Transportation Noise Pollution and Cardiovascular Health.

Epidemiological studies have found that transportation noise increases the risk for cardiovascular morbidity and mortality, with solid evidence for ischemic heart disease, heart failure, and stroke. According to the World Health Organization, at least 1.6 million healthy life years are lost annually from traffic-related noise in Western Europe. Traffic noise at night causes fragmentation and shortening of sleep, elevation of stress hormone levels, and increased oxidative stress in the vasculature and the brain. These factors can promote vascular (endothelial) dysfunction, inflammation, and arterial hypertension, thus elevating cardiovascular risk. The present review focusses on the indirect, nonauditory cardiovascular health effects of noise. We provide an updated overview of epidemiological research on the effects of transportation noise on cardiovascular risk factors and disease, and mechanistic insights based on the latest clinical and experimental studies and propose new risk markers to address noise-induced cardiovascular effects in the general population. We will discuss the potential effects of noise on vascular dysfunction, oxidative stress, and inflammation in humans and animals. We will elaborately explain the underlying pathomechanisms by alterations of gene networks, epigenetic pathways, circadian rhythm, signal transduction along the neuronal-cardiovascular axis, and metabolism. We will describe current and future noise mitigation strategies. Finally, we will conduct an overall evaluation of the status of the current evidence of noise as a significant cardiovascular risk factor.

The dynamic responses of mood and sleep physiology to chronic sleep restriction and subsequent recovery sleep.

Healthy sleep of sufficient duration preserves mood and disturbed sleep is a risk factor for a range of psychiatric disorders. As adults commonly experience chronic sleep restriction (SR), an enhanced understanding of the dynamic relationship between sleep and mood is needed, including whether susceptibility to SR-induced mood disturbance differs between sexes. To address these gaps, data from N=221 healthy adults who completed one of two multi-day laboratory studies with identical 9-day SR protocols were analyzed. Participants randomized to the SR (n=205) condition underwent 5 nights of SR to 4 h time-in-bed and were then randomized to one of seven sleep doses that ranged from 0 h to 12 h in 2 h increments; participants randomized to the control (n=16) condition received 10 h time-in-bed on all study nights. The Profile of Mood States (POMS) was used to assess mood every 2 h during wakefulness and markers of sleep homeostasis (EEG slow-wave activity) were derived via polysomnography. Mood progressively deteriorated across SR with marked disturbances in somatic mood components. Altered sleep physiology contributed to mood disturbance whereby increased EEG slow-wave activity was associated with increased POMS Total Mood Disturbance scores, a finding specific to males. Mood was restored in a dose-response fashion where improvements were greater with longer sleep doses. These findings suggest that when lifestyle and environmental factors are inhibited in the laboratory, the affective consequences of chronic sleep loss are primarily somatic mood disturbances. Altered sleep homeostasis may contribute to mood disturbance, yet sleep-dependent mechanisms may be sex-specific.

Sleep deprivation attenuates neural responses to outcomes from risky decision-making.

Sleep loss impacts a broad range of brain and cognitive functions. However, how sleep deprivation affects risky decision-making remains inconclusive. This study used functional MRI to examine the impact of one night of total sleep deprivation (TSD) on risky decision-making behavior and the underlying brain responses in healthy adults. In this study, we analyzed data from N = 56 participants in a strictly controlled 5-day and 4-night in-laboratory study using a modified Balloon Analogue Risk Task. Participants completed two scan sessions in counter-balanced order, including one scan during rested wakefulness (RW) and another scan after one night of TSD. Results showed no differences in participants' risk-taking propensity and risk-induced activation between RW and TSD. However, participants showed significantly reduced neural activity in the anterior cingulate cortex and bilateral insula for loss outcomes, and in bilateral putamen for win outcomes during TSD compared with RW. Moreover, risk-induced activation in the insula negatively correlated with participants' risk-taking propensity during RW, while no such correlations were observed after TSD. These findings suggest that sleep loss may impact risky decision-making by attenuating neural responses to decision outcomes and impairing brain-behavior associations.

Long-term influence of sleep/wake history on the dynamic neurobehavioural response to sustained sleep restriction.

