TY - JOUR
T1 - Spatial Analysis of Seven Islands in Indonesia to Determine Stunting Hotspots
AU - Sipahutar, Tiopan
AU - Eryando, Tris
AU - Budhiharsana, Meiwita Paulina
N1 - Funding Information:
The authors are grateful to Universitas Indonesia for supporting this study financially through a scholarship. Financial support for this study and publication was provided by Universitas Indonesia (contract number NKB-612/UN2.RST/HKP.05.00/2020).
Publisher Copyright:
Copyright © 2022, Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal)
PY - 2022/8
Y1 - 2022/8
N2 - Indonesia is a vast country struggling to reduce its stunting prevalence. Hence, identifying priority areas is urgent. In determining areas to prioritize, one needs to consider geographical issues, particularly correlations among areas. This study aimed to discover whether stunting prevalence in Indonesia occurs randomly or in clusters; and, if it occurs in clusters, which areas are the hotspots. This ecological study used aggregate data from the 2018 National Basic Health Research and Poverty Data and Information Report from the Statistics Indonesia. This study analyzed 514 districts/cities across 34 provinces on seven main islands in Indonesia. The method used was the Euclidean distance to define the spatial weight. Moran's index test was used to identify autocorrelation, while a Moran scatter plot was applied to identify stunting hotspots. Autocorrelation was found among districts/cities in Sumatra, Java, Sulawesi, and Bali East Nusa Tenggara West Nusa Tenggara Islands, resulting in 133 districts/cities identified as stunting hotspots on four major islands. Autocorrelation proves that stunting in Indonesia does not occur randomly.
AB - Indonesia is a vast country struggling to reduce its stunting prevalence. Hence, identifying priority areas is urgent. In determining areas to prioritize, one needs to consider geographical issues, particularly correlations among areas. This study aimed to discover whether stunting prevalence in Indonesia occurs randomly or in clusters; and, if it occurs in clusters, which areas are the hotspots. This ecological study used aggregate data from the 2018 National Basic Health Research and Poverty Data and Information Report from the Statistics Indonesia. This study analyzed 514 districts/cities across 34 provinces on seven main islands in Indonesia. The method used was the Euclidean distance to define the spatial weight. Moran's index test was used to identify autocorrelation, while a Moran scatter plot was applied to identify stunting hotspots. Autocorrelation was found among districts/cities in Sumatra, Java, Sulawesi, and Bali East Nusa Tenggara West Nusa Tenggara Islands, resulting in 133 districts/cities identified as stunting hotspots on four major islands. Autocorrelation proves that stunting in Indonesia does not occur randomly.
KW - Indonesia
KW - spatial analysis
KW - stunting
KW - stunting hotspots
UR - http://www.scopus.com/inward/record.url?scp=85140726477&partnerID=8YFLogxK
U2 - 10.21109/kesmas.v17i3.6201
DO - 10.21109/kesmas.v17i3.6201
M3 - Article
AN - SCOPUS:85140726477
SN - 2460-0601
VL - 17
SP - 228
EP - 234
JO - Kesmas: Jurnal Kesehatan Masyarakat Nasional
JF - Kesmas: Jurnal Kesehatan Masyarakat Nasional
IS - 3
ER -
