Not urbanization level but socioeconomic, physical and social neighbourhood characteristics are associated with presence and severity of depressive and anxiety disorders

Care training and family caregiver anxiety: prospective cohort study

OBJECTIVES

The study aimed to improve family caregivers' skills and evaluate the effect on their anxiety levels.

METHOD

In our study, family caregivers of patients unable to perform daily activities were provided with care training. Their anxiety levels were examined before and after the training.

RESULTS

Care training increased the family caregivers' sense of self-efficacy but caused no significant difference in their anxiety levels. Factors such as gender, education level and employment status influenced anxiety levels. Higher education and income were associated with lower trait anxiety while employment status was linked to higher anxiety levels.

CONCLUSION

Care training increased the family caregivers' sense of self-efficacy while causing no difference in their anxiety levels. In order to reduce anxiety, other negative factors affecting the caregiver should be discovered and corrected.

Neighborhood factors associated with late effects among survivors of adolescent and young adult cancer

PURPOSE

The purpose of this study is to evaluate the associations between neighborhood income, education, and neighborhood racial composition (measured as a low percentage of white residents) and risk of developing cardiovascular diseases (CVD), diabetes (DM), and severe depression among survivors of AYA cancer and matched non-cancer peers.

METHODS

Two-year survivors of AYA cancers diagnosed at age 15-39 yrs at Kaiser Permanente Southern California (diagnosed 2000-2012) and individually matched (1:13) non-cancer subjects were included. The development of CVD, DM, and severe depression was ascertained via electronic health records. Neighborhood characteristics were obtained from census-based geocoded data. Cox regression evaluated associations between neighborhood characteristics and the health outcomes of interest among both the cancer survivors and the non-cancer comparison cohort and effect modification by cancer survivor status on these relationships.

RESULTS

Among cancer survivors (n = 6774), living in mostly non-white neighborhoods, was associated with risk of CVD (hazard ratio (HR) = 1.54 (95% CI 1.00-2.36)), while lower education level (HR = 1.41 (95% CI 1.02-1.94)) was associated with risk of severe depression. None of the neighborhood characteristics were associated with risk of DM. Effect modification was found for neighborhood education and risk of DM and severe depression.

CONCLUSION

When jointly considered, cancer survivors who resided in the most disadvantaged neighborhoods were at the highest risk of developing these health outcomes compared to other subgroups.

IMPLICATIONS FOR CANCER SURVIVORS

Our findings may inform screening strategy and addressing social determinants of health among AYA cancer survivors.

Comparing Transdiagnostic Risk Factors: Predicting Emergence of Significant Depressive, Anxiety, and Substance Abuse Symptoms Among Juvenile Delinquents

In a 7-year 11-wave study of low-SES adolescents (N = 856, age = 15.98), we compared multiple well-established transdiagnostic risk factors as predictors of first incidence of significant depressive, anxiety, and substance abuse symptoms across the transition from adolescence to adulthood. Risk factors included negative emotionality, emotion regulation ability, social support, gender, history of trauma, parental histories of substance abuse, parental mental health, and socioeconomic status. Machine learning models revealed that negative emotionality was the most important predictor of both depression and anxiety, and emotion regulation ability was the most important predictor of future significant substance abuse. These findings highlight the critical role that dysregulated emotion may play in the development of some of the most prevalent forms of mental illness.

Neighborhood disadvantage and parenting predict longitudinal clustering of uncinate fasciculus microstructural integrity and clinical symptomatology in adolescents

Parenting behaviors and neighborhood environment influence the development of adolescents' brains and behaviors. Simultaneous trajectories of brain and behavior, however, are understudied, especially in these environmental contexts. In this four-wave study spanning 9-18 years of age (N=224 at baseline, N=138 at final assessment) we used longitudinal k-means clustering to identify clusters of participants with distinct trajectories of uncinate fasciculus (UF) fractional anisotropy (FA) and anxiety symptoms; we examined behavioral outcomes and identified environmental factors that predicted cluster membership. We identified three clusters of participants: 1) high UF FA and low symptoms ("low-risk"); 2) low UF FA and high symptoms ("high-risk"); and 3) low UF FA and low symptoms ("resilient"). Adolescents in disadvantaged neighborhoods were more likely to be in the resilient than high-risk cluster if they also experienced maternal warmth. Thus, neighborhood disadvantage may confer neural risk for psychopathology that can be buffered by maternal warmth, highlighting the importance of considering multiple environmental influences in understanding emotional and neural development in youth.

Cities and mental health: The role of the built environment, and environmental and lifestyle factors in Barcelona

Built environment characteristics and related environmental exposures and behaviors have been, separately, implicated in the development of poor mental health. However, it is unclear how these factors act together in relation to mental health. We studied these factors simultaneously to evaluate the impact of the built environment, and the mediating role of environmental exposures and physical activity, on mental health, while also studying moderation by sex, age, and length of residence. We used a cross-sectional population-based sample of 3145 individuals aged 15-97 years from Barcelona, Spain. Time spent walking and mental health status were assessed with validated questionnaires, administered through a face-to-face interview. We characterized the built environment (e.g., building, population and intersection density and green space), road traffic noise, and ambient air pollution at the residential level using land cover maps, remote sensing, noise maps and land use regression models. Adjusted regression models accounting for spatial clustering were analyzed to study associations between built environment attributes and mental health, and mediation and moderation effects. Density attributes were directly or indirectly, through air pollution and less consistently through walking, associated with poor mental health. Green space indicators were associated with lower prevalence of poor mental health, partly through lower air pollution exposure and more walking. In some cases, these associations differed by sex, age or length of residence. Non-linear associations of density indicators with environmental exposures, and of particulate matter with poor mental health indicated threshold effects. We conclude that living in dense areas with high air pollution concentrations was associated with poor mental health. On the other hand, green areas with lower air pollution concentrations were protective against poor mental health. Greater urban density might benefit health, but might only do so when air pollution concentrations are low.

Green spaces exposure and the risk of common psychiatric disorders: A meta-analysis

Objective

To explore the effects of green spaces exposure on common psychiatric disorders.

Methods

PubMed, Embase, Web of Science and MEDLINE were screened and articles published prior to November 15, 2023 were included. Analyses were performed on common psychiatric disorders, categorized into depression, anxiety, dementia, schizophrenia, and attention deficit hyperactivity disorder (ADHD). And the subgroup analyses were conducted for depression, anxiety, dementia, and schizophrenia.

Results

In total, 2,0064 studies were retrieved, 59 of which were included in our study; 37 for depression, 14 for anxiety, 8 for dementia, 7 for schizophrenia and 5 for ADHD. Green spaces were found to benefit the moderation of psychiatric disorders (OR = 0.91, 95% CI: 0.89 to 0.92). Green spaces positively influence depression (OR = 0.89, 95% CI: 0.86 to 0.93), regardless of the cross-sectional or cohort studies. Green spaces can also help mitigate the risk of anxiety (OR = 0.94, 95%CI:0.92 to 0.96). As an important index for measuring green spaces, a higher normalized difference vegetation index (NDVI) level related to a lower level of depression (OR = 0.95, 95%CI:0.91 to 0.98) and anxiety (OR = 0.95, 95%:0.92 to 0.98). The protection was also found in dementia (OR = 0.95, 95% CI: 0.93 to 0.96), schizophrenia (OR = 0.74, 95% CI: 0.67 to 0.82), and ADHD (OR = 0.89, 95% CI: 0.86 to 0.92) results.

Conclusion

Green spaces decrease the risk of psychiatric disorders, including depression, anxiety, dementia, schizophrenia, and ADHD. Further studies on green spaces and psychiatric disorders are needed, and more green spaces should be considered in city planning.

Association of Neighborhood Deprivation and Depressive Symptoms With Epigenetic Age Acceleration: Evidence From the Canadian Longitudinal Study on Aging

BACKGROUND

Neighborhood deprivation and depression have been linked to epigenetic age acceleration. The next-generation epigenetic clocks including the DNA methylation (DNAm) GrimAge, and PhenoAge have incorporated clinical biomarkers of physiological dysregulation by selecting cytosine-phosphate-guanine sites that are associated with risk factors for disease, and have shown improved accuracy in predicting morbidity and time-to-mortality compared to the first-generation clocks. The aim of this study is to examine the association between neighborhood deprivation and DNAm GrimAge and PhenoAge acceleration in adults, and assess interaction with depressive symptoms.

