed consent was obtained from each participant. Informed consent was obtained through signature for literate participants, and with the aid of an impartial witness for those unable to read or write. Each interview lasted 20–30 minutes. Data analysis Data were checked for completeness, coded and entered into an Excel spreadsheet. STATA software Version 14.0 was used for data analysis. Descriptive analysis was used to describe the sample characteristics. The prevalence of non-adherence to TB medication was calculated as the proportion of patients who were non-adherent out of the total sample. Medians and inter-quartile ranges (IQR) were used to summarize continuous variables. The outcome variable (non-adherence) was defined as a patient decision not to follow medications or treatment recommendations and instructions. As the outcome variable (non-adherence) was common, the conventional logistic regression was not used as it could have over-estimated the odds ratio. We addressed this by using modified Poisson regression with robust standard error to estimate prevalence ratios (PR) so as to identify independent factors associated with non-adherence to medication among TB patients. Variables with a p ≤ 0.2 in bivariate analysis were included in the multivariable modified Poisson regression model with robust standard errors to control for potential cofounders. Crude prevalence ratio (cPR), adjusted prevalence ratio (aPR) and 95% confidence intervals (CI) were calculated. We considered results statistically significant if the p -value obtained was < 0.05. Results We interviewed a total of 362 participants. The median age was 38 years, interquartile range (IQR) (30–46) years. The majority, 267 (73.8%) of the participants were aged between 18–45 years. More than half, 246 (68%) of the participants were male. About half, 186 (51.4%) of the participants were married. Most participants, 155 (42.8%), had a primary education, and nearly half, 182 (49.7%) of the participants were unemployed (Table 1 ). Table 1 Socio-demographic characteristics of the study participants (n = 362) Variable Frequency (n) Percent (%) Age (years) 18–45 267 73.8 46–60 85 23.4 > 60 10 2.8 Median age in years (Interquartile range) 38 (30, 46) Sex Male 246 68.0 Female 116 32.0 Marital status Single 128 35.3 Married 186 51.4 Divorced or widowed 48 13.3 Level of education No formal 19 5.3 Primary 175 48.3 Secondary and above 168 46.4 Occupation Unemployed Employed 182 180 49.7 50.3 Alcohol consumption Not consuming 283 78.1 Risky consumption 4 1.1 Harmful consumption 65 18.0 Alcohol dependent 10 2.8 Cigarette smoking Yes 53 14.6 No 309 85.4 Distance to health facility (minutes) < 30 145 40.1 ≥ 30 217 59.9 Non-adherence to TB medications 52 14.4 Prevalence and factors associated with non-adherence to TB medications. The overall prevalence of non-adherence to TB medications found in this study was 14.4%, based on self-reported responses from participants (95% CI: 11.1%-18.4%). Findings from the univariable analysis revealed that non-adherence to TB medication was associated with age. Higher odds of non-adherence to TB medication were observed among participants aged 46–60 years (cPR = 1.71;95% CI: 1.02–2.88) and those with no formal to primary level of education (cPR = 1.95; 95% CI: 1.12–3.38). There was no association between non-adherence to TB medications and participants’ sex ( Table 2 ). Regarding family support, participants who reported receiving intermittent family support were more likely to be non-adherent to TB medication (cPR = 1.10; 95% CI:1.02–1.19) compared to those who consistently had family support. Furthermore, alcohol consumption was associated with a lower likelihood of non-adherence (cPR = 0.38; 95% CI: 0.16–0.93). In this study, methadone users had significantly higher odds of TB medication non-adherence compared to those who were not using methadone (cPR = 3.90; 95% CI: 2.41–6.31). Our findings showed that participants who spent 1–2 hours at the hospital had a higher risk of non-adherence to TB medications compared to those who spent more than 3 hours seeking care at the health facility (cPR = 1.17; 95% CI, 1.06–1.30). Moreover, univariate analysis found that participants who reported having a very bad to good relationship with healthcare workers (HCWs) were associated with a 59% lower prevalence of non-adherence to TB medications (cPR = 0.41; 95% CI: 0.25–0.67) compared to those who reported a very good relationship with HCWs. Independent risk factors for non-adherence Multivariable modified Poisson regression model identified several factors independently associated with non-adherence to TB medications ( Table 2 ). Very bad to good relationship with HCWs (aPR 0.41; 95% CI: 0.25–0.67) was independently associated with a lower prevalence of non-adherence to TB medications. In contrast, using methadone (aPR 3.04; 95% CI: 1.69–5.46) and spending 1–2 hours at the hospital (aPR = 4.44; 95% CI, 1.16–16.97) were both independently positively associated with non-adherence to TB medications. Table 2: Multivariable analysis of the factors associated with non-adherence to TB medication Univariable analysis Multivariable analysis Variable Total cPR 95% CI P – value aPR 95% CI P - value Age (years) 18–45 267 Ref Ref 46–60 85 1.71 1.02–2.88 0.042 1.12 0.63–1.99 0.710 > 60 10 0.81 0.12–5.34 0.826 0.47 0.04–5.55 0.551 Sex Male 246 1.76 0.94–3.29 0.078 1.22 0.63–2.40 0.556 Female 116 Ref Ref Level of education No formal to primary 194 1.95 1.12–3.38 0.018 1.74 0.96–3.16 0.069 Secondary and above 168 Ref Ref Alcohol consumption Yes 79 0.38 0.16–0.93 0.33 0.54 0.24–1.23 0.142 No 283 Ref Ref Family support Never 45 1.00 0.91–1.09 0.961 0.71 0.31–1.63 0.421 Somehow 97 1.10 1.02–1.19 0.015 1.41 0.81–2.47 0.228 Always 220 Ref Ref Relation with HCWs Very bad to Good 250 0.48 0.30–0.80 0.004 0.41 0.25–0.67 0.001 Very good 112 Ref Ref Methadone Yes 37 3.90 2.41–6.31 < 0.001 3.04 1.69–5.46 0.001 No 325 Ref Ref Time spent at hospital (hours) < 1 246 2.54 0.63 − 10.16 0.189 2.48 0.69–8.91 0.163 1–2 77 4.56 1.11 − 18.66 0.035 4.44 1.16–16.97 0.029 ≥ 3 39 Ref Ref Key: aPR: Adjusted Prevalence Ratio, Ref = Reference Category, HCW = Health Care Workers Discussion This study aimed to determine the prevalence and factors associated with non-adherence to medications. The prevalence of non-adherence in our study population was 14.4%. In this study, we have shown that participants aged 46–60 years, those with no formal to primary level education, those who consume alcohol, participants receiving intermittent family support, those reporting very bad to good relationships with healthcare workers, methadone users, and those spending 1–2 hours at the health facility were associated with non-adherence to TB medication. However, after adjusting for potential confounders, three factors remained significantly associated with non-adherence to TB medications: having a very bad to good relationship with healthcare workers, methadone use, and spending 1–2 hours at the health facility. The 14.4% prevalence of non-adherence to TB medications observed in our study is consistent with findings from other studies conducted elsewhere. For instance, the finding is similar to that found in the study conducted in Kosovo in 2017 which reported a non-adherence of 14.5% ( 15 ), and is also close to the 18.4% found in a 2020 study from Ghana ( 4 ). A systematic review and meta-analysis by Zegeye et al. reported a slightly higher prevalence of 21.29% ( 16 ). In contrast, the studies from South Korea and Nigeria reported substantially higher rates of non-adherence: 45% and 30.5%, respectively ( 16 , 17 ). These discrepancies could be attributed to several factors, including differences in study populations, sampling techniques, geographical settings, and sample sizes. Additionally, our findings are based on data from a single hospital. The relatively low prevalence of non-adherence in our study may be explained in part by the very bad to good patient-HCWs relationships, which appeared to be a protective factor. Another possible explanation is the implementation of the National Strategic Plan (NSP VI), whereby Tanzania has been recognized as one of seven countries that achieved WHO 2020 end TB milestone by successfully reducing TB mortality and incidence rate by 27% and 18%, respectively ( 10 ). The study revealed an association between methadone use and