The relationship of sleep complaints risk factors with sleep phase, quality, and quantity in Japanese workers

Insomnia symptoms and related factors in a community-based population: The Yamagata Cohort study

Objective/background

Insomnia is prevalent and is a risk factor for the development of lifestyle-related diseases and early death. To improve insomnia, it is necessary to identify the factors that affect it. This study investigated the associations between insomnia symptoms and mental, physical, and environmental factors in the general Japanese population.

Patients/methods

The study participants were 7,873 individuals who responded to the Health and Lifestyle Survey questionnaire that included sleep-related items between December 2021 and March 2022. Insomnia symptoms were defined as a score of 6 or higher on the Athens Insomnia Scale (AIS). A multivariate logistic regression analysis was performed to identify factors independently associated with insomnia symptoms.

Results

Of all subjects, 23.4% had insomnia symptoms. Factors associated with insomnia symptoms were older age, female sex, very difficult living conditions on current income, pain/discomfort, anxiety, lack of happiness, frequent nocturia, long duration from bathing time to bedtime, bedroom lighting, and short walking duration. The subgroup analysis showed stronger associations between walking time in men, higher body mass index in women, time from bathing time to bedtime, and daily walking duration in older adults.

Conclusions

Insomnia symptoms were common in community-based populations and were independently associated with three different factor groups including physical, psychological, and environmental factors. Improvements in insomnia symptoms require appropriate practical support tailored to an individual's situation.

Associations of bedroom PM2.5, CO2, temperature, humidity, and noise with sleep: An observational actigraphy study

OBJECTIVE

Climate change and urbanization increasingly cause extreme conditions hazardous to health. The bedroom environment plays a key role for high-quality sleep. Studies objectively assessing multiple descriptors of the bedroom environment as well as sleep are scarce.

METHODS

Particulate matter with a particle size <2.5 µm (PM2.5), temperature, humidity, carbon dioxide (CO2), barometric pressure, and noise levels were continuously measured for 14 consecutive days in the bedroom of 62 participants (62.9% female, mean ± SD age: 47.7 ± 13.2 years) who wore a wrist actigraph and completed daily morning surveys and sleep logs.

RESULTS

In a hierarchical mixed effect model that included all environmental variables and adjusted for elapsed sleep time and multiple demographic and behavioral variables, sleep efficiency calculated for consecutive 1-hour periods decreased in a dose-dependent manner with increasing levels of PM2.5, temperature, CO2, and noise. Sleep efficiency in the highest exposure quintiles was 3.2% (PM2.5, p < .05), 3.4% (temperature, p < .05), 4.0% (CO2, p < .01), and 4.7% (noise, p < .0001) lower compared to the lowest exposure quintiles (all p-values adjusted for multiple testing). Barometric pressure and humidity were not associated with sleep efficiency. Bedroom humidity was associated with subjectively assessed sleepiness and poor sleep quality (both p < .05), but otherwise environmental variables were not statistically significantly associated with actigraphically assessed total sleep time and wake after sleep onset or with subjectively assessed sleep onset latency, sleep quality, and sleepiness. Assessments of bedroom comfort suggest subjective habituation irrespective of exposure levels.

CONCLUSIONS

These findings add to a growing body of evidence highlighting the importance of the bedroom environment-beyond the mattress-for high-quality sleep.

Quality of Sleep and Work Productivity among White-Collar Workers during the COVID-19 Pandemic

