Cutoff scores and core items of the climate change anxiety scale in young adult Chinese participants: evidence from an online survey

Poor sleep quality, often resulting from poor sleep hygiene, is common among medical students. Educational interventions aimed at improving sleep knowledge are beneficial for sleep quality in healthy populations. However, sleep education is often given minimal attention in medical school curriculums. The aim of the study was to explore whether a short educational intervention could improve sleep knowledge, and consequently sleep quality, among medical students. We recruited preclinical- and clinical-stage medical students during the 2017-2018 academic year. Students completed a demographic survey, the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), and the Assessment of Sleep Knowledge in Medical Education (ASKME) questionnaire. Students then attended a lecture on the physiology and importance of sleep. To assess the efficacy of the intervention, questionnaires were repeated 4 months thereafter. A total of 87 students (31 preclinical) with a mean age of 25.86 years (standard deviation [SD], 3.33), 51 of whom were women, participated in the study. At baseline, students had poor sleep quality with a PSQI mean score of 5.9 (SD, 2.37), without significant sleepiness, and a mean ESS score of 8.86 (SD, 4.32). The mean ASKME scores were consistent with poor sleep knowledge at 11.87 (SD, 4.32). After the intervention, the mean ASKME results improved to 14.15 (SD, 4.5; P < .001), whereas sleep quality did not. The effect was similar in preclinical and clinical medical students. Sleep knowledge was inadequate among medical students, who also experienced poor sleep quality. A short educational intervention improved sleep knowledge but was insufficient at improving sleep quality. Further studies are needed to determine which interventions may provide benefit in both sleep knowledge and sleep quality.

Inappropriate sleep duration and poor sleep quality are associated with risk of stroke, but their interactive effect on stroke is unknown. We explored the interactive effect of sleep quality and duration on stroke risk. A prospective cohort study was conducted with 41,786 adults. Sleep quality was assessed using the Pittsburgh Sleep Quality Index. Sleep duration was measured by average hours of sleep per night. Cox regression models were used to calculate the association of sleep duration and quality with stroke. The delta method and a non-conditional logistic regression model were used and the relative excess risk due to interaction (RERI), the attributable proportion (AP), and the synergy index (S) were calculated. Compared with sleep duration 6–8 h/day, the risk ratio of stroke was 1.63 (1.23–2.11) times for sleep duration <6 h/day and 1.40 (1.08–1.75) times for >8 h/day. The stroke risk ratio was 2.37 (1.52–3.41) times in subjects with poor sleep quality compared with those with good sleep quality. Women who slept <6 h/day had higher stroke risk than men who slept <6 h/day. Men who slept >8 h/day had higher stroke risk than women who slept >8 h/day. Men with poor sleep quality had higher stroke risk than women with poor sleep quality. Stroke was associated with short/long sleep duration and poor sleep quality in subjects aged >46 years, compared with those aged 18–45 years. Stroke occurred more frequently in subjects with poor sleep quality combined with short sleep duration (odds ratio: 6.75; 95% confidence interval (CI): 2.45–14.12). RERI, AP, and S values (and their 95% CIs) were 5.54 (3.75–8.12), 0.72 (0.56–0.80), and 5.69 (4.23–9.90) for the poor sleep quality interact with short sleep duration. In persons with poor sleep quality accompanied by long sleep duration, RERI, AP, and S (95% CI) were 1.12 (1.01–1.27), 0.35 (0.26–0.51), and 2.05 (1.57–2.96), respectively. Subjective sleep disturbances are related with risk of stroke in Chinese adults. There are additive interactions between short/long sleep duration and poor sleep quality that affect risk of stroke.

