Association of PM2.5 with sleep-disordered breathing from a population-based study in Northern Taiwan urban areas

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.

Affective Sensitivity to Air Pollution (ASAP): Person-specific associations between daily air pollution and affective states

Individuals' sensitivity to climate hazards is a central component of their vulnerability to climate change. In this paper, we introduce and outline the utility of a new intraindividual variability construct, affective sensitivity to air pollution (ASAP)-defined as the extent to which an individual's affective states fluctuate in accordance with daily changes in air quality. As such, ASAP pushes beyond examination of differences in individuals' exposures to air pollution to examination of differences in individuals' sensitivities to air pollution. Building on known associations between air pollution exposure and adverse mental health outcomes, we empirically illustrate how application of Bayesian multilevel models to intensive repeated measures data obtained in an experience sampling study (N = 150) over one year can be used to examine whether and how individuals' daily affective states fluctuate with the daily concentrations of outdoor air pollution in their county. Results indicate construct viability, as we found substantial interindividual differences in ASAP for both affect arousal and affect valence. This suggests that repeated measures of individuals' day-to-day affect provides a new way of measuring their sensitivity to climate change. In addition to contributing to discourse around climate vulnerability, the intraindividual variability construct and methodology proposed here can help better integrate affect and mental health in climate adaptation policies, plans, and programs.

Associations between indoor fine particulate matter (PM2.5) and sleep-disordered breathing in an urban sample of school-aged children

OBJECTIVES

Environmental risk factors may contribute to sleep-disordered breathing. We investigated the association between indoor particulate matter ≤2.5µm in aerodynamic diameter (PM2.5) and sleep-disordered breathing in children in an urban US community.

METHODS

The sample consisted of children aged 6-12years living in predominantly low-income neighborhoods in Boston, Massachusetts. Indoor PM2.5 was measured in participants' main living areas for 7days using the Environmental Multipollutant Monitoring Assembly device. High indoor PM2.5 exposure was defined as greater than the sample weekly average 80th percentile level (≥15.6 μg/m3). Sleep-disordered breathing was defined as an Apnea-Hypopnea-Index (AHI) or Oxygen-Desaturation-Index (ODI) (≥3% desaturation) of ≥5 events/hour. Habitual loud snoring was defined as caregiver-report of loud snoring (most or all the time each week) over the past 4weeks. We examined the associations of PM2.5 with sleep-disordered breathing or snoring using logistic regression adjusting for potential confounders.

RESULTS

The sample included 260 children (mean age 9.6years; 41% female), with 32% (n = 76) classified as having sleep-disordered breathing. In a logistic regression model adjusted for socioeconomics and seasonality, children exposed to high indoor PM2.5 levels (n = 53) had a 3.53-fold increased odds for sleep-disordered breathing (95%CI: 1.57, 8.11, p = .002) compared to those with lower indoor PM2.5. This association persisted after additional adjustments for physical activity, outdoor PM2.5, environmental tobacco smoke, and health characteristics. Similar associations were observed for snoring and indoor PM2.5. CONCLUSIONS: Children with higher indoor PM2.5 exposure had greater odds of sleep-disordered breathing and habitual loud snoring, suggesting that indoor air quality contributes to sleep disparities.

Ambient ultrafine particles exacerbate oxygen desaturation during sleep in patients with chronic obstructive pulmonary disease: New insights into the effect spectrum of ultrafine particles on susceptible populations

The health effects of ultrafine particles (UFPs) are of growing global concern, but the epidemiological evidence remains limited. Sleep-disordered breathing (SDB) characterized by hypoxemia is a prevalent condition linked to many debilitating chronic diseases. However, the role of UFPs in the development of SDB is lacking. Therefore, this prospective panel study was performed to specifically investigate the association of short-term exposure to UFPs with SDB parameters in patients with chronic obstructive pulmonary disease (COPD). Ninety-one COPD patients completed 226 clinical visits in Beijing, China. Personal exposure to ambient UFPs of 0-7 days was estimated based on infiltration factor and time-activity pattern. Real-time monitoring of sleep oxygen saturation, spirometry, respiratory questionnaires and airway inflammation detection were performed at each clinical visit. Generalized estimating equation was used to estimate the effects of UFPs. Exposure to UFPs was significantly associated with increased oxygen desaturation index (ODI) and percent of the time with oxygen saturation below 90 % (T90), with estimates of 21.50 % (95%CI: 6.38 %, 38.76 %) and 18.75 % (95%CI: 2.83 %, 37.14 %), respectively, per 3442 particles/cm3 increment of UFPs at lag 0-3 h. Particularly, UFPs' exposure within 0-7 days was positively associated with the concentration of alveolar nitric oxide (CaNO), and alveolar eosinophilic inflammation measured by CaNO exceeding 5 ppb was associated with 29.63 % and 33.48 % increases in ODI and T90, respectively. In addition, amplified effects on oxygen desaturation were observed in current smokers. Notably, individuals with better lung function and activity tolerance were more affected by ambient UFPs due to longer time spent outdoors. To our knowledge, this is the first study to link UFPs to hypoxemia during sleep and uncover the key role of alveolar eosinophilic inflammation. Our findings provide new insights into the effect spectrum of UFPs and potential environmental and behavioral intervention strategies to protect susceptible populations.

Physical activity attenuates the association of long-term exposure to nitrogen dioxide with sleep quality and its dimensions in Chinese rural older adults

BACKGROUND

Joint impacts of air pollution and physical activity (PA) on sleep quality remain unaddressed. We aimed to investigate whether PA attenuates the association of long-term exposure to nitrogen dioxide (NO2) with sleep quality and its dimensions in older adults.

METHODS

This study included 3408 Chinese rural older adults. Annual NO2 was estimated using the Space-Time Extra-Trees model. PA was assessed by International Physical Activity Questionnaire. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI) scale. Linear regression models were used to assess the associations of long-term NO2 exposure and PA with sleep quality and its dimensions, and interaction plots were used to depict the attenuating effect of PA on associations of NO2 with sleep quality and its dimensions.

RESULTS

Three-year (3-y) average NO2 (per 0.64-μg/m3 increment) was positively associated with global PSQI (β = 0.41, 95 % CI: 0.23, 0.59), sleep duration (β = 0.16, 95 % CI: 0.11, 0.21), and habitual sleep efficiency (β = 0.22, 95 % CI: 0.17, 0.27), while PA was negatively associated with global PSQI (β = -0.33, 95 % CI: -0.46, -0.20) and five domains of PSQI other than sleep duration and sleep disturbances. The associations of NO2 with global PSQI, sleep duration, and habitual sleep efficiency were attenuated with increased PA (Pinteraction were 0.037, 0.020, and 0.079, respectively).

CONCLUSIONS

PA attenuates the adverse impacts of long-term NO2 exposure on sleep quality, especially on sleep duration, and habitual sleep efficiency, in Chinese rural elderly people. Participating in PA should be encouraged in this population, and continued efforts are still needed to reduce air pollution.

Childhood sleep: assessments, risk factors, and potential mechanisms

BACKGROUND

Sleep problem is a highly prevalent health issue among pediatric populations across the world. In this review, we aimed to identify risk factors contributing to sleep deficiency and poor sleep hygiene in children. Potential biological, psychosocial, and environmental mechanisms as well as research gaps in the literature are also discussed.

DATA SOURCES

A comprehensive search for relevant English language full-text, peer-reviewed publications was performed focusing on pediatric sleep studies from prenatal to childhood and adolescence in a variety of indexes in PubMed, SCOPUS, and Psych Info. Both relevant data based and systematic reviews are included.

RESULTS

This paper summarizes many risk factors for childhood sleep problems, including biological (e.g., genetics, gender, age and puberty, prenatal factors, postnatal factors); nutritional (e.g., macronutrients, micronutrients, omega-3 fatty acids, obesity); environmental (e.g., heavy metals, noise, light, air pollution); interpersonal (e.g., family, exposure to violence, screen media use, physical injury); and community/socioeconomic variables (e.g., racial/ethnicity and cultural factors, neighborhood conditions and socioeconomic status, school factors, public health disasters/emergencies), to better understand the development of sleep problems in children.

