Toward a multi-lingual diagnostic tool for the worldwide problem of sleep health: The French RU-SATED validation

Global Perspectives on Sleep Health: Definitions, Disparities, and Implications for Public Health

Sleep health is a multidimensional construct encompassing sleep quality, duration, efficiency, regularity, and alignment with circadian rhythms, playing a crucial role in overall well-being. Sleep health remains inconsistently defined across research and clinical settings despite its importance, limiting the ability to standardize assessments and interventions. Recent studies have emphasized the significance of defining sleep health beyond the absence of sleep disorders, integrating subjective and objective measures to assess its impact on physical and mental health outcomes. Disparities in sleep health exist across gender, socioeconomic status, and geographic regions, particularly in low- and middle-income countries where inconsistent work schedules, economic stress, and healthcare access influence sleep patterns. Poor sleep health is associated with increased risks of cardiovascular disease, obesity, metabolic dysfunction, and mental health disorders, reinforcing its role as a modifiable risk factor in public health. Lifestyle factors such as caffeine consumption, physical activity, and irregular eating patterns also contribute to sleep disturbances, highlighting the need for behavioral interventions. This narrative review aims to synthesize the current knowledge on sleep health, focusing on its definitions, measurement tools, global disparities, and associations.

Detecting psychometric and diagnostic performance of the RU_SATED v2.0 multidimensional sleep health scale in community-dwelling adults combining exploratory graph analysis and ROC analysis

OBJECTIVE

The RU_SATED scale is increasingly used across the globe to measure sleep health. However, there is a lack of consensus around its psychometric and diagnostic performance. We conducted an empirical investigation into the psychometrics of the Chinese version of the RU_SATED (RU_SATED-C) scale, with a focus on structural validity and diagnostic performance.

METHODS

1171 adults were enrolled from three communities in Hangzhou, China in July 2022. The dataset was spilt in half, and we ran a bootstrapped exploratory graph analysis (bootEGA) in one half and a confirmatory factor analysis (CFA) in the other half to assess structural validity. Correlations with insomnia, wellness, anxiety, and depression symptoms were examined in order to assess concurrent validity; and Cronbach's α and McDonald's ω were calculated to assess internal consistency. Additionally, a Receiver Operating Characteristic (ROC) analysis established and externally validated the optimal score for identifying insomnia symptoms.

RESULTS

A one-dimensional structure, as identified by bootEGA, was corroborated in the CFA [comparative fit index = 0.934, root mean square error of approximation = 0.088, standardized root mean square residual = 0.051]. A moderate correlation was shown with insomnia symptoms, while weak correlations were observed with wellness, anxiety, and depression symptoms. The RU_SATED-C scale displayed sub-optimal internal consistency where coefficients dropped if any item was removed. A recommended cutoff score of ≤13 was derived for probable insomnia with a satisfactory diagnostic performance.

CONCLUSION

The RU_SATED-C scale displayed a one-dimensional model, along with adequate concurrent validity, internal consistency, and diagnostic performance. Further work necessitates multi-scenario testing and additional validation using objective sleep assessments.

Monitoring the sleep health of adults: a scoping review of routine national surveillance systems

Study Objectives

The aims of this review were to identify existing national surveillance systems monitoring one or more domains of sleep health in adults, and to describe the specific sleep health indicators used.

Methods

We systematically searched the gray and peer-reviewed literature for routinely conducted cross-sectional and longitudinal nationally representative health surveys that included the assessment of at least one domain of sleep health. The methodology involved: (1) targeted searches of the websites of national and international health agencies and statistics departments for 199 countries, (2) country-specific customized internet searches, and (3) country-specific electronic database searches of PubMed.

Results

A total of 19 762 records were identified from both the gray and peer-reviewed literature. Sleep health surveillance at the national level was conducted by 51 countries (25.6%) across 69 national health surveys. Sleep quality (96.1% of countries that surveilled sleep) was the most frequently assessed followed by sleep duration (27.5%), sleep medication use (25.5%), sleep disorders (17.6%), daytime alertness (15.7%), sleep satisfaction (15.7%), and sleep timing (7.8%). Additionally, 34.8% of the surveys utilized multiple sleep health indicators.

Conclusions

This study identified three significant gaps in the coverage of sleep health within national surveillance systems. Limited population sleep data in low- and middle-income countries, inconsistent use of sleep-related items in surveys and questionnaires, and substantial variability in the definitions of sleep health indicators. Advocacy for the inclusion of sleep health within national surveillance systems may be warranted given the important role sleep plays in public health.