Chronic sleep restriction, common in today's 24/7 society, causes cumulative neurobehavioural impairment, but the dynamics of the build-up and dissipation of this impairment have not been fully elucidated. We addressed this knowledge gap in a laboratory study involving two, 5-day periods of sleep restriction to 4 hr per day, separated by a 1-day dose-response intervention sleep opportunity. We measured sleep physiological and waking neurobehavioural responses in 70 healthy adults, each randomized to one of seven dose-response intervention sleep doses ranging from 0 to 12 hr, or a non-sleep-restricted control group. As anticipated, sleep physiological markers showed homeostatic dynamics throughout the study, and waking neurobehavioural impairment accumulated across the two sleep restriction periods. Unexpectedly, there was only a slight and short-lived effect of the 1-day dose-response intervention sleep opportunity. Whether the dose-response intervention sleep opportunity involved extension, further restriction or total deprivation of sleep, neurobehavioural functioning during the subsequent second sleep restriction period was dominated by prior sleep-wake history. Our findings revealed a profound and enduring influence of long-term sleep-wake history as a fundamental aspect of the dynamic regulation of the neurobehavioural response to sleep loss.

Effects of Aircraft Noise on Sleep: Federal Aviation Administration National Sleep Study Protocol.

Aircraft noise can disrupt sleep and impair recuperation. The last U.S. investigation into the effects of aircraft noise on sleep dates back more than 20 years. Since then, traffic patterns and the noise levels produced by single aircraft have changed substantially. It is therefore important to acquire current data on sleep disturbance relative to varying degrees of aircraft noise exposure in the U.S. that can be used to check and potentially update the existing noise policy. This manuscript describes the design, procedures, and analytical approaches of the FAA's National Sleep Study. Seventy-seven U.S. airports with relevant nighttime air traffic from 39 states are included in the sampling frame. Based on simulation-based power calculations, the field study aims to recruit 400 participants from four noise strata and record an electrocardiogram (ECG), body movement, and sound pressure levels in the bedroom for five consecutive nights. The primary outcome of the study is an exposure-response function between the instantaneous, maximum A-weighted sound pressure levels (dBA) of individual aircraft measured in the bedroom and awakening probability inferred from changes in heart rate and body movement. Self-reported sleep disturbance due to aircraft noise is the secondary outcome that will be associated with long-term average noise exposure metrics such as the Day-Night Average Sound Level (DNL) and the Nighttime Equivalent Sound Level (Lnight). The effect of aircraft noise on several other physiological and self-report outcomes will also be investigated. This study will provide key insights into the effects of aircraft noise on objectively and subjectively assessed sleep disturbance.

Antidepressant effects of acute sleep deprivation are reduced in highly controlled environments.

BACKGROUND: Numerous studies summarized in a recent meta-analysis have shown sleep deprivation rapidly improves depressive symptoms in approximately 50 % of individuals with major depressive disorder (MDD), however those studies were typically conducted in clinical settings. Here we investigated the effects of sleep deprivation utilizing a highly controlled experimental approach. METHODS: 36 antidepressant-free individuals with MDD and 10 healthy controls (HC) completed a 5 day/4-night protocol consisting of adaptation, baseline, total sleep deprivation (TSD), and recovery phases. Light was kept consistently dim (≤50 lx), meals were regulated, and activity was restricted. In-the-moment mood was assessed using a modified Hamilton Rating Scale for Depression (HRSD) at screening and each morning following the experimental nights. RESULTS: Day of study had a significant effect on mood in both groups. Post-hoc analyses revealed that significant effects were attributed to mood improvement in the MDD group following study initiation prior to beginning TSD, and in the HC group following recovery sleep, but were not due to mood improvement in the MDD group during TSD. No further improvement in mood occurred during 36 h of TSD. LIMITATIONS: Strict eligibility requirements may limit generalizability. The requirement to be medication free may have biased toward a less severely depressed sample. CONCLUSIONS: Results revealed that individuals with moderate MDD can experience a significant reduction in depressive symptoms upon entering a highly controlled laboratory environment. Environmental effects on mood can be substantial and need to be considered.

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.

Effects of additive sensory noise on cognition.

Background: Adding noise to a system to improve a weak signal's throughput is known as stochastic resonance (SR). SR has been shown to improve sensory perception. Some limited research shows noise can also improve higher order processing, such as working memory, but it is unknown whether SR can broadly improve cognition. Objective: We investigated cognitive performance while applying auditory white noise (AWN) and/or noisy galvanic vestibular stimulation (nGVS). Methods: We measured cognitive performance (n = 13 subjects) while completing seven tasks in the cognition test battery (CTB). Cognition was assessed with and without the influence of AWN, nGVS, and both simultaneously. Performance in speed, accuracy, and efficiency was observed. A subjective questionnaire regarding preference for working in noisy environments was collected. Results: We did not find broad cognitive performance improvement under the influence of noise (p > 0.1). However, a significant interaction was found between subject and noise condition for accuracy (p = 0.023), indicating that some subjects exhibited cognitive changes with the addition of noise. Across all metrics, noisy environment preference may trend to be a potential indicator of whether subjects will exhibit SR cognitive benefits with a significant predictor in efficiency (p = 0.048). Conclusion: This study investigated using additive sensory noise to induce SR in overall cognition. Our results suggest that using noise to improve cognition is not applicable for a broad population; however, the effect of noise differs across individuals. Further, subjective questionnaires may be a means to identify which individuals are sensitive to SR cognitive benefits, but further investigation is needed.

