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. 2026 Sep 23;22(3):e70252. doi: 10.1111/mcn.70252

Community‐Based Interventions for Childhood Undernutrition in Sub‐Saharan Africa: A Systematic Review and Network Meta‐Analysis

Francis P Riwa 1,✉, Mark A Jones 2, Kazi Mizanur Rahman 3, Andrew A Mushi 4, Kate Mueller 1
PMCID: PMC13599352  PMID: 42775707

ABSTRACT

Childhood undernutrition remains a major public health challenge in sub‐Saharan Africa (SSA), despite global progress. This review evaluated the effectiveness of community‐based interventions for treating undernutrition among children aged 6–59 months in SSA. We systematically searched MEDLINE, Embase, CINAHL, PsycINFO, and Cochrane CENTRAL from inception to August 2024, without language restrictions. Randomised controlled trials (RCTs) and cluster RCTs evaluating community‐based nutrition‐specific or nutrition‐sensitive interventions were included. Primary outcomes were weight gain, height/length gain, and mid‐upper arm circumference (MUAC). Secondary outcomes were recovery, mortality, and micronutrient status. Forty‐eight studies met the inclusion criteria. Interventions included therapeutic and supplementary feeding, dietary and micronutrient supplementation, disease management, breastfeeding and complementary feeding, and multisectoral approaches. Across the evidence base, nutrition‐specific therapeutic feeding interventions, particularly lipid‐based nutrient supplements (LNS), ready‐to‐use therapeutic foods (RUTF), and ready‐to‐use supplementary foods (RUSF), were most consistently associated with improvements in weight gain, MUAC, and recovery. Height gains were observed less consistently, and micronutrient outcomes were infrequently reported. Four comparable studies were eligible for a network meta‐analysis (NMA) comparing LNS, corn‐soy blend (CSB), and controls. Within this limited evidence network, LNS was associated with greater short‐term improvements than controls in weight (+174 g; 95% CI 121–227), height (+0.32 cm; 0.04–0.60), and MUAC (+0.12 cm; 0.05–0.19), and with greater improvements than CSB in weight (+90 g; 29–150) and MUAC (+0.11 cm; 0.06–0.17) (moderate‐certainty evidence). Community‐based nutrition interventions improve anthropometric outcomes among undernourished children in SSA. Although the NMA suggested a potential benefit of LNS over CSB and controls for short‐term anthropometric outcomes, the evidence was limited to four studies. Standardised outcome reporting and longer‐term evaluations are needed to strengthen the evidence base and inform context‐specific intervention design.

Keywords: childhood undernutrition, community‐based intervention, evidence‐based intervention, multisectoral intervention, sub‐Saharan Africa, under‐fives

Summary

  • Community‐based nutrition interventions can improve child nutrition outcomes in sub‐Saharan Africa, although effectiveness varies by intervention type, implementation fidelity, and context.

  • Nutrition‐specific therapeutic feeding interventions, particularly nutrient‐dense supplementary and therapeutic foods, were most consistently associated with improvements in weight gain, mid‐upper arm circumference (MUAC), and recovery.

  • A network meta‐analysis of four studies found that lipid‐based nutrient supplements produced greater short‐term improvements in weight and MUAC than corn‐soy blend and controls, although comparative evidence remains limited.

  • Future research should prioritise standardised outcome measures, routine reporting of micronutrient indicators, and assessment of longer‐term recovery, growth, and intervention sustainability.

1. Introduction

Childhood undernutrition remains a significant public health and development challenge in sub‐Saharan Africa (SSA), where progress towards global nutrition targets has been markedly slower than in other regions, despite global improvements (Arndt et al. 2024; Marume et al. 2025; United Nations Children's Fund [UNICEF] 2023). Stunting, wasting, underweight, and micronutrient deficiencies disproportionately affect children under five and are driven by persistent regional disparities (Akter et al. 2026). Recent estimates indicate substantial variation in prevalence: stunting (8%–64%), wasting (1%–58%), and underweight (2%–63%), highlighting the ongoing challenge of reducing childhood undernutrition across SSA's diverse settings (Riwa et al. 2025). This slow and uneven progress underscores the urgent need to better understand the complex determinants of undernutrition and micronutrient deficiencies in SSA and to identify effective, scalable interventions that can be delivered through community platforms.

Undernutrition manifests in multiple forms, including wasting (low weight‐for‐height), stunting (low height‐for‐age), underweight (low weight‐for‐age), and micronutrient deficiencies caused by inadequate intake of essential vitamins and minerals (Arndt et al. 2024; World Health Organisation [WHO] 2025). Children under 5 are particularly vulnerable, especially during the first 1000 days, a critical period when insufficient nutrition can have long‐lasting effects on physical and cognitive development, educational attainment, and economic productivity in adulthood (Akter et al. 2026; Riwa et al. 2025). The updated WHO 2030 Global Nutrition Targets emphasise accelerating progress on early‐life nutrition indicators, including exclusive breastfeeding, growth, and micronutrient status, yet SSA remains off track for several of these goals (WHO 2025).

In SSA, multiple interrelated determinants contribute to the persistent burden of child undernutrition and micronutrient deficiencies (Bain et al. 2013). These determinants operate at individual, household, and community levels, creating sustained vulnerability among children aged 6–59 months in the region (Arndt et al. 2024). Immediate determinants include inadequate dietary diversity, insufficient energy and protein intake, and suboptimal infant and young child feeding (IYCF) practices. Underlying determinants encompass chronic food insecurity, poverty, limited access to health and nutrition services, and poor water, sanitation, and hygiene (WASH) conditions (Akter et al. 2026; Riwa et al. 2025). Basic determinants include weak health systems, inadequate infrastructure, political instability, and climate‐related shocks (e.g., droughts, floods) that disrupt food production and access. These structural factors create an environment in which undernutrition persists across generations (Arndt et al. 2024).

Additionally, a high burden of infectious diseases, including diarrhoea, respiratory infections, malaria, and human immunodeficiency virus (HIV), interacts with undernutrition in a vicious cycle. Recurrent infections impair nutrient absorption, increase metabolic demands, and exacerbate micronutrient deficiencies (Mukeshimana et al. 2025). Poor WASH conditions further increase the risk of infection, creating an environment in which even well‐nourished children are at risk of growth faltering.

A growing body of evidence underscores the importance of community‐based strategies for preventing and managing childhood undernutrition in resource‐limited settings. Community‐based interventions are delivered outside hospital or inpatient settings, typically through community health workers (CHWs), peer support groups, or outpatient health facilities, and are designed to reach children in their home environments (Njeru et al. 2021). Nutrition‐specific interventions directly address the immediate dietary and biological determinants of undernutrition, including micronutrient supplementation, lipid‐based nutrient supplements (LNS), fortified blended foods (FBF), nutrition education, and counselling (Escher et al. 2024; Ghodsi et al. 2021). Nutrition‐sensitive interventions aim to tackle underlying factors that influence household food security, caregiving practices, and exposure to illness, including WASH programmes, cash transfers and social protection, agricultural and livelihood interventions, and integrated CHW delivery services (Dewey and Adu‐Afarwuah 2008; Lassi et al. 2013; Ruel et al. 2013).

The 2023 WHO guideline on preventing and managing wasting emphasises the urgent need for evidence‐informed, community‐based approaches that can be scaled within existing health systems (WHO 2023). Community‐based management of acute malnutrition has been widely adopted in SSA (Baye et al. 2025), yet evidence on the optimal choice of food supplements, delivery models, and integration with nutrition‐sensitive interventions remains limited.

Despite several global systematic reviews of nutrition interventions, evidence specific to SSA remains fragmented, and many reviews have focused exclusively on facility‐based care or maternal nutrition rather than on community delivery for children aged 6–59 months (Bhutta et al. 2013; Das et al. 2020; Escher et al. 2024; Ghodsi et al. 2021). Additionally, a review found that LNS products generally outperformed standard FBF in anthropometric recovery among children with moderate acute malnutrition (MAM) (Gera et al. 2017). However, syntheses pooling evidence from diverse geographic regions may not fully capture SSA‐specific contextual factors, such as endemic malaria, poor WASH infrastructure, and weak health systems, which could influence intervention effectiveness.

This systematic review addresses this gap by synthesising evidence specific to SSA from randomised controlled trials (RCTs), conducting a network meta‐analysis (NMA) to compare multiple community‐based interventions simultaneously, and systematically evaluating nutrition‐specific and nutrition‐sensitive interventions. Our findings aim to inform policy and programme implementation for the community‐based management and treatment of undernutrition in children aged 6–59 months in SSA.

2. Methods

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) 2020 guidelines (Page et al. 2021) and with an a priori protocol registered on the Open Science Framework (OSF) and available online at https://doi.org/10.17605/OSF.IO/SH46N. Any changes and deviations from the protocol are documented and justified in the manuscript.