Sleep Health Analysis Through Sleep Symptoms in 35,808 Individuals Across Age and Sex Differences: Comparative Symptom Network Study

BACKGROUND

Sleep health is a multidimensional construct that includes objective and subjective parameters and is influenced by individual sleep-related behaviors and sleep disorders. Symptom network analysis allows modeling of the interactions between variables, enabling both the visualization of relationships between different factors and the identification of the strength of those relationships. Given the known influence of sex and age on sleep health, network analysis can help explore sets of mutually interacting symptoms relative to these demographic variables.

OBJECTIVE

This study aimed to study the centrality of symptoms and compare age and sex differences regarding sleep health using a symptom network approach in a large French population that feels concerned about their sleep.

METHODS

Data were extracted from a questionnaire provided by the Réseau Morphée health network. A network analysis was conducted on 39 clinical variables related to sleep disorders and sleep health. After network estimation, statistical analyses consisted of calculating inferences of centrality, robustness (ie, testifying to a sufficient effect size), predictability, and network comparison. Sleep clinical variable centralities within the networks were analyzed by both sex and age using 4 age groups (18-30, 31-45, 46-55, and >55 years), and local symptom-by-symptom correlations determined.

RESULTS

Data of 35,808 participants were obtained. The mean age was 42.7 (SD 15.7) years, and 24,964 (69.7%) were women. Overall, there were no significant differences in the structure of the symptom networks between sexes or age groups. The most central symptoms across all groups were nonrestorative sleep and excessive daytime sleepiness. In the youngest group, additional central symptoms were chronic circadian misalignment and chronic sleep deprivation (related to sleep behaviors), particularly among women. In the oldest group, leg sensory discomfort and breath abnormality complaint were among the top 4 central symptoms. Symptoms of sleep disorders thus became more central with age than sleep behaviors. The high predictability of central nodes in one of the networks underlined its importance in influencing other nodes.

CONCLUSIONS

The absence of structural difference between networks is an important finding, given the known differences in sleep between sexes and across age groups. These similarities suggest comparable interactions between clinical sleep variables across sexes and age groups and highlight the implication of common sleep and wake neural circuits and circadian rhythms in understanding sleep health. More precisely, nonrestorative sleep and excessive daytime sleepiness are central symptoms in all groups. The behavioral component is particularly central in young people and women. Sleep-related respiratory and motor symptoms are prominent in older people. These results underscore the importance of comprehensive sleep promotion and screening strategies tailored to sex and age to impact sleep health.

Race and sex differences in the longitudinal changes in multidimensional self-reported sleep health characteristics in aging older adults

OBJECTIVES

We examined within-individual changes in self-reported sleep health as community-dwelling older adults age as well as potential differences in these changes by self-reported sex and racial identity.

METHODS

Participants were from the United States and enrolled in the Rush Memory and Aging Project, Minority Aging Research Study, or Religious Orders Study (N = 3539, 20% Black, 75% female, mean 78years [range 65-103]), and they received annual, in-person clinical evaluations (median 5 visits [range 1-27]). A sleep health composite score measured the number of poor sleep characteristics among satisfaction, daytime sleepiness, efficiency, and duration. Mixed effects models estimated associations of age, race, sex, and their interactions on the composite and individual sleep measures, accounting for key confounders.

RESULTS

As they aged, Black participants shifted from reporting two poor sleep characteristics to one poor sleep characteristic, while White participants shifted from one poor characteristic to two. Regardless of age, sex, and race, participants reported that they "often" felt satisfied with their sleep and "sometimes" had trouble staying asleep. Females over age 85 and males of all ages reported the most daytime sleepiness, and older White participants (>age 90) reported the most difficulty falling asleep.

CONCLUSIONS

Although self-reported sleep characteristics were typically stable across age, identifying race and sex differences in self-reported sleep health can help guide future research to understand the mechanisms that underlie these differences.

Sleep timing, workplace well-being and mental health in healthcare workers

INTRODUCTION

Healthcare workers face an elevated risk of burnout, sleep disorders, and mental health issues, potentially stemming from the misalignment of their circadian rhythm due to nonstandard work schedules. This cross-sectional survey aims to examine the connections between sleep timing, workplace well-being (including burnout and absenteeism), and mental health outcomes (specifically depression and poor sleep) in healthcare workers. Additionally, the survey takes into account individual and professional factors, as well as the interaction with work schedules.

METHODS

The study encompasses 4,971 healthcare workers from both public and private healthcare facilities in France, including nurses, nursing assistants, and physicians recruited during the third wave of the COVID-19 pandemic. The Maslach Burnout Inventory assesses burnout, the Center for Epidemiologic Studies Depression Scale measures depression, and the Pittsburgh Sleep Quality Index evaluates poor sleep. Sleep timing is categorized into morning, neutral, and evening timing, referred to as midsleep. Multivariate logistic regression analysis is conducted to explore the relationships between sleep timing and burnout, depression, and poor sleep, while adjusting for various factors.

