Do the levels of particulate matters less than 10 μm and seasons affect sleep?

Association of long-term exposure to PM2.5 and its chemical components with the reduced quality of sleep

Poor sleep quality is a widespread concern. While the influence of particle exposure on sleep disturbances has received considerable attention, research exploring other dimensions of sleep quality and the chemical components of the particles remains limited. We employed a marginal structural model to explore the association of long-term exposure to PM2.5 and its chemical components with poor sleep quality. The odds ratio (95 % CI) for poor sleep quality was 1.335 (1.292-1.378), 1.097 (1.080-1.113), 1.137 (1.100-1.174), 1.197 (1.156-1.240), and 1.124 (1.107-1.140) per IQR increase in the concentration of PM2.5, SO42-, NO3-, NH4+, and BC, respectively. The score (and 95 % CI) of sleep latency, use of sleep medication, habitual sleep efficiency, subjective sleep quality, and daytime dysfunction were affected by PM2.5, with an increase of 0.059 (0.050-0.069), 0.054 (0.049-0.059), 0.011 (0.008-0.014), 0.011 (0.005-0.018), and 0.026 (0.018-0.034) per IQR increase in PM2.5 concentrations, respectively. This study supports the association of long-term exposure to PM2.5 and its chemical components with poor sleep quality.

Association of air pollution with risk and severity of obstructive sleep apnea: A systematic review and meta-analysis

BACKGROUND

Obstructive Sleep Apnea (OSA) is a significant health concern characterized by recurrent upper airway blockages during sleep, causing various health issues. There's growing evidence of a link between air pollution and OSA, though research results have been inconsistent. This systematic review and meta-analysis aims to consolidate and examine data on the relationship between air pollution and OSA's risk and severity.

METHODS

A literature search across PubMed, EMBASE, and Web of Science was conducted until January 10, 2024. The selection criteria targeted studies involving OSA participants or those at risk, with quantitative air pollution assessments. The Nested Knowledge software facilitated screening and data extraction, while the Newcastle-Ottawa Scale was used for quality assessment. Meta-analyses, utilizing random-effects models, computed pooled odds ratios (ORs) for the OSA risk associated with PM2.5 and NO2 exposure, analyzed using R software version 4.3.

RESULTS

The systematic review included twelve studies, four of which were analyzed in the meta-analysis. The meta-analysis revealed diverse results on the association of PM2.5 and NO2 with OSA risk. PM2.5 exposure showed a pooled OR of 0.987 (95 % CI: 0.836-1.138), indicating no substantial overall impact on OSA risk. Conversely, NO2 exposure was linked to a pooled OR of 1.095 (95 % CI: 0.920-1.270), a non-significant increase in risk. Many studies found a relationship between air pollution exposure and elevated Apnea-Hypopnea Index (AHI) levels, indicating a relationship between air pollution and OSA severity.

CONCLUSION

The findings suggest air pollutants, especially NO2, might play a role in worsening OSA risk and severity, but the evidence isn't definitive. This highlights the variability of different pollutants' effects and the necessity for more research. Understanding these links is vital for shaping public health policies and clinical approaches to address OSA amidst high air pollution.

Association between air pollutant exposure, body water distribution and sleep disorder indices in individuals with low-arousal-threshold obstructive sleep apnoea

BACKGROUND

Air pollution may alter body water distribution, it may also be linked to low-arousal-threshold obstructive sleep apnoea (low-ArTH OSA). Here, we explored the mediation effects of air pollution on body water distribution and low-ArTH OSA manifestations.

METHODS

In this retrospective study, we obtained sleep centre data from healthy participants and patients with low-ArTH OSA (N=1924) in northern Taiwan. Air pollutant exposure at different time intervals (1, 3, 6 and 12 months) was estimated using the nearest station estimation method, and government air-quality data were also obtained. Regression models were used to assess the associations of estimated exposure, sleep disorder indices and body water distribution with the risk of low-ArTH OSA. Mediation analysis was performed to explore the relationships between air pollution, body water distribution and sleep disorder indices.

RESULTS

First, exposure to particulate matter (PM) with a diameter of ≤10 µm (PM10) for 1 and 3 months and exposure to PM with a diameter of ≤2.5 µm (PM2.5) for 3 months were significantly associated with the Apnoea-Hypopnoea Index (AHI), Oxygen Desaturation Index (ODI), Arousal Index (ArI) and intracellular-to-extracellular water ratio (I-E water ratio). Significant associations were observed between the risk of low-ArTH OSA and 1- month exposure to PM10 (OR 1.42, 95% CI 1.09 to 1.84), PM2.5 (OR 1.33, 95% CI 1.02 to 1.74) and ozone (OR 1.27, 95% CI 1.01 to 1.6). I-E water ratio alternation caused by 1-month exposure to PM10 and 3-month exposure to PM2.5 and PM10 had partial mediation effects on AHI and ODI.

CONCLUSION

Air pollution can directly increase sleep disorder indices (AHI, ODI and ArI) and alter body water distribution, thus mediating the risk of low-ArTH OSA.

