ArticleScientific reports2025
A Bayesian quantile regression approach for determining risk factors of low birth weight of under five children in Cambodia.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Risk Factors of Coexisting Form of Undernutrition Among Under-5 Children in Bangladesh: Evidence From BDHS 2022 Data in a Bayesian Setting.Child: care, health and development · 2026Article
- Socioeconomic and geographic disparities in institutional delivery in Bangladesh: a Bayesian multilevel modelling framework.BMC public health · 2026Article
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Abstract
Birth weight (BW) is a key indicator of a newborn's health, survival, and development. It is associated with the risk of childhood mortality and is also related to health, physical growth, emotional well-being, and academic success throughout both childhood and adulthood. Therefore, it is crucial to pinpoint the sociodemographic characteristics that have an impact on BW. This study aimed to explore the risk factors associated with children's low birth weight using the latest nationwide secondary data extracted from the Cambodia Demographic and Health Survey (CDHS) 2021/22. The study included a weighted sample of 4701 children from the CDHS 2021-22 data. Multivariable simultaneous quantile regression models in a Bayesian setting were used to determine the factors associated with Cambodian children's low birth weight. The average BW is 3.064 (SD 0.483 kg) kg. It is observed that there are some outliers in the target variable and the birth weight of the child is deviated from normal distribution. Women who are young (15-17 years) for their first baby have more low BW infants overall than women who have their first babies later. For mothers aged 18-24 years, children's birth weight increases by 0.068 to 0.149 points when moving from the 10th to the 50th quantile. For overweight mothers, children's birth weight increases by 0.123 to 0.348 points when moving from the 10th to the 90th quantile. It is observed that the prevalence of smaller size of children comes from illiterate mothers and the prevalence decreases as the mother's education increases. More small children are born in rural areas than in urban areas in Cambodia. Our study findings show that the mother's poor economic status is one of the major risk factors for LBW. Moreover, the birth weights of children from the richest families in the 10th, 20th, 50th, 75th, and 90th quantiles are increased by 0.075, 0.058, 0.111, 0.114, and 0.053 points respectively. The child's sex and birth order, the mother's age at first birth, her education level and BMI, the number of ANC visits during pregnancy, drinking water sources, types of bathroom facilities, place of residence, and wealth index are all related to the child's size. Furthermore, mothers who have low education levels and grew up in low-income households require special consideration. To lessen the number of low birth weight babies, the authors suggest that the Cambodian government may prioritize food and health education in its school system. Additionally, the authors think that the policymakers will benefit from these findings in order to achieve SDG-3.
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