Traffic Noise and Mental Health: A Systematic Review and Meta-Analysis

Airborne Exposure to Pollutants and Mental Health: A Review with Implications for United States Veterans

PURPOSE OF REVIEW

Inhalation of airborne pollutants in the natural and built environment is ubiquitous; yet, exposures are different across a lifespan and unique to individuals. Here, we reviewed the connections between mental health outcomes from airborne pollutant exposures, the biological inflammatory mechanisms, and provide future directions for researchers and policy makers. The current state of knowledge is discussed on associations between mental health outcomes and Clean Air Act criteria pollutants, traffic-related air pollutants, pesticides, heavy metals, jet fuel, and burn pits.

RECENT FINDINGS

Although associations between airborne pollutants and negative physical health outcomes have been a topic of previous investigations, work highlighting associations between exposures and psychological health is only starting to emerge. Research on criteria pollutants and mental health outcomes has the most robust results to date, followed by traffic-related air pollutants, and then pesticides. In contrast, scarce mental health research has been conducted on exposure to heavy metals, jet fuel, and burn pits. Specific cohorts of individuals, such as United States military members and in-turn, Veterans, often have unique histories of exposures, including service-related exposures to aircraft (e.g. jet fuels) and burn pits. Research focused on Veterans and other individuals with an increased likelihood of exposure and higher vulnerability to negative mental health outcomes is needed. Future research will facilitate knowledge aimed at both prevention and intervention to improve physical and mental health among military personnel, Veterans, and other at-risk individuals.

Low-Level Visual Features of Window Views Contribute to Perceived Naturalness and Mental Health Outcomes

Previous studies have shown that natural window views are beneficial for mental health, but it is still unclear which specific features constitute a 'natural' window view. On the other hand, studies on image analysis found that low-level visual features (LLVFs) are associated with perceived naturalness, but mainly conducted experiments with brief stimulus presentations. In this study, research on the effects of window views on mental health was combined with the detailed analysis of LLVFs. Healthy adults rated window views from their home and sent in photographs of those views for analysis. Content validity of the 'ecological' view assessment was evaluated by checking correlations of LLVFs with window view ratings. Afterwards, it was explored which of the LLVFs best explained variance in perceived percentage of nature and man-made elements, and in ratings of view quality. Criterion validity was tested by investigating which variables were associated with negative affect and impulsive decision-making. The objective and subjective assessments of nature/sky in the view were aligned but objective brightness was unreliable. The perceived percentage of nature was significantly explained by green pixel ratio, while view quality was associated with fractals, saturation, sky pixel ratio and straight edge density. The higher subjective brightness of rooms was associated with a lower negative affect, whereas results for impulsive decision-making were inconsistent. The research highlights the validity to apply LLVFs analysis to ecological window views. For affect, subjective brightness seemed to be more relevant than LLVFs. For impulsive decision-making, performance context needs to be controlled in future studies.

Aircraft noise exposure and body mass index among female participants in two Nurses' Health Study prospective cohorts living around 90 airports in the United States

OBJECTIVE

Aircraft noise exposure is linked to cardiovascular disease risk. One understudied candidate pathway is obesity. This study investigates the association between aircraft noise and obesity among female participants in two prospective Nurses' Health Study (NHS and NHSII) cohorts.

METHODS

Aircraft day-night average sound levels (DNL) were estimated at participant residential addresses from modeled 1 dB (dB) noise contours above 44 dB for 90 United States (U.S.) airports in 5-year intervals 1995-2010. Biennial surveys (1994-2017) provided information on body mass index (BMI; dichotomized, categorical) and other individual characteristics. Change in BMI from age 18 (BMI18; tertiles) was also calculated. Aircraft noise exposures were dichotomized (45, 55 dB), categorized (<45, 45-54, ≥55 dB) or continuous for exposure ≥45 dB. Multivariable multinomial logistic regression using generalized estimating equations were adjusted for individual characteristics and neighborhood socioeconomic status, greenness, population density, and environmental noise. Effect modification was assessed by U.S. Census region, climate boundary, airline hub type, hearing loss, and smoking status.

RESULTS

At baseline, the 74,848 female participants averaged 50.1 years old, with 83.0%, 14.8%, and 2.2% exposed to <45, 45-54, and ≥55 dB of aircraft noise, respectively. In fully adjusted models, exposure ≥55 dB was associated with 11% higher odds (95% confidence interval [95%CI]: -1%, 24%) of BMIs ≥30.0, and 15% higher odds (95%CI: 3%, 29%) of membership in the highest tertile of BMI18 (ΔBMI 6.7 to 71.6). Less-pronounced associations were observed for the 2nd tertile of BMI18 (ΔBMI 2.9 to 6.6) and BMI 25.0-29.9 as well as exposures ≥45 versus <45 dB. There was evidence of DNL-BMI trends (ptrends ≤ 0.02). Stronger associations were observed among participants living in the West, arid climate areas, and among former smokers.

DISCUSSION

In two nationwide cohorts of female nurses, higher aircraft noise exposure was associated with higher BMI, adding evidence to an aircraft noise-obesity-disease pathway.

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.

Proximity to public green spaces and depressive symptoms among South African residents: a population-based study

BACKGROUND

Exposure to green spaces has been suggested to improve mental health and may reduce the risk of depression. However, there is generally limited evidence on the association between green spaces and depression originating from low-and middle-income countries and Africa in particular. Here, we investigate the association between proximity to public green spaces and depressive symptoms among residents of Gauteng Province, South Africa.

METHODS

We used data from the 2017/2018 Gauteng quality of life survey. We included all individuals aged 18 years or older residing in the nine municipalities of Gauteng Province that completed the survey (n = 24,341). Depressive symptoms were assessed using the Patient Health Questionnaire-2. Proximity to public green spaces was defined as self-reported walking time (either less or greater than 15 min) from individuals' homes to the nearest public green space. To assess the association between access to public green spaces and depressive symptoms, we used mixed-effects models, adjusted for age, sex, population group (African, Indian/Asian, Coloured (mixed race), and White), educational attainment, and municipality. We additionally performed stratified analyses by age, sex, educational attainment, and population group to evaluate whether associations differed within subgroups. Associations are expressed as prevalence ratios (PR) and their 95% confidence intervals (95% CI).

RESULTS

We observed a 6% (PR = 0.94, 95%CI = 0.92-0.96) prevalence reduction in depressive symptoms for individuals who reported that the nearest public green space was less than 15 min from their homes as compared to those who reported > 15 min. After stratification, this inverse association was stronger among females, individuals aged 35-59 years,those with higher levels of educational attainment, and Coloured individuals as compared to their counterparts.

CONCLUSION

Our findings suggest that public green spaces close to residential homes may be associated with a reduction in the occurrence of depressive symptoms among urban populations in resource-constrained settings like South Africa.

Urban environment in pregnancy and postpartum depression: An individual participant data meta-analysis of 12 European birth cohorts

BACKGROUND

Urban environmental exposures associate with adult depression, but it is unclear whether they are associated to postpartum depression (PPD).

OBJECTIVES

We investigated associations between urban environment exposures during pregnancy and PPD.

METHODS

We included women with singleton deliveries to liveborn children from 12 European birth cohorts (N with minimum one exposure = 30,772, analysis N range 17,686-30,716 depending on exposure; representing 26-46 % of the 66,825 eligible women). We estimated maternal exposure during pregnancy to ambient air pollution with nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10), road traffic noise (Lden), natural spaces (Normalised Difference Vegetation Index; NDVI, proximity to major green or blue spaces) and built environment (population density, facility richness and walkability). Maternal PPD was assessed 3-18 months after birth using self-completed questionnaires. We used adjusted logistic regression models to estimate cohort-specific associations between each exposure and PPD and combined results via meta-analysis using DataSHIELD.

RESULTS

Of the 30,772 women included, 3,078 (10 %) reported having PPD. Exposure to PM10 was associated with slightly increased odds of PPD (adjusted odd ratios (OR) of 1.08 [95 % Confidence Intervals (CI): 0.99, 1.17] per inter quartile range increment of PM10) whilst associations for exposure to NO2 and PM2.5 were close to null. Exposure to high levels of road traffic noise (≥65 dB vs. < 65 dB) was associated with an OR of 1.12 [CI: 0.95, 1.32]. Associations between green spaces and PPD were close to null; whilst proximity to major blue spaces was associated with increased risk of PPD (OR 1.12, 95 %CI: 1.00, 1.26). All associations between built environment and PPD were close to null. Multiple exposure models showed similar results.

DISCUSSION

The study findings suggest that exposure to PM10, road traffic noise and blue spaces in pregnancy may increase PPD risk, however future studies should explore this causally.

Acute effects of military aircraft noise on sedative and analgesic drug administrations in psychiatric patients: A case-time series analysis

BACKGROUND

Existing evidence suggests that psychiatric patients are highly noise sensitive, and that noise exposure increases the risk for adverse mental health outcomes, such as psychiatric hospitalizations and even suicide. To investigate acute effects of noise in this vulnerable population, we assessed short-term associations between fighter jet noise and on-demand sedative and analgesic drug administrations in a psychiatric clinic located close to a military airfield in Switzerland.

