Air pollution exposure and depression: A comprehensive updated systematic review and meta-analysis

PM2.5 exposure modifies the association of physical activity with depressive symptoms and glaucoma in middle aged and elderly Chinese

It remains unclear that trade-off between the benefits of regular physical activity (PA) and the potentially harmful effects of exposure to PM2.5 (particulate matter with aerodynamic diameter < 2.5 μm) in highly polluted regions. Therefore, we aimed to investigate the modification of PM2.5 on the associations of PA volume and intensity with depressive symptoms and glaucoma in individuals with or without depressive symptoms. Data of this study was obtained from the China Health and Retirement Longitudinal Survey (CHARLS) implemented during 2011 to 2020. PA volume and intensity were measured by a standardized questionnaire; a machine learning prediction model was applied to ascertain the PM2.5 concentrations. Cox proportional hazards regression models were employed to explore associations. A total of 20,930 participants were finally included, with 11,214 analyzed for PA and depressive symptom risk and 16,965 analyzed for PA and glaucoma risk. PA volume or intensity was independent protective factor for incident depressive symptoms, while PM2.5 was independent risk factor for depressive symptoms and glaucoma in participants with or without depressive symptoms. Among participants with low PM2.5 exposure (< 35 micrograms per cubic meter [µg/m3]), PA volume or intensity showed an inverse association with the risk of incident depressive symptoms, but insignificant associations between PA volume or intensity and glaucoma risk were observed in either participants with or without depressive symptoms. Among participants with high PM2.5 exposure (≥ 35 µg/m3), higher PA volume or intensity increased the risks of depressive symptoms and glaucoma. Higher PA level was associated with a reduced risk of depressive symptoms only among participants with low PM2.5 exposure, and higher PA did not decrease the risk of glaucoma regardless of PM2.5 level. Our findings recommend regular PA to prevent depressive symptoms in less polluted regions and reinforce the importance of air quality improvement.

Associations between multiple ambient air pollutants, genetic risk, and incident mental disorders: An interaction study in the UK population

Mental disorders can be triggered by genetic and environmental risk factors. Limited studies have explored the effects of long-term exposure to air pollution on mental disorders, and most of the studies have focused on individual air pollutants. This study aimed to examine the relationship between long-term exposure to multiple air pollutants and incident mental disorders, including depression, anxiety, and schizophrenia, and whether the associations were affected by genetic susceptibility. Participants in the UK Biobank with no history of mental disorders were followed from baseline (2006 to 2010) to October 31st, 2022. Cox regression was applied to evaluate the correlation between PM2.5 absorbance, PM2.5, PM2.5-10, PM10, NO2, and NOx and any or specific mental disorders. Additive and multiplicative scales were used to measure the interaction between air pollution and schizophrenia polygenic risk score (PRS), depression PRS, or anxiety PRS on specific mental diseases. After a median of 13.36 years of follow-up on 252,376 participants, we observed per interquartile increase of PM2.5 absorbance (0.32 per meter), PM2.5 (1.28 μg/m3), NO2 (10.08 μg/m3), and NOx (16.78 μg/m3) were related to a 2-6 % higher risk of incident mental disorders. The HR (95 % CI) of incident mental disorder for the 2nd, 3rd, and 4th quartile of the air pollution score were 1.05 (1.01-1.18), 1.13 (1.09-1.18), and 1.14 (1.09-1.19), respectively, in comparison to the lowest level of the score. Per interquartile increase in the air pollution score was associated with a 6 %, 24 %, 4 %, and 6 % higher risk of incident mental disorders, schizophrenia, depression, and anxiety, respectively. No interaction between air pollution and genetic risk of schizophrenia, depression or anxiety on corresponding incident disorders was observed. These findings emphasize the importance of implementing air pollution control standards to decrease the burden of mental disorders.

Ambient air pollution and depressed mood in the National Longitudinal Study of Adolescent to Adult Health (Add Health) wave 4

Depression is a major contributor to the global burden of disease. There is limited understanding of how environmental exposures may contribute to depression etiology. We used wave 4 of the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine associations between low-level ambient air pollution exposure and depressed mood in a generally healthy population of over 10 000 24-32 year olds. Annual mean PM2.5 levels in the 2008-2009 study were close to the current US standard. In fully adjusted quasibinomial logistic regression models, there were no meaningful associations between IQR increases in air pollutant and change in depressed mood status regardless of specific pollutant or moving average lags. In interaction effects models, an IQR increase in lag day 0-30 PM2.5 resulted in 1.20 (95% CI, 1.02-1.41) times higher likelihood of having depressed mood but only for persons with chronic lung disease (interaction P = .04); the association was null for participants without chronic lung disease (OR, 0.98; 95% CI, 0.91-1.05). Our findings suggest that among persons with a lifetime history of chronic lung disease, greater exposure to even low-level PM2.5, PM10, and sulfate may be associated with modest increases in the likelihood of having depressed mood. This article is part of a Special Collection on Environmental Epidemiology.

Low-Cost PM2.5 Sensor Performance Characteristics against Meteorological Influence in Sub-Saharan Africa: Evidence from the Air Sensor Evaluation and Training Facility for the West Africa Project

Fine particulate matter (PM2.5) pollution represents a major environmental health risk in Africa. The use of low-cost sensors (LCS) for air quality monitoring for policy and civic engagement in sub-Saharan Africa (SSA) has become paramount, as access to traditional reference-grade instruments is still sparse. Yet, studies pertaining to sensor performance under SSA's meteorological conditions and diverse emission sources are limited. Hence, we tested eight low-cost PM2.5 sensors on the market from different manufacturers containing Plantower PMS, Alphasense OPC-N3, and AVO-Sensor sensors by collocating them with the federal equivalent method Teledyne T640 to ascertain data accuracy, reliability, and responsiveness during wet and dry periods. After 6 months of collocation, PM2.5 concentrations from the LCS showed low intrasensor variability in both the wet and dry periods, but high intersensor variability with the Teledyne T640. A strong relationship existed between the LCS and Teledyne T640, with average coefficient of determination (R2) values of 0.7 (range: 05-0.9) and 0.8 (0.64-0.97) in the wet and dry periods, respectively. Larger errors were also associated with LCS data during the dry than the wet period, with the average mean absolute error and root mean squared error, respectively, 4.5 and 5.3 times higher in the dry period. Uncertainties with large errors were also observed with high PM2.5 measured in the wet period, levels that were more common during the dry period typically characterized by long-range transport of PM2.5 pollution. The results show that season significantly affects LCS performance and data quality and that care must be taken during deployment and data usage in SSA, with regular maintenance, particularly in the dry season. Strong collaborative efforts between governmental agencies, industries, and civil society are needed to come up with an effective framework for their application.

Gender Differences in the Association Between Childhood Neighborhood Quality and Depressive Symptoms Trajectory in Middle-Aged and Elderly Chinese: A Seven-Year Longitudinal Study

This study aimed to examine the role of childhood neighborhood quality on trajectories of depressive symptoms throughout later life based on a nationally representative sample, and to explore the role of gender in the association. Linear mixed-effects model analysis was performed to investigate a longitudinal association of childhood neighborhood quality with depressive symptoms. A total of 7,016 participants aged 45 and above were included in this study. Depressive symptoms progression was significantly faster (β [95% confidence interval, CI]: 0.13 [0.01, 0.25]; P = .027) in the low childhood neighborhood quality when compared with the high childhood neighborhood quality. The quality of childhood neighborhood was significantly associated with a change in depressive symptoms over time in females (β [95% CI]: 0.19 [0.02, 0.36]; P = .029) but not in males (β [95% CI]: 0.09 [-0.06, 0.25]; P = .224). Targeted interventions should be developed to prevent depressive symptoms for those vulnerable groups.

Prenatal and Postnatal Ambient Air Pollution and Kawasaki Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Accumulating evidence indicates associations between ambient air pollution and Kawasaki disease (KD), but the results remain inconsistent.

OBJECTIVES

This systematic review and meta-analysis aimed to comprehensively summarize the current evidence on the effects of ambient air pollutants on KD.