2.1. Data Sources and Search Strategy

A comprehensive literature search was conducted across five electronic databases, MEDLINE (via PubMed), Embase, CINAHL (EBSCO), PsycINFO, and the Cochrane Central Register of Controlled Trials (CENTRAL), from inception to August 13, 2024, without language or date restrictions. The MEDLINE search strategy combined Medical Subject Headings (MeSH) with keywords for community‐based, evidence‐based, and multisectoral interventions, childhood undernutrition, and sub‐Saharan Africa. Search terms were translated for other databases using the Systematic Review Accelerator Polyglot tool. Forward and backward citation searches of all included studies were also conducted to identify additional eligible studies. The full search strategy is provided in Supplemental Table 1.

2.2. Study Eligibility Criteria

Studies were selected using the Population, Intervention, Comparators, Outcomes, Type of Studies, and Settings (PICOTS) framework. Given the review's primary objective of evaluating the effectiveness of community‐based interventions, eligibility was restricted to RCTs or cluster RCTs, as these designs provide the strongest evidence for intervention effectiveness by strengthening causal inference and reducing the risk of selection bias and confounding. Studies were eligible if they were conducted in community‐based or outpatient settings in any of the 49 SSA countries classified by the World Bank regional classification (Supplemental Table 2) (World Bank Group 2022).

Eligible interventions included nutrition‐specific and nutrition‐sensitive strategies to address undernutrition in children aged 6–59 months. There were no restrictions on intervention duration or follow‐up period, and both end‐of‐intervention and post‐intervention outcomes were eligible for inclusion. Studies were required to report at least one primary anthropometric outcome, such as weight gain, height/length gain, or mid‐upper arm circumference (MUAC). Secondary outcomes included anthropometric recovery, mortality, and micronutrient status. Because recovery criteria varied across studies, recovery outcomes were reported according to the definitions used in the original studies. Micronutrient outcomes included biomarkers reported by eligible studies, such as haemoglobin concentration, anaemia prevalence, serum retinol (vitamin A status), iron status indicators, and other related biochemical measures. Studies were excluded if they were conducted in inpatient or hospital settings; included participants outside the target age group without disaggregated data; focused on primary prevention rather than the treatment of undernutrition; or targeted children with conditions other than undernutrition, including HIV, malaria, parasitic infections, or acute diarrhoea. Key concepts, terminology, and outcome definitions are provided in Supplemental Table 3.

2.3. Study Screening and Selection

All identified records were imported into EndNote 20 (The EndNote Team 2013) for deduplication, then uploaded to Covidence for screening and data management (Veritas Health Innovation 2021). Titles and abstracts were screened independently by two reviewers (FPR and KM), with disagreements resolved by discussion or by a third reviewer (MAJ or KMR). Full texts were assessed independently by three reviewers (FPR, MAJ, and KMR), with adjudication by a fourth reviewer (KM) as required.

2.4. Data Extraction

One reviewer (FPR) independently extracted data from the included studies using a standardised extraction form, which was developed and piloted on a subset of studies before full data extraction. The extracted data included study characteristics, intervention details (using the Template for Intervention Description and Replication [TIDieR] checklist) (Hoffmann et al. 2014), participant demographics, outcomes, results, and information required for risk‐of‐bias assessment. When both intention‐to‐treat (ITT) and per‐protocol (PP) results were available, ITT estimates were prioritised to improve comparability and reduce bias.

2.5. Methodological Quality

Two reviewers (FPR and MAJ) independently assessed the risk of bias for each included study using the Cochrane Risk of Bias 2 (RoB 2) tool for randomised and cluster RCTs (Higgins et al. 2019). They evaluated bias arising from the randomisation process, deviations from intended interventions, missing data, outcome measurement, and the selection of reported results. Cluster RCTs were also assessed for timing‐related identification and recruitment bias. Discrepancies were resolved by discussion. Summary figures were generated using the RobVis visualisation tool (McGuinness and Higgins 2021).

2.6. Data Synthesis and Statistical Analysis

A descriptive synthesis of all included studies, detailing study characteristics, populations, interventions, comparators, outcomes, and findings, was summarised in tables and in the text. For interventions involving food supplements judged sufficiently similar in terms of interventions (comparable food supplement formulations), population (children with undernutrition), comparators, and outcomes, a frequentist NMA was conducted using the netmeta package within the MetaInsight platform (Balduzzi et al. 2023; Owen et al. 2019). A random‐effects model was used to estimate mean differences (MDs) and 95% confidence intervals (CIs) for changes in weight, height, and MUAC from baseline to final follow‐up. Interpretation prioritised the direction and magnitude of effects and cross‐study consistency over statistical significance alone. Network inconsistency was assessed by comparing direct and indirect treatment estimates (Supplemental Table 4).

2.7. Certainty of Evidence Assessment

The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was independently applied by two reviewers (FPR and MAJ) to assess the certainty of evidence adapted for NMA comparisons (Brignardello‐Petersen et al. 2018). Disagreements were resolved through discussion. Studies unsuitable for meta‐analysis due to clinical or methodological heterogeneity were synthesised narratively. Only studies assessed as low risk or with some concerns using the RoB 2 tool were included in the narrative synthesis; high‐risk studies were summarised separately and excluded from inferential interpretation.

2.8. Changes and Deviations From the Registered Protocol

We revised the eligibility criteria from the original registered protocol to refine the study screening and selection process.

3. Results

3.1. Study Selection

A total of 5975 records were identified, of which 3699 remained after duplicate removal. After title and abstract screening (n = 3699) and full‐text review (n = 387), 48 studies met the eligibility criteria (Figure 1). No additional studies were identified through citation searching.

Figure 1.

Figure 1

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PRISMA flow diagram of study selection.

3.2. Characteristics of Included Studies

The 48 included studies were conducted across 21 SSA countries from 1986 to 2024, primarily in Western and Southern Africa. Sample sizes ranged from 60 to 3945 children, most aged 6–59 months and diagnosed with MAM or uncomplicated severe acute malnutrition (SAM). Interventions fell into five main categories (nutrition‐specific and nutrition‐sensitive) and were delivered in community or outpatient settings. Most studies included medium‐term follow‐up (4–6 months), with some assessing short‐term (< 2 months) and long‐term (up to 12 months) outcomes. Detailed characteristics are presented in Table 1.

Table 1.

Summary of key characteristics of included studies.

Characteristics Summary/description
N 48 randomised controlled trials (RCTs)/cluster RCTs
Years 1986–2024
Study design Individual RCTs: n = 34 (74%); Cluster RCTs: n = 14 (29%)
Countries 21 sub‐Saharan African (SSA) countries: Benin (n = 2; 4%), Burkina Faso (n = 4; 8%), Cameroon (n = 1; 2%), Chad (n = 1; 2%), the Democratic Republic of Congo (DRC) (n = 3; 6%), Ethiopia (n = 2; 4%), Ghana (n = 1; 2%), Guinea Bissau (n = 1; 2%), Kenya (n = 2; 4%), Malawi (n = 12; 24%), Mali (n = 1; 2%), Niger (n = 2; 4%), Nigeria (n = 2; 4%), Sierra Leone (n = 4; 8%), South Africa (n = 4; 8%), Uganda (n = 2; 4%), the United Republic of Tanzania (URT) (n = 1; 2%), Zambia (n = 1; 2%) 2 multi‐country studies: Malawi and Mozambique (n = 1; 2%) and Niger, the Central African Republic (CAR), Senegal and Madagascar (n = 1; 2%)
Regions Western/Southern Africa: n = 35 (73%); Eastern/Central Africa: n = 11 (23%)
Sample size (baseline) 60–3945 participants
Population (age) Children aged 6–59 months
Sex distribution Both sexes: n = 11; Single‐sex: n = 34 (males‐only n = 20; females‐only n = 14); NR: n = 3
Undernutrition classification SAM: weight‐for‐height (WHZ) Z‐score < – 3 or mid‐upper arm circumference (MUAC) < 115 mm; MAM: WHZ – 2 to – 3
Setting & delivery model Community‐based, delivery in person at health centres, community venues, or homes
Intervention category Dietary andmicronutrient supplementation, multisectoral approaches, therapeutic and supplementary feeding, disease management, and breastfeeding and complementary feeding interventions
Intervention durationa Short‐term < 2 months: n = 5; Medium‐term 4–6 months: n = 36; Long‐term up to 12 months: n = 7
Anthropometric measurements All studies reported ≥ 1 anthropometric measure (weight, height/length, MUAC or WHZ, HAZ, WAZ)
Micronutrient status 10/48 studies (primarily haemoglobin [Hb] or serum retinol)
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Abbreviations: HAZ, height‐for‐age Z‐score; MAM, moderate acute malnutrition; MUAC, mid‐upper arm circumference; NR, not reported; RCT, randomised controlled trials; SAM, severe acute malnutrition; SSA, sub‐Saharan Africa; WAZ, weight‐for‐age Z‐score.

