Barriers to and enablers of adherence to the treatment of active drug-sensitive tuberculosis in people living with HIV: a mixed method systematic review

Abstract

Background

Adherence to tuberculosis (TB) treatment is essential in improving treatment outcomes and reducing TB-related mortality. People living with HIV (PLWH) are at a higher risk of developing and dying from TB. This systematic review aims to identify barriers and enablers affecting TB treatment adherence among people with HIV/TB coinfection.

Methods

A systematic search of the literature was carried out in January 2023 across four databases including MEDLINE, EMBASE, CINAHL, and the Cochrane Database of Systematic Reviews. The search strategy incorporated both subject keywords and MeSH terms related to “tuberculosis” AND “HIV” AND “adherence” AND “barriers” OR “enablers” and relevant synonyms, limited to English language publications from 2010 onwards. An integrative method was used to synthesise the data obtained from selected studies. Identified factors were categorized using a modified World Health Organization (WHO) framework for treatment adherence.

Results

Of the 3,216 studies yielded by the search, 21 studies met the inclusion criteria and were included in the final analysis. Reported barriers to adherence included male gender, presence of comorbidities, advanced HIV/TB disease, alcohol consumption, tobacco use, low socioeconomic status, limited knowledge of TB, stigma, negative interactions with healthcare services, and systemic deficiencies in healthcare delivery. In contrast, enablers of adherence included being married, educational achievement, employment, social support, nutritional support, SMS reminders, adequate disease knowledge, concurrent antiretroviral therapy (ART), and positive relationships with healthcare providers. The influence of factors such as age, family size, partner’s HIV status, and partner’s ART status on adherence remained inconclusive.

Conclusion

Adherence to TB treatment among individuals with HIV/TB coinfection is significantly influenced by social determinants, including educational level, socioeconomic status, and the quality of healthcare service delivery. Targeted interventions addressing these determinants may enhance treatment adherence and improve treatment outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-25631-7.

Background

A total of 1.25 million people died from tuberculosis (TB) in 2023. Globally, 10% of people with TB have HIV coinfection, and 20% of deaths from TB are among people living with HIV (PLWH) [1]. Worldwide, TB is the leading cause of death from a single infectious agent [1]. The case fatality rate of TB is as high as 20% in some parts of the world [1], and it also has significant economic implications [2]. It is predicted that the worldwide cost will reach approximately $984 billion in the next decade if TB incidence rates stay the same [2]. PLWH are more susceptible to developing active TB and dying from it. Although the advent of antiretroviral therapy (ART) and tuberculosis preventive treatments, including isoniazid preventive therapy (IPT), has helped reduce the incidence and mortality from HIV/TB coinfection, PLWH are still 16 times more likely to develop active TB than individuals without HIV [1, 3].

Anti-tuberculous therapy (ATT) drugs are efficacious in the treatment of TB, and the treatment success rate has improved in some areas globally, reaching 90%[1]. However, successful TB treatment outcomes are closely linked to patients’ adherence to medication and treatment plans [4]. The Directly Observed Therapy Short course (DOTS) strategy, which one of its pillars involves taking ATT under the direct observation of a healthcare professional, has been used extensively to improve adherence and achieve overall TB control [5]. However, its effectiveness has been debated [6, 7] and there are concerns about the implications of the strategy on human rights, its lack of consideration for wider socio-economic determinants of health, and the potential to intensify stigma associated with the treatment [7, 8]. It has also been shown to add to the financial burden of health service users [7].

The varying outcomes from DOTS and other strategies to improve adherence have also brought to the fore the need to always put socioeconomic determinants into context while planning adherence interventions and acknowledge that adherence is widely influenced by social and economic factors rather than just individual behaviour [9–12].

Also, factors such as short distances to health facilities and good communication have been shown to improve adherence to ATT during treatment [13]. On the other hand, drug side effects and lack of knowledge have been reported to constitute barriers to adherence [13]. Most other studies [14–17] did not include PLWH who form an important subset of people with TB. PLWH have been reported to have a lower treatment success rate and a higher risk of loss to follow-up (LTFU) from treatment compared to people without HIV [17–20]. To our knowledge, there are no systematic reviews evaluating adherence to ATT in patients with HIV/TB coinfection [21, 22]. In light of this, we conducted a systematic review to identify factors that enhance (enablers) or pose a challenge (barriers) to adhering to ATT in patients with HIV/TB coinfection.

Methods

A search of four databases (MEDLINE, EMBASE, CINAHL, and the Cochrane Database of Systematic Reviews) was conducted in January 2023 (Fig. 1). The search strategy incorporated both subject keywords and MeSH terms related to “tuberculosis” AND “HIV” AND “adherence” AND “barriers” OR “enablers” and relevant synonyms, limited to English language publications from 2010 onwards. Details of the search strategy are attached in the additional file (Annex 3: Search Strategy, supplementary file).

Fig. 1.

PRISMA flow chart showing selection of studies

Studies were screened and included in this review if they comprised a cohort of patients with HIV/TB coinfection and if they reported ATT adherence and factors/barriers/facilitators associated with it. Studies were excluded if they included children (aged less than 18 years), or people with latent, multidrug, or extensively drug-resistant TB (Table 1). We did not include drug-resistant TB as treatment regimens are often longer, TB drugs have more adverse effects, and adherence is likely to be different compared to drug-sensitive TB. In addition, to ensure methodological quality, grey literature, conference abstracts, reviews, commentaries, and case reports were excluded.

Table 1.

Inclusion and exclusion criteria of studies included in the systematic review

Criteria	Details
Inclusion	• Studies including cohorts of patients with HIV/TB coinfection. • Reported antituberculosis treatment (ATT) adherence. • Reported factors, barriers, or facilitators associated with ATT adherence. Both qualitative and quantitative studies were included.
Exclusion	• Studies involving children (< 18 years). • Studies involving latent TB, multidrug-resistant TB (MDR-TB), or extensively drug-resistant TB (XDR-TB). – Rationale: Drug-resistant TB regimens are longer, have more adverse effects, and adherence patterns differ from drug-sensitive TB. • Conference abstracts, reviews, commentaries, and case reports.

