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Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter?
BACKGROUND: Neonatal mortality accounts for an increasing share of under-five deaths, and they are declining at a slower rate than postnatal deaths. Apparently, neonatal mortality is increasingly becoming a major public health problem in Ghana and the world over. The current study sought to analyze...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432984/ https://www.ncbi.nlm.nih.gov/pubmed/37600403 http://dx.doi.org/10.1016/j.heliyon.2023.e18961 |
_version_ | 1785091548626550784 |
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author | Takramah, Wisdom Kwami Aheto, Justice Moses K. |
author_facet | Takramah, Wisdom Kwami Aheto, Justice Moses K. |
author_sort | Takramah, Wisdom Kwami |
collection | PubMed |
description | BACKGROUND: Neonatal mortality accounts for an increasing share of under-five deaths, and they are declining at a slower rate than postnatal deaths. Apparently, neonatal mortality is increasingly becoming a major public health problem in Ghana and the world over. The current study sought to analyze neonatal mortality as a function of predictor variables and to estimate and understand unobserved household and community-level residual effects on neonatal mortality to provide data driven evidence to shape informed policies and interventions aimed at reducing the neonatal mortality burden. METHODS: The current study extracted three-level complex data on 5884 children born in the five years preceding the 2014 Ghana Demographic and Health Survey. A two-level and three-level multilevel logistic models were applied to estimate unobserved household and community-level variations in neonatal mortality in the presence of set of predictor variables. Sampling weights were incorporated in both the descriptive and inferential analysis since the data used emanated from a complex survey. Model fit statistics such as AIC scores for a weighted two-level and three-level random intercept logistic models were compared. The model with the lowest AIC score was considered the most preferred model. RESULTS: The household-level random intercept model suggested that the odds of neonatal mortality was higher among multiple births [OR = 3.15 (95% CI: 1.17, 8.50)], babies born to mothers who received prenatal care from non-skilled worker [OR = 5.88 (95% CI: 2.90, 11.91)], babies delivered through caesarian section [OR = 2.47 (95% CI: 1.06, 5.79)], a household with 1–4 members [OR = 10.23 (95% CI: 4.17, 25.50)], a short preceding birth interval (<24 months) [OR = 3.05 (95% CI: 1.18, 7.88)], and preceding birth interval between 24 and 47 months [OR = 2.88 (95% CI: 1.41, 5.91)]. Substantial unobserved household-level residual variations in neonatal mortality were observed. CONCLUSION: The findings of the current study provide an actionable information to be used by government and other stakeholders in the health sector to renew commitment to reduce neonatal mortality to an acceptable level. There is the need to intensify maternal health education by health providers to encourage pregnant women to visit antenatal clinics at least four times so they could benefit substantially from ANC services. |
format | Online Article Text |
id | pubmed-10432984 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104329842023-08-18 Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter? Takramah, Wisdom Kwami Aheto, Justice Moses K. Heliyon Research Article BACKGROUND: Neonatal mortality accounts for an increasing share of under-five deaths, and they are declining at a slower rate than postnatal deaths. Apparently, neonatal mortality is increasingly becoming a major public health problem in Ghana and the world over. The current study sought to analyze neonatal mortality as a function of predictor variables and to estimate and understand unobserved household and community-level residual effects on neonatal mortality to provide data driven evidence to shape informed policies and interventions aimed at reducing the neonatal mortality burden. METHODS: The current study extracted three-level complex data on 5884 children born in the five years preceding the 2014 Ghana Demographic and Health Survey. A two-level and three-level multilevel logistic models were applied to estimate unobserved household and community-level variations in neonatal mortality in the presence of set of predictor variables. Sampling weights were incorporated in both the descriptive and inferential analysis since the data used emanated from a complex survey. Model fit statistics such as AIC scores for a weighted two-level and three-level random intercept logistic models were compared. The model with the lowest AIC score was considered the most preferred model. RESULTS: The household-level random intercept model suggested that the odds of neonatal mortality was higher among multiple births [OR = 3.15 (95% CI: 1.17, 8.50)], babies born to mothers who received prenatal care from non-skilled worker [OR = 5.88 (95% CI: 2.90, 11.91)], babies delivered through caesarian section [OR = 2.47 (95% CI: 1.06, 5.79)], a household with 1–4 members [OR = 10.23 (95% CI: 4.17, 25.50)], a short preceding birth interval (<24 months) [OR = 3.05 (95% CI: 1.18, 7.88)], and preceding birth interval between 24 and 47 months [OR = 2.88 (95% CI: 1.41, 5.91)]. Substantial unobserved household-level residual variations in neonatal mortality were observed. CONCLUSION: The findings of the current study provide an actionable information to be used by government and other stakeholders in the health sector to renew commitment to reduce neonatal mortality to an acceptable level. There is the need to intensify maternal health education by health providers to encourage pregnant women to visit antenatal clinics at least four times so they could benefit substantially from ANC services. Elsevier 2023-08-06 /pmc/articles/PMC10432984/ /pubmed/37600403 http://dx.doi.org/10.1016/j.heliyon.2023.e18961 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Takramah, Wisdom Kwami Aheto, Justice Moses K. Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter? |
title | Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter? |
title_full | Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter? |
title_fullStr | Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter? |
title_full_unstemmed | Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter? |
title_short | Multilevel modelling of neonatal mortality in Ghana: Does household and community levels matter? |
title_sort | multilevel modelling of neonatal mortality in ghana: does household and community levels matter? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432984/ https://www.ncbi.nlm.nih.gov/pubmed/37600403 http://dx.doi.org/10.1016/j.heliyon.2023.e18961 |
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