CONCLUSIONS

Poor childhood sleep is a multifactorial issue affected by a wide range of prenatal and early-life biological, environmental, and psychosocial risk factors and contributors. A better understanding of these risk factors and their mechanisms is an important first step to develop future research and prevention programs focusing on pediatric sleep problems.

The joint association of ambient air pollution and different sleep posture with mild obstructive sleep apnea: A study conducted at Taipei Sleep Center

BACKGROUND

Growing evidence suggests the detrimental impact of supine position and air pollution on obstructive sleep apnea (OSA), as well as the potential benefits of nonsupine positions. However, their interaction effects on OSA remain unclear.

OBJECTIVES

To evaluate the interaction effects of air pollution (NO2/PM2.5) and sleep position on OSA on additive and multiplicative scales.

METHODS

This study included 3330 individuals. Personal exposure to air pollution was assessed using a spatiotemporal model. OSA was diagnosed through polysomnography. The associations of supine and nonsupine positions and air pollutants with mild-OSA and their interaction effects on mild-OSA. were explored through generalized logistic regression.

RESULTS

Supine position and high NO2 level independently increased the risk of mild-OSA, while PM2.5 was not associated with mild-OSA. Significant interactions were observed between supine position and NO2 at different lag periods (0-7 days, 0-1 year, and 0-2 years) (P = 0.042, 0.013, and 0.010, respectively). The relative excess risks due to interactions on the additive scale for 1-week, 1-year, and 2-year NO2 exposure and supine position were 0.63 (95 % CI: 0.10-1.16), 0.56 (95 % CI: 0.13-0.99), and 0.64 (95 % CI: 0.18-1.10); the corresponding odds ratios for interactions on the multiplicative scale were 1.45 (95 % CI: 1.01-2.07), 1.55 (95 % CI: 1.09-2.22), and 1.60 (95 % CI: 1.12-2.28). The positive interactions persisted in men and participants with obesity. No interaction was observed between nonsupine position and NO2 levels; nevertheless, significant interactions were noted on both the negative additive and multiplicative scales in men.

CONCLUSION

Prolonged supine sleep significantly increased the risk of mild-OSA, particularly in men and individuals with obesity. Although the benefits of nonsupine position are considerably less than the risks of NO2 exposure, avoiding prolonged supine sleep may reduce the risk of mild-OSA caused by high levels of NO2 in men.

Air pollution, glymphatic impairment, and Alzheimer's disease

Epidemiological evidence demonstrates a link between air pollution exposure and the onset and progression of cognitive impairment and Alzheimer's disease (AD). However, current understanding of the underlying pathophysiological mechanisms is limited. This opinion article examines the hypothesis that air pollution-induced impairment of glymphatic clearance represents a crucial etiological event in the development of AD. Exposure to airborne particulate matter (PM) leads to systemic inflammation and neuroinflammation, increased metal load, respiratory and cardiovascular dysfunction, and sleep abnormalities. All these factors are known to reduce the efficiency of glymphatic clearance. Rescuing glymphatic function by restricting the impact of causative agents, and improving sleep and cardiovascular system health, may increase the efficiency of waste metabolite clearance and subsequently slow the progression of AD. In sum, we introduce air pollution-mediated glymphatic impairment as an important mechanistic factor to be considered when interpreting the etiology and progression of AD as well as its responsiveness to therapeutic interventions.

Neural mechanism facilitating PM2.5-related cardiac arrhythmias through cardiovascular autonomic and calcium dysregulation in a rat model

Particulate matter < 2.5 μm (PM2.5) exposure is associated with increased arrhythmia events and cardiovascular mortality, but the detailed mechanism remained elusive. In the current study, we aimed to investigate the autonomic alterations in a rodent model after acute exposure to PM2.5. Twelve male WKY rats were randomized to control and PM2.5 groups. All were treated with 2 exposures of oropharyngeal aerosol inhalations (1 μg PM2.5 per gram of body weight in 100 μL normal saline for the PM2.5 group) separately by 7 days. Polysomnography and electrocardiography were surgically installed 7 days before oropharyngeal inhalation and monitored for 7 days after each inhalation. Physiologic monitors were used to define active waking (AW), quiet sleep (QS), and paradoxical sleep (PS). Autonomic regulations were measured by heart rate variability (HRV). The protein expression of ventricular tissue of the 2 groups was compared at the end of the experiment. In sleep pattern analysis, QS interruption of the PM2.5 group was significantly higher than the control group (0.52 ± 0.13 events/min, 0.35 ± 0.10 events/min, p = 0.002). In HRV analysis, the LF/HF was significantly higher for the PM2.5 group than the control group (1.15 ± 0.16, 0.64± 0.30, p = 0.003), largely driven by LF/HF increase during the QS phase. Ionic channel protein expression from Western blots showed that the PM2.5 group had significantly lower L-type calcium channel and higher SERCA2 and rectifier potassium channel expressions than the control group, respectively. Our results showed that acute PM2.5 exposure leads to interruption of QS, sympathetic activation, and recruitment of compensatory calcium handling proteins. The autonomic and calcium dysregulations developed after PM 2.5 exposure may explain the risk of sleep disturbance and sleep-related arrhythmia.

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.

International Consensus Statement on Obstructive Sleep Apnea

BACKGROUND

Evaluation and interpretation of the literature on obstructive sleep apnea (OSA) allows for consolidation and determination of the key factors important for clinical management of the adult OSA patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA).

METHODS

Using previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence-based review (EBR), or evidence-based review with recommendations (EBR-R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus.

RESULTS

The ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA treatment on multiple OSA-associated comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated.

CONCLUSION

This review of the literature consolidates the available knowledge and identifies the limitations of the current evidence on OSA. This effort aims to create a resource for OSA evidence-based practice and identify future research needs. Knowledge gaps and research opportunities include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy.

Urinary polycyclic aromatic hydrocarbon metabolites were associated with short sleep duration and self-reported trouble sleeping in US adults: data from NHANES 2005-2016 study population

Background

The aim of the current study was to investigate the link between human exposure to PAHs with short sleep duration (SSD) and self-reported trouble sleeping.

Methods

A total of 9,754 participants and 9,777 participants obtained from NHANES 2005-2016 were included in this cross-sectional study about SSD and self-reported trouble sleeping, respectively. The association between urinary PAHs metabolites with the prevalence of SSD and self-reported trouble sleeping by the weighted multivariate logistic regression model, restricted cubic spline (RCS) curves, and weighted quantile sum (WQS) regression.

Results

After adjusting for all covariates, 1-hydroxynapthalene, 2-hydroxynapthalene, 3-hydroxyfluorene, 2-hydroxyfluorene, 1-hydroxyphenanthrene, and 1-hydroxyphenanthrene demonstrated positive associations with SSD prevalence. Besides, 1-hydroxynapthalene, 2-hydroxynapthalene, 3-hydroxyfluorene, 2-hydroxyfluorene, 1-hydroxyphenanthrene, and 1-hydroxyphenanthrene exhibited positive associations with the prevalence of self-reported trouble sleeping following the adjustment for all covariates. RCS curves confirmed the non-linear associations between 1-hydroxynapthalene, 2-hydroxynapthalene, 3-hydroxyfluorene, 2-hydroxyfluorene, and 1-hydroxyphenanthrene with the prevalence of SSD, and 1-hydroxynapthalene, 3-hydroxyfluorene, and 2-hydroxyfluorene with the prevalence of self-reported trouble sleeping. The WQS results showed that mixed exposure to PAH metabolites had a significant positive association with the prevalence of SSD (OR: 1.087, 95% CI: 1.026, 1.152, p = 0.004) and self-reported trouble sleeping (OR: 1.190, 95% CI: 1.108, 1.278, p < 0.001).

Conclusion

Urinary concentrations of PAH metabolites exhibited a close association with the prevalence of SSD and self-reported trouble sleeping in US adults. More emphasis should be placed on the importance of environmental effects on sleep health.