METHODS

The PubMed, Web of Science, Embase, and Scopus databases were searched up to January 18, 2025 for studies investigating the effects of ambient air pollution on KD. A fixed- or random-effects model was used to calculate pooled ORs with 95% CIs for an increase in ambient air pollutant concentration of 10 μg/m3. The risk of bias was assessed using the Risk of Bias In Nonrandomized Studies of Exposures tool, and the quality of evidence was assessed by the Grading of Recommendations, Assessment, Development, and Evaluations framework. The protocol was registered with PROSPERO (CRD42024545321).

RESULTS

Thirteen studies with 124,857 participants were included. Seven studies were at high risk of bias. The meta-analysis revealed an increased risk of KD after short-term postnatal exposure to PM2.5 (OR: 1.011; 95% CI: 1.003-1.019; I2 = 0%; high-quality evidence) and PM10 (OR: 1.004; 95% CI: 1.000-1.008; I2 = 38%; high-quality evidence), as well as long-term postnatal exposure to PM2.5 (OR: 1.415; 95% CI: 1.179-1.697; I2 = 41%; high-quality evidence). Prenatal exposure to carbon monoxide, nitric oxide, nitrogen oxides, and sulfur dioxide; short-term postnatal exposure to nitric oxide; and long-term postnatal exposure to carbon monoxide and nitrogen oxides were also associated with KD occurrence.

CONCLUSIONS

Both prenatal and postnatal exposure to several ambient pollutants are associated with the risk of KD.

Ambient ozone exposure and pregnancy complications and adverse birth outcomes: A systematic review and meta-analysis

BACKGROUND

Ambient ozone pollution is becoming a global health threat under global warming. Evidence on the association between ambient ozone and pregnancy complications and adverse birth outcomes has grown enormously. To provide a comprehensive assessment of the evidence, we performed a systematic review and meta-analysis to outline current epidemiological evidence.

METHODS

A systematic literature search up to January 2024 was conducted in PubMed, Web of Science, Cochrane Library and Embase. We included studies that examined the association of ambient ozone exposure with pregnancy complications and birth outcomes. Data extraction was performed independently. All eligible studies were synthesized qualitatively. A random-effects meta-analysis was used to summarize the available effect estimates that calculated with a 10 μg/m3 exposure. We further evaluated whether geographic location, study design, study quality, and exposure assessments explain the heterogeneity. This study protocol was registered with PROSPERO (CRD42024499445).

RESULTS

A total of 10,940 records were originally searched, 65 articles were finally included. Our results showed that first trimester ozone exposure significantly increased the risk of preeclampsia (pooled odds ratio (OR) = 1.018, 95%CI: 1.006-1.030). For birth outcomes, short-term ozone exposure was associated with the risk of preterm birth, with the pooled OR of 1.005 (95%CI: 1.002-1.008) and 1.003(95%CI:1.000-1.005). First trimester and whole pregnancy ozone exposure were associated with the risk of small for gestational age, with the pooled OR of 1.007 (95%CI: 1.002-1.012) and 1.030 (95%CI: 1.010-1.050), respectively.

CONCLUSION

First trimester ozone exposure was associated with adverse pregnancy complications and adverse birth outcomes. Future investigations that considering local climates and population characteristics are warranted to explore the vulnerability at local and regional levels for tailored preventions.

DNA methylation of core clock genes in patients with major depressive disorder: Association with air pollution exposure and disease severity

BACKGROUND

Major Depressive Disorder (MDD) is a multifactorial disease which could be influenced by exposure to air pollution through disruption of sleep-wake cycles and other circadian-related behaviors. Our study aimed to investigate the interplay between air pollution exposure, DNA methylation of core clock genes involved in circadian rhythms, and MDD severity.

METHODS

Four hundred sixteen MDD patients (64 % females) agreed to participate and donated a blood sample to measure DNA methylation of the core clock genes CRY1, PER1, PER2, CLOCK, BMAL1. MDD severity and functioning was assessed using five rating scales. Daily mean estimates of particulate matter with diameter ≤ 2.5 μm (PM2.5) and nitrogen dioxide (NO2) were assigned to study participants based on their residential address, and averaged to estimate different cumulative exposure windows. Multivariate regression models were applied to assess associations between air pollutants and core clock genes methylation and between DNA methylation of those same genes and MDD severity.

RESULTS

PM2.5 exposure in the six months preceding recruitment was associated with CLOCK hypomethylation (β=-0.11, 95 % confidence interval [CI]:0.20; -0.02) and CRY1 hypermethylation (β=0.32, 95 %CI: 0.06; 0.58). All NO2 exposure windows were associated with CRY1 hypermethylation. Increasing methylation of CLOCK was associated with lower MDD severity considering several scales (e.g., Hamilton Depression Rating Scale: β=-7.21, 95 %CI:3.97; -0.44).

CONCLUSIONS

Taken together our findings shed some light on the complex mechanism underlying the pathogenesis of MDD, with a potentially relevant role of the environment and of its impact on epigenetic mechanisms altering the expression of core clock genes.

Association of ambient air pollution exposure with psychological distress in mid and later adulthood: A 26-year prospective cohort study

BACKGROUND

Existing evidence on associations between exposure to air pollution and psychological distress from middle to older age is limited by consideration of short exposure periods, poor historical covariates, exposures and outcomes, and cross-sectional study designs. We aimed to examine this association over a 26-year period between ages 43 and 69.

METHODS

We utilised data from the Medical Research Council National Survey of Health and Development Study (the 1946 British birth cohort). Land-use regression models estimated exposure to specific air pollutants using household addresses for 1991 (NO2), 2001 (PM10, NO2), and 2010 (NO2, NOx, PM10, PM2.5, PMcoarse, PM2.5abs). These were linked to the closest data collection wave at ages 43, 53 and 60-64, respectively. Psychological distress was assessed through the 28-item version of the General Health Questionnaire (GHQ-28), at ages 53, 60-64 and 69. Associations between each of the pollutants with psychological distress were analysed using generalised linear mixed models, adjusted for pollution exposure before age 43, assigned sex, social class, smoking status, neighbourhood deprivation, and previous mental health problems. We also examined effect modification by social class.

RESULTS

At age 69, 2125 participants completed the GHQ-28. In fully adjusted models, higher NO2 exposure was associated with higher GHQ-28 scores across a 26-year period (β=0.023, 95%CI:0.005, 0.040 per interquartile range increase in exposure), whereas higher exposure to PM10 was associated with lower GHQ-28 scores across a 16-year period (β=-0.021, 95%CI:-0.037, -0.006). There was no evidence of associations between exposure to other pollutants at age 60-64 and GHQ-28 at age 69. We found no effect modification by social class.

CONCLUSIONS

In this cohort there was some evidence of an association between higher cumulative exposure to NO2 and higher psychological distress, but mixed associations with other exposures. Policies to reduce pollutant exposure may help improve psychological symptoms in middle to late adulthood.

Large-scale plasma proteomics uncovers novel targets linking ambient air pollution and depression

Despite the growing recognition of association between air pollution and increased risk of depression, the intricate biological mechanisms underlying it remains unclear. In this study, a total of 1463 plasma proteins were measured by the Olink Explore platform for 50,553 participants in a large prospective cohort. Four air pollutants were assessed using land-use regression models: particulate matter with aerodynamic diameter ≤ 2.5μm (PM2.5), particulate matter with aerodynamic diameter > 2.5μm and ≤ 10μm (PM2.5-10), nitrogen dioxide (NO2), and nitric oxide (NO). The air pollution index was calculated using principal components analysis to assess joint exposure to air pollution. Logistic regression and Cox proportional hazards regression analyses were respectively used to explore the impact of the interaction between air pollution exposure and plasma proteins on the prevalence and incidence of depression. Functional enrichment analysis and drug prediction analysis were conducted to explore the biological mechanisms and drugs associated with identified plasma proteins with interaction effects. Logistic regression analysis detected seven significant air pollutant and plasma protein interactions for the prevalence of depression, such as CDHR5 vs. PM2.5 (OR: 0.58; 95% CI: 0.48-0.71), TNFRSF13C vs. NO (OR :0.70, 95% CI: 0.58-0.84) and ICAM5 vs. air pollution index (OR: 1.38, 95% CI: 1.17-1.63). Two significant interactions were identified for the incidence of depression: CDHR5 vs. PM2.5 (HR: 0.62, 95% CI: 0.50-0.76) and HSD11B1 vs. PM2.5 (HR: 1.48, 95% CI: 1.22-1.81). The plasma proteins that interacted with air pollutants were enriched in various Gene Ontology terms and pathways involving immunity, endocrine, inflammation, neurological function and metabolism, such as neuroinflammatory response, neuron projection guidance, regulation of lymphocyte mediated immunity, steroid biosynthetic process and lipid digestion. We also found that these proteins interacted with multiple drugs, such as risperidone, olanzapine and progesterone. This study identified novel targets linking ambient air pollution and depression, providing the insights for biological mechanisms of air pollution affecting the risk of depression.