non-adherence to TB medication, with methadone users demonstrating higher rates of non-adherence. In contrast, a study conducted in Ukraine found that TB patients receiving methadone maintenance treatment (MMT) had better adherence to TB medication compared to those not on MMT. This improved adherence was attributed to increased retention in treatment when MMT was integrated with TB care among people who inject drugs (PWIDs) ( 19 ). Similarly, findings from a cross-sectional survey conducted in Kenya by the National Tuberculosis, Leprosy and Lung Disease Program in 2018 indicated that participants with substance use disorder were more likely to adhere to TB medications compared to non-substance users ( 20 ). The lower adherence observed in our study among methadone users may be due to several interrelated factors. First, the comorbidity of TB and substance use disorder often results in more complex treatment regimens, which can be challenging to manage. Many methadone users also experience homelessness, limiting their ability to maintain regular medication routines and access consistent healthcare ( 21 ). Psychiatric comorbidities, such as depression and anxiety, may also contribute to non-adherence by impairing memory and increasing the likelihood of missed clinic visits. Additionally, patients may fear potential side effects from taking both TB medications and methadone, which can lead to dose reduction or discontinuation. Logistical challenges may further complicate adherence. For example, patients who must attend both TB and methadone clinics on the same day may prioritize methadone treatment, leading to missed TB appointments due to time constraints. Stigma and discrimination related to substance use disorder can also affect adherence, as patients may experience shame or self-blame, which undermines motivation to follow treatment plans. Furthermore, ongoing substance use while on methadone treatment may lead to relapse, causing individuals to prioritize obtaining illicit drugs over adhering to prescribed medication regimens ( 22 ). To address these challenges, a multidisciplinary care approach is essential. Integrating harm reduction strategies and providing comprehensive support can help patients on methadone better manage their conditions and improve adherence to TB medications. Findings from our study showed that participants who reported having a very bad to good relationship with their healthcare workers (HCWs) were more likely to adhere to TB medication compared to those who reported a very good relationship. Similarly, findings from a 2025 study in Uganda reported that very good HCWs-patient relationships reflected by positive coefficients for medication reminders and emotional support were paradoxically associated with non-adherence to TB medications ( 23 ). Contrary to the findings, a study from Kenya found that participants who perceived friendly HCWs had higher rates of adherence than those who described their HCWs as unfriendly ( 24 ). Interestingly, a study from Ethiopia found no statistically significant association between the quality of patient - HCWs relationships and TB medication adherence ( 25 ). A very good patient-HCWs relationship may contribute to non-adherence if patients become overly reliant on the HCWs, perceiving less personal responsibility for their medication. This is more likely when the HCWs is seen as consistently available and supportive, leading to reduced patient accountability and potentially contributing to non-adherence ( 23 ). Another possible explanation is the emergence of emotional or social complexities when the patient-HCWs relationship becomes too personal, potentially blurring professional boundaries and allowing treatment decisions to be influenced by non-medical factors such as shame or emotional involvement, which may contribute to non-adherence to TB medications. Interestingly, findings from the current study indicate that participants who spent a shorter amount of time (1–2 hours) at the hospital seeking healthcare services were more likely to be non-adherent to TB medications compared to those who spent a longer time (≥ 3 hours). This result contrasts with findings from several studies conducted globally. For instance, a systematic review and meta-analysis conducted in 2019 by Zegeye et al. found that patients who experienced longer waiting times (≥ 1 hour) were more likely to be non-adherent to TB medications compared to those with shorter waiting times ( 16 ). Similarly, a 2020 study from Nepal by Baral et al. reported that longer waiting times were associated with higher levels of non-adherence to TB treatment ( 26 ). A possible explanation for the differing findings in the present study could be that patients who spend more time at the facility may receive more comprehensive attention, including engagement in peer health education and counseling. In contrast, those seen for shorter time or more quickly may receive rushed or superficial care, potentially reducing their trust in healthcare providers and their willingness to follow treatment instructions. This rushed interaction might lead patients to underestimate the seriousness of their condition, which can reduce motivation and lead to non-adherence. Supporting this view, a systematic review study in 2016 by Michael et al. highlighted that spending more time in patient-provider communication helps to build trust and positively influences adherence to TB treatment ( 27 ). Likewise, a 2012 study by James et al. found that one-on-one or group counseling, involving the provision of detailed information about TB and the importance of completing the treatment course, was significantly associated with TB medications adherence. Patients are more likely to follow treatment guidelines when they are thoroughly informed, rather than rushed through care in a short time period ( 28 ). Study strengths The large sample size of our study and adequate number of variables presents one of the strengths of our study to support our findings. Study limitations and mitigation Recall bias, where patients struggle to accurately remember details like all types of medications given, the date and number of visits they have to attend, can skew adherence estimates. This bias was minimized by giving the participant sufficient time while interviewing for adequate recall of long-term memory. This bias was also minimized by using standardized questionnaires and having well-trained interviewers. In addition to that also a pilot survey was conducted to find out the recall period, experience, and behavior under the study and this was used so as to mitigate this bias. Apart from that, also recall bias was minimized by verifying reported information by using preexisting records like medical records rather than relying on participant information and experiences. Social desirability bias, where participants give favorable responses, was reduced by using structured interview questions. Conclusion We found that prevalence of non-adherence to TB medications at a RRH was low among the current TB patients. Patients’ very bad to good relationship with HCWs were associated with good adherence to TB medications while methadone uses and spending 1–2 hours at the hospital were associated with non-adherence to TB medications for patients with TB disease. Abbreviations aPR, adjusted prevalence ratio; CDC, Centre for Disease Control CI, confidence interval; cPR, crude prevalence ratio DOT, Directly Observed Therapy; HCWs, Healthcare workers; IQR, interquartile range, MDR-TB, Multi-Drug-Resistant Tuberculosis MRRH, Mwananyamala Regional Referral Hospital; NSP-IV, National Strategic Plan VI PCT, Patient Centered TB Treatment TB, Tuberculosis WHO, World Health Organization; Declarations The authors declare no conflict of interest. Ethics approval and consent to participate Ethical clearance with certificate number MUHAS-REC-03-2023-1610 was provided by the Muhimbili University of Health and Allied Sciences (MUHAS) Institutional Review Board Ethics Committee. The study was conducted in accordance with the ethical standards and principle of the MUHAS and the Declaration of Helsinki . Permission to conduct the study at the field was requested and provided by the medical officer in charge for Mwananyamala Hospital. Written informed consents were obtained from each participant prior to their inclusion into the