Spatial Analysis of Stunting Prevalence According to Family Data Collection Indicators in Indonesia

Yuli Puspita Devi; Milla Herdayati; Martya Rahmaniati Makful; Muthmainnah Muthmainnah; Mario Ekoriano; Nurvita Ruwandasari; Kholifatul Mardiah

doi:10.56338/mppki.v8i3.6931

Yuli Puspita Devi Department of Epidemiology, Biostatistics, Population Studies and Health Promotion, Faculty of Public Health, Universitas Airlangga, Jawa Timur, Indonesia
Milla Herdayati Department of Population Studies and Biostatistics, Faculty of Public Health, Universitas Indonesia, Depok, West Java, Indonesia
Martya Rahmaniati Makful Department of Population Studies and Biostatistics, Faculty of Public Health, Universitas Indonesia, Depok, West Java, Indonesia
Muthmainnah Muthmainnah Department of Epidemiology, Biostatistics, Population Studies and Health Promotion, Faculty of Public Health, Universitas Airlangga, Jawa Timur, Indonesia
Mario Ekoriano National Research and Innovation Agency (BRIN), Jakarta Pusat, Indonesia
Nurvita Ruwandasari Primary Health Care of Karangandong, Gresik, East Java, Indonesia
Kholifatul Mardiah Department of Epidemiology, Biostatistics, Population Studies and Health Promotion, Faculty of Public Health, Universitas Airlangga, Surabaya, East Java, Indonesia

DOI: https://doi.org/10.56338/mppki.v8i3.6931

Keywords: Child Health, Stunting, Spatial Analysis, Family Data Collection, Spatial Error Model

Abstract

Introduction: Stunting is malnutrition in children that reduces productivity and susceptibility to degenerative diseases. In 2021, West Java Province recorded the highest stunting prevalence on Java Island. We analyzed the distribution and risk factors for the prevalence of stunting in the West Java Province by considering spatial effects.

Methods: This study was ecologically designed using a spatial approach. Data were obtained from Studi Status Gizi Indonesia/Indonesian Nutritional Status Study and Pendataan Keluarga/Family Data Collection, which will be released in 2021 especially in West Java. Data analysis was conducted using a spatial error model (SEM) in GeoDa, and stunting prevalence mapping was performed using QGIS (Quantum geographic information system) 2.1.8 version.

Results: No spatial correlation was identified for stunting prevalence in West Java Province in 2021. However, a spatial correlation was observed in the residual value of the determinants of stunting prevalence. SEM analysis showed that the proportion of low-income families, inadequate drinking water sources, unmet needs, inactive Bina Keluarga Balita/Toddler Family Development, unwanted pregnancies, family planning, and limited access to internet-based information had a significant effect on stunting prevalence.

Conclusion: This study provides suggestions for increased focus on addressing environmental problems in rural areas and overcoming poverty in all districts/cities in West Java Province which was the province with the highest number of population.

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