Effects of ambient fine particulate matter on the exacerbation of psychiatric disorders in southern Taiwan: a case-crossover study

This study investigated the impact of short-term exposures to ambient fine particulate matter 2.5 (PM2.5) on the exacerbation of psychiatric disorders (PDs) in southern Taiwan between 2014 and 2020. Data on emergency room visits (ERVs) for PDs and air pollutant levels were obtained from the Chang Gung Research Database and the Environmental Protection Administration, respectively. A time-stratified case-crossover design was adopted to estimate the risks of ERVs for PDs. At lag4 days, a 10-μg/m3 increase in PM2.5 was associated with significant increases in ERVs in both single- and multi-pollutant models, with odds ratio (OR) of 1.18 [95% confidence interval (95% CI): 1.00, 1.38] (PM2.5), 1.20 (95% CI: 1.00, 1.43) (PM2.5 + SO2), 1.23 (95% CI: 1.03, 1.46) (PM2.5 + O3), and 1.25 (95% CI: 1.03, 1.52) (PM2.5 + SO2 + O3). For cumulative lags (lag0-6), a 10-μg/m3 increase in PM2.5 was associated with significant increases in ERVs only for multi-pollutant model (PM2.5 + SO2), with OR of 1.41 (95% CI: 1.03, 1.93). Among males, significant increases in ERVs were observed at lag4 and lag0-6 days; however, no significant associations were observed in females. In conclusion, short-term exposure to PM2.5 increased the risk of PDs exacerbation, exhibiting both delayed and cumulative effects, with male patients found to be more sensitive.

A systematic review of air pollution exposure and brain structure and function during development

OBJECTIVES

Air pollutants are known neurotoxicants. In this updated systematic review, we evaluate new evidence since our 2019 systematic review on the effect of outdoor air pollution exposure on childhood and adolescent brain structure and function as measured by magnetic resonance imaging (MRI).

METHODS

Using PubMed, Web of Science, and Scopus we conducted an updated literature search and systematic review of articles published through January 2025, using key terms for air pollution and functional and/or structural MRI. Two raters independently screened all articles using Covidence and implemented the risk of bias instrument for systematic reviews used to inform the World Health Organization Global Air Quality Guidelines.

RESULTS

We identified 29 relevant papers, and 20 new studies met our inclusion criteria. Including six studies from our 2019 review, the 26 publications to date include study populations from the United States, Netherlands, Spain, and United Kingdom. Studies investigated exposure periods spanning pregnancy through early adolescence, and estimated air pollutant exposure levels via personal monitoring, geospatial residential estimates, or school courtyard monitors. Brain MRI occurred when children were on average 6-14.7 years old; however, one study assessed newborns. Several MRI modalities were leveraged, including structural morphology, diffusion tensor imaging, restriction spectrum imaging, arterial spin labeling, magnetic resonance spectroscopy, as well as resting-state and task-based functional MRI. Air pollutants were associated with widespread brain differences, although the magnitude and direction of findings are largely inconsistent, making it difficult to draw strong conclusions.

CONCLUSION

Prenatal and childhood exposure to outdoor air pollution is associated with structural and functional brain variations. Compared to our initial 2019 review comprised of only cross-sectional studies, the current literature now includes longitudinal studies and more advanced neuroimaging methods. Further research is needed to clarify the effects of developmental timing, along with the downstream implications of outdoor air pollution exposure on children's cognitive and mental health.

Traffic pollution, reproductive health, and depressive symptoms in a healthy multiethnic sample of reproductive age women in the Ovarian Aging Study

OBJECTIVE

This study aimed to determine whether exposure to traffic-related air pollution (TRAP) is associated with depressive symptoms while also characterizing the contribution of key explanatory factors related to sociodemographics and health. In addition, it aimed to also explore the role of reproductive health as a pathway through which exposure to TRAP may relate to depressive symptoms.

METHODS

Participants were 688 healthy reproductive-age women in the Ovarian Aging Study. TRAP was derived from distance-weighted traffic counts using residential addresses. Depressive symptoms were assessed by the Center for Epidemiological Studies Depression scale. Explanatory factors were assessed by interview and clinic measures, including demographics (age, race/ethnicity), socioeconomic status (SES) (individual SES, neighborhood SES), general health (smoking, body mass index), and reproductive health (menarcheal age, contraceptive use, parity, menstrual cycle characteristics).

RESULTS

In cross-sectional, step-wise multivariate regression analyses, greater exposure to TRAP was related to more depressive symptoms ( b = 0.779, P = 0.015). Lower individual SES, longer menstrual cycle length, and experiencing change (vs no change) in menstrual cycle length were also related to more depressive symptoms ( P 's < 0.05). Examination of each model step showed that variance in depressive symptoms was attributable to TRAP (1.2%, P = 0.004), demographics (1.0%, P = 0.217), SES (1.4%, P = 0.007), general health (0.3%, P = 0.356), and reproductive health (2.0%, P = 0.015). Finally, menstrual cycle length, a marker of reproductive health status, partially mediated effects of TRAP on depressive symptoms (indirect effect: b = 0.064, P = 0.020).

CONCLUSIONS

Findings showed that exposure to TRAP is associated with depression, along with SES and reproductive health factors, and that reproductive health may be a pathway through which TRAP relates to depression.

Associations between residential segregation, ambient air pollution, and hippocampal features in recent trauma survivors

Background

Residential segregation is associated with differential exposure to air pollution. Hippocampus structure and function are highly susceptible to pollutants and associated with posttraumatic stress disorder (PTSD) development. Therefore, we investigated associations between residential segregation, air pollutants, hippocampal neurobiology, and PTSD in recent trauma survivors.

Methods

Participants (N = 278; 34% non-Hispanic white, 46% Non-Hispanic Black, 16% Hispanic) completed multimodal neuroimaging two weeks after trauma. Yearly averages of air pollutants (PM2.5 and NO2) and racial/economic segregation (Index of Concentration at the Extremes) were derived from each participant's address. Linear models assessed if air pollutants mediated associations between segregation and hippocampal volume, threat reactivity, or parahippocampal cingulum fractional anisotropy (FA) after covarying for age, sex, income, and 2-week PTSD symptoms. Further models evaluated if pollutants or segregation prospectively predicted PTSD symptoms six months post-trauma.

Results

Non-Hispanic Black participants lived in neighborhoods with significantly greater segregation and air pollution compared to Hispanic and non-Hispanic white participants (ps<.001). There was a significant indirect effect of NO2 between segregation and FA values (β = 0.08, 95% CI[0.01, 0.15]), and an indirect effect of PM2.5 between segregation and threat reactivity (β = -0.08, 95% CI[-0.14, -0.01]). There was no direct effect of segregation on hippocampal features. Pollutants and segregation were not associated with PTSD symptoms .

Conclusion

Residential segregation is associated with greater air pollution exposure, which is in turn associated with variability in hippocampal features among recent trauma survivors. Further research is needed to assess relationships between other environmental factors and trauma and stress-related disorders.

