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Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study
BACKGROUND: Almost all (99%) neonatal deaths arise in low-income and middle-income countries. Approximately 450 new-born children die every hour, which is mainly from preventable causes. There has been increased recognition of the need for these countries to implement public health interventions tha...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4403673/ https://www.ncbi.nlm.nih.gov/pubmed/25887409 http://dx.doi.org/10.1186/s12889-015-1738-x |
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author | Li, Chao Yan, Hong Zeng, Lingxia Dibley, Michael J Wang, Duolao |
author_facet | Li, Chao Yan, Hong Zeng, Lingxia Dibley, Michael J Wang, Duolao |
author_sort | Li, Chao |
collection | PubMed |
description | BACKGROUND: Almost all (99%) neonatal deaths arise in low-income and middle-income countries. Approximately 450 new-born children die every hour, which is mainly from preventable causes. There has been increased recognition of the need for these countries to implement public health interventions that specifically target neonatal deaths. The purpose of this paper is to identify the predictors of neonatal death in Type 4 rural (poorest) counties in Shaanxi Province of northwestern China. METHODS: A cross-sectional study was conducted in Shaanxi Province, China. A single-stage survey design was identified to estimate standard errors. Because of concern about the complex sample design, the data were analysed using multivariate logistic regression analysis. Socioeconomic and maternal health service utilization factors were added into the model. RESULTS: During the study period, a total of 4750 women who delivered in the past three years were randomly selected for interview in the five counties. There were 4880 live births and 54 neonatal deaths identified. In the multiple logistic regression, the odds of neonatal death was significantly higher for multiparous women (OR = 2.77; 95% CI: 1.34, 5.70) and women who did not receive antennal health care in the first trimester of pregnancy (OR = 2.49; 95% CI: 1.41, 4.40). Women who gave birth in a county-level hospital (OR = 0.18; 95% CI: 0.04, 0.86) and had junior high school or higher education level (OR = 0.20; 95% CI: 0.05, 0.84) were significantly protected from neonatal death. CONCLUSIONS: Public health interventions directed at reducing neonatal death should address the socioeconomic factors and maternal health service utilization, which significantly influence neonatal mortality in rural China. Multipara, low educational level of the women, availability of prenatal visits in the first trimester of pregnancy and hospital delivery should be considered when planning the interventions to reduce the neonatal mortality in rural areas. |
format | Online Article Text |
id | pubmed-4403673 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44036732015-04-21 Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study Li, Chao Yan, Hong Zeng, Lingxia Dibley, Michael J Wang, Duolao BMC Public Health Research Article BACKGROUND: Almost all (99%) neonatal deaths arise in low-income and middle-income countries. Approximately 450 new-born children die every hour, which is mainly from preventable causes. There has been increased recognition of the need for these countries to implement public health interventions that specifically target neonatal deaths. The purpose of this paper is to identify the predictors of neonatal death in Type 4 rural (poorest) counties in Shaanxi Province of northwestern China. METHODS: A cross-sectional study was conducted in Shaanxi Province, China. A single-stage survey design was identified to estimate standard errors. Because of concern about the complex sample design, the data were analysed using multivariate logistic regression analysis. Socioeconomic and maternal health service utilization factors were added into the model. RESULTS: During the study period, a total of 4750 women who delivered in the past three years were randomly selected for interview in the five counties. There were 4880 live births and 54 neonatal deaths identified. In the multiple logistic regression, the odds of neonatal death was significantly higher for multiparous women (OR = 2.77; 95% CI: 1.34, 5.70) and women who did not receive antennal health care in the first trimester of pregnancy (OR = 2.49; 95% CI: 1.41, 4.40). Women who gave birth in a county-level hospital (OR = 0.18; 95% CI: 0.04, 0.86) and had junior high school or higher education level (OR = 0.20; 95% CI: 0.05, 0.84) were significantly protected from neonatal death. CONCLUSIONS: Public health interventions directed at reducing neonatal death should address the socioeconomic factors and maternal health service utilization, which significantly influence neonatal mortality in rural China. Multipara, low educational level of the women, availability of prenatal visits in the first trimester of pregnancy and hospital delivery should be considered when planning the interventions to reduce the neonatal mortality in rural areas. BioMed Central 2015-04-16 /pmc/articles/PMC4403673/ /pubmed/25887409 http://dx.doi.org/10.1186/s12889-015-1738-x Text en © Li et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), 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 Li, Chao Yan, Hong Zeng, Lingxia Dibley, Michael J Wang, Duolao Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study |
title | Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study |
title_full | Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study |
title_fullStr | Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study |
title_full_unstemmed | Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study |
title_short | Predictors for neonatal death in the rural areas of Shaanxi Province of Northwestern China: a cross-sectional study |
title_sort | predictors for neonatal death in the rural areas of shaanxi province of northwestern china: a cross-sectional study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4403673/ https://www.ncbi.nlm.nih.gov/pubmed/25887409 http://dx.doi.org/10.1186/s12889-015-1738-x |
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