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Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study

OBJECTIVE: To develop and validate a prediction model for excess pregnancy weight gain using early pregnancy factors. DESIGN: Prospective cohort study SETTING: We recruited from 12 obstetrical, family medicine, and midwifery centers in Ontario, Canada PARTICIPANTS: We recruited English-speaking wome...

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Autores principales: McDonald, Sarah D., Yu, Zhijie Michael, van Blyderveen, Sherry, Schmidt, Louis, Sword, Wendy, Vanstone, Meredith, Biringer, Anne, McDonald, Helen, Beyene, Joseph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266315/
https://www.ncbi.nlm.nih.gov/pubmed/32484813
http://dx.doi.org/10.1371/journal.pone.0233774
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author McDonald, Sarah D.
Yu, Zhijie Michael
van Blyderveen, Sherry
Schmidt, Louis
Sword, Wendy
Vanstone, Meredith
Biringer, Anne
McDonald, Helen
Beyene, Joseph
author_facet McDonald, Sarah D.
Yu, Zhijie Michael
van Blyderveen, Sherry
Schmidt, Louis
Sword, Wendy
Vanstone, Meredith
Biringer, Anne
McDonald, Helen
Beyene, Joseph
author_sort McDonald, Sarah D.
collection PubMed
description OBJECTIVE: To develop and validate a prediction model for excess pregnancy weight gain using early pregnancy factors. DESIGN: Prospective cohort study SETTING: We recruited from 12 obstetrical, family medicine, and midwifery centers in Ontario, Canada PARTICIPANTS: We recruited English-speaking women with singleton pregnancies between 8(+0)–20(+6) weeks. Of 1296 women approached, 1050 were recruited (81%). Of those, 970 women had complete data (970/1050, 92%) and were recruited at a mean of 14.8 weeks. PRIMARY OUTCOME MEASURE: We collected data on psychological, physical, and social factors and used stepwise logistic regression analysis to develop a multivariable model predicting our primary outcome of excess pregnancy weight gain, with random selection of 2/3 of women for training data and 1/3 for testing data. RESULTS: Nine variables were included in the final model to predict excess pregnancy weight gain. These included nulliparity, being overweight, planning excessive gain, eating in front of a screen, low self-efficacy regarding pregnancy weight gain, thinking family or friends believe pregnant women should eat twice as much as before pregnancy, being agreeable, and having emotion control difficulties. Training and testing data yielded areas under the receiver operating characteristic curve of 0.76 (95% confidence interval, 0.72 to 0.80) and 0.62 (95% confidence interval 0.56 to 0.68), respectively. CONCLUSIONS: In this first validated prediction model in early pregnancy, we found that nine psychological, physical, and social factors moderately predicted excess pregnancy weight gain in the final model. This research highlights the importance of several predictors, including relatively easily modifiable ones such as appropriate weight gain plans and mindfulness during eating, and lays an important methodological foundation for other future prediction models.
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spelling pubmed-72663152020-06-10 Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study McDonald, Sarah D. Yu, Zhijie Michael van Blyderveen, Sherry Schmidt, Louis Sword, Wendy Vanstone, Meredith Biringer, Anne McDonald, Helen Beyene, Joseph PLoS One Research Article OBJECTIVE: To develop and validate a prediction model for excess pregnancy weight gain using early pregnancy factors. DESIGN: Prospective cohort study SETTING: We recruited from 12 obstetrical, family medicine, and midwifery centers in Ontario, Canada PARTICIPANTS: We recruited English-speaking women with singleton pregnancies between 8(+0)–20(+6) weeks. Of 1296 women approached, 1050 were recruited (81%). Of those, 970 women had complete data (970/1050, 92%) and were recruited at a mean of 14.8 weeks. PRIMARY OUTCOME MEASURE: We collected data on psychological, physical, and social factors and used stepwise logistic regression analysis to develop a multivariable model predicting our primary outcome of excess pregnancy weight gain, with random selection of 2/3 of women for training data and 1/3 for testing data. RESULTS: Nine variables were included in the final model to predict excess pregnancy weight gain. These included nulliparity, being overweight, planning excessive gain, eating in front of a screen, low self-efficacy regarding pregnancy weight gain, thinking family or friends believe pregnant women should eat twice as much as before pregnancy, being agreeable, and having emotion control difficulties. Training and testing data yielded areas under the receiver operating characteristic curve of 0.76 (95% confidence interval, 0.72 to 0.80) and 0.62 (95% confidence interval 0.56 to 0.68), respectively. CONCLUSIONS: In this first validated prediction model in early pregnancy, we found that nine psychological, physical, and social factors moderately predicted excess pregnancy weight gain in the final model. This research highlights the importance of several predictors, including relatively easily modifiable ones such as appropriate weight gain plans and mindfulness during eating, and lays an important methodological foundation for other future prediction models. Public Library of Science 2020-06-02 /pmc/articles/PMC7266315/ /pubmed/32484813 http://dx.doi.org/10.1371/journal.pone.0233774 Text en © 2020 McDonald et al http://creativecommons.org/licenses/by/4.0/ 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 author and source are credited.
spellingShingle Research Article
McDonald, Sarah D.
Yu, Zhijie Michael
van Blyderveen, Sherry
Schmidt, Louis
Sword, Wendy
Vanstone, Meredith
Biringer, Anne
McDonald, Helen
Beyene, Joseph
Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study
title Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study
title_full Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study
title_fullStr Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study
title_full_unstemmed Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study
title_short Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study
title_sort prediction of excess pregnancy weight gain using psychological, physical, and social predictors: a validated model in a prospective cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266315/
https://www.ncbi.nlm.nih.gov/pubmed/32484813
http://dx.doi.org/10.1371/journal.pone.0233774
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