Differential Neurotoxicity Induced in Rats by Injection of PMs from 31 Major Cities in China

The effects of particulate matter (PMs) from different cities on the nervous system remain unclear. In this study, aqueous solutions of 0.45 μm membrane-filtered PM from 31 major Chinese cities were intravenously administered to rats. Neurotoxicity and mechanisms were investigated by quantifying rat behavior, analyzing in vivo biomarkers, and examining the PM physicochemical properties. PMs from different cities had variable impacts on rat responses, as manifested by the movement speed of the right ear, particularly at 1 h and 4-6 days postexposure. Physiological mechanisms were linked to the regulation of glucocorticoids via the hypothalamic-pituitary-adrenal axis and miR-107/miR-124 expression in the blood. Additionally, PM toxicity was strongly influenced by particle morphology, size, and zeta potential, which varied greatly across cities. Using random forest and multiple linear regression, we revealed that PM particle sizes (458.67 and 531.17 nm) and PM zeta potentials (-3.78, -17.01, and -20.31 mV) had the most important impacts on rat responsiveness, which was in line with blood biomarkers levels in rats such as Glucocorticoid, IL-1β, and IFN-α. These findings indicate that PMs from 31 cities contribute to varying neurotoxicity, thus presenting a possible differential burden on Alzheimer's disease in the aging population across many different regions.

EnvironMental Health: A Framework for an Emerging Field at the Intersection of the Environment and Mental Health Crises

Understanding how the environment shapes our mental and cognitive health is imperative to support efforts that promote healthy and sustainable living conditions. The etiology of mental health conditions remains often unclear, and social factors have received more scrutiny than natural or built environments. We present a conceptual framework illustrating the emerging intersection between the environment and neuropsychological health, intended to structure and guide research and funding, as well as public health and environmental initiatives. We conducted a scoping review of reviews of existing evidence on the impacts of the environment on mental and cognitive health. We found that an extensive body of work was focused on chemical hazards and the built environment and their associations with neurological and mental health, including attention-deficit/hyperactivity disorder (ADHD), autism, dementia, and mood. We identified emerging areas of research intersecting environmental factors such as air, water, light, and green space with schizophrenia and behavioral health. Our analysis of the intersections between the environment and mental and cognitive health allows for the identification of knowledge clusters and gaps, contextualizing needs and opportunities for future research and funding strategies. These significant connections showcase the importance of understanding the relationships between the environment and mental and cognitive health. With this work, we assert that the protection of the environment and its integration into healthcare can bring cascading benefits and synergies to mental and cognitive health and well-being and address the social and economic burden of the mental health crises.

What is the relationship between exposure to environmental pollutants and severe mental disorders? A systematic review on shared biological pathways

Severe mental disorders are multi-dimensional constructs, resulting from the interaction of genetic, biological, psychosocial, and environmental factors. Among the latter, pollution and climate change are frequently being considered in the etiopathogenesis of severe mental disorders. This systematic review aims to investigate the biological mechanisms behind the relationship between environmental pollutants, climate change, and mental disorders. An extensive literature search was performed on PubMed, Scopus, and APA PsycInfo databases according to the PRISMA guidelines. Articles were considered eligible if they involved humans or animals examining the association between exposure to environmental pollutants and if the resulting biological mechanisms that may have an impact on mental health and may support or even cause severe mental disorders (SMD) are assessed. For this reason, only studies dealing with biomarkers or biological pathways were taken into account. The 47 papers included in the review were divided into two groups: those conducted on human participants (15 studies) and those utilizing animal models (31 studies); one study included both humans and animals. Studies carried out with humans, which are mainly focused on measuring the impact of particulate matter (PM2.5 and PM10) exposure on mental health, showed an increased risk of depression or psychotic relapses through the inflammation and oxidative stress pathways, or through the alteration of the hypothalamic-pituitary-adrenal (HPA) axis. Animal models showed the potential impact of pollution on brain functioning through increased inflammatory responses, oxidative stress, HPA axis disruption, hippocampal damage, and neurotransmitters dysregulation. Our findings show that environmental pollutants have an impact on human mental health through different biological pathways. The biological mechanisms by which environmental pollution and climate change influence the onset and exacerbation of severe mental disorders are complex and include gene expression, inflammation, oxidative stress, and anatomical brain changes. A better understanding of those pathways is important for the progress of knowledge on the pathophysiology of severe mental disorders according to the one health model, that promotes a collaborative, multisectoral, and transdisciplinary approach across various levels to optimize health outcomes by recognizing the interconnectedness of humans, animals, plants, and their shared environment.

Proximity to public transportation and incidence of depression risk among older adults: A three-year longitudinal analysis from the Japan Gerontological evaluation study

OBJECTIVE

Depression in older adults has been associated with environmental factors, such as green spaces and walkable neighborhoods; however, evidence on the relationship between proximity to public transportation and mental health is scarce. This multi-municipality longitudinal study examined the association between proximity to public transportation and risk of depression among older adults and considered car usage.

METHODS

We analyzed data from 4947 functionally independent adults, aged 65 years and older who resided in 25 municipalities across Japan. Data were obtained via the Japan Gerontological Evaluation Study in 2016 and 2019. We assessed depression over three years in older adults without depression at baseline via the Geriatric Depression Scale-15. We subjectively and objectively measured their proximity to public transportation. Logistic regression analyses were performed, adjusted for covariates, with analyses stratified by car usage.

RESULTS

Of the participants, 9.76 % developed depression over a three-year period. Those without car usage and with reported lack of proximal public transport exhibited a higher incidence of depression (OR = 1.60, 95 %CI: 1.05-2.42) compared with those who had better access. No significant association was observed in the car user group. Furthermore, no significant association was observed in the analysis that used objective measures with Geographic Information System (GIS) data.

CONCLUSION

Subjective limited access to public transport was significantly associated with the risk of depression among older adults without car usage. Hence, improving and maintaining transportation infrastructure may mitigate the risk of depression.

Mental Health Vulnerabilities and Environmental Justice: A Collaborative Online International Learning Experience

Collaboration and intercultural interaction and engagement are relevant to all aspects of higher education including distance/remote/virtual courses. Collaborative Online International Learning (COIL) experiences connect students in different countries and provide them with meaningful and significant opportunities for global and intercultural exposure. Such an educational environment enhances students' cultural awareness and knowledge, and guides their personal, relational, and professional actions. Accordingly, engagement in COIL experiences can increase students' understanding of and ability to respond to significant global health-care issues both locally and internationally and to recognize their impact on mental health, and can lead to reflection and awareness that will endure beyond students' individual class experiences. One of these urgent issues is mental health vulnerabilities associated with environmental justice issues. This article describes participation in an international collaborative experience between the Universidad San Francisco de Quito, Ecuador, and the College of Nursing at the University of South Alabama, USA.

Impact of air pollution on depressive symptoms and the modifying role of physical activity: Evidence from the CHARLS study

The association between air pollution and depressive symptoms has not been thoroughly investigated, and the role of physical activity (PA) is particularly unclear. Although PA has been shown to alleviate depression, it may also increase exposure to air pollution, potentially exacerbating its adverse effects. A total of 17,332 participants aged 45 years and older from the 2018 wave of the China Health and Retirement Longitudinal Study (CHARLS) were included in this study to assess the causal effect of air pollution on depressive symptoms in China and to clarify the role of PA in this relationship. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale (CES-D). Data on particulate matter (PM1, PM2.5, and PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO) were obtained from the ChinaHighAirPollutants (CHAP) dataset. PA levels were measured using a standardized questionnaire and categorized as low or high. An instrumental variable (IV) approach was used to estimate the causal effect of air pollution on depressive symptoms. Potential effect modification by PA was assessed. The IV estimates showed that all air pollutants were significantly and adversely associated with depressive symptoms, with a per interquartile range (IQR) increase in PM1, PM2.5, PM10, NO2, SO2, O3, and CO associated with 1.57 (95% confidence interval (CI): 1.15, 1.99), 1.49 (95% CI: 1.10, 1.89), 1.71 (95% CI: 1.26, 2.17), 2.22 (95% CI: 1.62, 2.81), 1.30 (95% CI: 0.96, 1.65), 4.67 (95% CI: 3.37, 5.98), and 0.97 (95% CI: 0.71, 1.22) units increase in CES-D scores, respectively. PA significantly modified this association, with higher PA levels mitigating the adverse effects of air pollution on depressive symptoms.

Developing a translational research framework for MDD: combining biomolecular mechanisms with a spiraling risk factor model

Objective

The global incidence and burden of Major Depressive Disorder (MDD) are increasing annually, with current antidepressant treatments proving ineffective for 30-40% of patients. Biomolecular mechanisms within the microbiota-gut-brain axis (MGBA) may significantly contribute to MDD, potentially paving the way for novel treatment approaches. However, integrating the MGBA with the psychological and environmental aspects of MDD remains challenging. This manuscript aims to: 1) investigate the underlying biomolecular mechanisms of MDD using a modeling approach, and 2) integrate this knowledge into a comprehensive 'spiraling risk factor model' to develop a biopsychosocial translational research framework for the prevention and treatment of MDD.

