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Under age five children survival times in Nigeria: a Bayesian spatial modeling approach

Overview of attention for article published in BMC Public Health, November 2022
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Title
Under age five children survival times in Nigeria: a Bayesian spatial modeling approach
Published in
BMC Public Health, November 2022
DOI 10.1186/s12889-022-14660-1
Pubmed ID
Authors

Osafu Augustine Egbon, Mariella Ananias Bogoni, Bayowa Teniola Babalola, Francisco Louzada

Abstract

Nigeria is among the top five countries in the world with the highest under-five mortality rates. In addition to the general leading causes of under-five mortality, studies have shown that disparity in sociocultural values and practices across ethnic groups in Nigeria influence child survival, thus there is a need for scientific validation. This study quantified the survival probabilities and the impact of socioeconomic and demographic factors, proximate and biological determinants, and environmental factors on the risk of under-five mortality in Nigeria. The Kaplan-Meier survival curve, Nelson Aalen hazard curve, and components survival probabilities were estimated. The Exponential, Gamma, Log-normal, Weibull, and Cox hazard models in a Bayesian mixed effect hierarchical hazard modeling framework with spatial components were considered, and the Deviance and Watanabe Akaike information criteria were used to select the best model for inference. A [Formula: see text] level of significance was assumed throughout this work. The 2018 Nigeria Demographic and Health Survey dataset was used, and the outcome variable was the time between birth and death or birth and the date of interview for children who were alive on the day of the interview. Findings show that the probability of a child dying within the first two months is 0.04, and the probability of a boy child dying before attaining age five is 0.106, while a girl child is 0.094 probability. Gender, maternal education, household wealth status, source of water and toilet facility, residence, mass media, frequency of antenatal and postnatal visits, marital status, place of delivery, multiple births, who decide healthcare use, use of bednet are significant risk factors of child mortality in Nigeria. The mortality risk is high among the maternal age group below 24 and above 44years, and birth weight below 2.5Kg and above 4.5Kg. The under-five mortality risk is severe in Kebbi, Kaduna, Jigawa, Adamawa, Gombe, Kano, Kogi, Nasarawa, Plateau, and Sokoto states in Nigeria. This study accentuates the need for special attention for the first two months after childbirth as it is the age group with the highest expected mortality. A practicable way to minimize death in the early life of children is to improve maternal healthcare service, promote maternal education, encourage delivery in healthcare facilities, positive parental attitude to support multiple births, poverty alleviation programs for the less privileged, and a prioritized intervention to Northern Nigeria.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 16%
Researcher 3 9%
Student > Postgraduate 2 6%
Student > Bachelor 1 3%
Unspecified 1 3%
Other 2 6%
Unknown 18 56%
Readers by discipline Count As %
Medicine and Dentistry 5 16%
Nursing and Health Professions 3 9%
Environmental Science 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Agricultural and Biological Sciences 1 3%
Other 3 9%
Unknown 18 56%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 December 2022.
All research outputs
#20,284,083
of 24,938,276 outputs
Outputs from BMC Public Health
#14,319
of 16,598 outputs
Outputs of similar age
#353,199
of 483,624 outputs
Outputs of similar age from BMC Public Health
#353
of 443 outputs
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