Long-term exposure to ozone and sleep disorders in children: A multicity study in China

Evidence regarding the link between long-term ambient ozone (O3) exposure and childhood sleep disorders is little. This study aims to examine the associations between long-term exposure to O3 and sleep disorders in children. We conducted a population-based cross-sectional survey, including 185,428 children aged 6-18 years in 173 schools across 14 Chinese cities during 2012 and 2018. Parents or guardians completed a checklist using Sleep Disturbance Scale for Children, and O3 exposure at residential and school addresses was estimated using a satellite-based spatiotemporal model. We used generalized linear mixed models to test the associations with adjustment for factors including socio-demographic variables, lifestyle, meteorology and multiple pollutants. Mean concentrations of O3, particulate matter with diameters ≤2.5 mm (PM2.5) and nitrogen dioxide (NO2) were 89.0 μg/m3, 42.5 μg/m3 and 34.4 μg/m3, respectively. O3 and NO2 concentrations were similar among provinces, while PM2.5 concentration varied significantly among provinces. Overall, 19.4% of children had at least one sleep disorder. Long-term exposure to O3 was positively associated with odds of sleep disorders for all subtypes. For example, each interquartile increment in home-school O3 concentrations was associated with a higher odds ratio for global sleep disorder, at 1.22 (95% confidence interval: 1.18, 1.26). Similar associations were observed for sleep disorder subtypes. The associations remained similar after adjustment for PM2.5 and NO2. Moreover, these associations were heterogeneous regionally, with more prominent associations among children residing in southeast region than in northeast and northwest regions in China. We concluded that long-term exposure to O3 is positively associated with risks of childhood sleep disorders. These associations varied by geographical region of China.

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.

Exposures to particulate matters and childhood sleep disorders-A large study in three provinces in China

OBJECTIVES

Evidence on the link between long-term ambient particulate matter (PM) exposures and childhood sleep disorders were scarce. We examined the associations between long-term exposures to PM2.5 and PM1 (PM with an aerodynamic equivalent diameter <2.5 μm and <1 μm, respectively) with sleep disorders in children.

METHODS

We performed a population-based cross-sectional survey in 177,263 children aged 6 to 18 years in 14 Chinese cities during 2012-2018. A satellite-based spatiotemporal model was employed to estimate four-year annual average PM2.5 and PM1 exposures at residential and school addresses. Parents or guardians completed a checklist using the Sleep Disturbance Scale for Children. We estimated the associations using generalized linear mixed models with adjustment for characteristics of children, parents, and indoor environments.

RESULTS

Long-term PM2.5 and PM1 exposures were positively associated with odds of sleep disorders for almost all domains. For example, increments in PM2.5 and PM1 per 10 μg/m3 were associated with odds ratios of global sleep disorder of 1.24 (95 % confidence interval [CI]: 1.14, 1.35) and 1.31 (95 %CI: 1.18, 1.46), respectively. Similar results were observed for subtypes of sleep disorder. These associations were heterogeneous regionally, with stronger associations among children residing in southeast region than in northeast and northwest regions. Moreover, larger estimates of PM1 were found than that of PM2.5 in southeast region.

CONCLUSION

Long-term PM2.5 and PM1 exposures are independently associated with higher risks of childhood sleep disorders, and these associations vary by geographical region.

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.

Interior decorative volatile organic compounds exposure induces sleep disorders through aberrant branched chain amino acid transaminase 2 mediated glutamatergic signaling resulting from a neuroinflammatory cascade

Air pollution has been recognized as a contributing factor to sleep disorders (SD), which have been correlated with an elevated susceptibility to a variety of human diseases. Nevertheless, research has not definitively established a connection between SD and interior decorative volatile organic compounds (ID-VOCs), a significant indoor air pollutant. In this study, we employed a mouse model exposed to ID-VOCs to explore the impacts of ID-VOCs exposure on sleep patterns and the potential underlying mechanism. Of the 23 key compositions of ID-VOCs identified, aromatic hydrocarbons were found to be the most prevalent. Exposure to ID-VOCs in mice resulted in SD, characterized by prolonged wake fullness and decreased sleep during the light period. ID-VOCs exposure triggered neuroinflammatory responses in the suprachiasmatic nucleus (SCN), with microglia activation leading to the overproduction of inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-1α (IL-1α), and complement component 1q (C1q), ultimately inducing A1 astrocytes. Consequently, the upregulation of branched chain amino acid transaminase 2 (BCAT2) in A1 astrocytes resulted in elevated extracellular glutamate and disruption of the wake-sleep transition mechanism, which might be the toxicological mechanism of SD caused by ID-VOCs.

Contemporary Concise Review 2023: Environmental and occupational lung diseases

Air pollutants have various effects on human health in environmental and occupational settings. Air pollutants can be a risk factor for incidence, exacerbation/aggravation and death due to various lung diseases, including asthma, chronic obstructive pulmonary disease (COPD), hypersensitivity pneumonitis or pneumonia (HP), pulmonary fibrosis such as pneumoconiosis and malignant respiratory diseases such as lung cancer and malignant pleural mesothelioma. Environmental and occupational respiratory diseases are crucial clinical and social issues worldwide, although the burden of respiratory disease due to environmental and occupational causes varies depending on country/region, demographic variables, geographical location, industrial structure and socioeconomic situation. The correct recognition of environmental and occupational lung diseases and taking appropriate measures are essential to their effective prevention.

The Association between Short-Term Exposure to PM1 and Daily Hospital Admission and Related Expenditures in Beijing

Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 μm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 μg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health.

Association Between Home Renovation and Sleeping Problems Among Children Aged 6-18 Years: A Nationwide Survey in China

BACKGROUND

Although the indoor environment has been proposed to be associated with childhood sleep health, to our knowledge no study has investigated the association between home renovation and childhood sleep problems.

METHODS

The study included 186,470 children aged 6-18 years from the National Chinese Children Health Study (2012-2018). We measured childhood sleeping problems via the Chinese version of the Sleep Disturbance Scale for Children (C-SDSC). Information on home renovation exposure within the recent 2 years was collected via parent report. We estimated associations between home renovation and various sleeping problems, defined using both continuous and categorized (binary) C-SDSC t-scores, using generalized mixed models. We fitted models with city as a random effect variable, and other covariates as fixed effects.

