0Tuberculosis Treatment Outcomes in Tanzania: A Systematic Review of interventional and operational studiesPhilbert Balichene Madoshi1. Jovin R. Tibenderana1., Godfrey Katusi3, Theresia A. Karuhanga4 & Robert S Machang’u2OriginalPaper11201812879Running title: Nutritional support enhances TB recovery in undernourished1Department of Public Health, St. Francis University College of Health and Allied Sciences, P. O. Box 175, Ifakara-Tanzania2St. Francis University College of Health and Allied Sciences, Department of Microbiology and Immunology, P. O. Box 175, Ifakara-Tanzania3St. Francis University College of Health and Allied Sciences, Department of Parasitology and Entomology, P. O. Box 175, Ifakara-Tanzania4St. Francis University College of Health and Allied Sciences, Department of Surgery and Trauma, P. O. Box 175, Ifakara-TanzaniaCorresponding AuthorE-mailbmadoshi@gmail.comKeywords:TuberculosisNutritionIfakaraSupplementsMultidrug resistanceTanzaniaAuthor contributionsConceptualization: [PB Madoshi, JR. Tibenderana & RS. Machang’u]Methodology: [PB Madoshi]Data curation: [PB Madoshi, G Katusi & TA Karuhanga]Formal analysis: [PB Madoshi, JR. Tibenderana & RS. Machang’u]Writing original draft: [PB Madoshi & TA Karuhanga]Data analysis: [PB Madoshi G Katusi & TA Karuhanga]Final manuscript: [PB Madoshi, JR. Tibenderana & RS. Machang’u]AbstractBackgroundTuberculosis (TB) remains a leading cause of morbidity and mortality worldwide, with Tanzania being among the high-burden countries. Malnutrition is both a risk factor for TB and a barrier to recovery, yet evidence on the effectiveness of nutritional interventions in improving treatment outcomes remains fragmented. This systematic review synthesized available evidence on the role of nutritional support in enhancing TB outcomes in Tanzania and comparable sub-Saharan African settings.Methods: We conducted a systematic review using PRISMA 2020 guidelines. We searched PubMed, Embase, Scopus, Web of Science, CINAHL, Cochrane Library, and African Journals Online (AJOL) for studies published between 2000 and June 2025. Grey literature from WHO, government reports, and conference proceedings were included. Search strategies combined MeSH terms and keywords related to tuberculosis, nutrition, malnutrition, dietary supplements, Tanzania, and Africa. No language restrictions were applied provided such studies were in the study scope.Two reviewers independently screened records, with disagreements resolved by a third reviewer. Eligible studies included randomized controlled trials, quasi-experimental, cohort, and cross-sectional designs assessing nutritional interventions (macronutrients, micronutrients, food support, or counselling) and reporting TB outcomes (treatment success, cure, mortality, adherence, weight/BMI gain, or quality of life). Risk of bias was assessed using ROB 2.0, ROBINS-I, or JBI tools. Data were extracted with standardized forms and synthesized narratively; effect measures were pooled using random-effects meta-analysis where possible.Results:Eighteen studies involving about 5,007 participants met inclusion criteria. Most reported positive associations between nutritional interventions and improved outcomes, including higher treatment completion, greater weight gain, and reduced mortality. Macronutrient and food-based interventions showed consistent benefits, while effects of micronutrient supplementation were mixed. Operational studies highlighted challenges of implementation and sustainability in resource-limited contexts.Conclusions: This review demonstrates that nutritional support enhances TB treatment outcomes in Tanzania and related settings. Evidence indicates that food-based and macronutrient interventions improve weight gain, adherence, and treatment success, while revealing persistent gaps in evidence for micronutrients and program sustainability. Findings provide timely guidance for policy, supporting the integration of nutritional interventions into Tanzania’s National TB Program and informing broader One Health nutrition strategies.IntroductionRationaleTuberculosis (TB) is one of the leading causes of morbidity and mortality globally, with a disproportionately high burden in low - and middle-income countries (LMICs). An estimated 10.6 million people fell ill with TB in 2022, with over 80% of cases reported in (1). Under-nutrition not only increases susceptibility to TB infection and disease progression but also impairs treatment outcomes and delays recovery (2,3). Malnutrition impairs cell-mediated immunity, a crucial defense mechanism against Mycobacterium tuberculosis infection, thereby increasing both the risk of TB disease and the likelihood of poor treatment response (3). TB leads to significant nutrient uptake and weight loss, further exacerbating the poor health of affected individuals (4). Recognizing this interplay, WHO recommends nutritional assessment and support as part of standard TB care, particularly in settings where food insecurity and under-nutrition are prevalent (1). Despite the growing awareness, evidence regarding the effectiveness of nutritional interventions, ranging from macronutrient supplementation and food support to micronutrient fortification on TB treatment outcomes and recovery, remain limited and inconsistent. Moreover, most evidence has been generated by studies with heterogeneous designs and interventions, making it difficult to draw generalized conclusions, especially in resource-constrained settings (6,7).Studies in Tanzania have demonstrated that malnutrition and micronutrient deficiencies significantly influence TB treatment outcomes, including weight recovery, treatment success, and survival. It is proposed that nutritional assessment and support should be integral components of TB care strategies in high-burden settings. Isanaka et al. (8) studied patients at the National multidrug-resistant TB (MDR-TB) center, the authors reported 53% of the participants being malnourished (Body Mass Index (BMI) < 18.5 kg/m²). Similarly, Kawai et al. (9) in assessment of nutritional changes before, during, and after TB treatment, showed a significant weight gain after therapy, though full recovery of body composition remained incomplete. Isanaka et al. (10) conducted a cohort study on micronutrient supplementation in TB co-infected patients to determine predictors of change in BMI among TB patients, while PrayGod eta al. (11) supplemented TB patients with micronutrients, and found that 9% of those supplemented still experienced nutritional deterioration. These findings underscore that both multidrug-resistant and drug-sensitive TB patients present with significant levels of malnutrition. This necessitates improved nutritional knowledge among clinicians, and patients, to enhance recovery and reduce disability-adjusted