IntroductionUnderstanding health behaviors, such as sleep and dietary patterns, is important for health promotion and disease prevention. College period is a complicated, difficult time to maintain healthy behaviors. In this regard, little is known about the impact of sleep and diet quality on well-being among college young adults. Hence, we aimed to study the impact of sleep and diet quality on well-being in college students.Materials and MethodsThree hundred-twelve Mexican college students (82% females; 20.6 ± 3.4years) were included in a cross-sectional study. Participants completed the following validated questionnaires: Well-being Index to assess well-being (high scores indicate high well-being), Pittsburg Sleep Quality Index for sleep quality (scores &gt; 5 indicate poor sleep quality), and a validate version of the Health Eating Index for Mexican population to assess diet quality (scores &gt; 80 indicate good diet quality). BMI and physical activity were also assessed. Scores were treated as continuous variables, and statistical analysis were performed using SPSS v24 and adjusted for confounding variables.ResultsSixty-seven percent of our population showed a poor sleep quality and eighty-four percent needs to make changes in their diet in order to improve its quality. On the other hand, fifty-one percent of the studied population had a low well-being perception. Poor sleep quality (p &lt; 0.001) and low diet quality (p &lt; 0.001) associated with a lower well-being perception. In addition, poor sleep quality is associated with low diet quality (p &lt; 0.05). Regarding food consumption, higher sweets (p &lt; 0.001) and soft-drink (p &lt; 0.001) intake was inversely associated with well-being scores. Likewise, high consumption of sweets (p &lt; 0.05) and soft-drink (p &lt; 0.05), and low fruit (p &lt; 0.05) and cereal (p &lt; 0.05) consumption are linked to poor sleep quality.DiscussionOur results show that half of the studied population had a low well-being, and also that poor sleep and diet quality are frequent among college students. Interestingly, the fact that poor sleep and diet quality were associated to a lower perception of well-being highlights the importance of promoting sleep hygiene and diet quality among college students as an important strategy to improve well-being and health, even in young adults. In addition, we found that higher sweets and soft-drink consumption were associated to both low well-being perception and poor sleep quality. Hence, it is important to promote healthy habits regarding eating and sleeping well, in order to improve well-being perception among college students.

The impact of hospitalization on sleep in late-life is underexplored. The current study examined patterns of sleep quality before, during, and following hospitalization, investigated predictors of sleep quality patterns, and examined predictors of classification discordance between two suggested clinical cutoffs used to demarcate poor/good sleep. This study included older adults (n = 163; mean age 79.7 ± 6.9 years, 31% female) undergoing inpatient post-acute rehabilitation. Upon admission to inpatient post-acute rehabilitation, patients completed the Pittsburgh Sleep Quality Index (PSQI) retrospectively regarding their sleep prior to hospitalization. They subsequently completed the PSQI at discharge, and 3 months, 6 months, 9 months, and 1 year post discharge. Patient demographic and clinical characteristics (pain, depression, cognition, comorbidity) were collected upon admission. Using latent class analysis methods, older adults could be classified into (1) Consistently Good Sleepers and (2) Chronically Poor Sleepers based on patterns of self-reported sleep quality pre-illness, during, and up to 1 year following inpatient rehabilitation. This pattern was maintained regardless of the clinical cutoff employed (> 5 or > 8). Logistic regression analyses indicated that higher pain and depressive symptoms were consistently associated with an increased likelihood of being classified as a chronic poor sleeper. While there was substantial classification discordance based on clinical cutoff employed, no significant predictors of this discordance emerged. Clinicians should exercise caution in assessing sleep quality in inpatient settings. Alterations in the cutoffs employed may result in discordant clinical classifications of older adults. Pain and depression warrant detailed considerations when working with older adults on inpatient units when poor sleep is a concern.