Short-term and intermediate-term fine particulate air pollution are synergistically associated with habitual sleep variability in adolescents - A cross-sectional study

BACKGROUND

Both air pollution and poor sleep have been associated with increased risk of cardiovascular diseases. However, the association between air pollution and sleep health, especially among adolescents, is rarely investigated.

METHODS

To investigate the association between fine particulate (PM2.5) air pollution and habitual sleep patterns, we analyzed data obtained from 246 adolescents who participated in the Penn State Child Cohort follow-up examination. We collected their individual-level 24-h (short-term) PM2.5 concentration by using a portable monitor. We estimated their residential-level PM2.5 concentration during the 60-day period prior to the examination (intermediate-term) using a kriging approach. Actigraphy was used to measure participants' sleep durations for seven consecutive nights. Habitual sleep duration (HSD) and sleep variability (HSV) were calculated as the mean and SD of the seven-night sleep duration. Multivariable-adjusted linear regression models were used to assess the association between PM2.5 exposures and HSD/HSV. An interaction between short-term and intermediate-term PM2.5 was created to explore their synergistic associations with HSD/HSV.

RESULTS

Elevated short-term and intermediate-term PM2.5 exposure were significantly (p < 0.05) associated with higher HSV, but not HSD. Specifically, the mean (95% CI) increase in HSV associated with 1 SD higher 24-h (26.3 μg/m3) and 60-day average (2.2 μg/m3) PM2.5 were 14.6 (9.4, 14.8) and 4.9 (0.5, 9.2) minutes, respectively. In addition, there was a synergistic interaction (p = 0.08) between short-term and intermediate-term PM2.5 exposure on HSV, indicative that the association between intermediate-term PM2.5 and HSV became stronger as short-term PM2.5 increases, and vice versa.

CONCLUSION

Short-term individual-level and intermediate-term residential-level PM2.5 exposures are adversely and synergistically associated with increased sleep variability, an indicator of instability of sleep quantity, in adolescents. Through such an association with sleep pattern, PM2.5 air pollution may increase long-term cardiometabolic risks.

Associations between air pollution, intracellular-to-extracellular water distribution, and obstructive sleep apnea manifestations

Background

Exposure to air pollution may be a risk factor for obstructive sleep apnea (OSA) because air pollution may alter body water distribution and aggravate OSA manifestations.

Objectives

This study aimed to investigate the mediating effects of air pollution on the exacerbation of OSA severity through body water distribution.

Methods

This retrospective study analyzed body composition and polysomnographic data collected from a sleep center in Northern Taiwan. Air pollution exposure was estimated using an adjusted nearest method, registered residential addresses, and data from the databases of government air quality motioning stations. Next, regression models were employed to determine the associations between estimated air pollution exposure levels (exposure for 1, 3, 6, and 12 months), OSA manifestations (sleep-disordered breathing indices and respiratory event duration), and body fluid parameters (total body water and body water distribution). The association between air pollution and OSA risk was determined.

Results

Significant associations between OSA manifestations and short-term (1 month) exposure to PM_2.5 and PM₁₀ were identified. Similarly, significant associations were identified among total body water and body water distribution (intracellular-to-extracellular body water distribution), short-term (1 month) exposure to PM_2.5 and PM₁₀, and medium-term (3 months) exposure to PM₁₀. Body water distribution might be a mediator that aggravates OSA manifestations, and short-term exposure to PM_2.5 and PM₁₀ may be a risk factor for OSA.

Conclusion

Because exposure to PM_2.5 and PM₁₀ may be a risk factor for OSA that exacerbates OSA manifestations and exposure to particulate pollutants may affect OSA manifestations or alter body water distribution to affect OSA manifestations, mitigating exposure to particulate pollutants may improve OSA manifestations and reduce the risk of OSA. Furthermore, this study elucidated the potential mechanisms underlying the relationship between air pollution, body fluid parameters, and OSA severity.

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.

Associations between Aircraft Noise Exposure and Self-Reported Sleep Duration and Quality in the United States-Based Prospective Nurses' Health Study Cohort

BACKGROUND

Sleep disruption is linked with chronic disease, and aircraft noise can disrupt sleep. However, there are few investigations of aircraft noise and sleep in large cohorts.

OBJECTIVES

We examined associations between aircraft noise and self-reported sleep duration and quality in the Nurses' Health Study, a large prospective cohort.

METHODS

Aircraft nighttime equivalent sound levels (Lnight) and day-night average sound levels (DNL) were modeled around 90 U.S. airports from 1995 to 2015 in 5-y intervals using the Aviation Environmental Design Tool and linked to geocoded participant residential addresses. Lnight exposure was dichotomized at the lowest modeled level of 45 A-weighted decibels [dB(A)] and at multiple cut points for DNL. Multiple categories of both metrics were compared with < 45 dB(A). Self-reported short sleep duration (< 7 h/24-h day) was ascertained in 2000, 2002, 2008, 2012, and 2014, and poor sleep quality (frequent trouble falling/staying asleep) was ascertained in 2000. We analyzed repeated sleep duration measures using generalized estimating equations and sleep quality by conditional logistic regression. We adjusted for participant-level demographics, behaviors, comorbidities, and environmental exposures (greenness and light at night) and examined effect modification.

RESULTS

In 35,226 female nurses averaging 66.1 years of age at baseline, prevalence of short sleep duration and poor sleep quality were 29.6% and 13.1%, respectively. In multivariable models, exposure to Lnight ≥ 45 dB(A) was associated with 23% [95% confidence interval (CI): 7%, 40%] greater odds of short sleep duration but was not associated with poor sleep quality (9% lower odds; 95% CI: - 30 % , 19%). Increasing categories of Lnight and DNL ≥ 45 dB(A) suggested an exposure-response relationship for short sleep duration. We observed higher magnitude associations among participants living in the West, near major cargo airports, and near water-adjacent airports and among those reporting no hearing loss.

DISCUSSION

Aircraft noise was associated with short sleep duration in female nurses, modified by individual and airport characteristics. https://doi.org/10.1289/EHP10959.

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.

Early-Life Exposure to PM2.5 and Sleep Disturbances in Preschoolers from 551 Cities of China

Rationale: Air pollution has been linked with sleep disturbance in adults, but the association in children remains unclear. Objectives: To examine the associations of prenatal and postnatal exposure to fine particulate matter (particulate matter ⩽2.5 μm in aerodynamic diameter; PM_2.5) with sleep quality and sleep disturbances among children in 551 Chinese cities. Methods: A total of 1,15,023 children aged 3-7 years from the Chinese National Cohort of Motor Development were included. Sleep quality was measured using the Children's Sleep Habits Questionnaire (CSHQ). PM_2.5 exposure was estimated using a satellite-based model. Generalized additive mixed models with Gaussian and binomial distributions were used to examine the associations of PM_2.5 exposure with CSHQ scores and risk of sleep disturbance, respectively, adjusting for demographic characteristics and temporal trends. Measurements and Main Results: Early-life PM_2.5 exposure was associated with higher total CSHQ score, and the association was stronger for exposure at age 0-3 years (change of CSHQ score per interquartile range increase of PM_2.5 = 0.46; 95% confidence interval [CI], 0.29-0.63) than during pregnancy (0.22; 95% CI, 0.12-0.32). The associations were more evident in sleep-disordered breathing and daytime sleepiness. Postnatal PM_2.5 exposure was associated with increased risk of sleep disturbance (adjusted odds ratio for per-interquartile range increase of PM_2.5 exposure at age 0-3 years, 1.10; 95% CI, 1.04-1.15), but no associations were found for prenatal exposure. Children who were exclusively breastfed for <6 months and had neonatal ICU admission may be more vulnerable to sleep disturbance related to PM_2.5 exposure. Conclusions: PM_2.5 exposure can impair sleep quality in preschool children.

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.

