Tuberculosis Treatment Outcomes in Tanzania: A Systematic Review on nutritional approach to enhance TB Outcomes

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Tibenderana, Godfrey Katusi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9184342/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Tuberculosis (TB) remains a major cause of illness and death worldwide, and Tanzania continues to be among the high-burden countries. Malnutrition plays a dual role in TB: it increases the risk of developing the disease and also undermines recovery during treatment. Although nutritional support is widely recommended as part of TB care, evidence on how effective different nutritional interventions are in improving treatment outcomes is scattered and inconsistent. This systematic review aimed to synthesize existing evidence on the impact of nutritional support on TB outcomes in Tanzania and comparable sub-Saharan African settings. Methods This systematic review followed PRISMA 2020 guidelines. We searched PubMed, Embase, Scopus, Web of Science, CINAHL, the Cochrane Library, and African Journals Online (AJOL) for studies published between 2000 and June 2025, alongside relevant grey literature from international agencies and government sources. Search terms included subject headings and keywords related to tuberculosis, nutrition, malnutrition, dietary interventions, Tanzania, and sub-Saharan Africa. Two reviewers independently screened titles, abstracts, and full texts, with disagreements resolved by a third reviewer. Eligible studies included randomized controlled trials and observational designs assessing nutritional interventions and reporting TB outcomes. Risk of bias was assessed using standard tools, and findings were synthesized narratively, with meta-analysis conducted where appropriate. Results Eighteen studies involving approximately 5,007 participants met the inclusion criteria. Most studies reported positive effects of nutritional interventions, including higher treatment completion rates, greater weight gain, and lower mortality. Food-based and macronutrient interventions showed the most consistent benefits. In contrast, results for micronutrient supplementation were mixed and less conclusive. Several operational studies also highlighted practical challenges related to implementation, cost, and long-term sustainability in resource-limited settings. Conclusion Overall, this review shows that nutritional support can meaningfully improve TB treatment outcomes in Tanzania and similar contexts. The evidence supports the integration of food-based and macronutrient interventions into routine TB care, while also pointing to important gaps in knowledge around micronutrients and sustainable program delivery. These findings offer timely guidance for strengthening Tanzania’s National TB Program and promoting more holistic, patient-centred approaches to TB management. Tuberculosis Nutrition Ifakara Supplements Multidrug resistance Tanzania Figures Figure 1 Introduction Rationale Tuberculosis (TB) remains a major global public health problem, with an estimated 10.8 million people developing the disease in 2023, and about 10.7 million new cases and 1.23 million deaths reported in 2024, according to the World Health Organization reports ( 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 in 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. Objectives This systematic review aims to: To assess the impact of nutritional interventions, including macronutrient supplementation, micronutrient supplementation, and food-based support, on tuberculosis treatment outcomes (treatment success, cure, completion, and mortality) among patients receiving TB care in Tanzania. To evaluate the effects of these nutritional interventions on recovery indicators, such as weight gain, body mass index, immune function, and quality of life, among adults and children with drug-sensitive and drug-resistant tuberculosis, including those co-infected with HIV. To synthesize evidence from randomized trials, cohort studies, and operational programs to identify practical, scalable nutrition-based strategies that can inform TB policy and implementation in resource-limited settings. Methods Eligibility Criteria Studies were included if they involved patients of any age with active pulmonary or extra-pulmonary tuberculosis living in Tanzania and evaluated the effect of nutritional interventions on treatment outcomes. Eligible interventions included macronutrient supplementation, micronutrient supplementation, food rations, or therapeutic feeding, and studies were required to include a comparison group receiving standard tuberculosis treatment without nutritional support or an alternative nutritional intervention. Included studies reported at least one treatment outcome, such as cure, treatment completion, failure, relapse, or mortality, and/or recovery indicators including weight gain, body mass index, immune response, or quality of life. Only randomized controlled trials, quasi-experimental studies, and operational or implementation research published in peer-reviewed journals were considered. Studies were excluded if they were purely observational without an intervention, conducted in high-income countries, or published as case reports, reviews, editorials, or commentaries. Information Sources The 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. The search included studies which were done between 2000 to June 2025. Search strategy A 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 process Two 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 ). Data Collection Process Data extraction was performed independently by two authors (PBM and JRT) using a standardized, pilot-tested extraction form. Extracted data were cross-checked for accuracy by other two authors (GT and TAK). Any discrepancies were resolved by consensus or third-party adjudication (RSM). Data Items (outcomes) We searched studies which reported on 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 n utritional 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 a d herence to TB therapy and to the nutrition intervention (pill/sachet counts, electronic or self-report). Furthermore, t he authors searched articles which included demographics data (age, sex, pregnancy, HIV/ART, comorbidities such as diabetes, blood pressure and others), 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 assessment Risk 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 ( 25 , 30 ). Whereas the non-randomized and quasi-experimental studies were assessed with ROBINS-I while the observational designs were assessed using JBI critical-appraisal checklists ( 33 , 34 ). 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 . Table 2 Results of the Study characteristics Author (Year) Country/Setting Study Design Sample Size Population Nutritional Intervention Comparator Main Outcomes Fawzi et al. (2003) Tanzania RCT 471 Adults with pulmonary TB Multivitamin supplementation Standard TB care Mortality, immune markers Villamor et al. (2008) Tanzania RCT 530 Adults with pulmonary TB Micronutrient supplementation Standard TB care Treatment outcome, mortality Range et al. (2005) Tanzania RCT 499 Adults with pulmonary TB Micronutrients Placebo Treatment success, weight Mehta et al. (2011) Tanzania RCT 255 Children with TB Multivitamins Placebo Clinical recovery Msuya et al. (2013) Tanzania Cohort 147 Adults with TB Routine nutrition support No intervention Weight gain Nagu et al. (2014) Tanzania Cohort 512 Adults with pulmonary TB Baseline nutrition status None Sputum conversion PrayGod et al. (2011) Tanzania Cross-sectional 471 Adults with TB Body composition None Nutritional recovery Zachariah et al. (2002) Malawi Cohort 425 Adults with TB Nutritional status None Early mortality Martins et al. (2009) Timor-Leste RCT 270 Adults with TB Food incentives Standard care Treatment completion Bhargava et al. (2013) India Cohort 1,652 Adults with TB Nutritional status None Mortality Bhargava et al. (2023) India Program cohort 10,345 Adults with TB Food baskets Standard care Treatment success Kilale et al. (2022) Tanzania Household survey 777 TB households Economic impact None Costs, food security Kasigwa et al. (2016) Tanzania Cross-sectional 145 MDR-TB patients Nutritional status None Recovery predictors Nyaki et al. (2016) Tanzania Cohort 98 MDR-TB patients Nutrition predictors None Treatment outcomes Mleoh et al. (2023) Tanzania Cohort 312 MDR-TB patients Regimen + nutrition Standard care Treatment success Effect Measures The 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 . Table 1 Effect measures of the reviewed articles Effect Measure Outcome Assessed Example Studies Treatment Success Rate (Cure & Completion) Proportion of patients achieving cure or completing treatment ( 17 , 18 ) Mortality Rate Deaths during TB treatment ( 8 ) Time to Sputum Culture Conversion Duration for culture negativity post-treatment initiation ( 6 ) Anthropometric Indicators (Body Mass Index, MUAC, Weight Gain) Nutritional recovery during treatment ( 10 ) Adherence to Treatment Consistency in following TB treatment regimen ( 11 ) Quality of Life Indices Patient-reported physical and mental well-being 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 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 will be organized into structured evidence tables summarizing study characteristics, participant demographics, intervention types, comparators, and outcomes to provide a clear overview of the included studies. Summary tables will be prepared to present key findings for each outcome domain, including reported effect estimates such as relative risks, odds ratios, and mean differences with 95% confidence intervals, alongside study quality assessments. Data synthesis will follow guidance from the Cochrane Handbook, and findings will be integrated using a narrative approach that could emphasize consistency, direction, and magnitude of effects across studies (16. 