Methods

For the first aim, a systematic review (PROSPERO registration) was conducted using PubMed, Embase, and Scopus to query literature published between 2016-2020, with select additional sources. A narrative review was performed for the second aim.

Results

In addition to genetics and neurobiology, research consistently indicates that hyperactivation of the HPA axis and a pro-inflammatory state are interrelated components of the MGBA and likely underlying mechanisms of MDD. Dysregulation of the MGBA, along with imbalances in mental and physical conditions, lifestyle factors, and pre-existing treatments, can trigger a downward spiral of stress and anxiety, potentially leading to MDD.

Conclusions

MDD is not solely a brain disorder but a heterogeneous condition involving biomolecular, psychological, and environmental risk factors. Future interdisciplinary research can utilize the integrated biopsychosocial insights from this manuscript to develop more effective lifestyle-focused multimodal treatment interventions, enhance diagnosis, and stimulate early-stage prevention of MDD.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42020215412.

Examining associations of air pollution and green space with depressive symptoms in adults: A LongITools cross-cohort analysis

OBJECTIVES

Evidence suggests that high levels of air pollution and less green space increase depressive symptoms in adults. However, results are mixed and cross-cohort comparisons are scarce, largely due to heterogeneity in exposure assessment. Also, the impact of these exposures on the trajectory of depressive symptoms over time has been less studied. We investigated the association of air pollution and green space with depressive symptoms in adulthood and whether these exposures modify the trajectory of depressive symptoms leveraging harmonized data from four population-based cohorts across the Netherlands and United Kingdom (UK).

METHODS

We analyzed data from the Dutch Famine Birth Cohort (DFBC) (n = 840, baseline ages: 56-61), and the Rotterdam Study (RS) (RS-I n = 4,049, baseline ages: 61-101 and RS-II n = 2,861, baseline ages: 55-99), in the Netherlands, and the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 17,100, baseline ages: 18-71) in the UK, each using a different validated instrument for depressive symptoms, with 3-11 repeated measures. European-wide environmental data was linked to participants' addresses at baseline. Linear mixed-models were used to estimate associations of air pollution and green space with standardized cohort-specific depressive symptoms, and whether these exposures modify the trajectory of depressive symptoms.

RESULTS

Long-term exposure to fine particulate matter (PM2.5) was positively associated with overall higher standardized depressive symptom scores in ALSPAC and RS-I (β per 10 μg/m3 increase in PM2.5: 0.07 SD, 95%CI 0.02, 0.11 and 0.13 SD, 95%CI 0.02, 0.24, respectively). Exposure to higher normalized difference vegetation index (NDVI) at 300 m buffer was associated with lower depressive symptoms in DFBC (β per 0.1 increase in NDVI: 0.08, 95%CI -0.14, -0.01). In RS-II, the positive effect of higher NDVI at 300-m buffer on depressive symptoms decreased over time, but this effect was very small (β per 0.1 increase in NDVI: 0.01 SD per year, 95%CI 0.00, 0.01).

CONCLUSION

Air pollution in the form of particulate matter as well as green space were associated with depressive symptoms across multiple cohorts. In the majority of cohorts, depressive symptoms increased with age, but we found little evidence that trajectories of depressive symptoms are influenced by exposure to environmental variables.

The impact of solid fuel use on major depression and the buffering effect of outdoor time in the UK adults: A 12-year cohort study

BACKGROUND

This study aims to investigate age- and gender-specific effects of household solid fuels for heating on major depression and buffering effects of outdoor time in a high-income country.

METHODS

Data were obtained from the UK Biobank. Participants with complete information on our studied variables and no prior diagnosis of major depression at baseline were included. Cox proportional hazards regression models were used to examine the effects of household solid fuels for heating on major depression. Subgroup analyses were conducted to investigate the buffering effects of outdoor time in summer and winter. Sensitivity analyses were performed to test the robustness of the main findings.

RESULTS

Of 255,505 participants (50.2 % women), the 12-year cumulative incidence of major depression was 4.4 %. Household solid fuels for heating increased the risk of major depression only in women aged <45 years (HR (95%CI) = 1.30 (1.04, 1.63)). In this group, the solid fuel effect was moderated by outdoor time spending both in summer (HR (95%CI), ≤2 h/day: 1.61 (1.13, 2.28); >2 h/day: 1.13 (0.84, 1.52)) and winter (≤1 h/day: 1.35 (1.01, 1.08); >1 h/day: 1.24 (0.86, 1.77)).

LIMITATIONS

Self-reported measures might lead to recall bias and some potential confounders, such as ventilation efficiency, were not measured and controlled in data analyses.

CONCLUSIONS

Younger women are more vulnerable to the impact of domestic air pollution on major depression. Promoting outdoor activities is a cost-effective and efficient approach to mitigating the risk of major depression caused by household solid fuels.

Association between long-term ambient air pollution exposure and the incidence of breast cancer: A meta-analysis based on updated evidence

BACKGROUND

Air pollution is a significant risk factor for breast cancer. However, epidemiological studies have yielded inconsistent results. Previous systematic reviews and meta-analyses have identified an association between nitrogen dioxide (NO2) exposure and the incidence of breast cancer, yet no consistent association has been observed for particulate matter (PM). With recent studies providing new evidence, updated meta-analyses are necessary.

METHODS

Relevant studies were identified through comprehensive literature searches in the Web of Science and PubMed databases. The pooled effect estimates for the associations of NO2, PM2.5, and PM10 with breast cancer incidence were calculated using a random-effects model. Publication bias was corrected, and sensitivity analyses were conducted to ensure the robustness of the findings. Subgroup analyses were performed based on menopausal status, hormone receptor subtype, and study region.

RESULTS

A total of 22 studies were included in this meta-analysis. The pooled hazard ratios with 95 % confidence intervals (CIs) for breast cancer incidence per 10 μg/m3 increase in NO2 and PM2.5 were 1.02 (95 % CI: 1.01, 1.03) and 1.06 (95 % CI: 1.02, 1.11), respectively. No significant association was observed between PM10 and breast cancer incidence. NO2 and PM10 exposures were significantly associated with the incidence of postmenopausal breast cancer. The associations of NO2, PM2.5, and PM10 with estrogen/progesterone receptor-positive (ER+/PR+) breast cancer were not significantly different from those with estrogen/progesterone receptor-negative (ER-/PR-) breast cancer. Exposure to both NO2 and PM2.5 was associated with breast cancer incidence in Europe, whereas in North America, only NO2 exposure showed a significant association.

CONCLUSION

This study is the first to document a significant association between long-term exposure to ambient PM2.5 and breast cancer incidence through meta-analysis. Air pollution has a pronounced impact on postmenopausal breast cancer, and the strength of the association between specific air pollutants and breast cancer incidence varies across regions. These findings suggest that long-term exposure to NO2 and PM2.5 may increase the incidence of breast cancer.

Synergistic air pollution exposure elevates depression risk: A cohort study

Depression is a leading mental health disorder worldwide, contributing substantially to the global disease burden. While emerging evidence suggests links between specific air pollutants and depression, the potential interactions among multiple pollutants remain underexplored. Here we show the influence of six common air pollutants on depressive symptoms among middle-aged and older Chinese adults. In single-pollutant models, a 10 μg m-3 increase in SO2, CO, PM10, and PM2.5 is associated with increased risks of depressive symptoms, with odds ratios (95% confidence intervals) of 1.276 (1.238-1.315), 1.007 (1.006-1.008), 1.066 (1.055-1.078), and 1.130 (1.108-1.153), respectively. In two-pollutant models, SO2 remains significantly associated with depressive symptoms after adjusting for other pollutants. Multi-pollutant models uncover synergistic effects, with SO2, CO, NO2, PM10, and PM2.5 exhibiting significant interactions, identifying SO2 as the primary driver of these associations. Mediation analyses further indicate that cognitive and physical impairments partially mediate the relationship between air pollution and depressive symptoms. These findings underscore the critical mental health impacts of air pollution and highlight the need for integrated air quality management strategies. Targeted mitigation of specific pollutants, particularly SO2, is expected to significantly enhance public mental health outcomes.