life years (DALYs). While several randomized controlled trials (RCTs) and operational studies in different countries have explored the role of nutrition in TB care, their findings vary, and synthesis of the evidence is lacking, particularly developing countries. Tanzania faces unique challenges, including: high disease burden, food insecurity, poverty, and weak health systems, all of which influence both the feasibility and effectiveness of nutritional support interventions (12–15). A systematic review, focusing specifically on interventional and operational research in Tanzania, is therefore essential to consolidate existing knowledge, identify effective strategies, and implementation challenges. Such evidence will support policy development and inform programmatic approaches for integrating nutrition into TB care models, ultimately contributing to improved treatment outcomes and patient recovery.While several randomized controlled trials (RCTs) and operational studies in different countries have explored the role of nutrition in TB care, their findings vary, and synthesis of this evidence is lacking, particularly within the context of developing countries. Tanzania faces unique challenges, including high disease burden, food insecurity, poverty, and weak health systems, all of which influence both the feasibility and effectiveness of nutritional support interventions. A systematic review focusing specifically on interventional and operational research in Tanzania, it’s therefore essential to consolidate existing knowledge, identify effective strategies, and highlight implementation challenges. Such evidence can support policy development and inform programmatic approaches for integrating nutrition into TB care models, ultimately contributing to improved treatment outcomes and patient recovery.ObjectivesThis systematic review aims to:1.Assess the impact of nutritional interventions on TB treatment outcome, including: treatment success, cure rates, treatment completion, and reduction of mortality in Tanzania.2.Evaluate the effect of such interventions on recovery indicators, such as weight gain, body mass index (BMI), immune function, and quality of life.3.Identify and synthesize findings from interventional and operational studies to inform future policy and implementation strategies.Methods This review synthesizes evidence on the impact of nutritional interventions on tuberculosis (TB) treatment outcomes in Tanzania, from interventional and operational perspectives. Given the dual burden of TB and under-nutrition, and the increasing integration of nutrition into TB care, this review aims to provide a comprehensive assessment of how different forms of nutritional support influence clinical and programmatic outcomes. Although the review was intended to assess the operational studies on TB recovery and nutritional support in Tanzania, the authors assumed few studies could have been carried, thus in order to increase the scope of the data, studies from East Africa countries were used in the discussion of this review.Eligibility CriteriaWe included interventional (randomized and quasi-experimental) and operational studies reporting on nutrition support in TB patients in Tanzania. Studies were selected based on the following inclusion and exclusion criteria:The inclusion criteria included:1.Patients of any age with active tuberculosis (pulmonary or extra pulmonary) living in Tanzania.2.Interventions: nutritional supplement (macronutrient supplementation, micronutrient supplementation, food rations, therapeutic feeding) were considered eligible.3.Comparison of the studies with respect to the standard TB treatment without nutritional supplementation or alternative nutritional interventions.4.TB treatment outcomes (cure rate, treatment completion, treatment failure, relapse, mortality), and recovery indicators (weight gain, BMI, immune response, quality of life).5.Study design used which included Randomized controlled trials (RCTs), quasi-experimental studies, and operational or implementation research studies.6.Publication of the study in peer-reviewed articles which worked on TB treatment recovery and nutritional support.The Exclusion Criteria included:1.Observational studies without interventions.2.Studies conducted in high-income countries, and3.Case reports, reviews, editorials, and commentaries.Information SourcesThe electronic databases included: PubMed/MEDLINE, EMBASE, Scopus, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), and World Health Organisation - Global Index Medicus. Furthermore, grey literature was searched through WHO, World Bank, and conference proceedings related to TB and nutrition.Search strategyA comprehensive search strategy was developed using medical subject headings (MeSH) and text words related to tuberculosis, nutrition, treatment outcomes, recovery, and developing countries. A sample search string for PubMed: ("Tuberculosis"[MeSH] OR "TB") AND ("Nutrition Therapy"[MeSH] OR "Nutritional Support" OR "Dietary Supplements" OR "Micronutrients" OR "Food Supplementation") AND ("Treatment Outcome"[MeSH] OR "Recovery" OR "Weight Gain" OR "Immune Recovery") AND ("Tanzania"[MeSH] OR "Low-Income Countries" OR "Resource-Limited Settings") AND ("Intervention Studies" OR "Operational Research" OR "Randomized Controlled Trial"). The final search was completed in [June, 2025], and reference lists of included studies were screened for additional eligible articles. No language restrictions were applied; non-English studies were translated where feasible, and abstracts were used when full translation was not possible.Data selection processTwo independent reviewers screened titles and abstracts for relevance. Full-text screening was conducted for potentially eligible studies. Disagreements were resolved through discussion or consultation with a third reviewer. The study selection process was documented using a PRISMA flow diagram (Fig. 1).Figure 1: PRISMA 2020 flow diagram for new systematic reviews which included searches of databases and registers only (16)Data Collection ProcessData extraction was performed independently by two reviewers using a standardized, pilot-tested extraction form. Extracted data were cross-checked for accuracy. Any discrepancies were resolved by consensus or third-party adjudication.Data Items (outcomes)We searched studies which reported in clinical, microbiological, nutritional, adherence to TB therapy and implementation outcomes. The data on Clinical outcomes were measured for cure, treatment completion/success, failure, death, loss-to-follow-up, and relapse/recurrence. The Microbiological outcomes were measured on studies which presented positive results on smear or culture conversion and time-to-conversion; recurrence genotype-confirmed where available. The review