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Regional Differences in Various Risk Factors for Postpartum Depression: Applying Mixed Models to the PRAMS Dataset
Purpose: The purpose of this study was to assess the association between various risk factors with postpartum depression severity using a large dataset that included variables such as previous mental health status, social factors, societal factors, health care access, and other state-wide or region-...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8594048/ https://www.ncbi.nlm.nih.gov/pubmed/34816242 http://dx.doi.org/10.3389/fgwh.2021.726422 |
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author | Gifford, Janace J. Pluchino, Jenna R. Della Valle, Rebecca Schwarz, Jaclyn M. |
author_facet | Gifford, Janace J. Pluchino, Jenna R. Della Valle, Rebecca Schwarz, Jaclyn M. |
author_sort | Gifford, Janace J. |
collection | PubMed |
description | Purpose: The purpose of this study was to assess the association between various risk factors with postpartum depression severity using a large dataset that included variables such as previous mental health status, social factors, societal factors, health care access, and other state-wide or region-specific variables. Methods: We obtained the most recently available (2016–2017) dataset from the Pregnancy Risk Assessment Monitoring System (PRAMS), which is a dataset compiled by the Centers for Disease Control (CDC) that collects state-specific, population-based data on maternal attitudes and experiences before, during, and shortly after pregnancy from over 73,000 women in 39 states. We utilized a hierarchical linear model to analyze the data across various levels, with a symptom severity scale (0–8) as the dependent variable. Results: Of the 21 variables included in the final model, nine variables were statistically significant predictors of symptom severity. Statistically significant predictors of increased postpartum depression symptom severity included previous depression diagnosis and depression symptoms during pregnancy, baby not residing with mother, unintentional pregnancy, women with less than a high school degree and more than a college degree, Women Infants Children (WIC) enrollment, and married women. In contrast to these other factors, attendance at a postpartum follow up appointment was associated with significantly increased symptom severity. Age revealed an inverted curve in predicting postpartum symptom severity. Conclusions: There was no significant difference in symptom severity scores across the 39 participating states. Most notably, postpartum depression symptom severity was associated with previous depression diagnosis and previous symptom severity, but our results also reveal novel social and education factors that contribute to the support and well-being of the mother and child. |
format | Online Article Text |
id | pubmed-8594048 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85940482021-11-22 Regional Differences in Various Risk Factors for Postpartum Depression: Applying Mixed Models to the PRAMS Dataset Gifford, Janace J. Pluchino, Jenna R. Della Valle, Rebecca Schwarz, Jaclyn M. Front Glob Womens Health Global Women's Health Purpose: The purpose of this study was to assess the association between various risk factors with postpartum depression severity using a large dataset that included variables such as previous mental health status, social factors, societal factors, health care access, and other state-wide or region-specific variables. Methods: We obtained the most recently available (2016–2017) dataset from the Pregnancy Risk Assessment Monitoring System (PRAMS), which is a dataset compiled by the Centers for Disease Control (CDC) that collects state-specific, population-based data on maternal attitudes and experiences before, during, and shortly after pregnancy from over 73,000 women in 39 states. We utilized a hierarchical linear model to analyze the data across various levels, with a symptom severity scale (0–8) as the dependent variable. Results: Of the 21 variables included in the final model, nine variables were statistically significant predictors of symptom severity. Statistically significant predictors of increased postpartum depression symptom severity included previous depression diagnosis and depression symptoms during pregnancy, baby not residing with mother, unintentional pregnancy, women with less than a high school degree and more than a college degree, Women Infants Children (WIC) enrollment, and married women. In contrast to these other factors, attendance at a postpartum follow up appointment was associated with significantly increased symptom severity. Age revealed an inverted curve in predicting postpartum symptom severity. Conclusions: There was no significant difference in symptom severity scores across the 39 participating states. Most notably, postpartum depression symptom severity was associated with previous depression diagnosis and previous symptom severity, but our results also reveal novel social and education factors that contribute to the support and well-being of the mother and child. Frontiers Media S.A. 2021-10-29 /pmc/articles/PMC8594048/ /pubmed/34816242 http://dx.doi.org/10.3389/fgwh.2021.726422 Text en Copyright © 2021 Gifford, Pluchino, Della Valle and Schwarz. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Global Women's Health Gifford, Janace J. Pluchino, Jenna R. Della Valle, Rebecca Schwarz, Jaclyn M. Regional Differences in Various Risk Factors for Postpartum Depression: Applying Mixed Models to the PRAMS Dataset |
title | Regional Differences in Various Risk Factors for Postpartum Depression: Applying Mixed Models to the PRAMS Dataset |
title_full | Regional Differences in Various Risk Factors for Postpartum Depression: Applying Mixed Models to the PRAMS Dataset |
title_fullStr | Regional Differences in Various Risk Factors for Postpartum Depression: Applying Mixed Models to the PRAMS Dataset |
title_full_unstemmed | Regional Differences in Various Risk Factors for Postpartum Depression: Applying Mixed Models to the PRAMS Dataset |
title_short | Regional Differences in Various Risk Factors for Postpartum Depression: Applying Mixed Models to the PRAMS Dataset |
title_sort | regional differences in various risk factors for postpartum depression: applying mixed models to the prams dataset |
topic | Global Women's Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8594048/ https://www.ncbi.nlm.nih.gov/pubmed/34816242 http://dx.doi.org/10.3389/fgwh.2021.726422 |
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