METHODS

The Canadian Longitudinal Study on Aging recruited 51 338 participants aged 45-85 years across provinces in Canada. This cross-sectional analysis is based on a subsample of 1 445 participants at baseline (2011-2015) for whom epigenetic data were available. Epigenetic age acceleration (years) was assessed using the DNAm GrimAge and PhenoAge, and measured as residuals from regression of the biological age on chronological age.

RESULTS

A greater neighborhood material and/or social deprivation compared to lower deprivation (b = 0.66; 95% confidence interval [CI] = 0.21, 1.12) and depressive symptoms scores (b = 0.07; 95% CI = 0.01, 0.13) were associated with higher DNAm GrimAge acceleration. The regression estimates for these associations were higher but not statistically significant when epigenetic age acceleration was estimated using DNAm PhenoAge. There was no evidence of a statistical interaction between neighborhood deprivation and depressive symptoms.

CONCLUSIONS

Depressive symptoms and neighborhood deprivation are independently associated with premature biological aging. Policies that improve neighborhood environments and address depression in older age may contribute to healthy aging among older adults living in predominantly urban areas.

"Urban-Satellite" estimates in the ABCD Study: Linking Neuroimaging and Mental Health to Satellite Imagery Measurements of Macro Environmental Factors

While numerous studies over the last decade have highlighted the important influence of environmental factors on mental health, globally applicable data on physical surroundings are still limited. Access to such data and the possibility to link them to epidemiological studies is critical to unlocking the relationship of environment, brain and behaviour and promoting positive future mental health outcomes. The Adolescent Brain Cognitive Development (ABCD) Study is the largest ongoing longitudinal and observational study exploring brain development and child health among children from 21 sites across the United States. Here we describe the linking of the ABCD study data with satellite-based "Urban-Satellite" (UrbanSat) variables consisting of 11 satellite-data derived environmental indicators associated with each subject's residential address at their baseline visit, including land cover and land use, nighttime lights, and population characteristics. We present these UrbanSat variables and provide a review of the current literature that links environmental indicators with mental health, as well as key aspects that must be considered when using satellite data for mental health research. We also highlight and discuss significant links of the satellite data variables to the default mode network clustering coefficient and cognition. This comprehensive dataset provides the foundation for large-scale environmental epidemiology research.

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.

Regional differences in the effects of healthy aging on depressive symptoms: a Korean longitudinal study of aging (2006-2020)

Background

Depression is a widely prevalent, often recurrent condition. To analyze the regional differences in depressive symptoms over time, we investigated urban-rural differences in change in depression over time in South Korea and the association between healthy aging and depressive symptoms among middle-aged and older adults.

Methods

Data collected in the Korean Longitudinal Study of Aging, from 2006 to 2020, of adult participants aged ≥45 years without depressive symptoms were analyzed. Healthy aging was defined under five principal components: absence of chronic disease, good physical function, normal cognitive function, active social engagement, and good psychological adaptation. Depressive symptoms were measured using the short version of the Center for Epidemiologic Studies Depression Scale. Using the Andersen-Gill model for recurrent time-to-event, we examined the effect of healthy aging on depressive symptoms, with a subgroup analysis based on the residential area.

Results

Of the 7,708 participants, 78.2% lived in urban areas and 39.4% achieved healthy aging. In 2008, rural residents had a higher incidence of depressive symptoms (rural 11.8%; urban 8.9%); however, after 2016, the depressive symptoms of urban residents gradually increased (rural 6.4%; urban 12.1%). Unhealthy aging (adjusted hazard ratio = 3.04, 95% confidence interval: 2.72-3.39) and urban residence (adjusted hazard ratio = 1.15, 95% confidence interval: 1.06-1.24) were risk factors for depressive symptoms. The subgroup analysis revealed that individuals who did not achieve healthy aging had an increased risk of depressive symptoms, regardless of their residential area (hazard ratio [95% confidence interval]: urban, 3.13 [2.75-3.55]; rural 2.59 [2.05-3.28]).

Conclusion

As urbanization accelerates, urban residents have a higher risk of depressive symptoms than rural residents. Healthy aging is an essential factor in reducing depressive symptoms. To achieve healthy aging, appropriate interventions and policies that target the middle-aged adults and gradually extend to older adults are needed, considering individual and regional factors.

Mapping insomnia symptoms and circadian preferences to mental health problems in men and women across the lifespan

This study identified subgroups in the general population based on combinations in three night-time insomnia symptoms and four dimensions of circadian preferences ("sleep profiles") and investigated the associations between sleep profiles and nine common mental health problems. The data came from the Lifelines cohort add-on study "Comorbid Conditions of ADHD" and included 37,716 individuals (aged 4-91 years) from the Dutch general population who completed a digital survey. Latent profile analysis was used to identify sleep profiles in twelve age-sex subgroups. Linear regression was used to investigate whether sleep profiles differ in mental health problems. Participants were classified into three sleep profiles: "Healthy Larks", who had early circadian preferences and no insomnia symptoms; "Sleepy Owls" with late circadian preferences and nonrestorative sleep; and "Sleepless Doves" with intermediate circadian preferences and severe insomnia symptoms. Compared to "Healthy Larks", all mental health problems were significantly more severe in "Sleepy Owls" and even worse in "Sleepless Doves". These associations were similar in men and women but weakened with age. However, "Sleepy Owls" and "Sleepless Doves" did not differ in heavy alcohol drinking, drug use, and smoking. Our findings strengthened the evidence for the universal role of healthy sleep in mental wellbeing.

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.

Short-term exposure sequences and anxiety symptoms: a time series clustering of smartphone-based mobility trajectories

BACKGROUND

Short-term environmental exposures, including green space, air pollution, and noise, have been suggested to affect health. However, the evidence is limited to aggregated exposure estimates which do not allow the capture of daily spatiotemporal exposure sequences. We aimed to (1) determine individuals' sequential exposure patterns along their daily mobility paths and (2) examine whether and to what extent these exposure patterns were associated with anxiety symptoms.

METHODS

We cross-sectionally tracked 141 participants aged 18-65 using their global positioning system (GPS) enabled smartphones for up to 7 days in the Netherlands. We estimated their location-dependent exposures for green space, fine particulate matter, and noise along their moving trajectories at 10-min intervals. The resulting time-resolved exposure sequences were then partitioned using multivariate time series clustering with dynamic time warping as the similarity measure. Respondents' anxiety symptoms were assessed with the Generalized Anxiety Disorders-7 questionnaire. We fitted linear regressions to assess the associations between sequential exposure patterns and anxiety symptoms.

RESULTS

We found four distinctive daily sequential exposure patterns across the participants. Exposure patterns differed in terms of exposure levels and daily variations. Regression results revealed that participants with a "moderately health-threatening" exposure pattern were significantly associated with fewer anxiety symptoms than participants with a "strongly health-threatening" exposure pattern.

CONCLUSIONS

Our findings support that environmental exposures' daily sequence and short-term magnitudes may be associated with mental health. We urge more time-resolved mobility-based assessments in future analyses of environmental health effects in daily life.

The association between short-term exposure to nitrogen dioxide and hospital admission for schizophrenia: A systematic review and meta-analysis

BACKGROUND

Ambient air pollution has been identified as a primary risk factor for mental disorders. In recent years, the relationship between exposure to ambient nitrogen dioxide (NO2) and the risk of hospital admissions (HAs) for schizophrenia has garnered increasing scientific interest, but evidence from epidemiological studies has been inconsistent. Therefore, a systematic review and meta-analysis were conducted to comprehensively identify potential correlations.

METHODS

A literature search in 3 international databases was conducted before December 31, 2022. Relative risk (RR) and corresponding 95% confidence intervals (CI) were calculated to evaluate the strength of the associations. Summary effect sizes were calculated using a random-effects model due to the expected heterogeneity (I2 over 50%).

RESULTS

A total of ten eligible studies were included in the meta-analysis, including 1,412,860 participants. The pooled analysis found that an increased risk of HAs for schizophrenia was associated with exposure to each increase of 10 μg/m3 in NO2 (RR = 1.029, 95% CI = 1.016-1.041, P < .001). However, the heterogeneity was high for the summary estimates, reducing the credibility of the evidence. In 2-pollutant models, results for NO2 increased by 0.3%, 0.2% and 2.3%, respectively, after adjusting for PM2.5, PM10 and SO2.