Impact of ground-level ozone exposure on sleep quality and electroencephalogram patterns at different time scales

Ozone exposure is associated with various adverse health outcomes, but its impact on sleep quality is uncertain. Here we assessed the causal effect of long-term (yearly and monthly) exposure to ozone on nocturnal workday sleep time in a national representative sample from the China Family Panel Study, using a difference-in-differences approach. We further followed ninety healthy Chinese young adults four times in four seasons from September 2020 to June 2021, measured their daily sleep architecture using accelerometers, ascertained daily ozone exposure, recorded 5-min eye-closed resting-state electroencephalogram (EEG) signals at the last day of each one-week-long measurement session, and explored the effect of ozone exposure on objectively-measured sleep architecture. In the national sample, we found that every 1 interquartile range (IQR) μg/m³ increase in yearly and monthly ozone exposure was causally associated with 7.31 (p = 0.0039) and 4.19 (p = 0.040) minutes decline in nocturnal workday sleep time; the dose-response curve represented a quasi-linear pattern with no safety threshold, and plateaued at higher concentrations. In the small-scale study with objectively-measured sleep architecture, we found that every 1 IQR μg/m³ increase in the weekly ozone exposure was associated with 5.33 min decrease in night-time total sleep time (p = 0.031), 1.63 percentage points decrease in sleep efficiency (p < 0.001), 1.99 min increase in sleep latency (p = 0.0070), and 5.34 min increase in wake after sleep onset time (p = 0.0016) in a quasi-linear pattern. Notably, we found the accumulating trend of ozone exposure on sleep quality during both the short-term and long-term periods. We also found that short-term ozone exposure was associated with altered EEG patterns, mediated by sleep quality. This study indicates that long-term and short-term ozone exposures have negative and accumulating impacts on sleep quality and might impair brain functioning. More hidden health burdens of ozone are worth exploring.

Associations of cooking fuel types and daily cooking duration with sleep quality in rural adults: Effect modification of kitchen ventilation

BACKGROUND

Associations of combined different cooking fuel types and cooking duration with sleep quality were scarcely reported. This study aimed to explore the associations of exposure to household air pollution (HAP) from different cooking fuel types and cooking duration with sleep quality and examine the effect modification of kitchen ventilation on these associations.

METHODS

A total of 28,135 eligible participants were obtained from the Henan rural cohort study. Sleep quality was assessed by the Pittsburgh sleep quality index (PSQI), and participants with a PSQI score > 5 were identified as having poor sleep quality. A questionnaire was used to collect the cooking fuel types, cooking frequency, cooking duration, and kitchen ventilation. The average daily cooking duration was calculated as the cooking frequency per week multiplied by the cooking duration for each meal divided by 7.

RESULTS

Both domestic fuel use and cooking duration were positively related to poor sleep quality. The solid fuel users with a cooking duration ≥1.5 h/day had a higher prevalence of poor sleep quality (OR: 1.390, 95% CI: 1.233, 1.567), relative to those who never cooked. Notably, the estimated OR and 95% CI for poor sleep quality of clean fuel users with a cooking duration <1.5 h/day plus mechanical or natural ventilation versus those who never cooked was 1.05 (0.933, 1.187) or 1.306 (1.163, 1.466) and these associations were modified by kitchen ventilation.

CONCLUSION

Positive associations of combined different cooking fuel types and cooking duration with the prevalence of poor sleep quality were attenuated by kitchen ventilation, implying that installing mechanical ventilation may be an effective measure to improve sleep quality in low- and middle-income countries. These results need to be confirmed by future studies, which measure HAP more accurately using personal monitoring devices or behavior diaries.

Association between residential greenness and obstructive sleep apnoea among adults in Southern China

BACKGROUND

No previous study has explored the association of residential greenness with obstructive sleep apnoea (OSA) indexes.

OBJECTIVE

To investigate the association of exposure to residential greenness with OSA indexes in adults in Guangdong Province, Southern China.

METHODS

From January 1, 2005 to December 31, 2015, a total of 3925 participants were recruited from the Sleep Center of Guangdong Provincial People's Hospital. Apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) were measured by polysomnography or home sleep test (HST). Participants' daytime sleepiness scores were evaluated using The Epworth Sleeping Scale (ESS). The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were used to assess residential greenness levels. Generalized linear regression models were used to assess the associations of residential greenness with OSA indexes after adjusting for multiple covariates.

RESULTS

The mean (standard deviation) age of the participants was 63.3 (14.4) years. In adjusted models, an interquartile range (IQR) increase in 3-year average NDVI was significantly associated with 9.8 % (95 % confidence interval [95 % CI]: 17.5 %, 2.1 %); 14.5 % (95 % CI: 24.5 %, 4.4 %) and 6.9 % (95 % CI: 13.7 %, 0.0 %) decreases in AHI, ODI and ESS scores, respectively. Furthermore, an IQR increase in 3-year average EVI was significantly associated with 7.8 % (95 % CI: 13.7 %, 1.9 %); 10.8 % (95 % CI: 18.3 %, 3.2 %) and 7.2 % (95 % CI: 12.5 %, 2.0 %) declines in AHI, ODI and ESS scores, respectively. Significant associations were only observed among males, adults aged ≥65 years old, and in the warm season.

CONCLUSIONS

Our study indicates that higher residential greenness was significantly associated with lower OSA indexes in adult population in South China, especially in males, in the elderly, and in the warm season.

Effects of the COVID-19 pandemic on sleep health among Middle Eastern and North African (MENA) populations: a systematic review of the literature

OBJECTIVES

This study sought to conduct a systematic review of the literature on the impact of the COVID-19 pandemic on sleep health among Middle Eastern and North African (MENA) populations, understudied geographic regions including with regards to sleep health.

SETTING

A systematic literature search of studies published from inception to 27 March 2022 was conducted on multiple databases using developed keywords.

PARTICIPANTS

Studies were included if they (1) investigated one or more aspects/dimensions of sleep health as an outcome (eg, sleep duration, sleep quality, sleep problems); (2) measured the impact of a COVID-19 pandemic-related domain (eg, impact of quarantine, work from home, lifestyle changes); (3) focused on at least one MENA region population; (4) were peer-reviewed; (5) included ≥100 participants; (6) were written in English and (7) had full-text article publicly available.

PRIMARY AND SECONDARY OUTCOMES MEASURED

Primary outcomes were sleep duration, sleep quality and sleep problems.

RESULTS

In line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 164 studies were included for data extraction. The Newcastle-Ottawa scale for cross-sectional studies was used to assess the quality of the studies. Overall, the COVID-19 pandemic significantly impacted sleep duration, sleep quality and presence and severity of sleep disorders in MENA populations, including adults, children, students, healthcare workers and people with chronic illnesses. The directionality and strength of associations, as well as the determinants of sleep health, varied by subpopulations.

CONCLUSIONS

Longitudinal studies are needed to understand the longer-term impact of the COVID-19 pandemic on the sleep health of MENA populations. Sleep health interventions and policy measures should be tailored to the need of each subpopulation.

PROSPERO REGISTRATION NUMBER

CRD42022321128.

Climate-mediated air pollution associated with COPD severity

Air pollution has been reported to be associated with chronic obstructive pulmonary disease (COPD). Our study aim was to examine the mediating effects of air pollution on climate-associated health outcomes of COPD patients. A cross-sectional study of 117 COPD patients was conducted in a hospital in Taiwan. We measured the lung function, 6-min walking distance, oxygen desaturation, white blood cell count, and percent emphysema (low attenuation area, LAA) and linked these to 0-1-, 0-3-, and 0-5-year lags of individual-level exposure to relative humidity (RH), temperature, and air pollution. Linear regression models were conducted to examine associations of temperature, RH, and air pollution with severity of health outcomes. A mediation analysis was conducted to examine the mediating effects of air pollution on the associations of RH and temperature with health outcomes. We observed that a 1 % increase in the RH was associated with increases in forced expiratory volume in 1 s (FEV₁), eosinophils, and lymphocytes, and a decrease in the total-lobe LAA. A 1 °C increase in temperature was associated with decreases in oxygen desaturation, and right-, left-, and upper-lobe LAA values. Also, a 1 μg/m³ increase in PM_2.5 was associated with a decrease in the FEV₁ and an increase in oxygen desaturation. A 1 μg/m³ increases in PM₁₀ and PM_2.5 was associated with increases in the total-, right-, left, upper-, and lower-lobe (PM_2.5 only) LAA. A one part per billion increase in NO₂ was associated with a decrease in the FEV₁ and an increase in the upper-lobe LAA. Next, we found that NO₂ fully mediated the association between RH and FEV₁. We found PM_2.5 fully mediated associations of temperature with oxygen saturation and total-, right-, left-, and upper-lobe LAA. In conclusion, climate-mediated air pollution increased the risk of decreasing FEV₁ and oxygen saturation and increasing emphysema severity among COPD patients. Climate change-related air pollution is an important public health issue, especially with regards to respiratory disease.