RESULTS

Out of the overall participants, 89,732 (48%) were exposed to recent home renovations. Compared to the unexposed group, children exposed to home renovations had higher odds of total sleep disorder (odd ratios [OR] = 1.3; 95% confidence interval [CI] = 1.2, 1.4). Associations varied when we considered different types of home renovation materials. Children exposed to multiple types of home renovation had higher odds of sleeping problems. We observed similar findings when considering continuous C-SDSC t-scores. Additionally, sex and age of children modified the associations of home renovation exposure with some of the sleeping problem subtypes.

CONCLUSIONS

We found that home renovation was associated with higher odds of having sleeping problems and that they varied when considering the type of renovation, cumulative exposure, sex, and age differences.

Association between exposure to heavy metals in atmospheric particulate matter and sleep quality: A nationwide data linkage study

BACKGROUND

Recent studies have demonstrated that long-term exposure to particulate matter (PM) is associated with poor sleep quality. However, no studies have linked PM constituents, particularly heavy metals, to sleep quality.

OBJECTIVE

This study investigated the association between exposure to heavy metals in PM and sleep quality.

METHODS

We obtained nationwide data from the Korean Community Health Survey conducted in 2018 among adults aged 19-80 years. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI). Poor sleep quality was defined as PSQI ≥5. One-year and three-month average concentrations of heavy metals (lead, manganese, cadmium, and aluminum) in PM with diameter ≤10 μm were obtained from nationwide air quality monitoring data and linked to the survey data based on individual district-level residential addresses. Logistic regression analyses were performed after adjusting for age, gender, education level, marital status, smoking status, alcohol consumption, history of hypertension, and history of diabetes mellitus.

RESULTS

Of 32,050 participants, 17,082 (53.3%) reported poor sleep quality. Increases in log-transformed one-year average lead (odds ratio, 1.14; 95% confidence interval, 1.08-1.20), manganese (1.31; 1.25-1.37), cadmium (1.03; 1.00-1.05), and aluminum concentrations (1.17; 1.10-1.25) were associated with poor sleep quality. Increases in log-transformed three-month average manganese (odds ratio, 1.13; 95% confidence interval, 1.09-1.17) and aluminum concentrations (1.28; 1.21-1.35) were associated with poor sleep quality.

CONCLUSION

We showed for the first time that exposure to airborne lead, manganese, cadmium, and aluminum were associated with poor sleep quality. This study may be limited by self-reported sleep quality and district-level exposure data.

Climate Change for the Pulmonologist: A Focused Review

Climate change adversely impacts global health. Increasingly, temperature variability, inclement weather, declining air quality, and growing food and clean water supply insecurities threaten human health. Earth's temperature is projected to increase up to 6.4 °C by the end of the 21st century, exacerbating the threat. Public and health care professionals, including pulmonologists, perceive the detrimental effects of climate change and air pollution and support efforts to mitigate its effects. In fact, evidence is strong that premature cardiopulmonary death is associated with air pollution exposure via inhalation through the respiratory system, which functions as a portal of entry. However, little guidance is available for pulmonologists in recognizing the effects of climate change and air pollution on the diverse range of pulmonary disorders. To educate and mitigate risk for patients competently, pulmonologists must be armed with evidence-based findings of the impact of climate change and air pollution on specific pulmonary diseases. Our goal is to provide pulmonologists with the background and tools to improve patients' health and to prevent adverse outcomes despite climate change-imposed threats. In this review, we detail current evidence of climate change and air pollution impact on a diverse range of pulmonary disorders. Knowledge enables a proactive and individualized approach toward prevention strategies for patients, rather than merely treating ailments reactively.

The association between childhood adiposity in northeast China and anthropogenic heat flux: A new insight into the comprehensive impact of human activities

Anthropogenic heat has been reported to have significant health impacts, but research on its association with childhood adiposity is still lacking. In this study, we matched the 2008-2012 average anthropogenic heat flux, as simulated by a grid estimation model using inventory methods, with questionnaire and measurement data of 49,938 children randomly recruited from seven cities in Northeast China in 2012. After adjusting for social demographic and behavioral factors, we used generalized linear mixed-effect models to assess the association between anthropogenic heat flux and adiposity among children. We also examined the effect modification of various social demographic and behavioral confounders. We found that each 10 W/m2 increase in total anthropogenic heat flux and that from the industry source was associated with an increase of 5.82% (95% CI = 0.84%-11.05%) and 6.62% (95% CI = 0.87%-12.70%) in the odds of childhood adiposity. Similarly, the excess rate of adiposity among children were 5.26% (95% CI = -1.33%-12.29%) and 8.51% (95% CI = 2.24%-15.17%) per 1 W/m2 increase in the anthropogenic heat flux from transportation and buildings, and was 7.94% (95% CI = 2.28%-13.91%) per 0.001 W/m2 increase in the anthropogenic heat flux from human metabolism. We also found generally greater effect estimates among female children and children who were exposed to passive smoking during pregnancy, born by caesarean section, non-breastfed/mixed-fed, or lived within 20 m adjacent to the main road. The potential deleterious effect of anthropogenic heat exposure on adiposity among children may make it a new but major threat to be targeted by future mitigation strategies.

The neighborhood environment and sleep health in adolescents

OBJECTIVE

Neighborhood-level factors, including education, health and environment, and socioeconomic exposures, are important contextual determinants of child health. We explored whether these factors, measured via the Childhood Opportunity Index 2.0, were associated with sleep health in adolescents.

METHODS

Actigraphy was used to assess sleep duration, timing, and efficiency among 110 adolescents in eighth (13.9 (0.4)) and ninth (14.9 (0.4)) grade. Home addresses were geocoded and linked to Childhood Opportunity Index 2.0 scores (including 3 subtype scores and the 29 individual factor Z-scores). Mixed-effects linear regression was used to determine associations between the Childhood Opportunity Index 2.0 scores and the sleep outcomes, adjusting for sex, race, parent education, household income, school grade and weeknight status. Interactions were also tested by school grade, weeknight status, sex, and race.

RESULTS

No associations were observed between overall or subtype scores with sleep outcomes in adolescents. However, we detected associations between select individual Childhood Opportunity Index 2.0 Z-scores, spanning health & environment and education domains, and sleep outcomes. For example, greater fine particulate matter was associated with later timing of sleep onset and offset; ozone concentration was associated with earlier sleep onset and offset; greater exposure to extreme temperature was associated with later sleep onset and offset and increased odds of optimal sleep efficiency.