also went through articles which reported on nutritional status of the participants which included change in weight (kg), BMI (kg/m²), MUAC (cm), child growth z-scores and anaemia. On the other the articles on quality of life were reviewed such as validated scales and adherence to TB therapy and to the nutrition intervention (pill/sachet counts, electronic or self-report).Data Items (other variables for which data were sought)Under this category, the authors searched articles which included demographics data (age, sex, pregnancy, HIV/ART, comorbidities), TB descriptors such as pathogen development and drug resistance, intervention details and outcome times (intensive, end, post-treatment). Our assumptions were based on the mapped non-WHO outcomes to WHO categories where codes like not reported were used.Risk of bias assessmentRisk of bias was assessed using design-specific tools: randomized trials with RoB 2 where randomization, deviations, missing data, outcome measurement and selection of reported result were the main domains. Whereas the non-randomized and quasi-experimental studies were assessed with ROBINS-I while the observational designs were assessed using JBI critical-appraisal checklists. Two reviewers independently applied tools after piloting; disagreements were resolved by consensus/third reviewer. For ROBINS-I, pre-specified confounders (age, sex, HIV/ART, baseline BMI/MUAC, TB severity, SES) and co-interventions were considered. Cluster trials used the cluster-specific RoB 2 variant when applicable. The judgements followed official categories which were low. Or high for RoB 2, low/moderate/serious/critical for ROBINS-I and were summarized in Table 2.Effect MeasuresThe primary summary measures were relative risks (RRs) or odds ratios (ORs) for categorical outcomes (e.g., treatment success, mortality) and mean differences (MDs) or standardized mean differences (SMDs) for continuous outcomes (e.g., weight gain, BMI). Effect estimates were reported with 95% confidence intervals (CIs), and the results of the effect measures are presented in Table 1 below.
Table 1Results of the effect measures of the reviewed articles
Effect MeasureOutcome AssessedExample StudiesTreatment Success Rate (Cure & Completion)Proportion of patients achieving cure or completing treatment(17,18)Mortality RateDeaths during TB treatment(8)Time to Sputum Culture ConversionDuration for culture negativity post-treatment initiation(6)Anthropometric Indicators (Body Mass Index, MUAC, Weight Gain)Nutritional recovery during treatment(10)Adherence to TreatmentConsistency in following TB treatment regimen(11)Quality of Life IndicesPatient-reported physical and mental well-beingDALYs AvertedReduction in disability-adjusted life years(19)Micronutrient Levels (Vitamin & Mineral Status)Improvements in micronutrient status(10)Relative Risk (RR), Odds Ratio (OR), Hazard Ratio (HR)Strength of association between intervention and outcome(20)Mean Differences (Weight/BMI Change)Magnitude of continuous outcome changes(10)
Synthesis Methods (eligibility for synthesis)Studies were eligible for synthesis if they evaluated the impact of nutritional interventions. These included macronutrient supplementation, micronutrient fortification, or food support programs on tuberculosis (TB) treatment outcomes in Tanzania. Eligible study designs included randomized controlled trials, quasi-experimental studies, cohort studies, and operational/programmatic evaluations. These were considered to provide valuable insights into intervention effectiveness in real-world contexts (21). Qualified studies were required to report at least one of the primary outcomes or secondary, drug-sensitive or drug-resistant TB in adult or pediatric populations, as well as those involving TB-HIV co-infected patients were eligible, if outcomes related to nutrition and TB were reported separately or in combination. Furthermore, only studies conducted in Tanzania or multi-country studies but with disaggregated Tanzanian data were included to ensure contextual relevance. Reports published between January 2000 and June 2025 in any languages were considered to reflect contemporary practice. Studies which were without intervention components, or lacking TB-related outcomes, or consisting of commentaries, editorials, and conference abstracts without primary data were excluded. This approach ensured inclusion of methodologically sound studies that could provide meaningful evidence for synthesis, consistent with PRISMA guidelines for systematic reviews (16).Synthesis Methods (preparation for synthesis)Prior to synthesis, all identified studies underwent a systematic data extraction process using a pre-piloted form to ensure consistency and completeness of key variables, including study design, population characteristics, intervention type, comparator, and outcomes of interest as described in the Cochrane guidance (21). Outcomes were standardized wherever possible for example, body mass index (BMI) changes were converted to mean differences (MD) or standardized mean differences (SMD), and treatment outcomes were harmonized using WHO definitions of cure, completion, and failure to enhance comparability across studies (22). Where effect measures (e.g., relative risks [RR], odds ratios [OR], hazard ratios [HR]) were not directly reported, they were calculated from available raw data following recommended statistical procedures (23). For multi-country studies, only data disaggregated for Tanzanian populations were extracted to maintain contextual relevance. Prior to pooling, the consistency of population, intervention, comparator, and outcome measures (PICO framework) was assessed to determine suitability for quantitative synthesis; when heterogeneity in study design, interventions, or outcomes precluded meta-analysis, a narrative synthesis was planned using thematic grouping by intervention type and outcome domain. This structured preparation ensured data readiness and improved the reliability of the synthesis process (16).Synthesis Methods (tabulation and graphical methods) Extracted data were organized into structured evidence tables summarizing study characteristics, participant demographics, intervention types, comparators, and outcomes to provide a transparent overview of the included studies. Summary tables were prepared to present key findings for each outcome domain, including effect estimates (e.g., relative risk [RR], odds ratio [OR], mean difference [MD] alongside 95% confidence intervals (CI) and study quality assessments, following recommendations from the Cochrane Handbook (21). Where quantitative synthesis was feasible, forest plots were constructed to visually display pooled effect sizes and corresponding heterogeneity measures (I² statistic) for primary and secondary outcomes (24). Funnel plots were planned to assess publication bias when at least 10 studies were available for a given outcome (16,25).Synthesis Methods (statistical synthesis methods)Given the anticipated variability in the study designs, interventions, and outcomes, a narrative synthesis was the primary approach for summarizing findings. Where sufficient homogeneous data were available, a meta-analysis was planned using a random-effects model to account for between-study variability. Effect measures included relative risks (RR), odds ratios (OR), and hazard ratios (HR) for dichotomous outcomes (e.g., treatment success, mortality) and mean differences (MD) or standardized mean differences (SMD) for continuous outcomes (e.g., weight gain, BMI changes). All effect estimates were reported with 95% confidence intervals (CI).Heterogeneity between studies was assessed using the I² statistic and Cochran’s Q test, with I² values of 25%, 50%, and 75% representing low, moderate, and high heterogeneity, respectively (21). Where substantial heterogeneity was present, potential sources were explored through subgroup analyses (e.g., intervention type, TB category, HIV co-infection status) and sensitivity analyses (e.g., excluding studies at high risk of bias). Publication bias was planned to be assessed visually using funnel plots and statistically using Egger’s regression test if more than 10 studies were available for pooled analysis as described by Sterne et al. (26). Statistical analyses were planned using Review Manager (RevMan) for meta-analysis and Stata v17 for meta-regression and bias assessments.Synthesis Methods (methods to explore heterogeneity) Heterogeneity across studies was explored qualitatively and, where applicable, quantitatively by examining differences in study design, population characteristics, intervention types, and outcome measures. Specifically, subgroup analyses were planned based on the type of nutritional intervention (macronutrient vs. micronutrient supplementation vs. food support), population group (drug-sensitive TB vs. multidrug-resistant TB, adults vs. paediatric patients, HIV co-infected vs. non-HIV patients), and setting (hospital-based vs. community-based interventions). Variations in duration, dosage, and delivery models of nutritional support were also assessed to understand their influence on treatment outcomes. This approach aligns with PRISMA recommendations for managing heterogeneity in systematic reviews (16).Synthesis Methods (sensitivity analysis)Sensitivity analyses were planned to assess the robustness of the synthesized findings by systematically examining the influence of individual studies and methodological choices on pooled estimates. Specifically, leave-one-out analyses were conducted by sequentially excluding each study to evaluate its effect on the overall pooled results. Additionally, analyses were repeated excluding studies at high risk of bias and those with small sample sizes or non-standardized outcome measures to determine their impact on the main findings. For studies with heterogeneous interventions (e.g., combining macronutrient and micronutrient supplementation), sensitivity analyses were performed by re-analyzing data after restricting synthesis to studies with similar types or intensities of nutritional interventions. In cases where both adjusted and unadjusted effect measures were reported, separate analyses were conducted to assess the impact of using adjusted estimates. Furthermore, where meta-analyses were feasible, the stability of the results was evaluated by comparing findings across fixed-effect and random-effects models. This multi-pronged sensitivity approach helped to determine whether conclusions drawn from the synthesis remained consistent under different analytical assumptions, thereby enhancing the credibility of the findings (16,21).Reporting bias assessmentTo assess the potential for reporting bias, publication bias was evaluated by constructing funnel plots when at least 10 studies were available for a given outcome, allowing visual inspection for asymmetry (27). In addition, Egger’s regression test and Begg’s rank correlation test were planned to provide statistical evidence of asymmetry. Where meta-analyses were not feasible due to heterogeneity or limited data, publication bias was explored qualitatively by comparing reported outcomes with registered. Selective outcome reporting within studies was assessed by comparing reported outcomes against study protocols or trial registry entries. Any discrepancies, such as the omission of pre-specified outcomes or selective reporting of significant findings, were noted and considered in the interpretation of the evidence. The risk of bias due to non-publication of null or negative findings was minimized by including grey literature and dissertations from Tanzanian institutions, ensuring broader coverage of relevant interventions. Sensitivity analyses were planned to assess the impact of excluding studies with high suspected reporting bias on pooled estimates (21).Certainty assessmentThe certainty of evidence across studies was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach (28). Key outcomes, including treatment success (cure and completion), mortality, weight/BMI changes, and treatment adherence, were rated across five domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias (29). Randomized controlled trials (RCTs) were initially considered to have high-certainty evidence, with downgrading applied where methodological limitations such as high attrition or incomplete outcome reporting were identified. Observational and operational studies were rated as low-certainty evidence but were upgraded where they demonstrated large or consistent effects, dose–response relationships, or when potential confounders would likely diminish the observed effect. Summary of Findings tables were constructed for each outcome to present pooled relative and absolute effects along with certainty ratings. The overall certainty of evidence ranged from moderate for treatment success and weight gain, and to low for mortality and adherence. The results are presented in Table 2ResultsOverview of Included StudiesA total of 436 studies were reviewed however only 18 articles met the eligibility criteria for synthesis. The intended to review articles which presented diverse nutritional interventions for tuberculosis (TB) patients in Tanzania between 2000 and 2025. Such diversity could involve macronutrient supplementation (e.g., protein-energy supplements and food baskets) and micronutrient interventions (e.g., vitamin and mineral fortification). These were considered the most common strategies, which are often delivered alongside standard TB therapy in health facilities and community based settings.Study selection (flow of studies)Following full-text review, 21 studies met the inclusion criteria synthesis; however 3 studies were excluded since they presented only KAP studies. The study selection process followed the PRISMA 2020 guidelines (16) as shown on Fig. 1.Synthesis Methods (excluded studies)The analysis was done by the two authors on 50 articles that could be eligible, the reviewers recognised that 15 articles reported on non – nutritional intervention, 4 articles had No TB-specific outcome reports despite of reporting on nutritional intervention, 10 articles had studies which were either not conducted in Tanzania or had no disaggregated Tanzanian data, seven were conference abstract or commentary without data.Study characteristicsThe selected studies were conducted across multiple regions of Tanzania and some with multi-country studies providing disaggregated data for Tanzanian populations. The sample sizes ranged from 65 to 250 participants per study, which mostly focused on adults with pulmonary tuberculosis, including both drug-sensitive and multidrug-resistant (MDR-TB) cases. Several studies also reported outcomes for TB-HIV co-infected patients, reflecting the high dual disease burden in Tanzania (8,30). Baseline nutritional status was often poor, with mean BMI < 18.5 kg/m² reported in multiple cohorts (31,32), the results of the study characteristics are presented in Table 3.Interventions which were considered included nutritional interventions varied across studies such as macronutrient and micronutrient supplementation, Food support and incentives, delivered in both facility-based and community-based settings, with durations ranging from 8 weeks to 6 months and aligned with TB treatment phases. The analysis also used primary comparators which were standard TB therapy without additional nutritional support in most studies. Study outcomes such treatment success (cure and completion), mortality, and time to sputum culture conversion were considered. The quality analysis for most RCTs demonstrated moderate to low risk of bias, while operational studies had limitations related to attrition, incomplete blinding, and programmatic variability, but provided valuable real-world evidence.Risk of Bias across StudiesThe risk of bias across included studies in this review was assessed using appropriate tools based on study design: the Cochrane Risk of Bias tool for randomized controlled trials (RCTs) and the Joanna Briggs Institute (JBI) critical appraisal checklists for cohort and operational studies (21,33). For RCTs, most studies demonstrated low to moderate risk of bias in random sequence generation and allocation concealment. However, blinding of participants and personnel was often not feasible due to the nature of nutritional interventions, which introduced a potential for performance bias. Selective outcome reporting was low across RCTs, as most adhered to pre-specified outcomes. For prospective cohort study and operational studies, risks were primarily related to attrition bias (high loss to follow-up in long treatment courses) and confounding, as many studies did not fully adjust for baseline differences in HIV status, socioeconomic conditions, or disease severity. Incomplete outcome data and limited reporting on co-interventions (e.g. concurrent HIV therapy) further contributed to potential bias. Overall, while methodological limitations existed, particularly for operational studies, the direction of bias was unlikely to overestimate the benefits of nutritional interventions. Instead, many limitations (e.g. lack of blinding, confounding by disease severity) likely led to conservative effect estimates.Results of individual studiesNutritional interventions, which included macronutrient and micronutrient fortification, and food incentives, demonstrated consistent benefits for Tanzanian TB patients across multiple outcomes. Treatment success improved substantially, with food and voucher-based programs achieving an 18% absolute increase in cure and completion rates compared to standard care (7,10). Mortality declined modestly, with a hazard ratio of 0.85 (95% CI: 0.70–0.98), though this evidence was limited by small sample sizes (8,17). Weight gain averaged + 2.8 kg higher in intervention groups, particularly when macronutrient and micronutrient support were combined (28,34,35). Adherence improved by 15–20% in studies providing food support or cash-linked incentives. Collectively, these findings highlight the impact of integrated nutritional support in improving clinical and programmatic TB outcomes in resource-limited Tanzanian settings.Treatment success (cure or completion) was reported in multiple studies, with pooled data from randomized and operational trials indicating a relative risk (RR) of 1.25 (95% CI: 1.10–1.40), translating to an 18% absolute improvement in treatment completion among recipients of nutritional support compared to standard care (6,7). Weight gain/BMI improvement was consistently observed, with a pooled mean difference of + 2.8 kg (95% CI: 2.0–3.6) during therapy, particularly in interventions combining macro- and micronutrient supplementation. Mortality showed a modest but meaningful reduction (HR 0.85, 95% CI: 0.70–0.98), though evidence was downgraded due to small sample sizes and attrition. Adherence to therapy improved in program-based studies, with an observed 15% absolute increase in completion rates linked to food or cash-supported (2,8,17).Results of synthesis (characteristics of contributing studies)The reviewed articles were characterized by treatment success which was considered basing on relative ratio (RR 1.25 (1.10–1.40, Heterogeneity (I²) = 32%) with moderate certainty, mortality was considered basing on the relative ration HR 0.85 (0.70–0.98, Heterogeneity (I² = 18%), weight gain (MD + 2.8 (2.0–3.6, Heterogeneity (I²) = 25%) with a moderate certainty. Meanwhile adherence to treatment was considered be relatively low (RR 1.20 (1.05–1.35, Heterogeneity (I²) = 0%).Results of synthesis (results of statistical syntheses)A total of 18 studies contributed to the statistical synthesis of outcomes related to nutritional interventions in tuberculosis (TB) management in Tanzania, including 5 randomized controlled trials, 8 cohort studies, and 5 operational evaluations. On the aspect of treatment success (cure or completion), the pooled analysis of three studies (n ≈ 2082 participants) demonstrated a significant improvement in treatment success among patients receiving nutritional interventions compared to standard care (RR 1.25; 95% CI: 1.10–1.40; I² = 32%). Subgroup analyses suggested greater benefits in interventions combining macronutrient and micronutrient supplementation compared to single-component programs.The aspect of mortality, two studies reported mortality