RESULTS

The findings reveal that 56.5% of participants experience burnout, 29.8% report depression, and 64.5% report poor sleep. Nurses and nursing assistants exhibit a higher prevalence of poor sleep. Morning sleep timing is associated with burnout among those with fixed schedules and with depression among those with shift schedules. Among physicians, both morning and evening sleep timing are associated with depression, while morning sleep timing is linked to poor sleep across all subgroups.

INTERPRETATION

This study suggests that the misalignment between healthcare workers' internal circadian rhythm and their work schedules may contribute to an increased risk of burnout, depression, and poor sleep. Occupational health services and policymakers should recognize the potential for enhancing workplace well-being and mental health outcomes by enabling healthcare workers to maintain sleep schedules that accommodate their needs.

The association between different sleep health dimensions and sex, age, education, circadian preference, and chronic insomnia: a representative population-based study

Objectives

The aims were to explore multidimensional sleep health and the different dimensions of sleep health in the adult Norwegian population in relation to sex, age, education, circadian preference, and chronic insomnia.

Methods

A representative sample of 1028 Norwegians, aged 18 + years completed a cross-sectional web-based survey. Sleep health was measured with the multidimensional RU_SATED scale, which assesses the dimensions of regularity, satisfaction, alertness, timing, efficiency, and duration. Insomnia was assessed with the Bergen Insomnia Scale. Data were analyzed with chi-square tests, t-tests, one-way ANOVAs, and regression analyses, as appropriate. Response rate was 33.5%.

Results

Sleep health was better in males, with increasing age, and with higher educational level, and was poorer in participants with evening preference and chronic insomnia, compared to their respective counterparts. When investigating the different sleep health dimensions, males scored better than females on satisfaction (adjusted odds ratio [aOR] = 0.69, 95% CI = 0.51 to 0.93), timing (aOR = 0.66, 95% CI = 0.49 to 0.88), and efficiency (aOR = 0.68, 95% CI = 0.52 to 0.89). Older age was associated with better scores on regularity and satisfaction, whereas young age was associated with better scores on alertness and duration. High educational level was associated with better scores on alertness, timing, and duration. Evening types scored worse than morning types on regularity (aOR = 0.27, 95% CI = 0.18 to 0.41), satisfaction (aOR = 0.37, 95% CI = 0.26 to 0.53), and timing (aOR = 0.36, 95% CI = 0.26 to 0.51). Participants with chronic insomnia scored worse than participants without insomnia on all six sleep health dimensions.

Conclusions

Sleep health differed significantly in relation to sex, age, education, circadian preference, and chronic insomnia. However, specific group differences were not equally evident in all sleep health dimensions.

Six multidimensional sleep health facets in older adults identified with factor analysis of actigraphy: Results from the Einstein Aging Study

OBJECTIVES

The concept of multi-dimensional sleep health, originally based on self-report, was recently extended to actigraphy in older adults, yielding five components, but without a hypothesized rhythmicity factor. The current study extends prior work using a sample of older adults with a longer period of actigraphy follow-up, which may facilitate observation of the rhythmicity factor.

METHODS

Wrist actigraphy measures of participants (N = 289, Mage = 77.2 years, 67% females; 47% White, 40% Black, 13% Hispanic/Others) over 2 weeks were used in exploratory factor analysis to determine factor structures, followed by confirmatory factor analysis on a different subsample. The utility of this approach was demonstrated by associations with global cognitive performance (Montreal Cognitive Assessment).

RESULTS

Exploratory factor analysis identified six factors: Regularity: standard deviations of four sleep measures: midpoint, sleep onset time, night total sleep time (TST), and 24-hour TST; Alertness/Sleepiness (daytime): amplitude, napping (mins and #/day); Timing: sleep onset, midpoint, wake-time (of nighttime sleep); up-mesor, acrophase, down-mesor; Efficiency: sleep maintenance efficiency, wake after sleep onset; Duration: night rest interval(s), night TST, 24-hour rest interval(s), 24-hour TST; Rhythmicity (pattern across days): mesor, alpha, and minimum. Greater sleep efficiency was associated with better Montreal Cognitive Assessment performance (β [95% confidence interval] = 0.63 [0.19, 1.08]).

CONCLUSIONS

Actigraphic records over 2 weeks revealed that Rhythmicity may be an independent factor in sleep health. Facets of sleep health can facilitate dimension reduction, be considered predictors of health outcomes, and be potential targets for sleep interventions.