The 2018 version of the Mixed Methods Appraisal Tool [23] (MMAT) was used to assess the quality of the studies included in this review, as previously used by Oga-Omenka et al.[24] and Clifford et al.[25]. Scores were calculated as the percentage of criteria met out of five items specific to each study design in the tool. As reported in previous studies [24, 25], a cut-off of 60% was considered “acceptable quality”. All studies in this review met this predefined threshold (Annex 2: Quality Assessment Results, supplementary file).

Data extraction and analysis

Information on the study design, setting, population characteristics, HIV/TB diagnosis, treatment and adherence, and treatment outcomes was collected (Table 2). The first and second authors screened titles, abstracts, and full texts for eligibility, with disagreements resolved by discussing with the last author. Data extraction was performed independently by the first and second authors using a pre-designed Microsoft Word form developed specifically for this review. In studies where both ART and ATT adherence were measured, only the findings related to adherence to ATT were extracted. An integrative method [26] was employed to analyse the key findings reported by the selected studies. Quantitative findings were summarized according to effect sizes and proportions, while qualitative findings were summarized thematically (Table 3). Using the WHO framework of dimensions of factors that affect adherence [4], factors from both were then integrated and mapped into one of the following categories of the framework: sociodemographic/patient-related; socioeconomic status-related; factors related to knowledge, attitudes, beliefs, and perceptions about TB; stigma, disclosure, and social support factors; medication-related factors; disease-related, and health service-related factors (Fig. 2).

Table 2.

