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

An association between PM2.5 components and respiratory infectious diseases: A China's mainland-based study

The particulate matter with diameter of less than 2.5 µm (PM2.5) is an important risk factor for respiratory infectious diseases, such as scarlet fever, tuberculosis, and similar diseases. However, it is not clear which component of PM2.5 is more important for respiratory infectious diseases. Based on data from 31 provinces in mainland China obtained between 2013 and 2019, this study investigated the effects of different PM2.5 components, i.e., sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and organic matter (OM), and black carbon (BC), on respiratory infectious diseases incidence [pulmonary tuberculosis (PTB), scarlet fever (SF), influenza, hand, foot, and mouth disease (HFMD), and mumps]. Geographical probes and the Bayesian kernel machine regression (BKMR) model were used to investigate correlations, single-component effects, joint effects, and interactions between components, and subgroup analysis was used to assess regional and temporal heterogeneity. The results of geographical probes showed that the chemical components of PM2.5 were associated with the incidence of respiratory infectious diseases. BKMR results showed that the five components of PM2.5 were the main factors affecting the incidence of respiratory infectious diseases (PIP>0.5). The joint effect of influenza and mumps by co-exposure to the components showed a significant positive correlation, and the exposure-response curve for a single component was approximately linear. And single-component modelling revealed that OM and BC may be the most important factors influencing the incidence of respiratory infections. Moreover, respiratory infectious diseases in southern and southwestern China may be less affected by the PM2.5 component. This study is the first to explore the relationship between different components of PM2.5 and the incidence of five common respiratory infectious diseases in 31 provinces of mainland China, which provides a certain theoretical basis for future research.

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.

Associations of light exposure patterns with sleep among Dutch children: The ABCD cohort study

Light exposure affects the circadian system and consequently can affect sleep quality. Only few studies examined this relationship in children. We evaluated associations between light exposure patterns and sleep metrics in children. We measured the sleep parameters of 247 Dutch children, aged between 11 and 13 years and recruited from the ABCD cohort, using actigraphy and sleep records for 7 consecutive nights. Personal light exposures were measured with a light meter during the whole day and night. We applied generalized mixed-effects regression models, adjusted for possible confounders, to evaluate the associations of light exposure patterns on sleep duration, sleep efficiency and sleep-onset delay. In the models mutually adjusted for potential confounders, we found the amount of hours between the first time of bright light in the morning and going to sleep and the duration of bright light to be significantly associated with decreased sleep duration (in min; β: -2.02 [95% confidence interval: -3.84, -0.25], β: -8.39 [95% confidence interval: -16.70, -0.07], respectively) and with shorter sleep-onset delay (odds ratio: 0.88 [95% confidence interval: 0.80, 0.97], odds ratio: 0.40 [95% confidence interval: 0.19, 0.87], respectively). Increased light intensities at night were associated with decreased sleep duration (T2 β: -8.54 [95% confidence interval: -16.88, -0.20], T3 β: -14.83 [95% confidence interval: -28.04, -1.62]), while increased light intensities before going to bed were associated with prolonged sleep onset (odds ratio: 4.02 [95% confidence interval: 2.09, 7.73]). These findings further suggest that children may be able to influence their sleep quality by influencing the light exposure patterns during day and night.

Long-term influence of air pollutants on morbidity and all-cause mortality of cardiometabolic multi-morbidity: A cohort analysis of the UK Biobank participants

BACKGROUND

The effects of air pollutants on cardiometabolic diseases (CMDs) have been widely explored, whereas their influences on cardiometabolic multi-morbidity (CMM) were not clear.

METHODS

We employed the UK Biobank cohort (N = 317,160) to study the association between six air pollutants (PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx) and four CMDs including type II diabetes (T2D), coronary artery disease (CAD), stroke and hypertension. CMM was defined as occurrence of two or more of the four diseases. Multi-state Cox models were performed to estimate hazard ratio (HR) and its 95% confidence interval (95%CI).