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.

Elder people can be more susceptible to the association between short-term ambient air pollution and sleep disorder outpatient visits: a time-series study

Sleep disorders attract increasing concerns. However, the evidence of the association between ambient air pollution and sleep disorders is limited. Therefore, our aim was to determine the association between short-term air pollution exposure and outpatient visits for sleep disorders in Xi'an, the largest city in Northwest China. Baseline outpatient data of daily sleep disorders between 2011 and 2013 were collected. Quasi-Poisson distribution was applied by adjusting the day of the week and weather conditions. A total of 49,282 sleep disorder outpatient visits were recorded. The most significant association between air pollutants and outpatient visits was observed on concurrent day: per 10 μg/m3 increase of NO2, SO2, and PM10 at lag 0 corresponded to increased outpatient sleep disorder visits at 0.22% (95% CI: 0.03%, 0.42%), 1.53% (95% CI: 0.53, 2.53%), and 2.57% (95% CI: 1.33%, 3.82%), respectively. As for gender-specific analysis, there was no statistically significant difference between males and females. The result of season-specific analysis showed no statistically significant difference between warm seasons and cool seasons, either. As for age-specific analysis, obvious associations were observed in 20-40 age group (NO2) and > 40 age group (PM10 and SO2), while no evident association was found for the young age group (< 20 years old). Conclusively, short-term exposure to air pollutants, especially gaseous air pollutants, might increase the risk of sleep disorders, and such association appears to be more obvious in elder people. We provide novel data that there may be age differences in the relationship between short-term air pollution exposure and sleep disorders.

Co-exposure to multiple air pollutants and sleep disordered breathing in patients with or without obstructive sleep apnea: A cross-sectional study

BACKGROUND

Air pollution may be a contributing risk factor for obstructive sleep apnea (OSA). However, the health effects of co-exposure to multiple air pollutants on OSA patients remain unclear.

OBJECTIVES

To assess the joint effect of multi-pollutant on sleep disordered breathing (SDB) parameters in patients with or without OSA and identify the dominant pollutants.

METHODS

A total of 2524 outpatients from April 2020 to May 2021 were recruited in this cross-sectional study. Ambient air pollutant data were obtained from the nearest central monitoring stations to participants' residential address. SDB parameters were measured by the ApneaLink devices, including apnea-hypopnea index (AHI), hypopnea index (HI), oxygen desaturation index (ODI), average oxygen saturation (SpO₂), percentage sleep time with <90% saturation (T90), and desaturation. Bayesian kernel machine regression (BKMR) was applied to evaluate the effects of multiple pollutants.

RESULTS

Significant associations were observed between air pollutants and SDB parameters (including increases in AHI, HI, ODI, and desaturation) among patients with OSA. Co-exposure to air pollutants was positively correlated with AHI, HI, and ODI. PM₁₀ and O₃ dominated the effects of pollutant mixtures on OSA, with the highest posterior inclusion probability (PIP) values of 0.592 and 0.640, respectively. Stratified analysis showed that, compared to male patients with OSA, stronger effects on the SDB parameters were observed in female patients. Stronger associations were also found in the warm season than those in the cold season.

CONCLUSION

Co-exposure to air pollutants was associated with SDB parameters among patients with OSA, PM₁₀ and O₃ might play the dominant roles.

Deep neural networks for spatiotemporal PM2.5 forecasts based on atmospheric chemical transport model output and monitoring data

Reliable long-horizon PM_2.5 forecasts are crucial and beneficial for health protection through early warning against air pollution. However, the dynamic nature of air quality makes PM_2.5 forecasts at long horizons very challenging. This study proposed a novel machine learning-based model (MCNN-BP) that fused multiple convolutional neural networks (MCNN) with a back-propagation neural network (BPNN) for making spatiotemporal PM_2.5 forecasts for the next 72 h at 74 stations covering the whole Taiwan simultaneously. Model configuration involved an ensemble of massive hourly air quality and meteorological monitoring datasets and the existing publicly-available PM_2.5 simulated (forecasted) datasets from an atmospheric chemical transport (ACT) model. The proposed methodology collaboratively constructed two CNNs to mine the observed data (the past) and the forecasted data from ACT (the future) separately. The results showed that the MCNN-BP model could significantly improve the accuracy of spatiotemporal PM_2.5 forecasts and substantially reduce the forecast biases of the ACT model. We demonstrated that the proposed MCNN-BP model with effective feature extraction and good denoising ability could overcome the curse of dimensionality and offer satisfactory regional long-horizon PM_2.5 forecasts. Moreover, the MCNN-BP model has considerably shorter computational time (5 min) and lower computational load than the compute-intensive ACT model. The proposed approach hits a milestone in multi-site and multi-horizon forecasting, which significantly contributes to early warning against regional air pollution.

Association of air pollution exposure with low arousal threshold obstructive sleep apnea: A cross-sectional study in Taipei, Taiwan

Emerging evidence witnesses the association of air pollution exposure with sleep disorders or the risk of obstructive sleep apnea (OSA); however, the results are not consistent. OSA patients with or without a low arousal threshold (LAT) have different pathology and therapeutic schemes. No study has evaluated the potential diverse effects of air pollution on the phenotypes of OSA. The current study aimed to evaluate the associations of short-term and long-term exposure to air pollution with sleep-disordered measures and OSA phenotypes. This cross-sectional study consisted of 4634 participants from a sleep center in Taipei from January 2015 to April 2019. The personal exposure to ambient PM_2.5 and NO₂ was assessed by a spatial-temporal model. Overnight polysomnography was used to measure the sleep parameters. According to a developed clinical tool, we defined the low arousal threshold (LAT) and identified the OSA patients with or without LAT. We applied a generalized linear model and multinomial logistic regression model to estimate the change of sleep measures and risk of the OSA phenotypes, respectively, associated with an interquartile range (IQR) increment of personal pollution exposure after adjusting for the essential confounders. In the single-pollutant model, we observed the associations of NO₂ with sleep-disordered measures by decreasing the total sleep time, sleep efficiency, extending the time of wake after sleep onset, and the association of NO₂ with the increased risk of LAT OSA by around 15%. The two-pollutant model with both long-term and short-term exposures confirmed the most robust associations of long-term NO₂ exposure with sleep measures. An IQR increment of NO₂ averaged over the past year (6.0 ppb) decreased 3.32 min of total sleep time and 0.85% of sleep efficiency. Mitigating exposure to air pollution may improve sleep quality and reduce the risk of LAT OSA.

Environmental Noise and Effects on Sleep: An Update to the WHO Systematic Review and Meta-Analysis

BACKGROUND

Nighttime noise carries a significant disease burden. The World Health Organization (WHO) recently published guidelines for the regulation of environmental noise based on a review of evidence published up to the year 2015 on the effects of environmental noise on sleep.

OBJECTIVES

This systematic review and meta-analysis will update the WHO evidence review on the effects of environmental noise on sleep disturbance to include more recent studies.

METHODS

Investigations of self-reported sleep among residents exposed to environmental traffic noise at home were identified using Scopus, PubMed, Embase, and PsycINFO. Awakenings, falling asleep, and sleep disturbance were the three outcomes included. Extracted data were used to derive exposure-response relationships for the probability of being highly sleep disturbed by nighttime noise [average outdoor A-weighted noise level (Lnight) 2300-0700 hours] for aircraft, road, and rail traffic noise, individually. The overall quality of evidence was assessed using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria.