N = Number of studies.

a

Short‐term interventions showed quick improvements in weight and MUAC, while medium‐ and long‐term studies demonstrated sustained recovery or linear growth.

3.3. Risk of Bias Assessment

Of the 48 studies, 30 were assessed as having a low risk of bias or some concerns. Meanwhile, 18 were classified as high risk due to issues with randomisation, timing of participant recruitment, deviations from the intended intervention, missing outcome data, and outcome measurement. Supplemental Figure 1 illustrates the RoB assessment. High‐risk studies were excluded from the interpretative synthesis and summarised separately in Supplemental Table 5.

Table 1 summarises the key features of the included studies, including study designs, populations, settings, intervention duration, and outcomes. Detailed descriptions of the interventions are provided in Supplemental Tables 6 and 7.

3.4. Network Meta‐Analysis

Only four eligible trials with comparable populations and formulations, comparing LNS, CSB, and no‐treatment control, and sufficiently homogeneous outcomes were included in the NMA (Fabiansen et al. 2017; Mbabazi et al. 2023; Thakwalakwa et al. 2010; Thakwalakwa et al. 2012). One additional eligible trial (Othoo et al. 2021) lacked anthropometric data and was therefore excluded from the NMA. The remaining four trials examined 12‐week interventions among children aged 6–59 months with acute malnutrition and measured comparable anthropometric outcomes, including weight gain, height/length gain, and MUAC change. Two trials compared LNS, CSB, and control; one trial compared LNS and CSB; and one trial compared LNS and control (Supplemental Figure 2). Supplemental Figure 3 shows the networks for the weight, height/length, and MUAC outcomes, along with study counts. The network included three nodes (LNS, CSB, control) and 8 direct comparisons: LNS versus control (3 studies), CSB versus control (2 studies), and LNS versus CSB (3 studies). None reported recovery rates or other outcomes of interest.

The NMA demonstrated that LNS produced significantly greater gains in weight (+174 g), height (+0.32 cm), and MUAC (+0.12 cm) than control (p < 0.05). Additionally, LNS outperformed CSB in weight gain (+84 g) and MUAC (+0.11 cm). CSB was superior to control in weight gain (+90 g). No inconsistencies were observed between direct and indirect comparisons (Figure 2; Supplemental Table 4).

Figure 2.

Figure 2

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Network meta‐analysis forest plots for weight, height/length, and MUAC outcomes. (A) Weight. CI, Confidence Interval; CSB, Corn‐Soy Blend; LNS, Lipid‐Based Nutrient Supplements; MD, Mean Difference. Interpretation: Between‐study standard deviation: 0, Number of studies: 4, Number of treatments: 3. All outcomes are versus the reference treatment: Control. (B) Height. CI, Confidence Interval; CSB, Corn‐Soy Blend; LNS, Lipid‐Based Nutrient Supplements; MD, Mean Difference. Interpretation: Between‐study standard deviation: 0.21, Number of studies: 4, Number of treatments: 3. All outcomes are compared against the reference treatment: Control. (C) MUAC. CI, Confidence Interval; CSB, Corn‐Soy Blend; LNS, Lipid‐Based Nutrient Supplements; MD, Mean Difference. Interpretation: Between‐study standard deviation: 0; Number of studies: 4; Number of treatments: 3. All outcomes are versus the reference treatment: Control.

These forest plots show the comparative effects of LNS, CSB, and the no‐treatment control across the included studies. The results indicate that LNS produced significantly greater gains in weight, height/length, and MUAC than CSB and the control, consistent with the pooled NMA estimates.

3.5. Certainty of Evidence Assessment (GRADE)

We assessed the certainty of evidence for each network estimate using the GRADE approach. For NMA comparisons (LNS vs CSB vs no‐treatment control), GRADE rated the evidence as moderate for weight, height/length, and MUAC, primarily downgraded due to imprecision arising from the limited number of eligible studies. Table 2 presents the GRADE evidence profile summarising the certainty of evidence for key comparisons.

Table 2.

GRADE ‘Summary of Findings' for NMA comparisons of weight, height/length, and MUAC.

Outcome Intervention Comparator NMA Comments
Mean difference (95% CI) Quality of evidence (GRADE)
Weight LNS CSB 90 grams (29 to 150) ⊕ ⊕ ⊕ Ο Moderate Results are consistent, and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
LNS Control 174 grams (121 to 227) ⊕ ⊕ ⊕ Ο Moderate Results are consistent, and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
CSB Control 84 grams (43 to 125) ⊕ ⊕ ⊕ Ο Moderate Results are consistent, and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
Height LNS CSB 0.12 cm (− 0.15 to 0.40) ⊕ ⊕ ⊕ Ο Moderate Results are consistent, and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
LNS Control 0.32 cm (0.04 to 0.60) ⊕ ⊕ ⊕ Ο Moderate Results are consistent and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
CSB Control 0.19 cm (− 0.14 to 0.52) ⊕ ⊕ ⊕ Ο Moderate Results are consistent, and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
MUAC LNS CSB 0.11 cm (0.06 to 0.17) ⊕ ⊕ ⊕ Ο Moderate Results are consistent and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
LNS Control 0.12 cm (0.05 to 0.19) ⊕ ⊕ ⊕ Ο Moderate Results are consistent, and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
CSB Control 0.01 cm (− 0.08 to 0.09) ⊕ ⊕ ⊕ Ο Moderate Results are consistent, and directly applicable. Studies had low risk of bias. Publication bias could not be assessed due to insufficient number of studies. Downgraded by one level due to imprecision.
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Abbreviations: CI, confidence interval; CSB, corn‐soy‐blend; LNS, lipid‐based nutrient supplements; MUAC, mid‐upper arm circumference; NMA, network meta‐analysis.

Description of the interpretation of the GRADE four levels of certainty of evidence:

⊕⊕⊕⊕ High – We are very confident that the actual effect lies close to that of the estimated effect.

⊕ ⊕ ⊕ Ο Moderate – We are moderately confident in the effect estimate; the actual effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different.

⊕⊕ΟΟ Low – Our confidence in the effect estimate is limited; the actual effect may be substantially different from the estimate of the effect.

⊕ΟΟΟ Very low – We have very little confidence in the effect estimate; the actual effect is likely to be substantially different from the estimate of the effect.

3.6. Narrative Synthesis of Studies Not Included in the NMA

Table 3 summarises effectiveness findings from 26 studies with low risk of bias or some concerns, which were synthesised narratively. These studies varied widely in intervention type, follow‐up duration and population characteristics. To improve comparability, narrative synthesis and findings for primary and secondary outcomes are organised into five intervention categories: therapeutic and supplementary feeding (ready‐to‐use therapeutic foods [RUTF], ready‐to‐use supplementary foods [RUSF], LNS, fortified blended flours); breastfeeding and complementary feeding interventions; dietary and micronutrient supplementation; disease prevention and management; and multisectoral interventions (cash transfers, WASH‐integrated interventions). The remaining 18 high‐risk studies were excluded from the narrative synthesis.

Table 3.

Summary of findings for narrative studies (low and/or some concerns) by intervention category, undernutrition type, delivery model, location, and study quality (n = 26).