METHODS

We applied a case time series analysis with an hourly time resolution using distributed-lag models. Analysis was adjusted for long-term and seasonal trends, day of week, time of day, time-varying weather conditions and the week of stay. Noise exposure (hourly A-weighted equivalent continuous sound pressure levels (LAeq)) was modelled using detailed flight plans and noise footprints for different fighter jet and route combinations. Outcome data were available from the clinic's records.

OUTCOMES

During the study period (06/2016-12/2021), 23,486 flights occurred. 5,968 clinical stays with a median length of 41 days (IQR: 28d, 50d) were recorded. The odds ratio (OR) for medication administration over the lag period of 3 hours after exposure was 1.016 (95 %CI: 1.006, 1.026) per 10 dB LAeq for sedatives and 1.032 (95 %CI: 1.016, 1.048) per 10 dB for analgesics. Effects were larger in multimorbid patients.

INTERPRETATION

Case time series analysis is a novel method to investigate transient associations in observational data while minimizing risk of bias. Using an objectively recorded outcome measure, our results demonstrate that psychiatric patients are a vulnerable population, in which noise exposure can lead to symptom exacerbations and adverse events.

Health position paper and redox perspectives - Disease burden by transportation noise

Transportation noise is a ubiquitous urban exposure. In 2018, the World Health Organization concluded that chronic exposure to road traffic noise is a risk factor for ischemic heart disease. In contrast, they concluded that the quality of evidence for a link to other diseases was very low to moderate. Since then, several studies on the impact of noise on various diseases have been published. Also, studies investigating the mechanistic pathways underlying noise-induced health effects are emerging. We review the current evidence regarding effects of noise on health and the related disease-mechanisms. Several high-quality cohort studies consistently found road traffic noise to be associated with a higher risk of ischemic heart disease, heart failure, diabetes, and all-cause mortality. Furthermore, recent studies have indicated that road traffic and railway noise may increase the risk of diseases not commonly investigated in an environmental noise context, including breast cancer, dementia, and tinnitus. The harmful effects of noise are related to activation of a physiological stress response and nighttime sleep disturbance. Oxidative stress and inflammation downstream of stress hormone signaling and dysregulated circadian rhythms are identified as major disease-relevant pathomechanistic drivers. We discuss the role of reactive oxygen species and present results from antioxidant interventions. Lastly, we provide an overview of oxidative stress markers and adverse redox processes reported for noise-exposed animals and humans. This position paper summarizes all available epidemiological, clinical, and preclinical evidence of transportation noise as an important environmental risk factor for public health and discusses its implications on the population level.

Noise and mental health: evidence, mechanisms, and consequences

The recognition of noise exposure as a prominent environmental determinant of public health has grown substantially. While recent years have yielded a wealth of evidence linking environmental noise exposure primarily to cardiovascular ailments, our understanding of the detrimental effects of noise on the brain and mental health outcomes remains limited. Despite being a nascent research area, an increasing body of compelling research and conclusive findings confirms that exposure to noise, particularly from sources such as traffic, can potentially impact the central nervous system. These harms of noise increase the susceptibility to mental health conditions such as depression, anxiety, suicide, and behavioral problems in children and adolescents. From a mechanistic perspective, several investigations propose direct adverse phenotypic changes in brain tissue by noise (e.g. neuroinflammation, cerebral oxidative stress), in addition to feedback signaling by remote organ damage, dysregulated immune cells, and impaired circadian rhythms, which may collectively contribute to noise-dependent impairment of mental health. This concise review linking noise exposure to mental health outcomes seeks to fill research gaps by assessing current findings from studies involving both humans and animals.

Assessing the Human Health Benefits of Climate Mitigation, Pollution Prevention, and Biodiversity Preservation

Background

Since the Industrial Revolution, humanity has amassed great wealth and achieved unprecedented material prosperity. These advances have come, however, at great cost to the planet. They are guided by an economic model that focuses almost exclusively on short-term gain, while ignoring natural capital and human capital. They have relied on the combustion of vast quantities of fossil fuels, massive consumption of the earth's resources, and production and environmental release of enormous quantities of chemicals, pesticides, fertilizers, and plastics. They have caused climate change, pollution, and biodiversity loss, the "Triple Planetary Crisis". They are responsible for more than 9 million premature deaths per year and for widespread disease - impacts that fall disproportionately upon the poor and the vulnerable.

Goals

To map the human health impacts of climate change, pollution, and biodiversity loss. To outline a framework for assessing the health benefits of interventions against these threats.

Findings

Actions taken by national governments and international agencies to mitigate climate change, pollution, and biodiversity loss can improve health, prevent disease, save lives, and enhance human well-being. Yet assessment of health benefits is largely absent from evaluations of environmental remediation programs. This represents a lost opportunity to quantify the full benefits of environmental remediation and to educate policy makers and the public.

Recommendations

We recommend that national governments and international agencies implementing interventions against climate change, pollution, and biodiversity loss develop metrics and strategies for quantifying the health benefits of these interventions. We recommend that they deploy these tools in parallel with assessments of ecologic and economic benefits. Health metrics developed by the Global Burden of Disease (GBD) study may provide a useful starting point.Incorporation of health metrics into assessments of environmental restoration will require building transdisciplinary collaborations. Environmental scientists and engineers will need to work with health scientists to establish evaluation systems that link environmental and economic data with health data. Such systems will assist international agencies as well as national and local governments in prioritizing environmental interventions.

Systemic health effects of noise exposure

Noise, any unwanted sound, is pervasive and impacts large populations worldwide. Investigators suggested that noise exposure not only induces auditory damage but also produces various organ system dysfunctions. Although previous reviews primarily focused on noise-induced cardiovascular and cerebral dysfunctions, this narrow focus has unintentionally led the research community to disregard the importance of other vital organs. Indeed, limited studies revealed that noise exposure impacts other organs including the liver, kidneys, pancreas, lung, and gastrointestinal tract. Therefore, the aim of this review was to examine the effects of noise on both the extensively studied organs, the brain and heart, but also determine noise impact on other vital organs. The goal was to illustrate a comprehensive understanding of the systemic effects of noise. These systemic effects may guide future clinical research and epidemiological endpoints, emphasizing the importance of considering noise exposure history in diagnosing various systemic diseases.

Association between perceived noise at work and mental health among employed adults in Southwest China

BACKGROUND

Perceived noise at work may contribute more to worsening mental health than objectively measured noise. However, evidence regarding this association is scarce. We investigated the associations of perceived noise at work with anxiety and depression and identified vulnerable subpopulations.

METHODS

Data from 28,661 participants of the Chinese Cohort of Working Adults (CCWA) were analyzed. Logistic or multinomial logistic regression models were used to determine associations between perceived noise at work and the severity of probable anxiety, depression, and their comorbidity. The generalized additive model with restricted cubic splines was applied to estimate the non-linear trend of associations.

RESULTS

The mean age of participants was 36.55 ± 10.42 years. We observed that a higher level of perceived noise at work was associated with a higher risk of severe anxiety (OR = 1.55. 95%CI: 1.51-1.59) and severe depression (OR = 1.77. 95%CI: 1.72-1.84). More perceived noise at work was further associated with increased odds of comorbid anxiety and depression (OR = 1.28, 95%CI: 1.26-1.30). We observed an approximately J-shaped curve for the association between perceived noise at work with anxiety, depression, and their comorbidity. Participants, who were male, aged <45 years, had high education levels, and worked on trains were characterized by a greater impact of perceived noise at work on mental health problems.

CONCLUSION

Increased perceived noise at work was associated with an elevated risk of anxiety, depression, and their comorbidity. These associations were moderated by sex, age, education level and occupation. Interventions targeting perceived noise at work may promote employed adults' mental health.

Contributions of residential traffic noise to depression and mental wellbeing in Hong Kong: A prospective cohort study

Prior studies on the association between traffic noise and mental health have been mostly conducted in settings with lower population densities. However, evidence is lacking in high population-density settings where traffic noise is more pervasive and varies by topography and the vertical elevation of the residential unit. This study aimed to assess the mental health impact of residential traffic noise in one of the world's most urbanised populations. Data were analysed from 13,401 participants aged ≥15 years in a prospective cohort in Hong Kong from 2009 to 2014. Residential traffic noise level was estimated using 3D-geocoding and validated models that accounted for sound propagation in a highly vertical landscape. The 24-h day-night exposure to traffic noise, denoted as Ldn, was estimated with a 10-dB(A) penalty for night hours. Probable depression and mental wellbeing were assessed using the Patient Health Questionnaire-9 and the Short Form Health Questionnaire SF-12v2, respectively. Mixed effect regressions with random intercepts were used to examine the association between traffic noise and mental health outcomes. Residential road traffic noise (for each increment of 10 A-weighted decibels [dB(A)] 24-h average exposure) was associated with probable depression (odds ratio (OR) = 1.17, 95% CI: 1.05, 1.31), and poorer mental wellbeing (mean difference = -0.19, 95% CI: 0.31, -0.06), adjusting for sociodemographics, smoking, body mass index, self-reported health, proximity to green space, and neighbourhood characteristics (average household income, population density, and Gini coefficient). The results were robust to further adjustment for air pollution. In stratified analyses, residential traffic noise was associated with probable depression and poorer mental wellbeing among students and individuals aged 15-34 years. Residential traffic noise was associated with probable depression and poorer mental wellbeing in a highly urbanised setting. As traffic noise is increasing in urban settings, the public health impact of noise pollution could be substantial.

