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The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis
BACKGROUND: Racial inequities in maternal mortality in the U.S. continue to be stark. METHODS: The 2015–2018, 4-year total population, county-level, pregnancy-related mortality ratio (PRM; deaths per 100,000 live births; National Center for Health Statistics (NCHS), restricted use mortality file) wa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670647/ https://www.ncbi.nlm.nih.gov/pubmed/36384521 http://dx.doi.org/10.1186/s12889-022-14397-x |
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author | Harville, E. W. Grady, S.K. Langston, MA Juarez, P. J. Vilda, D. Wallace, M. E. |
author_facet | Harville, E. W. Grady, S.K. Langston, MA Juarez, P. J. Vilda, D. Wallace, M. E. |
author_sort | Harville, E. W. |
collection | PubMed |
description | BACKGROUND: Racial inequities in maternal mortality in the U.S. continue to be stark. METHODS: The 2015–2018, 4-year total population, county-level, pregnancy-related mortality ratio (PRM; deaths per 100,000 live births; National Center for Health Statistics (NCHS), restricted use mortality file) was linked with the Public Health Exposome (PHE). Using data reduction techniques, 1591 variables were extracted from over 62,000 variables for use in this analysis, providing information on the relationships between PRM and the social, health and health care, natural, and built environments. Graph theoretical algorithms and Bayesian analysis were applied to PHE/PRM linked data to identify latent networks. RESULTS: PHE variables most strongly correlated with total population PRM were years of potential life lost and overall life expectancy. Population-level indicators of PRM were overall poverty, smoking, lack of exercise, heat, and lack of adequate access to food. CONCLUSIONS: In this high-dimensional analysis, overall life expectancy, poverty indicators, and health behaviors were found to be the strongest predictors of pregnancy-related mortality. This provides strong evidence that maternal death is part of a broader constellation of both similar and unique health behaviors, social determinants and environmental exposures as other causes of death. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-14397-x. |
format | Online Article Text |
id | pubmed-9670647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96706472022-11-18 The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis Harville, E. W. Grady, S.K. Langston, MA Juarez, P. J. Vilda, D. Wallace, M. E. BMC Public Health Research BACKGROUND: Racial inequities in maternal mortality in the U.S. continue to be stark. METHODS: The 2015–2018, 4-year total population, county-level, pregnancy-related mortality ratio (PRM; deaths per 100,000 live births; National Center for Health Statistics (NCHS), restricted use mortality file) was linked with the Public Health Exposome (PHE). Using data reduction techniques, 1591 variables were extracted from over 62,000 variables for use in this analysis, providing information on the relationships between PRM and the social, health and health care, natural, and built environments. Graph theoretical algorithms and Bayesian analysis were applied to PHE/PRM linked data to identify latent networks. RESULTS: PHE variables most strongly correlated with total population PRM were years of potential life lost and overall life expectancy. Population-level indicators of PRM were overall poverty, smoking, lack of exercise, heat, and lack of adequate access to food. CONCLUSIONS: In this high-dimensional analysis, overall life expectancy, poverty indicators, and health behaviors were found to be the strongest predictors of pregnancy-related mortality. This provides strong evidence that maternal death is part of a broader constellation of both similar and unique health behaviors, social determinants and environmental exposures as other causes of death. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-14397-x. BioMed Central 2022-11-17 /pmc/articles/PMC9670647/ /pubmed/36384521 http://dx.doi.org/10.1186/s12889-022-14397-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Harville, E. W. Grady, S.K. Langston, MA Juarez, P. J. Vilda, D. Wallace, M. E. The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis |
title | The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis |
title_full | The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis |
title_fullStr | The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis |
title_full_unstemmed | The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis |
title_short | The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis |
title_sort | public health exposome and pregnancy-related mortality in the united states: a high-dimensional computational analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670647/ https://www.ncbi.nlm.nih.gov/pubmed/36384521 http://dx.doi.org/10.1186/s12889-022-14397-x |
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