Author, year Country Intervention category (specific intervention) Follow‐up length Undernutrition type Delivery model Outcomes and time points measured Study quality (RoB) Notes/Main findings
Altmann et al. (2018)† Chad Multisectoral approaches (WASH package + standard OTP) 12 weeks (2 months OTP + 1 month's post‐treatment) SAM Community/outpatient household WASH Weight gain (g/kg/d & g/d); recovery; mortality; MUAC; measured weekly at endline Some concerns ↑ Absolute weight gain; +10.5% recovery vs OTP alone; mortality = not significant (NS); effects context‐dependent
Bahwere et al. (2014) Malawi Therapeutic and supplementary feeding (WPC‐RUTF vs standard peanut RUTF) 4 months SAM Outpatient therapeutic feeding Weight gain; recovery, and weekly follow‐ups Low WPC‐RUTF is non‐inferior to standard RUTF for weight and recovery
Donnen et al. (1998)‡ Democratic Republic of the Congo (DRC) Dietary and micronutrient supplementation (vitamin A; mebendazole; vs control) 12 months (assessment at 3, 6, 9, 12 months) MAM Community Weight, height, MUAC; serum retinol; anaemia; albumin Some concerns Vitamin A improved weight/MUAC in deficient children; deworming ↓ gains; mixed overall effects
Dossa et al. (2001)† Benin Multisectoral approaches (iron + albendazole vs placebo) 3 & 10 months Stunted preschoolers Community Weight, height, MUAC, WHZ, HAZ; Hb at baseline/3/10 months Some concerns Hb ↑ in iron arms; anthropometric changes broadly similar across groups
Dossa et al. (2001) Benin Dietary and micronutrient supplementation (multi‐vitamin‐multimineral vs placebo) 6 weeks (with ~4 months follow‐up) Stunted toddlers (17–32 months) Community Weight, height, MUAC, WHZ, HAZ at baseline/during/after Some concerns Similar anthropometric growth between groups over a short follow‐up
Glatthaar et al. (1986) South Africa Breastfeeding and complementary feeding (nutrition education vs routine care) 11 months Underweight children Community/home Weight, height (WAZ/WHZ/HAZ) before/after Some concerns NS anthropometric impact as a standalone rehabilitation measure
Grellety et al. (2017)† DRC Multisectoral approaches (UCT + standard SAM/RUTF + counselling vs standard) 6 months SAM Outpatient; social protection add‐on Weight gain; WAZ/WHZ; recovery; mortality; measured weekly/monthly Low ↑ Weight, WAZ, WHZ; recovery 96.3% vs 88.4%; mortality NS cash‐plus strengthens outcomes
Griswold et al. (2021) Sierra Leone Therapeutic and supplementary feeding (CSWB + oil; SC + A; RUSF vs CSB +control) 12 weeks MAM Community Recovery; sustained recovery; measured bi‐weekly, at 4 weeks, and 3 months Some concerns Odds of recovery NS across foods; sustained recovery is lower with RUSF vs CSWB + oil or SC + A
Hendrixson et al. (2020)† Sierra Leone Therapeutic and supplementary feeding (oat‐RUTF vs standard RUTF) ≤ 12 weeks SAM Outpatient Weight gain (g/kg/d); MUAC (mm/d); graduation; mortality Low ↑ Weight (MD 0.8 g/kg/d), ↑ MUAC, ↑ graduation (+ 10.6%); mortality NS
Isanaka et al. (2016) Niger Disease management (routine amoxicillin vs placebo) 12 weeks SAM Outpatient Nutritional recovery at/after 3 weeks & by 8 weeks; weight gain weekly; mortality Low No significant differences in recovery vs placebo; weight gain NS
Kangas et al. (2019) Burkina Faso Therapeutic and supplementary feeding (reduced‐dose RUTF vs standard) ≤ 16 weeks SAM Outpatient Weight gain (g/kg/d); MUAC (mm/wk); height (mm/wk); recovery Low No differences in weight/MUAC/recovery; lower linear growth with reduced
LaGrone et al. (2012) Malawi Therapeutic and supplementary feeding (CSB + + vs soy‐RUSF vs soy/whey‐RUSF) ≤ 12 weeks (bi‐weekly) MAM Community/outpatient Weight (g/kg/d); length (mm/d); MUAC (mm/d); recovery Low Recovery similar CSB + + vs RUSF; MUAC gain higher with soy/whey‐RUSF; length similar
Maleta et al. (2004)† Malawi Therapeutic and supplementary feeding (RTUF vs maize/soy flour) 12 weeks Underweight/stunted Community Weight; height, post‐intervention Some concerns ↑ Weight with RTUF (+77 g) height NS
Maru et al. (2024)† Ethiopia Therapeutic and supplementary feeding (simplified approach vs standard) ≤ 16 weeks (bi‐weekly) Wasting (SAM & MAM) Decentralised outpatient Recovery (MUAC criterion) every 2 weeks; death) Some concerns Non‐inferior recovery (94.3% vs 92.4%); mortality NS; reduced RUTF costs
Matilsky et al. (2009) Malawi Therapeutic and supplementary feeding (Fortified spreads vs CSB) ≤ 8 weeks MAM Community Recovery (WHZ > ‐2); weight/height; adverse outcomes (bi‐weekly) Low Higher recovery with fortified spreads (79%–80% vs 72% CSB); weight/height similar)
Medoua et al. (2016) Cameroon Therapeutic and supplementary feeding (CSB+ vs RUSF) 56 days (8 weeks) MAM (25–59 months) Community/outpatient Weight gain (14 d); MUAC (baseline/end); recovery Some concerns ↑ Weight gain with RUSF; recovery similar (73% vs 85%); no deaths
Nane 2021, † Ethiopia Therapeutic and supplementary feeding (local‐ingredients supplement vs CSB +) 12 weeks MAM (6–59 months) Community/outpatient Weight/height/MUAC (over 12 weeks); recovery Low Non‐inferior to CSB+ across weight/height/MUAC and recovery
Oakley et al. (2010)† Malawi Therapeutic and supplementary feeding (10% vs 25% milk RUTF) ≤ 8 weeks SAM Outpatient Weight (g/kg/d), height (mm/d), MUAC (mm/d); recovery at 8 weeks Low 25% milk RUTF superior (↑ weight, height, MUAC; ↑ recovery 84% vs 81%)
O'Brien et al. (2022) Burkina Faso Disease management (azithromycin vs amoxicillin) 8 weeks SAM Outpatient Weight gain; recovery; MUAC; HAZ/WAZ/WHZ at weeks 0–1, 1–2, 2–4, 4–8 Low No significant differences between antibiotics for growth or recovery
Othoo et al. (2021) Kenya Therapeutic and supplementary feeding (Spirulina‐CSB vs CSB vs placebo) 6 months MAM with IDA (6–23 months) Community Hb; recovery from IDA; MUAC; recovery rate “per 100 persons daily” Low Higher IDA recovery and recovery rate with Spirulina‐CSB vs CSB/placebo
Phuka et al. (2009) Malawi Therapeutic and supplementary feeding (Likuni Phala vs fortified spreads) 12 weeks Underweight (6–18 months) Community Weight; LAZ/WLZ/WAZ; MUAC; Hb; measured q2 weeks and endline Low Similar effects on moderate wasting/underweight; limited effect on stunting
Roediger et al. (2020) Malawi Therapeutic and supplementary feeding (protein‐quality optimised RUSF vs control RUSF) ≤ 12 weeks (4/8/12 weeks) MAM Community/outpatient Weight; MUAC; recovery; measured at 4, 8, 12 weeks Low No differences in MAM recovery, weight, and MUAC NS
Stephenson et al. (2022)† Malawi Management/Treatment (DHA‐HO‐RUTF; HO‐RUTF; S‐RUTF) ≤ 12 weeks SAM Outpatient Weight/height/MUAC (mm/d); recovery; adverse events Low All groups improved; S‐RUTF highest recovery; no RUTF outperformed S‐RUTF on other growth outcomes
Stewart et al. (2019) Malawi Breastfeeding and complementary feeding (one egg/day vs control) 6 months Children 6–9 months (MUAC > 12.5 cm) Community/home LAZ/stunting; WAZ/underweight; WLZ/wasting (assessed at baseline, 3, 6 months) Low No effect on linear growth, stunting, underweight, or wasting
Stobaugh et al. (2016)† Malawi & Mozambique Therapeutic and supplementary feeding (whey‐RUSF vs soy‐RUSF) ≤ 12 weeks MAM Community/outpatient; double‐blind Recovery; MUAC; WHZ; weight; length; bi‐weekly and endline Low ↑ Recovery, ↑ MUAC/WHZ/weight with whey‐RUSF; length NS
Vray et al. (2024) Niger, Central African Republic (CAR), Senegal, and Madagascar Therapeutic and supplementary feeding (fortified flour + antibiotic or prebiotic) 12 weeks MAM (6–24 months) Community/multi‐country WHZ thresholds (≥ ‐1.5; ≥ ‐2); MUAC; HAZ at week 12 Low Similar overall recovery (~44%); WHZ ≥ ‐2 higher with add‐on arms (p = 0.005); MUAC/HAZ NS
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Note: GRADE certainty of evidence – GRADE ratings were not applied to narratively synthesised studies. They were only used for the NMA comparisons. Therefore, narratively, findings should be interpreted with respect to the RoB 2 assessments above rather than certainty ratings. Data are presented as MDs with 95% CIs based on ITT analysis.

Abbreviations: CIs, Confidence Intervals; CSB, Corn‐Soy Blend; CSB + +, Corn‐Soy Blend “plus‐plus”; CSWB w/oil, Corn Soy Whey Blend with fortified vegetable oil; DHA‐HO‐RUTF, High‐Oleic Acid Ready‐to‐Use Therapeutic Food; Hb, Haemoglobin; HAZ, Height‐for‐Age Z‐score; IDA, Iron Deficiency Anaemia; LAZ, Length‐for‐Age Z‐Score; MAM, Moderate Acute Malnutrition; MDs, Mean Differences; MUAC, Mid‐Upper Arm Circumference; NP, Not Reported; OTP, Outpatient Therapeutic Feeding Programme; PM‐RUTF, Peanut and Milk‐Based RUTF; RCT, Randomised Controlled Trial; RoB, Risk of Bias; RR, Relative Risk; RR, Risk Ratio; RTUF, Ready‐to‐Use Food; RUTF, Ready‐to‐Use‐Therapeutic Food; RUSF, Ready‐to‐Use Supplementary Food; S‐RUTF, Standard Ready‐to‐Use Therapeutic Food; SAM, Severe Acute Malnutrition; SC + A, Super Cereal Plus with amylase; UCT, Unconditional Cash Transfer; WASH, Water, Sanitation, and Hygiene; WAZ, Weight‐for‐Age Z‐Score; WHZ, Weight‐for‐Height Z‐score; WLZ, Weight‐for‐Length Z‐Score; WPC, Whey Protein Concentrate.