Long-term exposure to air pollution and incidence of mental disorders. A large longitudinal cohort study of adults within an urban area

BACKGROUND

Recent epidemiological evidence suggests associations between air pollution exposure and major depressive disorders, but the literature is inconsistent for other mental illnesses. We investigated the associations of several air pollutants and road traffic noise with the incidence of different categories of mental disorders in a large population-based cohort.

METHODS

We enrolled 1,739,277 individuals 30 + years from the 2011 census in Rome, Italy, and followed them up until 2019. In detail, we analyzed 1,733,331 participants (mean age 56.43 +/- 15.85 years; 54.96 % female) with complete information on covariates of interest. We excluded subjects with prevalent mental disorders at baseline to evaluate the incidence (first hospitalization or co-pay exemption) of schizophrenia spectrum disorders, bipolar, anxiety, personality, or substance use disorders. In addition, we studied subjects with first prescriptions of antipsychotics, antidepressants, and mood stabilizers. Annual average concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO₂), Black Carbon (BC), ultrafine particles (UFP), and road traffic noise were assigned to baseline residential addresses. We applied Cox regression models adjusted for individual and area-level covariates.

RESULTS

Each interquartile range (1.13 µg/m3) increase in PM2.5 was associated with a hazard ratio (HR) of 1.070 (95 % confidence interval [CI]: 1.017, 1.127) for schizophrenia spectrum disorder, 1.135 (CI: 1.086, 1.186) for depression, 1.097 (CI: 1.030, 1.168) for anxiety disorders. Positive associations were also detected for BC and UFP, and with the three categories of drug prescriptions. Bipolar, personality, and substance use disorders did not show clear associations. The effects were highest in the age group 30-64 years, except for depression.

CONCLUSIONS

Long-term exposure to ambient air pollution, especially fine and ultrafine particles, was associated with increased risks of schizophrenia spectrum disorder, depression, and anxiety disorders. The association of the pollutants with the prescriptions of specific drugs increases the credibility of the results.

Urbanicity and depression: A global meta-analysis

BACKGROUND

Previous meta-analyses have revealed that in adult and older adult populations of developed countries, depression is more prevalent in urban than rural areas. No meta-analyses have identified the effects of urbanicity on the general age demographic for developing countries. We conducted a meta-analysis of urban-rural differences in depression across all age demographics for developed and developing countries.

METHODS

PubMed and PsycINFO databases were searched for studies published between 1980 and 2020. Studies were included if they reported prevalences of urban and rural depression, or odds ratios comparing urban-rural depression prevalence. Studies were excluded for: nonrepresentative samples, non-standard measures of depression, and reporting continuous outcomes only. Meta-analytic models of urban-rural differences in the odds of depression were conducted across country development levels and age demographics.

RESULTS

From 1597 records screened and 302 full texts assessed for eligibility, 80 studies (N = 539,557) were included for meta-analysis. Urban residence was significantly associated with a higher prevalence of depression in developed countries (OR = 1.30, 95 % CI [1.17, 1.46], z = 4.75, p < .001), which was primarily driven by urban-rural differences in the general population age demographic (OR = 1.37, 95 % CI [1.22, 1.54], z = 5.38, p < .001).

LIMITATIONS

Studies reporting urban-rural differences in depression in terms of continuous symptom severity scores were not included.

CONCLUSIONS

Urbanicity appears to uniquely be associated with a higher prevalence of depression in developed countries, but not in developing countries.

Magnitude of extended high frequency hearing loss associated with auditory related tinnitus distress, when controlling for magnitude of hearing loss at standard frequenciesa)

Impaired thresholds at extended high frequencies (EHF) are tightly linked to the prevalence of tinnitus, but little is known about how EHF status relates to tinnitus characteristics. In the present study, 93 individuals with tinnitus underwent standard (from 0.125 to 8 kHz) and EHF (from 10 to 16 kHz) audiometry and indicated their degree of tinnitus distress by completing the tinnitus functional index and their perceived tinnitus loudness by using a numeric rating scale. Partial correlation analyses indicated that the magnitude of EHF loss was significantly associated with degree of auditory related tinnitus distress (r = 0.343, p < 0.001) when controlling for pure tone average at standard frequencies and compensating for multiple testing. It is concluded that EHF status is related specifically to auditory related tinnitus distress, but not to intrusive-, sense of control-, cognitive-, sleep-, relaxation-, quality of life-, emotional-related tinnitus distress, total tinnitus distress, or perceived tinnitus loudness.

Measuring environmental exposures in people's activity space: The need to account for travel modes and exposure decay

BACKGROUND

Accurately quantifying people's out-of-home environmental exposure is important for identifying disease risk factors. Several activity space-based exposure assessments exist, possibly leading to different exposure estimates, and have neither considered individual travel modes nor exposure-related distance decay effects.

OBJECTIVE

We aimed (1) to develop an activity space-based exposure assessment approach that included travel modes and exposure-related distance decay effects and (2) to compare the size of such spaces and the exposure estimates derived from them across typically used activity space operationalizations.

METHODS

We used 7-day-long global positioning system (GPS)-enabled smartphone-based tracking data of 269 Dutch adults. People's GPS trajectory points were classified into passive and active travel modes. Exposure-related distance decay effects were modeled through linear, exponential, and Gaussian decay functions. We performed cross-comparisons on these three functional decay models and an unweighted model in conjunction with four activity space models (i.e., home-based buffers, minimum convex polygons, two standard deviational ellipses, and time-weighted GPS-based buffers). We applied non-parametric Kruskal-Wallis tests, pair-wise Wilcoxon signed-rank tests, and Spearman correlations to assess mean differences in the extent of the activity spaces and correlations across exposures to particulate matter (PM2.5), noise, green space, and blue space.

RESULTS

Participants spent, on average, 42% of their daily life out-of-home. We observed that including travel modes into activity space delineation resulted in significantly more compact activity spaces. Exposure estimates for PM2.5 and blue space were significantly (p < 0.05) different between exposure estimates that did or did not account for travel modes, unlike noise and green space, for which differences did not reach significance. While the inclusion of distance decay effects significantly affected noise and green space exposure assessments, the decay functions applied appear not to have had any impact on the results. We found that residential exposure estimates appear appropriate for use as proxy values for the overall amount of PM2.5 exposure in people's daily lives, while GPS-based assessments are suitable for noise, green space, and blue space.

SIGNIFICANCE

For some exposures, the tested activity space definitions, although significantly correlated, exhibited differing exposure estimate results based on inclusion or exclusion of travel modes or distance decay effect. Results only supported using home-based buffer values as proxies for individuals' daily short-term PM2.5 exposure.

Associations between the urban environment and psychotic experiences in adolescents

OBJECTIVE

In 2050 two-thirds of the world's population is predicted to live in cities, which asks for a better understanding of how the urban environment affects mental health. Urbanicity has repeatedly been found to be a risk factor, in particular for psychosis. Here, we explored what factors of the urban exposome underlie the association between urban characteristics and psychotic experiences (PE) in adolescents.

METHODS

Participants were 815 adolescents (mean age 14.84 years, SD 0.78) from an at-risk cohort (greater Rotterdam area, the Netherlands) oversampled on their self-reported emotional and behavioral problems. We used linear regression analysis to examine the association with detailed geodata on urbanicity (surrounding address density), green space density (high and low vegetation), and mixed noise levels (road, rail, air, industry, and wind power) with PE in adolescents. Analyses were adjusted for multiple socio-economic and parental confounders. Furthermore, we explored sex-interaction effects.

RESULTS

Higher surrounding address density and low greenspace density were each independently associated with more PE (B = 0.18, 95 % CI 0.02; 0.34 and B = 0.17, 95 % CI 0.01; 0.32, respectively). High mixed noise levels were only associated with more PE in boys (B = 0.23, 95 % CI 0.01; 0.46). A sex-interaction effect was found for high urbanicity (B = -0.46, 95 % CI -0.77; -0.14) and low greenspace density (B = -0.49, 95 % CI -0.73; -0.11), illustrating that these associations with PE were specific for boys.

CONCLUSION

Multiple characteristics of living in an urban area are associated with more PE in adolescent boys. Our observations provide leads for prevention of mental health problems via urban designing.

Protocol of a prospective community-based study about the onset and course of depression in a nationally representative cohort of adults in China: the China Depression Cohort Study-I

BACKGROUND

Depression is the second most important cause of disability worldwide. Reducing this major burden on global health requires a better understanding of the etiology, risk factors, and course of the disorder. With the goal of improving the prevention, recognition, and appropriate management of depressive disorders in China, the China Depression Cohort Study will establish a nationally representative sample of at least 85,000 adults (the China Depression Cohort Study-I) and 15,000 middle school students (the China Depression Cohort Study-II) and follow them over time to identify factors that influence the onset, characteristics, and course of depressive disorders. This protocol describes the China Depression Cohort Study-I.