RESULTS

Eleven studies (n=109,070 responses) were included in addition to 25 studies (n=64,090 responses) from the original WHO analysis. When sleep disturbance questions specifically mentioned noise as the source of disturbance, there was moderate quality of evidence for the probability of being highly sleep disturbed per 10-dB increase in Lnight for aircraft [odds ratio (OR)=2.18; 95% confidence interval (CI): 2.01, 2.36], road (OR=2.52; 95% CI: 2.28, 2.79), and railway (OR=2.97; 95% CI: 2.57, 3.43) noise. When noise was not mentioned, there was low to very low quality of evidence for being sleep disturbed per 10-dB increase in Lnight for aircraft (OR=1.52; 95% CI: 1.20, 1.93), road (OR=1.14; 95% CI: 1.08, 1.21), and railway (OR=1.17; 95% CI: 0.91, 1.49) noise. Compared with the original WHO review, the exposure-response relationships closely agreed at low (40 dB Lnight) levels for all traffic types but indicated greater disturbance by aircraft traffic at high noise levels. Sleep disturbance was not significantly different between European and non-European studies.

DISCUSSION

Available evidence suggests that transportation noise is negatively associated with self-reported sleep. Sleep disturbance in this updated meta-analysis was comparable to the original WHO review at low nighttime noise levels. These low levels correspond to the recent WHO noise limit recommendations for nighttime noise, and so these findings do not suggest these WHO recommendations need revisiting. Deviations from the WHO review in this updated analysis suggest that populations exposed to high levels of aircraft noise may be at greater risk of sleep disturbance than determined previously. https://doi.org/10.1289/EHP10197.

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.

Association of traffic air pollution with severity of obstructive sleep apnea in urban areas of Northern Taiwan: A cross-sectional study

BACKGROUND

Although recent studies have indicated an association between obstructive sleep apnea (OSA) and air pollution, they have reported inconsistent results. Moreover, few studies investigated the effects of short-term air pollution exposure.

OBJECTIVE

To estimate the health effects of short- and long-term exposure to traffic air pollution on mild OSA in Taipei.

METHODS

We collected participants' data from Taipei Sleep Center and air pollution data from Taiwan Environmental Protection Administration. A spatiotemporal model was used to estimate the individual exposure level. Generalized linear models were used to assess the percent change of overall apnea-hypopnea index (AHI), AHI in rapid eye movement period (AHI-REM), AHI in non-REM (AHI-NREM), and oxygen desaturation index (ODI) associated with an interquartile (IQR) increase in personal pollution exposure. A generalized logistic model was used to estimate the ORs of different severities of OSA compared with the reference group.

RESULTS

In the patients with AHI of <15, both short- and long-term exposure to NO₂ were significantly associated with AHI and ODI increases: an IQR increase in 2-year mean NO₂ increased 7.3% of AHI and 8.4% of ODI; these values were the highest among all exposure windows. The effects of NO₂ on AHI increase were stronger in the men and younger patients. Moreover, the association between AHI and NO₂ in the patients with AHI of <15 was mediated by the REM stage. NO₂ exposure was associated with an increased risk of mild OSA that reached up to 24.8% per IQR increase in NO₂ averaged over 2 years. PM_2.5 exerted no effects on AHI, but an IQR increase in 1-year and 2-year mean PM_2.5 was associated with 6.8% and 8.8% increases in ODI, respectively.

CONCLUSIONS

Both short- and long-term exposure to traffic air pollution were associated with the risk of mild OSA, which was modified by REM stage.

The Need for Social and Environmental Determinants of Health Research to Understand and Intervene on Racial/Ethnic Disparities in Obstructive Sleep Apnea

Obstructive sleep apnea (OSA), a sleep-disordered breathing (SDB) disorder, affects at least 25 million adults in the United States and is associated with increased risk for hypertension, diabetes, and cardiovascular disease (CVD). Racial/ethnic minorities have a disproportionate burden of OSA along with the health sequelae associated with this condition. Despite supporting evidence of racial/ethnic disparities, few studies have investigated SDB including OSA among minoritized racial/ethnic groups. In this scoping review of the literature, the authors summarize current findings related to racial/ethnic disparities in OSA, identified social and environmental determinants of health, treatment inequities, and promising evidence-based interventions and conclude with future research directions.

Objective sleep assessments for healthy people in environmental research: A literature review

To date, although many studies had focused on the impact of environmental factors on sleep, how to choose the proper assessment method for objective sleep quality was often ignored, especially for healthy subjects in bedroom environment. In order to provide methodological guidance for future research, this paper reviewed the assessments of objective sleep quality applied in environmental researches, compared them from the perspective of accuracy and interference, and statistically analyzed the impact of experimental type and subjects' information on method selection. The review results showed that, in contrast to polysomnography (PSG), the accuracy of actigraphy (ACT), respiratory monitoring-oxygen saturation monitoring (RM-OSM), and electrocardiograph (ECG) could reach up to 97%, 80.38%, and 79.95%, respectively. In terms of sleep staging, PSG and ECG performed the best, ACT the second, and RM-OSM the worst; as compared to single methods, mix methods were more accurate and better at sleep staging. PSG interfered with sleep a great deal, while ECG and ACT could be non-contact, and thus, the least interference with sleep was present. The type of experiment significantly influenced the choice of assessment method (p < 0.001), 85.3% of researchers chose PSG in laboratory study while 82.5% ACT in field study; moreover, PSG was often used in a relatively small number of young subjects, while ACT had a wide applicable population. In general, researchers need to pay more attention at selection of assessments in future studies, and this review can be used as a reliable reference for experimental design.

The Association between Childhood Exposure to Ambient Air Pollution and Obesity: A Systematic Review and Meta-Analysis

Obesity has become a worldwide epidemic; 340 million of children and adolescents were overweight or obese in 2016, and this number continues to grow at a rapid rate. Epidemiological research has suggested that air pollution affects childhood obesity and weight status, but the current evidence remains inconsistent. Therefore, the aim of this meta-analysis was to estimate the effects of childhood exposure to air pollutants on weight. A total of four databases (PubMed, Web of Science, Embase, and Cochrane Library) were searched for publications up to December 31, 2021, and finally 15 studies met the inclusion criteria for meta-analysis. Merged odds ratios (ORs), coefficients (β), and 95% confidence intervals (95% CIs) that were related to air pollutants were estimated using a random-effects model. The meta-analysis indicated that air pollutants were correlated with childhood obesity and weight gain. For obesity, the association was considerable for PM₁₀ (OR = 1.12, 95% CI: 1.06, 1.18), PM_2.5 (OR = 1.28, 95% CI: 1.13, 1.45), PM₁ (OR = 1.41, 95% CI: 1.30, 1.53), and NO₂ (OR = 1.11, 95% CI: 1.06, 1.18). Similarly, BMI status increased by 0.08 (0.03-0.12), 0.11 (0.05-0.17), and 0.03 (0.01-0.04) kg/m² with 10 μg/m³ increment in exposure to PM₁₀, PM_2.5, and NO₂. In summary, air pollution can be regarded as a probable risk factor for the weight status of children and adolescents. The next step is to conduct longer-term and large-scale studies on different population subgroups, exposure concentrations, and pollutant combinations to provide detailed evidence. Meanwhile, integrated management of air pollution is essential.