PurposeThe relationships between sleep quality and sleep hygiene awareness in the Chinese population were unclear. We aimed to investigate the associations and related factors between sleep quality and sleep hygiene awareness in adults and to identify the most central domain for sleep quality using network analysis.MethodsA cross-sectional survey was conducted from April 22 to May 5, 2020. Adults (18 years old or above) who had access to smartphones were invited to participate in this survey. The Pittsburg Sleep Quality Index (PSQI) and the Sleep Hygiene Awareness and Practice Scale (SHAPS) were used to evaluate the sleep quality and sleep hygiene awareness of the participants. Propensity score matching (PSM) was used as sensitivity analysis to reduce the confounding effects. Multiple logistic regression was performed to evaluate the associations. The R packages “bootnet” and “qgraph” were used to estimate the connection and calculate the network centrality indices between good and poor sleepers.ResultsIn total, 939 respondents were included in the analysis. Of them, 48.8% (95% CI: 45.6–52.0%) were identified as poor sleepers. Participants with nervous system diseases, psychiatric diseases, and psychological problems were more likely to have poor sleep quality. The notion that using sleep medication regularly was beneficial to sleep was associated with poor sleep quality. Similarly, the notion that waking up at the same time each day disrupted sleep was also associated with poor sleep quality. The findings were consistent before and after PSM. Subjective sleep quality was the most central domain for sleep quality in good and poor sleepers.ConclusionPoor sleep quality was positively associated with certain sleep hygiene notions in Chinese adults. Effective measures such as self-relief, sleep hygiene education, and cognitive behavioral treatment may have been needed to improve sleep quality, especially during the COVID-19 outbreak.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11325-023-02798-0.

The aims of this study were to examine: (1) the association between sociodemographic and lifestyle factors and sleep quality in a population-based cohort of Australian women and (2) possible influence of reproductive status and mental and physical health factors on these associations. Data on 3,655 women (mean age = 46.6 years, range 34.3-67.4) were obtained from the Mater Hospital University of Queensland Study of Pregnancy for this cross-sectional study. Self-rated sleep quality was assessed using the Pittsburgh Sleep Quality Index. For the purpose of this study, two cutoff points (scores 5 and 10) were used to divide women into three categories: normal (65.2%), moderately poor (26.4%), and very poor sleep quality (8.5%). Other covariates were measured at 21-year follow-up as well. After adjusting for reproductive status, mental and physical health, there were significant associations between moderately poor sleep quality and education and between very poor sleep quality and unemployment, both measures of socioeconomic status. In addition, work-related exertion was associated with increased rates of moderately poor sleep quality, whereas those women undertaking moderate exercise were less likely to experience very poor sleep quality. Independent associations between sociodemographic factors and exercise with moderately poor and very poor sleep quality were identified. These findings demonstrate the dynamic nature of the association between exercise/exertion, socioeconomic status, and sleep quality and highlight the importance of taking these into consideration when dealing with issues of poor sleep quality in women.

Background: Approximately 40% of the population reports sleep problems such as poor quality sleep and insufficient sleep duration. Physical activity (PA) can help improve sleep, but data on whether PA intensity or duration is most strongly associated with sleep are lacking. In addition, given that sedentary behaviour (e.g., TV, computer use) is distinct from physical inactivity, the association between sedentary behaviour and sleep in young adults needs to be characterized. Objective: To describe the relationships between sleep quality and sleep duration and (1) frequency and duration of light, moderate, and vigorous PA, and (2) different types of sedentary behaviours (TV, computer, reading) in young adults. Methods: Self-report data for 658 participants were from the 22nd wave of the Nicotine Dependence in Teens (NDIT) cohort study (mean age=24.0 years, 46% male [300 of 658]). PA measures assessed frequency (number of days) and minutes of light, moderate and vigorous PA in the past week. Sedentary measures assessed number of hours spent reading, watching TV, and using the computer per day. Sleep measures included (1) the Pittsburgh Sleep Quality Index (PSQI) which assessed seven dimensions of sleep (daytime dysfunction, disturbances, duration, efficiency, latency, quality, use of sleeping medications), (2) general sleep quality, and (3) sleep duration in the past month. General sleep quality and sleep duration were two separate additional measures distinct from similar PSQI items (r=0.73 between general sleep quality and PSQI score; r=0.69 between sleep duration and PSQI score). Data were analyzed using multiple linear regression. Due to evidence of non-normality the PSQI score was log-transformed. Results: Controlling for age, sex, and maternal education, each additional day of light or vigorous PA was associated with 3 minutes less sleep per night (p&lt;0.05). Each additional 10 minutes of moderate PA was associated with greater general sleep quality (β=0.004, p=0.04). TV was associated with a poorer PSQI score (β=0.01, p&lt;0.05) and each additional hour of reading was associated with 2 minutes less sleep per night (p=0.04). Computer use was associated with a poorer PSQI score (β=0.02, p=0.005) and poorer sleep quality (β=-0.02, p=0.05). Results were similar when sedentary and PA measures were included in the same model. The inclusion of body mass index, self-rated mental and general health, and stress did not affect the results and were omitted from the final models. Conclusion: PA and sedentary behaviours are independently associated with sleep duration and quality. Sedentary behaviours are associated with poorer sleep duration and quality. In contrast, PA frequency may decrease sleep duration while PA duration may improve sleep quality. Clinicians who treat sleep problems in young adults may need to take PA and sedentary behavior into account in treatment plans.