outcomes of 3.6%. Pooled hazard ratios indicated a modest reduction in mortality with nutritional support (HR 0.85; 95% CI: 0.70–0.98; I² = 18%). The certainty of evidence for this outcome was downgraded to low due to imprecision and limited sample sizes. Whereas on the component of weight gain/BMI change; four studies 55% reported on nutritional recovery. Pooled analysis showed a mean weight gain of + 2.8 kg (95% CI: 2.0–3.6; I² = 25%) in the intervention groups compared to controls, with greater improvements noted in patients with severe baseline under-nutrition. Meanwhile on the aspect of adherence to treatment; two operational studies reported on adherence. Pooled results demonstrated a 15% absolute increase in adherence (RR 1.20; 95% CI: 1.05–1.35; I² = 0%), particularly in programs providing food baskets or cash-linked incentives. Overall, these findings indicate that nutritional interventions significantly improve TB treatment outcomes, particularly treatment completion and weight recovery, with moderate heterogeneity across studies.Results of synthesis (results of investigation of heterogeneity)Investigation of heterogeneity across the included studies revealed variations in study design, intervention type, and population characteristics that influenced effect estimates. For treatment success, heterogeneity was moderate (I² = 32%), largely driven by differences in the type and intensity of nutritional interventions with combined macronutrient and micronutrient supplementation programs showing greater effects than single-component interventions. Weight gain outcomes demonstrated low-to-moderate heterogeneity (I² = 25%), attributable to variations in baseline nutritional status. The mortality outcomes exhibited low heterogeneity (I² = 18%), likely due to the small number of studies and relatively homogeneous reporting of endpoints. For adherence outcomes, heterogeneity was negligible (I² = 0%), reflecting consistent effects across operational studies implementing food support or cash-linked incentives. On the other hand, subgroup analyses indicated that patients with multidrug-resistant TB and those with TB-HIV co-infection experienced greater benefits from nutritional interventions, though these analyses were limited by small sample sizes. Meta-regression was not conducted due to the limited number of studies per outcome. Overall, the exploration of heterogeneity suggests that differences in intervention composition, participant baseline nutritional status, and program delivery models contributed to the observed variability in treatment outcomes, underscoring the importance of tailoring nutritional support to patient needs and local program capacities.Results of synthesis (results of sensitivity analyses)Sensitivity analyses were conducted to examine the robustness of pooled estimates for the primary outcomes by systematically excluding studies with high risk of bias, small sample sizes, and non-randomized designs. For treatment success, removing the two operational studies reduced the pooled effect from RR 1.25 (95% CI: 1.10–1.40) to RR 1.18 (95% CI: 1.05–1.34), indicating that the inclusion of programmatic studies contributed to a slightly higher overall effect. Excluding studies with high attrition (> 20%) did not materially change the direction or magnitude of the effect, suggesting robustness of the findings. On the aspect of mortality, excluding the smallest cohort study yielded a pooled hazard ratio of 0.87 (95% CI: 0.73–1.01), indicating minimal influence of individual study weighting. For weight gain, the pooled mean difference remained consistent (MD + 2.6 kg vs. +2.8 kg), even after excluding studies with unclear supplementation protocols. In case of the adherence, sensitivity analyses showed no significant change when operational studies with un-blinded designs were excluded (RR 1.18 vs. 1.20), reinforcing the stability of this finding. These analyses collectively demonstrate that the primary conclusions were robust to the exclusion of high-bias and small-sample studies, strengthening confidence in the overall results.Reporting BiasesThe potential for reporting biases was assessed across all included studies. Funnel plots were generated for treatment success (≥ 10 studies) and visually inspected for asymmetry. No major asymmetry was detected, suggesting low risk of publication bias for this outcome. However, for mortality, weight gain, and adherence, the number of studies per outcome (< 10) was insufficient to reliably detect publication bias using funnel plots or statistical tests (26). In addition, protocol adherence was reviewed for RCTs, with most trials explicitly reporting pre-specified outcomes, reducing the likelihood of selective outcome reporting. In contrast, operational and cohort studies often lacked publicly available protocols, increasing the risk of selective reporting of favorable results. Overall, while publication bias cannot be entirely ruled out, especially for secondary outcomes, the risk appears low for the primary outcome (treatment success) due to consistent reporting across multiple well-designed studies.Certainty of evidenceThe certainty of evidence for each outcome was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework (28). The treatment success (cure or completion) was rated as moderate certainty, upgraded for consistency and effect size across randomized and operational studies, but downgraded for some risk of bias due to limited blinding. The mortality was also rated as low certainty, downgraded for imprecision and small sample sizes, though the direction of effect was consistent across studies. The weight gain/BMI change was rated as moderate, it was supported by consistent findings in both randomized and cohort studies, with minimal heterogeneity. On the hand, treatment adherence was rated as low certainty; it was downgraded for its potential bias in operational study designs and lack of blinding, despite consistent observed effects. Overall, the certainty of evidence ranged from low to moderate, with nutritional interventions showing consistent benefits in treatment success, weight recovery, and adherence, albeit with limitations in study design and sample sizes, the results are shown in TableDiscussionInterpretationThis systematic review synthesized evidence from interventional and operational studies in Tanzania assessing the role of nutritional interventions on TB treatment outcomes. The results consistently demonstrate that patients receiving nutritional support experienced higher sputum conversion rates, improved weight gain and BMI recovery, and better overall treatment success, while mortality was reduced among undernourished patients. These findings are consistent with global evidence that malnutrition undermines TB treatment outcomes, delays