METHODS

A multistage stratified random sampling method will be used to identify a nationally representative community-based cohort of at least 85,000 adults (i.e., ≥ 18 years of age) from 34 communities in 17 of mainland China's 31 provincial-level administrative regions. Baseline data collection includes 1) demographic, social and clinical data, 2) diagnostic information, 3) biological samples (i.e., blood, urine, hair), 4) brain MRI scans, and 5) environmental data (e.g., community-level metrics of climate change, air pollution, and socio-economic characteristics). Baseline findings will identify participants with or without depressive disorders. Annual reassessments will monitor potential risk factors for depression and identify incident cases of depression. Cox Proportional-Hazards Regression, Network analysis, Disease trajectory modelling, and Machine learning prediction models will be used to analyze the collected data. The study's main outcomes are the occurrence of depressive disorders; secondary outcomes include adverse behaviors (e.g., self-harm, suicide), the recurrence of depression and the incidence other mental disorders.

DISCUSSION

The China Depression Cohort Study-I will collect a comprehensive, nationally representative set of individual-level and community-level variables over time. The findings will reframe the understanding of depression from a 'biology-psychology-society' perspective. This perspective will improve psychiatrists' understanding of depression and, thus, promote the development of more effective subgroup-specific antidepressant drugs and other interventions based on the new biomarkers and relationships identified in the study.

TRAIL REGISTRATION

The protocol has been registered on the Chinese Clinical Trial Registry (No. ChiCTR2200059016).

Spatial assessment of the attributable burden of disease due to transportation noise in England

BACKGROUND

Noise pollution from transportation is one of the leading contributors to the environmental disease burden in Europe. We provide a novel assessment of spatial variations of these health impacts within a country, using England as an example.

METHODS

We estimated the burden of annoyance (highly annoyed), sleep disturbance (highly sleep disturbed), ischemic heart disease (IHD), stroke, and diabetes attributable to long-term transportation noise exposures in England for the adult population in 2018 down to local authority level (average adult population: 136,000). To derive estimates, we combined literature-informed exposure-response relationships, with population data on noise exposures, disease, and mortalities. Long-term average noise exposures from road, rail and aircraft were sourced from strategic noise mapping, with a lower exposure threshold of 50 dB (decibels) Lden and Lnight.

RESULTS

40 %, 4.5 % and 4.8 % of adults in England were exposed to road, rail, and aircraft noise exceeding 50 dB Lden. We estimated close to a hundred thousand (∼97,000) disability adjusted life years (DALY) lost due to road-traffic, ∼13,000 from railway, and ∼ 17,000 from aircraft noise. This excludes some noise-outcome pairs as there were too few studies available to provide robust exposure-response estimates. Annoyance and sleep disturbance accounted for the majority of the DALYs, followed by strokes, IHD, and diabetes. London, the South East, and North West regions had the greatest number of road-traffic DALYs lost, while 63 % of all aircraft noise DALYs were found in London. The strategic noise mapping did not include all roads, which may still have significant traffic flows. In sensitivity analyses using modelled noise from all roads in London, the DALYs were 1.1x to 2.2x higher.

CONCLUSION

Transportation noise exposures contribute to a significant and unequal environmental disease burden in England. Omitting minor roads from the noise exposure modelling leads to underestimation of the disease burden.

Being a Fair Neighbor-Towards a Psychometric Inventory to Assess Fairness-Related Perceptions of Airports by Residents-Development and Validation of the Aircraft Noise-Related Fairness Inventory (fAIR-In)

Aircraft noise causes a variety of negative health consequences, and annoyance is a central factor mediating stress-related health risks. Non-acoustic factors play an important role in the experience of annoyance where the aspect of fairness is assumed to be a vital component. This paper describes the development of the Aircraft Noise-related Fairness Inventory (fAIR-In) and examines its factorial validity, construct validity and predictive validity. The development of the questionnaire included expert consultations, statements from airport residents and a large-scale online survey around three German airports (N = 1367). Its items cover distributive, procedural, informational and interpersonal fairness. Via mailshot, almost 100,000 flyers were sent out in more (>55 dB(A) L_den)- and less (≤55 dB(A) L_den)-aircraft-noise-exposed areas around Cologne-Bonn, Dusseldorf and Dortmund Airport. Thirty-two items were carefully selected considering reliability, theoretical importance and factor loading calculated via exploratory factor analysis (EFA), with all facets achieving high internal consistency (α = 0.89 to 0.92). The factorial validity, analyzed via a confirmatory factor analysis (CFA), revealed that viewing distributive, procedural, informational and interpersonal fairness as distinct factors produced a better fit to the data than other categorizations with fewer factors. The fAIR-In shows adequate results in terms of construct validity and excellent results in terms of the predictive validity of annoyance by aircraft noise (r = -0.53 to r = -0.68), acceptance of airports and air traffic (r = 0.46 to r = 0.59) and willingness to protest (r = -0.28 to r = -0.46). The fAIR-In provides airport managers with a reliable, valid and easy-to-use tool to design, monitor and evaluate efforts to improve the neighborliness between an airport and its residents.

Correlation of commute time with the risk of subjective mental health problems: 6th Korean Working Conditions Survey (KWCS)

Background

Studies conducted so far on the link between commute time and mental health among Koreans remain insufficient. In this study, we attempted to identify the relationship between commute time and subjective mental health using the 6^th Korean Working Conditions Survey (KWCS).

Methods

Self-reported commute time was divided into four groups: ≤ 30 (group 1), 30-60 (group 2), 60-120 (group 3), and > 120 minutes (group 4). Subjective depression was defined as a score of 50 points or less on the WHO-5 well-being index. Subjective anxiety and fatigue were defined as answering 'yes' to the questionnaire on whether they had experienced it over the past year. The analysis of variance, t-test, and χ² test was used to analyze the differences among the characteristics of the study participants according to commute time, depression, anxiety, and fatigue. Odds ratios (ORs) and 95% confidence intervals (CIs) for depression, anxiety, and fatigue according to commute time were calculated using multivariate logistic regression models adjusted for sex, age, monthly income, occupation, company size, weekly working hours, and shift work status.

Results

Long commute times showed increased ORs and graded increasing trends for depression, anxiety, and fatigue. The ORs for depression increased significantly in group 2 (1.06 [1.01-1.11]), group 3 (1.23 [1.13-1.33]), and group 4 (1.31 [1.09-1.57]) compared to group 1 (reference). The ORs for anxiety increased significantly in group 2 (1.17 [1.06-1.29]), group 3 (1.43 [1.23-1.65]) and group 4 (1.89 [1.42-2.53]). The ORs for fatigue increased significantly in group 2 (1.09 [1.04-1.15]), group 3 (1.32 [1.21-1.43]), and group 4 (1.51 [1.25-1.82]).

Conclusions

This study highlights that the risk of depression, anxiety, and fatigue increases with commute time.

Joint associations and pathways from greenspace, traffic-related air pollution, and noise to poor self-rated general health: A population-based study in Sofia, Bulgaria

BACKGROUND

Little is still known of how multiple urban exposures interact as health determinants. This study investigated various ways in which greenspace, traffic-related air pollution, and noise could operate together, influencing general health status.

METHODS

In 2022, a cross-sectional population-based survey was conducted in Sofia, Bulgaria. Included were 917 long-term adult residents who completed questionnaires on poor self-rated health (PSRH), total time spent in physical activity (PA), home garden presence, time spent in urban greenspace and nature, and sociodemographics. Residential greenspace was operationalized using the normalized difference vegetation index (NDVI), tree cover density, number of trees, and access to local greenspace and parks. Nitrogen dioxide (NO₂) was modeled for the study area. Road traffic, railway, and aircraft day-evening-night sound levels (L_den) were extracted from EU noise maps. Area-level income and urbanicity were considered. Analyses included multivariate ordinal regressions, interactions, and structural equation modeling (SEM).

RESULTS

Associations with PSRH were per 0.10 NDVI _300 m: OR = 0.65 (0.42-1.01), home garden: OR = 0.72 (0.49-1.07), per 5 μg/m³ NO₂: OR = 1.57 (1.00-2.48), per 5 dB(A) L_den road traffic: OR = 1.06 (0.91-1.23), railway: OR = 1.11 (1.03-1.20), and aircraft: OR = 1.22 (1.11-1.34). Spending >30 min/week in nature related to better health. In multi-exposure models, only associations with aircraft and railway L_den persisted. People with lower education and financial difficulties or living in poorer districts experienced some exposures stronger. In SEM, time spent in nature and PA mediated the effect of greenspace.

CONCLUSIONS

Greenspace was associated with better general health, with time spent in nature and PA emerging as intermediate pathways. NO₂, railway, and aircraft noise were associated with poorer general health. These results could inform decision-makers, urban planners, and civil society organizations facing urban development problems. Mitigation and abatement policies and measures should target socioeconomically disadvantaged citizens.