Background and Objectives: The COVID-19 pandemic has disrupted routine sleep and work patterns in the general population. We conducted an anonymous online survey among white-collar workers from various finance, IT and technology companies in Lithuania to define factors associated with worse sleep quality and diminished productivity during a COVID-19 lockdown. Materials and Methods: Employees of selected companies in Lithuania completed an anonymous questionnaire online that included the Pittsburgh Sleep Quality Index (PSQI), The Sleep Locus of Control (SLOC), the Generalized Anxiety Disorder Scale-7 (GAD-7), and the World Health Organization’s Health and Work Performance Questionnaire (WHO-HPQ). Respondents also provided information about their sleep hygiene, physical activity and alcohol use. Results: Data of 114 respondents (56, 49.1% male) were used for analysis. Among them, 49 (43.0%) suffered from poor sleep and 29 (25.4%) had clinically relevant levels of anxiety. However, there were only negligible levels of absenteeism in the sample (a median of zero hours of work lost over the past month). In a stepwise linear regression model (F(5,108) = 11.457, p < 0.001, R2adj = 0.316), high levels of anxiety, daily hours spent using the screen, use of electronic devices in the bedroom, smoking in the evening, and COVID-19-related changes in appetite were associated with worse sleep quality. Absenteeism was associated with physical activity of moderate intensity and decreased self-reported productivity during the pandemic (F(2,111) = 7.570, p = 0.001, R2adj = 0.104). However, there was no strong relationship between sleep-related variables (i.e., sleep hygiene, sleep locus of control, quality of sleep) or levels of anxiety and measures of work productivity. Conclusions: Our findings suggest that while bad sleep hygiene, anxiety, and changes in appetite are associated with worse sleep quality among white-collar workers during the pandemic, work productivity may remain high irrespective of disrupted sleep.

Short-term and long-term associations with sleep onset latency in school children in Japan

BACKGROUND

This study aims to examine the relationships between sleep onset latency and multiple sleep-related factors of seventh and tenth graders during the transition from childhood to adolescence.

METHODS

Regarding sleep onset latency, we examined the short-term associations in Phase IV (2002) and long-term associations in Phase V (2005) of the Toyama Birth Cohort Study. In total, 4,673 boys and 4,694 girls in Phase IV and 2,969 boys and 3,108 girls in Phase V answered the questionnaire items regarding sleep, physical and mental health, lifestyle, socioeconomic status, and family and school factors. Considering sleep onset latency as the outcome and 13 sleep-related factors as independent variables, we calculated the odds ratio using binary logistic regression. The longitudinal study was conducted with 1,703 boys and 1,919 girls whose sleep onset latency was within 30 min in Phase IV.

RESULTS

The following factors were found to be related to longer sleep onset latency in the short term: sleep duration, physical activity, game time, and self-esteem in boys and sleep duration, bedroom environment, game time, abdominal pain, long-standing illness, onset of puberty, mental health difficulties, and school avoidance feelings in girls. Regarding its long-term effects, having a single parent and self-esteem in boys and breakfast, game time, long-standing illness, obesity, onset of puberty, and school avoidance feelings in girls were associated with longer sleep onset latency.

CONCLUSIONS

Education of adolescent health and sleep hygiene at home and school should include both short-term and long-term associations between sleep and a healthy lifestyle by gender.

Effect of Long-Term Diving Exposure on Sleep of Male Occupational Divers in Southern Taiwan: A Cross-Sectional Study

OBJECTIVE

Divers with a history of decompression sickness may be at high risk for sleep problems. However, limited studies have investigated the relationship between diving exposure and sleep problems of occupational divers. This study investigated the association between diving exposure and sleep quality and quantity among male occupational divers in southern Taiwan.

METHODS

This descriptive, cross-sectional study included 52 occupational divers and 121 non-divers recruited from southern Taiwan in 2018. Survey data were collected using the Taiwanese version of the Hospital Anxiety and Depression Scale, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and a self-report questionnaire that included demographic variables, diving exposure/protocols, and factors associated with sleep quality.

RESULTS

Among all participants examined, occupational divers were significantly more likely to have both poor sleep quality (adjusted odds ratio [OR] = 3.00; 95% confidence interval [CI] = 1.48-6.06; P = 0.002) and excessive daytime sleepiness (adjusted OR = 4.49; 95% CI = 2.12-9.52; P < 0.001). The diving exposure time, depth, ascent rate, and decompression table use showed no significant associations between poor and good sleepers in the divers group. However, a history of decompression sickness was associated with poor sleep quality among divers (adjusted OR = 2.20; 95% CI = 1.07-4.54; P = 0.032).

CONCLUSIONS

Our results showed that occupational divers had poor sleep quality and more excessive sleepiness than non-divers. Decompression sickness likely contributes to poor sleep quality. Prevention and early detection of decompression sickness-related sleep problems should be an occupational health priority.