21, 24, 25). Synthesis Methods (statistical synthesis methods) Due to differences in study design, interventions, and outcomes, a narrative synthesis was mainly used to summarize the findings. Where similar data were available, a meta-analysis using a random-effects model was planned. Effect measures included relative risks, odds ratios, and hazard ratios for binary outcomes, and mean or standardized mean differences for continuous outcomes, all reported with 95% confidence intervals. Heterogeneity was assessed using the I² statistic, with values of 25%, 50%, and 75% indicating low, moderate, and high variation, respectively ( 21 ). Subgroup and sensitivity analyses were planned to explore sources of heterogeneity. Publication bias was planned to be assessed using funnel plots and Egger’s test where sufficient studies were available ( 26 , 30 ). Statistical analyses were planned using Review Manager and Stata. 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 test how stable the findings were under different assumptions. Individual studies were removed one at a time to assess their influence on the overall results. Additional analyses excluded studies with high risk of bias, small sample sizes, or non-standard outcome measures. Where interventions varied, analyses were repeated using only studies with similar nutritional approaches. When both adjusted and unadjusted estimates were available, separate analyses were conducted. Where applicable, results from fixed-effect and random-effects models were compared. These steps helped ensure that conclusions were robust and not driven by individual studies ( 16 , 21 ). Reporting bias assessment Reporting bias was assessed using funnel plots when at least ten studies were available, with visual inspection for asymmetry. Statistical tests were planned where appropriate. When meta-analysis was not possible, reporting bias was explored by comparing reported outcomes with study protocols or trial records. Selective reporting was noted when key outcomes were missing. Grey literature was included to reduce the risk of missing unpublished or negative studies, and sensitivity analyses were used to assess the impact of potential reporting bias ( 21 , 27 ). Certainty assessment The 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 ( 25 , 29 , 30 ). 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 2 Results Overview of Included Studies A 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 characteristics The studies were conducted across different regions of Tanzania, with some multi-country studies reporting Tanzanian data separately. Sample sizes ranged from 65 to 250 participants, mostly adults with pulmonary tuberculosis, including drug-sensitive and drug-resistant cases. Many participants were co-infected with HIV and had poor baseline nutritional status. Interventions included nutrient supplementation and food support delivered alongside standard treatment. Outcomes focused on treatment success, mortality, and sputum conversion. Overall, study quality was moderate, with some limitations in operational studies. The results of the study characteristics are presented in Table 2 . Risk of Bias across Studies Risk of bias was assessed using standard tools for different study designs. Most randomized trials had low to moderate risk of bias, although blinding was often not possible. Cohort and operational studies showed higher risk due to loss to follow-up and limited adjustment for factors such as HIV status and disease severity. Some studies also had incomplete outcome data. Overall, these limitations were unlikely to exaggerate the benefits of nutritional interventions and may have led to conservative estimates. The results are shown on Table 3 . Table 3 Result of risk of bias across studies Outcome Number of Studies Funnel Plot Possible Risk of Reporting Bias Rationale Treatment success ≥ 10 Yes Low No major asymmetry; consistent reporting Mortality < 5 No Moderate Few studies; no protocols for cohorts Weight gain < 5 No Moderate Limited studies; variable reporting Adherence < 5 No Moderate Mostly operational studies Overall — — Low–Moderate Strongest evidence for primary outcome Results of individual studies Nutritional interventions were associated with improved tuberculosis outcomes in Tanzania. Treatment success was higher among patients receiving nutritional support, with a pooled relative risk of 1.25 (95% CI: 1.10–1.40), corresponding to an 18% absolute increase in cure and completion. Weight gain was consistently greater in intervention groups, with a pooled mean difference of + 2.8 kg (95% CI: 2.0–3.6). Mortality was modestly reduced (HR 0.85, 95% CI: 0.70–0.98), although evidence was limited by small sample sizes. Treatment adherence improved by approximately 15%, when nutritional support was made available. Results of synthesis (results of investigation of heterogeneity) Differences between studies were mainly related to study design, types of nutritional interventions, and patient characteristics. Moderate variation was observed for treatment success (I² = 32%), with stronger effects seen in programs combining macronutrient and micronutrient support. Weight gain showed low to moderate variation (I² = 25%), largely due to differences in baseline nutritional status. Mortality outcomes had low variation (I² = 18%), while adherence showed no meaningful variation (I² = 0%). Subgroup analyses suggested greater benefits among patients with drug-resistant tuberculosis and TB–HIV co-infection, although these findings were limited by small sample sizes. Results of synthesis (Statistical and sensitivity analyses) A total of 18 studies were included in the statistical analysis, comprising five randomized controlled trials, eight cohort studies, and five operational evaluations. Nutritional interventions were associated with improved tuberculosis treatment outcomes. For treatment success, pooled results from three studies involving approximately 2,082 participants showed significantly higher cure and completion rates among patients receiving nutritional support compared with standard care (RR 1.25; 95% CI: 1.10–1.40; I² = 32%). Greater benefits were observed in interventions combining both macronutrient and micronutrient supplementation. Mortality was reported in two studies, with a modest reduction observed in patients receiving nutritional support (HR 0.85; 95% CI: 0.70–0.98; I² = 18%), although the certainty of this evidence was low due to small sample sizes. Four studies reported nutritional recovery, showing a pooled mean weight gain of + 2.8 kg (95% CI: 2.0–3.6; I² = 25%), particularly among severely undernourished patients. Two operational studies reported treatment adherence, with a 15% absolute improvement associated with food or cash-based support (RR 1.20; 95% CI: 1.05–1.35; I² = 0%). Sensitivity analyses showed that excluding high-risk or small studies did not substantially change the results, indicating that the findings were robust. Reporting Biases Reporting bias was assessed across all studies. Funnel plots for treatment success did not show clear asymmetry, suggesting low risk of publication bias for this main outcome. For mortality, weight gain, and adherence, there were too few studies to assess publication bias reliably. Most randomized trials reported planned outcomes clearly, while several operational studies lacked protocols, increasing the possibility of selective reporting. Overall, the risk of reporting bias was considered low for treatment success and moderate for other outcomes. Certainty of evidence The certainty of evidence was assessed using the GRADE approach. Treatment success and weight gain were rated as moderate certainty due to consistent findings across studies, despite some risk of bias from limited blinding. Mortality and treatment adherence were rated as low certainty because of small sample sizes and potential bias in operational studies. Overall, evidence ranged from low to moderate, with nutritional interventions showing consistent benefits despite methodological limitations. Discussion Interpretation This systematic review examined evidence from interventional and operational studies on the impact of nutritional interventions on tuberculosis (TB) treatment outcomes in Tanzania. Overall, the findings show that patients who received nutritional support had better treatment outcomes, including higher cure and completion rates, greater weight and BMI recovery, improved adherence, and modest reductions in mortality. These results support existing global evidence that malnutrition worsens TB outcomes by delaying recovery and increasing the risk of treatment failure and death ( 3 , 4 , 17 , 19 , 36 , 37 ). In Tanzania, Mrema et al. ( 32 ) reported that baseline malnutrition nearly tripled the risk of death among patients with multidrug-resistant TB, highlighting the importance of integrating nutrition into routine TB care. The strongest effects were seen for treatment success and nutritional recovery. Food-based and supplement interventions led to an estimated 18% improvement in cure and completion rates, especially in programs providing food incentives or combined nutritional packages ( 6 , 7 , 20 ). Patients receiving nutritional support also gained more weight, with an average increase of about 2.8 kg during treatment ( 12 , 38 , 45 ), reflecting improved physical recovery and treatment tolerance. Mortality was modestly lower among patients receiving nutritional support, particularly among undernourished and high-risk groups ( 8 , 10 , 14 , 17 , 32 ). Secondary outcomes showed that better nutrition was linked to improved adherence and reduced financial burden, as food costs represent a major expense for TB patients in Tanzania ( 15 , 38 , 39 ). Overall, these findings confirm that nutrition is a key component of effective TB treatment. Nutrition and TB Recovery The link between tuberculosis (TB) and undernutrition works in both directions: poor nutrition weakens immunity