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Dynamic Model of Stunting Incidents and Policies in Padang City

Media Kesehatan Masyarakat Indonesia · Vol. 21 No. 2 (2025) · pp. 180–191

DOI
10.30597/mkmi.v21i2.44902
ISSN
2356-4067, 0216-2482
Published
2025-06-30
Publisher
Faculty of Public Health, Hasanuddin University, Makassar
Language
en
License
creativecommons.org/licenses/by-nc-sa/4.0/

Abstract

Stunting remains a significant public health challenge with complex, interconnected causative factors. Traditional static approaches fail to capture the dynamic relationships between environmental, health, and socioeconomic determinants. Dynamic modeling is essential for understanding these multifaceted interactions and developing effective prevention policies. Despite declining trends, Padang City's high prevalance of stunting necessitates urgent, targeted interventions to achieve national targets. This study aims to develop a dynamic model analyzing stunting factors in Padang City and formulate effective prevention policies. A quantitative descriptive method with a dynamic systems approach was employed. Primary data were obtained through stakeholder questionnaires, while secondary data were obtained from the Padang City Health Office and Statistical Reports (2018-2023). Analysis utilized PowerSim Studio 10 for dynamic systems modeling and Interpretative Structural Modeling (ISM) for policy strategy development. Seven main factors influencing stunting were identified: low birth weight, maternal health, immunization, diarrhea, living in slum areas, access to clean water access, and household sanitation. Simulation modeling demonstrated that improving environmental conditions, increasing immunization coverage, and administering iron tablets could reduce stunting rates by 50% over 25 years. ISM analysis revealed environmental factors (sanitation, waste management, and access clean water) as key elements with the highest driving force. Consistent immunization coverage could reduce stunting prevalence from 24.2% to 12% within the projection period, while improved sanitation programs may lower prevalence by 15%. The research provides an integrated approach prioritizing basic infrastructure improvement, environmental sanitation enhancement, cross-sector coordination, and community capacity building. This dynamic modeling framework offers valuable insights for comprehensive stunting prevention strategies. However, limitations include a modeling-only scope requiring field validation for implementation effectiveness.

Keywords

Collaboration network of the authors

40 authors · 121 co-authorship links · 8 across different organisations · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Negeri Padang
  • Queen Mary University of London
  • Hasanuddin University
  • Poltekkes Kemenkes Padang
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Indang DewataAffiliation unknown6
Eri BarlianUniversitas Negeri Padang4
Linda HandayuniAffiliation unknown3
Abdul RazakUniversitas Negeri Padang2
Defriani DwiyantiAffiliation unknown2
Dian Adhetya ArifUniversitas Negeri Padang2
Nia KurniawanAffiliation unknown2
Andri MaulidiAffiliation unknown2
Midratul FardillaUniversitas Negeri Padang1
Hafida IstigfariniUniversitas Negeri Padang1
Neviyarni NeviyarniAffiliation unknown1
Mahalul AzamAffiliation unknown1
Alfitri AlfitriAffiliation unknown1
Netrawati NetrawatiAffiliation unknown1
Rihaliza RihalizaAffiliation unknown1
Firman FirmanHasanuddin University1
Muchsin RiviwantoAffiliation unknown1
Abdi Iswahyudi YasrilAffiliation unknown1
Muhyiatul FadilahAffiliation unknown1
Helendra HelendraAffiliation unknown1
Indra MyraldiAffiliation unknown1
Ristiono RistionoAffiliation unknown1
Rahmawati RarussyamsuAffiliation unknown1
Marlina MarlinaAffiliation unknown1
Yori Zela ZelikaAffiliation unknown1
Rapitos SidiqPoltekkes Kemenkes Padang1
Neni Fitra HayatiAffiliation unknown1
Nur EfendiAffiliation unknown1
Nur Hasan SyahAffiliation unknown1
Ahmad Muammar KadafiAffiliation unknown1
Fajar KaprawiAffiliation unknown1
Rijal SatriaAffiliation unknown1
Ade Prasetyo AgungAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/mkmi/oai, first harvested 5 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Dynamic Model of Stunting Incidents and Policies in Padang City</dc:title>
	<dc:creator xml:lang="en">Yuniarti, Elsa</dc:creator>
	<dc:creator xml:lang="en">Yulhendri, Yulhendri</dc:creator>
	<dc:creator xml:lang="en">Nugraha, Fitra Arya Dwi</dc:creator>
	<dc:creator xml:lang="en">Syah, Nurhasan</dc:creator>
	<dc:creator xml:lang="en">Umar, Iswandi</dc:creator>
	<dc:creator xml:lang="en">Heldi, Heldi</dc:creator>
	<dc:creator xml:lang="en">Azzahra, Nabila</dc:creator>
	<dc:subject xml:lang="en">Stunting</dc:subject>
	<dc:subject xml:lang="en">Dynamic Model</dc:subject>
	<dc:subject xml:lang="en">Policy</dc:subject>
	<dc:description xml:lang="en">Stunting remains a significant public health challenge with complex, interconnected causative factors. Traditional static approaches fail to capture the dynamic relationships between environmental, health, and socioeconomic determinants. Dynamic modeling is essential for understanding these multifaceted interactions and developing effective prevention policies. Despite declining trends, Padang City's high prevalance of stunting necessitates urgent, targeted interventions to achieve national targets. This study aims to develop a dynamic model analyzing stunting factors in Padang City and formulate effective prevention policies. A quantitative descriptive method with a dynamic systems approach was employed. Primary data were obtained through stakeholder questionnaires, while secondary data were obtained from the Padang City Health Office and Statistical Reports (2018-2023). Analysis utilized PowerSim Studio 10 for dynamic systems modeling and Interpretative Structural Modeling (ISM) for policy strategy development. Seven main factors influencing stunting were identified: low birth weight, maternal health, immunization, diarrhea, living in slum areas, access to clean water access, and household sanitation. Simulation modeling demonstrated that improving environmental conditions, increasing immunization coverage, and administering iron tablets could reduce stunting rates by 50% over 25 years. ISM analysis revealed environmental factors (sanitation, waste management, and access clean water) as key elements with the highest driving force. Consistent immunization coverage could reduce stunting prevalence from 24.2% to 12% within the projection period, while improved sanitation programs may lower prevalence by 15%. The research provides an integrated approach prioritizing basic infrastructure improvement, environmental sanitation enhancement, cross-sector coordination, and community capacity building. This dynamic modeling framework offers valuable insights for comprehensive stunting prevention strategies. However, limitations include a modeling-only scope requiring field validation for implementation effectiveness.</dc:description>
	<dc:publisher xml:lang="en">Faculty of Public Health, Hasanuddin University, Makassar</dc:publisher>
	<dc:date>2025-06-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/mkmi/article/view/44902</dc:identifier>
	<dc:identifier>10.30597/mkmi.v21i2.44902</dc:identifier>
	<dc:source xml:lang="en">Media Kesehatan Masyarakat Indonesia; Vol. 21 No. 2: JUNE 2025; 180-191</dc:source>
	<dc:source>2356-4067</dc:source>
	<dc:source>0216-2482</dc:source>
	<dc:source>10.30597/mkmi.v21i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/mkmi/article/view/44902/13592</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 by author</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by-nc-sa/4.0/</dc:rights>
</oai_dc:dc>