Childhood stunting in Indonesia: assessing the performance of Bayesian spatial conditional autoregressive models

Stunting continues to be a significant health issue, particularly in developing nations, with Indonesia ranking third in prevalence in Southeast Asia. This research examined the risk of stunting and influencing factors in Indonesia by implementing various Bayesian spatial conditional autoregressive...

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Bibliographic Details
Published in:Geospatial health 2024-10, Vol.19 (2)
Main Authors: Aswi, Aswi, Rahardiantoro, Septian, Kurnia, Anang, Sartono, Bagus, Handayani, Dian, Nurwan, Nurwan, Cramb, Susanna
Format: Article
Language:English
Subjects:
Bayes Theorem
bayesian
Child, Preschool
conditional autoregressive (CAR)
Diet
Female
Growth Disorders - epidemiology
Humans
Indonesia
Indonesia - epidemiology
Infant
Infant, Low Birth Weight
Male
Models, Statistical
Poverty
Prevalence
Risk Factors
Socioeconomic Factors
spatial
Spatial Analysis
Stunting
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Summary:Stunting continues to be a significant health issue, particularly in developing nations, with Indonesia ranking third in prevalence in Southeast Asia. This research examined the risk of stunting and influencing factors in Indonesia by implementing various Bayesian spatial conditional autoregressive (CAR) models that include covariates. A total of 750 models were run, including five different Bayesian spatial CAR models (Besag-York-Mollie (BYM), CAR Leroux and three forms of localised CAR), with 30 covariate combinations and five different hyperprior combinations for each model. The Poisson distribution was employed to model the counts of stunting cases. After a comprehensive evaluation of all model selection criteria utilized, the Bayesian localised CAR model with three covariates were preferred, either allowing up to 2 clusters with a variance hyperprior of inverse-gamma (1, 0.1) or allowing 3 clusters with a variance hyperprior of inverse-gamma (1, 0.01). Poverty and recent low birth weight (LBW) births are significantly associated with an increased risk of stunting, whereas child diet diversity is inversely related to the risk of stunting. Model results indicated that Sulawesi Barat Province has the highest risk of stunting, with DKI Jakarta Province the lowest. These areas with high stunting require interventions to reduce poverty, LBW births and increase child diet diversity.
ISSN:1827-1987
1970-7096
1970-7096
DOI:10.4081/gh.2024.1321