Evidence map›Paper›PMID 41652514›Full record

ArticleJournal of health, population, and nutrition2026

Determinants of multiple modes of failure in child mortality in Bangladesh: fine and gray modeling approach.

Tanha Akter Tithy, Md Atiqul Islam

Abstract read
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Article in Journal of health, population, and nutrition, 2026. 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Tanha Akter TithyDepartment of Statistics, Jagannath University, Dhaka, 1100, Bangladesh.
Md Atiqul IslamDepartment of Statistics, Jagannath University, Dhaka, 1100, Bangladesh. atique@stat.jnu.ac.bd.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnnually, millions of children under-five die from preventable causes. This study aimed to investigate risk factors associated with the time to death from several causes in children under-five in Bangladesh. METHODOLOGY: The data were extracted from the 2022 Bangladesh Demographic and Health Survey (BDHS). A total of 13,119 under-five children were selected. Eleven causes of child mortality were categorized into disease, non-disease, and other causes. The event was death (in months), and children who were alive at the interview date were censored. This study employed the Cumulative Incidence Function (CIF) to describe cause-specific probabilities over time and the Fine and Gray competing risk model to analyze the risks of death, using sub-distribution hazard ratios (SHR). RESULT AND DISCUSSION: Among 464 (3.5%) under-five deaths, 141 (30.4%), 258 (55.6%), and 65 (14%) died from disease, non-disease, and other causes, respectively. The Sylhet division (SHR: 2.51, Confidence interval (CI): 1.25-5.01, p = 0.009) had a higher risk of child mortality due to disease, and delivery by cesarean section (SHR: 0.544, CI: 0.31-0.96, p = 0.035) had a lower risk of child mortality due to non-disease. Additionally, significant variables included mother's age, birth order number, and place of delivery for disease; mother's age, mother's education, wealth index, birth order number, and place of delivery for non-disease; and division, mother's education level, birth order number, and place of delivery for other causes.

conclusionSupporting young mothers, reducing socioeconomic disparities, and tailoring interventions by birth order and specific cause of death can improve child health.

Indexed as

Child MortalityInfant MortalityBangladeshCause of DeathChild, PreschoolFemaleHealth SurveysHumansInfantInfant, NewbornMaleProportional Hazards ModelsRisk FactorsSocioeconomic FactorsChild mortalityCompeting riskCox-PHFine and grayHazard ratioSurvival

Identifiers

PMID41652514
PMCPMC12973842

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LicenceCC BY-NC-ND
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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.