CONCLUSIONS

This study provides evidence that NO2 exposure significantly increases the risk of hospital admission for schizophrenia. Future studies are required to clarify the potential biological mechanism between schizophrenia and NO2 exposure to provide a more definitive result.

Community indicators for mental health in Europe: a scoping review

Background

Community indicators may predict and influence individuals` mental health, and support or impede mental health management. However, there is no consensus on which indicators should be included in predictions, prognostic algorithms, or management strategies for community-based mental health promotion and prevention approaches. Therefore, this scoping review provides an overview of relevant community-level indicators for mental health in the general as well as risk populations in a European context.

Methods

We conducted a scoping review in the following electronic databases: PubMed, Embase, and PsycInfo. Eligible studies focused on context factors such as either the physical or social environment, reporting at least one mental health outcome and referring to a European population. Publications between 2012 and March 8, 2022 are considered.

Results

In total, the search yielded 12,200 identified records. After the removal of duplicates, 10,059 records were screened against the eligibility criteria. In total, 169 studies were included in the final analysis. Out of these included studies, 6% focused on pan-European datasets and 94% on a specific European country. Populations were either general or high-risk populations (56 vs. 44%, respectively) with depressive disorder as the main reported outcome (49%), followed by general mental health (33%) and anxiety (23%). Study designs were cross-sectional studies (59%), longitudinal (27%), and others (14%). The final set of indicators consisted of 53 indicators, which were grouped conceptually into 13 superordinate categories of community indicators. These were divided into the domains of the physical and social environment. The most commonly measured and reported categories of community indicators associated with mental health outcomes were social networks (n = 87), attitudinal factors toward vulnerable groups (n = 76), and the characteristics of the built environment (n = 56).

Conclusion

This review provides an evidence base of existing and novel community-level indicators that are associated with mental health. Community factors related to the physical and social environment should be routinely recorded and considered as influencing factors or potentially underestimated confounders. The relevance should be analyzed and included in clinical outcomes, data, monitoring and surveillance as they may reveal new trends and targets for public mental health interventions.

Excessive Noise in Neonatal Units and the Occupational Stress Experienced by Healthcare Professionals: An Assessment of Burnout and Measurement of Cortisol Levels

Excessive noise in the work environment has been associated with extra-auditory symptoms, which can have harmful long-term effects on individuals. The purpose of this study was to identify noise levels in neonatal intensive care units and investigate their impact on the occurrence of stress among healthcare professionals, using cortisol levels as a biomarker for Burnout Syndrome. This descriptive, observational, and cross-sectional study was conducted in four public teaching hospitals in Fortaleza, Ceará, Brazil. Sound pressure levels in the environment were measured, and questionnaires were administered to collect sociodemographic data and assess perceptions of the work environment and Burnout symptoms. Saliva samples were collected at the beginning and end of work shifts for cortisol quantification. The average sound pressure ranged from 59.9 to 66.4 dB(A), exceeding the recommended levels set by Brazilian and international legislation. Among the 256 participants, the average age was 39.4 years, with 95% being female. The majority (70.9%) were nurses, and 22.7% were physicians. There was no significant association found between noise and Burnout Syndrome, nor with changes in cortisol levels. However, a significant association was observed between the perception of excessive noise and the sensation of a stressful work shift (p = 0.012). All evaluated professionals displayed symptoms of Burnout. The high sound pressure levels indicated that the assessed environments did not meet the recommended standards for acoustic comfort, and this was associated with the participants' perception of stressful work shifts. While Burnout symptoms were evident in our participants, it was not possible to confirm a correlation with high noise levels.

Mental Health of the Russian Federation Population versus Regional Living Conditions and Individual Income

The objective of our study was to assess the impact of regional living conditions on the Russian population's mental health. For the analysis, we used data from the cross-sectional stage of a 2013-2014 study, "Epidemiology of Cardiovascular Diseases in the Regions of the Russian Federation (ESSE-RF)". The final sample included 18,021 men and women 25-64 years of age from 11 regions of Russia. Using principal component analysis, we performed an integral simultaneous assessment of stress, anxiety, and depression. To describe the regional living conditions, we utilized five regional indices, which were computed from publicly available data of the Federal State Statistics Service of Russia. Overall, mental health indicators were improved, on the one hand, with the deterioration of social conditions and an aggravation of the demographic depression in the region, but on the other hand, they were improved with an increase in economic and industrial development, along with economic inequality among the population. In addition, the impact of regional living conditions on mental health increased with a higher individual wealth. The obtained results provided new fundamental knowledge on the impact of the living environment on health, using the case study of the Russian population, which has been little studied in this regard.

Social and physical neighbourhood characteristics and 10-year incidence of depression and anxiety in older adults: Results from the Longitudinal Aging Study Amsterdam

OBJECTIVE

A growing literature suggests that neighbourhood characteristics are associated with mental health outcomes, but the evidence in older adults is inconsistent. We investigated the association of neighbourhood characteristics, pertaining to demographic, socio-economic, social and physical environment domains, with the subsequent 10-year incidence of depression and anxiety, in Dutch older adults.

METHODS

In the Longitudinal Aging Study Amsterdam depressive and anxiety symptoms were assessed four times between 2005/2006 and 2015/2016, using the Center for Epidemiological Studies Depression Scale (n = 1365) and the Anxiety subscale of the Hospital Anxiety and Depression Scale (n = 1420). Neighbourhood-level data on urban density, percent population over 65 years of age, percent immigrants, average house price, average income, percent low-income earners, social security beneficiaries, social cohesion, safety, proximity to retail facilities, housing quality, percent green space, percent water coverage, air pollution (particulate matter (PM2.5)), and traffic noise, were obtained for study baseline years 2005/2006. Cox proportional hazard regression models, clustered within neighbourhood, were used to estimate the association between each neighbourhood-level characteristic and the incidence of depression and anxiety.

RESULTS

The incidence of depression and anxiety was 19.9 and 13.2 per 1000 person-years, respectively. Neighbourhood characteristics were not associated with the incidence of depression. However, various neighbourhood characteristics were associated with an increased incidence of anxiety, including: higher urban density level, higher percent immigrants, greater proximity to retail facilities, lower housing quality score, lower safety score, higher PM2.5 levels and less green space.

CONCLUSION

Our results indicate that several neighbourhood characteristics are associated with anxiety but not with depression incidence in older age. Several of these characteristics have the potential to be modifiable and thus could serve as a target for interventions at the neighbourhood-level in improving anxiety, provided that future studies replicate our findings and provide further evidence for a causal effect.

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.

The Contribution of Environmental Science to Mental Health Research: A Scoping Review

Mental health is influenced by multiple complex and interacting genetic, psychological, social, and environmental factors. As such, developing state-of-the-art mental health knowledge requires collaboration across academic disciplines, including environmental science. To assess the current contribution of environmental science to this field, a scoping review of the literature on environmental influences on mental health (including conditions of cognitive development and decline) was conducted. The review protocol was developed in consultation with experts working across mental health and environmental science. The scoping review included 202 English-language papers, published between 2010 and 2020 (prior to the COVID-19 pandemic), on environmental themes that had not already been the subject of recent systematic reviews; 26 reviews on climate change, flooding, air pollution, and urban green space were additionally considered. Studies largely focused on populations in the USA, China, or Europe and involved limited environmental science input. Environmental science research methods are primarily focused on quantitative approaches utilising secondary datasets or field data. Mental health measurement was dominated by the use of self-report psychometric scales. Measures of environmental states or exposures were often lacking in specificity (e.g., limited to the presence or absence of an environmental state). Based on the scoping review findings and our synthesis of the recent reviews, a research agenda for environmental science's future contribution to mental health scholarship is set out. This includes recommendations to expand the geographical scope and broaden the representation of different environmental science areas, improve measurement of environmental exposure, prioritise experimental and longitudinal research designs, and giving greater consideration to variation between and within communities and the mediating pathways by which environment influences mental health. There is also considerable opportunity to increase interdisciplinarity within the field via the integration of conceptual models, the inclusion of mixed methods and qualitative approaches, as well as further consideration of the socio-political context and the environmental states that can help support good mental health. The findings were used to propose a conceptual model to parse contributions and connections between environmental science and mental health to inform future studies.