The impact of environmental pollution on the physical health of middle-aged and older adults in China

While several studies have demonstrated the negative impacts of environmental pollution on population health, in general, few studies have examined the potential differential effects on the physical health of middle-aged and older populations, i.e., 45 years and older. Given the twin concerns of environmental pollution and population aging in China, this article employed a fixed effects model to infer the impact of environmental pollution on public health with a particular focus on middle-aged and older adults. The analyses were based on data from the 2011 to 2018 waves of the CHARLS and pollutant data from prefecture-level cities. The results showed that both the level and intensity of environmental pollution significantly increased the risk of chronic diseases and negatively impacted the physical health of middle-aged and older adults. Environmental pollution had its greatest negative effect on the physical health of the elderly, urban residents, residents of the Eastern region, and those with lower incomes than their counterparts. We further found that the potential channels of health effect were through reduced physical exercise and sleep duration and an increase in depressive symptoms, and the pollution prevention actions alleviated the health deterioration of environmental pollution for the middle-aged and the elderly. It is imperative for the government to urgently reinforce policy enforcement to decrease air and water pollution and enhance the ability to circumvent pollution for the lower socioeconomic groups.

Associations of ambient air pollution with overnight changes in body composition and sleep-related parameters

This study aims to investigate the association of air pollution with overnight change in 4body composition and sleep-related parameters. Body composition of 197 subjects in New Taipei city was measured before and after sleep by bioelectric impedance analysis. Air pollutant data were collected from Taiwan Environmental Protection Administration. Sleep parameters were examined by polysomnography. We observed fine particulate matter (PM_2.5) decreased arterial oxygen saturation (SaO₂) and increased apnea-hypopnea index (AHI); NO₂ increased arousal, AHI, and decreased mean SaO₂; and O₃ inmcreased mean SaO₂. We observed 0.99-μg/m³ increase in PM_2.5 was associated with 18.8% increase in changes of right arm fat percentage (95% confidence interval (CI): 0.004, 0.375) and 0.011-kg increase in changes of right arm fat mass (95% CI: 0.000, 0.021). 2.45-ppb increase in NO₂ was associated with 0.181-kg decrease in changes of muscle mass (95% CI: -0.147, -0.001), 0.192-kg decrease in changes of fat free mass (95% CI: -0.155, -0.001), 21.1% increase in changes of right leg fat percentage (95% CI: 0.012, 0.160), and 21.3% increase in changes of left leg fat percentage (95% CI: 0.006, 0.168). 1.56-ppb increase in O₃ was associated with 29.3% decrease in changes of right leg fat percentage (95% CI: -0.363, -0.013), 0.058-kg increase in changes of right leg fat free mass (95% CI: 0.008, 0.066), and 0.059-kg increase in changes of right leg muscle mass (95% CI: 0.010, 0.066). We observed AHI was associated with overnight changes in fat percentage, total fat mass, muscle mass, bone mass, fat free mass, extracellular water, basal metabolic rate, leg fat percentage, leg fat mass, and trunk fat percentage (p < 0.05). In conclusion, exposure to air pollutants was associated with overnight body composition changes and sleep-related parameters. Nocturnal changes in total muscle mass and leg fat percentage likely contribute to the relationship between air pollution and obstructive sleep apnea.

Association of short-term exposure to air pollution with depression in patients with sleep-related breathing disorders

Air pollution is associated with sleep-related breathing disorders; however, the effects of air pollution on depression in patients with SRBDs remain unclear. A cross-sectional study was conducted to collect polysomnographic (PSG) data and Beck Depression Inventory-IA (BDI-IA) responses from 568 subjects with SRDBs in a sleep center in 2015 to 2017. Exposure to air pollution, including particulate matter with an aerodynamic diameter of ≤10 μm (PM₁₀), particulate matter with an aerodynamic diameter of ≤2.5 μm (PM_2.5), nitrogen (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO) and ozone (O₃), in 1-month averages was collected. Associations of air pollution with the respiratory disturbance index (RDI), oxygen desaturation index (ODI), arousal index (ARI), sleep architecture, and BDI-IA were examined. We observed that interquartile range (IQR) increases in 1-month PM_2.5, PM₁₀, and NO₂ levels were respectively associated with 4.1/hour (h) (95% confidence interval (CI): 1.7/h to 6.4/h), 3.7/h (95% CI: 1.4/h to 6.0/h) and 1.9/h (95% CI: 0.1/h to 3.7/h) increases in the ARI. For sleep architecture, IQR increases in 1-month PM_2.5 and CO levels were respectively associated with a 6.2% (95% CI: 6.1% to 6.3%) increase in non-rapid eye movement sleep 1 (N1) and a 2.0% (95% CI: -3.8% to -0.1%) decrease in non-rapid eye movement sleep 2 (N2). For depression, an IQR change in the 1-month CO was associated a moderate/severe depressive status according to the BDI-IA (odds ratio, OR: 2.981, p < 0.05; 95% CI: 1.032 to 8.611). Short-term exposure to air pollution increased the risk of arousal and light sleep as well as depression in patients with SRBDs. The results suggest that SRBD patients could be a population at risk for depression due to short-term exposure to air pollution.

Association between household solid fuel use for cooking and sleep disturbance in rural China: findings from the China Kadoorie Biobank data

BACKGROUND

Solid fuel use for cooking is a main source of household air pollution, particularly in rural China. Evidence on the association between household air pollution and sleep quality remains limited. This study aimed to examine the association between household solid fuels used for cooking and sleep disturbance.

METHODS

The data of 283,170 adults from baseline survey of the China Kadoorie Biobank Study were included. Detailed information about exposure to solid fuels used for cooking were collected. Sleep disturbance was indicated as any of the three sleep disorders, including disorders of initiating and maintaining sleep, disorders of early morning awakening, and daytime dysfunction. Logistic regression analysis was used to examine the association between sleep disturbance and level of exposure to household solid fuels used for cooking.

RESULTS

About 18% of participants reported sleep disturbance. Fully adjusted analysis indicated exposure to household solid fuels used for cooking was significantly associated with sleep disturbance. Compared to those with 0-3 years exposure (first tertile) to solid fuels used for cooking, the participants with 3-26 years exposure (second tertile) and >26 years exposure (third tertile) had greater odds of having sleep disturbance at 1.16 (95% CI: 1.12-1.19) and 1.33 (95% CI: 1.29-1.37) times, respectively.

CONCLUSIONS

Use of household solid fuels is associated with prevalence of sleep disturbance; the longer duration of exposure to solid fuels use for cooking, the higher is the prevalence of sleep disturbance. Further study is warranted to examine the underlying mechanisms of the association.

Insomnia associated with traffic noise and proximity to traffic-a cross-sectional study of the Respiratory Health in Northern Europe III population

STUDY OBJECTIVES

Exposure to traffic noise increases the risk of sleeping disturbance, but little is known about the effect of traffic-related air pollution on insomnia symptoms. We aimed to investigate the separate associations of self-reported proximity to traffic and traffic noise with insomnia.

METHODS

This is a cross-sectional study of the population included in the Respiratory Health in Northern Europe study, consisting of randomly selected men and women born between 1945 and 1973, from 7 Northern European centers. Hearing traffic noise in the bedroom, bedroom window proximity to traffic, and insomnia symptoms were self-reported. Bedroom window proximity to traffic was used as a surrogate for exposure to traffic-related air pollution. The following insomnia symptoms were assessed: difficulty initiating sleep, difficulty maintaining sleep, and early morning awakening.

RESULTS

A total of 12,963 individuals was included. Traffic noise was positively associated with all three insomnia symptoms: difficulty initiating sleep (odds ratio [OR] = 3.54; 95% confidence interval [CI]: 1.85, 6.76), difficulty maintaining sleep (OR = 2.95; 95% CI: 1.62, 5.37), and early morning awakening (OR = 3.25; 95% CI: 1.97, 5.37). Proximity to traffic without disturbing noise was associated with difficulty initiating sleep (OR = 1.62; 95% CI: 1.45, 1.82).

CONCLUSIONS

This study adds further support to the identification of traffic noise as a risk factor for insomnia. Proximity to traffic without being exposed to noise was associated with an increased risk of difficulty initiating sleep. Our findings indicate that insomnia may be associated with both traffic noise and traffic-related air pollution.