Characteristics of studies and summary of results

S/N	Author Year	Study Design	Country	Aim	Sample Size	Methods	Outcome Measured	Main Results
1.	Meda et al. 2014 [29]	Cross- Sectional Study	Burkina Faso	To identify potential determinants of medication adherence (MA) among patients with TB, HIV, or both	1043 patients which consisted 309 TB patients, 553 HIV/AIDS cases, and 181 patients co- infected with TB and HIV	Face-to-face interview using semi-structured questionnaires and data collection from clinical records.	Medication Adherence	In patients co-infected with TB and HIV Adjusted predictors of good medication adherence: good attitude towards TB/HIV. Adjusted predictors of poor medication adherence: high number of persons sleeping in the household. In patients without HIV Adjusted predictors of good medication adherence: no alcohol use, ever been lost to follow-up, and awareness of disease transmission. Adjusted predictor of poor medication adherence: lack of financial means to access care.
2.	Knight et al. 2015 [33]	Prospective observational Cohort Study	South Africa	To quantify changes in adherence to ATT associated with initiation of ART by prospectively measuring adherence to TB drugs immediately before and after initiation of ART	50 adult patients with TB who were ART- naïve at the time of initiation of ATT	Adherence to TB treatment was measured by pill count, self-report, and electronic Monitoring System (eMEMS).	Adherence to anti-TB treatment pre and post initiation of ART.	ART seemed to lead to an 8% – 10% decrease in the proportion of patients adherent to ATT. Employment was the only predictor for optimal adherence.
3.	Mazinyo et al. 2016 [32]	Retrospective Cohort Study	South Africa	To determine the level of adherence to concurrent administration of ART and ATT and to identify risk factors for non-adherence in two South African provinces from 2008 to 2010.	1,252 patients receiving concurrent ART/TB treatment	Data extraction from clinical records	Adherence to concurrent ART/TB treatment and factors associated with non- adherence	Factors associated with non-adherence are extrapulmonary TB (RR: 1.71, 95% CI:1.12 to 2.60) and not disclosing HIV status (RR: 1.96, 95% CI: 1.96 to 3.76)
4.	Ukoha-Kalu et al. 2020[43]	Cross- Sectional Study	Nigeria	To assess the degree of drug adherence and its determinants in patients with TB/HIV co-infection	60 patients with HIV/TB co- infection attending the ART clinic at the Federal Medical Centre.	Interviewer- administered questionnaire	Adherence, health literacy of patients, relations, healthcare providers	Forgetfulness, adverse effects, and lack of money for transportation (all <20%) were the major reasons reported by the patients as to why they missed their medications
5.	Naidoo et al. 2013 [28]	Cross- Sectional Study	South Africa	To investigate factors associated with adherence to ATT and ART To specifically investigate the significance of alcohol misuse as a predictive factor for non-adherence to ATT and to dual therapy (ATT/ART)	757 HIV positive patients on both ART and ATT	Socio- demographic questionnaire, Kessler Psychological Distress scale, AUDIT – Alcohol Use Disorder Identification Test, Self- reported information	Adherence to dual therapy of ART and ATT	In patients with TB/HIV co-infection: Predictive factors for non- adherence: medium poverty [OR: 2.60 (1.46– 4.65)] High levels of poverty [OR: 3.89 (1.87–8.12)] Having one (1) chronic health condition [OR: 2.73 (1.31–5.65)] Having three (3) or more chronic conditions [OR: 5.33 (2.27–12.55)] High risk for alcohol misuse [OR: 13.09 (2.96–57.990)] Having a partner who is HIV positive [OR: 3.12 (1.84–5.29) Predictors of adherence: Perceiving health status as being ‘poor’ [OR: 0.20 (0.14–0.29)] Having a sex partner on ART [OR: 0.50 (0.25–0.97)]	In patients without HIV: Predictors of non-adherence: Medium levels of poverty [OR: 1.73 (1.34–2.24)] High levels of poverty [OR: 1.65 (1.14–2.39)] Having one (1) chronic health condition [OR: 1.86 (1.41–2.46)] Having three or more chronic conditions [OR: 2.37 (1.45–3.88)] High risk for alcohol misuse [OR: 3.06 (1.94–4.81)] Having a partner who is HIV positive [OR: 1.43 (1.10–1.84)]. Predictors of adherence: Perceiving health status as being ‘poor’ [OR: 0.44 (0.32–0.60)]. Perceiving health status to be ‘good’ [OR: 0.50 (0.37–0.67)]. Being HIV negative [OR: 0.44 (0.33–0.59)]
6.	Gebremariam et al. 2010[35]	Qualitative Study	Ethiopia	To explore patients' and health care professionals' views about barriers and facilitators to ATT adherence in TB/HIV co-infected patients on concomitant treatment for TB and HIV	15 patients with HIV and TB and 9 health care providers	In-depth interviews and Focus Group Discussions	Factors affecting medication intake	Factors that influenced adherence to ATT positively were beliefs in the curability of TB, beliefs in the severity of TB in the presence of HIV infection and support from families and health professionals. Barriers to treatment adherence were experiencing adverse effects, pill burden, economic constraints, lack of food, lack of disclosure of HIV or TB status due to fear of stigma, and lack of adequate communication with health professionals.
7.	Sardar et al 2010[37]	Cross- Sectional Study	India	To study the prevalence and determinants of non- adherence to intensive phase ATT in HIV patients	111 HIV-TB coinfection patients.	Interviewer- administered questionnaire	Adherence to ATT	Predictors of non-adherence: Visiting quacks during the intensive phase of ATT (aOR = 3.08, C.I. = 1.90, 5.08), the urge to leave treatment once patient started feeling better (aOR. = 4.05, C.I. = 2.0, 14.8), “No Counseling” (aOR= 47.12, 95% C.I. = 7.99, 195.27). Knowledge about correct route of transmission of TB was protective against non-adherence (a.O.R. = 0.29, 95% C.I. = 0.10, 0.38)
8.	Kebede et al. 2012 [36]	Cross- Sectional Study	Ethiopia	To assess the degree of drug adherence and its determinants in patients with TB/HIV co-infection	24 adult patients with HIV/TB co-infection in Tercha District Hospital in South Ethiopia	Interviewer- administered Questionnaire	ART and ATT adherence	Educational status and good patient health care provider relationship was significantly associated with adherence (P=0.000). The reason for the missed doses were mostly lack of money for transport (26.0%) and forgetting to take medications (17.4%)
9.	Maruza et al. 2011 [39]	Prospective Cohort Study	Brazil	To identify risk factors for default from ATT in people living with HIV.	339 HIV/TB co-infected patients in a clinic in Pernambuco, Brazil.	Follow-up of patient until treatment completion or default, interviewer- administered questionnaire, data extraction from clinical records.	ATT default	Risk factors were identified for default: male gender (aOR=2.28), smoking (aOR=2.62), CD4 count <200 cells/mm3 (aOR = 2.93) Protective factors for default: Age over 29 years (aOR = 0.50), complete or incomplete secondary or university education (aOR = 0.33) and the use of ART (aOR = 0.12).