Neighbourhood walkability in relation to cognitive functioning in patients with disorders along the heart-brain axis

This study examined associations of neighbourhood walkability with cognitive functioning (i.e., global cognition, memory, language, attention-psychomotor speed, and executive functioning) in participants without or with either heart failure, carotid occlusive disease, or vascular cognitive impairment. Neighbourhood walkability at baseline was positively associated with global cognition and attention-psychomotor speed. These associations were stronger in patients with vascular cognitive impairment. Individuals who live in residential areas with higher walkability levels were less likely to have impairments in language and executive functioning at two-year follow-up. These findings highlight the importance of the built environment for cognitive functioning in healthy and vulnerable groups.

Urban living and chronic diseases in the presence of economic growth: Evidence from a long-term study in southeastern China

High-speed urban development has brought about an increase in per capita income in low- and middle-income countries (LMICs) as well as the high prevalence rate of chronic diseases. Based on a study of chronic diseases from 2011 to 2021 in southeastern China, we used multivariate adjusted logistic regression method to analyze the effect of urban living on the incidence of typical chronic diseases and the trend of such effect with the improvement of public healthcare system. We adopted potential mediating risk factors of urban lifestyles including body mass index (BMI), frequency of dining out, sedentary time, and psychological distress in the adjusted estimation. Baseline results indicate a positive relationship between living in urban areas and the prevalence of type 2 diabetes, hyperlipidemia, and hypertension. Regarding the mediating factors, psychological distress had the highest positive coefficient (Cr) on type 2 diabetes, hyperlipidemia, and hypertension (Cr: 0.4881-0.7084), followed by BMI (Cr: 0.1042-0.1617) and frequency of dining out (Cr: 0.0311-0.0478), and finally, sedentary time (Cr: 0.0103-0.0147). However, regression results on the follow-up survey reveal that trend in the impact of living in urban areas on chronic disease diminished as the level of the healthcare system improved. Additionally, urban living was more positively correlated with the incidence of metabolic disease than with the incidence of cardiovascular disease and cancer. Our findings provide empirical evidence that future urban health planning in LMICs should pay sustained attention to upgrading the level of public health infrastructure covering urban residents as well as rural-to-urban migrants, constructing a long-term dynamic system of chronic disease prevention and control, and regularly monitoring the mental health problems of residents in order to interrupt the process of urban chronic disease prevalence in an early stage.

Air pollution, depressive and anxiety disorders, and brain effects: A systematic review

Accumulating data suggest that air pollution increases the risk of internalizing psychopathology, including anxiety and depressive disorders. Moreover, the link between air pollution and poor mental health may relate to neurostructural and neurofunctional changes. We systematically reviewed the MEDLINE database in September 2021 for original articles reporting effects of air pollution on 1) internalizing symptoms and behaviors (anxiety or depression) and 2) frontolimbic brain regions (i.e., hippocampus, amygdala, prefrontal cortex). One hundred and eleven articles on mental health (76% human, 24% animals) and 92 on brain structure and function (11% human, 86% animals) were identified. For literature search 1, the most common pollutants examined were PM2.5 (64.9%), NO2 (37.8%), and PM10 (33.3%). For literature search 2, the most common pollutants examined were PM2.5 (32.6%), O3 (26.1%) and Diesel Exhaust Particles (DEP) (26.1%). The majority of studies (73%) reported higher internalizing symptoms and behaviors with higher air pollution exposure. Air pollution was consistently associated (95% of articles reported significant findings) with neurostructural and neurofunctional effects (e.g., increased inflammation and oxidative stress, changes to neurotransmitters and neuromodulators and their metabolites) within multiple brain regions (24% of articles), or within the hippocampus (66%), PFC (7%), and amygdala (1%). For both literature searches, the most studied exposure time frames were adulthood (48% and 59% for literature searches 1 and 2, respectively) and the prenatal period (26% and 27% for literature searches 1 and 2, respectively). Forty-three percent and 29% of studies assessed more than one exposure window in literature search 1 and 2, respectively. The extant literature suggests that air pollution is associated with increased depressive and anxiety symptoms and behaviors, and alterations in brain regions implicated in risk of psychopathology. However, there are several gaps in the literature, including: limited studies examining the neural consequences of air pollution in humans. Further, a comprehensive developmental approach is needed to examine windows of susceptibility to exposure and track the emergence of psychopathology following air pollution exposure.

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.

Worries about inadequate medical treatment in case of a COVID-19 infection: the role of social inequalities, COVID-19 prevalence and healthcare infrastructure

Background

This study investigates individual and regional determinants of worries about inadequate medical treatment in case of a COVID-19 infection, an important indicator of mental wellbeing in pandemic times as it potentially affects the compliance with mitigation measures and the willingness to get vaccinated. The analyses shed light on the following questions: Are there social inequalities in worries about inadequate medical treatment in case of a COVID-19 infection? What is the role of the regional spread of COVID-19 infections and regional healthcare capacities?

Methods

Based on data derived from the German Socioeconomic Panel (SOEP), a representative sample of the German population aged 18 years and over, we estimated multilevel logistic regression models with individual-level (level 1) and regional-level (level 2) variables. The regional variables of interest were (a) the number of COVID-19 infections, (b) the number of hospital beds as an overall measure of the regional healthcare capacities, and (c) the number of free intensive care units as a measure of the actual capacities for treating patients with severe courses of COVID-19.

Results

Women, older respondents, persons with migrant background and those with a lower socioeconomic status were more likely to report worries about inadequate medical treatment in case of a COVID-19 infection. Moreover, respondents with chronic illness, lower subjective health and those who consider COVID-19 as a threat for their own health were more likely to report worries. In addition, also regional characteristics were relevant. Worries were more common in poorer regions with higher COVID-19 infections and worse health infrastructure as indicated by the number of hospital beds.

Conclusions

The analysis not only indicates that several social groups are more concerned about inadequate medical treatment in case of a COVID-19 infection, but also highlights the need for considering regional-level influences, such as the spread of the virus, poverty rates and healthcare infrastructure, when analyzing the social and health-related consequences of the pandemic.

Anxiety Screening among the General Population of Latvia and Associated Factors

Background and Objectives: The aim of this study was to determine the point prevalence of at least mild anxiety symptoms and symptoms of generalized anxiety disorder in the Latvian general population, and to analyze the associated factors. Materials and Methods: A computer-assisted face-to-face survey was conducted in 2019−2020 with a multistage stratified probability sample of the Latvian general adult population (n = 2687). Anxiety was assessed using the 7-item Generalized Anxiety Disorder (GAD-7) scale; a score of ≥5 was defined as indicating the presence of mild symptoms of anxiety, and a score of ≥10 as the cutoff for identifying cases of generalized anxiety disorder. The Patient Health Questionnaire 9 (PHQ-9) and MINI International Neuropsychiatric Interview (M.I.N.I.) modules were used for assessing comorbid conditions. Multinomial logistic regression was conducted. Results: The point prevalence of mild anxiety symptoms was 10.9%. The point prevalence of generalized anxiety disorder symptoms was 3.9%. Higher odds of mild anxiety symptoms were detected in respondents of a young age (vs. 65 y.o. and older, aOR 3.1, p < 0.001), unmarried respondents (vs. married/cohabiting, aOR 1.5, p = 0.02), those living in the capital city (aOR 1.6, p = 0.008) or rural areas (aOR 1.5, p = 0.03) (vs. other towns), respondents with poor self-rated health (vs. good, aOR 2.6, p < 0.001), and diagnosed alcohol use disorder (aOR 1.9, p < 0.001), suicidal behavior (aOR 2.4, p < 0.001), and symptoms of depression (aOR 6.4, p < 0.001) (vs. no such conditions). As for symptoms of generalized anxiety disorder, female sex (vs. males, aOR 2.5, p = 0.003), age below 44 years (vs. 65+, aOR 6.2, p = 0.002), average self-rated health (vs. good, aOR 2.6, p = 0.005), and poor self-rated health (vs. good, aOR 5.3, p < 0.001), together with comorbid suicidal behavior (aOR 6.1, p < 0.001) and symptoms of depression (aOR 43.4, p < 0.001) (vs. no such conditions), increased the odds. Conclusions: Young age, poor self-rated health, and comorbid symptoms of depression and suicidal behavior were significant factors associated with symptoms of both mild anxiety and generalized anxiety disorder. Being unmarried, living in the capital city or rural areas, and alcohol use disorder were associated with mild anxiety symptoms alone. Female sex was associated with generalized anxiety disorder symptoms alone.

