Evidence map›Paper›PMID 42468956›Full record

ArticleBMJ open2026

Local innovations and systemic barriers in stunting reduction: a qualitative analysis of food and social assistance programmes in Indonesia.

Anissa Rizkianti, Juariah Juariah, Laili Rahayuwati, Mira Trisyani, Desy Nuri Fajarningtiyas, Andhika Ajie Baskoro

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Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Anissa RizkiantiResearch Centre for Population, National Research and Innovation Agency Republic of Indonesia, South Jakarta, Indonesia anis025@brin.go.id.ORCID http://orcid.org/0000-0002-1255-5199
Juariah JuariahDivision of Social and Population, Regional Research and Development Agency of West Java, Bandung, Indonesia.
Laili RahayuwatiFaculty of Nursing, Universitas Padjadjaran, Sumedang, Indonesia.
Mira TrisyaniFaculty of Nursing, Universitas Padjadjaran, Sumedang, Indonesia.
Desy Nuri FajarningtiyasResearch Centre for Population, National Research and Innovation Agency Republic of Indonesia, South Jakarta, Indonesia.ORCID http://orcid.org/0000-0003-3757-6858
Andhika Ajie BaskoroResearch Centre for Population, National Research and Innovation Agency Republic of Indonesia, South Jakarta, Indonesia.ORCID http://orcid.org/0000-0003-4865-2449

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionReducing stunting remains a pressing global challenge, particularly in low and middle-income countries (LMICs), where nutrition insecurity and limited access to health services persist. With its large-scale national social assistance and health programmes, Indonesia offers valuable insights into implementing integrated strategies for stunting prevention. This study examines the substantive elements of food and social assistance interventions as well as the contextual and structural factors that influence their implementation. It also assesses how multisectoral collaboration contributes to the implementation process of nutrition-specific efforts aimed at reducing stunting.

methodsWe conducted a qualitative case study in two districts of West Java Province, representing contrasting urban and rural contexts. Data were collected through 78 in-depth interviews with policymakers, implementers and primary beneficiaries. The policy implementation framework developed by Edward was used as a guide for the thematic analysis.

resultsWe identified key factors influencing programme delivery, including communication, resource availability, commitment of implementers and bureaucratic structure. Urban settings demonstrated better outreach, service utilisation and intersectoral coordination while rural areas faced logistical and administrative barriers. Innovative local practices, such as digital health monitoring and women's farmer groups helped bridge implementation gaps. However, structural constraints, such as inflexible eligibility criteria, poor data integration and fiscal dependency on the central government, limited the programme's reach.

conclusionIndonesia's experience demonstrates that effective stunting reduction requires national policy frameworks and locally adapted, multisectoral approaches that address system-level barriers. The practical lessons from this study can empower LMICs aiming to scale up integrated nutrition, health and social protection programmes, equipping them with the necessary knowledge and insights.

Indexed as

Food AssistanceGrowth DisordersPublic AssistanceFood SupplyHealth Services AccessibilityHumansIndonesiaQualitative ResearchRural PopulationHealth policyHealth Services AccessibilityNutritionPUBLIC HEALTH

Identifiers

PMID42468956
PMCPMC13384135

What OpenQuestion holds

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.