study. Confidentiality of the respondents was ensured at all stages of the study. Funding This study did not receive any external funding. Authors’ contributions This work is a Master’s thesis work conducted by TZ and supervised by MA and CM. Initial conceptualization was done by TZ reviewed and improved by MA and CM. TZ coordinated and conducted data collection, formulated the analysis plan, and developed the first draft of the manuscript. MA, HM, SM, LF and CM reviewed and supported data analysis and produced the final manuscript, ready for submission. All author reviewed and approved the final manuscript. Authors Information TZ was a postgraduate student pursuing a Masters in Public Health (MPH) under the supervision of MA and CM, Senior Lecturers at MUHAS, Tanzania. Acknowledgement We would like to extend our sincere gratitude to the leadership of MUHAS and the School of Public Health and Social Sciences for their leadership and support during the implementation of this study. We are also deeply thankful to all the participants who participated in this study. Special thanks go to the data collectors Saudan Massawe, Lucy Lesso, and Elizabeth Sallu for their contribution to the success of this study. Availability of Data and Materials The datasets during the current study will be available from the corresponding author upon request. References WHO. Tuberculosis [Internet]. 2023 [cited 2023 Jul 4]. Available from: https://www.who.int/news-room/fact-sheets/detail/tuberculosis WHO. Global tubercolosis report 2018 [Internet]. Vol. 63, World Health Organization. 2018. 476 p. Available from: https://apps.who.int/iris/handle/10665/274453 CDC. CDC impact in Tanzania. Centers Dis Control [Internet]. 2019;(May):1–2. 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Healthcare Worker-Related Factors Contributing to Tuberculosis Treatment Non-Adherence among Patients in Kisumu East Sub-County. J Tuberc Res [Internet]. 2024;12(01):13–33. Available from: https://www.scirp.org/pdf/jtr_2024030813543007.pdf Eden Kassa TE. Non-Adherence to Anti-TB Drugs and Its Predictors among TB/HIV Co- Infected Patients in Mekelle, Ethiopia. Omi J Radiol [Internet]. 2014;06(06). Available from: https://hal.science/hal-04020963v1/document Yadav RK, Kaphle HP, Yadav DK, Marahatta SB, Shah NP, Baral S, et al. Health related quality of life and associated factors with medication adherence among tuberculosis patients in selected districts of Gandaki Province of Nepal. J Clin Tuberc Other Mycobact Dis [Internet]. 2021;23:100235. Available from: https://doi.org/10.1016/j.jctube.2021.100235 Michael J DiStefano HS. mHealth for Tuberculosis Treatment Adherence : and Evaluation. Glob Heal Sci Pract 2016 [Internet]. 2016;4(2):211–21. Available from: https://dx.doi.org/10.9745/GHSP-D-16-00018 M’Imunya JM, Kredo T, Volmink J. Patient education and counselling for promoting adherence to treatment for tuberculosis. Cochrane Database Syst Rev [Internet]. 2012; Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6532681/pdf/CD006591.pdf Additional Declarations No competing interests reported. Supplementary Files StudyQuestioannaire.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 Sep, 2025 Reviews received at journal 03 Sep, 2025 Reviews received at journal 24 Aug, 2025 Reviews received at journal 20 Aug, 2025 Reviews received at journal 10 Aug, 2025 Reviewers agreed at journal 10 Aug, 2025 Reviewers agreed at journal 09 Aug, 2025 Reviewers agreed at journal 08 Aug, 2025 Reviewers agreed at journal 06 Aug, 2025 Reviewers agreed at journal 06 Aug, 2025 Reviewers invited by journal 05 Aug, 2025 Editor assigned by journal 06 Jul, 2025 Editor invited by journal 03 Jul, 2025 Submission checks completed at journal 03 Jul, 2025 First submitted to journal 03 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6857120","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496360188,"identity":"6fa1bff1-0381-4b59-ad39-4d9cb26761df","order_by":0,"name":"Tresphory Zumba","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYDCCA0DM2MDAYMAOJBgMLIjXImHAA2IZSJCiRSIBxCVCC9/t48+kbu6wqzOXfH51w48CCQb+9u4EvFokzyWkSeeeSZawnJ1TdrMH6DCJM2c34NVicIbhmHRuG7OEwe2ctBs8QC0GErmEtDC2AbXUSxjcPJN28w9xWpjZgFoOSxjcYD92myhbJM+wMVvnnjkuubMnh+22jIEED0G/8J1hf3g7d0c1vzn78Wc33/yxkeNv78WvBQnwGIBJYpWDAPsDUlSPglEwCkbBCAIAAtRHn+gzFJEAAAAASUVORK5CYII=","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":true,"prefix":"","firstName":"Tresphory","middleName":"","lastName":"Zumba","suffix":""},{"id":496360189,"identity":"c52b7d11-115f-4274-9f8f-b8308a8d023d","order_by":1,"name":"Candida Moshiro","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Candida","middleName":"","lastName":"Moshiro","suffix":""},{"id":496360190,"identity":"4cc41c8a-4105-4c1e-9b3f-504dca5e40e7","order_by":2,"name":"Sabina Mugusi","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Sabina","middleName":"","lastName":"Mugusi","suffix":""},{"id":496360191,"identity":"f49e8726-8c45-4e2d-9125-57bdb1a6f667","order_by":3,"name":"Lulu Fundikira","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Lulu","middleName":"","lastName":"Fundikira","suffix":""},{"id":496360192,"identity":"6e0209e4-f440-40b5-beec-8cf345cce1fb","order_by":4,"name":"Hussein H. Mwanga","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hussein","middleName":"H.","lastName":"Mwanga","suffix":""},{"id":496360193,"identity":"4d8f5120-1278-4a79-a126-6fe634b1913b","order_by":5,"name":"Maryam Amour","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Amour","suffix":""}],"badges":[],"createdAt":"2025-06-09 19:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6857120/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6857120/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88814205,"identity":"e0ee883a-580e-40b3-a21e-f1d42938deb0","added_by":"auto","created_at":"2025-08-11 16:08:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":780382,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6857120/v1/741441e2-1d00-41a5-bf63-15103403b166.pdf"},{"id":88812107,"identity":"0e657cc6-fa42-400b-9785-ef7a494e7eef","added_by":"auto","created_at":"2025-08-11 15:42:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":170159,"visible":true,"origin":"","legend":"","description":"","filename":"StudyQuestioannaire.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6857120/v1/8d8e0e6d302139d239c3877b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence and Factors Associated with Non-adherence to Antituberculosis Medications in Dar es salaam, Tanzania","fulltext":[{"header":"Background","content":"\u003cp\u003eTuberculosis (TB) is the 13th leading cause of death and the second leading infectious killer worldwide, after COVID-19 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Majority of people affected by TB live in low- and middle-income countries (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In 2020, approximately 1.5\u0026nbsp;million people died from TB disease globally (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In 2022, about 10\u0026nbsp;million people worldwide, fell ill with TB, including 5.6\u0026nbsp;million men, 3.3\u0026nbsp;million women, and 1.1\u0026nbsp;million children (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). According to a 2016 report by the World Health Organization (WHO), South Africa and Nigeria were the most affected countries in Africa (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). A 2022 report from the Centers for Disease Control and Prevention (CDC) indicated that in Tanzania, about 36% of TB patients were undiagnosed and untreated due to stigma and discrimination within the society (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTuberculosis treatment necessitates six consecutive months of uninterrupted medication to ensure effectiveness. The TB medications are important in decreasing the rate of TB disease transmission, reducing morbidity, mortality and disability (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). It has been reported that approximately 85% of the patients who develop TB disease can be completely cured by using TB medications for six months (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). To optimize TB treatment outcomes and enhance medication adherence, thereby preventing drug resistance, treatment failure, and relapse, the WHO introduced the directly observed treatment (DOT) strategy in 1998 in