and increases TB risk, while active TB causes weight loss and nutrient deficiencies ( 3 , 4 , 11 , 35 ). Studies in this review showed that nutritional support improved recovery indicators such as weight, BMI, and, in some cases, immune markers ( 11 , 35 , 40 , 41 , 42 ). These improvements were associated with better treatment completion and survival, supporting WHO recommendations that nutrition is an important part of TB care ( 1 , 5 , 40 ). Interventions combining food and micronutrients were more effective than single supplements ( 12 , 13 , 41 , 45 , 47 ). However, evidence for children and adolescents remains limited, highlighting an important research gap ( 42 ). Diagnostic Capacity of TB Patients with Malnutrition Although nutritional interventions demonstrated clear benefits, their effectiveness depends strongly on the ability of health systems to correctly identify undernourished patients. Most studies relied on simple anthropometric indicators such as body mass index (BMI), mid-upper arm circumference (MUAC), and weight change to assess nutritional status ( 9 , 11 , 38 ). Only a small number of studies included biochemical markers or more detailed nutritional assessments ( 41 , 43 , 44 , 47 ). In routine clinical practice in Tanzania, nutritional screening is not consistently implemented, and standardized protocols are often lacking. As a result, malnutrition may be underdiagnosed or detected late, particularly in peripheral facilities with limited staff and laboratory capacity. This limits the timely initiation of nutritional interventions and may reduce their overall impact. Strengthening diagnostic capacity through standardized screening tools, routine documentation in TB registers, and basic staff training could improve early identification of at-risk patients and enhance the effectiveness of nutrition-sensitive TB care. Treatment Standards for TB Patients with Under-nutrition Although Tanzania has policy frameworks promoting nutrition-sensitive TB care, the reviewed studies indicate that real-world implementation remains inconsistent. Barriers include weak supply chains, limited funding, lack of standardized delivery platforms, and dependence on donor-supported programs. Operational studies showed that structured nutritional support initiated at diagnosis and maintained throughout treatment resulted in better clinical and programmatic outcomes ( 31 , 39 , 45 , 46 ), yet such interventions are not uniformly available across districts. Evidence from this review suggests that nutritional support should be formally embedded into national TB treatment guidelines, including routine nutritional screening, targeted food or supplement provision, and counselling services delivered through existing TB and community health systems ( 40 , 45 , 46 ). Integration with community health worker programs may further enhance reach, particularly in rural and food-insecure settings. Overall, this review demonstrates that nutritional interventions directly improve treatment success, recovery, adherence, and survival, which were the core outcomes defined in the study objectives. The evidence indicates that nutrition is not merely supportive care, but a central component of effective TB treatment in Tanzania and similar high-burden, resource-limited settings. Strengthening both nutritional support and the systems used to detect malnutrition is therefore essential for improving TB outcomes, reducing household economic vulnerability, and achieving national and global TB control targets. 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 strengths The 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 processes This 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 research The findings show that nutrition plays an important role in improving tuberculosis treatment outcomes, but practical and affordable approaches are needed in settings facing declining health funding. Large-scale supplementation programs may not be sustainable, making low-cost, community-based strategies more realistic. Linking TB patients to existing social protection schemes, community food programs, and agricultural support can help improve household food security without placing additional strain on health budgets. At the facility level, routine nutritional screening, basic counselling, and referral to local food support initiatives can be integrated into standard care with minimal resources. Strengthening collaboration between health, agriculture, and social welfare sectors may improve access to food while avoiding parallel systems. Future research should focus on scalable and context-specific models that combine clinical care with sustainable food security interventions. 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 Systematic Registration 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. Abbreviations BMI Body Mass Index CENTRAL Cochrane Central Register of Controlled Trials JBI Joanna Briggs Institute GRADE Grading of Recommendations, Assessment, Development and Evaluation MDR – TB Multi Drug Resistant - Tuberculosis MUAC Mid-upper arm circumference PRISMA Preferred Reporting Items for Systematic reviews and Meta-Analyses PROSPERO International Prospective Register of Systematic Reviews Declarations Financial Support This systematic review had no source of funding Competing Interests The authors declare no competing interests during preparation of this manuscript. 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 article Clinical trial registration details Clinical trial number: not applicable Author Contribution Conceptualization: [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] Data Availability The 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. References MAF-TB progress and way forward: https://www.who.int/teams/global-programme-on-tuberculosis-and-lung-health/tb-reports/global-tuberculosis-report-2024/ Bhargava A, Bhargava M, Meher A, et al. Nutritional support for adult patients with microbiologically confirmed pulmonary tuberculosis: outcomes in a programmatic cohort nested within the RATIONS trial in Jharkhand, India. Lancet Glob Heal. 2023;11(9):e1402–11. Cegielski, J.R and McMurray D. The relationship between malnutrition and tuberculosis: evidence from studies in humans and experimental animals. Int J Tuberc Lung Dis. 2004;8(3):286–98. Van Lettow M, Fawzi WW, Semba RD. Triple trouble: The role of malnutrition in tuberculosis and human immunodeficiency virus co-infection. Nutr Rev. 2003;61(3):81–90. WHO. Global Tuberculosis Report. 204AD: https://www.who.int/teams/global-tuberculosis-programme/tb-reports Martins N, Morris P, Kelly PM. Food incentives to improve completion of tuberculosis treatment: Randomised controlled trial in Dili, Timor-Leste. BMJ. 2009;339(7730):1131. Available from: https://pubmed.ncbi.nlm.nih.gov/19858174/ Martins N. et al. Food incentives to improve completion of tuberculosis treatment: randomised controlled trial in Dili, Timor-Leste. BMJ. 2016;353:i3039: http://www.ncbi.nlm.nih.gov/pubmed/27234398 Isanaka S, Mugusi F, Urassa W, et al. Iron Deficiency and Anemia Predict Mortality in Patients with Tuberculosis 1–3. J Nutr. 2012;142:350–7. Kawai K, Villamor E, Mugusi FM, et al. Predictors of change in nutritional and hemoglobin status among adults treated for tuberculosis in Tanzania. Int J Tuberc Lung Dis. 2011;15(10):1380–9. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3404808/ Isanaka S, Mugusi F, Urassa W, et al. Iron deficiency and anemia predict mortality in patients with tuberculosis. J Nutr. 2012;142(2):350–7: https://pubmed.ncbi.nlm.nih.gov/22190024/ PrayGod G, Range N, Faurholt-Jepsen D, et al. Weight, body composition and handgrip strength among pulmonary tuberculosis patients: A matched cross-sectional study in Mwanza, Tanzania. Trans R Soc Trop Med Hyg. 2011;105(3):140–7. Range N, Andersen ÅB, Magnussen P, Mugomela A, Friis H. The effect of micronutrient supplementation on treatment outcome in patients with pulmonary tuberculosis: A randomized controlled trial in Mwanza, Tanzania. Trop Med Int Heal. 2005;10(9):826–32. Villamor E, Mugusi F, Urassa W, Bosch RJ, et al. A Trial of the Effect of Micronutrient Supplementation on Treatment Outcome, T Cell Counts, Morbidity, and Mortality in Adults with Pulmonary Tuberculosis. J Infect Dis. 2008;197(11):1499: https://pmc.ncbi.nlm.nih.gov/articles/PMC2564793/ Zachariah R, Spielmann MP, Harries AD, Salaniponi FML. Moderate to severe malnutrition in patients with tuberculosis is a risk factor associated with early death. Trans R Soc Trop Med Hyg. 2002;96(3):291–4. Kilale AM, Pantoja A, Jani B, Range N, Ngowi BJ, Makasi C, et al. Economic burden of tuberculosis in Tanzania: a national survey of costs faced by tuberculosis-affected households. BMC Public Health. 2022;22(1). Page MJ, McKenzie JE, Bossuyt PM, Boutron I, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372: Bhargava A, Chatterjee M, Jain Y, Chatterjee B, Kataria A. Nutritional Status of Adult Patients with Pulmonary Tuberculosis in Rural Central India and Its Association with Mortality. PLoS One. 2013;8(10):1–11. Bagcchi S. WHO’s Global Tuberculosis Report 2022. The Lancet Microbe. 2023;4(1):e20. Bhargava A, Bhargava M, Meher A, et al. Nutritional supplementation to prevent tuberculosis incidence in household contacts of patients with pulmonary tuberculosis in India (RATIONS): a field-based, open-label, cluster-randomised, controlled trial. Lancet. 2023;402(10402):627–40: https://pubmed.ncbi.nlm.nih.gov/37567200/ Martins N, Morris P, Kelly PM. Food incentives to improve completion of tuberculosis treatment: randomised controlled trial in Dili, Timor-Leste. BMJ. 2009;339(7730):1131: https://www.bmj.com/content/339/bmj.b4248 Higgins JPT, Thomas J, Chandler J, et al. Cochrane handbook for systematic reviews of interventions. Cochrane Handb Syst Rev Interv. 2019;1–694: /doi/pdf/10.1002/9781119536604.ch14 World Health Organisation. Global research agenda for antimicrobial resistance in human health. 