Association between perceived environmental pollution and poor sleep quality: results from nationwide general population sample of 162,797 people

Determinants of subjective outdoor thermal comfort in an urban historic and cultural heritage landscape in Xi'an, China

In this study, we investigated factors related to subjective outdoor thermal comfort in the Ancient Ming Dynasty Walled City in Xi'an, China. Environmental data were collected from study sites by microclimate monitoring. Survey locations, demographics, psychological characteristics, thermal sensation vote (TSV), and thermal comfort vote (TCV) data were collected from 639 individuals in a questionnaire survey. Generalized linear regression analysis and path analysis were used to understand the associations between the TSV, environmental and psychological factors, and TCV. We found that green space locations, higher age, and greater subjective well-being and environmental satisfaction were associated with increased TCV. The universal thermal climate index was associated with TCV, and this association could have been affected by the individual's psychological state. Our findings suggest that environmental factors and psychological factors had non-negligible effects on the subjective thermal comfort of individuals located in an open urban area with historical and cultural significance.

Pedestrian flow-environmental pollutants interactions and health risks to residents in high-occupancy public areas of apartment buildings

The current interaction of pedestrian flow and environmental pollutants in high-occupancy public areas of apartment and the risks of residents being exposed to environmental pollutants are issues that are often overlooked but urgently need to be addressed. In this study, we provide a comprehensive of pedestrian flow-environmental pollutants interactions and health risks to residents in first-floor public areas of apartment with high-occupancy. The main findings indicate that under closed management conditions, there is a significant increase in TVOC and noise levels during the peak periods of nighttime pedestrian flow. In the correlation analysis, the significant impact of time granularity selection in clarifying the correlation between pedestrian flow and environmental pollutants has been highlighted, with larger time granularities generally showing stronger correlations, while finer time granularities may help identify specific risks in areas directly connected to the external environment. There is a significant correlation exists between pedestrian flow and environmental pollutants (TVOC, ozone, and noise), with higher concentrations of these pollutants observed during peak pedestrian flow periods, thereby increasing the risk of residents being exposed to adverse environmental conditions. To mitigate the risks associated with TVOC pollution and noise exposure, it is crucial to maintain proper ventilation, avoid conducting cleaning or maintenance activities during peak hours, and implement noise-reducing measures, such as distancing noise sources from residential areas or installing soundproofing barriers. Additionally, the study identifies total volatile organic compounds originating from property maintenance activities and clarifies their dispersion patterns, emphasizing the importance of developing robust, standardized maintenance protocols for indoor environmental quality assurance. This research can improve the environmental sustainability of apartment buildings and provide a theoretical basis for the development of environmental health strategies for high-occupancy public areas of apartment buildings.

Effects of personal noise exposure, sleep quality, and burnout on quality of life: An online participation cohort study in Taiwan

Chronic noise exposure in daily life not only causes physical and mental illness but also reduces quality of life. However, collecting objective data on sound exposure and subjective acoustic comfort through a traditional one-shot survey is difficult. This study applied online chatbots in social media to explore the effects of daily sound exposure, personal characteristics, noise sensitivity, burnout status, and sleep quality on quality of life using a short-term participatory cohort design. During the two-month survey in 2022, 207 participants completed at least 15 days of collection of data on sound exposure and perception, as well as periodic structural questionnaires during the follow-ups. Linear regression and generalized linear models were applied to explore the factors influencing personal burnout, the Pittsburgh Sleep Quality Index, and quality of life. A chain mediation model was applied to explore the direct and indirect effects of noise exposure on quality of life. The results showed a better quality of life among respondents who rated their home environment better, were in good health, had better daily acoustic comfort, and were less exposed to noise during the week. In contrast, respondents with lower daily acoustic comfort and a higher frequency of noise-induced sleep disturbances and mood disorders were more likely to have poorer sleep quality. A higher personal burnout was associated with poorer health, longer exposure to noise during the week, a higher frequency of noise-induced illnesses, and neurotic traits. In the mediation analyses, noise-induced sleep disturbance and better daily acoustic comfort also had important direct influences on quality of life compared to the indirect pathway through sleep quality and personal burnout. In conclusion, noise exposure in daily life not only exacerbated poor sleep quality and personal burnout but also reduced quality of life.