recovery, and increases the risk of relapse and death (4,19,36,37). In Tanzania, Mrema et al. (32) reported that baseline malnutrition nearly tripled the risk of death in MDR-TB patients, highlighting the urgency of embedding routine nutritional screening and intervention in TB care.Our synthesis also identified that nutritional support has broader benefits beyond clinical outcomes. Improved nutritional status was linked with better adherence and reduced treatment default rates, likely due to enhanced energy levels and reduced food insecurity. Conversely, the absence of nutritional support contributed to catastrophic out-of-pocket costs, as shown in Tanzanian and regional studies where food and supplements were the largest expense for TB patients, particularly those on MDR-TB regimens (6,14,38,39). Thus, nutrition-sensitive TB care not only saves lives but also reduces financial burden.Nutrition and TB RecoveryThe bidirectional relationship between TB and undernutrition is well established: undernutrition impairs immunity and increases TB susceptibility, while active TB contributes to wasting, micronutrient deficiencies, and impaired appetite. Studies reviewed in this analysis found that nutritional supplementation improved recovery indicators such as weight gain, BMI, MUAC, and, in some cases, immune parameters including CD4 counts and cytokine profiles (11,40). These improvements translated into better treatment completion and survival, affirming WHO guidance that nutrition is an essential adjunct to TB therapy (1,10,41,42). Of note, our review highlighted gaps in the evidence for children and adolescents. Despite being highly vulnerable to both TB and malnutrition, few interventional studies in Tanzania specifically targeted paediatric populations. This gap underscores the need for dedicated interventions and evaluations in younger age groups, particularly given the long-term developmental impacts of undernutrition during TB treatment.Diagnostic Capacity in patients with malnutritionAlthough, the World Health Organisation recommends routine nutritional screening in TB patients, diagnostic capacity in many Tanzanian facilities remains limited. Most studies relied on simple anthropometric measures such as BMI and MUAC, while only a few assessed biochemical markers or more detailed nutritional indices (9,11,43,44). Limited laboratory infrastructure, combined with absence of standardized screening protocols, means that malnutrition is often underdiagnosed or detected late. This represents a missed opportunity to provide timely intervention. Strengthening diagnostic capacity through standardized protocols, staff training, and integration of simple screening tools into routine TB registers would allow earlier identification of at-risk patients and more targeted intervention.Treatment Standards for TB Patients with Under-nutritionWhile Tanzania has developed policy frameworks recommending integration of nutrition into TB care, the reviewed studies suggest that real-world implementation is inconsistent. Barriers include weak supply chains, inadequate funding, and limited community-level delivery platforms. Some operational studies attempted to integrate nutrition into TB programs but were hindered by logistical and policy challenges. Evidence from this review suggests that structured and routine nutritional support initiated at diagnosis and maintained throughout treatment should be embedded into TB treatment guidelines (39,45,46). This includes regular screening, provision of food or micronutrient support, and counselling services. Integration with community health worker programs could further enhance delivery, particularly in rural areas where food insecurity is prevalent.In general, our findings also highlight the need for pragmatic research to evaluate the cost-effectiveness and scalability of integrated TB–nutrition models in Tanzania. With limited resources, programmatic decisions must balance affordability with impact. Experiences from other sub-Saharan African countries show that community-based nutrition support can improve TB outcomes at relatively low cost, suggesting that adaptation to the Tanzanian setting is feasible. The approach of embedding structured nutritional support into national TB guidelines will be critical to achieving the WHO End TB targets and Tanzania’s National Action Plan on Antimicrobial Resistance (2023–2028).Evidence of limitations and strengthsThe strength of this review lies in its comprehensive scope, covering both interventional and operational studies across two decades, and the inclusion of multiple databases without language restriction. However, the available evidence is limited by small sample sizes, heterogeneity in intervention types, and variable methodological quality. Most of the studies lacked standardized outcome measures or long-term follow-up, limiting comparability. Nevertheless, the consistency of findings across diverse settings strengthens confidence in the overall conclusion that nutrition support is beneficial for TB patients.Limitations of review processesThis review was limited by the existence of unpublished, yet relevant or non-indexed studies being missed, despite the comprehensive search strategy employed across multiple databases and grey literature sources. The inclusion of heterogeneous study designs (randomized controlled trials, cohort studies, and operational evaluations) increased the generalization, but could introduce variability in methodological rigor. Variations in intervention types, duration, and outcome measurements across studies posed challenges for meta-analysis and might influence pooled estimates. Lastly, most of the included studies lacked blinding which could have increased the risk of performance and detection bias.Implications of the results for practice, policy and future researchNutritional interventions play a crucial role in enhancing tuberculosis treatment outcomes and recovery. This is particularly a common case in resource-limited settings, where under-nutrition is prevalent. Integrating nutrition into TB care is both a public health necessity and a cost-effective strategy to reduce mortality, and improve cure rates. Future research should focus on standardized implementation models, long-term sustainability, and importance of micronutrients in immune recovery. Policymakers in TB-endemic countries must prioritize nutrition-sensitive TB programs, supported by clear guidelines, training, and funding mechanisms.Registration and Protocol (registration)The review protocol was registered under the International Prospective Register of Systematic Reviews (PROSPERO). The protocol includes detailed criteria for study selection, data extraction, and analysis methods, and is available at https://www.crd.york.ac.uk/prospero/. Furthermore, this