RESULTS

During a median follow-up of 12.8 years, 52,211 participants developed only one CMD, 15,446 further developed CMM, and 16,861 ultimately died. It was demonstrated that per interquartile range increase (IQR) increases in PM2.5, PM10, PM2.5-10, PM2.5abs, NO2, and NOx would increase 12% (9%-15%), 4% (1%-7%), 3% (1%-6%), 7% (4%-10%), 11% (8%-15%) and 10% (7%-13%) higher risk of developing one CMD from health baseline; 7% (2%-12%), 8% (3%-13%), 6% (2%-11%), 10% (5%-15%), 13% (7%-18%) and 10% (5%-15%) greater risk of occurring CMM from one CMD baseline; and 11% (-2%∼26%), 22% (7%-38%), 17% (3%-32%), 31% (16%-49%), 33% (17%-51%) and 32% (17%-50%) larger risk of causing death from CMM baseline, respectively.

CONCLUSIONS

We revealed that people living in areas with high air pollution suffered from higher hazard of CMD, CMM and all-cause mortality; our findings implied keeping clean air was an effective approach to prevent or mitigate initiation, progression, and death from healthy to CMDs and from CMDs to CMM.

Exposure to polycyclic aromatic hydrocarbons increases the risk of poor sleep pattern in US adults: results from the NHANES (2005-2010)

Recently, polycyclic aromatic hydrocarbons (PAHs) were found to be linked to various diseases. The current study's objective was to explore whether or not there was a relation between PAH exposure and poor sleep pattern. We evaluated nine urine PAH metabolites as exposures in our cross-sectional research based on the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2010. Logistic regression, restricted cubic spline regression (RCS) model, weighted quantile sum (WQS) regression, subgroup analysis, and mediation analysis were used to assess the associations between PAH metabolism and poor sleep pattern risk. After controlling for all confounding variables, several primary PAH metabolites, namely 1-hydroxynapthalene (1-NAP, OR 1.32, 95% CI 1.04-1.68), 2-hydroxyfluorene (2-FLU, OR 1.34, 95% CI 1.05-1.71), 1-hydroxyphenanthrene (1-PHE, OR 1.30, 95% CI 1.03-1.64), 9-hydroxyfluorene (9-FLU, OR 1.38, 95% CI 1.09-1.74), and ∑PAHs (OR 1.33, 95% CI 1.05-1.69), compared to the bottom tertile, were associated with increased risk of poor sleep pattern. The WQS regression analysis showed that 9-FLU and 1-NAP comprised the two most important factors related to poor sleep pattern. Mediation analysis revealed that inflammation acted as a mediator between PAHs and the prevalence of poor sleep pattern. In conclusion, exposure to PAHs may be associated with poor sleep pattern. Inflammation is a mediator of the effects of PAH exposure on poor sleep pattern.

Association of multiple air pollutants with oxygen saturation during sleep in COPD patients: Effect modification by smoking status and airway inflammatory phenotypes

Air pollution contributes substantially to the development of chronic obstructive pulmonary disease (COPD). To date, the effect of air pollution on oxygen saturation (SpO₂) during sleep and potential susceptibility factors remain unknown. In this longitudinal panel study, real-time SpO₂ was monitored in 132 COPD patients, with 270 nights (1615 h) of sleep SpO₂ recorded. Exhaled nitric oxide (NO), hydrogen sulfide (H₂S) and carbon monoxide (CO) were measured to assess airway inflammatory characteristics. Exposure levels of air pollutants were estimated by infiltration factor method. Generalized estimating equation was used to investigate the effect of air pollutants on sleep SpO₂. Ozone, even at low levels (<60 μg/m³), was significantly associated with decreased SpO₂ and extended time of oxygen desaturation (SpO₂ < 90%), especially in the warm season. The associations of other pollutants with SpO₂ were weak, but significant adverse effects of PM₁₀ and SO₂ were observed in the cold season. Notably, stronger effects of ozone were observed in current smokers. Consistently, smoking-related airway inflammation, characterized by higher levels of exhaled CO and H₂S but lower NO, significantly augmented the effect of ozone on SpO₂ during sleep. This study highlights the importance of ozone control in protecting sleep health in COPD patients.