The relationship between sleep quality and anxiety and depression among older caregivers of centenarians in China: A cross-sectional study

To explore the relationship between sleep quality and anxiety and depression in older caregivers. From April 2020 to November 2022, GAD-7, GDS-15, and PSQI were used to measure anxiety, depression, and sleep quality. The correlation of each variable was explored by regression analysis. Among 442 caregivers ≥ 65 years old, the prevalence of sleep disorders, anxiety, and depression was 40.5 %, 20.2 %, and 26.4 %. After adjustment for multiple potential confounders, anxiety (OR1.1; 95 % CI 1-1.2) and depression (OR 1.29; 95 % CI 1.21-1.38) were associated with sleep disorders. Daytime dysfunction components of PSQI measurements were associated with anxiety(P < 0.05). Meanwhile, sleep efficiency, sleep medication use, and daytime dysfunction components of PSQI measurements were associated with depression(P < 0.05). Therefore, the sleep quality of older caregivers is strongly related to anxiety and depression. It is necessary to provide sleep guidance or professional intervention for older caregivers to reduce anxiety and depression.

Exposures to ambient air pollutants increase prevalence of sleep disorder in adults: Evidence from Wuhan Chronic Disease Cohort Study (WCDCS)

BACKGROUND

Sleep disorder contributes to memory dysfunction and chronic diseases. Clear evidence of environment disturbance, such as residential noise, are associated with an increased risk of sleep disorder. However, not enough studies have been conducted on association between residential air pollutants and sleep disorder. We sought to determine whether exposures to residential air pollutants associated with risk of sleep disorder among adults.

METHODS

Using the dataset of the Wuhan Chronic Disease Cohort Study (WCDCS), we investigated the prevalence of sleep disorder and five sleep disorder symptoms in the study. The data of air pollutants (including PM10, PM2.5, NO2, SO2 and O3) were obtained from 10 air quality monitoring stations in Wuhan. We utilized logistic regression model to evaluate the associations of five types of air pollutants with odds ratio (OR) of sleep disorder and symptoms. The potential moderating effects of socio-demographic factors in the associations were explored using the interaction effects model.

RESULTS

Of the study participants, 52.1 % had sleep disorder. Exposures to higher concentrations of air pollutants were associated with increased prevalence of sleep disorder. For example, per interquartile range (IQR) increases in concentrations of PM10, PM2.5 or SO2 corresponded to the increase of sleep disorder increased prevalence at 14.7 % (adjusted odds ratio (aOR) = 1.147, 95 %CI:1.062, 1.240), 8.9 % (aOR = 1.089, 95 %CI: 1.003, 1.182) and 15.8 % (aOR = 1.158, 95 %CI: 1.065, 1.260). For symptoms specific analyses, significant linkages of PM10, PM2.5, SO2 with difficulty in falling asleep, wake up after falling asleep and early awaken were observed. Moderating effects of age and place of residence on the linkages of PM10 with increased prevalence of sleep disorder were identified.

CONCLUSION

Higher level of air pollution exposure could increase the prevalence of sleep disorder. Middle-aged and elderly population, as well as the rural residents are more likely to suffer from sleep disorder.

Toward a Holistic Computational Representation for Sleep Quality and its Support for Explainability

Sleep quality is recognized as one of the main factors that affect human health. Thus, several studies have been encouraged to analyze features, such as stress level and female menopause, which are directly related to sleep quality. While these works rely mostly on reductionism as the philosophical framework, we approach this problem from a holist perspective, using a model with 10 features that could provide more reliable explanations for inductive conclusions. We demonstrate the principles of this hypothesis by analyzing the data regarding the day before a sleep episode of 1736 volunteers. This analysis shows, for example, the performance of each feature when they are jointly used along prediction tasks. Moreover, we evaluate the readability and accuracy of explanations, given as description logic sentences and based on a knowledge representation that considers the 10 features as elements that compose a sleep quality ontological definition.

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.

Long-term exposure to ambient black carbon is associated with sleep disturbance in college students

BACKGROUND

Evidence suggests an association of air pollution with sleep quality. However, there is limited knowledge regarding the effect of black carbon, a key component of ambient particulate matter, on sleep.

OBJECTIVES

To investigate the association of long-term exposure to black carbon and sleep quality in a group of college students.

METHODS

A retrospective cohort study was conducted in five universities in different regions of China. The concentrations of black carbon and other environment factors were defined as the averages during the 6 years prior to the recruitment. Averagely daily dose of black carbon exposure was estimated according to the respiratory rate. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI) with a cutoff >5 indicating sleep disturbance. Linear regression and logistic regression models were used to estimate the association. The sensitivity analyses were conducted to estimate the effects of 1-month, 6-month and 1-year mean levels of exposure to black carbon on sleep quality.

RESULTS

A total of 20,053 incoming college students were included. 29.3% reported impaired sleep quality, with a mean PSQI score of 4.3 ± 2.2. The logistic regression showed that the risk of impaired sleep quality was positively associated with black carbon exposure, especially in the highest quantile (OR: 1.26, 95% CI: 1.11-1.43) compared with the lowest quartile after adjusting for potential confounders. Subgroup analysis showed that the effect of black carbon on sleep quality was stronger in participants with higher BMI, lower household income, and lower parental educational level. The results of sensitivity analyses were similar with main analyses.