10.	Satti et al 2016 [38]	Case Control Study	India	To assess the influence of patient related factors for DOTS treatment default among HIV-TB co-infected cases as compared to controls	120 HIV/TB co-infected patients and age-sex matched controls	Interview and structured questionnaire	ATT default	Significant risk factors associated with defaulting included unskilled occupation (AOR:3.56), lower middle class socioeconomic status (AOR: 17.16), small family size (AOR: 21.3), marital disharmony (AOR: 6.78), not being satisfied with the conduct of health personnel (AOR: 7.38), smoking (AOR: 8.5), poor knowledge score (AOR: 9.31) and adverse effects of drugs (AOR: 4.18).
11.	Ushie et al 2012 [44]	Qualitative Study	Nigeria.	To understand whether circumstances exist under which infected persons may have concerns about involving family and friends in their life and how this can influence their adherence to treatment	52 HIV/TB co infected patients	Six focus group discussions (FGDs), 4 case histories and 21 in-depth interviews (IDIs) were conducted	Influence of family on adherence	Overall, family support promotes adherence in co-infected patients.
12.	Elbireer et al 2011 [41]	Case Control Study	Uganda	To identify health facility and patient-specific factors associated with ATT default in HIV-infected patients.	127 cases and 217 unmatched controls	Interviews using a semi-structured questionnaire	ATT default	Factors associated with defaulting from were: Distance from home to clinic (OR: 2.22; 1.21–4.06); long waiting time at the clinic (OR 4.18; 2.18–8.02); poor drug availability (OR 4.75;2.29–9.84); conduct of staff (OR 2.72; 1.02–7.25); lack of opportunity to express feelings (OR 3.47; 1.67–7.21). Other patient-related factors were lack of health education, i.e. not being aware of the duration of treatment or the risk of discontinuing it (OR 5.31; 1.94–14.57); not knowing that TB can be cured (OR 44.11; 13.66–142.41); length of ATT (OR 10.77;5.18–22.41), and adverse effects of treatment OR 5.53 (2.25–13.61).
13.	Benzekri et al[47]	Randomised interventional study	Senegal	To compare the feasibility, acceptability, and potential impact of implementing two different forms of nutrition support for HIV-TB co-infected adults in the Casamance region of Senegal.	26 HIV-TB co-infected adults in the Casamance region of Senegal, West Africa	Nutrition support in the form of either a food basket or ready-to-use therapeutic Food, distributed monthly for six months.	Clinical outcomes, nutritional status, treatment adherence, and food security between two groups	The implementation of nutrition support was found to be feasible and acceptable to study participants. However, local food baskets were more acceptable. Adherence exceeded 95% for both ART and ATT in both groups.
14.	Kipp et al[30]	Prospective cohort study	Thailand	To identify the effects of TB and HIV stigma on missed doses during ATT	93 HIV/TB co-infected patients out of a cohort of 480 TB patients	Questionnaire, Pill count.	ATT default	Higher experienced and felt TB stigma was associated with increasing missed doses among HIV/TB co-infected patients (aRR 1.39). Experienced and felt HIV stigma also increased missed doses among HIV/TB co- infected patients (aRR 1.43, 95%CI 1.31–1.56) In patients without HIV: Little evidence that TB stigma had an effect on missed doses.
15.	Souza Damasio et al[40]	Cross-sectional study	Brazil	To evaluate the influence of social and clinical aspects in terms of medication adherence of patients co-infected with HIV/Tuberculosis	38 subjects	Interviews	Adherence to medications	Time of diagnosis for HIV above five years is related to lower adherence.
16.	Hermans et al[42]	Quasi-experimental study	Uganda	To test the effect of mobile phone text message reminder service on 8-week TB treatment LFU in individuals coinfected with HIV.	582 patients – 291 cases and 291 preintervention controls	Three different types of text messages: adherence reminders, reminders of upcoming appointments, and educational quizzes	Risk of LFU in the first 2 months of TB treatment	The SMS reminder service did not show a clear effect on short-term risk of LFU. However, the intervention was deemed as helpful by 96% of participants
17.	Hirsch-Moverman et al[46]	Interventional study	Lesotho	To describe the use and acceptability of the mHealth component of the START study intervention	835 individuals – including 633 patients and 202 treatment supporters in clinics across Lesotho	Automated SMS to provide reminders and adherence support. Interviews with participants	Effectiveness of the intervention package to improve early ART initiation and retention during tuberculosis (TB) treatment, as well as TB treatment success.	The adherence to TB medications was 89.1% in CIP versus 79.5% in SOC. About half of participants stated that the messages were a facilitator to adherence
18.	Kayigamba et al[48]	Retrospective cohort study	Rwanda	To examine the determinants of: adherence to TB treatment, sputum smear conversion at two months, and TB mortality. To also examine the independent effect of adherence on mortality.	581 of 725 new TB patients in the provinces. Treatment cards of 144 patients cannot be retrieved	Data extraction from clinical records	Determinants of: adherence to TB treatment, sputum smear conversion at two months, and TB mortality. The effect of adherence on mortality.	Those who were HIV infected but not on ART were significantly more often poorly adherent (OR 2.4; 95% CI 1.1–3.7). In multivariable analysis using logistic regression, adjusting for age and sex, only untreated HIV was significantly associated with poor adherence (OR 2.4, 95%CI 1.2–4.6).
19.	Pepper et al[34]	Prospective cohort study	South Africa	To determine factors associated with loss to follow-up during TB treatment	111 eligible to initiate ART at TB diagnosis according to national guidelines	Regression analysis	Factors associated with loss to follow-up during TB treatment	All TB patients who were lost to follow-up did not initiate ART. Using our logistic regression model, presentation to an ART clinic for assessment was the only factor associated with decreased loss to follow-up.
20.	Iweama et al[45]	Cross sectional study	Nigeria	To assess medication nonadherence and associated factors among tuberculosis patients in north-west Nigeria.	85 TB patients with TB/HIV co-infection	Pre-tested Tuberculosis Medication Adherence Questionnaire (TBMAQ)	Medication nonadherence	More than half (56.7%) reported that side effects of anti-TB drugs affected their treatment adherence. The use of ART and CPT medications was a strong risk factor (AOR = 24.9, 95% CI: 19.6–304.3) for TB medication nonadherence among patients.
21.	Masini et al[49]	Cross sectional study	Kenya	To identify patient-related factors that were associated with time to TB treatment interruption and the geographic distribution of the risk of treatment interruption by county	35% of the population that were HIV positive	Data extraction from clinical records. Survival analysis	Factors associated with time to treatment interruption	HIV-positive patients not on ART had higher treatment interruption rates than HIV-positive on ART. HIV patients who are on ART and HIV-negative patients have a noticeably longer time to treatment interruption compared to HIV-positive patients not on ART and patients who were not tested for HIV