Regular exercise may be associated with better self-rated health and sleep status. However, this correlation among various age groups, such as young, middle-aged, and older people, as well as during the COVID-19 pandemic, has not been examined. This study examined the correlation between regular exercise and self-rated health and sleep quality among adults in Japan during the COVID-19 pandemic. Data were collected using an online survey conducted between February 26 and 27, 2021. A total of 1410 adults in Japan (age range, 20–86 years) completed the online survey. Regular exercise was divided into: (1) more than 30 min of moderate exercise a day, (2) more than 2 days per week, and (3) continuous for 1 year or longer. Self-rated health and sleep quality were assessed using the Likert scale. After adjusting for multiple confounders, regular exercise was correlated with decreased poor self-rated health and poor sleep quality in middle-aged adults; however, no significant correlation was observed among young and older adults. The promotion of regular exercise among middle-aged people during the COVID-19 pandemic may contribute to better self-rated health and sleep quality status.

This study aimed to determine the prevalence and associated factors of depressive symptoms, poor sleep, and life quality among patients with systemic sclerosis (SSc). This was a cross-sectional study including 120 SSc patients. Demographic and clinical data were obtained. The Short Form Health Survey 36 (SF-36), Pittsburgh Sleep Quality Index (PSQI), and short form of the Beck Depression Questionnaire were used to evaluate life quality, sleep quality, and self-reported depressive symptoms, respectively. The obtained data were analyzed to identify the demographic and clinical risk associations for depressive symptoms, poor sleep, and life quality. Of 120 participants, 108 patients (90%) were female. The mean age was 42.23 years, and the mean disease duration was 13.58 years. Most of the patients were married, unemployed, or housekeepers. Most of them had moderate economic conditions and tertiary education. The total scores of the SF-36 and PSQI questionnaires were 93.25±3.7 and 9.02±4.51, respectively, which showed good life quality but poor sleep quality. The prevalence of depressive symptoms was 44.16% (n=53), and most of them had mild to moderate depressive symptoms. The factors that correlated with life quality were occupational status and cough. The factors that negatively correlated with sleep quality were the presence of digital ulcers, cough, and dysphasia. The presence of cough, dyspnea, and gastroesophageal reflux disease was associated with depressive symptoms. Our study showed a high prevalence of poor sleep quality and depressive symptoms among SSc patients. We found that gastrointestinal symptoms, respiratory symptoms, and digital ulcers affected patients' life quality, sleep quality, and mental status. Our results also demonstrated that depression was correlated with poor sleep quality, and they were both risk factors for diminished life quality. Identification of these factors would help to make pharmacological and non-pharmacological interventions to improve the quality of life and sleep in SSc patients.