CONCLUSIONS

Specific neighborhood factors indexed by the Childhood Opportunity Index 2.0 were associated with sleep health among adolescents. In particular, neighborhood air quality measures were associated with sleep timing and efficiency, warranting further investigation.

Association of long-term exposure to air pollution with chronic sleep deprivation in South Korea: A community-level longitudinal study, 2008-2018

BACKGROUND AND OBJECTIVE

Although there are many findings about the effects of fine particulate matter (PM_2.5) and sleep deprivation on health respectively, the association between PM_2.5 and chronic sleep deprivation has rarely been investigated. Thus, we aimed to investigate this association using a nationwide survey in South Korea.

METHOD

We examined the association between long-term exposure to PM_2.5 and chronic sleep deprivation using a national cross-sectional health survey covering the entire 226 districts in inland South Korea from 2008 to 2018, with a machine learning-based national air pollution prediction model with 1 km² spatial resolution.

RESULTS

Chronic sleep deprivation was positively associated with PM_2.5 in the total population (odds ratio (OR): 1.09, 95% confidence interval (CI): 1.05-1.13) and sub-population (low, middle, high population density areas with OR: 1.127, 1.09, and 1.059, respectively). The association was consistently observed in both sexes (males with OR: 1.09, females with OR: 1.09)) and was more pronounced in the elderly population (OR: 1.12) than in the middle-aged (OR: 1.07) and young (OR: 1.09) populations.

CONCLUSIONS

Our results are consistent with the hypothesis regarding the relationship between long-term PM_2.5 exposure and chronic sleep deprivation, and the study provides quantitative evidence for public health interventions to improve air quality that can affect chronic sleep conditions.

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.

Unexpected association between ambient ozone and adult insomnia outpatient visits: A large-scale hospital-based study

Growing evidence indicates that short-term ozone (O₃) exposure has substantial health consequences, but the relationship between short-term ambient O₃ and insomnia, a common sleep disorder, is not clear. This study aimed to investigate the short-term effects of ambient O₃ exposure on outpatient visits for adult insomnia and to explore the potential modifiers. A large-scale multihospital-based study was carried out in Chongqing, the largest city in Southwest China. Daily data on outpatient visits for adult insomnia, average concentrations of ambient air pollutants and meteorological factors were collected. We conducted quasi-Poisson regression with generalized additive model to assess the association between ambient O₃ and outpatient visits for adult insomnia in varied windows of exposure. Subgroup analyses were applied to identify its modifiers. Totally, 140,159 adult insomnia outpatient visits were identified. The daily maximum 8-h average concentration of O₃ was 69 μg/m³ during the study period, which greatly below the updated Chinese and WHO recommended limits (daily maximum 8-h average, O₃: 100 μg/m³). Short-term O₃ exposure was significantly negatively associated with outpatient visits for adult insomnia in different lag periods and the greatest decrease of outpatient visits for adult insomnia was found at lag 02 [0.93% (95% CI: 0.48%, 1.38%)]. Additionally, stronger links between O₃ and adult insomnia outpatient visits were presented in cool seasons, and we did not observe any significant modified effects of gender and age. Moreover, the negative O₃-insomnia association remained robust after controlling for other common air pollutants and comorbidities. In summary, short-term exposure to lower level of ambient O₃, was associated with reduced daily outpatient visits for adult insomnia and such association showed to be more obvious in cool seasons.

Long-term exposure to ambient air pollutants and their interaction with physical activity on insomnia: A prospective cohort study

Exposure to air pollution or lack of physical activity (PA) increases the risk of insomnia. However, evidence on joint exposure to air pollutants is limited, and the interaction of joint air pollutants and PA on insomnia is unknown. This prospective cohort study included 40,315 participants with related data from the UK Biobank, which recruited participants from 2006 to 2010. Insomnia was assessed by self-reported symptoms. The annual average air pollutant concentrations of particulate matter (PM_2.5, PM₁₀), nitrogen oxides (NO₂, NO_X), sulfur dioxide (SO₂) and carbon monoxide (CO) were calculated based on participants' addresses. We applied a weighted Cox regression model to evaluate the correlation between air pollutants and insomnia and newly proposed an air pollution score to assess joint air pollutants effect using a weighted concentration summation after obtaining the weights of each pollutant in the Weighted-quantile sum regression. With a median follow-up of 8.7 years, 8511 participants developed insomnia. For each 10 μg/m³ increase in NO₂, NO_X, PM₁₀, SO₂, the average hazard ratios (AHRs) and 95% confidence interval (CI) of insomnia were 1.10 (1.06, 1.14), 1.06 (1.04, 1.08), 1.35 (1.25, 1.45) and 2.58 (2.31, 2.89), respectively; For each 5 μg/m³ increase in PM_2.5 and each 1 mg/m³ increase in CO, the corresponding AHRs (95%CI) were 1.27 (1.21, 1.34) and 1.83 (1.10, 3.04), respectively. The AHR (95%CI) for insomnia associated with per interquartile range (IQR) increase in air pollution scores were 1.20 (1.15, 1.23). In addition, potential interactions were examined by setting cross-product terms of air pollution score with PA in the models. We observed an interaction between air pollution scores and PA (P = 0.032). The associations between joint air pollutants and insomnia were attenuated among participants with higher PA. Our study provides evidence on developing strategies for improving healthy sleep by promoting PA and reducing air pollution.

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.

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.

What is the role of particulate matter 2.5 (PM2.5) on excess weight? A cross-sectional study in young Spanish people aged 2─14 years

PURPOSE

To assess the relationship between particulate matter 2.5 (PM2.5) levels and the prevalence of excess weight in a representative sample of Spanish young people aged 2─14 years.

METHODS

This was an ecological cross-sectional study using data from the 2017 wave of the Encuesta Nacional de Salud Española (ENSE), a nationally representative survey of the Spanish young and adult population. The final sample included 4378 young Spanish people (51.0% boys). The weight (kg) and height (cm) of the study participants were proxy-reported by parents or guardians. Excess weight was determined according to the age- and sex-criteria of the International Obesity Task Force. The PM_2.5 level was calculated as the annual monitoring data indicator for 2017 among the different regions in Spain. Logistic regression models were performed to estimate the relationships between PM_2.5 and weight.