order to ensure effective treatment, follow-up, and monitoring of patients (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Also, in order to improve medication adherence for TB patients, Patient Centered TB Treatment (PCT) was introduced in Tanzania in 2006. As a result, more than 75% of TB patients are now monitored and supervised at the community level. Individuals undergoing TB treatment are afforded the choice of DOT administered by healthcare professionals within a clinical setting or by trained non-medical personnel within their respective communities (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, it has been shown from a study done in Dar es Salaam in 2016 that, patients on home-based DOTS were more likely to experience poor treatment outcomes and higher mortality rates, despite demonstrating good adherence to treatment (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In contrast, patients supervised through facility-based DOTS were less likely to die (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, DOT and PCT methods are not currently used and this may impact adherence to medications for TB patients (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to WHO, medication adherence refers to \u0026ldquo;the extent to which a person\u0026rsquo;s behavior-taking medication, following a diet, or executing lifestyle changes, corresponds with agreed recommendations from health care provider\u0026rdquo; (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Adherence to TB medication is crucial for treatment success, while non-adherence is associated with adverse outcomes such as increased mortality, morbidity and relapse (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Non-adherence to TB medications remains a significant obstacle facing TB control programs, hindering both prevention and treatment efforts. Patients who take less than 95% of their prescribed TB medications are considered non-adherent (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Poor medication adherence has a clear link with multi-drug resistant tuberculosis (MDR-TB) and about 28% of all MDR-TB cases in Tanzania come from Dar es Salaam region (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Apart from that, if TB is not well treated and controlled, it imposes a considerable economic burden on individuals and the community. A study conducted in Dar es Salaam revealed over 53% of TB patients borrowed money, some even sold personal assets, to afford treatment (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNon-adherence to tuberculosis medication is influenced by a complex interplay of factors, including patient-related issues such as alcohol consumption and side effects, as well as health system challenges, particularly prevalent in Sub-Saharan Africa. Despite the availability of free TB medications in Tanzania, the country remains among those with a high TB burden, further complicated by HIV co-infection. With a national non-adherence rate of 16.9%, achieving the global goal of ending the TB epidemic by 2030 requires improved diagnosis, management, and patient education on medication adherence. While existing research has explored contributing factors, a more nuanced understanding of the specific determinants of non-adherence within the local context of a Regional Referral Hospital is essential. Therefore, this study aimed to determine the prevalence and factors associated with non-adherence to TB medications among patients receiving care at this facility.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e\u003cb\u003eStudy design\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study employed an analytical cross-sectional design, utilizing quantitative methods to collect and analyze data.\u003c/p\u003e\u003cp\u003e\u003cb\u003eParticipants\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe randomly interviewed a total of 362 participants above 18 years old from a Regional Referral Hospital (RRH) in Dar es Salaam.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData collection methods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData were collected at the TB clinic of the RRH for a period of 8 weeks, from March to April 2023. Information was collected simultaneously from each participant to investigate the association between exposure to risk factors and the outcomes of interest. Participants selection was random. The interview was pretested on 20 TB participants at another RRH, with similar characteristics as the index hospital, to ensure the validity and reliability. Feedback from the pretest was incorporated to improve the questionnaire (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Following their clinic visit, participants were invited to a private room for a face-to-face interview, conducted with N95 mask protection. Participants were invited to participate after they had been seen by the health care workers at the TB clinic. Before the interview, fieldworkers provided a study briefing, and voluntary verbal and written informed consent was obtained from each participant. Informed consent was obtained through signature for literate participants, and with the aid of an impartial witness for those unable to read or write. Each interview lasted 20\u0026ndash;30 minutes.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eData were checked for completeness, coded and entered into an Excel spreadsheet. STATA software Version 14.0 was used for data analysis. Descriptive analysis was used to describe the sample characteristics. The prevalence of non-adherence to TB medication was calculated as the proportion of patients who were non-adherent out of the total sample. Medians and inter-quartile ranges (IQR) were used to summarize continuous variables.\u003c/p\u003e\u003cp\u003eThe outcome variable (non-adherence) was defined as a patient decision not to follow medications or treatment recommendations and instructions. As the outcome variable (non-adherence) was common, the conventional logistic regression was not used as it could have over-estimated the odds ratio. We addressed this by using modified Poisson regression with robust standard error to estimate prevalence ratios (PR) so as to identify independent factors associated with non-adherence to medication among TB patients.\u003c/p\u003e\u003cp\u003eVariables with a \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.2 in bivariate analysis were included in the multivariable modified Poisson regression model with robust standard errors to control for potential cofounders. Crude prevalence ratio (cPR), adjusted prevalence ratio (aPR) and 95% confidence intervals (CI) were calculated. We considered results statistically significant if the \u003cem\u003ep\u003c/em\u003e-value obtained was \u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe interviewed a total of 362 participants. The median age was 38 years, interquartile range (IQR) (30\u0026ndash;46) years. The majority, 267 (73.8%) of the participants were aged between 18\u0026ndash;45 years. More than half, 246 (68%) of the participants were male. About half, 186 (51.4%) of the participants were married. Most participants, 155 (42.8%), had a primary education, and nearly half, 182 (49.7%) of the participants were unemployed (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocio-demographic characteristics of the study participants (n\u0026thinsp;=\u0026thinsp;362)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u0026ndash;45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46\u0026ndash;60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMedian age in years (Interquartile range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e38 (30, 46)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced or widowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLevel of education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo formal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eOccupation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e182\u003c/p\u003e\u003cp\u003e180\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49.7\u003c/p\u003e\u003cp\u003e50.