Influence of socioeconomic status on objective sleep measurement: A systematic review and meta-analysis of actigraphy studies

Sosso, Faustin Armel Etindele; Holmes, Sari D.; Weinstein, Ali A.

doi:10.1016/j.sleh.2021.05.005

Cited by 94 publications

(63 citation statements)

References 38 publications

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“…Extended availability can lead to additional workloads outside regular working hours and to fragmentation of individual areas of life, which has consequences for stress and recovery [62]. Systematic reviews and meta-analyses found that socioeconomic status also influenced sleep parameters, with lower socioeconomic status being associated with disturbed mental health and poorer sleep parameters [28,31,63,64]. Lower socioeconomic status was observed to be associated with lower total sleep duration, longer sleep latency, greater sleep fragmentation and higher sleep onset variability [64].…”

Section: Discussionmentioning

confidence: 99%

Subjective and Objective Consequences of Stress in Subjects with Subjectively Different Sleep Quality—A Cross-Sectional Study

Thielmann

Schierholz

Böckelmann

2021

IJERPH

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Background: Restful sleep plays an important role in long-term health and occupational safety. Heart rate variability (HRV) is used as stress indicator. The aim of this study was to determine whether HRV at rest or during sleep, as an objective indicator of stress, reflects subjectively assessed sleep quality. Methods: 84 subjects (37.3 ± 15.6 years) were classified into good sleepers and poor sleepers based on the results of the Pittsburgh Sleep Quality Index (PSQI). The cut-off value to distinguish between good and bad sleepers recommended by Buysse et al. 1989 is >5. Mental health status was determined using the 12-Item General Health Questionnaire (GHQ-12). A 24 h electrocardiogram (ECG) was recorded for HRV analysis (total and 6 h night phase). Results: The poor sleepers showed a significantly lower mental health status (p = 0.004). The multifactorial variance analysis of the total phase time parameters Min HR (p = 0.032, η2 = 0.056) and SI (p = 0.015, η2 = 0.072) showed significant interaction effects. In the 6h night phase, significant interaction effects were found for SDNN (p = 0.036, η2 = 0.065) and SD2 (p = 0.033, η2 = 0.067). In addition, there was a significant negative correlation between HRV and stress and a positive correlation between HRV and mental health. Conclusions: Although this study did not demonstrate a direct relationship between sleep quality and HRV, it was shown that there are important connections between sleep quality and mental health, and between HRV and mental health.

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Section: Discussionmentioning

confidence: 99%

Subjective and Objective Consequences of Stress in Subjects with Subjectively Different Sleep Quality—A Cross-Sectional Study

Thielmann

Schierholz

Böckelmann

2021

IJERPH

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“…Promote use of PSG and actigraphy in SES research. It is easier and more conventional to use validated questionnaires or self-reported items to investigate health disparities; however, PSG as well as actigraphy provide very useful and accurate details, including sleep continuity or WASO, that can objectively indicate sleep disorders or sleep health disparities with more accuracy than subjective assessments [ 7 ]. More basic training and advanced lectures related to PSG and actigraphy should be provided to students as well as researchers with interest in sleep, regardless of their background or their expertise.…”

Section: Discussionmentioning

confidence: 99%

“…The majority of studies investigating sleep disturbances use self-reported instruments such as the Insomnia Severity Index (ISI) and the Pittsburgh Sleep Quality Index (PSQI), while very few studies in sleep research and health disparities have used objective measurement like actigraphy and polysomnography as an assessment tool [ 7 , 8 ]. Polysomnography involves the recording of several variables such as the electrical activity of the brain via electroencephalography, muscle activity via electromyogram and eyeball activity via electrooculogram [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

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

Sosso¹

2022

Clocks & Sleep

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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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“…The temporality of the relationship between EDS and SEP needs to be further assessed in longitudinal studies, rather than cross-sectional, which can discern the direction of the interaction and allow clear causality interpretations on how SEP influences EDS. In order to implement and design clinical and public health initiatives to improve the overall population health and reduce the gap in health disparities, inclusion of objective measures of sleep, obtained by actigraphy or polysomnography should be included in future research [ 52 , 53 ]. Considering that sleep is an intricate and individual process that is heavily influenced by complex and dynamic interrelations across a lifetime, the development of a multivariable model that allows to consider and describe the various modifiable factors that take play in EDS would lead to better novel clinical interventions.…”

Section: Discussionmentioning

confidence: 99%

Socioeconomic Position and Excessive Daytime Sleepiness: A Systematic Review of Social Epidemiological Studies

Bendaoud

Sosso²

2022

Clocks & Sleep

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The objectives of this empirical study are to describe and discuss the current literature available on the relationship between excessive daytime sleepiness (EDS) and the socioeconomic position (SEP) as well as to provide recommendations for consideration of SEP in sleep medicine and biomedical research. Databases Medline/PubMed, Web of Science, Google scholar and Scopus were screened from January 1990 to December 2020 using PRISMA guidelines and 20 articles were included in the final synthesis. Nineteen studies were cross-sectional and one study was longitudinal. Among these studies, 25.00% (n = 5) are focused on children and adolescent and the remaining 75.00% (n = 15) focused on adults and seniors. Ages ranged from 8 to 18 years old for children/adolescent and ranged from 18 to 102 years old for adults. Main SEP measures presented in these studies were education, income, perceived socioeconomic status and employment. The sample size in these studies varied from N = 90 participants to N = 33,865 participants. Overall, a lower educational level, a lower income and full-time employment were associated with EDS. Symptoms of EDS are prevalent in women, especially those with a low income or no job; and children and adolescents with difficult living conditions or working part time reported more sleep disturbances. SEP is already considered as an important determinant for many health outcomes, but if SEP is embedded in the experimental design in psychosomatic research, biomedical research and clinical practice as a constant variable regardless of outcome; it will move forward future investigations.

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Influence of socioeconomic status on objective sleep measurement: A systematic review and meta-analysis of actigraphy studies

Cited by 94 publications

References 38 publications

Subjective and Objective Consequences of Stress in Subjects with Subjectively Different Sleep Quality—A Cross-Sectional Study

Subjective and Objective Consequences of Stress in Subjects with Subjectively Different Sleep Quality—A Cross-Sectional Study

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

Socioeconomic Position and Excessive Daytime Sleepiness: A Systematic Review of Social Epidemiological Studies

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