Daily space-time activities, multiple environmental exposures, and anxiety symptoms: A cross-sectional mobile phone-based sensing study

BACKGROUND

Few mobility-based studies have investigated the associations between multiple environmental exposures, including social exposures, and mental health.

OBJECTIVE

To assess how exposure to green space, blue space, noise, air pollution, and crowdedness along people's daily mobility paths are associated with anxiety symptoms.

METHODS

358 participants were cross-sectionally tracked with Global Positioning System (GPS)-enabled mobile phones. Anxiety symptoms were measured at baseline using the Generalized Anxiety Disorder-7 (GAD-7) questionnaire. Green space, blue space, noise, and air pollution were assessed based on concentric buffers of 50 m and 100 m around each GPS point. Crowdedness was measured by the number of nearby Bluetooth-enabled devices detected along the mobility paths. Multiple linear regressions with full covariate adjustment were fitted to examine anxiety-environmental exposures associations. Random forest models were applied to explore possible nonlinear associations and exposure interactions.

RESULTS

Regression results showed null linear associations between GAD-7 scores and environmental exposures. Random forest models indicated that GAD-7-environment associations varied nonlinearly with exposure levels. We found a negative association between green space and GAD-7 scores only for participants with moderate green space exposure. We observed a positive association between GAD-7 scores and noise levels above 60 dB and air pollution concentrations above 17.2 μg m^-3. Crowdedness was positively associated with GAD-7 scores, but exposure-response functions flattened out with pronounced crowdedness of >7.5. Blue space tended to be positively associated with GAD-7 scores. Random forest models ranked environmental exposures as more important to explain GAD-7 scores than linear models.

CONCLUSIONS

Our findings indicate possible nonlinear associations between mobility-based environmental exposures and anxiety symptoms. More studies are needed to obtain an in-depth understanding of underlying anxiety-environment mechanisms during daily life.

High-Precision Dynamic Traffic Noise Mapping Based on Road Surveillance Video

High-precision dynamic traffic noise maps can describe the spatial and temporal distributions of noise and are necessary for actual noise prevention. Existing monitoring point-based methods suffer from limited spatial adaptability, and prediction model-based methods are limited by the requirements for traffic and environmental parameter specifications. Road surveillance video data are effective for computing and analyzing dynamic traffic-related factors, such as traffic flow, vehicle speed and vehicle type, and environmental factors, such as road material, weather and vegetation. Here, we propose a road surveillance video-based method for high-precision dynamic traffic noise mapping. First, it identifies dynamic traffic elements and environmental elements from videos. Then, elements are converted from image coordinates to geographic coordinates by video calibration. Finally, we formalize a dynamic noise mapping model at the lane level. In an actual case analysis, the average error is 1.53 dBA. As surveillance video already has a high coverage rate in most cities, this method can be deployed to entire cities if needed.

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.

The association between community-level socioeconomic status and depressive symptoms among middle-aged and older adults in China

BACKGROUND

There was little evidence concerning the association of community socioeconomic status (SES) and the cross-level interaction between community- and individual-level SES with depressive symptoms in China. This study aimed to investigate the association of community-level SES with depressive symptoms among Chinese middle-aged and older people and to examine whether individual-level SES moderates this relationship.

METHODS

Using data from the China Health and Retirement Longitudinal 2011-2018 Study, the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10) short form was used to measure depressive symptoms in 35,546 Chinese individuals aged 45 years and older. Community SES was calculated as a sum of z scores of the average years of schooling and household income per capita, which were derived by aggregating the individual measures to the community level. Two-level hierarchical linear regression was used.

RESULTS

Community SES was negatively related to CES-D-10 scores (coef=-0.438). A 1-SD increase in individual SES was associated with lower CES-D-10 scores (coef=-0.490). The cross-level interaction on individual- and community-level SES was significantly associated with depressive symptoms, indicating that with the increase of individual-level SES, the effect of community-level SES on depression decreases. Stratified analyses observed robust associations of community SES with CES-D scores between urban and rural residents.

CONCLUSIONS

This study showed that individuals who live in lower-SES communities had more severe depressive symptoms, particularly individuals with low SES. Additional attention should be given to the community socioeconomic context of middle-aged and older adults with lower SES, which may be helpful to reduce SES inequalities in depressive symptoms in China.

The association between community-level socioeconomic status and cognitive function among Chinese middle-aged and older adults: a study based on the China Health and Retirement Longitudinal Study (CHARLS)

Background

Although numerous studies focused on the relationship between area socioeconomic status (SES) and health, only a few of them investigated how community-level SES was linked to late-life cognitive function as well as the potential pathways underlying this association, and very few of them focused on the context of China. This study examined how community-level SES was linked to cognitive function and the potential pathways underlying this association among middle-aged and older adults in China.

Methods

Data was drawn from the waves 1–4 of China Health and Retirement Longitudinal Study. We measured cognitive function with the components of the Telephone Interview of Cognitive Status battery. Community-level SES was derived from a sum of z scores of the percentage of the illiterate and the per-capita net income status within communities. We adopted two-level hierarchical linear regression models to explore the associations between community-level SES and cognitive function. A multilevel mediation analysis with structural equation modeling was undertaken to disaggregate the direct and indirect pathways of the associations.

Results

Higher community-level SES was associated with better cognitive function (β = 0.562, 95% CI = 0.390, 0.734), and this significant association was only present in rural participants, not in urban participants. Furthermore, we discovered the mediating effects of outdoor exercise facilities within communities (β = 0.023, 95% CI = 0.000, 0.056) and individual-level SES (β = 0.108, 95% CI = 0.057, 0.156) to explain the relationship between community SES and cognitive function.

Conclusions

These findings highlight the importance of community environmental interventions in maintaining individuals’ cognitive health in China, especially for older adults. Our results provided solid empirical evidence for reducing mental health inequalities in China, and suggested that developing an aging-friendly environment and properly distributing community resources are important to improve cognitive function of older adults.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02946-3.

Perceived neighborhood and fall history among community-dwelling older adults living in a large Brazilian urban area: a multilevel approach

Few studies have examined the neighborhood features related to falls in the older population in low-and-middle-income countries, including Brazil. This study aimed to evaluate if perceived neighborhood features are related to falls among older Brazilian adults living in a large urban area. This cross-sectional study was conducted using data from 834 participants (≥60 years) from a multistage household survey in Belo Horizonte, Brazil. The association between fall history in the previous year and perceived neighborhood features (quality of services, physical and social disorder, and safety) was examined using multilevel logistic regression. The fall prevalence was 13.6%. Older adults living in neighborhoods with a higher physical disorder were more likely to report fall in the previous year, even after controlling for demographic, clinical and social variables (OR = 2.59; 95% CI = 1.14-5.87). The other neighborhood features investigated were not associated with a fall history. Our findings suggest that improving the physical environment represents an important strategy to prevent falls in the Brazilian urban older population.

Expanding the environmental scope: an environment-wide association study for mental well-being

BACKGROUND

Identifying modifiable factors associated with well-being is of increased interest for public policy guidance. Developments in record linkage make it possible to identify what contributes to well-being from a myriad of factors. To this end, we link two large-scale data resources; the Geoscience and Health Cohort Consortium, a collection of geo-data, and the Netherlands Twin Register, which holds population-based well-being data.

OBJECTIVE

We perform an Environment-Wide Association Study (EnWAS), where we examine 139 neighbourhood-level environmental exposures in relation to well-being.

METHODS

First, we performed a generalized estimation equation regression (N = 11,975) to test for the effects of environmental exposures on well-being. Second, to account for multicollinearity amongst exposures, we performed principal component regression. Finally, using a genetically informative design, we examined whether environmental exposure is driven by genetic predisposition for well-being.

RESULTS

We identified 21 environmental factors that were associated with well-being in the domains: housing stock, income, core neighbourhood characteristics, livability, and socioeconomic status. Of these associations, socioeconomic status and safety are indicated as the most important factors to explain differences in well-being. No evidence of gene-environment correlation was found.

SIGNIFICANCE

These observed associations, especially neighbourhood safety, could be informative for policy makers and provide public policy guidance to improve well-being. Our results show that linking databases is a fruitful exercise to identify determinants of mental health that would remain unknown by a more unilateral approach.