Enhanced amygdala-cingulate connectivity associates with better mood in both healthy and depressive individuals after sleep deprivation.

Sleep loss robustly disrupts mood and emotion regulation in healthy individuals but can have a transient antidepressant effect in a subset of patients with depression. The neural mechanisms underlying this paradoxical effect remain unclear. Previous studies suggest that the amygdala and dorsal nexus (DN) play key roles in depressive mood regulation. Here, we used functional MRI to examine associations between amygdala- and DN-related resting-state connectivity alterations and mood changes after one night of total sleep deprivation (TSD) in both healthy adults and patients with major depressive disorder using strictly controlled in-laboratory studies. Behavioral data showed that TSD increased negative mood in healthy participants but reduced depressive symptoms in 43% of patients. Imaging data showed that TSD enhanced both amygdala- and DN-related connectivity in healthy participants. Moreover, enhanced amygdala connectivity to the anterior cingulate cortex (ACC) after TSD associated with better mood in healthy participants and antidepressant effects in depressed patients. These findings support the key role of the amygdala-cingulate circuit in mood regulation in both healthy and depressed populations and suggest that rapid antidepressant treatment may target the enhancement of amygdala-ACC connectivity.

Associations of bedroom PM2.5, CO2, temperature, humidity, and noise with sleep: An observational actigraphy study.

OBJECTIVE: Climate change and urbanization increasingly cause extreme conditions hazardous to health. The bedroom environment plays a key role for high-quality sleep. Studies objectively assessing multiple descriptors of the bedroom environment as well as sleep are scarce. METHODS: Particulate matter with a particle size <2.5 µm (PM2.5), temperature, humidity, carbon dioxide (CO2), barometric pressure, and noise levels were continuously measured for 14 consecutive days in the bedroom of 62 participants (62.9% female, mean ± SD age: 47.7 ± 13.2 years) who wore a wrist actigraph and completed daily morning surveys and sleep logs. RESULTS: In a hierarchical mixed effect model that included all environmental variables and adjusted for elapsed sleep time and multiple demographic and behavioral variables, sleep efficiency calculated for consecutive 1-hour periods decreased in a dose-dependent manner with increasing levels of PM2.5, temperature, CO2, and noise. Sleep efficiency in the highest exposure quintiles was 3.2% (PM2.5, p < .05), 3.4% (temperature, p < .05), 4.0% (CO2, p < .01), and 4.7% (noise, p < .0001) lower compared to the lowest exposure quintiles (all p-values adjusted for multiple testing). Barometric pressure and humidity were not associated with sleep efficiency. Bedroom humidity was associated with subjectively assessed sleepiness and poor sleep quality (both p < .05), but otherwise environmental variables were not statistically significantly associated with actigraphically assessed total sleep time and wake after sleep onset or with subjectively assessed sleep onset latency, sleep quality, and sleepiness. Assessments of bedroom comfort suggest subjective habituation irrespective of exposure levels. CONCLUSIONS: These findings add to a growing body of evidence highlighting the importance of the bedroom environment-beyond the mattress-for high-quality sleep.

Noise and Air Pollution as Risk Factors for Hypertension: Part I-Epidemiology.

Traffic noise and air pollution are 2 major environmental health risk factors in urbanized societies that often occur together. Despite cooccurrence in urban settings, noise and air pollution have generally been studied independently, with many studies reporting a consistent effect on blood pressure for individual exposures. In the present reviews, we will discuss the epidemiology of air pollution and noise effects on arterial hypertension and cardiovascular disease (part I) and the underlying pathophysiology (part II). Both environmental stressors have been found to cause endothelial dysfunction, oxidative stress, vascular inflammation, circadian dysfunction, and activation of the autonomic nervous system, thereby facilitating the development of hypertension. We also discuss the effects of interventions, current gaps in knowledge, and future research tasks. From a societal and policy perspective, the health effects of both air pollution and traffic noise are observed well below the current guideline recommendations. To this end, an important goal for the future is to increase the acceptance of environmental risk factors as important modifiable cardiovascular risk factors, given their substantial impact on the burden of cardiovascular disease.