†

↑ Increase gain.

‡

↓ Decrease gain.

3.7. Primary Outcomes

3.7.1. Weight Gain (n = 21)

Twenty‐one of the 26 studies reported weight gain. Seven demonstrated significant improvements (p < 0.05), most involving therapeutic and supplementary feeding with enhanced RUTF formulations, improved RUSF, and LNS‐based products (Bahwere et al. 2014; Hendrixson et al. 2020; Maleta et al. 2004; Matilsky et al. 2009; Medoua et al. 2016; Oakley et al. 2010; Stobaugh et al. 2016). Two multisectoral interventions, namely unconditional cash transfers (UCTs) alongside SAM management and household WASH plus the outpatient therapeutic feeding programme (OTP), also improved weight gain (Altmann et al. 2018; Grellety et al. 2017). Six studies examined complementary feeding, disease management, or reduced‐dose therapeutic approaches and reported non‐significant or inconsistent changes 2019. Additionally, six reported weight outcomes without effect estimates. The pattern still favoured nutrient‐dense supplements; however, the absence of statistical reporting reduced interpretability.

3.7.2. Height/Length Gain (n = 17)

Linear growth improvements were uncommon, with only two of 17 studies reporting greater height gains. These studies used therapeutic and supplementary feeding with standard‐dose or higher‐protein RUTF, yielding modest gains in linear growth (Oakley et al. 2010; Stephenson et al. 2022). One study comparing reduced‐dose to standard RUTF found lower height gain in the reduced‐dose group (Oakley et al. 2010). Eight studies reported no significant change, and six did not report effect estimates. Overall, linear growth effects were limited during the observed time frames.

3.7.3. MUAC Improvements (n = 16)

Sixteen of the 26 studies assessed MUAC. Five reported greater improvements, with four primarily through therapeutic and supplementary feeding using higher‐quality RUTF/RUSF formulations, particularly whey‐ or milk‐based formulations (Hendrixson et al. 2020; LaGrone et al. 2012; Oakley et al. 2010; Stobaugh et al. 2016). Another study examined dietary and micronutrient supplementation, including vitamin A, which significantly improved MUAC in children with vitamin A deficiency (Donnen et al. 1998). Six studies reported non‐significant differences, and five did not provide effect estimates.

Table 2 summarises the effectiveness findings by intervention category for studies with low risk or with some concerns.

3.8. Secondary Outcomes

3.8.1. Recovery (n = 19)

Of 19 studies reporting anthropometric recovery, eight observed greater improvements. Six of these studies evaluated therapeutic and supplementary feeding interventions, including fortified spread, higher‐milk RUTF, and whey‐enhanced RUSF (Hendrixson et al. 2020; Matilsky et al. 2009; Oakley et al. 2010; Othoo et al. 2021; Stephenson et al. 2022; Stobaugh et al. 2016). The remaining two studies assessed multisectoral interventions, namely UCT + SAM management and WASH + OTP (Altmann et al. 2018; Grellety et al. 2017). Eleven studies reported non‐significant differences.

3.8.2. Mortality (n = 6)

Six of 26 studies assessed mortality, and none reported statistically significant between‐group differences.

3.8.3. Micronutrient Status (n = 4)

Only 4 of 26 studies reported micronutrient outcomes (Donnen et al. 1998; Dossa et al. 2001; Othoo et al. 2021; Phuka et al. 2009). Two of these studies—one involving therapeutic and supplementary feeding with Spirulina‐CSB‐fortified food, and another involving dietary and micronutrient supplementation, including iron‐containing supplements and deworming—reported greater improvements in iron‐deficiency anaemia. Multivitamin supplementation had limited effects on anthropometric measures and mixed effects on micronutrient levels, highlighting inconsistent reporting of micronutrients across studies.

3.9. Summary of Main Findings

Across the included studies, nutrition‐specific therapeutic feeding strategies, including LNS, RUTF, and RUSF, were most consistently associated with improvements in weight gain, MUAC, and recovery among children aged 6–59 months with uncomplicated SAM or MAM. Improvements in linear growth were observed less consistently, mortality effects were generally null, and micronutrient outcomes were infrequently reported. Several studies incorporating nutrition‐sensitive components, such as WASH and cash‐transfer interventions, also reported benefits for recovery and weight gain. Although an NMA suggested greater short‐term anthropometric improvements with LNS than with CSB and no‐treatment controls, substantial heterogeneity in intervention characteristics, outcome definitions, and follow‐up durations limited cross‐study comparability and meta‐analytic pooling beyond the LNS–CSB network, as well as the generalisability of comparative findings.

4. Discussion

This systematic review synthesised evidence from 48 RCTs and cluster RCTs evaluating community‐based interventions for childhood undernutrition among children aged 6–59 months in SSA, providing an updated, region‐specific synthesis. Overall, the findings indicate that community‐based nutrition interventions can improve anthropometric outcomes, particularly weight gain and MUAC. Across the review, nutrition‐specific therapeutic feeding interventions, including LNS, RUTF, and RUSF, as well as fortified supplementary foods, were most consistently associated with positive outcomes. In contrast, effects on linear growth were generally limited, and evidence on micronutrient outcomes, mortality, and longer‐term recovery remained sparse.

Among the 26 studies included in the narrative synthesis with acceptable methodological quality, therapeutic feeding interventions demonstrated the most consistent improvements in weight gain, MUAC, and recovery among children with uncomplicated SAM and MAM. Positive effects were also observed across a range of formulations, particularly nutrient‐dense products containing milk‐ or whey‐based ingredients, suggesting that the nutritional composition of supplementary and therapeutic foods may be an important determinant of treatment response. Nevertheless, substantial variation in intervention design, participant characteristics, delivery approaches, treatment duration, and outcome measurement limited direct comparisons across studies.

Only four studies were sufficiently comparable to be included in the NMA. Within this limited evidence network, LNS was associated with greater short‐term improvements in weight gain, height, and MUAC than CSB and no‐treatment controls, with moderate‐certainty evidence and no evidence of inconsistency between direct and indirect comparisons. Although these findings are consistent with the broader pattern observed in the review, they should be interpreted with caution, as they are based on a limited number of studies evaluating a narrow range of interventions. Consequently, the NMA findings should be regarded as limited evidence of the comparative effectiveness of LNS.

The broader evidence base reviewed suggests that interventions providing concentrated energy, protein, and essential micronutrients are more likely to produce rapid improvements in anthropometric indicators than those that focus primarily on education, counselling, or disease management. However, improvements in height were uncommon, reflecting the well‐recognised challenge of achieving measurable gains in linear growth over relatively short intervention periods (Adu‐Afarwuah et al. 2015; Huybregts et al. 2012). Additionally, linear growth is influenced by multiple long‐term factors, including dietary adequacy, recurrent infection, environmental enteric dysfunction, household living conditions, and access to healthcare, many of which are unlikely to be sufficiently addressed by short‐duration supplementary feeding interventions alone (Budge et al. 2019).

These synthesised findings broadly align with previous systematic reviews and meta‐analyses that report favourable effects of nutrition‐specific interventions, particularly therapeutic and supplementary feeding products, for managing acute malnutrition (Bhutta et al. 2013; Das et al. 2020; Escher et al. 2024). Similarly, other reviews have found that lipid‐based and ready‐to‐use nutritional products often yield greater improvements in anthropometric outcomes than cereal‐based alternatives, particularly among children with acute malnutrition managed in community settings (Ackatia‐Armah et al. 2015; Bahwere et al. 2016; Gera et al. 2017). For example, Gera et al. (2017) reported higher recovery rates and improved anthropometric outcomes with LNS compared with FBF. Consistent with previous evidence, gains in weight and MUAC were more common than improvements in linear growth, while evidence on sustained recovery, relapse, and long‐term developmental outcomes remains limited.

Breastfeeding and complementary feeding interventions alone generally yield limited or inconsistent improvements in anthropometric outcomes among already undernourished children. Similarly, dietary and micronutrient supplementation demonstrated benefits primarily among children with identified nutrient deficiencies. These findings suggest that although education and micronutrient interventions remain important components of comprehensive nutrition programmes, they may be insufficient as standalone treatment strategies for acute malnutrition. In contrast, several studies incorporating nutrition‐sensitive components, including WASH interventions and UCTs, reported improvements in recovery and weight gain, highlighting the importance of addressing environmental, socioeconomic, and household‐level determinants alongside dietary interventions (Escher et al. 2024; Ruel et al. 2013). This review therefore extends the existing evidence base by providing an SSA‐specific synthesis and highlighting the diversity of community‐based intervention approaches currently implemented across the region.