The short- and long-term effects of the Great Recession on late-life depression in Europe: The role of area deprivation

INTRODUCTION

The prevalence of depression increases in times of economic crises. Less is known about whether people living in advantaged or disadvantaged areas suffer equally from negative effects of crisis.

OBJECTIVE

To explore the role of area deprivation on the short- and long-term effects of the Great Recession in Europe on late-life depression.

METHODS

Individual panel data from Austria, Belgium, Denmark, France, Germany, Italy, Spain, Sweden, Switzerland of the SHARE (age 50+, n = 6866) between 2004 and 2017 were used. Late-life depression (LLD) was measured by the EURO-D scale (4+ symptoms). Area deprivation was assessed by a country-specific z-standardized scale measuring perceived access to various services and quality of the social and built environment. Quarterly country-level GDP and yearly unemployment data were explored to define country-specific durations of the Great Recession. Individual fixed effects panel regressions were estimated controlling for time-varying socioeconomic and health-related confounders.

RESULTS

Prevalence and incidence of late-life depression was generally higher in deprived than in non-deprived areas, and these differences in prevalence and incidence increased during the Great Recession. Regressions showed that the Great Recession was related to a 23% higher long-term risk of late-life depression (OR: 1.23, CI: 1.05-1.44) for all study participants. In the short-term of the Great Recession, people from deprived areas had a 22% higher risk of late-life depression (OR: 1.22, CI: 1.02-1.46) than people from non-deprived areas.

CONCLUSION

The findings suggest that older adults exposed to adverse area determinants suffer more from the negative short-term effects of a severe economic crisis on depression and mental health inequalities may have increased between people living in deprived versus non-deprived areas. This potential increase in mental health inequalities warrants particular attention for those people living in deprived areas.

Effects of ambient air pollution on psychological stress and anxiety disorder: a systematic review and meta-analysis of epidemiological evidence

OBJECTIVES

Ambient air pollution (AAP) is an important risk factor for increased mental health morbidity. Studies have highlighted the effect of AAP on psychological stress and anxiety disorder. However, existing evidence regarding this is largely equivocal. This systematic review with meta-analysis aims to synthesize published evidence to calculate the pooled estimate of the effect of AAP on psychological stress and anxiety disorder.

CONTENT

A systematic bibliographic search was undertaken using PubMed, JGateplus, Google Scholar, and Cochrane Library for observational human studies published in English till 31st March 2020 reporting the effect of AAP on psychological stress and anxiety disorder. Study quality was assessed using the Joanna Briggs Institute critical appraisal tools. Meta-analysis was performed adopting a random-effects model using Meta-XL. Of 412 articles retrieved, a total of 30 articles [AAP and anxiety disorders, (n=17, 57%); AAP and psychological stress, (n=9, 30%) and AAP and both psychological stress and anxiety disorders, (n=4, 13%)] fulfilled the inclusion criteria covering a total population of 973,725 individuals. The pooled estimate (OR) of the effects of PM₁₀ on psychological stress was 1.03 [(95% CI: 1.00, 1.05) (p=0.17, I ²=41%)]. The pooled estimate of the effects of NO₂ and PM₁₀ on anxiety disorder was 0.93 [(95% CI: 0.89, 0.97) (p=0.91, I ²=0%)] and 0.88 [(95% CI: 0.78, 0.98) (p=0.01, I ²=59%)] respectively. The pooled estimate of the effects of PM_2.5 on anxiety Disorder was 0.88 [(95% CI: 0.72, 1.06) (p=0.00, I ²=80%)].

SUMMARY AND OUTLOOK

The present study provides the most updated pooled estimate of the effect of AAP on psychological stress and anxiety disorder. Future studies should focus on longitudinal studies conducted in LIC and LMIC countries using uniform and standardized criteria for exposure and outcome assessment as well as robust adjustment for confounders to minimize methodological heterogeneity resulting in reliable and comparable estimation of environmental mental health burden.

Interactive Effects of Neighborhood Safety and Screen Time on Adolescent Internalizing Symptoms

OBJECTIVE

Perceptions of less neighborhood safety and higher levels of screen time are independently linked to adolescent anxiety and depression. Furthermore, residing in a neighborhood perceived as less safe is associated with engaging in higher levels of screen time. Screen time may act as a potential mechanism by which the effects of neighborhood safety on internalizing symptoms differ. Yet, research has not investigated whether the relationship between neighborhood safety and psychosocial adjustment varies at high and low levels of screen time. Therefore, this study examined the interaction between perceived neighborhood safety and screen time on adolescent internalizing symptoms (i.e., anxiety and depressive symptoms).

METHOD

A total of 184 adolescents (53% female; mean age = 17.09, SD = 1.07) were recruited from an ongoing longitudinal study of adolescent drivers. Participants reported their perceptions of neighborhood safety, screen use, anxiety and depressive symptoms, and demographic characteristics. The independent and interactive contributions of neighborhood safety and screen time predicting anxiety and depressive symptoms in adolescents were tested with hierarchical linear regressions.

RESULTS

Perceptions of less neighborhood safety and higher levels of screen time each uniquely predicted adolescent anxiety and depressive symptoms. The relationship between living in a neighborhood perceived as less safe and anxiety symptoms was stronger for youth with high levels of screen time.

CONCLUSION

The findings suggest that youth residing in less safe neighborhoods may have higher levels of anxiety symptoms, and this anxiety symptomology is higher at high levels of screen time.

Predictors for successful psychotherapy: Does migration status matter?

Background

We investigated, if migration status, and additional sociodemographic and clinical factors, are associated with somatization and depressiveness at admission and with remission after inpatient psychotherapy.

Methods

Multiple linear and binary logistic regression analyses were used to identify predictors for severity of somatoform and depressive symptoms at admission of inpatient psychotherapy (T0), and for remission after inpatient psychotherapy (T1). We tested the association between symptoms concerning somatization (PHQ-15: Patient-Health-Questionnaire Somatization Module) and depression (PHQ-9: Patient-Health-Questionnaire Depression Module) and several sociodemographic and clinical factors in 263 patients at admission. For remission after treatment, we additionally included severity of symptoms at admission, number of diagnoses and duration of treatment in the regression models. Remission after treatment was defined as response plus a post value of less than 10 points in the respective questionnaire. Clinical relevance was interpreted using effect sizes (regression coefficients, Odds Ratio (OR)) and Confidence Intervals (CI).

Findings

Significant and clinically relevant predictors for high symptom severity at T0 were lower education (β = -0.13, p = 0.04), pretreatment(s) (β = 0.205, p = 0.002) and migration status (β = 0.139, p = 0.023) for somatization, and potential clinically relevant predictors (|β|>0.1) for depression were living alone (β = -0.116, p = 0.083), pretreatment(s) (β = 0.118, p = 0.071) and migration status (β = 0.113, p = 0.069). At T1 patients with pretreatment(s) (OR = 0.284 [95% CI: 0.144, 0.560], p<0.001) and multiple diagnoses (OR = 0.678 [95% CI: 0.472, 0.973], p = 0.035) were significantly and clinically relevant less likely to show a remission of depressive symptoms. In addition, a potentially clinically meaningful effect of migration status on remission of depressive symptoms (OR = 0.562 [95% CI: 0.264, 1.198], p = 0.136) cannot be ruled out. For somatoform symptoms pretreatment(s) (OR = 0.403, [95% CI: 0.156, 1.041], p = 0.061) and education (OR = 1.603, [95% CI: 0.670, 3.839], p = 0.289) may be regarded as clinically relevant predictors for remission.

Conclusion

The results of our study suggest that migration status has a clinically relevant influence on severity of somatoform and depressive symptoms at admission. Clinical relevance of migration status can also be assumed regarding the remission of depression. Migration status and further factors affecting the effectiveness of the treatment should be analyzed in future research among larger samples with sufficient power to replicate these findings.

The urban public realm and adolescent mental health and wellbeing: A systematic review

Adolescent mental health is becoming a critical concern. Mental illness rates are rising and many psychological disorders first present symptoms during teenage years. Studies consistently show associations between the built environment and mental health, including internalising mental health disorders in adults, but the evidence for adolescents is less robust and few studies attempt to isolate causality. This review examines the relationship between the urban public realm and adolescent mental health and wellbeing. Our search yielded 24 studies for inclusion. We undertook qualitative synthesis of 20 cross-sectional studies and conducted a separate quality analysis of four longitudinal studies. Greenspace and neighbourhood quality are associated with adolescent mental health and wellbeing although this may be due more to residual confounding, selection effects and same-source bias than evidence for a causal effect. Furthermore, the few longitudinal studies that seek to test causality remain prone to these biases. Overall, we find little evidence of an effect of the urban public realm on adolescent mental health and wellbeing, which, we argue, reflects the difficulty of researching complex pathways between environments and health and highlights a challenge to the field. To address this challenge, we propose a research agenda that prioritises more and better data drawn from diverse study designs, and more and better theories developed from diverse epistemologies.