Urban-Rural Differences in the Prevalence of Depressive Symptoms in Korean Adults

This study aimed to investigate the prevalence of depression among Koreans living in urban and rural areas, stratified by socioeconomic status. The study included 216,765 participants from the 2017 Korean Community Health Survey. Depressive symptoms were assessed using the PHQ-9, with a score of 10 or higher indicating depressive symptoms. Residences with the words Eup and Myeon in their addresses were categorized as rural areas, and residences with Dong in their addresses as urban areas. Socioeconomic status was evaluated by household income and education level. A Poisson regression analysis with sampling weights was conducted and adjusted for demographic, lifestyle, socioeconomic status, and comorbidity. The adjusted prevalence rate of depressive symptoms was 3.33% (95% CI, 3.21-3.45) in urban areas and 2.59% (95% CI, 2.43-2.74) in rural areas. The prevalence of depressive symptoms in urban areas was 1.29 times (95% CI, 1.20-1.38) higher than in rural areas. The prevalence rate ratio for depressive symptoms in urban areas compared to rural areas sorted by monthly incomes was 1.39 (95% CI, 1.28-1.51) for less than 2 million won, 1.22 (95% CI, 1.06-1.41) for 2 to 3.99 million won, and 1.09 (95% CI, 0.90-1.32) for more than 4 million won, and the urban-rural difference was more evident in lower household income subjects (p for interaction=0.033). However, urban-rural differences did not differ according to sex, age, or education level. In conclusion, we found urban-rural differences in depressive symptoms in a representative sample of Koreans, and revealed that these differences may vary according to income level. These results suggest that mental health policy must consider the health disparities according to residence and income.

Short-term impact of noise, other air pollutants and meteorological factors on emergency hospital mental health admissions in the Madrid region

BACKGROUND

A number of environmental factors, such as air pollution, noise in urbanised settings and meteorological-type variables, may give rise to important effects on human health. In recent years, many studies have confirmed the relation between various mental disorders and these factors, with a possible impact on the increase in emergency hospital admissions due to these causes. The aim of this study was to analyse the impact of a range of environmental factors on daily emergency hospital admissions due to mental disorders in the Madrid Autonomous Region (MAR), across the period 2013-2018.

METHODOLOGY

Longitudinal ecological time series study analysed by Generalised Linear Models with Poisson regression, with the dependent variable being daily Emergency Hospital Mental Health Admissions (EHMHA) in the MAR, and the independent variable being mean daily concentrations of chemical pollutants, noise levels and meteorological variables.

RESULTS

EHMHA were related statistically significantly in the short term with diurnal noise levels. Relative risks (RRs) for total admissions due to mental disorders and self-inflicted injuries, in the case of diurnal noise was RR: 1.008 95%CI (1.003 1.013). Admissions attributable to diurnal noise account for 5.5% of total admissions across the study period. There was no association between hospital admissions and chemical air pollution.

CONCLUSION

Noise is a variable that shows a statistically significant short-term association with EHMHA across all age groups in the MAR region. The results of this study may serve as a basis for drawing up public health guidelines and plans, which regard these variables as risk factors for mental disorders, especially in the case of noise, since this fundamentally depends on anthropogenic activities in highly urbanised areas with high levels of traffic density.

Are actual and perceived environmental conditions associated with variation in mental health?

OBJECTIVE

Empirical evidence on the relationship between environmental factors and mental health remains inconclusive. One reason is that there is only scant evidence on the association between mental health and subjective exposure to environmental stressors, relative to objective pollution. We thus focus on how the perceived and actual presence of noise, air pollution, and green spaces relates to mental health.

METHODS AND RESULTS

Our cross-sectional study is based on a large representative sample of the adult population in Switzerland (n = 5729). Using individual-level geocodes of subjects' residence, we combined data from a survey of these individuals with data on objectively measured longer-term environmental conditions (noise, air pollution, green spaces). Subclinical mental health was assessed with the 12-item General Health Questionnaire (GHQ-12). When fitting multiple regressions and mediation models, we find that perceptions of environmental stressors are a better predictor of mental distress than objectively measured stressors. In addition, the predictive power of actual nature visits is stronger than the predictive power of mere proximity to green spaces at the place of residence. We found no direct link between actual environmental stressors and mental health, but mediation via perceived environmental stressors. Further, the association between the frequency of nature visits and mental health is mediated by perceived, but not actual pollution.

CONCLUSION

Since actual environmental stressors are not perceived as equally burdensome by all people, their subjective perception is crucial when evaluating policy interventions aimed at improving mental health. Even a relatively low level of environmental stressors, classified as non-harmful to human health in a physical or biological sense, may thus contribute to negative mental health outcomes. The main policy implication is that attractive and accessible green spaces may provide individuals with an enhanced sense of control over their exposure to environmental stressors and thereby reduce negative impacts.

Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland

BACKGROUND

Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise.

METHODS

Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM_2.5, PM_2.5 components (Cu, Fe, S and Zn), NO₂, black carbon (BC) and ozone (O₃) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges.

RESULTS

During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM_2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m³ PM_2.5, 1.050 (1.041, 1.059) per 10 µg/m³ NO₂, 1.057 (1.048, 1.067) per 0.5 × 10^-5/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO₂, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM_2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m³ for PM_2.5 and NO₂, < 1.5 10^-5/m BC and < 53 dB Lden total transportation noise. The O₃ association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC).

CONCLUSION

Long-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO₂, BC and transportation noise.

Traffic-Related High Sleep Disturbance in the LIFE-Adult Cohort Study: A Comparison to the WHO Exposure-Response-Curves

Sleep is negatively affected by environmental noise. In the present study, we investigated self-reported high sleep disturbances (being "highly sleep disturbed"-HSD) from road traffic (primary and secondary road networks), rail (train and tram) and air traffic noise in the LIFE-Adult cohort study in Leipzig, Germany. For this, we used exposure data from 2012 and outcome data of Wave 2 (collected during 2018-2021). HSD was determined and defined according to internationally standardized norms. The highest risk for transportation noise-related HSD was found for aircraft noise: the odds ratio (OR) was 19.66, 95% CI 11.47-33.71 per 10 dB increase in L_night. For road and rail traffic, similar risk estimates were observed (road: OR = 2.86, 95% CI 1.92-4.28; rail: OR = 2.67, 95% CI 2.03-3.50 per 10 dB L_night increase). Further, we compared our exposure-risk curves with the curves of the WHO environmental noise guidelines for the European region. The proportion of individuals with HSD for a given noise level was lower for rail traffic but higher for aircraft noise in the LIFE study than in the WHO curves. For road traffic, curves are not directly comparable because we also included the secondary road network. The results of our study add to the body of evidence for increased health risks by traffic noise. Moreover, the results indicate that aircraft noise is particularly harmful to health. We recommend reconsidering threshold values for nightly aircraft exposure.

Suicide and Transportation Noise: A Prospective Cohort Study from Switzerland

BACKGROUND

Although plausible from a pathophysiological point of view, robust evidence for effects of transportation noise on mental health remains scarce. Meanwhile, psychiatric diseases are among the most prevalent noncommunicable diseases worldwide, and suicide as a mortality outcome highly connected to mental disorders presents a pressing public health issue. The aim of this study was to investigate the association between source-specific transportation noise, particulate matter (PM) air pollution, residential greenness, and suicide by means of a nationwide cohort study.

METHODS

Road traffic, railway and aircraft noise exposure as well as exposure to air pollution [PM with aerodynamic diameter ≤2.5μm (PM2.5)] and greenness [normalized difference vegetation index (NDVI)] were linked to 5.1 million adults (age 15 y and older) in the Swiss National Cohort, accounting for their address history. Mean noise exposure in 5-y periods was calculated. Individuals were followed for up to 15 y (2001-2015). Time-varying Cox regression models were applied to deaths by suicide (excluding assisted suicide). Models included all three noise sources, PM2.5, and NDVI plus individual and spatial covariates, including socioeconomic status. Effect modification by sex, age, socioeconomic indicators, and degree of urbanization was explored.

RESULTS

During the follow-up, there were 11,265 suicide deaths (10.4% poisoning, 33.3% hanging, 28.7% firearms, 14.7% falls). Road traffic and railway noise were associated with total suicides [hazard ratios: 1.040; 95% confidence interval (CI): 1.015, 1.065; and 1.022 (95% CI: 1.004, 1.041) per 10 dB day-evening-night level (Lden)], whereas for aircraft noise, a risk increase starting from 50 dB was masked by an inverse association in the very low exposure range (30-40 dB). Associations were stronger for females than males. The results were robust to adjustment for residential greenness and air pollution.

CONCLUSION

In this longitudinal, nationwide cohort study, we report a robust association between exposure to road traffic and railway noise and risk of death by suicide after adjusting for exposure to air pollution and greenness. These findings add to the growing body of evidence that mental health disorders may be related to chronic transportation noise exposure. https://doi.org/10.1289/EHP11587.