Disturbances in circadian rhythms are common among night-shift workers and result in poor sleep quality. Nevertheless, the heterogeneity of circadian rhythms and their relationship with sleep quality is less explored in nursing interns. Therefore, we aimed to identify the latent subtypes of circadian rhythm, explore their relationship with sleep quality, and evaluate their moderating role between perceived stress and sleep quality in nursing interns. In all, 452 nursing interns were recruited between October 2020 and January 2021 from Be Resilient to Nursing Career (BRNC), which is a multicenter, prospective cohort of a career growth program for nursing students. They were assessed using the 10-item Chinese Perceived Stress Scale, Circadian Type Inventory, and Pittsburgh Sleep Quality Index. Latent profile analysis and moderation analysis were performed. Overall, 72.3% of the nursing interns reported poor sleep quality. We identified three latent subtypes of circadian rhythms, namely, Vigorousness (40.1%), Inadaptability (18.6%), and Flexibility (41.1%). Females (OR = 1.97, 95% Cl: 1.01-3.83, P = 0.047) with normal body mass index (OR = 1.62, 95% CI: 0.95-2.76, P = 0.078) were prone to Flexibility. Circadian rhythm types significantly moderated the association between perceived stress and sleep quality (P < 0.05). Nursing interns suffer from poor sleep. There exists heterogeneity of circadian rhythm subtypes in nursing interns, and attention should be paid to those with Inadaptability type. The association between perceived stress and sleep quality is significantly moderated by circadian rhythm subtypes.

ObjectivesWe examined the associations of estimated allocations of time spent in physical activity, sedentary behavior and sleep with self-rated sleep quality. MethodsBetween 2011 and 2016, 1918 participants (mean age 71 ± 9 years, 51% women) from the population-based Rotterdam Study were included. Durations of light physical activity, moderate-to-vigorous physical activity, sedentary behavior, and sleep were assessed by accelerometry, self-rated sleep quality with the Pittsburgh Sleep Quality Index. Associations were assessed with compositional isotemporal substitution analyses. ResultsSpending 30 minutes more in sedentary behavior (adjusted mean difference in PSQI score: 0.21, 95% confidence interval [0.15; 0.28] or in light physical activity (adjusted mean difference in PSQI score: 0.25 [0.03; 0.46], and 30 minutes less in sleep, was associated with poorer sleep quality. ConclusionsOur findings suggest reducing sedentary behavior and increasing sleep duration might be a potential intervention target to improve sleep quality in this population of middle-aged and older adults.

Sleep duration and quality in relation to non-alcoholic fatty liver disease in middle-aged workers and their spouses

Tinnitus is a common disorder, but its impact on daily life varies widely in population-based samples. It is unclear whether this interference in daily life is associated with mental health problems that are commonly detected in clinical populations. To investigate the association of tinnitus and its interference in daily life with symptoms of depression and anxiety and poor sleep quality in a population-based sample of middle-aged and elderly persons in a cross-sectional analysis and during a 4-year follow-up. This cohort study evaluated data from the population-based Rotterdam Study of individuals 40 years or older living in Rotterdam, the Netherlands. Between 2011 and 2016, data on tinnitus were obtained during a home interview at least once for 6128 participants. Participants with information on depressive and anxiety symptoms and self-rated sleep quality, with Mini-Mental State Examination scores indicating unimpaired cognition, and with repeatedly obtained tinnitus and mental health outcome data were included. Data analyses were conducted between September 2019 and April 2020. The presence of tinnitus and its interference with daily life were assessed during a home interview. Depressive symptoms were assessed with the Center for Epidemiologic Studies-Depression, anxiety symptoms with the Hospital Anxiety and Depression Scale, and sleep quality with the Pittsburgh Sleep Quality Index. Linear regression analyses and linear mixed models adjusted for relevant confounders were used to assess the cross-sectional and longitudinal association of tinnitus with mental health. Of 5418 complete-case participants (mean [SD] age, 69.0 [9.8] years; 3131 [57.8%] women), 975 (mean [SD] age, 71.7 [4.5] years; 519 [53.2%] women) had repeated measurements available for follow-up analyses. Compared with participants without tinnitus and participants with nonbothersome tinnitus, participants with tinnitus interfering with daily life reported more depressive (difference, 0.20; 95% CI, 0.11-0.28) and anxiety (difference, 0.15; 95% CI, 0.08-0.22) symptoms and poorer sleep quality (difference, 0.10; 95% CI, 0.03-0.16). Compared with participants without tinnitus, participants with nonbothersome tinnitus also reported more depressive (difference, 0.06; 95% CI, 0.03-0.09) and anxiety (difference, 0.05; 95% CI, 0.02-0.07) symptoms and poorer sleep quality (difference, 0.05; 95% CI, 0.03-0.08). Individuals indicating more interference with daily life reported having more mental health problems. During a mean follow-up of 4.4 years (range, 3.5-5.1 years), participants with tinnitus reported more anxiety symptoms and poorer sleep quality than those without tinnitus. Findings of this population-based cohort study indicate that tinnitus was associated with more mental health problems in middle-aged and elderly persons in the general population, in particular when tinnitus interfered with daily life but not solely. Over time, more severe tinnitus was associated with an increase in anxiety symptoms and poor sleep quality. This outcome suggests that mental health problems may be part of the burden of tinnitus, even among individuals who do not report their tinnitus interfering with daily life.