Associations of changes in neighbourhood walkability with changes in walking activity in older adults: a fixed effects analysis

Background

Supporting older adults to engage in physically active lifestyles requires supporting environments. Walkable environments may increase walking activity in older adults, but evidence for this subgroup is scarce, and longitudinal studies are lacking. This study therefore examined whether changes in neighbourhood walkability were associated with changes in walking activity in older adults, and whether this association differed by individual-level characteristics and by contextual conditions beyond the built environment.

Methods

Data from 668 participants (57.8–93.4 years at baseline) across three waves (2005/06, 2008/09 and 2011/12) of the Longitudinal Aging Study Amsterdam (LASA) were used. These individuals did not relocate during follow-up. Self-reported outdoor walking activity in minutes per week was assessed using the LASA Physical Activity Questionnaire. Composite exposure measures of neighbourhood walkability (range: 0 (low)-100 (high)) within 500-m Euclidean buffer zones around each participant’s residential address were constructed by combining objectively measured high-resolution Geographic Information System data on population density, retail and service destination density, land use mix, street connectivity, green space density, and sidewalk density. Fixed effects linear regression analyses were applied, adjusted for relevant time-varying confounders.

Results

Changes in neighbourhood walkability were not statistically significantly associated with changes in walking activity in older adults (β_500m = − 0.99, 95% CI = -6.17–4.20). The association of changes in neighbourhood walkability with changes in walking activity did not differ by any of the individual-level characteristics (i.e., age, sex, educational level, cognitive impairment, mobility disability, and season) and area-level characteristics (i.e., road traffic noise, air pollution, and socioeconomic status).

Conclusions

This study did not show evidence for an association between changes in neighbourhood walkability and changes in walking activity in older adults. If neighbourhood walkability and walking activity are causally linked, then changes in neighbourhood walkability between 2005/06 and 2011/12 might have been not substantial enough to produce meaningful changes in walking activity in older adults.

Urbanization level and neighborhood deprivation, not COVID-19 case numbers by residence area, are associated with severe psychological distress and new-onset suicidal ideation during the COVID-19 pandemic

BACKGROUND

Recent studies indicate an urgent need to take action against mental health issues during the COVID-19 pandemic. However, the association between larger-scale environmental factors such as living conditions and mental health problems during the pandemic is currently unknown.

METHODS

A nationwide, cross-sectional internet survey was conducted in Japan between August and September 2020 to examine the association between urbanization level and neighborhood deprivation as living conditions and COVID-19 case numbers by prefecture. Prevalence ratios (PRs) for severe psychological distress, suicidal ideation, and new-onset suicidal ideation during the pandemic were adjusted for potential confounders.

RESULTS

Among 24,819 responses analyzed, the prevalence of mental health problems was 9.2% for severe psychological distress and 3.6% for new-onset suicidal ideation. PRs for severe psychological distress were significantly associated with higher urbanization level (highest PR = 1.30, 95% CI = 1.08-1.56). PRs for new-onset suicidal ideation were significantly associated with higher urbanization level (highest PR = 1.83, 95% CI = 1.37-2.45) and greater neighborhood deprivation (highest PR = 1.35, 95% CI = 1.06-1.72). Severe psychological distress and new-onset suicidal ideation were significantly more prevalent when there was higher urbanization plus lower neighborhood deprivation (PR = 1.34 [1.15-1.56], and 1.57 [1.22-2.03], respectively).

CONCLUSION

These findings suggest that it is not the number of COVID-19 cases by residence area but higher urbanization level and greater neighborhood deprivation (lower neighborhood-level socioeconomic status) that are associated with severe psychological distress and new-onset suicidal ideation during the pandemic. These findings differ in part from evidence obtained before the pandemic.

Association between neighbourhood characteristics and antidepressant use at older ages: a register-based study of urban areas in three European countries

BACKGROUND

Research evidence on the association between neighbourhood characteristics and individual mental health at older ages is inconsistent, possibly due to heterogeneity in the measurement of mental-health outcomes, neighbourhood characteristics and confounders. Register-based data enabled us to avoid these problems in this longitudinal study on the associations between socioeconomic and physical neighbourhood characteristics and individual antidepressant use in three national contexts.

METHODS

We used register-based longitudinal data on the population aged 50+ from Turin (Italy), Stockholm (Sweden), and the nine largest cities in Finland linked to satellite-based land-cover data. This included individual-level information on sociodemographic factors and antidepressant use, and on neighbourhood socioeconomic characteristics, levels of urbanicity, green space and land-use mix (LUM). We assessed individual-level antidepressant use over 6 years in 2001-2017 using mixed-effects logistic regression.

RESULTS

A higher neighbourhood proportion of low-educated individuals predicted lower odds for antidepressant use in Turin and Stockholm when individual-level sociodemographic factors were controlled for. Urbanicity predicted increased antidepressant use in Stockholm (OR=1.02; 95% CI 1.01 to 1.03) together with more LUM (OR=1.03; 1.01-1.05) and population density (OR=1.08; 1.05-1.10). The two latter characteristics also predicted increased antidepressant use in the Finnish cities (OR=1.05; 1.02-1.08 and OR=1.14; 1.02-1.28, respectively). After accounting for all studied neighbourhood and individual characteristics of the residents, the neighbourhoods still varied by odds of antidepressant use.

CONCLUSIONS

Overall, the associations of neighbourhood socioeconomic and physical characteristics with older people's antidepressant use were small and inconsistent. However, we found modest evidence that dense physical urban environments predicted higher antidepressant use among older people in Stockholm and the Finnish cities.

Trends in mental health inequalities in urban Canada

OBJECTIVES

Canadians do not all enjoy equal levels of health. The presence of income-related health inequalities has been well established in Canada, but there is a lack of consistent reporting of mental health inequalities in Canada's largest cities. This study reports the prevalence and inequalities in mental health outcomes at the city, provincial, and national levels over time.

METHODS

Self-reported poor mental health, life stress, and physician-diagnosed self-reported mood and anxiety disorder from the Canadian Community Health Survey were pooled over five-year intervals and combined with neighbourhood income information from the Canadian Census. First, prevalence rates were calculated for each interval at the neighbourhood level for urban communities. Second, the distributions of these neighbourhood rates were summarized at the city level and for Canada as a whole using overall prevalence rates and concentration indices of inequality. Finally, trends in these city- and country-level outcomes were also explored.

RESULTS

At the national level, starting from 2001 to 2005, the prevalence of poor mental health (27.9%), mood disorder (7.3%), and anxiety disorder (6.8%) had significantly increased by 2011-2015. Inequalities were present in 2001-2005 and worsened over time. The prevalence rate at the national level of life stress was 66.6% in 2001-2005 and decreased over time.

CONCLUSION

The large and increasing values of inequalities and the difference in prevalence rates and inequalities in cities highlight the necessity for mental disorder-specific data and for city-level analysis of inequalities. The next steps in reducing inequalities involve deconstructing the health inequalities, and continued monitoring.

Comparison of Depressive Symptoms and Its Influencing Factors among the Elderly in Urban and Rural Areas: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Depression amongst the elderly population is a worldwide public health problem, especially in China. Affected by the urban-rural dual structure, depressive symptoms of the elderly in urban and rural areas are significantly different. In order to compare depressive symptoms and its influencing factors among the elderly in urban and rural areas, we used the data from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS). A total of 7690 participants at age 60 or older were included in this study. The results showed that there was a significant difference in the prevalence estimate of depression between urban and rural elderly (χ2 = 10.9.76, p < 0.001). The prevalence of depression among rural elderly was significantly higher than that of urban elderly (OR-unadjusted = 1.88, 95% CI: 1.67 to 2.12). After adjusting for gender, age, marital status, education level, minorities, religious belief, self-reported health, duration of sleep, life satisfaction, chronic disease, social activities and having income or not, the prevalence of depression in rural elderly is 1.52 times (OR = 1.52, 95% CI: 1.32 to 1.76) than that of urban elderly. Gender, education level, self-reported health, duration of sleep, chronic diseases were associated with depression in both urban and rural areas. In addition, social activities were connected with depression in urban areas, while minorities, marital status and having income or not were influencing factors of depression among the rural elderly. The interaction analysis showed that the interaction between marital status, social activities and urban and rural sources was statistically significant (divorced: coefficient was 1.567, p < 0.05; social activities: coefficient was 0.340, p < 0.05), while gender, education level, minorities, self-reported health, duration of sleep, life satisfaction, chronic disease, social activities having income or not and urban and rural sources have no interaction (p > 0.05). Thus, it is necessary to propose targeted and precise intervention strategies to prevent depression after accurately identifying the factors' effects.