Therapeutic Potential of Herbal Medicines in Combating Particulate Matter (PM)-Induced Health Effects: Insights from Recent Studies

Particulate matter (PM), particularly fine (PM2.5) and ultrafine (PM0.1) particles, originates from both natural and anthropogenic sources, such as biomass burning and vehicle emissions. These particles contain harmful compounds that pose significant health risks. Upon inhalation, ingestion, or dermal contact, PM can penetrate biological systems, inducing oxidative stress, inflammation, and DNA damage, which contribute to a range of health complications. This review comprehensively examines the protective potential of natural products against PM-induced health issues across various physiological systems, including the respiratory, cardiovascular, skin, neurological, gastrointestinal, and ocular systems. It provides valuable insights into the health risks associated with PM exposure and highlights the therapeutic promise of herbal medicines by focusing on the natural products that have demonstrated protective properties in both in vitro and in vivo PM2.5-induced models. Numerous herbal medicines and phytochemicals have shown efficacy in mitigating PM-induced cellular damage through their ability to counteract oxidative stress, suppress pro-inflammatory responses, and enhance cellular defense mechanisms. These combined actions collectively protect tissues from PM-related damage and dysfunction. This review establishes a foundation for future research and the development of effective interventions to combat PM-related health issues. However, further studies, including in vivo and clinical trials, are essential to evaluate the safety, optimal dosages, and long-term effectiveness of herbal treatments for patients under chronic PM exposure.

Association of social vulnerability and depression incidence post intracerebral haemorrhage: a cohort study

Objectives

Survivors of intracerebral haemorrhage (ICH) are at high risk of incident depression, which is modified by social determinants of health (SDOH) and associated with worse functional outcomes. We sought to determine the role of prestroke SDOH in depression incidence after ICH to better characterise post-ICH outcomes.

Study design

We analysed data from a cohort study of ICH survivors without prestroke depression, presenting at Massachusetts General Hospital between 2006 and 2017. We collected information from electronic health records (EHR), follow-up interviews and CT/MRI. The relationship between social vulnerability, air quality and post-ICH depression incidence within 12 months of acute haemorrhage was investigated using logistic regression models that also included EHR and CT/MRI information as predictors.

Results

Participants were 576 survivors, median age of 72 (IQR=61-81), 317 (55%) self-reported as male and 482 (84%) as white. 204 (35%) were diagnosed with depression within 12 months of ICH. Hospital admission longer than 1 week (OR 1.80, 95% CI 1.08 to 3.00), cerebral amyloid angiopathy (CAA) burden (OR 1.45, 95% CI 1.25 to 1.68) and social vulnerability (OR 3.03, 95% CI 1.49 to 6.19) were associated with depression incidence post-ICH.

Conclusions

In addition to CAA burden and patient location 1-week post-ICH, social vulnerability was independently associated with depression among ICH survivors. Our findings suggest that social vulnerability influences ICH outcomes. Future studies should investigate how poststroke clinical care interventions can address SDOH effects to reduce incident depression and improve outcomes among ICH survivors.

Persistent organic pollutants exposure and risk of depression: A systematic review and meta-analysis

Recently, more and more epidemiological studies have examined the impact of exposure to persistent organic pollutants (POPs) on depression, but the results are inconsistent. Thus, we conducted a systematic review and meta-analysis to better understand the effects of POPs exposure on the risk of depression in the general population. We searched PubMed, Embase, Web of Science, and Scopus databases for studies before March 20, 2024. Random-effects meta-analysis was applied to calculate pooled relative risk (OR) and 95% confidence intervals (CIs). We also assessed potential heterogeneity and publication bias across studies and conducted sensitivity analysis. A total of 26 studies were included, and the results indicated that exposure to ΣPBDEs, PBDE-47, and PBDE-99 increased the risk of depression, with OR of 1.37 (95 % CI = 1.06-1.79), 1.30 (95% CI = 1.08-1.56), 1.46 (95 % CI = 1.00-2.12) respectively. On the contrary, the exposure assessment results of PFOS showed a negative correlation with the risk of depression. There is no association between exposure to ΣPFAS, ΣPCBs, and ΣOCPs and increased risk of depression. More standardized studies and more samples are needed in the future to confirm the findings of this study. This finding could provide theoretical references for the prevention and management of depression and offer insights for the risk assessment of POPs exposure.

Air Pollution's Hidden Toll: Links Between Ozone, Particulate Matter, and Adolescent Depression

Rising rates of depression among youth present a growing mental health crisis. Despite growing concerns regarding the risks of air pollution exposure on youth mental and physical health, associations between ambient air pollutants and depression have been largely overlooked in youth. In this cross-sectional study, we investigated associations between ozone, particulate matter, and depressive symptoms in adolescents across 224 Colorado census tracts (average age of 14.45 years, 48.8% female, 48.9% of minority race/ethnicity). Students in participating schools reported depressive symptoms and demographic information, and school addresses were used to compute ozone and particulate matter levels per census tract. Possible confounding variables, including sociodemographic and geographic characteristics, were also addressed. Exploratory analyses examined demographic moderators of these associations. Census tracts with higher ozone concentrations had a higher percentage of adolescents experiencing depressive symptoms. Particulate matter did not emerge as a significant predictor of adolescent depressive symptoms. Secondary analyses demonstrated that associations with ozone were moderated by racial/ethnic and gender compositions of census tracts, with stronger effects in census tracts with higher percentages of individuals with marginalized racial/ethnic and gender identities. Ultimately, this project strengthens our understanding of the interplay between air pollution exposures and mental health during adolescence.

Risk factors of under-five and infant mortality: An umbrella review of systematic reviews and meta-analyses

Background

Ensuring child survival is a critical global challenge, requiring a robust and comprehensive understanding of the risk factors contributing to under-five mortality (U5M). We aimed to synthesise and summarise the current available evidence on risk factors of U5M and infant mortality worldwide to inform global child health programmes.

Methods

We searched six major databases (Embase, Medline, Scopus, CINAHL, Web of Science, and Global Health) and repositories of systematic reviews, as well as grey literature sources to identify systematic reviews and meta-analyses that examined the associations between risk factors of U5M and infant mortality between 1 January 1990 and 4 March 2024. The quality of reviews was assessed using A Measurement Tool to Assess Systematic Reviews, Version 2 (AMSTAR 2). The strength of evidence and direction of associations was graded.

Results

Of 5684 records, we included 32 reviews (including five systematic reviews without meta-analysis) which comprised 1042 primary studies. We synthesised 28 and 29 unique risk factors associated with U5M and infant mortality, respectively. Although there was no convincing evidence for the risk factors, we found probable evidence of association between exclusive breastfeeding (consistent negative association), and maternal death (consistent positive association) with U5M. There was also probable evidence for the association of short (<18 months) interpregnancy intervals (less consistent negative association), pre-pregnancy maternal obesity (consistent positive association), and maternal HIV infection (consistent positive association) with infant mortality.

Conclusions

While the review identified a broad range of risk factors, the overall evidence for most factors associated with under-five and infant mortality was 'limited-suggestive' or 'limited and no conclusive'. Thus, further high-quality studies are required to strengthen the evidence on these risk factors.

Registration

PROSPERO CRD42023455542.

Air pollution mixture exposure during pregnancy and postpartum psychological functioning: racial/ethnic- and fetal sex-specific associations

BACKGROUND

Prenatal air pollution (AP) exposure has been linked to postpartum psychological functioning, impacting health outcomes in both women and children. Extant studies primarily focused on individual pollutants.

OBJECTIVE

To assess the association between prenatal exposure to a mixture of seven AP components and postpartum psychological functioning using daily exposure data and data-driven statistical methods.