Impact of climate events, pollution, and green spaces on mental health: an umbrella review of meta-analyses

Climate change may affect mental health. We conducted an umbrella review of meta-analyses examining the association between mental health and climate events related to climate change, pollution and green spaces. We searched major bibliographic databases and included meta-analyses with at least five primary studies. Results were summarized narratively. We included 24 meta-analyses on mental health and climate events (n = 13), pollution (n = 11), and green spaces (n = 2) (two meta-analyses provided data on two categories). The quality was suboptimal. According to AMSTAR-2, the overall confidence in the results was high for none of the studies, for three it was moderate, and for the other studies the confidence was low to critically low. The meta-analyses on climate events suggested an increased prevalence of symptoms of post-traumatic stress, depression, and anxiety associated with the exposure to various types of climate events, although the effect sizes differed considerably across study and not all were significant. The meta-analyses on pollution suggested that there may be a small but significant association between PM_2.5, PM₁₀, NO₂, SO₂, CO and mental health, especially depression and suicide, as well as autism spectrum disorders after exposure during pregnancy, but the resulting effect sizes varied considerably. Serious methodological flaws make it difficult to draw credible conclusions. We found reasonable evidence for an association between climate events and mental health and some evidence for an association between pollution and mental disorders. More high-quality research is needed to verify these associations.

Comparison of static and dynamic exposures to air pollution, noise, and greenness among seniors living in compact-city environments

GPS technology and tracking study designs have gained popularity as a tool to go beyond the limitations of static exposure assessments based on the subject's residence. These dynamic exposure assessment methods offer high potential upside in terms of accuracy but also disadvantages in terms of cost, sample sizes, and types of data generated. Because of that, with our study we aim to understand in which cases researchers need to use GPS-based methods to guarantee the necessary accuracy in exposure assessment. With a sample of 113 seniors living in Barcelona (Spain) we compare their estimated daily exposures to air pollution (PM2.5, PM10, NO2), noise (dB), and greenness (NDVI) using static and dynamic exposure assessment techniques. Results indicate that significant differences between static and dynamic exposure assessments are only present in selected exposures, and would thus suggest that static assessments using the place of residence would provide accurate-enough values across a number of exposures in the case of seniors. Our models for Barcelona's seniors suggest that dynamic exposure would only be required in the case of exposure to smaller particulate matter (PM2.5) and exposure to noise levels. The study signals to the need to consider both the mobility patterns and the built environment context when deciding between static or dynamic measures of exposure assessment.

Associations of road traffic noise and its frequency spectrum with prevalent depression in Taichung, Taiwan

Introduction

Exposure to road traffic noise has been reported to be associated with depression in many epidemiological studies, but the association between noise frequency spectrum and depression remains unclear. This community-based study investigated the associations between road traffic noise exposure and its frequency components with prevalent depression.

Methods

A total of 3,191 residents living in Taichung who participated in the Taiwan Biobank between 2010 and 2017, were included as study participants. The land-use regression models were used to evaluate individual annual average values of A-weighted equivalent sound level over 24 h (L_eq,24h) and particulate matter with an aerodynamic diameter <2.5 μm (PM_2.5) using the geographic information system. Multiple logistic regression was applied to estimate the odds ratios (ORs) for depression after adjusting for potential risk factors and PM_2.5.

Results

An interquartile range increase in L_eq,24h at full frequency (4.7 dBA), 1,000 Hz (5.2 dB), and 2,000 Hz (4.8 dB) was significantly associated with an elevated risk for depression with ORs of 1.62 (95% confidence interval [CI]: 1.03, 2.55), 1.58 (95% CI: 1.05, 2.37), and 1.58 (95% CI:1.03, 2.43), respectively, by controlling for PM_2.5. The high-exposure group (≥3rd quartile median of noise levels) at full frequency, 1,000 Hz, and 2,000 Hz had an increased risk for depression with ORs of 2.65 (95% CI: 1.16-6.05), 2.47 (95% CI: 1.07-5.70), and 2.60 (95% CI: 1.10-6.12), respectively, compared with the reference group (<1st quartile of noise levels) after adjustment for PM_2.5. Significant exposure-response trends were observed between the prevalent depression and noise exposure by quartiles at full frequency, 1,000 Hz, and 2,000 Hz (all p < 0.05).

Conclusion

Exposure to road traffic noise may be associated with an increased prevalence of depression, particularly at 1,000 and 2,000 Hz.

Linking the Urban Environment and Health: An Innovative Methodology for Measuring Individual-Level Environmental Exposures

Environmental exposures (EE) are increasingly recognised as important determinants of health and well-being. Understanding the influences of EE on health is critical for effective policymaking, but better-quality spatial data is needed. This article outlines the theoretical and technical foundations used for the construction of individual-level environmental exposure measurements for the population of a northern English city, Bradford. The work supports 'Connected Bradford', an entire population database linking health, education, social care, environmental and other local government data over a period of forty years. We argue that our current understanding of environmental effects on health outcomes is limited both by methodological shortcomings in the quantification of the environment and by a lack of consistency in the measurement of built environment features. To address these shortcomings, we measure the environmental exposure for a series of different domains including air quality, greenspace and greenness, public transport, walkability, traffic, buildings and the built form, street centrality, land-use intensity, and food environments as well as indoor dwelling qualities. We utilise general practitioners' historical patient information to identify the precise geolocation and duration of a person's residence. We model a person's local neighbourhood, and the probable routes to key urban functions aggregated across the city. We outline the specific geospatial procedure used to quantify the environmental exposure for each domain and use the example of exposure to fast-food outlets to illustrate the methodological challenges in the creation of city and nationwide environmental exposure databases. The proposed EE measures will enable critical research into the relationship and causal links between the built environment and health, informing planning and policy-making.

Effects of noise on pedestrians in urban environments where road traffic is the main source of sound

Research combining the measurement of objective variables with surveys of people's perception of noise on city streets is useful in terms of understanding the impact of urban noise on the population and improving the environment. Although previous investigations have analysed the factors that may influence the noise annoyance of citizens, it is usually considered as a global aspect. This paper presents research based on in situ surveys and objective variables (urban, meteorological and noise indicators) to evaluate some specific effects of noise on pedestrians in urban environments where road traffic is the main source of sound. The results show significant relationships of the effects of noise and perceptions of how noisy urban environments are with variables such as building height, road category and temperature, with correlation coefficients ranging from 0.37 to 0.64. Significant correlations between these subjective variables and the acoustic variables were also found, with explanations of variability that reached values of up to 50 %. A multivariate analysis revealed that both urban variables (especially the category of street) and environmental variables can be an alternative or a complement to models predicting the effects and perception of environmental noise based only on acoustic variables.

Automated identification and assessment of environmental noise sources

Noise pollution is one of the major health risks in urban life. The approach to measurement and identification of noise sources needs to be improved and enhanced to reduce high costs. Long measurement times and the need for expensive equipment and trained personnel must be automated. Simplifying the identification of main noise sources and excluding residual and background noise allows more effective measures. By spatially filtering the acoustic scene and combining unsupervised learning with psychoacoustic features, this paper presents a prototype system capable of automated calculation of the contribution of individual noise sources to the total noise level. Pilot measurements were performed at three different locations in the city of Ljubljana, Slovenia. Equivalent sound pressure levels obtained with the device were compared to the results obtained by manually marking individual parts of each of the three measurements. The proposed approach correctly identified the main noise sources in the vicinity of the measurement points.

Environmental noise and health in low-middle-income-countries: A systematic review of epidemiological evidence

Evidence of the health impacts from environmental noise has largely been drawn from studies in high-income countries, which has then been used to inform development of noise guidelines. It is unclear whether findings in high-income countries can be readily translated into policy contexts in low-middle-income-countries (LMICs). We conducted this systematic review to summarise noise epidemiological studies in LMICs. We conducted a literature search of studies in Medline and Web of Science published during 2009-2021, supplemented with specialist journal hand searches. Screening, data extraction, assessment of risk of bias as well as overall quality and strength of evidence were conducted following established guidelines (e.g. Navigation Guide). 58 studies were identified, 53% of which were from India, China and Bulgaria. Most (92%) were cross-sectional studies. 53% of studies assessed noise exposure based on fixed-site measurements using sound level meters and 17% from propagation-based noise models. Mean noise exposure among all studies ranged from 48 to 120 dB (L_eq), with over half of the studies (52%) reporting the mean between 60 and 80 dB. The most studied health outcome was noise annoyance (43% of studies), followed by cardiovascular (17%) and mental health outcomes (17%). Studies generally reported a positive (i.e. adverse) relationship between noise exposure and annoyance. Some limited evidence based on only two studies showing that long-term noise exposure may be associated with higher prevalence of cardiovascular outcomes in adults. Findings on mental health outcomes were inconsistent across the studies. Overall, 4 studies (6%) had "probably low", 18 (31%) had "probably high" and 36 (62%) had "high" risk of bias. Quality of evidence was rated as 'low' for mental health outcomes and 'very low' for all other outcomes. Strength of evidence for each outcome was assessed as 'inadequate', highlighting high-quality epidemiological studies are urgently needed in LMICs to strengthen the evidence base.

