Prediction Models Comparison of Stunting in Districts/Cities of Stunting Locus with Different Geographical Characteristics in Jambi Province

Analysis of the 2018 Indonesia Basic Health Survey

DOI

10.2991/978-2-494069-33-6_41How to use a DOI?

Keywords

prediction; stunting; underfive children; secondary analysis

Abstract

Stunting is still a nutritional problem in Indonesia and also in Jambi Province. The causes of stunting are multifactorial. The purpose of this study was to analyze predictive models of stunting in under five children in districts of focus on stunting with different geographical characteristics. This study was secondary research using part of the 2018 Basic Health Research (Riskesdas) data with a cross sectional design. Samples were under five children (24–59 months) total 859 peoples. The independent variables were household characteristics, father, mother and child factors. The dependent variable was Stunting (Height to Age if Z score <  −2 Standard Deviation). Data analysis using Chi-square and Multiple Logistics Regression. The incidence of stunting in Jambi Province was 26.4%, varying from 16.9–35.3% in several districts at the locus of Stunting. The prediction model in the districts with the locus of stunting varies but it made pattern on one root cause, namely the socio-economic level. Prediction models in highland geography was the mother’s occupation after being controlled by infectious diseases, smoking, monitoring of child growth and development, access to health care facilities, place of delivery, personal hygiene and father’s height. Stunting prediction model in the lowlands was the mother’s occupation after being controlled by access to health care facilities, mother’s education, place of delivery, socioeconomic, parity and pregnancy complication. The prediction model in watersheds area was the socioeconomic after being controlled by infectious diseases, smoking, pregnancy status, mother’s education [1], monitoring growth of under five children, place of delivery and parity. While the prediction model in urban areas was maternal height after being controlled by environmental health, place of delivery, parity and socio-economics. It is recommended that the districts governments strengthen multi-sectoral synergy in the handling and prevention of stunting and improve the socio-economic level of the community.

Copyright

© 2023 The Author(s)

Open Access

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TY  - CONF
AU  - Ummi Kalsum
AU  - Islakhiyah Islakhiyah
AU  - Hendra Dhermawan Sitanggang
PY  - 2022
DA  - 2022/12/22
TI  - Prediction Models Comparison of Stunting in Districts/Cities of Stunting Locus with Different Geographical Characteristics in Jambi Province
BT  - Proceedings of the 3rd Progress in Social Science, Humanities and Education Research Symposium (PSSHERS 2021)
PB  - Atlantis Press
SP  - 345
EP  - 363
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-494069-33-6_41
DO  - 10.2991/978-2-494069-33-6_41
ID  - Kalsum2022
ER  -