RESULTS

Compared to young people located in regions with low levels of PM_2.5, those reporting greater odds for excess weight were found in regions with medium PM_2.5 (OR = 1.23; 95% CI, 1.02-1.49) and high PM_2.5 (OR = 1.35; 95% CI, 1.11-1.64) after adjusting for several sociodemographic, lifestyle and environmental covariates.

CONCLUSIONS

The prevalence of excess weight in young people was positively associated with PM_2.5 levels in Spain. This finding supports the hypothesis that air pollution exposure can result in excess weight in the young population, which, in turn, might lead to the development of metabolic disorders. From a socioecological perspective, a practical need to take environmental factors into consideration is important to address unhealthy weight in Spanish young people.

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.

Exposure to fine particulate matter constituents and cognitive function performance, potential mediation by sleep quality: A multicenter study among Chinese adults aged 40-89 years

Although exposure to fine particulate matter (PM_2.5) has been associated with cognitive decline, little is known about which PM_2.5 constituents are more harmful. Recent study on the association between PM_2.5 and sleep quality prompted us to propose that sleep quality may mediate the adverse effects of PM_2.5 components on cognitive decline. Understanding the association between PM_2.5 constituents and cognitive function, as well as the mediating role of sleep quality provides a future intervention target for improving cognitive function. Using data involving 1834 participants from a multicenter cross-sectional study in nine cities of the Beijing-Tianjin-Hebei (BTH) region in China, we undertook multivariable linear regression analyses to quantify the association of annual moving-average PM_2.5 and its chemical constituents with cognitive function and to assess the modifying role of exposure characteristic in this association. Besides, we examined the extent to which this association of PM_2.5 constituents with cognitive function was mediated via sleep quality by a mediation analysis. We observed significantly negative associations between an increase of one interquartile range increase in PM_2.5 [-0.876 (95 % CI: -1.205, -0.548)], organic carbon [-0.481 (95 % CI: -0.744, -0.219)], potassium [-0.344 (95 % CI: -0.530, -0.157)], iron [-0.468 (95 % CI: -0.646, -0.291)], and ammonium ion [-0.125 (95 % CI: -0.197, -0.052)] and cognitive decline. However, we didn't find any individual components more harmful than PM_2.5. Poor sleep quality partially mediated the estimated associations, which were explained ranging from 2.28 % to 11.99 %. Stratification analyses showed that people living in areas with lower greenspace were more susceptible to specific PM_2.5 components. Our study suggests that the adverse effect of suffering from PM_2.5 components is more pronounced among individuals with poor sleep quality, amplifying environmental inequalities in health. Besides reducing environmental pollution, improving sleep quality may be another measure worth considering to improve cognition if our research is confirmed in the future.

Association between ambient air pollution exposure and insomnia among adults in Taipei City

Ambient air pollution was known to cause central nervous system diseases and depressive symptoms. In this study, we examined the associations between air pollution exposure and the prevalence of insomnia in Taipei City of Taiwan. We applied the health information system of electrical medical records of Taipei City Hospital to collect a total of 5108 study subjects (insomniacs N = 912 and non-insomniacs N = 4196) over 18 years old from the family medicine and internal medicine outpatients of six branches of Taipei City Hospital. These patients were grouped into insomniacs and non-insomniacs following the primary insomnia diagnosis (ICD9:780.52, 780.54, 307.41, 307.42, ICD10: G47.00, G47.01, G47.09, F51.01, F51.09) and the prescription times of anxiolytics and hypnotics. We estimated one-year average concentrations of PM2.5, ozone, and NOx before the first date of insomnia diagnosis and the last date of outpatient visit for insomniacs and non-insomniacs, respectively, by using the data of nearest air quality monitoring stations relative to study subjects' residential addresses. Logistic regression analysis was employed to examine the independent effects of air pollution concentrations on the risk of insomnia. One-year average PM2.5, ozone, and NOx levels for insomniacs was significantly higher than those of non-insomniacs. After adjusting for confounding factors, increase each 1(μg/m3) in one-year average PM2.5 showed a statistically significant association with insomnia (the odds ratio 1.610, 95% CI [1.562,1.660]). As to multi pollutants, one-year average PM2.5 (1.624, [1.570, 1.681] and ozone (1.198, [1.094, 1.311]) exposure showed a significant association with insomnia. Subgroup analysis revealed that the influence of PM2.5 and ozone on insomnia have significant risks in people with major chronic disease. This study demonstrated a positive association between PM2.5 and ozone exposure and the prevalence of hypnotic-treated insomnia. Especially, the people with major chronic diseases were with obvious effect of PM2.5 and ozone on risk of insomnia.

Association between air pollution and 24-h movement behaviours in a representative sample of Spanish youth

PURPOSE

The aim of this study was to analyse the relationship between air pollution and 24-h movement guidelines in Spanish children/adolescents.

METHODS

This cross-sectional study analysed secondary data from the Encuesta Nacional de Salud Española (2017), a representative survey for the Spanish population. The original dataset included 6016 Spanish young people (aged 0-14 years). Since the data on 24-h movement recommendations were limited to Spanish young people aged 2-14 years, the final sample included 4398 (49.2% girls) Spanish young people. Air pollution was evaluated by particulate matter 2.5 (PM_2.5) from different Spanish regions and divided into tertiles representing areas with low, medium, and high pollution. Sleep duration and recreational screen time and were reported by the parents/caregivers. Physical activity was evaluated by an adapted version of the International Physical Activity Questionnaire. Time spent in screen time, sleep, and physical activity were classified as meeting or not the 24-h movement guidelines.

RESULTS

After adjusting for several covariates (sex, age, immigrant status, region, socioeconomic status, and body mass index), lower odds of meeting with the 24-h movement recommendations were found in those living in areas with medium (odds ratio [OR] = 0.55; confident interval [CI] 95%, 0.46-0.67) or high air pollution (OR = 0.45; CI 95%, 0.36-0.55), compared with those living in areas with low air pollution.

CONCLUSIONS

The movement behaviour of young people seems to be associated with the presence of air pollution among Spanish youth. Spanish public health agencies could consider the development of strategies to mitigate the health risks for children/adolescents in high air polluted areas.