Daytime and nighttime smartphone use: A study of associations between multidimensional smartphone behaviours and sleep among 24,856 Danish adults

The around-the-clock smartphone use and its relation to disturbed sleep is a public health concern. The present study aimed to quantify the effects of different dimensions of smartphone behaviours (frequency of daytime use, problematic use, use before sleep and use during the sleep period) on disturbed sleep (sleep quality and sleep quantity) and to disentangle their inter-relationship in a large population-based sample of 24,856 Danish adults aged ≥16 years. Data come from the SmartSleep Experiment, which is a web-based survey carried out using a citizen science approach. Tested items were used to evaluate smartphone use and disturbed sleep was evaluated with the Karolinska Sleep Questionnaire (KSQ). Linear and multinomial logistic regression was employed to evaluate the relationship between smartphone use and disturbed sleep. While several of the smartphone measures were associated with disturbed sleep when assessed individually, smartphone use during the sleep period was the only dimension consistently associated with disturbed sleep when assessed independently of other smartphone behaviours. Weekly smartphone use during the sleep period versus no use was associated on average with a 0.96 point higher score (95% confidence interval [CI] 0.90-1.02) on the 5-point KSQ scale, and a higher risk of both short (odds ratio [OR] 1.32, 95% CI 1.08-1.62) and long (OR 1.94, 95% CI 1.63-2.32) sleep duration. Smartphone use during the sleep period is the factor strongest associated to disturbed sleep relative to other dimensions of smartphone use. Recommendations around smartphone use during the sleep period are warranted in order to protect the fundamentally important biological and mental processes of sleep.

Which sleep hygiene factors are important? comprehensive assessment of lifestyle habits and job environment on sleep among office workers

BACKGROUND

Although several lifestyle habits are associated with sleep, it is unclear which factors are important. Among office workers, the effect of job environment should also be considered. The multivariate analyses on the effects of lifestyle habits and job environment on sleep among office workers was conducted.

METHODS

A cross-sectional survey of 6,342 employees from 29 companies was conducted in 2017-2019. Complete responses and informed consent were provided by 5,640 participants. The survey examined demographic variables, sleep schedules, Pittsburgh Sleep Quality Index (PSQI), Brief Job Stress Questionnaire (BJSQ), and lifestyle habits.

RESULTS

Mean values were as follows: age, 36.9 years (±10.2); PSQI, 6.52 (±2.83); and total sleep time, 6h06m (±1h40m) on work days and 7h39m (±1h58m) on free days. After adjusting for job environment and demographic variables, irregular meal time (1.45-2.86), not eating vegetables every day (1.35), nightcap (2.74-3.55), weight gain (1.20-1.42), lack of sunlight in the morning in the bedroom (1.48-1.60), waking up before dawn (2.18), electronic display use in bed (1.50), and daily caffeine intake (1.27) were significantly associated with sleep disturbance. Irregular meal time (1.51-2.37), lack of morning breakfast (1.74-2.95), having dinner within 2 hours before bed time (0.49-0.64), not eating vegetables every day (1.52), lack of sunlight exposure in the morning (1.43-2.01), and caffeine use every day (1.42) were also associated with eveningness (p<.01).

CONCLUSION

Each sleep hygiene factor had a different effect size. Sleep hygiene interventions to promote worker sleep health should prioritize factors in accordance with effect size.

Mobile Phone Use and Mental Health. A Review of the Research That Takes a Psychological Perspective on Exposure

The purpose of this study was to carry out a review of observational studies that consider links between mobile phone use and mental health from a psychological or behavioral perspective. Systematic literature searches in PubMed and PsycINFO for articles published until 2017 were done. Exclusion criteria included: papers that considered radiofrequency fields, attention, safety, relational consequences, sexual behavior, cyberbullying, and reviews, qualitative, and case or experimental studies. A total of 4738 papers were screened by title and abstract, 404 were retrieved in full text, and 290 were included. Only 5% had any longitudinal design. Self-reporting was the dominating method of measurement. One third of the studies included children or youth. A majority of adult populations consisted of university students and/or self-selected participants. The main research results included associations between frequent mobile phone use and mental health outcomes, such as depressive symptoms and sleep problems. Mobile phone use at bedtime was associated with, e.g., shorter sleep duration and lower sleep quality. "Problematic use" (dependency) was associated with several negative outcomes. In conclusion, associations between mobile phone use and adverse mental health outcomes are found in studies that take a psychological or behavioral perspective on the exposure. However, more studies of high quality are needed in order to draw valid conclusions about the mechanisms and causal directions of associations.