Age and sex differences in bedroom habits and bedroom preferences

Investigating the influence of an adjustable zoned air mattress on sleep: a multinight polysomnography study

Introduction

A comfortable mattress should improve sleep quality. In this study, we sought to investigate the specific sleep parameters that could be affected by a mattress and explore any potential differences between the effects felt by each sex.

Methods

A total of 20 healthy young adults (10 females and 20 males; 22.10 ± 1.25 years) participated in the experiments. A smart adjustable zoned air mattress was designed to maintain comfortable support, and an ordinary mattress was used for comparison. The participants individually spent four nights on these two mattresses in four orders for polysomnography (PSG) scoring. Sleep architecture, electroencephalogram (EEG) spectrum, and heart rate variability (HRV), which reflect the central and autonomic nervous activities, were used to compare the difference between the two mattresses.

Results

An individual difference exited in sleep performance. The modes of influence of the mattresses were different between the sexes. The adjustable air mattress and the increase in experimental nights improved female participants' sleep efficiency, while male participants exhibited a smaller response to different mattresses. With an increasing number of experiment nights, both sexes showed increased REM and decreased N2 proportions; the N3 sleep proportion decreased in the male participants, and the heart rate decreased in both sexes. The performance of the EEG spectrum supports the above results. In addition, the adjustable air mattress weakened automatic nerve activity during N3 sleep in most participants. The female participants appeared to be more sensitive to mattresses. Experiment night was associated with psychological factors. There were differences in the results for this influence between the sexes.

Conclusion

This study may shed some light on the differences between the ideal sleep environment of each sex.

Assessing the indoor air quality and their predictor variable in 21 home offices during the Covid-19 pandemic in Norway

In this study, concentrations of pollutants: formaldehyde, carbon dioxide (CO₂), and total volatile organic compounds (TVOC) and parameters: indoor room temperature and relative humidity (RH) were measured in 21 home offices for at least one week in winter in Trondheim, Norway. Eleven of these were measured again for the same duration in summer. Potentially explanatory variables of these parameters were collected, including building and renovation year, house type, building location, trickle vent status, occupancy, wood stove, floor material, pets, RH, and air temperature. The association between indoor air pollutants and their potential predictor variables was analyzed using generalized estimation equations to determine the significant parameters to control pollutants. Significantly seasonal differences in concentrations were observed for CO₂ and formaldehyde, while no significant seasonal difference was observed for TVOC. For TVOC and formaldehyde, trickle vent, RH, and air temperature were among the most important predictor variables. Although higher concentrations of CO₂ were measured in cases where the trickle vent was closed, the most important predictor variables for CO₂ were season, RH, and indoor air temperature. The formaldehyde concentrations were higher outside working hours but mostly below health thresholds recommendations; for CO₂, 11 of the measured cases had indoor concentrations exceeding 1000 ppm in 10% of the measured time. For TVOC, the concentrations were above the recommended values by WHO in 73% of the cases. RH was generally low in winter. The temperature was generally kept over the recommended level of 22-24 °C during working hours.

A survey of bedroom ventilation types and the subjective sleep quality associated with them in Danish housing

We performed a survey of the types of bedroom ventilation in Danish dwellings (January-February 2020) and the associated subjective sleep quality. Five hundred and seventeen people responded. Their median age was 33 years old and 55.4% of them were males. We used an online questionnaire and collected information on the type of bedroom ventilation, bedroom airing behaviour by the respondents, the bedroom environment, building surroundings and location, and sleep disturbance caused by stuffy air, noise, and the thermal environment. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI); its median among respondents was >5 indicating reduced sleep quality. 35.4% of the bedrooms had mechanical, 24.6% exhaust, and 40.0% natural ventilation. Sleeping in a bedroom with mechanical ventilation tended to reduce sleep disturbance. The absence of mechanical ventilation and the presence of carpet in the bedroom were all associated with stuffy air causing sleep disturbance, which was the second most sleep disturbing factor. PSQI increased significantly with increased sleep disturbance. People who reported that their sleep was disturbed by stuffy air or "too warm" conditions opened windows frequently during the day or night, but no association was found between PSQI and bedroom airing behaviours. Our results are valid for the heating season and the survey would have to be repeated in the non-heating season to permit generalization of the findings. The results present associations and are qualitative, so field measurements are necessary to validate the present observations and provide further explanations.

Environmental factors affecting sleep quality in summer: a field study in Shanghai, China

Although the environment can greatly influence an individual's sleep quality, China is yet to conduct comprehensive research on the topic. This study investigated the bedroom environment and sleep quality of 41 households during summer in Shanghai. Bedroom environments were comprehensively evaluated through environmental perception questionnaires filled by participants after waking up every morning. Parameters, such as air temperature, relative humidity, CO₂ concentration, and noise level were continuously monitored. Furthermore, participants' sleep quality was observed using both subjective questionnaires and physiological measures. Environmental measurements showed that the most comfortable air temperature and relative humidity was 24.8 °C and 64%, respectively. Physiological measurements showed that the average duration of slow wave sleep (SWS) and sleep efficiency (SE) was 73.8 min and 86.7%, respectively. Additionally, SWS was negatively correlated with air temperature (r = -0.377, p = 0.015) and CO₂ concentration (r = -0.362, p = 0.02), and SE was negatively correlated with noise level (r = -0.32, p = 0.042). The subjective and objective results consistently indicated that higher air temperature, CO₂ concentration, and noise level leads to poor sleep quality in summer. In addition, air temperature and CO₂ concentration had a greater impact on the sleep quality of males, while noise level had a greater impact on the sleep quality of females.

Efficacy of a Theory-Based Cognitive Behavioral Technique App-Based Intervention for Patients With Insomnia: Randomized Controlled Trial

Background

Sleep hygiene is important for maintaining good sleep and reducing insomnia.

Objective

This study examined the long-term efficacy of a theory-based app (including cognitive behavioral therapy [CBT], theory of planned behavior [TPB], health action process approach [HAPA], and control theory [CT]) on sleep hygiene among insomnia patients.

Methods

The study was a 2-arm single-blind parallel-group randomized controlled trial (RCT). Insomnia patients were randomly assigned to a treatment group that used an app for 6 weeks (ie, CBT for insomnia [CBT-I], n=156) or a control group that received only patient education (PE, n=156) through the app. Outcomes were assessed at baseline and 1 month, 3 months, and 6 months postintervention. Primary outcomes were sleep hygiene, insomnia, and sleep quality. Secondary outcomes included attitudes toward sleep hygiene behavior, perceived behavioral control, behavioral intention, action and coping planning, self-monitoring, behavioral automaticity, and anxiety and depression. Linear mixed models were used to evaluate the magnitude of changes in outcomes between the two groups and across time.

Results

Sleep hygiene was improved in the CBT-I group compared with the PE group (P=.02 at 1 month, P=.04 at 3 months, and P=.02 at 6 months) as were sleep quality and severity of insomnia. Mediation analyses suggested that perceived behavioral control on sleep hygiene as specified by TPB along with self-regulatory processes from HAPA and CT mediated the effect of the intervention on outcomes.

Conclusions

Health care providers might consider using a CBT-I app to improve sleep among insomnia patients.

Trial Registration

ClinicalTrials.gov NCT03605732; https://clinicaltrials.gov/ct2/show/NCT03605732