Table 3.

Qualitative and quantitative findings of non-adherence to anti tuberculous treatment in HIV/TB co-infection

FACTOR	Quantitative Findings		Qualitative Findings
	Barriers to adherence	Enablers of adherence	Barriers to adherence	Enablers of adherence
Number of persons sleeping in the household	• Small family size (aOR: 21.3; CI: 6.4- 70.91) – a risk factor for treatment default [41]
	• The higher the number of persons sleeping in the household, the lower the adherence score (β = −0.058, CI: −0.105 - −0.012)[29]
Knowledge, Attitude, Beliefs, and Perceptions about TB.	• Poor knowledge score (aOR: 9.31 CI:2.83–30.56) was associated with treatment default[38]. • The urge to leave treatment once patient started feeling better (aOR. = 4.05, C.I. = 2.0, 14.8) [40]. • Lack of health education, i.e. not being aware of the duration of treatment or the risk of discontinuing it (OR 5.31; 1.94–14.57) [41] • Not knowing that TB can be cured (OR 44.11; 13.66–142.41) [41]. • Not knowing the duration of treatment (OR 10.77; 5.18–22.41) [41].	• The better the attitude, the higher the adherence score, (β = 0.148, CI: 0.047 - 0.249, p = 0.004), OR = 1.16 [41]. • Perceiving health status as being ‘poor’ (i.e. belief in the severity of health condition) [OR: 0.20 (0.14–0.29)[33]. • Knowledge about correct route of transmission of TB (aOR. = 0.29, 95% C.I. = 0.10, 0.38) [37].		Beliefs in the curability of TB and beliefs in the severity of TB in the presence of HIV infection influenced adherence positively [38].
Use of ART	• ART seemed to lead to an 8% – 10% decrease in the proportion of patients adherent to TB treatment according to pill count and an 18% – 22% decrease in the according to eMEMS in the first month following ART initiation independent of the cut-off used to define adherence (90%, 95% or 100% of prescribed doses taken) [37]. • The use of ART and CPT medications was a strong risk factor (AOR = 24.9, 95% CI: 19.6–304.3) for TB medication nonadherence among patients[45]	• Use of ART (aOR = 0.12, 95% CI = 0.05 - 0.33) was protective against treatment default [42]. • Those who were HIV infected but not on ART were significantly more often poorly adherent (OR 2.4; 95% CI 1.1–3.7) [48] • Not initiating ART was associated with lost to follow-up [34] • HIV-positive patients not on ART had higher treatment interruption rates than HIV-positive on ART. HIV patients who are on ART have noticeably longer time to treatment interruption compared to HIV-positive patients not on ART[49]
Educational Status		• Educational status was associated with (P=0.021) medication adherence [39]. • People with at least a secondary level of education have a lesser odd of defaulting (aOR = 0.33) [42].
Employment status or type.	• Unskilled occupation (aOR: 3.56; 95% CI: 1.1–11.56.1.56] associated with treatment default[38].	• Employment status was found to be significantly associated to medication adherence [38]. • Being employed was associated with optimal adherence (aOR - 4.11, 95% confidence interval 1.06–16.0) [34].
Economic and poverty related factors	• 20.0% said the reason they missed their medications was because they did not have money to transport themselves to the health facility[43]. • Medium and high levels of poverty [OR: 2.60 (1.46–4.65) and 3.89 (1.87–8.12 respectively)] were predictors of non- adherence [29]. • 26% cited lack of money for transport as the reason for missed doses[37]. • Lower middle-class socioeconomic status (AOR: 17.16; 95% CI: 3.93–74.82.93.82) was a risk factor for TB treatment default[38].		• Economic constraints posed a barrier to treatment adherence[38].
Food and nutrition	•	• Adherence exceeded 95% for patients who received nutritional support[47]	• Lack of food was associated with non- adherence. "That (food) is a very serious problem for many of our patients. They almost want to kill us wanting help. They come here asking for help from NGOs. They say that especially TB drugs increase appetite. They feel hungry after they start feeling well a bit, and food becomes a problem." (nurse)[38].
Extrapulmonary TB	Extrapulmonary TB was associated with non-adherence (RR: 1.71, 95% CI: 1.12 to 2.60)[32].
Stigma/Disclosure of HIV status	• Not disclosing HIV status to at least a friend or family member is a risk factor for non- adherence (RR: 1.96, 95% CI: 1.96 to 3.76) [36]. • Higher experienced and felt TB stigma was associated with increasing missed doses among TB/HIV co-infected patients (aRR 1.39, 95%CI 1.13–1.72) [35]. • Experienced and felt AIDS stigma also increased missed doses among TB/HIV co- infected patients (aRR 1.43, 95%CI 1.31–1.56)[35].		Stigma with lack of disclosure was associated with non-adherence. "I don't want neighbours to see me here [at the TB clinic][38].
Side Effects/Pill Burden	• Adverse effects of drugs (aOR: 4.18; 95% CI: 1.35–12.9.35.9) were associated with treatment default [38]. • 18.3% reported that experiencing adverse effects was the reason for missing ATT[45]. • Adverse effects of treatment (OR: 5.53, 2.25–13.61)[41]. • More than half (56.7%) reported that side effects of anti-TB drugs affected their treatment adherence[45]		• Adverse effects were a barrier to treatment adherence [35]. • Pill burden was a barrier to adherence [35].
Forgetfulness	• 17.4% cited forgetfulness as the reason for missed doses [37]. • 10 patients (16.7%) reported ‘forgetfulness’ as the reason for missing their anti - TB medications [43].
Presence of other chronic conditions	Having one chronic health condition and three or more chronic health conditions [OR: 2.73 (1.31–5.65) and 5.33 (2.27–12.55.27.55) respectively] were predictors of non-adherence[28].
Alcohol use	High risk for alcohol misuse [OR: 13.09 (2.96–57.990)] is a predictor of non-adherence[28].
Partner’s HIV status	Having a partner who is HIV positive [OR:3.12 (1.84–5.29)] is associated with non- adherence [28].
Partner’s ART status		Having a sex partner on ART [OR:0.50 (0.25–0.97)] is a predictor of adherence [28].
Social Support				• Support from families and health professionals associated positively with adherence [35]. • Family support promotes adherence in co-infected patients[44].
Communication/Relationship with Healthcare Workers	• Receiving “No Counselling” from healthcare workers (aOR. = 47.12, 95% C.I. = 7.99, 195.27) was a significant predictor of non- adherence [37]. • Not being satisfied with the conduct of health personnel (aOR = 7.38; 2.32–23.39.32.39) is a significant risk factor for non-adherence [38]. • Conduct of staff (OR 2.72; 1.02–7.25) [41]. • Lack of opportunity to express feelings (OR 3.47;1.67–7.21) [41].	Good patient - health care provider relationship was significantly associated with adherence (P=0.000)[46].	Lack of adequate communication with health professionals was a barrier to treatment adherence[35].
Visiting quacks	• Visiting quacks during the intensive phase of treatment was associated with non- adherence (aOR. = 3.08, 95% C.I. = 1.90, 5.08) [37].
Gender	• Being male (aOR = 2.28, 95% CI =1.06 - 4.94, P - 0.036) was associated with treatment default [39].
Smoking	• Smoking (AOR: 8.5; 95% CI: 2.31–31.21.31.21) is a risk factor for treatment default [38]. • People who smoke (aOR = 2.62, 95% CI =1.31 - 5.26, P - 0.007) have increased odds of treatment default [39].
CD4+ count	• CD4 T-cell count less than 200 cells/mm3 (aOR = 2.93, 95% CI = 1.56 - 5.23, P- 0.001) is a predictor of treatment default [39].
Age		Age over 29 years (aOR = 0.50; 0.25 −0.99) negatively correlated with treatment default [39].
Marital Status/Condition	Marital disharmony (aOR 6.78; 1.93–23.76.93.76) is a risk factor for treatment default [44].
Distance to clinic	Distance from home to clinic greater than 10 km (OR 2.22; 1.21–4.06) associated with treatment default [41].
Waiting time	Long waiting time at the clinic (OR 4.18; 2.18–8.02) [41].
Drug availability	Poor drug availability (OR 4.75; 2.29–9.84) [41].
SMS reminder	• Deemed helpful by 96% of participants[39]. • Adherence to TB medications was 89.1% in CIP versus 79.5% in SOC. About half of participants stated that the messages were a facilitator to adherence[48]
Time of diagnosis	• Time of diagnosis for HIV above five years is related to lower adherence[43]