To explore the relationship between sleep duration, sleep quality and the occurrence of cognitive frailty in the older adults. A total of 9,970 participates were screened in China over the past 9 years. They were divided into cognitive frailty group and non-cognitive frailty groups, and they were evaluated for sleep duration and sleep quality and their relationship with cognitive frailty was analyzed. If interactions are found, further hierarchical analysis is conducted. One thousand six hundred eighty-four participants (16.89%) were diagnosed with cognitive frailty. Participants with cognitive frailty were more likely to be "unmarried," live in rural areas, and were female, with no social activity in the last month. Poor sleep quality, short sleep duration, no napping, and excessive napping are at high risk of cognitive frailty. There was a significant interaction between daytime napping and sleep duration and sleep quality. Among participants with good sleep quality, those who took excessive naps had a 123% increased risk of developing cognitive frailty, with an OR of 2.23 (95% CI: 1.72, 2.86). In the subgroup with sleep duration > 9 h, participants who napped excessively had a significantly increased risk of cognitive frailty (OR = 1.62, 95% CI 1.14-2.30, p < 0.001). Chinese older adults with poor sleep quality are at a 67% higher risk of cognitive weakness, and individuals with less than 6 h of sleep are at a 48% higher risk of cognitive weakness; No napping and excessive napping, the risk of cognitive debilitation increased by 23 and 69%, respectively. There is an additive interaction between sleep duration and quality and daytime napping on cognitive frailty in the older adults.

Introduction: Given that no consensus has yet been reached over the optimal cut-off points of waist circumference (WC) for Chinese, this study aimed to determine the appropriate cut-off points of WC for detecting central obesity and severe central obesity in a Chinese adult population. Methods: Data from the cross-sectional survey of the PRC-USA Collaborative study of Cardiovascular and Cardiopulmonary Epidemiology in 1993-1994 was used, including 10265 subjects (4921 men and 5344 women) aged 35-69 years. Each integer of WC in centimeters was used as the cut-off point to detect clustering of cardiovascular risk factors, which was defined as the presence of two or more risk factors among hypertension, diabetes, hypercholesterolemia, hypertriglyceridemia and low levels of high-density lipoprotein cholesterol. Based on the Receiver operating characteristic (ROC) curve analysis, the WC value corresponding to the point on the ROC curve nearest to the upper left corner of the ROC graph was considered the optimal cut-off for central obesity and the value corresponding to the point with specificity of 90% or more was considered the optimal cut-off for severe central obesity. Results: The optimal cut-off value of WC to detect clustering of risk factors was ≥84 cm for men and was ≥80 cm for women with the shortest distance to the upper left corner being 0.4304 and 0.4504, respectively. The cut-off values of WC with specificity above 90% were ≥93 cm and ≥91 cm for men and women respectively. Conclusions: These results were equal or similar to the WC cut-off points proposed by the Guidelines for Prevention and Control of Overweight and Obesity in Chinese Adults, i.e., ≥85/80 cm (men/women) for increased risk for obesity related diseases and ≥95/90 cm (men/women) for much higher risk. For practical reasons, WC≥85/80 cm and ≥95/90 cm (men/women) could be the optimal cut-off values for detecting central obesity and severe central obesity, respectively, in Chinese adult population.