Noise and Air Pollution as Risk Factors for Hypertension: Part II-Pathophysiologic Insight.

Traffic noise and air pollution are environmental stressors found to increase risk for cardiovascular events. The burden of disease attributable to environmental stressors and cardiovascular disease globally is substantial, with a need to better understand the contribution of specific risk factors that may underlie these effects. Epidemiological observations and experimental evidence from animal models and human controlled exposure studies suggest an essential role for common mediating pathways. These include sympathovagal imbalance, endothelial dysfunction, vascular inflammation, increased circulating cytokines, activation of central stress responses, including hypothalamic and limbic pathways, and circadian disruption. Evidence also suggests that cessation of air pollution or noise through directed interventions alleviates increases in blood pressure and intermediate surrogate pathways, supporting a causal link. In the second part of this review, we discuss the current understanding of mechanisms underlying and current gaps in knowledge and opportunities for new research.

The posterior dominant rhythm: an electroencephalographic biomarker for cognitive recovery after general anaesthesia.

BACKGROUND: The posterior dominant rhythm (PDR) was the first oscillatory pattern noted in the EEG. Evoked by wakeful eyelid closure, these oscillations dissipate over seconds during loss of arousal. The peak frequency of the PDR maintains stability over years, suggesting utility as a state biomarker in the surveillance of acute cognitive impairments. This EEG signature has not been systematically investigated for tracking cognitive dysfunction after anaesthetic-induced loss of consciousness. METHODS: This substudy of Reconstructing Consciousness and Cognition (NCT01911195) investigated the PDR and cognitive function in 60 adult volunteers randomised to either 3 h of isoflurane general anaesthesia or resting wakefulness. Serial measurements of EEG power and cognitive task performance were assessed relative to pre-intervention baseline. Mixed-effects models allowed quantification of PDR and neurocognitive trajectories after return of responsiveness (ROR). RESULTS: Individuals in the control group showed stability in the PDR peak frequency over several hours (median difference/inter-quartile range [IQR] of 0.02/0.20 Hz, P=0.39). After isoflurane general anaesthesia, the PDR peak frequency was initially reduced at ROR (median difference/IQR of 0.88/0.65 Hz, P<0.001). PDR peak frequency recovered at a rate of 0.20 Hz h-1. After ROR, the PDR peak frequency correlated with reaction time and accuracy on multiple cognitive tasks (P<0.001). CONCLUSION: The temporal trajectory of the PDR peak frequency could be a useful perioperative marker for tracking cognitive dysfunction on the order of hours after surgery, particularly for cognitive domains of working memory, visuomotor speed, and executive function. CLINICAL TRIAL REGISTRATION: NCT01911195.

Future research directions to identify risks and mitigation strategies for neurostructural, ocular, and behavioral changes induced by human spaceflight: A NASA-ESA expert group consensus report.

A team of experts on the effects of the spaceflight environment on the brain and eye (SANS: Spaceflight-Associated Neuro-ocular Syndrome) was convened by NASA and ESA to (1) review spaceflight-associated structural and functional changes of the human brain and eye, and any interactions between the two; and (2) identify critical future research directions in this area to help characterize the risk and identify possible countermeasures and strategies to mitigate the spaceflight-induced brain and eye alterations. The experts identified 14 critical future research directions that would substantially advance our knowledge of the effects of spending prolonged periods of time in the spaceflight environment on SANS, as well as brain structure and function. They used a paired comparison approach to rank the relative importance of these 14 recommendations, which are discussed in detail in the main report and are summarized briefly below.