Neighborhood influences on the development of self-regulation among children of color living in historically disinvested neighborhoods: Moderators and mediating mechanisms

We present a conceptual model of the ways in which built and social environments shape the development of self-regulation in early childhood. Importantly, in centering children of color growing up in historically disinvested neighborhoods, we first describe how systemic structures of racism and social stratification have shaped neighborhood built and social environment features. We then present evidence linking these neighborhood features to children's development of self-regulation. Furthermore, we take a multilevel approach to examining three potential pathways linking neighborhood contexts to self-regulation: school environment and resources, home environment and resources, and child health behaviors. Finally, we consider how racial-ethnic-cultural strengths and multilevel interventions have the potential to buffer children's development of self-regulation in disinvested neighborhood contexts. Advancing multilevel approaches to understand the development of self-regulation among children of color living in historically disinvested neighborhoods is an important step in efforts to promote equity in health and education.

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.

Short-term ambient air pollution exposure and adult primary insomnia outpatient visits in Chongqing, China: A time-series analysis

Growing evidence suggest that air pollutants can be associated with sleep disorders. However, no study has explored the association of short-term air pollution exposure with primary insomnia, a specific type of sleep disorders. To evaluate the correlation of short-term air pollution exposure with adult primary insomnia outpatient visits in Chongqing, China, we collected data of adult primary insomnia outpatient visits and air pollutants' concentrations between 2013 and 2019 and the associations were estimated with single-day lags as well as moving average lags using a generalized additive model. Totally, 23,919 outpatient visits for adult primary insomnia were identified. The daily data of adult insomnia outpatient visits, air pollutants (NO₂, CO, SO₂, O₃, PM₁₀ and PM_2.5) and meteorological conditions (daily mean temperature and relative humidity) were gathered. Short-term exposure to multiple air pollutants, especially NO₂ and SO₂, was associated with adult primary insomnia visits. A 10 μg/m³ increase in NO₂ and SO₂ at lag 05 corresponded to increased primary insomnia outpatient visits 3.87% (95% CI: 1.50%-6.24%) and 7.22% (95% CI: 2.10%-12.35%), respectively. Moreover, stronger links were presented in females and cool seasons for NO₂ while in the elderly for SO₂. Collectively, this time-series study suggested that short-term exposure to air pollutants, especially to NO₂ and SO₂, was associated with higher risk of adult primary insomnia outpatient visits, and such association could to be sex-, age-, and season-modified.

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.

An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations

Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels.

Association between built environments and weight status: evidence from longitudinal data of 9589 Australian children

Background

No studies appear to examine potential associations between changes in built environments across childhood and the developmental trajectories of child weight status.

Objective

Examine the developmental trajectories of child weight status with respect to changes in childhood exposure to the built environments.

Methods

This study used data of 9589 children with biennial follow-up (2004–2016), retrieved from the Longitudinal Study of Australian Children. Changes in objectively-measured child weight status (i.e., body mass index-BMI, waist circumference) were investigated in relation to changes in seven built environments (i.e., neighbourhood safety; green space quality; footpaths and street conditions; public transport; shopping facilities; basic services; and local traffic) subjectively reported by caregivers. Group-based discrete trajectory mixture models were used to classify children according to their developmental trajectories of built environments and weight status. Multilevel multinomial logistic regression was employed to examine associations between built environments and child weight status adjusted for confounding.

Results

Two, four, and six trajectory groups were developed for built environment variables. Three groups namely “moderate”, “high”, and “extreme increase” were generated for each BMI and waist circumference. Findings from multilevel analyses indicated that growing up in neighbourhoods that are considered highly safe, with better quality of green space nearby, and in areas with low local traffic over time are protective against unhealthy weight increase in childhood. Meanwhile, living with better access to shopping facilities and basic services was associated with an unhealthy increase in BMI and/or waist circumference. No clear associations appeared between the quality of footpath and street conditions, access to public transport, and child weight status.

Conclusions

Built environments might act either as a risk or protective factor of an unhealthy increase in child weight status. Enabling health-promoting neighbourhoods (i.e., highly safe, quality green space nearby, low local traffic) is important to support a healthy weight trajectory across childhood.

A quasi-experimental study of parent and child well-being in families of color in the context of COVID-19 related school closure

Families of color living in historically disinvested neighborhoods face a multitude of health disparities which have been exacerbated by COVID-19 and the resulting strategies to mitigate its transmission. School closure, which occurred with little warning and few, if any, resources for preparation, disrupted multiple aspects of families' lives; these disruptions are anticipated to adversely impact mental health and well-being. The current study aims to advance understanding of the experiences of families of young children of color during the pandemic by utilizing a natural experiment design to test impact on child and parent mental health and sleep in the context of COVID-19 related school closure among families in historically disinvested neighborhoods. Data from this study come from an ongoing study of 281 families of color enrolled in 41 pre-kindergarten (pre-K) programs in neighborhoods across New York City (NYC). In NYC, school closure occurred on March 16, 2020, during a data collection period involving phone surveys with parents; the quasi-experimental design allows for comparison of the 198 families who had completed the survey prior to March 16, and the 83 families who completed the survey after March 16, using identical protocols and procedures. Results demonstrate poorer mental health among parents surveyed after school closure as compared to before school closure. No differences were found for parent sleep, child mental health, or child sleep. Implications of this work highlight the need for structural and systemic supports for families faced with compounding stressors as a result of the COVID-19 pandemic and related school closure.

PM2.5 Exposure associated with Microbiota Gut-Brain Axis: Multi-omics Mechanistic Implications from the China BAPE study

Recent studies have shown that PM_2.5 may activate the hypothalamus-pituitary-adrenal (HPA) axis by inducing hormonal changes, potentially explaining the increase in neurological and cardiovascular risks. In addition, an association between PM_2.5 and gut microbiota and metabolites was established. The above evidence represents crucial parts of the gut-brain axis (GBA). In view of this evidence, we proposed a hypothesis that PM_2.5 exposure may affect the HPA axis through the gastrointestinal tract microbiota pathway (GBA mechanism), leading to an increased risk of neurological and cardiovascular diseases. We conducted a real-world prospective repeated panel study in Jinan, China. At each visit, we measured real-time personal PM_2.5 and collected fecal and blood samples. A linear mixed-effects model was used to analyze the association between PM_2.5 and serum biomarkers, gut microbiota, and metabolites. We found that PM_2.5 was associated with increased serum levels of hormones, especially the adrenocorticotropic hormone (ACTH) and cortisol, which are reliable hormones of the HPA axis. Gut microbiota and tryptophan metabolites and inflammation, which are important components of the GBA, were significantly associated with PM_2.5. We also found links between PM_2.5 and changes in the nervous and cardiovascular outcomes, e.g., increases of 19.77% (95% CI: −36.44, 125.69) in anxiety, 1.19% (95% CI: 0.65, 1.74) in fasting blood glucose (FBG), 2.09% (95% CI: 1.48, 2.70) in total cholesterol (TCHOL), and 0.93% (95% CI: 0.14, 1.72) in triglycerides (TG), were associated with 10 μg/m³ increase in PM_2.5 at the lag 0–72 h, which represent the main effects of GBA. This study indicated the link between PM_2.5 and the microbiota GBA for the first time, providing evidence of the potential mechanism for PM_2.5 with neurological and cardiovascular system dysfunction.