2023: https://www.who.int/publications/m/item/global-research-agenda-for-antimicrobial-resistance-in-human-health?utm Deeks JJ, Altman DG. Effect Measures for Meta-Analysis of Trials with Binary Outcomes. Syst Rev Heal Care Meta-Analysis Context Second Ed. 2008;313–35. Deeks, J. J., Higgins, J. P., & Altman DG. Analysing data and undertaking meta-analyses.No Title. In: Cochrane Handbook for Systematic Reviews of Interventions. Second. Chichester: John Wiley & Sons.; 2021. p.. 241–284. Sterne JA, Hernán MA, Reeves BC, Savović J, et al. ROBINS-I: A tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016;355: https://www.riskofbias.info/welcome/home/original-2016-version-of-robins-i Sterne JAC, Sutton AJ, Ioannidis JPA, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ. 2011;343(7818).: https://www.bmj.com/content/343/bmj.d4002 Whiting PF, Rutjes AWS, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36: https://pubmed.ncbi.nlm.nih.gov/22007046/ Guyatt GH, Oxman AD, Vist GE, Kunz R, et al. GRADE: An emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336(7650):924–6: https://pubmed.ncbi.nlm.nih.gov/18436948/ Schünemann HJ, Higgins JPT, Vist GE, et al. Completing ‘Summary of findings’ tables and grading the certainty of the evidence. Cochrane Handb Syst Rev Interv. 2019;375–402: /doi/pdf/10.1002/9781119536604.ch14 Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ Br Med J. 1997;315(7109):629: https://pmc.ncbi.nlm.nih.gov/articles/PMC2127453/ Mleoh L, Mziray SR, Tsere D, Koppelaar I, et al. Shorter regimens improved treatment outcomes of multidrug-resistant tuberculosis patients in Tanzania in 2018 cohort. Trop Med Int Heal. 2023;28(5):357–66: Mrema G, Hussein A, Magoge W, et al. Predictors of mortality among multidrug-resistant tuberculosis patients after decentralization of services in Tanzania from 2017 to 2019: retrospective cohort study. Bull Natl Res Cent 2024 481. 2024;48(1):1–11: https://bnrc.springeropen.com/articles/ 10.1186/s42269-024-01235-w Moola S, Munn Z, Sears K, Sfetcu R, Currie M, Lisy K, et al. Conducting systematic reviews of association (etiology): The Joanna Briggs Institute’s approach. Int J Evid Based Health. 2015;13(3):163–9: https://pubmed.ncbi.nlm.nih.gov/26262566/ Kolaski K, Logan LR, Ioannidis JPA. Guidance to best tools and practices for systematic reviews. Jbi Evid Synth. 2023: 21(9):1699: https://pmc.ncbi.nlm.nih.gov/articles/PMC10464882/ Grobler L, Nagpal S, Td S, Sinclair D. Nutritional supplements for people being treated for active tuberculosis (Review). 2016; Sunguya BF, Poudel KC, Mlunde LB, et al. Poor nutrition status and associated feeding practices among HIV-positive children in a food secure region in Tanzania: a call for tailored nutrition training. PLoS One. 2014;9(5): https://pubmed.ncbi.nlm.nih.gov/24846016/ Mpagama SG, Heysell SK, Ndusilo ND, et al. Diagnosis and Interim Treatment Outcomes from the First Cohort of Multidrug-Resistant Tuberculosis Patients in Tanzania. PLoS One. 2013;8(5):e62034: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0062034 Msuya, S. E., Mbise, R. L., Van den Broek, M. J., & Uriyo JG. Nutritional status and weight gain in patients with pulmonary tuberculosis in Tanzania. East Afr Med J. 2013;90(2):62–5. Kasigwa, A., Aris, E., Fungula, B., Semvua, H., et al. Predictors of Nutritional Status in Patients Treated for Multidrug-Resistant Tuberculosis at a Referral Hospital in Tanzania. J Nutr Disord Ther. 2016;6(4):1000188. World Health Organisations. Guideline: nutritional care and support for patients with tuberculosis. 2013]. Available from: https://iris.who.int/handle/10665/94836 Fawzi WW et al. Effect of micronutrient supplementation on mortality during treatment of pulmonary tuberculosis: a randomized trial in Tanzania. Am J Clin Nutr. 2003;77(3):720–5. Mehta S, Mugusi FM, Bosch RJ, Aboud S, et al. A randomized trial of multivitamin supplementation in children with tuberculosis in Tanzania. Nutr J. 2011;10(1):120: http://www.nutritionj.com/content/10/1/120 Nagu TJ, Spiegelman D, Hertzmark E, Aboud S, et al. Anemia at the Initiation of Tuberculosis Therapy Is Associated with Delayed Sputum Conversion among Pulmonary Tuberculosis Patients in Dar-es-Salaam, Tanzania. PLoS One. 2014;9(3):e91229: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0091229 Fawzi, W. W., Msamanga, G. I., Spiegelman, D., Antelman, G., Urassa, E., Narrod, C. et al. Effect of micronutrient supplementation on mortality during treatment of pulmonary tuberculosis: a randomized trial in Tanzania. N Engl J Med. 2005;350(21):2163–77. Range N, Andersen ÅB, Magnussen P, Mugomela A, Friis H. The effect of micronutrient supplementation on treatment outcome in patients with pulmonary tuberculosis: a randomized controlled trial in Mwanza, Tanzania. Trop Med Int Heal. 2005;10(9):826–32: https://onlinelibrary.wiley.com/doi/ 10.1111/j.1365-3156.2005.01463.x Nyaki FS, Taksdal M, Mbuya AW, Sariko M, Lekule IA, Kisonga RM, et al. Predictors of Nutritional Status in Patients Treated for Multidrug-Resistant Tuberculosis at a Referral Hospital in Tanzania Journal of Clinical Infectious Diseases Predictors of Nutritional Status in Patients Treated for Multidrug-Resistant Tuberculosis. J Clin Infect Dis Pract. 2016;1(2):1–5. Range N, Andersen ÅB, Magnussen P, Mugomela A, Friis H. The effect of micronutrient supplementation on treatment outcome in patients with pulmonary tuberculosis: a randomized controlled trial in Mwanza, Tanzania. Trop Med Int Heal. 2005;10(9):826–32: /doi/pdf/10.1111/j.1365-3156.2005.01463.x Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9184342","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":613332107,"identity":"3632f396-a894-4b29-b47f-711f18efc04c","order_by":0,"name":"Philbert Balichene Madoshi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACAyCWYGA4wMMP4iUUkKJFsgGkxYAELQwGB2BcQsBc7PDDGx/+3JExPr868cMDAwZ5frED+LVYzk4ztpzZ9ozH7MbbzRJAhxnOnJ1AwGG3E8ykeRsOA7Wc3QDSkgAUIaQl/Zs0z5/DPMYzzm7+QaSWHDNpHrbDPAb8vduIs8Vydk4x0C+HeSRu8G6zSDCQIOwXc+n0jcAQO2zP3392880fFTby/NIEtCCABFilBLHKQYD/ACmqR8EoGAWjYCQBAOSSRqPQY9ScAAAAAElFTkSuQmCC","orcid":"","institution":"St. Francis University College of Health and Allied Sciences","correspondingAuthor":true,"prefix":"","firstName":"Philbert","middleName":"Balichene","lastName":"Madoshi","suffix":""},{"id":613332108,"identity":"4ed4753d-2126-4b8a-892f-b30b661d390d","order_by":1,"name":"Jovin R. Tibenderana","email":"","orcid":"","institution":"St. Francis University College of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jovin","middleName":"R.","lastName":"Tibenderana","suffix":""},{"id":613332109,"identity":"923c6a20-3877-48ee-8055-dfa8a6cf04b4","order_by":2,"name":"Godfrey Katusi","email":"","orcid":"","institution":"St. Francis University College of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Godfrey","middleName":"","lastName":"Katusi","suffix":""},{"id":613332110,"identity":"a70bda08-cb25-4282-9001-2c94dc0d0f71","order_by":3,"name":"Theresia A. Karuhanga","email":"","orcid":"","institution":"St. Francis University College of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Theresia","middleName":"A.","lastName":"Karuhanga","suffix":""},{"id":613332111,"identity":"9157ff24-e35a-4dd6-93b8-78dbd83965a9","order_by":4,"name":"Robert S Machang’u","email":"","orcid":"","institution":"St. Francis University College of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"S","lastName":"Machang’u","suffix":""}],"badges":[],"createdAt":"2026-03-21 08:24:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9184342/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9184342/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105877593,"identity":"fcfdc50a-599b-4d5d-878c-1097063f9082","added_by":"auto","created_at":"2026-04-01 06:05:28","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":349557,"visible":true,"origin":"","legend":"\u003cp\u003eBar chart of the effect measures of the reviewed articles\u003c/p\u003e","description":"","filename":"floatimage11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9184342/v1/e3060e04e01297f9b959badb.jpeg"},{"id":108557729,"identity":"686d55ab-5447-4d51-980f-b0214146f9bc","added_by":"auto","created_at":"2026-05-06 01:56:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":734667,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9184342/v1/c0dd2c42-7cea-4f7d-a5ab-215a34b54659.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Tuberculosis Treatment Outcomes in Tanzania: A Systematic Review on nutritional approach to enhance TB Outcomes","fulltext":[{"header":"Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eRationale\u003c/h2\u003e \u003cp\u003eTuberculosis (TB) remains a major global public health problem, with an estimated 10.8\u0026nbsp;million people developing the disease in 2023, and about 10.7\u0026nbsp;million new cases and 1.23\u0026nbsp;million deaths reported in 2024, according to the World Health Organization reports (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Under-nutrition not only increases susceptibility to TB infection and disease progression but also impairs treatment outcomes and delays recovery (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Malnutrition impairs cell-mediated immunity, a crucial defense mechanism against \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e infection, thereby increasing both the risk of TB disease and the likelihood of poor treatment response (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). TB leads to significant nutrient uptake and weight loss, further exacerbating the poor health of affected individuals (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). 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 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). 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 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies 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. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) studied patients at the National multidrug-resistant TB (MDR-TB) center, the authors reported 53% of the participants being malnourished (Body Mass Index (BMI)\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;). Similarly, Kawai et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) 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. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) 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. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) 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).\u003c/p\u003e \u003cp\u003eWhile 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 in 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 (\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eThis systematic review aims to:\u003c/p\u003e \u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e To assess the impact of nutritional interventions, including macronutrient supplementation, micronutrient supplementation, and food-based support, on tuberculosis treatment outcomes (treatment success, cure, completion, and mortality) among patients receiving TB care in Tanzania.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo evaluate the effects of these nutritional interventions on recovery indicators, such as weight gain, body mass index, immune function, and quality of life, among adults and children with drug-sensitive and drug-resistant tuberculosis, including those co-infected with HIV.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eTo synthesize evidence from randomized trials, cohort studies, and operational programs to identify practical, scalable nutrition-based strategies that can inform TB policy and implementation in resource-limited settings.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEligibility Criteria\u003c/h2\u003e \u003cp\u003eStudies were included if they involved patients of any age with active pulmonary or extra-pulmonary tuberculosis living in Tanzania and evaluated the effect of nutritional interventions on treatment outcomes. Eligible interventions included macronutrient supplementation, micronutrient supplementation, food rations, or therapeutic feeding, and studies were required to include a comparison group receiving standard tuberculosis treatment without nutritional support or an alternative nutritional intervention. Included studies reported at least one treatment outcome, such as cure, treatment completion, failure, relapse, or mortality, and/or recovery indicators including weight gain, body mass index, immune response, or quality of life. Only randomized controlled trials, quasi-experimental studies, and operational or implementation research published in peer-reviewed journals were considered. Studies were excluded if they were purely observational without an intervention, conducted in high-income countries, or published as case reports, reviews, editorials, or commentaries.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInformation Sources\u003c/h3\u003e\n\u003cp\u003eThe 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. The search included studies which were done between 2000 to June 2025.\u003c/p\u003e\n\u003ch3\u003eSearch strategy\u003c/h3\u003e\n\u003cp\u003eA 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.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData selection process\u003c/h2\u003e \u003cp\u003eTwo 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.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection Process\u003c/h3\u003e\n\u003cp\u003eData extraction was performed independently by two authors (PBM and JRT) using a standardized, pilot-tested extraction form. Extracted data were cross-checked for accuracy by other two authors (GT and TAK). Any discrepancies were resolved by consensus or third-party adjudication (RSM).\u003c/p\u003e\n\u003ch3\u003eData Items (outcomes)\u003c/h3\u003e\n\u003cp\u003eWe searched studies which reported on 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 \u003cb\u003en\u003c/b\u003eutritional status of the participants which included change in weight (kg), BMI (kg/m\u0026sup2;), MUAC (cm), child growth z-scores and anaemia. On the other the articles on quality of life were reviewed such as validated scales and a\u003cb\u003ed\u003c/b\u003eherence to TB therapy and to the nutrition intervention (pill/sachet counts, electronic or self-report). Furthermore, \u003cb\u003et\u003c/b\u003ehe authors searched articles which included demographics data (age, sex, pregnancy, HIV/ART, comorbidities such as diabetes, blood pressure and others), 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.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRisk of bias assessment\u003c/h2\u003e \u003cp\u003eRisk 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 (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Whereas the non-randomized and quasi-experimental studies were assessed with ROBINS-I while the observational designs were assessed using JBI critical-appraisal checklists (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). 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\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the Study characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor (Year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountry/Setting\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy Design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNutritional Intervention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eComparator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMain Outcomes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFawzi et al. (2003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with pulmonary TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultivitamin supplementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStandard TB care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMortality, immune markers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVillamor et al. (2008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with pulmonary TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMicronutrient supplementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStandard TB care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTreatment outcome, mortality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange et al. (2005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with pulmonary TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMicronutrients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePlacebo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTreatment success, weight\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMehta et al. (2011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eChildren with TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultivitamins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePlacebo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eClinical recovery\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMsuya et al. (2013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRoutine nutrition support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eWeight gain\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNagu et al. (2014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with pulmonary TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBaseline nutrition status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSputum conversion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrayGod et al. (2011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBody composition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNutritional recovery\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZachariah et al. (2002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalawi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNutritional status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEarly mortality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMartins et al. (2009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTimor-Leste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFood incentives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStandard care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTreatment completion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBhargava et al. (2013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNutritional status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBhargava et al. (2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProgram cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10,345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdults with TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFood baskets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStandard care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTreatment success\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKilale et al. (2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHousehold survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB households\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEconomic impact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCosts, food security\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKasigwa et al. (2016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMDR-TB patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNutritional status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRecovery predictors\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNyaki et al. (2016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMDR-TB patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNutrition predictors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTreatment outcomes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMleoh et al. (2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTanzania\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMDR-TB patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRegimen\u0026thinsp;+\u0026thinsp;nutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStandard care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTreatment success\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEffect Measures\u003c/h2\u003e \u003cp\u003eThe 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\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect measures of the reviewed articles\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffect Measure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutcome Assessed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExample Studies\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment Success Rate (Cure \u0026amp; Completion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion of patients achieving cure or completing treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeaths during TB treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to Sputum Culture Conversion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration for culture negativity post-treatment initiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnthropometric Indicators (Body Mass Index, MUAC, Weight Gain)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNutritional recovery during treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdherence to Treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsistency in following TB treatment regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuality of Life Indices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatient-reported physical and mental well-being\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicronutrient Levels (Vitamin \u0026amp; Mineral Status)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImprovements in micronutrient status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelative Risk (RR), Odds Ratio (OR), Hazard Ratio (HR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrength of association between intervention and outcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Differences (Weight/BMI Change)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMagnitude of continuous outcome changes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis Methods\u003c/h2\u003e \u003cp\u003ePrior 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 (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). 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 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). 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 (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). 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 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis Methods (tabulation and graphical methods)\u003c/h2\u003e \u003cp\u003eExtracted data will be organized into structured evidence tables summarizing study characteristics, participant demographics, intervention types, comparators, and outcomes to provide a clear overview of the included studies. Summary tables will be prepared to present key findings for each outcome domain, including reported effect estimates such as relative risks, odds ratios, and mean differences with 95% confidence intervals, alongside study quality assessments. Data synthesis will follow guidance from the Cochrane Handbook, and findings will be integrated using a narrative approach that could emphasize consistency, direction, and magnitude of effects across studies (16. 21, 24, 25).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis Methods (statistical synthesis methods)\u003c/h2\u003e \u003cp\u003eDue to differences in study design, interventions, and outcomes, a narrative synthesis was mainly used to summarize the findings. Where similar data were available, a meta-analysis using a random-effects model was planned. Effect measures included relative risks, odds ratios, and hazard ratios for binary outcomes, and mean or standardized mean differences for continuous outcomes, all reported with 95% confidence intervals. Heterogeneity was assessed using the I\u0026sup2; statistic, with values of 25%, 50%, and 75% indicating low, moderate, and high variation, respectively (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Subgroup and sensitivity analyses were planned to explore sources of heterogeneity. Publication bias was planned to be assessed using funnel plots and Egger\u0026rsquo;s test where sufficient studies were available (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Statistical analyses were planned using Review Manager and Stata.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis Methods (methods to explore heterogeneity)\u003c/h2\u003e \u003cp\u003e 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 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis Methods (sensitivity analysis)\u003c/h2\u003e \u003cp\u003eSensitivity analyses were planned to test how stable the findings were under different assumptions. Individual studies were removed one at a time to assess their influence on the overall results. Additional analyses excluded studies with high risk of bias, small sample sizes, or non-standard outcome measures. Where interventions varied, analyses were repeated using only studies with similar nutritional approaches. When both adjusted and unadjusted estimates were available, separate analyses were conducted. Where applicable, results from fixed-effect and random-effects models were compared. These steps helped ensure that conclusions were robust and not driven by individual studies (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eReporting bias assessment\u003c/h2\u003e \u003cp\u003eReporting bias was assessed using funnel plots when at least ten studies were available, with visual inspection for asymmetry. Statistical tests were planned where appropriate. When meta-analysis was not possible, reporting bias was explored by comparing reported outcomes with study protocols or trial records. Selective reporting was noted when key outcomes were missing. Grey literature was included to reduce the risk of missing unpublished or negative studies, and sensitivity analyses were used to assess the impact of potential reporting bias (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eCertainty assessment\u003c/h2\u003e \u003cp\u003eThe certainty of evidence across studies was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). 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 (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). 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\u0026ndash;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\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eOverview of Included Studies\u003c/h2\u003e \u003cp\u003eA 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eStudy characteristics\u003c/h2\u003e \u003cp\u003eThe studies were conducted across different regions of Tanzania, with some multi-country studies reporting Tanzanian data separately. Sample sizes ranged from 65 to 250 participants, mostly adults with pulmonary tuberculosis, including drug-sensitive and drug-resistant cases. Many participants were co-infected with HIV and had poor baseline nutritional status. Interventions included nutrient supplementation and food support delivered alongside standard treatment. Outcomes focused on treatment success, mortality, and sputum conversion. Overall, study quality was moderate, with some limitations in operational studies. The results of the study characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eRisk of Bias across Studies\u003c/h2\u003e \u003cp\u003eRisk of bias was assessed using standard tools for different study designs. Most randomized trials had low to moderate risk of bias, although blinding was often not possible. Cohort and operational studies showed higher risk due to loss to follow-up and limited adjustment for factors such as HIV status and disease severity. Some studies also had incomplete outcome data. Overall, these limitations were unlikely to exaggerate the benefits of nutritional interventions and may have led to conservative estimates. The results are shown on Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResult of risk of bias across studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Studies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFunnel Plot Possible\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRisk of Reporting Bias\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRationale\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment success\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo major asymmetry; consistent reporting\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFew studies; no protocols for cohorts\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight gain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLimited studies; variable reporting\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdherence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMostly operational studies\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow\u0026ndash;Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStrongest evidence for primary outcome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eResults of individual studies\u003c/h2\u003e \u003cp\u003eNutritional interventions were associated with improved tuberculosis outcomes in Tanzania. Treatment success was higher among patients receiving nutritional support, with a pooled relative risk of 1.25 (95% CI: 1.10\u0026ndash;1.40), corresponding to an 18% absolute increase in cure and completion. Weight gain was consistently greater in intervention groups, with a pooled mean difference of +\u0026thinsp;2.8 kg (95% CI: 2.0\u0026ndash;3.6). Mortality was modestly reduced (HR 0.85, 95% CI: 0.70\u0026ndash;0.98), although evidence was limited by small sample sizes. Treatment adherence improved by approximately 15%, when nutritional support was made available.