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Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis
BACKGROUND: U.S. mortality rate of term infants is higher than most other developed countries. Term infant mortality is associated with exogenous socio-environmental factors. Previous research links low socioeconomic status and rurality with high infant mortality, but does not examine the effect of...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343321/ https://www.ncbi.nlm.nih.gov/pubmed/30669972 http://dx.doi.org/10.1186/s12884-019-2190-1 |
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author | Mohamoud, Yousra A. Kirby, Russell S. Ehrenthal, Deborah B. |
author_facet | Mohamoud, Yousra A. Kirby, Russell S. Ehrenthal, Deborah B. |
author_sort | Mohamoud, Yousra A. |
collection | PubMed |
description | BACKGROUND: U.S. mortality rate of term infants is higher than most other developed countries. Term infant mortality is associated with exogenous socio-environmental factors. Previous research links low socioeconomic status and rurality with high infant mortality, but does not examine the effect of individual level factors on this association. Separating out the effect of contextual factors from individual level factors has important implications for targeting interventions. Therefore, we aim to estimate the independent effect of poverty and urban-rural classification on term infant mortality. METHODS: We used linked 2013 period cohort birth-infant death files from the National Center for Health Statistics (NCHS). Counties were assigned to low, medium and high poverty groups using US Census Bureau county-level percent of children ≤18 years living in poverty, and were classified based on NCHS urban-rural classification. Bivariate and multilevel logistic regression models were used to estimate odds of term infant death, accounting for individual and county level variables. RESULTS: There were 2,551,828 term births in 2013, with an overall term mortality of 2.1 per 1000 births. Odds of term infant mortality increased from 1.4 (95% CI: 1.2, 1.6) to 1.8 (95% CI: 1.6, 2.0) comparing births over increasing county poverty to those in the lowest. The associations remained significant in the multivariable model, for highest poverty 1.3 (95% CI: 1.1, 1.5). Similarly, the odds of term infant mortality increased with increasing rurality, from 1.3 (95% CI: 1.2, 1.5) in medium metro counties to 1.7 (95% CI: 1.5, 2.0) in non-core counties compared to large fringe metro counties. However, only rural non-core counties remained statistically associated with increased risk of term infant mortality after adjusting for individual level maternal characteristics. CONCLUSIONS: High poverty and very rural counties remained associated with term infant mortality independent of individual maternal sociodemographic, health and obstetric factors. Interventions should focus on contextual factors such as economic environment and availability of health and social services in addition to individual factors to reduce term infant mortality. |
format | Online Article Text |
id | pubmed-6343321 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63433212019-01-24 Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis Mohamoud, Yousra A. Kirby, Russell S. Ehrenthal, Deborah B. BMC Pregnancy Childbirth Research Article BACKGROUND: U.S. mortality rate of term infants is higher than most other developed countries. Term infant mortality is associated with exogenous socio-environmental factors. Previous research links low socioeconomic status and rurality with high infant mortality, but does not examine the effect of individual level factors on this association. Separating out the effect of contextual factors from individual level factors has important implications for targeting interventions. Therefore, we aim to estimate the independent effect of poverty and urban-rural classification on term infant mortality. METHODS: We used linked 2013 period cohort birth-infant death files from the National Center for Health Statistics (NCHS). Counties were assigned to low, medium and high poverty groups using US Census Bureau county-level percent of children ≤18 years living in poverty, and were classified based on NCHS urban-rural classification. Bivariate and multilevel logistic regression models were used to estimate odds of term infant death, accounting for individual and county level variables. RESULTS: There were 2,551,828 term births in 2013, with an overall term mortality of 2.1 per 1000 births. Odds of term infant mortality increased from 1.4 (95% CI: 1.2, 1.6) to 1.8 (95% CI: 1.6, 2.0) comparing births over increasing county poverty to those in the lowest. The associations remained significant in the multivariable model, for highest poverty 1.3 (95% CI: 1.1, 1.5). Similarly, the odds of term infant mortality increased with increasing rurality, from 1.3 (95% CI: 1.2, 1.5) in medium metro counties to 1.7 (95% CI: 1.5, 2.0) in non-core counties compared to large fringe metro counties. However, only rural non-core counties remained statistically associated with increased risk of term infant mortality after adjusting for individual level maternal characteristics. CONCLUSIONS: High poverty and very rural counties remained associated with term infant mortality independent of individual maternal sociodemographic, health and obstetric factors. Interventions should focus on contextual factors such as economic environment and availability of health and social services in addition to individual factors to reduce term infant mortality. BioMed Central 2019-01-22 /pmc/articles/PMC6343321/ /pubmed/30669972 http://dx.doi.org/10.1186/s12884-019-2190-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Mohamoud, Yousra A. Kirby, Russell S. Ehrenthal, Deborah B. Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis |
title | Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis |
title_full | Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis |
title_fullStr | Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis |
title_full_unstemmed | Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis |
title_short | Poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis |
title_sort | poverty, urban-rural classification and term infant mortality: a population-based multilevel analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343321/ https://www.ncbi.nlm.nih.gov/pubmed/30669972 http://dx.doi.org/10.1186/s12884-019-2190-1 |
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