Fig. 2.

Factors affecting adherence to anti-tuberculous treatment (ATT) in patients with HIV/TB co-infection. Adapted from WHO’s Framework of Adherence [4]

Factors that had statistically significant associations in quantitative analysis were sought, and in qualitative studies, we sought any theme reported as being contributory to adherence/non-adherence. Each barrier or enabler was ranked according to the number of studies that reported it and its relevance within each study as done by previous systematic reviews [23, 24] (Figs. 3 and 4, Annex 1: weighted ranking of factors, supplementary file). A factor (barrier or enabler) was ranked from one to three according to the significance of the finding. Three was allocated to a factor when it affects >50% of participants or has an OR/RR of < 0.65 or >1.5 for quantitative studies; and considered to be of significant relevance or mentioned by >50% of participants in a qualitative study. A factor is ranked two if it affects 25% − 50% of study participants or has an OR/RR of 0.65–0.8 or 1.25–1.5 for quantitative studies and is considered to be of moderate relevance or is mentioned by 25–50% of participants in a qualitative study. One is assigned to a factor that affects few participants (less than 25%) and a zero if factors are not mentioned. Exponentiation of beta coefficients was performed to obtain the odds ratio of factors reported in a logistic regression format [27]. Using studies [28–30] that included participants both with and without HIV, a descriptive comparison of results was made to highlight the differences in the barriers and enablers of adherence between both populations. The PRISMA 2020 guideline [31] was followed to report the findings from this review.

Fig. 3.

Barriers to adherence in patients with HIV/TB co-infection (each factor was ranked 1,2, or 3 based on its importance in the study that reported it and the scores in all studies that reported it was totalled)

Fig. 4.

Enablers of adherence in patients with HIV/TB co-infection (each factor was ranked 1,2, or 3 based on its importance in the study that reported it and the scores in all studies that reported it was totalled)

Results

Characteristics of the included studies

The search yielded a total of 3,216 articles. After deduplication, screening of titles, and review of abstracts and full texts, 21 articles fulfilled the inclusion criteria (Fig. 1). All the studies included had scores of at least 60% in the quality assessment tool meeting the acceptable threshold. All the included studies were conducted in low and middle-income countries. Four studies were conducted in South Africa [28, 32–34]. Two studies each were carried out in Ethiopia [35, 36], India [37, 38], Brazil [39, 40], and Uganda [41, 42]. Three in Nigeria [43–45], while Burkina Faso [29], Lesotho [46], Senegal [47], Rwanda [48], Kenya [49], and Thailand [30] accounted for each of the remaining studies. Furthermore, all the countries except Burkina Faso and Uganda belong to the WHO TB and HIV/TB high burden countries (HBCs) [50] list. Eight out of the 21 included studies were cross-sectional studies [28, 29, 36, 37, 40, 43, 45, 49], two were retrospective cohort studies [32],4847, four were prospective cohort studies [30, 33, 34, 39], two were case control studies [38, 41] and qualitative studies [35, 44], one was quasi-experimental [42] and two were randomised controlled trials [46, 47].

Sociodemographic and patient related factors

Men appeared to be more likely to be nonadherent to ATT [28, 32, 33] with rates of nonadherence more than twice that of women in a study conducted in Brazil (aOR 2.28; 1.06–4.94) [39]. Marital disharmony, defined as being single, widowed, or divorced, was found to be a risk factor for lost to follow-up[38] (aOR 6.78; 1.93–23.76) while being married appeared to be protective against nonadherence [37, 39]. In a study conducted in Burkina Faso, a high number of people living in a household [29] was reported to constitute a barrier while in an Indian study, a small family size [38] was a barrier to adherence. Other patient-related factors identified as barriers were forgetfulness, which was cited as the reason for missing doses by approximately 20% of participants in two studies [37, 43], visiting quacks [37], and having additional comorbid health conditions (OR 5.33; 2.27–12.55) [28].

Alcohol use [28, 39] and smoking [38, 39] were reported as barriers, and adherence appeared to be better for people who did not consume alcohol [37, 38]. Age >29 years was protective against nonadherence in one study [39] and another study showed that nonadherence was lower within the age range of 20–34 years [37]. A study from Uganda [41] showed that persons lost to follow-up were more likely to be younger (less than 35 years) than non-defaulters were (less than 37years); similarly, in South Africa [33], older age was associated with better adherence.

Socioeconomic status related factors

The socioeconomic status-related factors found to negatively impact adherence were medium and high levels of poverty (OR 2.60; 1.46–4.65 and 3.89; 1.87–8.12) respectively [28], belonging to lower- middle-class socioeconomic status, and being an unskilled worker [38]. Other factors associated with nonadherence included lack of money for transport to healthcare facilities to obtain medications [37, 43], and lack of food [35]. The provision of meals or food vouchers for patients was found to significantly improve adherence [47]. Individuals who had received some education (at least secondary level) [36] or could read and write [33], and those who were employed [33, 43] were found to have a lower risk of defaulting from treatment.

