Evidence map›Paper›PMID 41990011›Full record

ArticlePloS one2026

Pooled incidence and predictors of infant mortality in low- and middle-income countries using gamma shared frailty model: Insights for achieving the Sustainable Development Goals.

Dejen Kahsay Asgedom, Habtamu Solomon Demeke, Etsay Woldu Anbesu, Ausman Ahmed Mohammed, Simachew Getaneh Endalamew, Bewuketu Terefe, Solomon Keflie Assefa, Asefa Asimasu Taddese

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Article in PloS one, 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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5 · Who and what money

Authors and funding

8 authors.

Dejen Kahsay AsgedomDepartment of Public Health, College of Medicine and Health Science, Samara University, Samara, Ethiopia.ORCID https://orcid.org/0009-0000-5777-1269
Habtamu Solomon DemekeDepartment of Public Health, College of Medicine and Health Science, Samara University, Samara, Ethiopia.
Etsay Woldu AnbesuDepartment of Public Health, College of Medicine and Health Science, Samara University, Samara, Ethiopia.
Ausman Ahmed MohammedDepartment of Nursing, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.
Simachew Getaneh EndalamewDepartment of Veterinary Epidemiology and Public Health, School of Veterinary Medicine, Bahir Dar University, Bahir Dar, Ethiopia.ORCID https://orcid.org/0009-0005-2692-7394
Bewuketu TerefeDepartment of Community Health Nursing, School of Nursing, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia.
Solomon Keflie AssefaDepartment of Public Health, Pawi Health Science College, Pawi, Ethiopia.ORCID https://orcid.org/0009-0005-6988-9471
Asefa Asimasu TaddeseAcademy of Wellness and Human Development, Faculty of Arts and Social Sciences, Hong Kong Baptist University, Hong Kong SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLow- and middle-income countries (LMICs) account for a large share of global infant deaths, but there is a lack of evidence on the pooled estimate of infant mortality and its predictors in LMICs. Therefore, this study aimed to assess the pooled incidence of infant mortality and its associated factors in LMICs.

methodsWe used clustered data extracted from the recent Demographic and Health Surveys (DHS 2018-DHS 2024) of all LMICs. A total of 1,404,826weighted numbers of recent live births were included in the study. A lognormal shared gamma frailty model was employed. We used the Akaike information criterion (AIC), Bayesian information criterion (BIC), and log-likelihood values for model comparison. An adjusted time ratio ([Formula: see text]) with a 95% confidence interval (CI) in the final model was used to select variables that had a significant association with time to infant death. The data were analyzed via R software version 4.3.1.

resultsA total of 1,404,826 live births were included in the final analysis. By the end of the follow-up period, 72,569 infants (5.17%, 95% CI: 5.13-5.21) had died before their first birthday. The pooled estimate of the IMR in LMICs was 39 per 1000 live births (95% CI: 32.68-44.95). Maternal education, family size ≥ 5, being a multiparous mother, being delivered at health facilities, being a female infant, immediate initiation of breast feeding, living in Europe & Central Asia, and living in West & East Asia were significantly associated with a lower risk of infant death. Conversely, maternal age 25-34, maternal age 35-49, unimproved toilet facilities, poor and middle wealth indices, maternal age at birth ≤19, birth interval of <18 and 18-23 months, multiple births, 2nd birth order, small birth size, low and medium Human Development Index (HDI), low and medium literacy rate, low-income and lower-middle income countries, rural residence, living in West Africa, South & Central Africa, and South Asia were significantly associated with a higher risk of infant mortality.

conclusionThe infant mortality rate (IMR) in LMICs remains high compared with that in WHO targets and shows significant regional variation. West Africa and South Asia had the highest pooled estimate of infant deaths. Variables such as maternal age, education, wealth index, age at first birth, parity, family size, child sex, birth interval, multiple pregnancy, birth order number, perceived child size at birth, place of delivery, residence, country's literacy rate, income group, and HDI value were identified as significant predictors of time to infant death. Therefore, public health interventions that enhance health facility delivery, optimal birth spacing, maternal education, and immediate breastfeeding are crucial to reduce the incidence of infant mortality in LMICs.

Indexed as

Developing CountriesInfant MortalitySustainable DevelopmentAdultFemaleHumansIncidenceInfantInfant, NewbornMale

Identifiers

PMID41990011
PMCPMC13086360

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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.