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This is a real-world population based panel study using multi-omics technology

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Link between PM_2.5 and microbiota gut-brain axis is reported for the first time

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PM_2.5 affected gut microbiota, tryptophan metabolism, and inflammatory factors

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Important hormones of the HPA axis increased with PM_2.5 exposure

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PM_2.5 was associated with nervous and cardiovascular outcomes

Associations of long-term exposure to ambient air pollution and physical activity with insomnia in Chinese adults

BACKGROUND

Air pollution is a potential environmental risk for sleep disturbance. However, the evidence is very limited in China. On the other hand, physical activity (PA) is a preventive behavior that can improve insomnia, but whether PA mitigates the negative impact of air pollution on insomnia is unknown.

METHODS

We obtained data from the baseline of China Multi-Ethnic Cohort (CMEC) survey, and examined the association between air pollution and insomnia, as well as PA's modification effect of on this association. We included 70,668 respondents and assessed insomnia by self-reported symptoms collected using electronic questionnaires. Using satellite data, we estimated the residence-specified, three-year average PM₁, PM_2.5, PM₁₀ (particulate matter with aerodynamic diameters of ≤1 μm, ≤2.5 μm and 10 μm, respectively), O₃ (ozone), and NO₂ (nitrogen dioxide) concentrations. We established the associations between air pollutants and insomnia through logistic regression. We evaluated the modification impact of total and domain-specific PA (leisure, occupation, housework, transportation) by introducing an interaction term.

RESULTS

Positive associations were observed between long-term exposure to PM₁, PM_2.5, PM₁₀, and O₃ and insomnia symptoms, with ORs (95% CI) of 1.09 (1.03-1.16), 1.11 (1.07-1.15), 1.07 (1.05-1.10) and 1.15 (1.11-1.20), respectively. As total PA increased, the ORs of air pollution for insomnia tended to decrease and then rise. We observed varying modification effects of domain-specific PA. With an increase in leisure PA, the ORs for PM_2.5 and PM₁₀ significantly declined. However, increased ORs of air pollutants were related to insomnia among participants with higher levels of occupational and housework PA.

CONCLUSION

Long-term exposure to higher concentrations of PM₁, PM_2.5, PM₁₀, and O₃ increases the risk of insomnia symptoms. Moderate to high levels of leisure PA alleviate the harmful effects of air pollution on insomnia, while high levels of occupation and housework PA intensify such effects.

Sleep, Classroom Behavior, and Achievement Among Children of Color in Historically Disinvested Neighborhoods

Children of color are more likely to have poor sleep health than White children, placing them at risk for behavioral problems in the classroom and lower academic performance. Few studies, however, have utilized standardized measures of both classroom behavior and achievement. This study examined whether children's sleep (parent and teacher report) in first grade concurrently related to independent observations of classroom behavior and longitudinally predicted achievement test scores in second grade in a sample of primarily Black (86%) children (n = 572; age = 6.8) living in historically disinvested neighborhoods. Higher teacher-reported child sleepiness was associated with lower adaptive behaviors and higher problem behaviors in the classroom, and predicted lower achievement. Parent-reported bedtime resistance and disordered breathing also predicted lower achievement.

Association of long-term exposure to air pollution with chronic sleep deprivation in adults from 141 urban communities in South Korea: a community-level longitudinal study, 2008‒2016

Aims

It has been well known that air pollution and sleep deprivation individually have impacts on human health; however, the association between the two has not been well researched. The aim of this study was to investigate this relationship at a community level.

Methods

We collected sleep outcomes from the Korean Community Health Survey between years of 2008 and 2016. The data contained 1 130 080 selected adults aged ⩾ 19 years, from 141 communities. As sleep outcomes, annual chronic sleep deprivation (% of people who sleep ⩽ 5 h per day on average) and average values of daily mean sleep duration were used. Community-specific annual averages of particulate matter with a diameter ⩽ 10 μm (PM₁₀), nitrogen dioxide (NO₂) and carbon monoxide (CO) were collected and then applied to a linear mixed effects model to estimate the association between air pollution over the past 4 years and sleep outcomes. Population density, green space, health behaviour, and gross regional domestic product per capita variables were considered as confounders in all mixed effect models.

Results

From the linear mixed effect models, we found that the chronic sleep deprivation % was positively associated with PM₁₀ (0.33% increase with 95% CI 0.05–0.60; per 10 μg/m³) and NO₂ (0.68% with 95% CI 0.44–0.92; per 10 ppm). Higher PM₁₀ and NO₂ were also associated with shorter sleep duration, with a reduction of 0.37 min (95% CI −0.33 to 1.07 min; per 10 μg/m³) and 2.09 min (95% CI 1.50–2.68 min; per 10 ppm), respectively. The associations between PM₁₀ and sleep outcomes were higher in females than males and in the older age groups (⩾ 60-years) than in younger age groups (19–39 and 40–59 years). However, the association between NO₂ and sleep outcomes were more higher in males than in females and in the younger age groups (19–39 years) than other age groups.

Conclusions

Our findings provide epidemiological evidence that long-term interventions to reduce air pollutions are anticipated to provide improvements in sleep deficiency.

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.