4.1. Strengths and Limitations of the Evidence Base

The systematic review has several strengths. It was conducted in accordance with a prospectively registered protocol and PRISMA guidelines, with duplicate screening, data extraction, a risk‐of‐bias assessment using RoB‐2, and a certainty appraisal using the GRADE framework. By focusing specifically on SSA, the review provides contextually relevant evidence for the region. Additionally, including both nutrition‐specific and nutrition‐sensitive interventions enabled a comprehensive assessment of community‐based approaches across diverse settings and intervention models.

Several limitations should also be considered. Although 48 studies met the inclusion criteria, substantial heterogeneity in intervention types, doses, delivery methods, outcome definitions, and reporting practices limited the feasibility of quantitative synthesis. As a result, only four studies were eligible for inclusion in the NMA, which restricts the strength and generalisability of the comparative intervention estimates. While the NMA results were supported by the broader narrative synthesis, they should be interpreted with caution given the limited, sparsely connected evidence network. Additionally, most studies had relatively short follow‐up periods, limiting the ability to draw conclusions about sustained recovery, relapse, linear growth, and long‐term developmental outcomes. A further 18 studies were excluded from the interpretative synthesis due to a high risk of bias and inconsistent reporting of micronutrient outcomes, with only a few including biomarker data. These limitations emphasise the need for more standardised outcome reporting and longer‐term assessments of community‐based nutrition interventions in SSA.

4.2. Implications for Programmes, Policy, and Research

Community‐based nutrition interventions, particularly therapeutic feeding interventions such as LNS, RUTF, and RUSF, were most consistently associated with improvements in weight gain, MUAC, and recovery among children aged 6–59 months in SSA. Interventions should prioritise implementation fidelity, caregiver adherence, and strong CHW support to improve effectiveness. Several studies also suggest that integrating nutrition‐sensitive approaches, including WASH and cash‐transfer interventions, may enhance recovery outcomes by addressing the underlying determinants of undernutrition. While the NMA suggested a potential short‐term advantage of LNS over CSB and controls, these findings were based on only four studies and should be interpreted with caution. Finally, future research should prioritise longer‐term follow‐up, standardised outcome measures, and improved reporting of micronutrient and recovery outcomes to strengthen the evidence base for community‐based nutrition interventions in SSA.

5. Conclusion

This systematic review provides updated, SSA‐specific evidence that community‐based nutrition interventions can improve outcomes for undernourished children aged 6–59 months. Across the narratively synthesised studies, therapeutic feeding interventions, particularly LNS, RUTF, RUSF, and other energy‐dense formulations, were most consistently associated with improvements in weight gain, MUAC, and recovery, whereas effects on linear growth were generally limited. An NMA of four comparable studies suggests that LNS may yield greater short‐term anthropometric gains than CSB and no‐treatment controls. However, the limited size and density of the evidence network constrain the certainty and generalisability of these comparable findings. Consequently, the NMA results should be interpreted as limited evidence of comparable effectiveness. Overall, the evidence highlights the value of community‐based therapeutic feeding interventions and suggests that integrating them with nutrition‐sensitive strategies, such as WASH and cash transfer programmes, may further enhance recovery outcomes. Therefore, future studies should prioritise standardised outcome measures, improved reporting of micronutrient indicators, and longer‐term follow‐up to assess sustained recovery, relapse, and growth trajectories in diverse SSA settings.

Author Contributions

All authors meet the criteria for authorship. F.P.R. contributed to the conception and design of the work and to all processes and activities involved in the review, including drafting the final manuscript. M.A.J. contributed to the conception and design of the work, full‐text screening, data extraction checking, data interpretation, methodological quality and risk‐of‐bias assessment, and critical revision of the final manuscript. K.M.R. contributed to the conception and design of the work, full‐text screening, data extraction checking, data interpretation, and critical revision of the final manuscript. A.A.M. contributed to the conception and design of the work, data interpretation, and critical revision of the final manuscript. K.M. contributed to the conception and design of the work, title and abstract screening, data extraction checking, data interpretation, and critical revision of the final manuscript. All authors have read and approved the final manuscript and this submission.

Funding

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting File

MCN-22-e70252-s001.docx (7.1MB, docx)

Acknowledgements

We express our sincere gratitude to Sarah Bateup, Emmy Peterson (librarians), and Justin Clark (Research Enhancement Manager) from the Faculty of Health Sciences and Medicine at Bond University, Gold Coast, Queensland, Australia, for their invaluable assistance in developing the search strategy.

Data Availability Statement

The data that support the findings of this study are openly available within the article and its Supporting Information files.