Knowledge, attitudes, beliefs, and perceptions about TB

Poor knowledge of TB (aOR 9.31; 2.83–30.56) [38], feeling the urge to stop treatment once feeling better [37], and not receiving health education [41], i.e., not being aware of the risk of discontinuing treatment, were all shown to be associated with an increased risk of treatment default. Similarly, not knowing that TB can be cured [41] and not knowing the duration of treatment [41] were associated with an increased risk of nonadherence.

Conversely, knowing that HIV/TB coinfection is a cause of poor health (OR 0.20; 0.14–0.29) [28], and good knowledge of the correct route of transmission of TB (aOR 0.29; 0.10–0.38) [37] were associated with decreased nonadherence. A positive attitude toward TB, an understanding of adherence [29] and the curability of TB; and insight into the severity of TB in the presence of HIV coinfection favourably influenced adherence [35].

Stigma/disclosure of HIV/TB status and social support

The stigma of both TB and HIV experienced by patients increased the rate of nonadherence in patients with HIV/TB coinfection compared to that in TB patients without HIV [30]. Moreover, a lack of disclosure of HIV and/or TB status due to fear of stigma was found to increase the risk of nonadherence [32, 35]. Support from family members [44] and from healthcare professionals [35] was found to be helpful in promoting adherence.

Medication-related factors

Experiencing adverse effects of drugs/treatment was reported to contribute to nonadherence [38, 41]. About one in five patients [31], and more than half of patients [45] missed their ATT due to adverse effects [43] with complaints of pill burden regarded as an additional barrier [35].

Disease-related factors

The risk of nonadherence appears to be greater in patients with advanced HIV (low CD4 + count < 200cells/mm³)[39], and in those with extrapulmonary TB[32] and in people who have been diagnosed with HIV for more than 5 years [40]. The use of ART was found to be a barrier in a South African study [33] (causing an 8–22% decrease in adherence to ATT) and a Nigerian study [45]. However, four studies [34, 40, 48, 49] found that being on ART was a protective factor against being lost to follow-up with people on ART having lesser rates of treatment interruption and non-adherence [38].

Partner’s HIV status and partner’s use of ART influenced adherence to ATT differently in studies. For example, a study from South Africa [28] reported that having a partner with HIV (OR 3.12; 1.84–5.29) was associated with nonadherence but having a partner on ART (OR 0.50; 0.25–0.97) was a predictor of good adherence.

Health service-related factors

Not being counselled about their health conditions [37, 41], dissatisfaction with the conduct of healthcare providers and inadequate communication with them [35, 38], feeling that the conduct of staff is poor [41], and not ever being given a chance to express concerns about their TB treatment [41] were all associated with an increased likelihood of nonadherence to treatment. Distance to clinic greater than 10 km, long clinic waiting times, and poor drug availability, as in occasional stockouts, were also found to be predictors of nonadherence in a study from Uganda [41], while a good patient–healthcare provider relationship was found to enhance adherence [36]. Sending reminder text messages appeared to improve adherence and was found to be helpful by patients [42, 46].

Adherence in patients with HIV/TB coinfection compared to patients with TB only

Three studies [28–30] among the twenty-one included in this review compared patients with HIV/TB coinfection with TB patients without HIV (Table 3). Naidoo et al.[28] showed that four common factors are associated with nonadherence to ATT in both TB patients without HIV and patients with HIV coinfection: poverty, the presence of comorbid conditions, alcohol misuse, and having an HIV-positive partner. However, the odds of nonadherence in TB patients with HIV, with respect to each of these factors, were twice as high as those in patients with TB who were not HIV positive. For example, the adjusted odds ratio (OR) of nonadherence due to high levels of poverty was 1.65 (1.14–2.39) in patients without HIV, while the adjusted OR was 3.89 (1.87–8.12) in TB patients with HIV. TB stigma appeared to have a lesser effect on adherence in TB patients without HIV, while it was associated with increased rates of missed doses in patients with HIV/TB coinfection in one study [30] indicating that PLWH with TB may experience higher rates of stigma compared to those without HIV.

Discussion

This review highlights that social determinants of health including sociodemographic status, education, socioeconomic status, and healthcare service delivery, have a significant impact on ATT adherence in patients with HIV/TB coinfection. It demonstrates that gender, comorbid health conditions, alcohol use, smoking, poverty, poor knowledge of TB, and poor experience of healthcare services are barriers to adherence, while being employed, using text messages, good social support, and having good disease knowledge all support adherence. The impact of the use of ART on ATT adherence also seems positive. Partner’s HIV status on adherence could not be determined in this review given the small number of studies that examined the relationship and the heterogeneity of the studies included.

Studies reported poorer adherence among individuals who are uneducated, unemployed, and people living in poverty [28, 33, 38, 39, 43] (Fig. 3). This could result from inability to afford treatment/medication or even when medications are free, as in many national TB programmes, could be due to out-of-pocket expenditures (e.g., payment for laboratory tests) incurred by patients (at catastrophic costs) [51–54] leading to poor adherence. Other related factors include lack of funds for transport to healthcare facilities [37, 43], and lack of food [35]. Patients may miss drugs because of the belief that using medications on an empty stomach could be harmful [55]. Nutritional interventions involving the provision of food packages were found to increase adherence rates to ATT up to 95%[47]. Making ATT free alone may not be enough to decrease nonadherence, rather, empowering patients economically and addressing the wider economic constraints of patients, including nutritional support, may yield better treatment outcomes.

