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Correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the Nigerian experience
BACKGROUND: Nigeria’s high perinatal mortality rate (PNMR) could be most effectively reduced by targeting factors that are associated with increased newborn deaths. Low access to skilled birth attendants (SBAs) and weak health system are recognized factors associated with high PNMR but other socio-d...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262084/ https://www.ncbi.nlm.nih.gov/pubmed/25271134 http://dx.doi.org/10.1186/1471-2393-14-341 |
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author | Nkwo, Peter Onubiwe Lawani, Lucky Osaheni Ezugwu, Euzebus Chinonye Iyoke, Chukwuemeka Anthony Ubesie, Agozie C Onoh, Robinson Chukwudi |
author_facet | Nkwo, Peter Onubiwe Lawani, Lucky Osaheni Ezugwu, Euzebus Chinonye Iyoke, Chukwuemeka Anthony Ubesie, Agozie C Onoh, Robinson Chukwudi |
author_sort | Nkwo, Peter Onubiwe |
collection | PubMed |
description | BACKGROUND: Nigeria’s high perinatal mortality rate (PNMR) could be most effectively reduced by targeting factors that are associated with increased newborn deaths. Low access to skilled birth attendants (SBAs) and weak health system are recognized factors associated with high PNMR but other socio-demographic and reproductive factors could have significant influences as well. Identification of the major factors associated with high PNMR would be required in designing interventions to improve perinatal outcomes. METHODS: For this cross-sectional study, data from the Nigeria Demographic and Health Survey 2008 were used to estimate the PNMR of non-hospital births in identified socio-demographic and reproductive situations that are known to influence PNMR. The estimated PNMR were compared using logistic regression analysis. RESULTS: The PNMR was 36 per 1000 live births. North central region had the lowest PNMR while the south east region had the highest rate (odds ratio 1.59; 95% CI: 1.03, 2.45). Other correlates of high PNMR were belonging to the poorest wealth quintile (odds ratio 1.87; 95% CI: 1.30, 2.70), maternal age group 15–19 years (odds ratio 1.59; 95% CI: 1.05, 2.22), multiple birth (odds ratio 3.12; 95% CI: 2.11, 4.59), history of previous perinatal death (odds ratio 3.31; 95% CI: 2.73, 4.02), birth interval shorter than 18 months (odds ratio 1.65; 95% CI: 1.26, 2.17) and having a small birth size (odds ratio 2.56; 95% CI 1.79, 3.69). Birth attendant, place of birth, parity, maternal education and rural/urban residence had no association with PNMR. CONCLUSIONS: Reproductive factors that require midwifery skills were found to contribute most to PNMR. We recommend general strengthening of the health system, recruitment of SBAs and retraining of available birth attendants with emphasis on identification and referral of complicated cases. Family planning should be a core MCH activity to address the issues of teenage pregnancy and short pregnancy intervals. |
format | Online Article Text |
id | pubmed-4262084 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42620842014-12-11 Correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the Nigerian experience Nkwo, Peter Onubiwe Lawani, Lucky Osaheni Ezugwu, Euzebus Chinonye Iyoke, Chukwuemeka Anthony Ubesie, Agozie C Onoh, Robinson Chukwudi BMC Pregnancy Childbirth Research Article BACKGROUND: Nigeria’s high perinatal mortality rate (PNMR) could be most effectively reduced by targeting factors that are associated with increased newborn deaths. Low access to skilled birth attendants (SBAs) and weak health system are recognized factors associated with high PNMR but other socio-demographic and reproductive factors could have significant influences as well. Identification of the major factors associated with high PNMR would be required in designing interventions to improve perinatal outcomes. METHODS: For this cross-sectional study, data from the Nigeria Demographic and Health Survey 2008 were used to estimate the PNMR of non-hospital births in identified socio-demographic and reproductive situations that are known to influence PNMR. The estimated PNMR were compared using logistic regression analysis. RESULTS: The PNMR was 36 per 1000 live births. North central region had the lowest PNMR while the south east region had the highest rate (odds ratio 1.59; 95% CI: 1.03, 2.45). Other correlates of high PNMR were belonging to the poorest wealth quintile (odds ratio 1.87; 95% CI: 1.30, 2.70), maternal age group 15–19 years (odds ratio 1.59; 95% CI: 1.05, 2.22), multiple birth (odds ratio 3.12; 95% CI: 2.11, 4.59), history of previous perinatal death (odds ratio 3.31; 95% CI: 2.73, 4.02), birth interval shorter than 18 months (odds ratio 1.65; 95% CI: 1.26, 2.17) and having a small birth size (odds ratio 2.56; 95% CI 1.79, 3.69). Birth attendant, place of birth, parity, maternal education and rural/urban residence had no association with PNMR. CONCLUSIONS: Reproductive factors that require midwifery skills were found to contribute most to PNMR. We recommend general strengthening of the health system, recruitment of SBAs and retraining of available birth attendants with emphasis on identification and referral of complicated cases. Family planning should be a core MCH activity to address the issues of teenage pregnancy and short pregnancy intervals. BioMed Central 2014-09-30 /pmc/articles/PMC4262084/ /pubmed/25271134 http://dx.doi.org/10.1186/1471-2393-14-341 Text en © Nkwo et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Nkwo, Peter Onubiwe Lawani, Lucky Osaheni Ezugwu, Euzebus Chinonye Iyoke, Chukwuemeka Anthony Ubesie, Agozie C Onoh, Robinson Chukwudi Correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the Nigerian experience |
title | Correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the Nigerian experience |
title_full | Correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the Nigerian experience |
title_fullStr | Correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the Nigerian experience |
title_full_unstemmed | Correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the Nigerian experience |
title_short | Correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the Nigerian experience |
title_sort | correlates of poor perinatal outcomes in non-hospital births in the context of weak health system: the nigerian experience |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262084/ https://www.ncbi.nlm.nih.gov/pubmed/25271134 http://dx.doi.org/10.1186/1471-2393-14-341 |
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