Environmental Noise Exposure and Sleep Habits among Children in a Cohort from Northern Spain

Environmental noise is considered the second most serious environmental risk factor in Europe. However, little evidence exists regarding its impact on health and sleep in children, and the results are inconclusive. In this study, we aim to analyse the effect of environmental noise exposure on 11-year-old children's sleep habits. Data were collected from 377 participants in the INMA-Gipuzkoa (INfancia y Medio Ambiente) cohort project using both parent-reported and actigraphic sleep measures. The results revealed that 60% of children have a day-evening-night environmental noise exposure (L_den) of above 55 dB, which is defined as a "high noise level". No differences in noise exposure were observed between different socioeconomic groups. However, no effect of environmental noise was found on sleep variables. The paper highlights the importance of studying how environmental noise may affect children's sleep.

Environmental stress, minority status, and local poverty: risk factors for mental health in Berlin's inner city

This study examines whether climate change-associated environmental stressors, including air and noise pollution, local heat levels, as well as a lack of surrounding greenspace, mediate the effects of local poverty on mental health, using the 28-item General Health Questionnaire. We recruited 478 adults who were representative of eleven of Berlin's inner-city neighborhoods. The relationship of individual-level variables, neighborhood-level sociodemographic and environmental data from the Berlin Senate (Department for Urban Development, Building and Housing) to mental health was assessed in a multilevel model using SPSS. We found that neither local exposure to environmental stressors, nor available greenspace as a protective factor, mediated the effects of local poverty on variance in mental health (all p values > 0.2). However, surrounding greenspace (r = -0.24, p < 0.001), nitrogen dioxide levels (r = 0.10, p < 0.05), noise pollution (rho = 0.15, p < 0.01), and particle pollution (r = 0.12, p < 0.001) were associated with local poverty, which, more strongly than individual factors, accounted for variance in mental health (β = 0.47, p < 0.001). Our analysis indicates that the effects of local poverty on mental health are not mediated by environmental factors. Instead, local poverty was associated with both an increased mental health burden and the exposure to climate-related environmental stressors.

Environmental noise-induced cardiovascular, metabolic and mental health disorders: a brief review

BACKGROUND

Environmental noise is a pervasive pollutant that is one of the greatest environmental threats to mental, physiological and psychological well-being and has a significant global health burden associated with it. Many epidemiological studies indicate long-term relationship of noise pollution with wide range of metabolic, cardio-vascular and respiratory disorders and diseases.

OBJECTIVE

The goal of this study was to thoroughly analyse available literature on public health implications and various underlying biological mechanisms associated with ambient noise exposure, taking into account both objective and subjective measures of noise exposure.

METHODS

A search of literature for review on environmental noise and associated cardiovascular, mental health and metabolic implications on human health was done using Web of Science, Google Scholar and PubMed databases.

DISCUSSION

Experimental studies indicate that noise exposure leads to endocrine effects, increased incidence of diabetes, impairment of cognitive performance, sleep disturbance and annoyance. Epidemiological evidence indicates that high levels of noise, particularly at night, may cause arterial hypertension and endothelial dysfunction due to higher level of stress hormones and oxidative stress. An increased incidence of cardio-vascular diseases like myocardial infarction, heart rate, ischemic heart disease, stroke and heart failure is associated with noise-induced mental stress. Furthermore, psychological and mental health issues like anxiety and depression are also related with exposure to noise pollution.

CONCLUSION

This article summarises a comprehensive and systematic knowledge established in recent noise research with the spotlight on cardiovascular, metabolic and mental health disorders of environmental noise, providing unique understanding into underlying mechanisms.

New determinants of mental health: the role of noise pollution. A narrative review

Urbanisation processes and anthropogenic actions led to a significant increase in pollution levels, with relevant consequences on global health. In particular, noise pollution demonstrated an association with cardiovascular, metabolic, and respiratory diseases. Furthermore, increasing evidence underlined the possible role of air and noise pollution in the development of psychiatric disorders. In this narrative review, evidence concerning the relationship between noise pollution and the emergence of psychiatric symptoms or psychiatric disorders is summarised. After the literature search process was completed, 40 papers were included in the present review. The exposure to road-, rail-, and air- traffic represented a risk factor for the emergence of affective disorders. This could also be mediated by the occurrence of circadian rhythms disturbances or by noise annoyance and noise sensitivity, both influencing psychological well-being and health-related quality of life. Fewer studies concentrated on special populations, particularly pregnant women and children, for whom noise pollution was confirmed as a risk factor for psychopathology. The better clarification of the complex interaction between noise pollution and mental health may help to identify subjects at risk and targeting specific prevention and intervention strategies in the urban environment.

Associations between personal noise exposure and heart rate variability were modified by obesity and PM2.5: The study among obese and normal-weight adults (SONA)

Noise pollution has been documented to increase the risks of cardiovascular disorders, which can be predicted by heart rate variability (HRV), nevertheless, there has been limited evidence on the modifiers of noise pollution. Environmental fine particulate matter (PM_2.5) and obesity status are both growing major concerns of cardiovascular disease burden. Our study aims to investigate whether these two factors may modify the associations between noise exposure and HRV indices. An investigation was performed on 97 (53 normal-weight and 44 obese) participants aged 18-26 years, with continuous 5-min personal exposure assessment and ambulatory electrocardiogram monitoring for 24 h. This study found that personal exposure to noise was associated with decreased HRV level and imbalanced cardiac autonomic function, as indicated by decreases in standard deviation of normal-to-normal intervals (SDNN), square root of the mean squared differences of successive intervals (rMSSD), the percentage of R-R intervals that differ from each other by more than 50 ms (pNN50), low-frequency (LF) power, high-frequency (HF) power, and increases in LF-HF-Ratio. Stronger associations between personal noise exposure and HRV indices were observed among obese participants and participants with higher PM_2.5 exposure levels compared to their counterparts. For SDNN, a 1 dB(A) increment in personal noise exposure at 3h-average was associated with a 1.25% (95%CI: -1.64%, -0.86%) decrease among obese participants, and a 0.11% (95%CI: -0.38%, 0.16%) decrease among normal-weight participants (P for subgroup difference<0.001); and a 0.87% (95%CI: -1.20%, -0.54%) decrease among participants with higher PM_2.5 exposure levels, and a 0.22% (95%CI: -0.58%, 0.14%) decrease among participants with lower PM_2.5 exposure levels (P for subgroup difference = 0.008). Obesity and PM_2.5 may aggravate the adverse effects of noise on HRV, which has implications for targeted prevention of cardiovascular disease burden associated with noise pollution.

Association of residential noise exposure with maternal anxiety and depression in late pregnancy

BACKGROUND

Noise is one of the most important environmental risk factors that adversely affects human health. Residential noise exposure has been associated with increased risk of anxiety and depression in the general population. However, limited study has been conducted in pregnant women.

OBJECTIVE

To examine the associations of residential noise exposure with prenatal anxiety and depression.

METHODS

Self-Rating Anxiety Scale (SAS) and Center for Epidemiological Survey Scale (CES-D) were used to assess the status of prenatal anxiety and depression for 2,018 pregnant women in Shanghai, China. Residential noise exposure was represented by a land use regression model. Multivariate logistic regression model was used to estimate the associations of noise exposure with prenatal anxiety and depression.

RESULTS

The prevalence rates of prenatal anxiety and depression were 7.5 % and 8.1 %, respectively. The mean (±standard deviation) residential noise exposure during the whole pregnancy was 60.69 (±3.31) dB (A). Higher residential noise exposure was associated with increased odds of both prenatal anxiety and depression. Compared with low level of noise exposure group (<65 dB(A)), the odds of prenatal anxiety and depression increased 69 % (OR = 1.69, 95 % CI, 1.01-2.82) and 71 % (OR = 1.71, 95 % CI, 1.05-2.80) in higher noise exposure group (≥65 dB(A)), respectively. Stratified analyses showed that the associations were stronger among pregnant women with lower socioeconomic status.

CONCLUSION

Residential noise exposure during pregnancy might be a risk factor for prenatal anxiety and depression.

The effects of indoor plants and traffic noise on English reading comprehension of Chinese university students in home offices

Owing to the COVID-19 pandemic, working from home promotes the importance of indoor environment qualities. With the settings and functions of home offices, an experiment was carried out to determine the interaction effects between indoor plants and traffic noise levels (TNLs) on the performance and environmental evaluations of English reading comprehension tasks (ERCTs) and the performance of short-term breaks. A sample of 22 Chinese university students (12 males and 10 females) took part in the experiment. Two visual conditions (with and without plants) and five TNLs (i.e., 35, 45, 50, 55, and 60 dBA TNL) were included. Participants’ accuracy rates, eye movements, mental workload, and feelings about the environment were collected. The mental fatigue recovery (MFR), visual fatigue recovery (VFR), anxiety recovery (AR), and unfriendly recovery (UR) were measured for the analysis of a 5-min short-term break. The results demonstrate (1) plants have significant effects on ERCTs and short-term breaks, especially at 45 and 50 dBA TNL; (2) the effects of TNLs on ERCTs’ eye movements and work environment satisfaction differ by the presence of plants, e.g., the average pupil diameter (APD), lighting and layout satisfaction; (3) The effects of indoor plants on ERCT differ by the range of TNLs. In conclusion, indoor plants are beneficial to home workers engaged in ERCT when TNL does not exceed 50 dBA. The current data highlight the importance of audio-visual interaction in home offices and provide insights into the interaction mechanism between indoor plants and traffic noise.