Chronic exposure to metal fume PM2.5 on inflammation and stress hormone cortisol in shipyard workers: A repeat measurement study

Particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM_2.5) has been linked to adverse health outcomes in welding workers. The objective of this study was to investigate associations of chronic exposure to metal fume PM_2.5 in shipyard workers with health outcomes. A longitudinal study was conducted to determine the effects of metal fume PM_2.5 on FeNO, urinary metals, urinary oxidative stress, inflammation, and stress hormones in workers. There were 20 office workers and 49 welding workers enrolled in this study who were followed-up for a second year. We observed that Fe, Zn, and Mn were abundant in PM_2.5 to which welding workers were personally exposed, whereas PM_2.5 to which office workers were personally exposed was dominated by Pb, Cu, and Zn. We observed in the first and/or second visits that urinary 8-iso-prostaglandin F2-α (PGF2α) and 8-hydroxy-2'-deoxy guanosine (8-OHdG) were significantly increased by exposure. An increase in urinary interleukin (IL)-6 and decreases in urinary serotonin and cortisol were observed in the first and/or second visits after exposure. PM_2.5 was associated with decreases in urinary 8-OHdG and cortisol among workers. Next, we observed that urinary Ni, Co, and Fe had significantly increased among workers after a year of exposure. Urinary metals were associated with decreases in urinary 8-iso-PGF2α and cortisol among workers. Urinary Ni, Cu, and Fe levels were associated with an increase in urinary IL-6 and a decrease in urinary cortisol among workers. In conclusion, chronic exposure to metal fume PM_2.5 was associated with inflammation and a cortisol deficiency in shipyard workers, which could associate with adrenal glands dysfunction.

Environmental exposures and sleep outcomes: A review of evidence, potential mechanisms, and implications

Environmental exposures and poor sleep outcomes are known to have consequential effects on human health. This integrative review first seeks to present and synthesize existing literature investigating the relationship between exposure to various environmental factors and sleep health. We then present potential mechanisms of action as well as implications for policy and future research for each environmental exposure. Broadly, although studies are still emerging, empirical evidence has begun to show a positive association between adverse effects of heavy metal, noise pollution, light pollution, second-hand smoke, and air pollution exposures and various sleep problems. Specifically, these negative sleep outcomes range from subjective sleep manifestations, such as general sleep quality, sleep duration, daytime dysfunction, and daytime sleepiness, as well as objective sleep measures, including difficulties with sleep onset and maintenance, sleep stage or circadian rhythm interference, sleep arousal, REM activity, and sleep disordered breathing. However, the association between light exposure and sleep is less clear. Potential toxicological mechanisms are thought to include the direct effect of various environmental toxicants on the nervous, respiratory, and cardiovascular systems, oxidative stress, and inflammation. Nevertheless, future research is required to tease out the exact pathways of action to explain the associations between each environmental factor and sleep, to inform possible therapies to negate the detrimental effects, and to increase efforts in decreasing exposure to these harmful environmental factors to improve health.

Association of long-term exposure to ambient air pollution with the incidence of sleep disorders: A cohort study in China

BACKGROUND

Sleep disorders have been verified to be associated with adverse health outcomes. Recent studies have linked ambient air pollution to sleep disorders. However, evidence with large sample size and especially prospective studies is very limited.

METHODS

We used data from a prospective cohort study established from 2015 to 2018 in Ningbo, China. Participants were followed-up after baseline survey through linkage to the regional Health Information System (HIS). Sleep disorders were defined based on International Classification of Disease 10 (ICD-10). Spatial-temporal land-use regression (LUR) models were used to estimate the annual exposure to particulate matter with diameter ≤ 2.5 µm (PM_2.5), ≤ 10 µm (PM₁₀) and nitrogen dioxides (NO₂). The associations between long-term exposure to air pollutants and prevalence of sleep disorders were examined using logistic regression models, and Cox regression models for the effects of air pollution on the incidence of sleep disorders. A generalized weighted quantile sum (gWQS) regression was used in the multipollutant analysis.

RESULTS

A total of 38,775 participants were included in the final analysis. Based on baseline data, we observed significant positive associations between air pollution exposure and increased odds of prevalent sleep disorders (Odds Ratio (OR)= 1.48, 95% confidence interval (CI): 1.41-1.55 for PM_2.5; OR= 1.47,95%CI:1.38-1.57 for PM₁₀; OR= 1.38, 95%CI:1.31-1.46 for NO₂). In the longitudinal analysis, hazard ratios for incident sleep disorders associated with per interquartile range (IQR) increase in PM_2.5, PM₁₀ and NO₂ were 1.14 (1.03, 1.25), 1.13 (1.01, 1.27) and 1.13 (1.04, 1.23), respectively. A gWQS regression analysis showed significant association between air pollution mixture and incident sleep disorders (OR=1.11, 95%CI: 1.03-1.20).

CONCLUSIONS

Long-term exposure to PM_2.5, PM₁₀ and NO₂ were associated with increased risk of sleep disorders in a Chinese population. Our findings could provide evidence for a more general role in the adverse health impact of air pollution.

The effect of weather, air pollution and seasonality on the number of patient visits for epileptic seizures: A population-based time-series study

OBJECTIVE

The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures.

METHODS

Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7 days' lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined.

RESULTS

The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH₄, and NO. Six air pollutants, namely CH₄, NO, CO, NO₂, PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R² = 0.422).

CONCLUSION

The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.

Association of long-term exposure to ambient air pollutants with prolonged sleep latency: The Henan Rural Cohort Study

BACKGROUND

Prolonged sleep latency is associated with far-reaching public health consequences. Although evidence about the effect of air pollution on sleep problem has been shown, the effect on sleep latency remained unknown. The study aimed to analyze the association between long-term exposure to air pollution and prolonged sleep latency in rural China.

METHODS

In all, 27935 participants were included in the study from Henan Rural Cohort Study. A satellite-based spatiotemporal model was used to evaluate the 3-year average concentration of air pollutants at the home address of participants before the baseline survey. Air pollutants included NO₂ (nitrogen dioxide), PM₁ (particulate matter with aerodynamic diameters ≤1 μm), PM_2.5 (particulate matter with aerodynamic diameters ≤ 2.5 μm), and PM₁₀ (particulate matter with aerodynamic diametes ≤ 10 μm). A logistic regression model was conducted to assess the odds ratio (OR) and 95% confidence interval (95% CI) between air pollutants and prolonged sleep latency.

RESULTS

There were 5825 (20.85%) participants with prolonged sleep latency. The average concentration of NO₂, PM₁, PM_2.5, and PM₁₀ were 38.22 (2.54) μg/m³, 56.29 (1.75) μg/m³, 72.30 (1.87) μg/m³, and 130.01 (4.58) μg/m³. The odds ratio (95%CI) of prolonged sleep latency with an IQR increase of NO₂, PM₁, PM_2.5, and PM₁₀ were 1.59 (1.33-1.90), 1.23 (1.13-1.33), 1.28 (1.13-1.45) and 1.43 (1.22-1.67). The stratified analysis showed the effect of air pollutants was stronger among those with stroke.

CONCLUSION

Long-term exposure to NO₂, PM₁, PM_2.5 and PM₁₀ were associated with prolonged sleep latency. The adverse impact of air pollution should be considered when treating sleep problems.

The association between traffic-related air pollution and obstructive sleep apnea: A systematic review

Recent evidence suggests that air pollution exposure may be a contributing risk factor for obstructive sleep apnea (OSA), however, current evidence is conflicting. This systematic review aims to determine the association between air pollution and OSA in the general population, and examine for potential effect modification by seasonality, temperature and humidity. Five full-text articles were included in the review out of 905 articles found by systematically searching PubMed, Embase and Scopus databases. The included studies were limited to OSA in adults that were conducted in middle to high-income countries. The results highlight heterogeneity in the diagnostic criteria for OSA and method used to assess air pollution exposure. There is some evidence to support a relationship between air pollution exposure and OSA. However, the duration of exposure to different air pollutants including particulate matter (PM_2.5 and PM₁₀) and nitric oxides (NO₂) in relation to OSA varied across different seasons, temperatures, and countries. This variability of the pollutants across studies warrants a more robust study design using time-series analysis with multiple follow-ups to strengthen the evidence for this relationship before considering its implications.