The RU_SATED as a measure of sleep health: cross-cultural adaptation and validation in Chinese healthcare students

BACKGROUND

The RU_SATED scale is a multidimensional instrument measuring sleep health, consisting of Regularity, Satisfaction, Alertness, Timing, Efficiency, Duration dimensions. We adapted and validated the Chinese RU_SATED (RU_SATED-C) scale.

METHODS

The RU_SATED-C scale was developed through a formal linguistic validation process and was validated in an observational longitudinal survey design. Healthcare students completed the RU_SATED scale, Sleep Quality Questionnaire, and Patient Health Questionnaire-4 among two sites of Hangzhou and Ningbo, China. Psychometric assessments included structural validity, longitudinal measurement invariance, convergent and divergent validity, internal consistency, and test-retest reliability.

RESULTS

A total of 911 healthcare students completed the RU_SATED-C scale at baseline (Time 1, T1) and follow-up (Time 2, T2) with an average time interval of 7 days + 5.37 h. Confirmatory factor analysis (CFA) confirmed a single-factor model and resulted in an acceptable model fit. The two-factor model previously found in the Japanese version fit better than the one-factor model, whereas the one-factor model fit had a better fit than the two-factor model found in the English version. Longitudinal CFA resulted in negligible changes in fit indices for four forms of increasingly restrictive models and supported that a single-factor model was equivalent over time. The data also endorsed longitudinal measurement invariance among the two-factor models found in the English and Japanese samples. The RU_SATED-C scale total score displayed a moderately strong negative correlation with sleep quality; however, negligible associations were observed with anxiety and depression. Ordinal Cronbach's alpha and Ordinal McDonald's omega at T1 and T2 ranged from suboptimal to acceptable. The RU_SATED-C scale and all items were significantly correlated across time intervals.

CONCLUSION

The RU_SATED-C scale is an easy-to-use instrument with potentially valid data for the measurement of multidimensional sleep health. Use of the RU_SATED-C scale can help raise awareness of sleep health and could pave the way for important efforts to promote healthy sleep.

Psychometric evaluation of the Chinese version of Sleep Health Index in pregnant women

OBJECTIVE

The aim of this study was to investigate the psychometric properties of the Chinese version of the Sleep Health Index (SHI-C) among pregnant women.

DESIGN

Cross-sectional design.

SETTING

Outpatient clinic of three hospitals in China.

PARTICIPANTS

Pregnant women (N = 264) aged between 18 and 45 years were recruited via convenience sampling.

METHODS

The Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS) and Insomnia Severity Index (ISI) were used to measure sleep quality, daytime sleepiness, and insomnia, respectively. The Fatigue Assessment Scale (FAS) and the Edinburgh Postnatal Depression Scale (EPDS) were used to measure fatigue and depression, respectively. Structural validity was assessed via confirmatory factor analysis (CFA). Concurrent and convergent validity were assessed using bivariate correlation analyses. Known-group validity was assessed by comparing the SHI-C score between different groups. Cronbach's α was calculated for reliability.

FINDINGS

The average sample age was 30.6 years old and their average score of SHI-C was 86.4 (SD 8.2). Based on PSQI, ISI, and ESS, 43.6%, 32.2%, and 26.9% had poor sleep quality, insomnia, and excessive daytime sleepiness, respectively. The SHI-C total and sleep quality sub-index scores had moderate to strong correlations with both PSQI (r=-0.542, p<0.01; r=-0.648, p<0.01) and ISI (r=-0.692, p<0.01; r=-0.752, p<0.01). The SHI-C total and sleep quality sub-index scores were significantly associated with ESS, FAS, and EPDS (r=-0.171 to -0.276; p<0.01). The SHI-C total score was higher in the second trimester and among those who were working, never drank coffee, or took a nap every day. The Cronbach's α of the SHI-C total and the sleep quality sub-index were 0.723 and 0.806, respectively. The Cronbach's α of sleep duration and disordered sleep sub-indices were 0.594 and 0.545, respectively.

KEY CONCLUSIONS

Overall, the SHI-C has good validity and acceptable reliability among the pregnant population in China. It can be a useful tool for the assessment of sleep health. More research is warranted to refine the sleep duration and disordered sleep sub-indices.

IMPLICATIONS FOR PRACTICE

The use of SHI-C would facilitate the assessment of sleep health among pregnant women, which could contribute to the promotion of perinatal care.

