Bayesian Spatial Modelling of Stunting Cases in South Sulawesi Province: Influential Factors and Relative Risk

DOI

10.2991/978-94-6463-332-0_11How to use a DOI?

Keywords

Bayesian approach; Relative Risk; Spatial CAR Localised; Stunting

Abstract

Stunting remains a significant public health issue in Indonesia, and numerous research studies have been conducted to address this problem. In 2021, The Bayesian Spatial Conditional Autoregressive (CAR) Localized model was implemented across all 34 Indonesian provinces, revealing that approximately 56% of these provinces are at high risk of stunting. Furthermore, the Bayesian Spatial CAR Leroux model was employed to simulate the relative risk (RR) of stunting cases in one of Indonesia's provinces, South Sulawesi. The main objectives of this study were to determine the most suitable Bayesian CAR Localized model, estimate the RR of stunting, and identify the factors influencing stunting cases in South Sulawesi Province. Data on the number of stunting cases in each district of South Sulawesi Province in 2021 were collected from the South Sulawesi Provincial Health Service and utilized in this study. Population data for 2021 were obtained from the South Sulawesi Provincial Central Statistics Agency. Three covariates were included in this study: the number of people living in poverty, the number of malnourished children, and the number of children with complete basic immunizations. The findings revealed that the Bayesian spatial CAR Localized model with a hyperprior Inverse-Gamma IG (1;0.01) and two clusters, incorporating all three variables, was the most suitable model for predicting stunting cases in South Sulawesi Province in 2021. The number of people living in poverty and the number of malnourished children were positively correlated with the risk of stunting. Conversely, the number of children who have received all their baseline immunizations was inversely associated with the risk of stunting. Stunting affected approximately 54.17% of districts in South Sulawesi Province, with Jeneponto having the highest RR of stunting (RR = 1.37) and Makassar having the lowest RR (RR = 0.68) among the districts in the province.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Aswi Aswi
AU  - Bobby Poerwanto
AU  - Sudarmin
AU  - Nurwan
PY  - 2023
DA  - 2023/12/18
TI  - Bayesian Spatial Modelling of Stunting Cases in South Sulawesi Province: Influential Factors and Relative Risk
BT  - Proceedings of the 5th International Conference on Statistics, Mathematics, Teaching, and Research 2023 (ICSMTR 2023)
PB  - Atlantis Press
SP  - 87
EP  - 96
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-332-0_11
DO  - 10.2991/978-94-6463-332-0_11
ID  - Aswi2023
ER  -