The long-term and short-term effects of ambient air pollutants on sleep characteristics in the Chinese population: big data analysis from real world by sleep records of consumer wearable devices

Several studies on long-term air pollution exposure and sleep have reported inconsistent results. Large-scale studies on short-term air pollution exposures and sleep have not been conducted. We investigated the associations of long- and short-term exposure to ambient air pollutants with sleep in a Chinese population based on over 1 million nights of sleep data from consumer wearable devices. Air pollution data including particulate matter (PM_2.5, PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and ozone (O₃) were collected from the Ministry of Ecology and Environment. Short-term exposure was defined as a moving average of the exposure level for different lag days from Lag0 to Lag0-6. A 365-day moving average of air pollution was regarded as long-term exposure. Sleep data were recorded using wearable devices from 2017 to 2019. The mixed-effects model was used to evaluate the associations. We observed that sleep parameters were associated with long-term exposure to all air pollutants. Higher levels of air pollutant concentrations were associated with longer total sleep and light sleep duration, shorter deep sleep duration, and decreases in wake after sleep onset (WASO), with stronger associations of exposures to NO₂ and CO [a 1-interquartile range (IQR) increased NO₂ (10.3 μg/m³) was associated with 8.7 min (95% CI: 8.08 to 9.32) longer sleep duration, a 1-IQR increased CO (0.3 mg/m³) was associated with 5.0 min (95% CI: - 5.13 to - 4.89) shorter deep sleep duration, 7.7 min (95% CI: 7.46 to 7.85) longer light sleep duration, and 0.5% (95% CI: - 0.5 to - 0.4%) lower proportion of WASO duration to total sleep]. The cumulative effect of short-term exposure on Lag0-6 is similar to long-term exposure but relatively less. Subgroup analyses indicated generally greater effects on individuals who were female, younger (< 45 years), slept longer (≥ 7 h), and during cold seasons, but the pattern of effects was mixed. We supplemented two additional types of stratified analyses to reduce repeated measures of outcomes and exposures while accounting for individual variation. The results were consistent with the overall results, proving the robustness of the overall results. In summary, both short- and long-term exposure to air pollution affect sleep, and the effects are comparable. Although people tend to have prolonged total sleep duration with increasing air pollutant concentrations, their sleep quality might remain poor because of the reduction in deep sleep.

Ambient relative humidity-dependent obstructive sleep apnea severity in cold season: A case-control study

BACKGROUND

The objective of this study was to examine associations of daily averages and daily variations in ambient relative humidity (RH), temperature, and PM_2.5 on the obstructive sleep apnea (OSA) severity.

METHODS

A case-control study was conducted to retrospectively recruit 8628 subjects in a sleep center between January 2015 and December 2021, including 1307 control (apnea-hypopnea index (AHI) < 5 events/h), 3661 mild-to-moderate OSA (AHI of 5-30 events/h), and 3597 severe OSA subjects (AHI > 30 events/h). A logistic regression was used to examine the odds ratio (OR) of outcome variables (daily mean or difference in RH, temperature, and PM_2.5 for 1, 7, and 30 days) with OSA severity (by the groups). Two-factor logistic regression models were conducted to examine the OR of RH with the daily mean or difference in temperature or PM_2.5 with OSA severity. An exposure-response relationship analysis was conducted to examine the outcome variables with OSA severity in all, cold and warm seasons.

RESULTS

We observed associations of mean PM_2.5 and RH with respective increases of 0.04-0.08 and 0.01-0.03 events/h for the AHI in OSA patients. An increase in the daily difference of 1 % RH increased the AHI by 0.02-0.03 events/h in OSA patients. A daily PM_2.5 decrease of 1 μg/m³ reduced the AHI by 0.03 events/h, whereas a daily decrease in the RH of 1 % reduced the AHI by 0.03-0.04 events/h. The two-factor model confirmed the most robust associations of ambient RH with AHI in OSA patients. The exposure-response relationship in temperature and RH showed obviously seasonal patterns with OSA severity.

CONCLUSION

Short-term ambient variations in RH and PM_2.5 were associated with changes in the AHI in OSA patients, especially RH in cold season. Reducing exposure to high ambient RH and PM_2.5 levels may have protective effects on the AHI in OSA patients.

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.

Air pollution associated with cognitive decline by the mediating effects of sleep cycle disruption and changes in brain structure in adults

The effects of air pollution on sleep and dementia remain unclear. The objective of this study was to investigate the effects of air pollution on cognitive function as mediated by the sleep cycle. A cross-sectional study design was conducted to recruit 4866 subjects on which PSG had been performed. Fifty of them were further given a cognitive function evaluation by the MMSE and CASI as well as brain images by CT and MRI. Associations of 1-year air pollution parameters with sleep parameters, cognitive function, and brain structure were examined. We observed that O3 was associated with a decrease in arousal, an increase in the N1 stage, and a decrease in the N2 stage of sleep. NO2 was associated with an increase in the N1 stage, a decrease in the N2 stage, and an increase in REM. PM2.5 was associated with a decrease in the N1 stage, increases in the N2 and N3 stages, and a decrease in REM. The N1 and N2 stages were associated with cognitive decline, but REM was associated with an increase in cognitive function. The N1 stage was a mediator of the effects of PM2.5 on the concentration domain of the MMSE. O3 was associated with an increase in the pars orbitalis volume of the left brain. NO2 was associated with increases in the rostral middle frontal volume, supramarginal gyrus volume, and transverse temporal volume of the left brain, and the pars opercularis volume of the right brain. PM2.5 was associated with increases in the pars triangularis volume of the left brain and the fusiform thickness of the right brain. In conclusion, we observed that air pollution was associated with cognitive decline by mediating effects on the sleep cycle with changes in the brain structure in controlling executive, learning, and language functions in adults.