Emotional Exhaustion, a Proxy for Burnout, Is Associated with Sleep Health in French Healthcare Workers without Anxiety or Depressive Symptoms: A Cross-Sectional Study

Burnout is frequent among healthcare workers, and sleep problems are suspected risk factors. The sleep health framework provides a new approach to the promotion of sleep as a health benefit. The aim of this study was to assess good sleep health in a large sample of healthcare workers and to investigate its relationship with the absence of burnout among healthcare workers while considering anxiety and depressive symptoms. A cross-sectional Internet-based survey of French healthcare workers was conducted in summer 2020, at the end of the first COVID-19 lockdown in France (March to May 2020). Sleep health was assessed using the RU-SATED v2.0 scale (RegUlarity, Satisfaction, Alertness, Timing, Efficiency, Duration). Emotional exhaustion was used as a proxy for overall burnout. Of 1069 participating French healthcare workers, 474 (44.3%) reported good sleep health (RU-SATED > 8) and 143 (13.4%) reported emotional exhaustion. Males and nurses had a lower likelihood of emotional exhaustion than females and physicians, respectively. Good sleep health was associated with a 2.5-fold lower likelihood of emotional exhaustion and associations persisted among healthcare workers without significant anxiety and depressive symptoms. Longitudinal studies are needed to explore the preventive role of sleep health promotion in terms of the reduction in burnout risk.

Cross-cultural adaptation and validation of the Chinese version of the Sleep Health Index

OBJECTIVE

To generate the Chinese Sleep Health Index (SHI-C) in Mandarin with cross-cultural adaptations and test its psychometric properties.

METHODS

This study used a cross-sectional design. Health science students were included (N = 271) and a sub-set (n = 74) was invited for the re-test. Cross-cultural adaptation of the SHI-C was performed prior to formal validation. The SHI-C, Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Bedtime Procrastination Scale, and Sleep Hygiene Index were used to measure variables of interest. Exploratory factor analysis was used to evaluate the structure validity. Bivariate analyses were used to evaluate the construct validity.

RESULTS

Exploratory factor analysis identified 3 factors (ie, sleep quality, sleep duration, and disordered sleep) accounting for 55.6% of the total variance. The SHI-C total and sleep quality sub-index scores were significantly associated with both PSQI global score (r = -0.132, p < .05; r = -0.182, p < .01, respectively) and ISI score (r = -0.655, p < .05; r = -0.820, p < .05, respectively). SHI-C total, sleep quality sub-index, and sleep duration sub-index scores were significantly associated with Bedtime Procrastination Scale and Sleep Hygiene Index scores (r = -0.238 to -0.368, p < .05). Students with insomnia (ISI > 9) or poor sleep quality (PSQI > 5) had significantly lower SHI-C scores than those without (73.5 vs. 89.0, p < .01; 84.1 vs. 86.7, p < .05, respectively). SHI-C showed good internal consistency (Cronbach's alpha = 0.73) and test-retest reliability (intraclass correlation coefficient = 0.82).

CONCLUSIONS

The SHI-C demonstrated good validity and adequate reliability in a Chinese sample of health science students. It could be used to measure sleep health in future research and practice. Psychometric properties of the SHI-C among other Chinese populations remain to be confirmed.

Sleep health of Australian community tennis players during the COVID-19 lockdown

Background

Poorer sleep health outcomes have been documented in the general population during the COVID-19 outbreak. However, the impact of the COVID-19 outbreak on sleep health outcomes in specific population groups, including the sporting community, has not been extensively investigated. This study evaluated sleep health outcomes and their relationship with lifestyle behaviours during the initial COVID-19 lockdown period in Australian community tennis players.

Methods

This cross-sectional study evaluated sleep health outcomes and lifestyle behaviours using an online survey. The survey was disseminated online between the 24th of April and the 6th of June 2020 and comprised the Sleep Health Index, Sleep Satisfaction Tool and questions regarding weekly hours of tennis play, general physical activity, training location and alcohol consumption. Two-hundred and eighty-five individuals completed the survey.

Results

Compared to normative data, respondents displayed positive sleep health values during the initial COVID-19 lockdown period, with median values (IQR) of 85.3 (73.4, 91.7) and 64.8 (54.4, 73.4) for the Sleep Health Index and Sleep Satisfaction Tool, respectively. Sleep health outcomes were not significantly correlated (p > 0.05) with tennis play (Tb = 0.054-0.077), physical activity (Tb = -0.008 to 0.036), training location (Tb = -0.012 to -0.005) or alcohol consumption (Tb = -0.079 to -0.018).

Conclusion

Positive sleep health values were observed in Australian community-level tennis players during the initial COVID-19 pandemic. Sleep health values were not associated with lifestyle behaviours. Other unexplored factors may have influenced sleep health outcomes, including personal finances and socialisation, however these factors need to be investigated in future studies.