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAlcohol consumption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot consuming\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRisky consumption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHarmful consumption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAlcohol dependent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCigarette smoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e309\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eDistance to health facility (minutes)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNon-adherence to TB medications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrevalence and factors associated with non-adherence to TB medications.\u003c/b\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe overall prevalence of non-adherence to TB medications found in this study was 14.4%, based on self-reported responses from participants (95% CI: 11.1%-18.4%). Findings from the univariable analysis revealed that non-adherence to TB medication was associated with age. Higher odds of non-adherence to TB medication were observed among participants aged 46\u0026ndash;60 years (cPR\u0026thinsp;=\u0026thinsp;1.71;95% CI: 1.02\u0026ndash;2.88) and those with no formal to primary level of education (cPR\u0026thinsp;=\u0026thinsp;1.95; 95% CI: 1.12\u0026ndash;3.38). There was no association between non-adherence to TB medications and participants\u0026rsquo; sex (\u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eRegarding family support, participants who reported receiving intermittent family support were more likely to be non-adherent to TB medication (cPR\u0026thinsp;=\u0026thinsp;1.10; 95% CI:1.02\u0026ndash;1.19) compared to those who consistently had family support. Furthermore, alcohol consumption was associated with a lower likelihood of non-adherence (cPR\u0026thinsp;=\u0026thinsp;0.38; 95% CI: 0.16\u0026ndash;0.93). In this study, methadone users had significantly higher odds of TB medication non-adherence compared to those who were not using methadone (cPR\u0026thinsp;=\u0026thinsp;3.90; 95% CI: 2.41\u0026ndash;6.31).\u003c/p\u003e\u003cp\u003eOur findings showed that participants who spent 1\u0026ndash;2 hours at the hospital had a higher risk of non-adherence to TB medications compared to those who spent more than 3 hours seeking care at the health facility (cPR\u0026thinsp;=\u0026thinsp;1.17; 95% CI, 1.06\u0026ndash;1.30). Moreover, univariate analysis found that participants who reported having a very bad to good relationship with healthcare workers (HCWs) were associated with a 59% lower prevalence of non-adherence to TB medications (cPR\u0026thinsp;=\u0026thinsp;0.41; 95% CI: 0.25\u0026ndash;0.67) compared to those who reported a very good relationship with HCWs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIndependent risk factors for non-adherence\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMultivariable modified Poisson regression model identified several factors independently associated with non-adherence to TB medications (\u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e). Very bad to good relationship with HCWs (aPR 0.41; 95% CI: 0.25\u0026ndash;0.67) was independently associated with a lower prevalence of non-adherence to TB medications. In contrast, using methadone (aPR 3.04; 95% CI: 1.69\u0026ndash;5.46) and spending 1\u0026ndash;2 hours at the hospital (aPR\u0026thinsp;=\u0026thinsp;4.44; 95% CI, 1.16\u0026ndash;16.97) were both independently positively associated with non-adherence to TB medications.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e\u003cp\u003eTable\u0026nbsp;2: Multivariable analysis of the factors associated with non-adherence to TB medication\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eUnivariable analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u003cp\u003eMultivariable analysis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ecPR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP \u0026ndash; value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eaPR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eP - value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e18\u0026ndash;45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e46\u0026ndash;60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.02\u0026ndash;2.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.63\u0026ndash;1.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.710\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.12\u0026ndash;5.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.04\u0026ndash;5.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.551\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.94\u0026ndash;3.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.63\u0026ndash;2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.556\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eLevel of education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eNo formal to primary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.12\u0026ndash;3.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.96\u0026ndash;3.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.069\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSecondary and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eAlcohol consumption\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.16\u0026ndash;0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.24\u0026ndash;1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.142\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eFamily support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.91\u0026ndash;1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.31\u0026ndash;1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.421\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSomehow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.02\u0026ndash;1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.81\u0026ndash;2.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.228\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eAlways\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eRelation with HCWs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eVery bad to Good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.30\u0026ndash;0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.25\u0026ndash;0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eVery good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eMethadone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.41\u0026ndash;6.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.69\u0026ndash;5.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eTime spent at hospital (hours)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.63 \u0026minus;\u0026thinsp;10.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.69\u0026ndash;8.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.163\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1\u0026ndash;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.11 \u0026minus;\u0026thinsp;18.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.16\u0026ndash;16.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e\u003cp\u003eKey: aPR: Adjusted Prevalence Ratio, Ref\u0026thinsp;=\u0026thinsp;Reference Category, HCW\u0026thinsp;=\u0026thinsp;Health Care Workers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study aimed to determine the prevalence and factors associated with non-adherence to medications. The prevalence of non-adherence in our study population was 14.4%. In this study, we have shown that participants aged 46\u0026ndash;60 years, those with no formal to primary level education, those who consume alcohol, participants receiving intermittent family support, those reporting very bad to good relationships with healthcare workers, methadone users, and those spending 1\u0026ndash;2 hours at the health facility were associated with non-adherence to TB medication. However, after adjusting for potential confounders, three factors remained significantly associated with non-adherence to TB medications: having a very bad to good relationship with healthcare workers, methadone use, and spending 1\u0026ndash;2 hours at the health facility.