Bioaccumulation of Toxic Metals in Children Exposed to Urban Pollution and to Cement Plant Emissions

Cement plants located in urban areas can increase health risk. Although children are particularly vulnerable, biomonitoring studies are lacking. Toenail concentration of 24 metals was measured in 366 children (6-10 years), who live and attend school in a city hosting a cement plant. Living addresses and schools were geocoded and attributed to exposed or control areas, according to modeled ground concentrations of PM10 generated by the cement plant. Air levels of PM10 and NO2 were monitored. PM10 levels were higher in the exposed, than in the control area. The highest mean PM10 concentration was recorded close to the cement plant. Conversely, the highest NO2 concentration was in the control area, where vehicular traffic and home heating were the prevalent sources of pollutants. Exposed children had higher concentrations of Nickel (Ni), Cadmium (Cd), Mercury (Hg), and Arsenic (As) than controls. These concentrations correlated each other, indicating a common source. Toenail Barium (Ba) concentration was higher in the control- than in the exposed area. The location of the attended school was a predictor of Cd, Hg, Ni, Ba concentrations, after adjusting for confounders. In conclusion, children living and attending school in an urban area exposed to cement plant emissions show a chronic bioaccumulation of toxic metals, and a significant exposure to PM10 pollution. Cement plants located in populous urban areas seem therefore harmful, and primary prevention policies to protect children health are needed.

Solid fuels use for cooking and sleep health in adults aged 45 years and older in China

Outdoor air pollution has been linked to poor sleep health, but limited studies have investigated the relationship between solid cooking fuels and sleep health in adults. Therefore, we analyzed data from the China Health and Retirement Survey (CHARLS), a national survey of about 17,000 residents aged over 45. Participants were restricted to those who participated in CHARLS 2011, 2013 and 2015 (n = 8,668). Sleep health was indicated by self-reported average sleep hours at night and the numbers of unrested days/week in CHARLS 2015. We analyzed cooking fuel types reported and assessed the duration of solid fuels usage as consistent (indicated use in all three surveys or 6 + years) or inconsistent use (indicated use in one or two surveys or 1-4 years). We found consistent use of solid fuels was associated with a shorter sleep duration (OR = 1.17 95% CI 1.01, 1.35 for ≤ 6 h vs. 7-9 h/day) and higher frequencies of feeling unrested (OR = 1.32 95% CI 1.12, 1.55 for ≥ 5 days/week vs. none) compared with cleaner fuels use. The associations for inconsistent solid fuels use and sleep health were in the similar direction but smaller in magnitude. Further research is needed to confirm our findings and evaluate the exposure impact of specific fuel types to inform intervention strategies.

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.

Neighborhood environments and sleep among children and adolescents: A systematic review

Understanding salient environmental determinants of pediatric sleep is essential for informing interventions and public health initiatives. Emerging evidence suggests that the neighborhood environment can impact pediatric sleep, but this evidence has not yet been systematically reviewed. We conducted a systematic review of the scientific literature on associations between neighborhood environments and sleep in young children (0-5 y), school-aged children (6-12 y) and adolescents (13-18 y). We reviewed 85 articles published between 2003 and 2020. The most commonly examined neighborhood exposure was low socioeconomic status (40 studies), which was associated with sleep outcomes in 58% of studies (primarily shorter sleep duration, later sleep timing, or obstructive sleep apnea). Evidence was stronger for neighborhood safety/crime/violence (21 studies), with 86% of studies reporting associations with sleep outcomes (primarily self- or caregiver-reported sleep problems). Fewer studies examined associations of neighborhood physical environment exposures, including noise (15 studies), the built environment (seven studies), and air pollution (six studies). Limitations of the current body of evidence include 1) limited examination of neighborhood exposures other than socioeconomic status or safety, 2) use of primarily cross-sectional observational study designs, 3) lack of objective sleep outcome assessment, and 4) limits of current exposure assessment methods.

Validity and reliability of the Turkish version of Sleep Disturbance Scale for Children

OBJECT

This study examines the validity and reliability of the Sleep Disturbance Scale for Children (SDSC) in the Turkish language.

METHOD

This scale was translated into the Turkish language by applying the translation-back translation method and content validity analysis. A total of 1903 participants aged 5-15 years were included in the study. A sociodemographic data form, SDSC, and the Children's Sleep Habits Questionnaire (CSHQ) were filled by the parents. Internal consistency analysis, correlation analysis, test-retest analysis, and confirmatory factor analysis were applied to evaluate the reliability and validity of the applied scale.

RESULTS

The internal consistency of the scale was high (Cronbach α = 0.84). Test-retest reliability was found to be high as well. According to the confirmatory factor analysis, the Turkish version of the scale was compatible with the model of the original scale. According to the T-score evaluation, the frequency of sleep disorders was determined to be 4.15%, and the most common sleep disorder was sleep hyperhidrosis. Correlations between the scores of the SDSC and CSHQ were at a satisfactory level.

CONCLUSIONS

These results revealed that the SDSC is a valid and reliable scale that can be used in children aged 5-14 years in Turkey to question sleep disorder symptoms.

Effect of Air Pollution on Obesity in Children: A Systematic Review and Meta-Analysis

Air pollution exposure has been identified as being associated with childhood obesity. Nevertheless, strong evidence of such an association is still lacking. To analyze whether air pollution exposure affects childhood obesity, we conducted a systematic review and meta-analysis utilizing the PRISMA guidelines. Of 7343 studies identified, eight studies that investigated the effects of air pollutant characteristics, including PM_2.5, PM₁₀, PM_coarse, PM_absorbance, NO_x, and NO₂, on childhood obesity were included. The polled effects showed that air pollution is correlated with a substantially increased risk of childhood obesity. PM_2.5 was found to be associated with a significantly increased risk (6%) of childhood obesity (OR 1.06, 95% CI 1.02–1.10, p = 0.003). In addition, PM₁₀, PM_{2.5absorbance}, and NO₂ appeared to significantly increase the risk of obesity in children (OR 1.07, 95% CI 1.04–1.10, p < 0.00; OR 1.23, 95% CI 1.06–1.43, p = 0.07; and OR 1.10, 95% CI 1.04–1.16, p < 0.001, respectively). PM_coarse and NO_x also showed trends towards being associated with an increased risk of childhood obesity (OR 1.07, 95% CI 0.95–1.20, p = 0.291, and OR 1.00, 95% CI 0.99–1.02, p = 0.571, respectively). Strong evidence was found to support the theory that air pollution exposure is one of the factors that increases the risk of childhood obesity.

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.