METHODS

Analyses included 981 women recruited at 24.0 ± 9.9 weeks gestation and followed longitudinally. We estimated prenatal daily exposure levels for constituents of fine particles [elemental carbon (EC), organic carbon (OC), nitrate (NO3-), sulfate (SO42-), ammonium (NH4+)], nitrogen dioxide (NO2), and ozone (O3) using validated global 3-D chemical-transport models and satellite-based hybrid models based on residential addresses. Edinburgh Postnatal Depression Scale (EPDS) was administered to participants to derive a total EPDS score and the subconstruct scores for anhedonia and depressive symptoms. A distributed lag model (DLM) was employed within Bayesian Kernel Machine Regression (BKMR) to develop time-weighted exposure profile for each pollutant. These exposures were then input into a Weighted Quantile Sum (WQS) regression to estimate an overall mixture effect, adjusted for maternal age, education, race/ethnicity, season of delivery, and delivery year. Effect modification by race/ethnicity and fetal sex was also examined.

RESULTS

Women were primarily Hispanic (51%) and Black (32%) reporting ≤12 years of education (58%). Prenatal exposure to an AP mixture was significantly associated with increased anhedonia subscale z-scores, particularly in Hispanics (β = 0.07, 95%CI = 0.004-0.13, per unit increase in WQS index). It was also borderline associated with increased total EPDS (β = 0.11, 95%CI = 0.00-0.22) and depressive symptom subscale (β = 0.09, 95%CI = -0.02 to 0.19) z-scores, particularly among Hispanic women who gave birth to a male infant. Sulfate (SO42-), O3 and OC were major contributors to these associations.

IMPACT

This study utilizes an advanced data-driven approach to examine the temporally- and mixture-weighted effects of prenatal air pollution exposure on postpartum psychological functioning. We found that exposure to a prenatal air pollution mixture predicted poorer postpartum psychological functioning, particularly anhedonia symptoms in Hispanic women. Findings underscore the importance of considering both exposure mixtures as well as potential modifying factors to better help identify particular pollutants that drive effects and susceptible populations, which can inform more effective intervention strategies.

Hybrid FCMG-OP-FIS model approach to convert regression into classification data for machine learning-based AQI prediction

Air pollution from vehicle emissions, industrial activities, and medical facilities poses significant health risks in urban areas, underscoring the necessity for robust air quality index (AQI) monitoring. This paper presents a novel method for AQI prediction by integrating a fuzzy centre merge graph with an optimal value-based fuzzy inference system (FCMG-OP-FIS) and machine learning (ML). Traditional ML techniques encounter difficulties when converting regression datasets into classification formats, particularly when unable to label the dataset using the traditional method. The proposed FCMG-OP-FIS model efficiently converts regression data into a classification framework. Unlike traditional AQI prediction methods that rely solely on pollutant data, this approach incorporates both pollutant and meteorological data to improve prediction accuracy. The innovative fuzzy centre merge graph (FCMG) balances the dataset for optimal solutions and facilitates input grouping for Simulink, simplifying rule management. The FCMG-OP-FIS model generates a regression output for AQI, which is subsequently classified into levels (healthy, moderate, or unhealthy) using IF-THEN rules. To enhance accuracy further, a random forest classifier (RFC) is trained on the FCMG-OP-FIS classified output data. The regression output of the FCMG-OP-FIS model is validated using metrics such as RMSE (0.48), MSE (0.23), MAE (0.23), and MAPE (1.77%). Additionally, the classification output from the RFC model employs advanced validation techniques including stratified shuffle validation, grid search cross-validation, and confusion matrix analysis, achieving an accuracy rate of 99%, with the F1 score, precision, and recall over all at 99%. These results demonstrate the effectiveness of the proposed model in accurately labelling data for classification and predicting AQI through ML, highlighting its potential for practical application in environmental monitoring and management.

Particulate Matter-Induced Emerging Health Effects Associated with Oxidative Stress and Inflammation

Environmental pollution continues to increase with industrial development and has become a threat to human health. Atmospheric particulate matter (PM) was designated as a Group 1 carcinogen by the International Agency for Research on Cancer in 2013 and is an emerging global environmental risk factor that is a major cause of death related to cardiovascular and respiratory diseases. PM is a complex composed of highly reactive organic matter, chemicals, and metal components, which mainly cause excessive production of reactive oxygen species (ROS) that can lead to DNA and cell damage, endoplasmic reticulum stress, inflammatory responses, atherosclerosis, and airway remodeling, contributing to an increased susceptibility to and the exacerbation of various diseases and infections. PM has various effects on human health depending on the particle size, physical and chemical characteristics, source, and exposure period. PM smaller than 5 μm can penetrate and accumulate in the alveoli and circulatory system, causing harmful effects on the respiratory system, cardiovascular system, skin, and brain. In this review, we describe the relationship and mechanism of ROS-mediated cell damage, oxidative stress, and inflammatory responses caused by PM and the health effects on major organs, as well as comprehensively discuss the harmfulness of PM.

Fine particulate matter components associated with exacerbated depressive symptoms among middle-aged and older adults in China

Growing awareness acknowledges ambient fine particulate matter (PM2.5) as an environmental risk factor for mental disorders, especially among older people. However, there remains limited evidence regarding which specific chemical components of PM2.5 may be more detrimental. This nationwide prospective cohort study included 22,126 middle-aged and older adult participants of the China Health and Retirement Longitudinal Study (CHARLS, 2011-2016), to explore the individual and joint associations between long-term exposure to various PM2.5 components (sulfate, nitrate, ammonium, organic matter, and black carbon) and depressive symptoms. The depressive symptoms were assessed using the 10-item Center for Epidemiological Studies-Depression Scale (CES-D-10). Using the novel quantile-based g-computation for multi-pollutant mixture analysis, we found that exposure to the mixture of major PM2.5 components was significantly associated with aggravating depressive symptoms, with the exposure-response curve exhibiting consistent linear or supra-linear shape without a lower threshold. The estimated weight index indicated that, among major PM2.5 components, only nitrate, sulfate, and black carbon significantly contributed to the exacerbation of depressive symptoms. Given the expanding aging population, stricter regulation on the emissions of particularly toxic PM2.5 components may mitigate the escalating disease burden of depression.

Objective and subjective accounts of urban exposures for epidemiological research on mental health. Measurement and analysis

The interest in the impact of urban environmental exposures (UrbEEs) on mental health has greatly increased in the last two decades. Researchers have tended to measure said exposures either via objective measurement procedures (eg, air pollution campaigns and geographic information systems computations) or by self-reported techniques such as the use of scales and questionnaires. It has been suggested that studying both the objective features of the environments and people's perceptions are key to understand environmental determinants of health and might be needed to tailor effective interventions. However, there is little guidance on how to approach this matter, the comparability between objective and subjective accounts of UrbEEs and, more importantly, suitable statistical procedures to deal with the practicalities of this kind of data. In this essay, we aim to build the case for the joint use of both sets of variables in epidemiological studies and propose socioecological models as a valid theoretical framework to accommodate these. In the methodological sphere, we will also review current literature to select examples of (un)appropriate subjective accounts of urban exposures and propose a series of statistical procedures to estimate the total, direct and indirect effects of UrbEEs on mental health and the potential associations between objective and subjective UrbEEs accounts.

Logistic Regression: Limitations in the Estimation of Measures of Association with Binary Health Outcomes

INTRODUCTION

Logistic regression models are frequently used to estimate measures of association between an exposure, health determinant or intervention, and a binary outcome. However, when the outcome is frequent (> 10%), model estimates for relative risks and prevalence ratios might be biased. Despite the availability of several alternatives, many still rely on these models, and a consensus is yet to be reached. We aimed to compare the estimation and goodness-of-fit of logistic, log-binomial and robust Poisson regression models, in cross-sectional studies involving frequent binary outcomes.

METHODS

Two cross-sectional studies were conducted. Study 1 was a nationally representative study on the impact of air pollution on mental health. Study 2 was a local study on immigrants' access to urgent healthcare services. Odds ratios (OR) were obtained through logistic regression, and prevalence ratios (PR) through log-binomial and robust Poisson regression models. Confidence intervals (CI), their ranges, and standard-errors (SE) were also computed, along with models' relative goodness-of-fit through Akaike Information Criterion (AIC), when applicable.

RESULTS

In Study 1, the OR (95% CI) was 1.015 (0.970 - 1.063), while the PR (95% CI) obtained through the robust Poisson mode was 1.012 (0.979 - 1.045). The log-binomial regression model did not converge in this study. In Study 2, the OR (95% CI) was 1.584 (1.026 - 2.446), the PR (95% CI) for the log-binomial model was 1.217 (0.978 - 1.515), and 1.130 (1.013 - 1.261) for the robust Poisson model. The 95% CI, their ranges, and the SE of the OR were higher than those of the PR, in both studies. However, in Study 2, the AIC value was lower for the logistic regression model.