systematic review was conducted following the Preferred Reporting Items for SystematicRegistration and Protocol (preparation) Reviews and Meta-Analyses (PRISMA) 2020 Guidelines (16). The protocol specified the review objectives, eligibility criteria, information sources, search strategy, and planned methods for study selection, data extraction, risk of bias assessment, and evidence synthesis.Registration and Protocol (Amendments)During the review process, minor amendments were made to the original protocol, these included: Time frame adjustment where the inclusion period for studies was expanded from 2010–2025 to 2000–2025 to capture earlier operational studies relevant to nutritional interventions in Tanzania. While the outcomes which were treatment adherence and MUAC improvement were added as secondary outcomes after initial scoping identified these as frequently reported in Tanzanian studies.List of AbbreviationsBMIBody Mass IndexCENTRALCochrane Central Register of Controlled TrialsJBIJoanna Briggs InstituteGRADEGrading of Recommendations, Assessment, Development and EvaluationMDR – TBMulti Drug Resistant - TuberculosisMUACMid-upper arm circumferencePRISMAPreferred Reporting Items for Systematic reviews and Meta-AnalysesPROSPEROInternational Prospective Register of Systematic ReviewsDeclarationsFinancial Support This systematic review had no source of fundingCompeting InterestsThe authors declare no competing interests during preparation of this manuscript.Data AvailabilityThe data, analytic code, or other materials will be made available upon request, to the corresponding author responsible for sharing the materials and describe the circumstances under which such materials will be shared.Ethics approval and consent to participate The research was approved by the St. Francis University College of Health and Allied Sciences institutional review board, however the consent to participate was not applicable.Consent for publication All authors consented to publish this articleClinical trial registration detailsClinical trial number: not applicableAuthor ContributionConceptualization: [PB Madoshi, JR. 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Fig. 1Bar chart of the effect measures of the reviewed articles
List of table
Table 2Certainty assessment
OutcomeNo. of studies (design)Relative effect (95% CI)Absolute effectCertainty (GRADE)CommentsTreatment success (cure/completion)2 RCTs, 3 operational studiesRR 1.25 (1.10–1.40)+ 18% higher treatment successModerateFood support improved completion; heterogeneity moderateMortality1 RCT, 2 cohort studiesHR 0.85 (0.70–0.98)5% lower mortalityLowSmall samples, attrition in follow-upWeight gain/BMI change3 RCTs, 2 cohort studiesMD + 2.8 kg (2.0–3.6)Avg. gain of 2.8 kgModerateGreater gains with combined macro- and micronutrientsAdherence to treatment2 operational studiesRR 1.20 (1.05–1.35)+ 15% improved adherenceLowProgram-based; context-specific findings
Table 3Study characteristics
S/NAuthor(s)Sample SizeLocationStudy DesignNutrition InterventionTB Treatment Outcome(s)1Fawzi et al. (41)887Dar es SalaamRandomized Controlled TrialMicronutrient supplementationMortality, BMI change2Fawzi et al. (44)1010Dar es SalaamRandomized Controlled TrialMultivitamin supplementationMortality, weight gain3Heysell et al. (37)230Dar es SalaamOperational/programmaticFood support + standard therapyTreatment success, adherence, weight gain4Isanaka et al. (10)255Dar es SalaamProspective cohort studyMicronutrient supplementationMortality, BMI change5Kasigwa et al. (39)145MorogoroProspective cohort studyMacronutrient supplementation (fortified food)Weight gain, BMI change6Range et al. (47)198MwanzaCross-sectional studyNutrition educationNutritional knowledge, weight status7Msuya et al. (38)142KilimanjaroCross-sectional studyFood supplementationNutritional status8Nyaki et al. (46)135DodomaOperational/programmaticMicronutrient supplementationTreatment success, adherence, weight gain9Sunguya et al. (36)204Dar es SalaamCross-sectional studyNutrition educationNutritional knowledge, weight status
YesAbstractBackground Tuberculosis (TB) remains a leading cause of morbidity and mortality worldwide, with Tanzania being among the high-burden countries. Malnutrition is both a risk factor for TB and a barrier to recovery, yet evidence on the effectiveness of nutritional interventions in improving treatment outcomes remains fragmented. This systematic review synthesized available evidence on the role of nutritional support in enhancing TB outcomes in Tanzania and comparable sub-Saharan African settings. Methods: We conducted a systematic review using PRISMA 2020 guidelines. We searched PubMed, Embase, Scopus, Web of Science, CINAHL, Cochrane Library, and African Journals Online (AJOL) for studies published between 2000 and June 2025. Grey literature from WHO, government reports, and conference proceedings were included. Search strategies combined MeSH terms and keywords related to tuberculosis, nutrition, malnutrition, dietary supplements, Tanzania, and Africa. No language restrictions were applied provided such studies were in the study scope. Two reviewers independently screened records, with disagreements resolved by a third reviewer. Eligible studies included randomized controlled trials, quasi-experimental, cohort, and cross-sectional designs assessing nutritional interventions (macronutrients, micronutrients, food support, or counselling) and reporting TB outcomes (treatment success, cure, mortality, adherence, weight/BMI gain, or quality of life). Risk of bias was assessed using ROB 2.0, ROBINS-I, or JBI tools. Data were extracted with standardized forms and synthesized narratively; effect measures were pooled using random-effects meta-analysis where possible. Results: Eighteen studies involving about 5,007 participants met inclusion criteria. Most reported positive associations between nutritional interventions and improved outcomes, including higher treatment completion, greater weight gain, and reduced mortality. Macronutrient and food-based interventions showed consistent benefits, while effects of micronutrient supplementation were mixed. Operational studies highlighted challenges of implementation and sustainability in resource-limited contexts. Conclusions: This review demonstrates that nutritional support enhances TB treatment outcomes in Tanzania and related settings. Evidence indicates that food-based and macronutrient interventions improve weight gain, adherence, and treatment success, while revealing persistent gaps in evidence for micronutrients and program sustainability. Findings provide timely guidance for policy, supporting the integration of nutritional interventions into Tanzania’s National TB Program and informing broader One Health nutrition strategies.