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

BACKGROUND: Nighttime noise carries a significant disease burden. The World Health Organization (WHO) recently published guidelines for the regulation of environmental noise based on a review of evidence published up to the year 2015 on the effects of environmental noise on sleep. OBJECTIVES: This systematic review and meta-analysis will update the WHO evidence review on the effects of environmental noise on sleep disturbance to include more recent studies. METHODS: Investigations of self-reported sleep among residents exposed to environmental traffic noise at home were identified using Scopus, PubMed, Embase, and PsycINFO. Awakenings, falling asleep, and sleep disturbance were the three outcomes included. Extracted data were used to derive exposure-response relationships for the probability of being highly sleep disturbed by nighttime noise [average outdoor A-weighted noise level (Lnight) 2300-0700 hours] for aircraft, road, and rail traffic noise, individually. The overall quality of evidence was assessed using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. RESULTS: Eleven studies (n=109,070 responses) were included in addition to 25 studies (n=64,090 responses) from the original WHO analysis. When sleep disturbance questions specifically mentioned noise as the source of disturbance, there was moderate quality of evidence for the probability of being highly sleep disturbed per 10-dB increase in Lnight for aircraft [odds ratio (OR)=2.18; 95% confidence interval (CI): 2.01, 2.36], road (OR=2.52; 95% CI: 2.28, 2.79), and railway (OR=2.97; 95% CI: 2.57, 3.43) noise. When noise was not mentioned, there was low to very low quality of evidence for being sleep disturbed per 10-dB increase in Lnight for aircraft (OR=1.52; 95% CI: 1.20, 1.93), road (OR=1.14; 95% CI: 1.08, 1.21), and railway (OR=1.17; 95% CI: 0.91, 1.49) noise. Compared with the original WHO review, the exposure-response relationships closely agreed at low (40 dB Lnight) levels for all traffic types but indicated greater disturbance by aircraft traffic at high noise levels. Sleep disturbance was not significantly different between European and non-European studies. DISCUSSION: Available evidence suggests that transportation noise is negatively associated with self-reported sleep. Sleep disturbance in this updated meta-analysis was comparable to the original WHO review at low nighttime noise levels. These low levels correspond to the recent WHO noise limit recommendations for nighttime noise, and so these findings do not suggest these WHO recommendations need revisiting. Deviations from the WHO review in this updated analysis suggest that populations exposed to high levels of aircraft noise may be at greater risk of sleep disturbance than determined previously. https://doi.org/10.1289/EHP10197.

Brain structure and neurocognitive function in two professional mountaineers during 35 days of severe normobaric hypoxia.

BACKGROUND AND PURPOSE: Animal studies suggest that exposure to severe ambient hypoxia for several days may have beneficial long-term effects on neurodegenerative diseases. Because, the acute risks of exposing human beings to prolonged severe hypoxia on brain structure and function are uncertain, we conducted a pilot study in healthy persons. METHODS: We included two professional mountaineers (participants A and B) in a 35-day study comprising an acclimatization period and 14 consecutive days with oxygen concentrations between 8% and 8.8%. They underwent cerebral magnetic resonance imaging at seven time points and a cognitive test battery covering a spectrum of cognitive domains at 27 time points. We analysed blood neuron specific enolase and neurofilament light chain levels before, during, and after hypoxia. RESULTS: In hypoxia, white matter volumes increased (maximum: A, 4.3% ± 0.9%; B, 4.5% ± 1.9%) whilst gray matter volumes (A, -1.5% ± 0.8%; B, -2.5% ± 0.9%) and cerebrospinal fluid volumes (A, -2.7% ± 2.4%; B, -5.9% ± 8.2%) decreased. Furthermore, the number (A, 11-17; B, 26-126) and volumes (A, 140%; B, 285%) of white matter hyperintensities increased in hypoxia but had returned to baseline after a 3.5-month recovery phase. Diffusion weighted imaging of the white matter indicated cytotoxic edema formation. We did not observe changes in cognitive performance or biochemical brain injury markers. DISCUSSION: In highly selected healthy individuals, severe sustained normobaric hypoxia over 2 weeks elicited reversible changes in brain morphology without clinically relevant changes in cognitive function or brain injury markers. The finding may pave the way for future translational studies assessing the therapeutic potential of hypoxia in neurodegenerative diseases.

Dynamic ensemble prediction of cognitive performance in spaceflight.

During spaceflight, astronauts face a unique set of stressors, including microgravity, isolation, and confinement, as well as environmental and operational hazards. These factors can negatively impact sleep, alertness, and neurobehavioral performance, all of which are critical to mission success. In this paper, we predict neurobehavioral performance over the course of a 6-month mission aboard the International Space Station (ISS), using ISS environmental data as well as self-reported and cognitive data collected longitudinally from 24 astronauts. Neurobehavioral performance was repeatedly assessed via a 3-min Psychomotor Vigilance Test (PVT-B) that is highly sensitive to the effects of sleep deprivation. To relate PVT-B performance to time-varying and discordantly-measured environmental, operational, and psychological covariates, we propose an ensemble prediction model comprising of linear mixed effects, random forest, and functional concurrent models. An extensive cross-validation procedure reveals that this ensemble outperforms any one of its components alone. We also identify the most important predictors of PVT-B performance, which include an individual's previous PVT-B performance, reported fatigue and stress, and temperature and radiation dose. This method is broadly applicable to settings where the main goal is accurate, individualized prediction of human behavior involving a mixture of person-level traits and irregularly measured time series.