\u003c/p\u003e\u003cp\u003eThe 14.4% prevalence of non-adherence to TB medications observed in our study is consistent with findings from other studies conducted elsewhere. For instance, the finding is similar to that found in the study conducted in Kosovo in 2017 which reported a non-adherence of 14.5% (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), and is also close to the 18.4% found in a 2020 study from Ghana (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). A systematic review and meta-analysis by Zegeye et al. reported a slightly higher prevalence of 21.29% (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In contrast, the studies from South Korea and Nigeria reported substantially higher rates of non-adherence: 45% and 30.5%, respectively (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). These discrepancies could be attributed to several factors, including differences in study populations, sampling techniques, geographical settings, and sample sizes. Additionally, our findings are based on data from a single hospital. The relatively low prevalence of non-adherence in our study may be explained in part by the very bad to good patient-HCWs relationships, which appeared to be a protective factor. Another possible explanation is the implementation of the National Strategic Plan (NSP VI), whereby Tanzania has been recognized as one of seven countries that achieved WHO 2020 end TB milestone by successfully reducing TB mortality and incidence rate by 27% and 18%, respectively (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe study revealed an association between methadone use and non-adherence to TB medication, with methadone users demonstrating higher rates of non-adherence. In contrast, a study conducted in Ukraine found that TB patients receiving methadone maintenance treatment (MMT) had better adherence to TB medication compared to those not on MMT. This improved adherence was attributed to increased retention in treatment when MMT was integrated with TB care among people who inject drugs (PWIDs) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Similarly, findings from a cross-sectional survey conducted in Kenya by the National Tuberculosis, Leprosy and Lung Disease Program in 2018 indicated that participants with substance use disorder were more likely to adhere to TB medications compared to non-substance users (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The lower adherence observed in our study among methadone users may be due to several interrelated factors. First, the comorbidity of TB and substance use disorder often results in more complex treatment regimens, which can be challenging to manage. Many methadone users also experience homelessness, limiting their ability to maintain regular medication routines and access consistent healthcare (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Psychiatric comorbidities, such as depression and anxiety, may also contribute to non-adherence by impairing memory and increasing the likelihood of missed clinic visits. Additionally, patients may fear potential side effects from taking both TB medications and methadone, which can lead to dose reduction or discontinuation. Logistical challenges may further complicate adherence. For example, patients who must attend both TB and methadone clinics on the same day may prioritize methadone treatment, leading to missed TB appointments due to time constraints. Stigma and discrimination related to substance use disorder can also affect adherence, as patients may experience shame or self-blame, which undermines motivation to follow treatment plans. Furthermore, ongoing substance use while on methadone treatment may lead to relapse, causing individuals to prioritize obtaining illicit drugs over adhering to prescribed medication regimens (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). To address these challenges, a multidisciplinary care approach is essential. Integrating harm reduction strategies and providing comprehensive support can help patients on methadone better manage their conditions and improve adherence to TB medications.\u003c/p\u003e\u003cp\u003eFindings from our study showed that participants who reported having a very bad to good relationship with their healthcare workers (HCWs) were more likely to adhere to TB medication compared to those who reported a very good relationship. Similarly, findings from a 2025 study in Uganda reported that very good HCWs-patient relationships reflected by positive coefficients for medication reminders and emotional support were paradoxically associated with non-adherence to TB medications (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Contrary to the findings, a study from Kenya found that participants who perceived friendly HCWs had higher rates of adherence than those who described their HCWs as unfriendly (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Interestingly, a study from Ethiopia found no statistically significant association between the quality of patient\u003cb\u003e-\u003c/b\u003eHCWs relationships and TB medication adherence (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). A very good patient-HCWs relationship may contribute to non-adherence if patients become overly reliant on the HCWs, perceiving less personal responsibility for their medication. This is more likely when the HCWs is seen as consistently available and supportive, leading to reduced patient accountability and potentially contributing to non-adherence (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Another possible explanation is the emergence of emotional or social complexities when the patient-HCWs relationship becomes too personal, potentially blurring professional boundaries and allowing treatment decisions to be influenced by non-medical factors such as shame or emotional involvement, which may contribute to non-adherence to TB medications.\u003c/p\u003e\u003cp\u003eInterestingly, findings from the current study indicate that participants who spent a shorter amount of time (1\u0026ndash;2 hours) at the hospital seeking healthcare services were more likely to be non-adherent to TB medications compared to those who spent a longer time (\u0026ge;\u0026thinsp;3 hours). This result contrasts with findings from several studies conducted globally. For instance, a systematic review and meta-analysis conducted in 2019 by Zegeye et al. found that patients who experienced longer waiting times (\u0026ge;\u0026thinsp;1 hour) were more likely to be non-adherent to TB medications compared to those with shorter waiting times (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Similarly, a 2020 study from Nepal by Baral et al. reported that longer waiting times were associated with higher levels of non-adherence to TB treatment (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). A possible explanation for the differing findings in the present study could be that patients who spend more time at the facility may receive more comprehensive attention, including engagement in peer health education and counseling. In contrast, those seen for shorter time or more quickly may receive rushed or superficial care, potentially reducing their trust in healthcare providers and their willingness to follow treatment instructions. This rushed interaction might lead patients to underestimate the seriousness of their condition, which can reduce motivation and lead to non-adherence. Supporting this view, a systematic review study in 2016 by Michael et al. highlighted that spending more time in patient-provider communication helps to build trust and positively influences adherence to TB treatment (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Likewise, a 2012 study by James et al. found that one-on-one or group counseling, involving the provision of detailed information about TB and the importance of completing the treatment course, was significantly associated with TB medications adherence. Patients are more likely to follow treatment guidelines when they are thoroughly informed, rather than rushed through care in a short time period (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy strengths\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe large sample size of our study and adequate number of variables presents one of the strengths of our study to support our findings.