Serum bicarbonate level improves specificity of Berlin Sleep Questionnaire for obstructive sleep apnea

Several questionnaires have been developed to assist the diagnostic process in obstructive sleep apnea syndrome (OSAS). Berlin Sleep Questionnaire (BSQ) represents a validated screening tool for OSAS. Totally 450 patients admitted to the Sleep Center at Dicle University Medical Faculty were included prospectively. A risk analysis was performed for presence of OSAS using the BSQ. Arterial blood gas measurements were performed including bicarbonate (HCO3) level. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of BSQ for presence of OSAS and severe OSAS were determined. In patients with arterial HCO₃ >24.94 mEq/L; sensitivity, specificity, PPV and NPV, of the BSQ were 93.04, 57.1, 98.3, and 23.5%, respectively. The addition of arterial HCO₃ value increased the sensitivity of the BSQ in detecting OSAS patients. Although the cost of sleep studies is high for false positives from the BSQ plus arterial HCO3 level, this cost should be compared with the loss of work efficiency and severe healthcare costs of undiagnosed cases in the future. Therefore, finding possible OSAS cases in primary care health centers is important and adding serum HCO3 value to BSQ questionnaire may contribute to this topic.

Effects of climate and air pollution factors on outpatient visits for eczema: a time series analysis

Eczema resulting from external and internal factors accounts for the biggest global burden of disability owing to skin disease. This study aimed to determine an association between environmental factors and outpatient clinic visits for eczema. We collected data on dermatology clinic outpatient visits for eczema between January 2013 and July 2019. Data concerning environmental factors during this period were collated using national air quality network and air monitoring measurement parameters, namely barometric pressure, relative humidity, air temperature, and air pollutant concentrations, such as sulfur dioxide (SO₂) and particulate matter (PM₁₀). A distributed lag nonlinear model was used to investigate the relationship among eczema, environmental factors, and lagged effects. In total, 27,549 outpatient visits for eczema were recorded. In both single-factor and multiple-factor lag models, the effects of a 10-µg/m³ increase in PM₁₀ and SO₂ values had significantly positive effects on the number of daily outpatient visits over a total 5 days of lag after adjusting for temperature, the number of daily outpatient visits increased with 0.87%, 7.65% and 0.69%, 5.34%, respectively. Relative humidity (RR = 1.3870, 95% CI 1.3117-1.4665) and pressure (RR = 1.0394, 95% CI 1.0071-1.0727) had significantly positive effects on the number of daily outpatients in single-factor lag models. However temperature had a significantly negative effect on them in the number of daily outpatients (RR = 0.9686, 95% CI 0.9556-0.9819). Exposure to air pollution exacerbated eczema. Outpatient visits for eczema were found to have strong positive associations with changes in PM₁₀ levels.

Relationship between Diagnosis Period and Internal and External Air Quality in Patients with Tuberculosis

Objective

The aim of this study was to investigate the relationship between bacteriological case definitions and indoor and outdoor air quality parameters in tuberculosis (TB).

Materials and Methods

A total of 200 patients with TB diagnosed and treated in our hospital during 2012-2018 were included to this study. The air monitoring measurement parameters of the National Air Quality Network [particulate matter 10 (PM10), sulfur dioxide (SO2), air temperature, air pressure, and relative humidity] for the same time period were obtained from the web page http://laboratory.cevre.gov.tr/Default.ltr.aspx.

Results

Of the 200 patients, 62.5% (125) were males and 37.5% (75) were females. The rate of diagnosis based on culture and smear positivity was 48.4% (31), which was significantly higher than that in the clinic [10.9% (7)] among patients who used stove for warming. The rate of diagnosis based on culture and smear positivity [52.1% (25)] was significantly higher than that in the clinic [8.3% (4)] among patients who were exposed to biomass. The univariate analysis revealed no significant independent effect of warming and biomass use on case definition. According to the case definitions, the mean values of PM₁₀, SO₂, and temperature in the diagnosed month showed no statistically significant difference. The humidity level in the month was significantly higher, during which cases diagnosed using smear and culture positivity were compared with cases diagnosed using only culture positivity (p=0.023).

Conclusion

This study indicates that biomass used as a cooking fuel is a risk factor for pulmonary TB, implying that TB occurrence can be reduced significantly by lowering or preventing the exposure to cooking smoke emitted from biomass fuel.