References

  1. Ackatia‐Armah, R. S. , McDonald C. M., Doumbia S., Erhardt J. G., Hamer D. H., and Brown K. H.. 2015. “Malian Children With Moderate Acute Malnutrition who Are Treated With Lipid‐Based Dietary Supplements Have Greater Weight Gains and Recovery Rates Than Those Treated With Locally Produced Cereal‐Legume Products: A Community‐Based, Cluster‐Randomized Trial.” American Journal of Clinical Nutrition 101, no. 3: 632–645. 10.3945/ajcn.113.069807. [DOI] [PubMed] [Google Scholar]
  2. Adu‐Afarwuah, S. , Lartey A., Okronipa H., et al. 2015. “Lipid‐Based Nutrient Supplement Increases the Birth Size of Infants of Primiparous Women in Ghana.” American Journal of Clinical Nutrition 101, no. 4: 835–846. 10.3945/ajcn.114.091546. [DOI] [PubMed] [Google Scholar]
  3. Akter, S. , Siriphon A., Ayuttacorn A., and Boonchieng W.. 2026. “Prevalence and Determinants of Undernutrition Among Children Under Five in Coastal Bangladesh: A Community‐Based Study.” Food Science & Nutrition 14, no. 2: e71573. 10.1002/fsn3.71573. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Altmann, M. , Altare C., van der Spek N., et al. 2018. “Effectiveness of a Household Water, Sanitation and Hygiene Package on an Outpatient Program for Severe Acute Malnutrition: A Pragmatic Cluster‐Randomized Controlled Trial in Chad.” American Journal of Tropical Medicine and Hygiene 98, no. 4: 1005–1012. 10.4269/ajtmh.17-0699. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Arndt, M. B. , Abate Y. H., Abbasi‐Kangevari M., et al. 2024. “Global, Regional, and National Progress Towards the 2030 Global Nutrition Targets and Forecasts to 2050: a Systematic Analysis for the Global Burden of Disease Study 2021.” Lancet 404, no. 10471: 2543–2583. 10.1016/S0140-6736(24)01821-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Bahwere, P. , Balaluka B., Wells J. C., et al. 2016. “Cereals and Pulse‐Based Ready‐to‐Use Therapeutic Food as an Alternative to the Standard Milk‐ and Peanut Paste‐Based Formulation for Treating Severe Acute Malnutrition: A Noninferiority, Individually Randomized Controlled Efficacy Clinical Trial.” American Journal of Clinical Nutrition 103, no. 4: 1145–1161. 10.3945/ajcn.115.119537. [DOI] [PubMed] [Google Scholar]
  7. Bahwere, P. , Banda T., Sadler K., et al. 2014. “Effectiveness of Milk Whey Protein‐Based Ready‐to‐Use Therapeutic Food in Treatment of Severe Acute Malnutrition in Malawian Under‐5 Children: A Randomised, Double‐Blind, Controlled Non‐Inferiority Clinical Trial.” Maternal & Child Nutrition 10, no. 3: 436–451. 10.1111/mcn.12112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bain, L. E. , Awah P. K., Geraldine N., et al. 2013. “Malnutrition in Sub‐Saharan Africa: Burden, Causes and Prospects.” Pan African Medical Journal 15: 120. 10.11604/pamj.2013.15.120.2535. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Balduzzi, S. , Rücker G., Nikolakopoulou A., et al. 2023. “Netmeta: An R Package for Network Meta‐Analysis Using Frequentist Methods.” Journal of Statistical Software 106, no. 2: 1–40. 10.18637/jss.v106.i02. [DOI] [Google Scholar]
  10. Baye, K. , Hussein A., Angood C., et al. 2025. “Effectiveness of the Community Management of Acute Malnutrition in 16 Eastern and Southern African Countries.” Nutrition 139: 112852. 10.1016/j.nut.2025.112852. [DOI] [PubMed] [Google Scholar]
  11. Bhutta, Z. A. , Das J. K., Rizvi A., et al. 2013. “Evidence‐Based Interventions for Improvement of Maternal and Child Nutrition: What can be Done and at What Cost?” Lancet 382, no. 9890: 452–477. 10.1016/s0140-6736(13)60996-4. [DOI] [PubMed] [Google Scholar]
  12. Brignardello‐Petersen, R. , Bonner A., Alexander P. E., et al. 2018. “Advances in the GRADE Approach to Rate the Certainty in Estimates From a Network Meta‐Analysis.” Journal of Clinical Epidemiology 93: 36–44. 10.1016/j.jclinepi.2017.10.005. [DOI] [PubMed] [Google Scholar]
  13. Budge, S. , Parker A. H., Hutchings P. T., and Garbutt C.. 2019. “Environmental Enteric Dysfunction and Child Stunting.” Nutrition Reviews 77, no. 4: 240–253. 10.1093/nutrit/nuy068. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Das, J. K. , Salam R. A., Saeed M., Kazmi F. A., and Bhutta Z. A.. 2020. “Effectiveness of Interventions to Manage Acute Malnutrition in Children Under 5 Years of Age in Low‐ and Middle‐Income Countries: A Systematic Review.” Campbell Systematic Review 16, no. 2: e1082‐n/a. 10.1002/cl2.1082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Dewey, K. G. , and Adu‐Afarwuah S.. 2008. “Systematic Review of the Efficacy and Effectiveness of Complementary Feeding Interventions in Developing Countries.” Supplement, Maternal & Child Nutrition 4, no. Suppl 1: 24–85. 10.1111/j.1740-8709.2007.00124.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Donnen, P. , Brasseur D., Dramaix M., et al. 1998. “Vitamin A Supplementation but Not Deworming Improves Growth of Malnourished Preschool Children in Eastern Zaire.” Journal of Nutrition 128, no. 8: 1320–1327. 10.1093/jn/128.8.1320. [DOI] [PubMed] [Google Scholar]
  17. Dossa, R. , Ategbo E., De Koning F., Van Raaij J., and Hautvast J.. 2001. “Impact of Iron Supplementation and Deworming on Growth Performance in Preschool Beninese Children.” European Journal of Clinical Nutrition 55, no. 4: 223–228. 10.1038/sj.ejcn.1601126. [DOI] [PubMed] [Google Scholar]
  18. Escher, N. A. , Andrade G. C., Ghosh‐Jerath S., Millett C., and Seferidi P.. 2024. “The Effect of Nutrition‐Specific and Nutrition‐Sensitive Interventions on the Double Burden of Malnutrition in Low‐Income and Middle‐Income Countries: A Systematic Review.” Lancet Global Health 12, no. 3: e419–e432. 10.1016/S2214-109X(23)00562-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Fabiansen, C. , Yaméogo C. W., Iuel‐Brockdorf A.‐S., et al. 2017. “Effectiveness of Food Supplements in Increasing Fat‐Free Tissue Accretion in Children With Moderate Acute Malnutrition: A Randomised 2 × 2 × 3 Factorial Trial in Burkina Faso.” PLoS Medicine 14, no. 9: e1002387. 10.1371/journal.pmed.1002387. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Gera, T. , Pena‐Rosas J. P., Boy‐Mena E., and Sachdev H. S.. 2017. “Lipid Based Nutrient Supplements (LNS) for Treatment of Children (6 Months to 59 Months) With Moderate Acute Malnutrition (Mam): A Systematic Review.” PLoS One 12, no. 9: e0182096. 10.1371/journal.pone.0182096. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Ghodsi, D. , Omidvar N., Nikooyeh B., Roustaee R., Shakibazadeh E., and Al‐Jawaldeh A.. 2021. “Effectiveness of Community Nutrition‐Specific Interventions on Improving Malnutrition of Children under 5 Years of Age in the Eastern Mediterranean Region: A Systematic Review and Meta‐Analysis.” International Journal of Environmental Research and Public Health 18, no. 15: 7844. 10.3390/ijerph18157844. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Glatthaar, I. I. , Fehrsen G. S., Irwig L. M., and Reinach S. G.. 1986. “Protein‐Energy Malnutrition: The Role of Nutrition Education in Rehabilitation.” Human nutrition, Clinical nutrition 40C, no. 4: 271–285. [PubMed] [Google Scholar]
  23. Grellety, E. , Babakazo P., Bangana A., et al. 2017. “Effects of Unconditional Cash Transfers on the Outcome of Treatment for Severe Acute Malnutrition (SAM): A Cluster‐Randomised Trial in the Democratic Republic of the Congo.” BMC Medicine 15, no. 1: 87. 10.1186/s12916-017-0848-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Griswold, S. P. , Langlois B. K., Shen Y., et al. 2021. “Effectiveness and Cost‐Effectiveness of 4 Supplementary Foods for Treating Moderate Acute Malnutrition: Results From a Cluster‐Randomized Intervention Trial in Sierra Leone.” American Journal of Clinical Nutrition 114, no. 3: 973–985. 10.1093/ajcn/nqab140. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Hendrixson, D. T. , Godbout C., Los A., et al. 2020. “Treatment of Severe Acute Malnutrition With Oat or Standard Ready‐to‐Use Therapeutic Food: A Triple‐Blind, Randomised Controlled Clinical Trial.” Gut 69, no. 12: 2143–2149. 10.1136/gutjnl-2020-320769. [DOI] [PubMed] [Google Scholar]
  26. Higgins, J. P. T. , Thomas, J. , Chandler, J. , et al., ed. 2019. Cochrane Handbook for Systematic Reviews of Interventions, 2 ed.). John Wiley & Sons, Incorporated. 10.1002/9781119536604. [DOI] [Google Scholar]
  27. Hoffmann, T. C. , Glasziou P. P., Boutron I., et al. 2014. “Better Reporting of Interventions: Template for Intervention Description and Replication (TiDieR) Checklist and Guide.” BMJ (London) 348: g1687. 10.1136/bmj.g1687. [DOI] [PubMed] [Google Scholar]
  28. Huybregts, L. , Houngbé F., Salpéteur C., et al. 2012. “The Effect of Adding Ready‐to‐Use Supplementary Food to a General Food Distribution on Child Nutritional Status and Morbidity: A Cluster‐Randomized Controlled Trial.” PLoS Medicine 9, no. 9: e1001313. 10.1371/journal.pmed.1001313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Isanaka, S. , Langendorf C., Berthé F., et al. 2016. “Routine Amoxicillin for Uncomplicated Severe Acute Malnutrition in Children.” New England journal of medicine 374, no. 5: 444–453. 10.1056/NEJMoa1507024. [DOI] [PubMed] [Google Scholar]
  30. Kangas, S. T. , Salpéteur C., Nikièma V., et al. 2019. “Impact of Reduced Dose of Ready‐to‐Use Therapeutic Foods in Children with Uncomplicated Severe Acute Malnutrition: A Randomised Non‐Inferiority Trial in Burkina Faso.” PLoS medicine 16, no. 8: e1002887. 10.1371/journal.pmed.1002887. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. LaGrone, L. N. , Trehan I., Meuli G. J., et al. 2012. “A Novel Fortified Blended Flour, Corn‐Soy Blend ‘Plus‐Plus,’ Is Not Inferior to Lipid‐Based Ready‐to‐Use Supplementary Foods for the Treatment of Moderate Acute Malnutrition in Malawian Children.” American Journal of Clinical Nutrition 95, no. 1: 212–219. 10.3945/ajcn.111.022525. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Lassi, Z. S. , Das J. K., Zahid G., Imdad A., and Bhutta Z. A.. 2013. “Impact of Education and Provision of Complementary Feeding on Growth and Morbidity in Children Less Than 2 Years of Age in Developing Countries: A Systematic Review.” BMC Public Health 13 Suppl 3, no. Suppl 3: S13. 10.1186/1471-2458-13-s3-s13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Maleta, K. , Kuittinen J., Duggan M. B., et al. 2004. “Supplementary Feeding of Underweight, Stunted Malawian Children With a Ready‐To‐Use Food.” Journal of Pediatric Gastroenterology and Nutrition 38, no. 2: 152–158. 10.1002/j.1536-4801.2004.tb12134.x. [DOI] [PubMed] [Google Scholar]