This review demonstrated a direct relationship between good knowledge and understanding of TB and HIV disease and adherence to TB treatment and between the negative effect of inadequate knowledge and adherence [29, 37, 41] (Fig. 4). This may be the result of not receiving counselling at the point of diagnosis and not being educated by healthcare professionals about TB[38]. The lack of counselling was the single most influential factor contributing to non-adherence in one study [38]. It is therefore imperative that patients are adequately educated about their condition and empowered to participate in the care of their health.

In addition, men, unmarried individuals, and those who smoked or abused alcohol were identified as less adherent in this review. Similar findings were reported in other studies regarding the effects of gender [56–59] and marital status [60–63] on treatment adherence. Furthermore, health service-related factors, including long distance to care, inadequate communication, and poor relationships with healthcare staff, and poor treatment of patients by healthcare providers, negatively impact adherence [35, 37, 38, 41]. Healthcare service delivery, including good patient-healthcare provider relationships, accessibility to healthcare, and availability of skilled healthcare providers, has an important impact on patients’ health behaviour and treatment outcomes. For example, while long distance to clinics in and of itself has been found to be a barrier to adherence [41], lack of transport money to travel to such clinics and unavailability of medication after travelling long distances [38, 41], may also lead to a loss of motivation to adhere to treatment regimens [37, 40]. Easier access to healthcare services closer to service users and transport vouchers may improve adherence and treatment outcomes [22, 64]. The use of smart and electronic pill boxes, which alert patients to take their medications, could be useful for those taking both ART and ATT, as these devices have been shown to improve adherence in other chronic diseases [65, 66]. Pill burden was a barrier to adherence in our review. The use of fixed drug combinations (FDCs) for the treatment of TB reduces the pill burden in PLWH who also have to take ART [67–69].

Our review showed that facilitators of treatment adherence, such as good disease knowledge, have less of an effect on patients with HIV/TB coinfection than on those without HIV. Barriers to adherence, including poverty and having comorbid conditions, were more common in patients with HIV/TB coinfection than in those with TB alone.

The effects of stigma on adherence were also greater in patients with HIV/TB coinfection than in those without coinfection. A diagnosis of HIV is associated with a high risk of stigma due to the perception that the infection is a product of individual lifestyle choices since the routes of transmission are mostly sexual [70]. HIV stigma includes patients feeling ashamed or guilty of their status. This has been shown to lead to refusal to seek treatment or to disclose their HIV status [71] which may have contributed to nonadherence to ATT [72, 73].

This is the first systematic review evaluating the factors affecting adherence to ATT in patients with HIV/TB coinfection, thereby addressing a significant literature gap. We aligned our findings with the WHO framework [4] for adherence which enabled a structured synthesis and holistic understanding of identified factors. A limitation of our review is the significant heterogeneity among the included studies which prevented meta-analysis and limited the synthesis of our results. The definition of adherence was not consistent among the studies. For example, adherence was defined as having a low score on a standardised adherence scale in one study [29], and in the majority of other studies, as the percentage of doses missed. Some studies reported only the default of treatment or patients being lost to follow-up, making comparisons between studies difficult [74].

Furthermore, heterogeneity was observed in study populations and treatment delivery. In some studies, not all PLWH were taking ART, making it difficult to evaluate the effect of taking ATT on ART adherence. Also, some patients received treatment under the Directly Observed Treatment Short course (DOTS), and some did not. Some studies focused solely on the intensive phase of ATT, while others described the full treatment course. In addition, the effect of measures to improve adherence which have been introduced over the years like fixed-dose combinations (FDCs) cannot be concluded from our review as most studies did not indicate which treatment formulation was administered to PLWH. Moreover, all included studies were carried out in high-TB incidence, low-income countries, mostly in sub-Saharan African countries; therefore, our findings may not be applicable to high-income, low-incidence TB countries where health system structures and patient populations differ.

However, the fact that factors such as stigma, poverty, and social support were consistently reported across the studies may strengthen confidence in their significance. The limitations also highlight the implications for future research including the need for standard definitions and measures of adherence and studies from a wider range of settings.

Conclusion

This review summarises the factors associated with adherence to ATT in patients with HIV/TB coinfection, including socioeconomic, sociodemographic, stigma, disease severity, medication- and health-service-related factors. Male gender, other comorbid conditions, advanced HIV infection, severe TB disease, poverty, and poor disease knowledge limit adherence while being employed, and having good social support and good patient-healthcare provider relationships improve adherence. Patients with HIV/TB coinfection had worse adherence rates than did TB patients without HIV. Finally, we showed that socioeconomic status and healthcare provider-level factors, rather than individual-level factors, are the most important factors affecting adherence.

While it has been shown that interventions such as providing food and transport vouchers, financial aid, DOTS, and free TB care (including diagnostics and medication), may improve adherence in patients with HIV/TB coinfection, we recommend that governments and policymakers should ensure people are economically empowered and address disparities of wider socioeconomic factors and social determinants of health to improve adherence to treatment, improve treatment success, in order to achieve global TB control.

Abbreviations

TB

Tuberculosis

HIV

Human immunodeficiency virus

ATT

Anti-tuberculous therapy

SMS

Short message services

ART

Antiretroviral therapy

PLWH

People living with HIV

IPT

Isoniazid preventive therapy

HBCs

High burden countries

AOR

Adjusted odds ratio

Authors’ contributions

AL: Conceptualised the study, designed it, acquired, screened, and analysed the data, drafted the initial manuscript, and made reviews on the final manuscript. AH: Screened and analysed the data, made substantial review to the final manuscript. ST: made substantial review to the final manuscript. HK: Supervised the study, screened the data, interpretation of results, made substantial review to the final manuscript. All authors read and approved the final version of the manuscript.

Funding

The authors did not receive any funding for this work.

Data availability

All data relevant to the study are included in the article and additional file.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

ST is employed by and a shareholder of GSK. His comments and opinions are his own and not that of the company.Rest of the authors declare no conflict of interests.