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Measuring Sleep Health Disparities with Polysomnography: A Systematic Review of Preliminary Findings

Socioeconomic status (SES) has an unrecognized influence on behavioral risk factors as well as public health strategies related to sleep health disparities. In addition to that, objectively measuring SES’ influence on sleep health is challenging. A systematic review of polysomnography (PSG) studies...

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Autor principal: Etindele Sosso, Faustin Armel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883971/
https://www.ncbi.nlm.nih.gov/pubmed/35225955
http://dx.doi.org/10.3390/clockssleep4010009
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author Etindele Sosso, Faustin Armel
author_facet Etindele Sosso, Faustin Armel
author_sort Etindele Sosso, Faustin Armel
collection PubMed
description Socioeconomic status (SES) has an unrecognized influence on behavioral risk factors as well as public health strategies related to sleep health disparities. In addition to that, objectively measuring SES’ influence on sleep health is challenging. A systematic review of polysomnography (PSG) studies investigating the relation between SES and sleep health disparities is worthy of interest and holds potential for future studies and recommendations. A literature search in databases was conducted following Prisma guidelines. Search strategy identified seven studies fitting within the inclusion criteria. They were all cross-sectional studies with only adults. Except for one study conducted in India, all of these studies took place in western countries. Overall emerging trends are: (1) low SES with its indicators (income, education, occupation and employment) are negatively associated with PSG parameters and (2) environmental factors (outside noise, room temperature and health worries); sex/gender and BMI were the main moderators of the relation between socioeconomic indicators and the variation of sleep recording with PSG. Socioeconomic inequalities in sleep health can be measured objectively. It will be worthy to examine the SES of participants and patients before they undergo PSG investigation. PSG studies should always collect socioeconomic data to discover important connections between SES and PSG. It will be interesting to compare PSG data of people from different SES in longitudinal studies and analyze the intensity of variations through time.
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spelling pubmed-88839712022-03-01 Measuring Sleep Health Disparities with Polysomnography: A Systematic Review of Preliminary Findings Etindele Sosso, Faustin Armel Clocks Sleep Review Socioeconomic status (SES) has an unrecognized influence on behavioral risk factors as well as public health strategies related to sleep health disparities. In addition to that, objectively measuring SES’ influence on sleep health is challenging. A systematic review of polysomnography (PSG) studies investigating the relation between SES and sleep health disparities is worthy of interest and holds potential for future studies and recommendations. A literature search in databases was conducted following Prisma guidelines. Search strategy identified seven studies fitting within the inclusion criteria. They were all cross-sectional studies with only adults. Except for one study conducted in India, all of these studies took place in western countries. Overall emerging trends are: (1) low SES with its indicators (income, education, occupation and employment) are negatively associated with PSG parameters and (2) environmental factors (outside noise, room temperature and health worries); sex/gender and BMI were the main moderators of the relation between socioeconomic indicators and the variation of sleep recording with PSG. Socioeconomic inequalities in sleep health can be measured objectively. It will be worthy to examine the SES of participants and patients before they undergo PSG investigation. PSG studies should always collect socioeconomic data to discover important connections between SES and PSG. It will be interesting to compare PSG data of people from different SES in longitudinal studies and analyze the intensity of variations through time. MDPI 2022-02-18 /pmc/articles/PMC8883971/ /pubmed/35225955 http://dx.doi.org/10.3390/clockssleep4010009 Text en © 2022 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Etindele Sosso, Faustin Armel
Measuring Sleep Health Disparities with Polysomnography: A Systematic Review of Preliminary Findings
title Measuring Sleep Health Disparities with Polysomnography: A Systematic Review of Preliminary Findings
title_full Measuring Sleep Health Disparities with Polysomnography: A Systematic Review of Preliminary Findings
title_fullStr Measuring Sleep Health Disparities with Polysomnography: A Systematic Review of Preliminary Findings
title_full_unstemmed Measuring Sleep Health Disparities with Polysomnography: A Systematic Review of Preliminary Findings
title_short Measuring Sleep Health Disparities with Polysomnography: A Systematic Review of Preliminary Findings
title_sort measuring sleep health disparities with polysomnography: a systematic review of preliminary findings
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883971/
https://www.ncbi.nlm.nih.gov/pubmed/35225955
http://dx.doi.org/10.3390/clockssleep4010009
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