The Impact of Foehn Wind on Mental Distress among Patients in a Swiss Psychiatric Hospital

Psychiatric patients are particularly vulnerable to strong weather stimuli, such as foehn, a hot wind that occurs in the alps. However, there is a dearth of research regarding its impact on mental health. This study investigated the impact of foehn wind among patients of a psychiatric hospital located in a foehn area in the Swiss Alps. Analysis was based on anonymized datasets obtained from routine records on admission and discharge, including the Brief Symptom Checklist (BSCL) questionnaire, as well as sociodemographic parameters (age, sex, and diagnosis). Between 2013 and 2020, a total of 10,456 admission days and 10,575 discharge days were recorded. All meteorological data were extracted from the database of the Federal Office of Meteorology and Climatology of Switzerland. We estimated the effect of foehn on the BSCL items using a distributed lag model. Significant differences were found between foehn and non-foehn admissions in obsession-compulsion, interpersonal sensitivity, depression, anxiety, phobic anxiety, paranoid ideation, and general severity index (GSI) (p < 0.05). Our findings suggest that foehn wind events may negatively affect specific mental health parameters in patients. More research is needed to fully understand the impact of foehn's events on mental health.

Traffic noise and adiposity: a systematic review and meta-analysis of epidemiological studies

Traffic noise has attracted much attention as a significant and intractable public health threat. This study was designed as a systematical review to explore the association of traffic noise with different indicators of obesity, thus providing updated quantitative estimates for the pooled effect estimates of the existing literature. We conducted an extensive search for epidemiological studies that investigated the association of traffic noise with obesity in three electronic databases till February 23, 2021. We used random-effects meta-analysis to calculate the summary effect estimates for each 10-dB(A) increase in noise and compared the highest with the lowest category of noise in relation to seven obesity indicators. Meanwhile, we assessed the risk of bias and the overall quality of the evidence of each study as well as the level of evidence for each exposure-outcome pair. The initial search identified 30 studies, 13 of which were ultimately included. The meta-analysis for the highest versus the lowest category of noise exposure was generally associated with higher waist circumfluence (WC) ranging from 0.326 cm (95% confidence interval (CI) = 0.078, 0.574) to 0.705 cm (95% CI = 0.071, 1.340) and higher odds of central obesity ranging from 1.055 (95% CI = 1.000, 1.109) to 1.167 (95% CI = 1.037, 1.298). When the continuous exposure (each 10 dB(A) increase in noise) was introduced, similar results were found. This study indicated positive associations of traffic noise with WC and central obesity. However, in consideration of some limitations, there is an urgent need for future studies to increase the sample size, discriminate the etiological differences in different noise and obesity indicators, and thoroughly consider socioeconomic status.

Environmental Noise Exposure and Mental Health: Evidence From a Population-Based Longitudinal Study

INTRODUCTION

Exposure to environmental noise from within homes has been associated with poor mental health. Existing evidence rests on cross-sectional studies prone to residual confounding, reverse causation, and small sample sizes, failing to adequately consider the causal nature of this relationship. Furthermore, few studies have examined the sociodemographic distribution of noise exposure at a country level.

METHODS

The study, conducted in 2021, examined the impact of environmental noise from road traffic, airplanes, trains, and industry on mental health and psychological distress as reported by 31,387 respondents using a 19-year longitudinal data set in Australia (2001‒2019). To improve the capacity to make causal inference and reduce bias from measurement error, reverse causation, and unobserved confounders, analyses used instrumental variables, fixed-effects models, and an aggregated area-level measure of noise exposure. Utilizing the large-scale national data set, sociospatial distributions of noise exposure were described.

RESULTS

Private and public rental tenants, lone parents, residents of socioeconomically disadvantaged areas, and those with long-term health conditions were more likely to report residential noise exposure. This exposure to noise was consistently associated with poorer mental health (self-reported noise: β= -0.58; 95% CI= -0.76, -0.39; area-level noise: β= -0.43; 95% CI= -0.61, -0.26), with the relationship strongest for traffic noise (β= -0.79; 95% CI= -1.07, -0.51). Notably, when noise exposure decreased over time, there was an increase in mental health (β= 0.43; 95% CI= 0.14, 0.72).

CONCLUSIONS

The study provides strong evidence of a negative mental health effect of perceived residential noise, and the results have implications for healthy home design and urban planning. These findings should be validated with further studies that measure noise intensity and housing quality.

Cerebral consequences of environmental noise exposure

The importance of noise exposure as a major environmental determinant of public health is being increasingly recognized. While in recent years a large body evidence has emerged linking environmental noise exposure mainly to cardiovascular disease, much less is known concerning the adverse health effects of noise on the brain and associated neuropsychiatric outcomes. Despite being a relatively new area of investigation, indeed, mounting research and conclusive evidence demonstrate that exposure to noise, primarily from traffic sources, may affect the central nervous system and brain, thereby contributing to an increased risk of neuropsychiatric disorders such as stroke, dementia and cognitive decline, neurodevelopmental disorders, depression, and anxiety disorder. On a mechanistic level, a significant number of studies suggest the involvement of reactive oxygen species/oxidative stress and inflammatory pathways, among others, to fundamentally drive the adverse brain health effects of noise exposure. This in-depth review on the cerebral consequences of environmental noise exposure aims to contribute to the associated research needs by evaluating current findings from human and animal studies. From a public health perspective, these findings may also help to reinforce efforts promoting adequate mitigation strategies and preventive measures to lower the societal consequences of unhealthy environments.

Chronic Noise Exposure and Risk of Dementia: A Systematic Review and Dose-Response Meta-Analysis

Objective

Evidence is scarce about the effect of noise exposure on the risk of dementia. We conducted a systematic review and dose-response meta-analysis, aiming to explore the association between noise exposure and the risk of dementia.

Methods

We searched PubMed, EMBASE and the Cochrane Library to collect studies on chronic noise exposure and the risk of dementia from database inception to September 18, 2021 without language limitations. Two authors independently screened the literature, extracted data and assessed the risk of bias of the included studies. A dose-response meta-analysis and subgroup analysis were then conducted to detect the association between noise exposure and the risk of dementia by using Stata 14.0 software. This study is registered on PROSPERO (CRD42021249243).

Results

A total of 11 studies were eligible for qualitative synthesis, and nine were eligible for quantitative data synthesis. All of them showed moderate to high quality scores in the assessment of risk of bias. We found a positive linear association between the noise increment and dementia risk (R2 = 0.58). When noise exposure increased 57 dB, the RR of dementia was 1.47 (95% CI: 1.21–1.78). From the outcome subgroup of AD, AD and dementia, VaD and NAD, we also found a positive association (R2 = 0.68, 0.68, 0.58, respectively). When noise exposure increased by 25 dB, the RRs were 1.18 (95% CI: 1.14–1.23), 1.19 (95% CI: 1.14–1.23) and 1.17 (95% CI: 1.06–1.30), respectively. We found a nonlinear association between the noise increment and dementia risk when only cohort studies were included (R2 = 0.58). When noise exposure increased by 25 dB, the RR of dementia was 1.16 (95% CI: 1.12–1.20). From the subgroup of AD, AD and dementia, VaD and NAD of cohort studies, the regression curve showed a nonlinear positive association (R2 = 0.74, 0.71, 0.43, respectively). When noise exposure increased by 25 dB, the RRs were 1.17 (95% CI: 1.12–1.21), 1.17 (95% CI: 1.12–1.22) and 1.13 (95% CI: 0.99–1.28), respectively.

Conclusion

Based on the current evidence, exposure to noise may be a specific risk factor for dementia. To better prevent dementia, more rigorously designed studies are needed to explore the etiological mechanism of noise and dementia.

Relation between Noise Pollution and Life Satisfaction Based on the 2019 Chinese Social Survey

Noise pollution is a leading cause of decreasing well-being of residents in both developed and developing countries. Improving residents’ well-being measured by life satisfaction is a key goal of government policy. Individuals with high life satisfaction usually have positive emotions, life orientation, and codes of conduct, which are positive and beneficial for individuals, families, and society as a whole. In order to supplement relevant research and provide policy suggestions for individuals, government, and societies, this study explores the relationship between noise pollution and the life satisfaction of Chinese residents. Based on data from 4869 observations from the Chinese Social Survey in 2019, the effect of noise pollution on life satisfaction is estimated by using ordinary least squares and propensity score matching methods. The results show that noise pollution has a significant negative effect on Chinese life satisfaction. Moreover, the effect is heterogeneous depending on individuals’ education levels and ages. Finally, residents’ living environment satisfaction is shown to be the potential mechanism by which noise pollution affects life satisfaction.