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy limitations and mitigation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRecall bias, where patients struggle to accurately remember details like all types of medications given, the date and number of visits they have to attend, can skew adherence estimates. This bias was minimized by giving the participant sufficient time while interviewing for adequate recall of long-term memory. This bias was also minimized by using standardized questionnaires and having well-trained interviewers. In addition to that also a pilot survey was conducted to find out the recall period, experience, and behavior under the study and this was used so as to mitigate this bias. Apart from that, also recall bias was minimized by verifying reported information by using preexisting records like medical records rather than relying on participant information and experiences. Social desirability bias, where participants give favorable responses, was reduced by using structured interview questions.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe found that prevalence of non-adherence to TB medications at a RRH was low among the current TB patients. Patients\u0026rsquo; very bad to good relationship with HCWs were associated with good adherence to TB medications while methadone uses and spending 1\u0026ndash;2 hours at the hospital were associated with non-adherence to TB medications for patients with TB disease.\u003c/p\u003e\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eaPR, adjusted prevalence ratio;\u003c/p\u003e\u003cp\u003eCDC, Centre for Disease Control\u003c/p\u003e\u003cp\u003eCI, confidence interval;\u003c/p\u003e\u003cp\u003ecPR, crude prevalence ratio\u003c/p\u003e\u003cp\u003eDOT, Directly Observed Therapy;\u003c/p\u003e\u003cp\u003eHCWs, Healthcare workers;\u003c/p\u003e\u003cp\u003eIQR, interquartile range,\u003c/p\u003e\u003cp\u003eMDR-TB, Multi-Drug-Resistant Tuberculosis\u003c/p\u003e\u003cp\u003eMRRH, Mwananyamala Regional Referral Hospital;\u003c/p\u003e\u003cp\u003eNSP-IV, National Strategic Plan VI\u003c/p\u003e\u003cp\u003ePCT, Patient Centered TB Treatment\u003c/p\u003e\u003cp\u003eTB, Tuberculosis\u003c/p\u003e\u003cp\u003eWHO, World Health Organization;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance with certificate number MUHAS-REC-03-2023-1610 was provided by the Muhimbili University of Health and Allied Sciences (MUHAS) Institutional Review Board Ethics Committee.\u0026nbsp;The study was conducted in accordance with the ethical standards and principle of the MUHAS and\u003cstrong\u003e\u0026nbsp;the Declaration of Helsinki\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003ePermission to conduct the study at the field was requested and provided by the medical officer in charge for Mwananyamala Hospital. Written informed consents were obtained from each participant prior to their inclusion into the study. Confidentiality of the respondents was ensured at all stages of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is a Master\u0026rsquo;s thesis work conducted by TZ and supervised by MA and CM. Initial conceptualization was done by TZ reviewed and improved by MA and CM. TZ coordinated and conducted data collection, formulated the analysis plan, and developed the first draft of the manuscript. MA, HM, SM, LF and CM reviewed and supported data analysis and produced the final manuscript, ready for submission. All author reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTZ was a postgraduate student pursuing a Masters in Public Health (MPH) under the supervision of MA and CM, Senior Lecturers at MUHAS, Tanzania.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to extend our sincere gratitude to the leadership of MUHAS and the School of Public Health and Social Sciences for their leadership and support during the implementation of this study. We are also deeply thankful to all the participants who participated in this study. Special thanks go to the data collectors Saudan Massawe, Lucy Lesso, and Elizabeth Sallu for their contribution to the success of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets during the current study will be available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO. Tuberculosis [Internet]. 2023 [cited 2023 Jul 4]. Available from: https://www.who.int/news-room/fact-sheets/detail/tuberculosis\u003c/li\u003e\n\u003cli\u003eWHO. Global tubercolosis report 2018 [Internet]. Vol. 63, World Health Organization. 2018. 476 p. Available from: https://apps.who.int/iris/handle/10665/274453\u003c/li\u003e\n\u003cli\u003eCDC. CDC impact in Tanzania. Centers Dis Control [Internet]. 2019;(May):1\u0026ndash;2. Available from: https://www.cdc.gov/globalhealth/countries/tanzania/pdf/tanzania-factsheet-final-june-2013.pdf\u003c/li\u003e\n\u003cli\u003eDogah E, Aviisah M, Kuatewo DAM, Kpene GE, Lokpo SY, Edziah FS. Factors Influencing Adherence to Tuberculosis Treatment in the Ketu North District of the Volta Region, Ghana. Tuberc Res Treat [Internet]. 2021;2021:1\u0026ndash;6. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8026325/pdf/TRT2021-6685039.pdf\u003c/li\u003e\n\u003cli\u003eTuberculosis [Internet]. 2020. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://iris.who.int/bitstream/handle/10665/336069/9789240013131-eng.pdf?sequence=1\u003c/li\u003e\n\u003cli\u003eGube AA, Debalkie M, Seid K, Bisete K, Mengesha A, Zeynu A, et al. Assessment of Anti-TB Drug Nonadherence and Associated Factors among TB Patients Attending TB Clinics in Arba Minch Governmental Health Institutions, Southern Ethiopia. Tuberc Res Treat [Internet]. 2018;2018:1\u0026ndash;7. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5835254/pdf/TRT2018-3705812.pdf\u003c/li\u003e\n\u003cli\u003eMkopi A, Range N, Lwilla F, Egwaga S, Schulze A, Geubbels E, et al. Validation of indirect tuberculosis treatment adherence measures in a resource-constrained setting. Int J Tuberc Lung Dis [Internet]. 2014;18(7):804\u0026ndash;9. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://docserver.ingentaconnect.com/deliver/connect/iuatld/10273719/v18n7/s12.pdf?expires=1699186396\u0026amp;id=0000\u0026amp;titleid=3764\u0026amp;checksum=52994DAE240CD1D37001FF6BBE89BE62\u0026amp;host=https://www.ingentaconnect.com\u003c/li\u003e\n\u003cli\u003eMhimbira F, Hella J, Maroa T, Kisandu S, Chiryamkubi M, Said K, et al. Home-based and facility-based directly observed therapy of tuberculosis treatment under programmatic conditions in urban Tanzania. PLoS One [Internet]. 2016;11(8):1\u0026ndash;13. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0161171\u0026amp;type=printable\u003c/li\u003e\n\u003cli\u003eWHO. ADHERENCE TO LONG-TERM THERAPIES. Patient Prefer Adherence [Internet]. 2003; Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3711878/pdf/ppa-7-675.pdf\u003c/li\u003e\n\u003cli\u003eMinistry of Health Tanzania. The united republic of Tanzania, national strategic plan V for 2015-2020 for Tuberculosis and Leprosy. 2020;47. Available from: https://ntlp.go.tz/site/assets/files/1074/national_strategic_plan_2015_2020.pdf\u003c/li\u003e\n\u003cli\u003eNezenega ZS, Perimal‐lewis L, Maeder AJ. Factors influencing patient adherence to tuberculosis treatment in ethiopia: A literature review. Int J Environ Res Public Health [Internet]. 2020;17(15):1\u0026ndash;12. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7432798/pdf/ijerph-17-05626.pdf\u003c/li\u003e\n\u003cli\u003eMyemba DT, Bwire GM, Sambayi G, Maganda BA, Njiro BJ, Ndumwa HP, et al. Clinical characteristics and treatment outcomes of patients with MDR tuberculosis in Dar Es Salaam region, Tanzania. JAC-Antimicrobial Resist [Internet]. 2021;2(4):1\u0026ndash;8. Available from: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8210025/pdf/dlaa108.pdf\u003c/li\u003e\n\u003cli\u003eKilale AM, Pantoja A, Jani B, Range N, Ngowi BJ, Makasi C, et al. Economic burden of tuberculosis in Tanzania: a national survey of costs faced by tuberculosis-affected households. BMC Public Health [Internet]. 2022;22(1):1\u0026ndash;10. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-022-12987-3\u003c/li\u003e\n\u003cli\u003eZumba T. Study questionnaire. Dar es Salam; 2023. \u003c/li\u003e\n\u003cli\u003eKrasniqi S, Jakupi A, Daci A, Tigani B, Jupolli-krasniqi N, Pira M, et al. Tuberculosis Treatment Adherence of Patients in Kosovo. 2017;2017. \u003c/li\u003e\n\u003cli\u003eZegeye A, Dessie G, Wagnew F, Gebrie A, Islam SMS, Tesfaye B, et al. Prevalence and determinants of anti-tuberculosis treatment non-adherence in Ethiopia: A systematic review and meta-analysis. PLoS One [Internet]. 2019;14(1):1\u0026ndash;15. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0210422\u003c/li\u003e\n\u003cli\u003eBea S, Lee H, Kim JH, Jang SH, Son H, Kwon JW, et al. Adherence and Associated Factors of Treatment Regimen in Drug-Susceptible Tuberculosis Patients. Front Pharmacol [Internet]. 2021;12(March):1\u0026ndash;9. Available from: https://www.frontiersin.org/articles/10.3389/fphar.2021.625078/full\u003c/li\u003e\n\u003cli\u003eIweama CN, Agbaje OS, Umoke PCI, Igbokwe CC, Ozoemena EL, Omaka-Amari NL, et al. Nonadherence to tuberculosis treatment and associated factors among patients using directly observed treatment short-course in north-west Nigeria: A cross-sectional study. SAGE Open Med [Internet]. 2021;9. Available from: https://journals.sagepub.com/doi/pdf/10.1177/2050312121989497\u003c/li\u003e\n\u003cli\u003eOlga Morozovaa C, , Sergii Dvoryaka,*, and Frederick L. Alticeb C, aUkrainian Institute on Public Health Policy, 4 Malopidvalna Str., Office 6, Kyiv 01001 U, bYale University School of Medicine, New Haven, CT U, cYale University School of Public Health, 135 College Street, Suite 323, New Haven C, 06510-2283 U. Methadone treatment improves tuberculosis treatment among hospitalized opioid dependent patients in Ukraine. 2017;176(1):100\u0026ndash;106. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC5553122/pdf/nihms889175.pdf\u003c/li\u003e\n\u003cli\u003eMy CM, Cmy CY. Factors Associated With Non-Adherence to Tuberculosis Treatment in Kenya 2018. 2018; Available from: https://nltp.co.ke/wp-content/uploads/2020/10/TB-Adherence-Report-Final.pdf\u003c/li\u003e\n\u003cli\u003eMinja LT, Hella J, Mbwambo J, Nyandindi C, Omary US, Levira F, et al. High burden of tuberculosis infection and disease among people receiving medication-assisted treatment for substance use disorder in Tanzania. PLoS One [Internet]. 2021;16(4 April 2021). Available from: http://dx.doi.org/10.1371/journal.pone.0250038\u003c/li\u003e\n\u003cli\u003eWilliam L White 1, Michael D Campbell, Robert D Spencer, Howard A Hoffman, Brian Crissman RLD. Patterns of abstinence or continued drug use among methadone maintenance patients and their relation to treatment retention [Internet]. 2014 [cited 2025 Apr 15]. Available from: https://pubmed.ncbi.nlm.nih.gov/25052787/\u003c/li\u003e\n\u003cli\u003eAlinaitwe B, Shariff NJ, Madhavi Boddupalli B. Treatment adherence and its association with family support among pulmonary tuberculosis patients in Jinja, Eastern Uganda. Sci Rep [Internet]. 2025;15(1):1\u0026ndash;10. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC11961641/pdf/41598_2025_Article_96260.pdf\u003c/li\u003e\n\u003cli\u003eOchieng M, Nyaberi J, Mambo S, Wafula C. Healthcare Worker-Related Factors Contributing to Tuberculosis Treatment Non-Adherence among Patients in Kisumu East Sub-County. J Tuberc Res [Internet]. 2024;12(01):13\u0026ndash;33. Available from: https://www.scirp.org/pdf/jtr_2024030813543007.pdf\u003c/li\u003e\n\u003cli\u003eEden Kassa TE. Non-Adherence to Anti-TB Drugs and Its Predictors among TB/HIV Co- Infected Patients in Mekelle, Ethiopia. Omi J Radiol [Internet]. 2014;06(06). Available from: https://hal.science/hal-04020963v1/document\u003c/li\u003e\n\u003cli\u003eYadav RK, Kaphle HP, Yadav DK, Marahatta SB, Shah NP, Baral S, et al. Health related quality of life and associated factors with medication adherence among tuberculosis patients in selected districts of Gandaki Province of Nepal. J Clin Tuberc Other Mycobact Dis [Internet]. 2021;23:100235. Available from: https://doi.org/10.1016/j.jctube.2021.100235\u003c/li\u003e\n\u003cli\u003eMichael J DiStefano HS. mHealth for Tuberculosis Treatment Adherence : and Evaluation. Glob Heal Sci Pract 2016 [Internet]. 2016;4(2):211\u0026ndash;21. Available from: https://dx.doi.org/10.9745/GHSP-D-16-00018\u003c/li\u003e\n\u003cli\u003eM\u0026rsquo;Imunya JM, Kredo T, Volmink J. Patient education and counselling for promoting adherence to treatment for tuberculosis. Cochrane Database Syst Rev [Internet]. 2012; Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6532681/pdf/CD006591.pdf\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Adherence, Non-adherence to TB medication, Tuberculosis","lastPublishedDoi":"10.21203/rs.3.rs-6857120/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6857120/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNon-adherence to tuberculosis (TB) medication is a significant public health problem, associated with poor treatment outcomes such as drug resistance, relapse, increased economic burden, morbidity and mortality. Ensuring adherence to TB medication is key for treatment success. To effectively promote adherence, it is important to have a clear understanding of the factors associated with non-adherence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study aimed to determine the prevalence and factors associated with non-adherence to medications among TB patients attending a Regional Referral Hospital in Dar es Salaam.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted at the TB clinic of this hospital. A total of 362 participants were selected using a systematic random sampling method. Data were collected through face-to-face interviews. Informed consent was obtained from each respondent prior to data collection. Non-adherence to TB medications was measured by using a validated tool with four questions. Factors independently associated with non-adherence were determined using multivariable modified Poisson regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe median age of study participants was 38 years (interquartile range: 30–46 years). The majority, 267 (73.8%) were aged between 18–45 years. Most participants, 246 (68%), were male. The prevalence of non-adherence to TB medications was 14.4%. In the multivariable modified Poisson regression model, non-adherence to TB medications was associated with methadone use (adjusted prevalence ratio (aPR) = 3.04; 95% CI: 1.69–5.46) and spending 1–2 hours at the hospital (aPR = 4.44; 95% CI: 1.16–16.97). A strong healthcare worker-patient relationship was associated with lower odds of non-adherence (aPR = 0.41; 95% CI: 0.25–0.67).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, non-adherence to TB medications among current TB patients was low. Very bad to good relationship with HCWs was associated with good adherence to TB medications while methadone use, and spending 1–2 hours at the hospital were significantly associated with non-adherence to TB medications.\u003c/p\u003e\n\u003cp\u003eClinical trial number: Not applicable.\u003c/p\u003e","manuscriptTitle":"Prevalence and Factors Associated with Non-adherence to Antituberculosis Medications in Dar es salaam, Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 15:42:23","doi":"10.21203/rs.3.rs-6857120/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-08T13:14:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-03T07:48:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-24T11:04:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-20T14:57:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-10T15:55:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"164662583036093756589413118988965440193","date":"2025-08-10T15:43:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115576790485183308122974273189132740467","date":"2025-08-09T09:12:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128180224171343323802698050933807457729","date":"2025-08-08T11:54:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"109954908978628047870824574575577937144","date":"2025-08-06T05:30:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"100739526637913107182154357170354325976","date":"2025-08-06T04:42:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-06T03:01:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-06T16:42:22+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-03T17:27:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-03T09:47:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-07-03T09:43:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f8a02040-e8df-4466-ab6d-9a83bfd3af35","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-10T15:23:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 15:42:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6857120","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6857120","identity":"rs-6857120","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}