Evidence map›Paper›PMID 40645633›Full record

ArticleBMJ open2025

Joint modelling of anthropometric child undernutrition indicators to identify their risk factors in Bangladesh: evidence from the Multiple Indicator Cluster Survey (MICS) 2019.

Ruhul Amin, Tanjila Akter, Rukshana Ferdous, Romana Akter, Md Mehrab Shahriar, Md Atiqul Islam

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Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Ruhul AminBangladesh Institute of Governance and Management, Dhaka, Bangladesh.ORCID http://orcid.org/0000-0003-2074-0869
Tanjila AkterDepartment of Statistics, Shahjalal University of Science and Technology, Sylhet, Bangladesh.
Rukshana FerdousIndependent Researcher, Dhaka, Bangladesh.
Romana AkterDepartment of Statistics, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Md Mehrab ShahriarSecure Link Services BD Ltd, Dhaka, Bangladesh.
Md Atiqul IslamDepartment of Statistics, Jagannath University, Dhaka, Bangladesh atique@stat.jnu.ac.bd.ORCID http://orcid.org/0000-0003-2683-0945

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveStunting, wasting and underweight are the three widely recognised indicators of child undernutrition. This study aimed to simultaneously model all indicators while accounting for their association using a joint modelling technique to identify their risk factors.

designThis was a cross-sectional study design.

settingThe anthropometric data of children were elicited from the Bangladesh Multiple Indicator Cluster Survey (MICS) 2019.

main outcome measuresStunting, wasting and underweight were the main outcome measures of child undernutrition. Initially, a generalised linear mixed model (GLMM) was developed for each indicator separately to identify the underlying risk factors by considering children within the cluster (district level) as hierarchically nested. Finally, a joint model was developed by combining the separate GLMMs with the condition of correlated cluster-specific (district-specific) random effects.

resultsThe developed joint model provided precise effects of the risk factors and quantified the association among stunting, wasting and underweight. The joint correlations of underweight with stunting [Formula: see text] and underweight with wasting [Formula: see text] were significantly positive based on the predictors in the joint model. The age of children, household wealth status, and maternal education were risk factors for both stunting and underweight. The mother's age at first birth and the episode of fever were significantly correlated with both underweight and wasting, while the episode of fever was significantly associated with underweight. The region, residence and sex of children were significantly associated with all undernutrition indicators.

conclusionsThis study demonstrates the application of a joint model to simultaneously identify the risk factors associated with indicators of child undernutrition. The study findings reveal a substantial positive association between stunting and underweight, as well as between underweight and wasting, with shared risk factors contributing to the disparity in the prevalence of all forms of child undernutrition in Bangladesh.

Indexed as

Child Nutrition DisordersGrowth DisordersMalnutritionThinnessWasting SyndromeAnthropometryBangladeshChildChild, PreschoolCross-Sectional StudiesFemaleHumansInfantMaleRisk FactorsSocioeconomic Factorschildnutrition & dieteticspublic health

Identifiers

PMID40645633
PMCPMC12265825

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