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eResults of synthesis (results of investigation of heterogeneity)\u003c/h2\u003e \u003cp\u003eDifferences between studies were mainly related to study design, types of nutritional interventions, and patient characteristics. Moderate variation was observed for treatment success (I\u0026sup2; = 32%), with stronger effects seen in programs combining macronutrient and micronutrient support. Weight gain showed low to moderate variation (I\u0026sup2; = 25%), largely due to differences in baseline nutritional status. Mortality outcomes had low variation (I\u0026sup2; = 18%), while adherence showed no meaningful variation (I\u0026sup2; = 0%). Subgroup analyses suggested greater benefits among patients with drug-resistant tuberculosis and TB\u0026ndash;HIV co-infection, although these findings were limited by small sample sizes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eResults of synthesis (Statistical and sensitivity analyses)\u003c/h2\u003e \u003cp\u003eA total of 18 studies were included in the statistical analysis, comprising five randomized controlled trials, eight cohort studies, and five operational evaluations. Nutritional interventions were associated with improved tuberculosis treatment outcomes. For treatment success, pooled results from three studies involving approximately 2,082 participants showed significantly higher cure and completion rates among patients receiving nutritional support compared with standard care (RR 1.25; 95% CI: 1.10\u0026ndash;1.40; I\u0026sup2; = 32%). Greater benefits were observed in interventions combining both macronutrient and micronutrient supplementation.\u003c/p\u003e \u003cp\u003eMortality was reported in two studies, with a modest reduction observed in patients receiving nutritional support (HR 0.85; 95% CI: 0.70\u0026ndash;0.98; I\u0026sup2; = 18%), although the certainty of this evidence was low due to small sample sizes. Four studies reported nutritional recovery, showing a pooled mean weight gain of +\u0026thinsp;2.8 kg (95% CI: 2.0\u0026ndash;3.6; I\u0026sup2; = 25%), particularly among severely undernourished patients. Two operational studies reported treatment adherence, with a 15% absolute improvement associated with food or cash-based support (RR 1.20; 95% CI: 1.05\u0026ndash;1.35; I\u0026sup2; = 0%). Sensitivity analyses showed that excluding high-risk or small studies did not substantially change the results, indicating that the findings were robust.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eReporting Biases\u003c/h2\u003e \u003cp\u003eReporting bias was assessed across all studies. Funnel plots for treatment success did not show clear asymmetry, suggesting low risk of publication bias for this main outcome. For mortality, weight gain, and adherence, there were too few studies to assess publication bias reliably. Most randomized trials reported planned outcomes clearly, while several operational studies lacked protocols, increasing the possibility of selective reporting. Overall, the risk of reporting bias was considered low for treatment success and moderate for other outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eCertainty of evidence\u003c/h2\u003e \u003cp\u003eThe certainty of evidence was assessed using the GRADE approach. Treatment success and weight gain were rated as moderate certainty due to consistent findings across studies, despite some risk of bias from limited blinding. Mortality and treatment adherence were rated as low certainty because of small sample sizes and potential bias in operational studies. Overall, evidence ranged from low to moderate, with nutritional interventions showing consistent benefits despite methodological limitations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003eInterpretation\u003c/h2\u003e \u003cp\u003eThis systematic review examined evidence from interventional and operational studies on the impact of nutritional interventions on tuberculosis (TB) treatment outcomes in Tanzania. Overall, the findings show that patients who received nutritional support had better treatment outcomes, including higher cure and completion rates, greater weight and BMI recovery, improved adherence, and modest reductions in mortality. These results support existing global evidence that malnutrition worsens TB outcomes by delaying recovery and increasing the risk of treatment failure and death (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). In Tanzania, Mrema et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) reported that baseline malnutrition nearly tripled the risk of death among patients with multidrug-resistant TB, highlighting the importance of integrating nutrition into routine TB care.\u003c/p\u003e \u003cp\u003eThe strongest effects were seen for treatment success and nutritional recovery. Food-based and supplement interventions led to an estimated 18% improvement in cure and completion rates, especially in programs providing food incentives or combined nutritional packages (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Patients receiving nutritional support also gained more weight, with an average increase of about 2.8 kg during treatment (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), reflecting improved physical recovery and treatment tolerance. Mortality was modestly lower among patients receiving nutritional support, particularly among undernourished and high-risk groups (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Secondary outcomes showed that better nutrition was linked to improved adherence and reduced financial burden, as food costs represent a major expense for TB patients in Tanzania (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Overall, these findings confirm that nutrition is a key component of effective TB treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eNutrition and TB Recovery\u003c/h2\u003e \u003cp\u003eThe link between tuberculosis (TB) and undernutrition works in both directions: poor nutrition weakens immunity and increases TB risk, while active TB causes weight loss and nutrient deficiencies (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Studies in this review showed that nutritional support improved recovery indicators such as weight, BMI, and, in some cases, immune markers (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). These improvements were associated with better treatment completion and survival, supporting WHO recommendations that nutrition is an important part of TB care (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Interventions combining food and micronutrients were more effective than single supplements (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). However, evidence for children and adolescents remains limited, highlighting an important research gap (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic Capacity of TB Patients with Malnutrition\u003c/h2\u003e \u003cp\u003eAlthough nutritional interventions demonstrated clear benefits, their effectiveness depends strongly on the ability of health systems to correctly identify undernourished patients. Most studies relied on simple anthropometric indicators such as body mass index (BMI), mid-upper arm circumference (MUAC), and weight change to assess nutritional status (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Only a small number of studies included biochemical markers or more detailed nutritional assessments (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). In routine clinical practice in Tanzania, nutritional screening is not consistently implemented, and standardized protocols are often lacking. As a result, malnutrition may be underdiagnosed or detected late, particularly in peripheral facilities with limited staff and laboratory capacity. This limits the timely initiation of nutritional interventions and may reduce their overall impact. Strengthening diagnostic capacity through standardized screening tools, routine documentation in TB registers, and basic staff training could improve early identification of at-risk patients and enhance the effectiveness of nutrition-sensitive TB care.\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e \u003ch2\u003eTreatment Standards for TB Patients with Under-nutrition\u003c/h2\u003e \u003cp\u003eAlthough Tanzania has policy frameworks promoting nutrition-sensitive TB care, the reviewed studies indicate that real-world implementation remains inconsistent. Barriers include weak supply chains, limited funding, lack of standardized delivery platforms, and dependence on donor-supported programs. Operational studies showed that structured nutritional support initiated at diagnosis and maintained throughout treatment resulted in better clinical and programmatic outcomes (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e), yet such interventions are not uniformly available across districts. Evidence from this review suggests that nutritional support should be formally embedded into national TB treatment guidelines, including routine nutritional screening, targeted food or supplement provision, and counselling services delivered through existing TB and community health systems (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Integration with community health worker programs may further enhance reach, particularly in rural and food-insecure settings.\u003c/p\u003e \u003cp\u003e Overall, this review demonstrates that nutritional interventions directly improve treatment success, recovery, adherence, and survival, which were the core outcomes defined in the study objectives. The evidence indicates that nutrition is not merely supportive care, but a central component of effective TB treatment in Tanzania and similar high-burden, resource-limited settings. Strengthening both nutritional support and the systems used to detect malnutrition is therefore essential for improving TB outcomes, reducing household economic vulnerability, and achieving national and global TB control targets. The approach of embedding structured nutritional support into national TB guidelines will be critical to achieving the WHO End TB targets and Tanzania\u0026rsquo;s National Action Plan on Antimicrobial Resistance (2023\u0026ndash;2028).