Short- and long-term exposure to air pollution and lack of sunlight are associated with an increased risk of depression: A nested case-control study using meteorological data and national sample cohort data

Previous studies have suggested an increased risk of depression related to air pollutants. This study investigated the relationship of air pollutant exposure and meteorological factors with depression. The Korean National Health Insurance Service-Health Screening Cohort from 2002 to 2013 was analyzed. In total, 25,589 depression participants were 1:4 matched with 102,356 control participants for age, sex, income, and region of residence. Depression was defined based on a diagnosis (ICD-10: F31-33) by a psychiatric physician. Meteorological factors and air pollutants including sulfur dioxide (SO₂) (ppm), nitrogen dioxide (NO₂) (ppm), ozone (O₃) (ppm), carbon monoxide (CO) (ppm), and particulate matter with an aerodynamic diameter <10 μm (PM₁₀) (μg/m³) during the 30 days and 365 days before the index date were analyzed for associations with depression using conditional logistic regression. Subgroup analyses were performed according to age, sex, income, and region of residence. The odds ratios (ORs) for depression were 1.05 (95% CI = 1.02-1.08) at 365 days for 1 h less of sunshine. The ORs for depression were 1.02 (95% CI = 1.01-1.03) and 1.03 (95% CI = 1.00-1.05) at 30 days and 365 days for PM₁₀ (10 μg/m³), respectively. The ORs for depression were 1.18 (95% CI = 1.04-1.35) and 1.25 (95% CI = 1.07-1.47) at 30 days and 365 days for CO (ppm), respectively. In the subgroup analyses, the overall results were consistent. However, statistical significance diminished in the younger, high-income, and urban resident subgroups. Both short- and long-term exposure to PM₁₀ and CO and a reduced duration of sunshine were related to an increased risk of depression.

Does Young Adults' Neighborhood Environment Affect Their Depressive Mood? Insights from the 2019 Korean Community Health Survey

The rates of depression among young adults have been increasing in high-income countries and have emerged as a social problem in South Koreans aged 19–34. However, the literature is unclear on whether the neighborhood environment that young adults live in affects the onset and severity of their depressive symptoms. This study analyzed data from the 2019 Korean Community Health Survey (KCHS) using the Tobit model to identify the effect of the neighborhood environment on young adults’ depressive moods. Controlling for other corresponding factors, young adults’ neighborhood environment satisfaction affected their depression, and natural environment satisfaction (32.5%), safety level satisfaction (31.0%), social overhead capital (SOC), environment satisfaction (30.2%), trust between neighbors satisfaction (20.1%), and public transportation environmental satisfaction (12.2%) affected young adults’ depressive moods. Of these, natural environment satisfaction (32.5%), safety level environment satisfaction (31.0%), and SOC environment satisfaction (30.2%) affected young adults’ depressive mood to a similar extent. This implies that many young adults in South Korea live in inadequate neighborhood conditions. This research contributes to the literature by identifying the specific environmental factors that affect young adults’ depressive moods.

Introduction to Environmental Harmful Factors

In this Chapter, we systematically and comprehensively described various environmental harmful factors. They were classified into four aspects: physical factors, chemical factors, biological factors, and physiological and psychological stress factors. Their classification, modes of presence, toxicity and carcinogenicity, routes of exposure to human and toxic effects on the female reproductive health were introduced. It is expected that the exposure routes could be controlled and eliminated, and the pathogenic mechanism of environmental harmful factors should be investigated and explained to protect female reproductive health.

Residential segregation, neighborhood violence and disorder, and inequalities in anxiety among Jewish and Palestinian-Arab perinatal women in Israel

BACKGROUND

Residential segregation can foster health inequality mechanisms by increasing stress related to neighborhood violence and disorder.

AIMS

We studied the association between neighborhood violence and disorder and inequalities in anxiety between two groups of perinatal Israeli women (Jewish, Palestinian-Arab) living in ethno-nationally segregated neighborhoods, and explored the influence of neighborhood characteristics; social support and chronic stress to this inequality.

METHODS

We linked survey data on neighborhood violence and disorder, neighborhood social characteristics (collective efficacy, social capital and social support) and aggregate discrimination to neighborhood SES census data. The survey data was obtained from the "Family Relations, Violence and Health" study (2014-2015) and included a stratified national sample of women (Palestinian-Arab = 436, Jewish = 965) residing in 63 segregated neighborhoods. We conducted multi-variable logistic regression analysis for anxiety (measured based on State-trait Anxiety Inventory) using generalized estimating equation (GEE) to estimate odds ratios of the association with neighborhood violence and disorder (total score for 10 problems) while considering neighborhood characteristics (SES; social characteristics; aggregate discrimination), social support and chronic stress in different models for the total sample, and separately for Palestinian-Arab and Jewish women.

RESULTS

Palestinian-Arab women had higher anxiety (60.5% vs. 42.1%, respectively) and higher severity of neighborhood violence and disorder (49.5% vs. 16.2%, respectively) compared to Jewish women. After considering individual and neighborhood variables, adjusted odds ratio (AOR) and 95% confidence intervals (CI) = 1.63, 1.04-2.56. The association between neighborhood violence and disorder and anxiety was significant for low vs. no problems in the final model for the total sample (AOR, 95%CI = 1.28, 1.00-1.64). Similarly, significant association was found only for low severity vs. no problems for Jewish women (1.40, 1.07-1.86). While among Palestinian-Arab women the association between neighborhood violence and disorder and anxiety rendered insignificant in the final model. Neighborhood social cohesion and social support were protective factors from anxiety in both groups, high neighborhood SES was protective factor only among Jewish women, and neighborhood aggregate discrimination was a risk factor only in Palestinian-Arab women.

CONCLUSIONS

Inequalities in anxiety related to neighborhood violence and disorder in ethno-national perinatal groups of women likely reflect residential segregation. Policies entrenching segregation might have affected neighborhood mechanisms (SES inequalities, aggregate discrimination and low social cohesion) that lead to higher stress and ethno-national inequalities in anxiety among perinatal women.

Transportation noise exposure and anxiety: A systematic review and meta-analysis

BACKGROUND

Exposure to transportation noise is hypothesized to contribute to anxiety, but consistent associations have not been established.

OBJECTIVE

To provide a comprehensive synthesis of the literature by examining associations between traffic-related noise (i.e., road traffic noise, railway noise, aircraft noise and mixed traffic noise) and anxiety.

METHODS

We systematically searched Web of Science, Scopus, Embase, PubMed, and PsycINFO for English-language observational studies published up to February 2020 reporting on the traffic noise-anxiety association. We appraised the risk of bias using an assessment tool and the quality of evidence following established guidelines. A random-effects meta-analysis was performed for pooled and separated traffic-related noise sources.

RESULTS

Of the 3575 studies identified, 11 fulfilled the inclusion criteria and 9 studies were appropriate for meta-analysis. For the pooled overall effect size between transport noise and anxiety, we found 9% higher odds of anxiety associated with a 10 dB(A) increase in day-evening-night noise level (L_den), with moderate heterogeneity (OR = 1.09, 95% CI: [0.97; 1.23], I² = 70%). The association was more likely to be significant with more severe anxiety (OR = 1.08, 95% CI: [1.01; 1.15], I² = 48%). Sub-group analysis revealed that the effects of different noise sources on anxiety were inconsistent and insignificant. The quality of evidence was rated as very low to low.

CONCLUSIONS

Our findings support the hypothesis of an association between traffic noise and more severe anxiety. More high-quality studies are needed to confirm associations between different noise types and anxiety, as well as to better understand underlying mechanisms.