CONCLUSION

Long-term exposure to black carbon is associated with sleep disturbance in college students. Improvement of air quality may help improve sleep quality.

Poor sleep quality and associated factors among HIV-positive pregnant women in Northwest, Ethiopia: a facility-based, cross-sectional study

BACKGROUND

Poor sleep quality during pregnancy might have an impact on adverse birth outcomes like premature rupture of membrane, preterm birth, lifelong neurocognitive impairment, low birth weight, and increased the risk of neonatal morbidity and mortality. In Ethiopia, the magnitude of poor sleep quality among this group of people is extremely limited. So, this study aims to determine the magnitude of poor sleep quality and its associated factors among HIV-positive pregnant women attending public hospitals in Northwest Ethiopia.

METHODS

An institution-based cross-sectional study was done using a simple random sampling technique to recruit 411 HIV-positive pregnant women from January to March; 2021. Sleep quality over the last 1 month was measured using the Pittsburgh Sleep Quality Index (PSQI). General anxiety disorder (GAD-7), Sleep Hygiene Index (SHI), and List of Threatening of Experiences (LTE) instruments were used to identify factors associated with poor sleep quality. Bivariate and multivariable logistic regression with odds ratio and 95% CI were employed to identify determinant factors of poor sleep quality. Statistical significance association was declared at P-value < 0.05.

RESULTS

A total of 411 out of 423 HIV-positive pregnant women were interviewed, with a response rate of 97.1%. The overall magnitude of poor sleep quality among HIV-positive pregnant was found to be 39.4% with a 95% of confidence interval (CI) (34.3, 44.3). Stressful life events, [AOR = 3.10, 95% CI (1.60, 6.01)], having comorbid general anxiety symptoms [AOR = 2.46, 95% CI (1.58, 3.81)], unplanned pregnancy [AOR = 2.18, 95% CI (1.20, 3.96)], and poor sleep hygiene practice [AOR = 2.23, 95% CI (1.21, 4.10)] were significantly associated with poor quality of sleep.

CONCLUSION

The overall magnitude of poor sleep quality among HIV-positive pregnant women was high. Stressful life events, poor sleep hygiene, unplanned pregnancy, and comorbid general anxiety symptoms were the determinant factors of poor sleep quality that should be taken high consideration for early detection and appropriate intervention for poor sleep quality in HIV-positive pregnant women.

Government Trust, Environmental Pollution Perception, and Environmental Governance Satisfaction

Environmental governance is related to the healthy living standard of human beings and the sustainable development of an economic society. It is of great significance to explore the influence of government trust and environmental pollution perception on environmental governance satisfaction to improve the performance of government environmental governance. Based on the CSS2019 survey data, 3872 survey samples were statistically analyzed, and the optimal scale regression model was used to analyze the relationship between government trust, environmental pollution perception, and environmental governance satisfaction. The results showed that 52.27% of the respondents believed that the satisfaction of environmental governance was good, and both government trust and environmental pollution perception had significant positive effects on the satisfaction of environmental governance. The trust level of the central government, district and county governments, and township governments shows a "differential government trust" state, which is pyramidal. However, the impact of government trust on environmental governance satisfaction shows an inverted pyramid structure, and the township government has the largest effect, which is not matched with the distribution of government trust level. The influence effect of air pollution perception is relatively large, and the public is sensitive to air pollution. Government trust has an impact on the satisfaction of environmental governance through the "expectation-response" path. People are close to the township government and have the opportunity to contact and interact with the township government and its staff. They can directly observe the governance performance and share the public goods of environmental governance. Therefore, it is necessary to further improve the trust level of township governments, strengthen the control of air pollution and improve the township government's environmental governance ability.

The impact of perceived air pollution on labour supply: Evidence from China

Air pollution and ageing populations are two of the most important issues facing in the development of all countries around the world, and the resulting debate between air pollution and labour supply has become increasingly intense. This paper uses data from the 2017 China Migrants Dynamic Survey (CMDS data), exploring the impact of perceived air pollution on labour supply of the migrants based on the perspective of the heterogeneity of different groups' sensitivity to air pollution. After overcoming the reverse causality between perceived air pollution and labour supply using an instrumental variables approach, we find that there is a significant negative effect of perceived air pollution on labour supply. At the same time, this negative effect shows some heterogeneity in terms of the presence of susceptible persons in the family, workers' income levels and household registration. Therefore, in the current economic and social development, in addition to improving measured air quality, it is also necessary to focus on improving the perceived air quality of citizens, as well as improving the working environment of the vulnerable groups in the labour market and protecting their basic labour rights and interests, which is of positive significance for the continuation of the demographic dividend and providing impetus for high-quality and sustainable economic development.