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.

Urinary phthalates, phenols, and parabens in relation to sleep health markers among a cohort of Mexican adolescents

INTRODUCTION

Emerging research has shed light on the potential impact of environmental toxicants on sleep health, however, it remains unclear if these associations exist during adolescence and whether associations differ by sex. This study aimed to examine associations between phthalates, parabens, and phenols on adolescent sleep health using cross-sectional data from 470 participants from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) study.

MATERIAL AND METHODS

In 2015, spot urine samples were analyzed for exposure biomarkers of 14 phthalate metabolites, seven phenol, and four paraben analytes. Over seven consecutive days, sleep duration, midpoint, and fragmentation were assessed with wrist-actigraphy. We examined associations between summary phthalates, individual phthalate metabolites, and phenol and paraben analytes with mean weekday sleep duration, midpoint, and fragmentation using linear regression models adjusted for specific-gravity and sex, age, pubertal status, smoking and alcohol behavior, physical activity, and screen time.

RESULTS

Mean (SD) age was 13.8 (2.1) years; 53.5 % were female. Σ Plastic - summary measure for toxicants from plastic sources - and Σ DEHP and its metabolites, were associated with longer sleep duration in the unstratified sample. To illustrate, every 1-unit log increase in Σ DEHP was associated with 7.7 min (95 % CI: 0.32, 15.1; p < 0.05) longer duration. Summary measures of toxicants from plastic sources, personal care products, anti-androgenic toxicants, and multiple individual phthalates, phenols, and parabens were associated with later midpoint. The midpoint associations were largely female-specific. There were no associations with sleep fragmentation.

CONCLUSIONS

Higher EDC exposure may be related to longer sleep duration and later sleep timing during adolescence, and associations may vary by toxicant and according to sex.

Association between exposure to light at night (LAN) and sleep problems: A systematic review and meta-analysis of observational studies

BACKGROUND

Accumulating evidence have investigated the effects of nighttime light exposure on sleep problems. Nevertheless, the evidence of the relationship between light at night (LAN) and sleep problems remains scarce and inconsistent.

OBJECTIVE

Conducted a systematic review and meta-analysis based on observational studies to examine the association between LAN exposure and sleep problems among human subjects.

METHODS

We systematically searched three databases (PubMed, Web of Science, and Embase) to identify potentially eligible studies through May 25, 2022. The risk of bias and the quality of the generated evidence were assessed by two authors using the National Toxicology Program's Office of Health Assessment and Translation (OHAT) risk of bias rating tool and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guideline. Random-effects model was applied to synthesize the risk estimates across eligible studies. The heterogeneity of included studies was quantified by the statistics of I².

RESULTS

A total of 7 cross-sectional studies comprising 577,932 participants were included. Individuals with higher levels of LAN exposure were associated with a 22 % (Summary Odds Ratio, SOR: 1.22, 95 %CI: 1.13-1.33) increased prevalence of sleep problems. The pooled effect size of indoor LAN exposure (SOR: 1.74, 95%CI: 1.27-2.37) associated with sleep problems was significantly higher than outdoor LAN exposure (SOR: 1.19, 95%CI: 1.11-1.29; P = 0.022). Additionally, dose-response analysis demonstrated that LAN intensity threshold exceeding 5.8 nW/cm²/sr (SOR: 1.04, 95%CI: 1.01-1.07) had a significant effect on sleep problems and the prevalence of sleep problems was increasing with increase in LAN intensity.

CONCLUSIONS

Overall, our findings support the detrimental effects of LAN exposure on sleep. Maintaining bedroom darkness at night may be a feasible measure to reduce the prevalence of sleep problems. Future longitudinal studies with more advanced LAN assessment methods are required to move the field forward.

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.