  34. Maru, Y. , Tamiru D., Baye K., et al. 2024. “Effect of a Simplified Approach on Recovery of Children 6–59 Months with Wasting in Ethiopia: A Noninferiority, Cluster Randomized Controlled Trial.” Maternal and child nutrition 20, no. 4: e13670. 10.1111/mcn.13670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Marume, A. , Kasanzu S., and Chirenda J.. 2025. “Socio‐Economic and Rural‐Urban Disparities in the Double Burden of Childhood Malnutrition in Sub‐Saharan Africa.” Journal of Health, Population, and Nutrition 44, no. 1: 335. 10.1186/s41043-025-01075-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Matilsky, D. K. , Maleta K., Castleman T., and Manary M. J.. 2009. “Supplementary Feeding With Fortified Spreads Results in Higher Recovery Rates Than With a Corn/Soy Blend in Moderately Wasted Children.” Journal of Nutrition 139, no. 4: 773–778. 10.3945/jn.108.104018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Mbabazi, J. , Pesu H., Mutumba R., et al. 2023. “Effect of Milk Protein and Whey Permeate in Large Quantity Lipid‐Based Nutrient Supplement on Linear Growth and Body Composition Among Stunted Children: A Randomized 2 × 2 Factorial Trial in Uganda.” PLoS Medicine 20, no. 5: e1004227. 10.1371/journal.pmed.1004227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. McGuinness, L. A. , and Higgins J. P. T.. 2021. “Risk‐of‐Bias Visualization (Robvis): An R Package and Shiny Web App for Visualizing Risk‐of‐Bias Assessments.” Research Synthesis Methods 12, no. 1: 55–61. 10.1002/jrsm.1411. [DOI] [PubMed] [Google Scholar]
  39. Medoua, G. N. , Ntsama P. M., Ndzana A. C. A., Essa'a V. J., Tsafack J. J. T., and Dimodi H. T.. 2016. “Recovery Rate of Children With Moderate Acute Malnutrition Treated With Ready‐to‐Use Supplementary Food (RUSF) or Improved Corn–Soya Blend (CSB+): a Randomized Controlled Trial.” Public Health Nutrition 19, no. 2: 363–370. 10.1017/S1368980015001238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Mukeshimana, M. , Ntakirutimana T., Ishimwe Bazakare M. L., and Krantz G.. 2025. “Factors Contributing to the Persistence of Undernutrition Among Children Under 5 Years of Age in Rwanda: A Community Participatory Qualitative Study.” Global Health Action 18, no. 1: 2581454. 10.1080/16549716.2025.2581454. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Nane, D. , Hatløy A., Lindtjørn B., and Vall‐llosera Camps M.. 2021. “A Local‐Ingredients‐Based Supplement is an Alternative to Corn‐Soy Blends Plus for Treating Moderate Acute Malnutrition Among Children Aged 6 to 59 Months: A Randomized Controlled Non‐Inferiority Trial in Wolaita, Southern Ethiopia.” PloS one 16, no. 10: e0258715. 10.1371/journal.pone.0258715. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Njeru, R. W. , Uddin M. F., Zakayo S. M., et al. 2021. “Strengthening the Role of Community Health Workers in Supporting the Recovery of Ill, Undernourished Children Post Hospital Discharge: Qualitative Insights From Key Stakeholders in Bangladesh and Kenya.” BMC Health Services Research 21, no. 1: 1234. 10.1186/s12913-021-07209-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. O'Brien, K. S. , Sié A., Dah C., et al. 2022. “Comparing Azithromycin to Amoxicillin in the Management of Uncomplicated Severe Acute Malnutrition in Burkina Faso: A Pilot Randomized Trial.” American journal of tropical medicine and hygiene 106, no. 3: 930–938. 10.4269/ajtmh.21-1023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Oakley, E. , Reinking J., Sandige H., et al. 2010. “A Ready‐To‐Use Therapeutic Food Containing 10% Milk Is Less Effective Than One With 25% Milk in the Treatment of Severely Malnourished Children.” Journal of Nutrition 140, no. 12: 2248–2252. 10.3945/jn.110.123828. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Othoo, D. A. , Ochola S., Kuria E., and Kimiywe J.. 2021. “Impact of Spirulina Corn Soy Blend on Iron Deficient Children Aged 6‐23 Months in Ndhiwa Sub‐County Kenya: A Randomized Controlled Trial.” BMC Nutrition 7, no. 1: 70. 10.1186/s40795-021-00472-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Owen, R. K. , Bradbury N., Xin Y., Cooper N., and Sutton A.. 2019. “Metainsight: An Interactive Web‐Based Tool for Analyzing, Interrogating, and Visualizing Network Meta‐Analyses Using R‐Shiny and Netmeta.” Research Synthesis Methods 10, no. 4: 569–581. 10.1002/jrsm.1373. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Page, M. J. , McKenzie J. E., Bossuyt P. M., et al. 2021. “Updating Guidance for Reporting Systematic Reviews: Development of the PRISMA 2020 Statement.” Journal of Clinical Epidemiology 134: 103–112. 10.1016/j.jclinepi.2021.02.003. [DOI] [PubMed] [Google Scholar]
  48. Phuka, J. , Thakwalakwa C., Maleta K., et al. 2009. “Supplementary Feeding With Fortified Spread Among Moderately Underweight 6‐18‐month‐old Rural Malawian Children.” Maternal & Child Nutrition 5, no. 2: 159–170. 10.1111/j.1740-8709.2008.00162.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Riwa, F. P. , Odgers‐Jewell K., Jones M. A., and Mushi A. A.. 2025. “The Prevalence and Determinants of Undernutrition Among Infants and Children Aged 6 Months to 5 Years in Sub‐Saharan African Countries: A Systematic Scoping Review.” Nutrition Reviews 83: e1896–e1916. 10.1093/nutrit/nuae189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Roediger, R. , Stein H. H., Callaghan‐Gillespie M., et al. 2020. “Protein Quality in Ready‐to‐Use Supplementary Foods for Moderate Wasting.” Maternal and child nutrition 16, no. 4: e13019. 10.1111/mcn.13019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Ruel, M. T. , Alderman H., and Maternal and Child Nutrition Study G.. 2013. “Nutrition‐Sensitive Interventions and Programmes: How can They Help to Accelerate Progress in Improving Maternal and Child Nutrition?” Lancet (London, England) 382, no. 9891: 536–551. 10.1016/S0140-6736(13)60843-0. [DOI] [PubMed] [Google Scholar]
  52. Stephenson, K. , Callaghan‐Gillespie M., Maleta K., et al. 2022. “Low Linoleic Acid Foods With Added DHA Given to Malawian Children With Severe Acute Malnutrition Improve Cognition: A Randomized, Triple‐Blinded, Controlled Clinical Trial.” American Journal of Clinical Nutrition 115, no. 5: 1322–1333. 10.1093/ajcn/nqab363. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Stewart, C. P. , Caswell B., Iannotti L., et al. 2019. “The Effect of Eggs on Early Child Growth in Rural Malawi: The Mazira Project Randomized Controlled Trial.” American Journal of Clinical Nutrition 110, no. 4: 1026–1033. 10.1093/ajcn/nqz163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Stobaugh, H. C. , Ryan K. N., Kennedy J. A., et al. 2016. “Including Whey Protein and Whey Permeate in Ready‐to‐Use Supplementary Food Improves Recovery Rates in Children With Moderate Acute Malnutrition: A Randomized, Double‐Blind Clinical Trial.” American Journal of Clinical Nutrition 103, no. 3: 926–933. 10.3945/ajcn.115.124636. [DOI] [PubMed] [Google Scholar]
  55. Thakwalakwa, C. M. , Ashorn P., Jawati M., Phuka J. C., Cheung Y. B., and Maleta K. M.. 2012. “An Effectiveness Trial Showed Lipid‐Based Nutrient Supplementation but Not Corn–Soya Blend Offered a Modest Benefit in Weight Gain Among 6‐ to 18‐month‐old Underweight Children in Rural Malawi.” Public Health Nutrition 15, no. 9: 1755–1762. 10.1017/S1368980012003023. [DOI] [PubMed] [Google Scholar]
  56. Thakwalakwa, C. , Ashorn P., Phuka J., et al. 2010. “A Lipid‐Based Nutrient Supplement but Not Corn‐Soy Blend Modestly Increases Weight Gain Among 6‐ to 18‐Month‐Old Moderately Underweight Children in Rural Malawi.” Journal of Nutrition 140, no. 11: 2008–2013. 10.3945/jn.110.122499. [DOI] [PubMed] [Google Scholar]
  57. The EndNote Team . 2013. EndNote. Clarivate. https://endnote.com/. [Google Scholar]
  58. United Nations Children's Fund. 2023 . The World Health Organisation, & The International Bank for Reconstruction and Development/The World Bank (2023). Levels and trends in Child Malnutrition: UNICEF/WHO/World Bank Group Joint Child Malnutrition Estimates (Key Findings of the 2023 Edition, Issue. https://www.who.int/publications/i/item/9789240073791.
  59. Veritas Health Innovation . 2021. Covidence Systematic Review Software. Veritas Health Innovation. https://www.covidence.org/. [Google Scholar]
  60. Vray, M. , Tondeur L., Hedible B. G., et al. 2024. “Three‐Arm Clinical Trial of Improved Flour Targeting Intestinal Microbiota (MALINEA).” Maternal and child nutrition 20, no. 3: e13649. 10.1111/mcn.13649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. World Bank Group . 2022. Sub‐Saharan Africa (IFC Classification). Retrieved 24 November From. http://data.worldbank.org/country/C9.
  62. World Health Organisation (WHO) . 2023. “WHO Guidelines Approved by the Guidelines Review Committee.” In WHO Guideline on the Prevention and Management of Wasting and Nutritional Oedema (Acute Malnutrition) in Infants and Children Under 5 Years. World Health Organization © World Health Organization 2023. [PubMed] [Google Scholar]
  63. World Health Organisation . 2025. Global Nutrition Targets 2030: Breastfeeding Brief. https://iris.who.int/handle/10665/383126.

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