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Estimation of sleep problems among pregnant women during COVID-19 pandemic: a systematic review and meta-analysis
OBJECTIVE: To estimate the sleep problems among pregnant women during the COVID-19 pandemic. ELIGIBILITY CRITERIA: English, peer-reviewed, observational studies published between December 2019 and July 2021 which assessed and reported sleep problem prevalence using a valid and reliable measure were...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8980733/ https://www.ncbi.nlm.nih.gov/pubmed/35379627 http://dx.doi.org/10.1136/bmjopen-2021-056044 |
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author | Alimoradi, Zainab Abdi, Fatemeh Gozal, David Pakpour, Amir H |
author_facet | Alimoradi, Zainab Abdi, Fatemeh Gozal, David Pakpour, Amir H |
author_sort | Alimoradi, Zainab |
collection | PubMed |
description | OBJECTIVE: To estimate the sleep problems among pregnant women during the COVID-19 pandemic. ELIGIBILITY CRITERIA: English, peer-reviewed, observational studies published between December 2019 and July 2021 which assessed and reported sleep problem prevalence using a valid and reliable measure were included. INFORMATION SOURCES: Scopus, Medline/PubMed Central, ProQuest, ISI Web of Knowledge and Embase. RISK OF BIAS ASSESSMENT TOOL: The Newcastle-Ottawa Scale checklist. SYNTHESIS OF RESULTS: Prevalence of sleep problems was synthesised using STATA software V.14 using a random effects model. To assess moderator analysis, meta-regression was carried out. Funnel plot and Egger’s test were used to assess publication bias. Meta-trim was used to correct probable publication bias. The jackknife method was used for sensitivity analysis. INCLUDED STUDIES: A total of seven cross-sectional studies with 2808 participants from four countries were included. SYNTHESIS OF RESULTS: The pooled estimated prevalence of sleep problems was 56% (95% CI 23% to 88%, I(2)=99.81%, Tau(2)=0.19). Due to the probability of publication bias, the fill-and-trim method was used to correct the estimated pooled measure, which imputed four studies. The corrected results based on this method showed that pooled prevalence of sleep problems was 13% (95% CI 0% to 45%; p<0.001). Based on meta-regression, age was the only significant predictor of prevalence of sleep problems among pregnant women. LIMITATIONS OF EVIDENCE: All studies were cross-sectional absence of assessment of sleep problems prior to COVID-19, and the outcomes of the pregnancies among those with and without sleep problems in a consistent manner are among the limitation of the current review. INTERPRETATION: Pregnant women have experienced significant declines in sleep quality when faced with the COVID-19 pandemic. The short-term and long-term implications of such alterations in sleep on gestational and offspring outcomes are unclear and warrant further studies. PROSPERO REGISTRATION NUMBER: CRD42020181644. |
format | Online Article Text |
id | pubmed-8980733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-89807332022-04-05 Estimation of sleep problems among pregnant women during COVID-19 pandemic: a systematic review and meta-analysis Alimoradi, Zainab Abdi, Fatemeh Gozal, David Pakpour, Amir H BMJ Open Mental Health OBJECTIVE: To estimate the sleep problems among pregnant women during the COVID-19 pandemic. ELIGIBILITY CRITERIA: English, peer-reviewed, observational studies published between December 2019 and July 2021 which assessed and reported sleep problem prevalence using a valid and reliable measure were included. INFORMATION SOURCES: Scopus, Medline/PubMed Central, ProQuest, ISI Web of Knowledge and Embase. RISK OF BIAS ASSESSMENT TOOL: The Newcastle-Ottawa Scale checklist. SYNTHESIS OF RESULTS: Prevalence of sleep problems was synthesised using STATA software V.14 using a random effects model. To assess moderator analysis, meta-regression was carried out. Funnel plot and Egger’s test were used to assess publication bias. Meta-trim was used to correct probable publication bias. The jackknife method was used for sensitivity analysis. INCLUDED STUDIES: A total of seven cross-sectional studies with 2808 participants from four countries were included. SYNTHESIS OF RESULTS: The pooled estimated prevalence of sleep problems was 56% (95% CI 23% to 88%, I(2)=99.81%, Tau(2)=0.19). Due to the probability of publication bias, the fill-and-trim method was used to correct the estimated pooled measure, which imputed four studies. The corrected results based on this method showed that pooled prevalence of sleep problems was 13% (95% CI 0% to 45%; p<0.001). Based on meta-regression, age was the only significant predictor of prevalence of sleep problems among pregnant women. LIMITATIONS OF EVIDENCE: All studies were cross-sectional absence of assessment of sleep problems prior to COVID-19, and the outcomes of the pregnancies among those with and without sleep problems in a consistent manner are among the limitation of the current review. INTERPRETATION: Pregnant women have experienced significant declines in sleep quality when faced with the COVID-19 pandemic. The short-term and long-term implications of such alterations in sleep on gestational and offspring outcomes are unclear and warrant further studies. PROSPERO REGISTRATION NUMBER: CRD42020181644. BMJ Publishing Group 2022-04-03 /pmc/articles/PMC8980733/ /pubmed/35379627 http://dx.doi.org/10.1136/bmjopen-2021-056044 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Mental Health Alimoradi, Zainab Abdi, Fatemeh Gozal, David Pakpour, Amir H Estimation of sleep problems among pregnant women during COVID-19 pandemic: a systematic review and meta-analysis |
title | Estimation of sleep problems among pregnant women during COVID-19 pandemic: a systematic review and meta-analysis |
title_full | Estimation of sleep problems among pregnant women during COVID-19 pandemic: a systematic review and meta-analysis |
title_fullStr | Estimation of sleep problems among pregnant women during COVID-19 pandemic: a systematic review and meta-analysis |
title_full_unstemmed | Estimation of sleep problems among pregnant women during COVID-19 pandemic: a systematic review and meta-analysis |
title_short | Estimation of sleep problems among pregnant women during COVID-19 pandemic: a systematic review and meta-analysis |
title_sort | estimation of sleep problems among pregnant women during covid-19 pandemic: a systematic review and meta-analysis |
topic | Mental Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8980733/ https://www.ncbi.nlm.nih.gov/pubmed/35379627 http://dx.doi.org/10.1136/bmjopen-2021-056044 |
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