Long-term exposure to ambient PM1 strengthened the association of depression/anxiety symptoms with poor sleep quality: The Henan Rural Cohort study

Evidence from numerous epidemiological studies for the relationship between mental disorder and sleep quality was inconclusive and few studies assessed the modification effect of exposure to ambient air PM₁ (particulate matter with an aerodynamic diameter ≤ 1.0 µm) on this association. In this study, 27,572 participants aged 18-79 years from The Henan Rural Cohort study were included in the final analyses. The Patient Health Questionnaire-2 (PHQ-2) and Generalized Anxiety Disorder-2 (GAD-2) scales were used to estimate the frequency of depression and anxiety symptoms of all participants, respectively. The Pittsburgh Sleep Quality Index (PSQI) scale was used to assess night sleep quality and PSQI global score (GSC) ≥ 6 was classified as poor sleep quality. The three-year average exposure concentration of PM₁ before the baseline survey was determined as long-term exposure concentration of ambient PM₁. Logistic regression model was conducted to estimate the independent or joint effect of depression/anxiety symptoms and ambient PM₁ exposure on poor sleep quality. In the adjusted models, the odds ratios (ORs) and 95% confidence intervals (95% CIs) of poor sleep quality associated with depression and anxiety symptoms were 3.75 (3.37, 4.17) and 3.42 (3.06, 3.81), respectively, and that associated with long-term exposure to PM₁ was 1.06 (1.03, 1.09). An interaction effect was observed between anxiety symptoms score and PM₁ concentration on poor sleep quality. With the increment of PM₁ concentration, the association was strengthened between depression/anxiety symptoms and poor sleep quality. Besides, compared with the reference group, the ORs (95% CIs) of poor sleep quality in those with comorbidity of depression and anxiety symptoms were 4.98 (3.95, 6.29), 5.23 (3.98, 6.87), 5.76 (4.42, 7.49), and 5.58 (3.83, 8.14), respectively, from the first to the fourth quartile level of the PM₁ concentration. These findings suggested that long-term exposure to PM₁ strengthened the association of depression/anxiety symptoms with poor sleep quality in rural China.

Experimental study on sleep quality affected by carbon dioxide concentration

This study comprehensively investigated the impact of indoor carbon dioxide (CO₂ ) concentration on sleep quality. Three experimental conditions (800, 1900, 3000 ppm) were created in chambers decorated as bedroom and other environmental parameters that may influence the sleep quality were under strict control. Sleep quality of 12 subjects (6 men and 6 women) was monitored for 54 consecutive days through sleep quality questionnaire and physiological measures. Both subjective and physiological results showed that sleep quality decreased significantly with the increase of CO₂ concentration, and the comprehensive questionnaire score at 3000 ppm was only 80.8% of that at 800 ppm. A linear positive correlation was found between sleep onset latency (SOL) and CO₂ concentration, while a linear negative correlation occurred between slow-wave sleep (SWS) and CO₂ concentration. In addition, in the same sleep environment, men had higher subjective questionnaire scores after wake-up, longer SWS and shorter SOL, which lead to a better sleep quality compared with women, and there was a significant gender difference in sleep quality at 800 ppm (P < .05).

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

OBJECTIVE/BACKGROUND

Perceived environmental pollution may play a significant role in understanding environmentally induced health-related symptoms. This study aimed to determine whether perceived environmental pollution is associated with poor sleep quality.

METHODS

We conducted a cross-sectional study using data from a nationwide sample of 162,797 individuals aged ≥19 years from the 2018 Korea Community Health Survey. The Pittsburgh Sleep Quality Index was used for assessing sleep quality. Five types of perceived environmental pollutants involving air, water, soil, noise, and green space were assessed. We investigate the association between perceived environmental pollution and poor sleep quality. We also investigated whether an increasing number of perceived environmental pollutants magnified the odds of poor sleep quality.

RESULTS

The prevalence of poor sleep quality was 42.7% (n = 69,554), and 15.6%, 10.1%, 11.9%, 23.0%, and 11.5% reported perceived environmental pollution concerning air, water, soil, noise, and green space, respectively. A perception of air, soil, or noise pollution was significantly associated with poor sleep quality. In addition, those perceiving a greater number of environmental pollutants had significantly higher odds of poor sleep quality. Notably, this association was magnified in individuals living in rural areas.

CONCLUSIONS

Perceived environmental pollution was significantly associated with poor sleep quality. Our results suggest that a more comprehensive exposure to environmental pollution may not only have a worse effect on health outcomes including sleep quality.

Physical activity in an air-polluted environment: behavioral, psychological and neuroimaging protocol for a prospective cohort study (Healthy Aging in Industrial Environment study - Program 4)

BACKGROUND

Air pollution has been linked to increased mortality and morbidity. The Program 4 of the Healthy Aging in Industrial Environment study investigates whether the health and wellbeing benefits of physical activity (PA) can be fully realized in individuals living in highly polluted environments. Herein, we introduce the behavioral, psychological and neuroimaging protocol of the study.

METHODS

This is a prospective cohort study of N = 1500 individuals aged 18-65 years comparing: (1) individuals living in the highly polluted, industrial region surrounding the city of Ostrava (n = 750), and (2) controls from the comparison region with relative low pollution levels in Southern Bohemia (n = 750). Quota sampling is used to obtain samples balanced on age, gender, PA status (60% active runners vs. 40% insufficiently active). Participants are screened and complete baseline assessments through online questionnaires and in-person lab-based assessments of physiological, biomechanical, neuroimaging and cognitive function parameters. Prospective 12-month intensive monitoring of air pollution and behavioral parameters (PA, inactivity, and sleep) follows, with a focus on PA-related injuries and psychological factors through fitness trackers, smartphones, and mobile apps. Subsequently, there will be a 5-year follow-up of the study cohort.

DISCUSSION

The design of the study will allow for (1) the assessment of both short-term variation and long-term change in behavioral parameters, (2) evaluation of the incidence of musculoskeletal injuries and psychological factors impacting behavior and injury recovery, and (3) the impact that air pollution status (and change) has on behavior, psychological resilience, and injury recovery. Furthermore, the integration of MRI techniques and cognitive assessment in combination with data on behavioral, biological and environmental variables will provide an opportunity to examine brain structure and cognitive function in relation to health behavior and air pollution, as well as other factors affecting resilience against and vulnerability to adverse changes in brain structure and cognitive aging. This study will help inform individuals about personal risk factors and decision-makers about the impact of environmental factors on negative health outcomes and potential underlying biological, behavioral and psychological mechanisms. Challenges and opportunities stemming from the timing of the study that coincided with the COVID-19 pandemic are also discussed.