Determinants of Comprehensive Understanding of Stunting among Indonesian Pregnant Women and Mothers of Toddlers Aged 0–23 Months in 2023

Authors

  • Agnes Rosihan Kristianti Silalahi STIS Polytechnic of Statistics
  • Rini STIS Polytechnic of Statistics

DOI:

https://doi.org/10.34123/icdsos.v2025i1.688

Keywords:

understanding of stunting, pregnant women, mothers of toddlers aged 0–23 months, ordinal logistic regression, proportional odds model

Abstract

Stunting is a chronic nutritional disorder that remains a priority in Indonesia. As with
the second goal of the SDGs (zero hunger), the Ministry of Health (MoH) has implemented a
communication strategy for behavioural change and community empowerment through a class
program for pregnant women and mothers of toddlers class using the Maternal and Child Health
(MCH) book. However, it is still not optimal to increase the understanding of stunting. The 2023
Indonesian Health Survey (IHS) shows that women in Indonesia still have a poor comprehensive
understanding of stunting. It has includes pregnant women and breastfeeding mothers as key
target groups for stunting reduction. This study aims to describe and analyse the characteristics
of Indonesian pregnant women and mothers of toddlers aged 0–23 months that significantly
influence their comprehensive understanding levels of stunting. Data from 2023 IHS were
analysed using descriptive statistics with graph and table, together with inferential analysis
through ordinal logistic regression using the Proportional Odds Model (POM). The result shows
that the majority of these mothers have a poor level of comprehensive understanding of stunting,
with five variables having a significant influence, namely: access to information, education level,
employment status, socioeconomic status, and residence area.

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Published

2025-12-22

How to Cite

Silalahi, A. R. K., & Rahani, R. (2025). Determinants of Comprehensive Understanding of Stunting among Indonesian Pregnant Women and Mothers of Toddlers Aged 0–23 Months in 2023. Proceedings of The International Conference on Data Science and Official Statistics, 2025(1), 1283–1296. https://doi.org/10.34123/icdsos.v2025i1.688