ArticleBMC pediatrics2026
Prevalence and determinants of child malnutrition in Bangladesh: a comparative analysis of multilevel modeling.
Article in BMC pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChild malnutrition is a critical public health issue in Bangladesh, significantly affecting child development and health. This study analyzes the prevalence and determinants of malnutrition among children under five years old using data from the Bangladesh Demographic and Health Survey (BDHS) 2017-18.
methodsThe study employed Generalized Linear Mixed Models (GLMM) and Generalized Estimating Equations (GEE) to examine socio-economic, demographic, and health-related factors associated with stunting, wasting, and underweight conditions among children.
resultsThe study found that 31% of children were stunted, 22% were underweight, and 8% were wasted in Bangladesh in 2017-18, with overlaps likely among these forms of malnutrition. Higher parental education levels and wealthier household status were significantly (p < 0.05) associated with a lower prevalence of malnutrition. Children from Sylhet had 1.3 times higher odds of being stunted (AOR = 1.3, 95% C.I. = 1.05-1.65) and 1.46 times higher odds of being underweight (AOR = 1.46, 95% C.I. = 1.14-1.88) compared to children from Barisal. Mothers with normal BMI were significantly less likely to have stunted (AOR = 0.67, 95% C.I. = 0.56-0.79), wasted (AOR = 0.49, 95% C.I. = 0.37-0.66), and underweight (AOR = 0.63, 95% C.I. = 0.53-0.75) children compared to mothers with underweight BMI. Both GLMM and GEE models identified the same associated factors for stunting, wasting, and underweight, with close estimates. However, GLMM was found to have better predictive power for all three models, as indicated by higher area under the curve (AUC) values.
conclusionThe findings emphasize the association of poor parental education, economic conditions, and maternal health with child malnutrition in Bangladesh. The GLMM demonstrated better predictive power based on AUC values across all three outcomes, making it a more reliable choice for this type of analysis. Policymakers should prioritize enhancing maternal education, household economic status, and access to healthcare services.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.