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003eEvidence of limitations and strengths\u003c/h2\u003e \u003cp\u003eThe 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.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eLimitations of review processes\u003c/h3\u003e\n\u003cp\u003eThis 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.\u003c/p\u003e\n\u003ch3\u003eImplications of the results for practice, policy and future research\u003c/h3\u003e\n\u003cp\u003eThe findings show that nutrition plays an important role in improving tuberculosis treatment outcomes, but practical and affordable approaches are needed in settings facing declining health funding. Large-scale supplementation programs may not be sustainable, making low-cost, community-based strategies more realistic. Linking TB patients to existing social protection schemes, community food programs, and agricultural support can help improve household food security without placing additional strain on health budgets. At the facility level, routine nutritional screening, basic counselling, and referral to local food support initiatives can be integrated into standard care with minimal resources. Strengthening collaboration between health, agriculture, and social welfare sectors may improve access to food while avoiding parallel systems. Future research should focus on scalable and context-specific models that combine clinical care with sustainable food security interventions.\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003eRegistration and Protocol (registration)\u003c/h2\u003e \u003cp\u003eThe 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 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.crd.york.ac.uk/prospero/\u003c/span\u003e\u003cspan address=\"https://www.crd.york.ac.uk/prospero/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Furthermore, this systematic review was conducted following the Preferred Reporting Items for Systematic\u003c/p\u003e \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e \u003ch2\u003eRegistration and Protocol (preparation)\u003c/h2\u003e \u003cp\u003eReviews and Meta-Analyses (PRISMA) 2020 Guidelines (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). 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.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003eRegistration and Protocol (Amendments)\u003c/h2\u003e \u003cp\u003eDuring 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\u0026ndash;2025 to 2000\u0026ndash;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.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCENTRAL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCochrane Central Register of Controlled Trials\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eJBI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eJoanna Briggs Institute\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGRADE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGrading of Recommendations, Assessment, Development and Evaluation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMDR \u0026ndash; TB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMulti Drug Resistant - Tuberculosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMUAC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMid-upper arm circumference\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePRISMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePreferred Reporting Items for Systematic reviews and Meta-Analyses\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePROSPERO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Prospective Register of Systematic Reviews\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFinancial Support\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis systematic review had no source of funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests during preparation of this manuscript.\u003c/p\u003e\n\u003ch4\u003eEthics approval and consent to participate\u003c/h4\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consented to publish this article\u003c/p\u003e\n\u003ch3\u003eClinical trial registration details\u003c/h3\u003e\n\u003cp\u003eClinical trial number: not applicable\u003c/p\u003e\n\u003ch3\u003eAuthor Contribution\u003c/h3\u003e\n\u003cp\u003eConceptualization: [PB Madoshi, JR. Tibenderana \u0026amp; RS. Machang\u0026rsquo;u]Methodology: [PB Madoshi]Data curation: [PB Madoshi, G Katusi \u0026amp; TA Karuhanga]Formal analysis: [PB Madoshi, JR. Tibenderana \u0026amp; RS. Machang\u0026rsquo;u]Writing original draft: [PB Madoshi \u0026amp; TA Karuhanga]Data analysis: [PB Madoshi G Katusi \u0026amp; TA Karuhanga]Final manuscript: [PB Madoshi, JR. Tibenderana \u0026amp; RS. Machang\u0026rsquo;u]\u003c/p\u003e\n\u003ch3\u003eData Availability\u003c/h3\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMAF-TB progress and way forward: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/teams/global-programme-on-tuberculosis-and-lung-health/tb-reports/global-tuberculosis-report-2024/\u003c/span\u003e\u003cspan address=\"https://www.who.int/teams/global-programme-on-tuberculosis-and-lung-health/tb-reports/global-tuberculosis-report-2024/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhargava A, Bhargava M, Meher A, et al. 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J Clin Infect Dis Pract. 2016;1(2):1\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRange N, Andersen \u0026Aring;B, Magnussen P, Mugomela A, Friis H. The effect of micronutrient supplementation on treatment outcome in patients with pulmonary tuberculosis: a randomized controlled trial in Mwanza, Tanzania. Trop Med Int Heal. 2005;10(9):826\u0026ndash;32: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e/doi/pdf/10.1111/j.1365-3156.2005.01463.x\u003c/span\u003e\u003cspan address=\"/doi/pdf/10.1111/j.1365-3156.2005.01463.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Tuberculosis, Nutrition, Ifakara, Supplements, Multidrug resistance, Tanzania","lastPublishedDoi":"10.21203/rs.3.rs-9184342/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9184342/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTuberculosis (TB) remains a major cause of illness and death worldwide, and Tanzania continues to be among the high-burden countries. Malnutrition plays a dual role in TB: it increases the risk of developing the disease and also undermines recovery during treatment. Although nutritional support is widely recommended as part of TB care, evidence on how effective different nutritional interventions are in improving treatment outcomes is scattered and inconsistent. This systematic review aimed to synthesize existing evidence on the impact of nutritional support on TB outcomes in Tanzania and comparable sub-Saharan African settings.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e This systematic review followed PRISMA 2020 guidelines. We searched PubMed, Embase, Scopus, Web of Science, CINAHL, the Cochrane Library, and African Journals Online (AJOL) for studies published between 2000 and June 2025, alongside relevant grey literature from international agencies and government sources. Search terms included subject headings and keywords related to tuberculosis, nutrition, malnutrition, dietary interventions, Tanzania, and sub-Saharan Africa. Two reviewers independently screened titles, abstracts, and full texts, with disagreements resolved by a third reviewer. Eligible studies included randomized controlled trials and observational designs assessing nutritional interventions and reporting TB outcomes. Risk of bias was assessed using standard tools, and findings were synthesized narratively, with meta-analysis conducted where appropriate.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eEighteen studies involving approximately 5,007 participants met the inclusion criteria. Most studies reported positive effects of nutritional interventions, including higher treatment completion rates, greater weight gain, and lower mortality. Food-based and macronutrient interventions showed the most consistent benefits. In contrast, results for micronutrient supplementation were mixed and less conclusive. Several operational studies also highlighted practical challenges related to implementation, cost, and long-term sustainability in resource-limited settings.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOverall, this review shows that nutritional support can meaningfully improve TB treatment outcomes in Tanzania and similar contexts. The evidence supports the integration of food-based and macronutrient interventions into routine TB care, while also pointing to important gaps in knowledge around micronutrients and sustainable program delivery. These findings offer timely guidance for strengthening Tanzania\u0026rsquo;s National TB Program and promoting more holistic, patient-centred approaches to TB management.\u003c/p\u003e","manuscriptTitle":"Tuberculosis Treatment Outcomes in Tanzania: A Systematic Review on nutritional approach to enhance TB Outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-01 06:05:14","doi":"10.21203/rs.3.rs-9184342/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"37e8f5b9-613f-42e6-889c-b8cd199b7508","owner":[],"postedDate":"April 1st, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-06T01:46:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T09:53:43+00:00","index":30,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T01:55:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-01 06:05:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9184342","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9184342","identity":"rs-9184342","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}