CONCLUSION

The odds ratio overestimated PR with wider 95% CI and higher SE. The overestimation was greater as the outcome of the study became more prevalent, in line with previous studies. In Study 2, the logistic regression was the model with the best fit, illustrating the need to consider multiple criteria when selecting the most appropriate statistical model for each study. Employing logistic regression models by default might lead to misinterpretations. Robust Poisson models are viable alternatives in cross-sectional studies with frequent binary outcomes, avoiding the non-convergence of log-binomial models.

How does the macroenvironment influence brain and behaviour-a review of current status and future perspectives

The environment influences brain and mental health, both detrimentally and beneficially. Existing research has emphasised the individual psychosocial 'microenvironment'. Less attention has been paid to 'macroenvironmental' challenges, including climate change, pollution, urbanicity, and socioeconomic disparity. Notably, the implications of climate and pollution on brain and mental health have only recently gained prominence. With the advent of large-scale big-data cohorts and an increasingly dense mapping of macroenvironmental parameters, we are now in a position to characterise the relation between macroenvironment, brain, and behaviour across different geographic and cultural locations globally. This review synthesises findings from recent epidemiological and neuroimaging studies, aiming to provide a comprehensive overview of the existing evidence between the macroenvironment and the structure and functions of the brain, with a particular emphasis on its implications for mental illness. We discuss putative underlying mechanisms and address the most common exposures of the macroenvironment. Finally, we identify critical areas for future research to enhance our understanding of the aetiology of mental illness and to inform effective interventions for healthier environments and mental health promotion.

Do social economic status modify the association between air pollution and depressive or anxiety symptoms? A big sample cross-sectional study from the rural areas of Central China

BACKGROUND

Fewer studies have examined the relationship between air pollution and depressive or anxiety symptoms in rural residents. Social economic status (SES), as an important indicator of the current state of socioeconomic development, we know little about how it modifies the relationship between air pollution and symptoms of depression or anxiety.

METHODS

The patient health questionnaire (PHQ-2) and generalized anxiety scale (GAD-2) were used to learn about the prevalence of depressive and anxiety symptoms, the social economic status of the participants was categorized into two levels: lower and higher, and a binary logistic regression model was used to analyze the relationship between air pollution and residents' symptoms of depression or anxiety.

RESULTS

A total of 10,670 adults were enrolled in this study, of which a total of 1292 participants suffered from depressive symptoms and 860 suffered from anxiety symptoms. Short-term exposure to PM2.5 and O3, singly or in combination, may be associated with the onset of depression symptoms, and there was a significant interaction between SES and exposure to PM2.5 or O3. Residents of areas with higher SES may have a lower risk of suffering from anxiety symptoms after O3 exposure compared to participants living in lower SES.

LIMITATIONS

The study was a cross-sectional study, which may have lowered the quality level of the evidence.

CONCLUSIONS

Short-term PM2.5 and O3 exposure may be associated with an increased prevalence risk of depressive symptoms. Higher levels of SES may reduce the adverse effects of air pollution on depressive or anxiety symptoms.

Impact of air pollution exposure on the severity of major depressive disorder: Results from the DeprAir study

BACKGROUND

Major depressive disorder (MDD) is one of the most prevalent medical conditions worldwide. Different factors were found to play a role in its etiology, including environmental ones (e.g., air pollution). The aim of this study was to evaluate the association between air pollution exposure and MDD severity.

METHODS

Four hundred sixteen MDD subjects were recruited. Severity of MDD and functioning were evaluated through five rating scales: Montgomery-Asberg Depression Rating Scale (MADRS), Hamilton Depression Rating Scale (HAMD), Clinical Global Impression (CGI), Global Assessment of Functioning (GAF), and Sheehan Disability Scale (SDS). Daily mean estimates of particulate matter with diameter ≤10 (PM10) and 2.5 μm (PM2.5), nitrogen dioxide (NO2), and apparent temperature (AT) were estimated based on subjects' residential addresses. Daily estimates of the 2 weeks preceding recruitment were averaged to obtain cumulative exposure. Multivariate linear and ordinal regression models were applied to assess the associations between air pollutants and MDD severity, overall and stratifying by hypersusceptibility and AT.

RESULTS

Two-thirds of subjects were women and one-third had a family history of depression. Most women had depression with symptoms of anxiety, while men had predominantly melancholic depression. NO2 exposure was associated with worsening of MDD severity (HAMD: β = 1.94, 95% confidence interval [CI], [0.41-3.47]; GAF: β = -1.93, 95% CI [-3.89 to 0.02]), especially when temperatures were low or among hypersusceptible subjects. PM exposure showed an association with MDD severity only in these subgroups.

CONCLUSIONS

Exposure to air pollution worsens MDD severity, with hypersusceptibility and lower temperatures being exacerbating factors.

A Systematic Review of Air Pollution Exposure and Brain Structure and Function during Development

Objectives

Air pollutants are known neurotoxicants. In this updated systematic review, we evaluate new evidence since our 2019 systematic review on the effect of outdoor air pollution exposure on childhood and adolescent brain structure and function as measured by magnetic resonance imaging (MRI).

Methods

Using PubMed and Web of Science, we conducted an updated literature search and systematic review of articles published through March 2024, using key terms for air pollution and functional and/or structural MRI. Two raters independently screened all articles using Covidence and implemented the risk of bias instrument for systematic reviews informing the World Health Organization Global Air Quality Guidelines.

Results

We identified 222 relevant papers, and 14 new studies met our inclusion criteria. Including six studies from our 2019 review, the 20 publications to date include study populations from the United States, Netherlands, Spain, and United Kingdom. Studies investigated exposure periods spanning pregnancy through early adolescence, and estimated air pollutant exposure levels via personal monitoring, geospatial residential estimates, or school courtyard monitors. Brain MRI occurred when children were on average 6-14.7 years old; however, one study assessed newborns. Several MRI modalities were leveraged, including structural morphology, diffusion tensor imaging, restriction spectrum imaging, arterial spin labeling, magnetic resonance spectroscopy, as well as resting-state and task-based functional MRI. Air pollutants were associated with widespread brain differences, although the magnitude and direction of findings are largely inconsistent, making it difficult to draw strong conclusions.

Conclusion

Prenatal and childhood exposure to outdoor air pollution is associated with structural and functional brain variations. Compared to our initial 2019 review, publications doubled-an increase that testifies to the importance of this public health issue. Further research is needed to clarify the effects of developmental timing, along with the downstream implications of outdoor air pollution exposure on children's cognitive and mental health.

Long-term Exposure to Ambient Air Pollution and its Association with Mental Well-Being, Depression and Anxiety: A Nationally Representative Study

INTRODUCTION

Exposure to ambient air pollution may play a role in the onset of common mental disorders like depressive and anxiety disorders. The association of long-term exposure to particles smaller than 10 μm (PM10) with these diseases remains unclear. This study aimed to estimate the association of long-term exposure to PM10 with mental well-being and the frequency of probable diagnosis of common mental disorders.

METHODS

A nationally representative cross-sectional study was done in mainland Portugal. Long-term exposure was estimated through one-year average concentrations of PM10, calculated with data from the Portuguese Environment Agency, attributed individually considering individuals' postal codes of residence. The mental well-being and the probable diagnosis of common mental disorders were ascertained through the five-item Mental Health Inventory scale. Linear and Robust Poisson regression models were computed to estimate change percentages, prevalence ratios (PR), and their 95% confidence intervals (95% CI).

RESULTS

The median (interquartile range) concentration of PM10 was 18.6 (15.3 - 19.3) μg/m3. The mental well-being score was 72 (56 - 84) points, on a scale from 0 to 100. A probable diagnosis of common mental disorders was found in 22.7% (95% CI: 20.0 to 25.6). Long-term exposure to PM10 was associated with a non-statistically significant decrease in the mental well-being score [for each 10 μg/m³ increment in one-year average PM10 concentrations, there was a 2% (95% CI: -8 to 4) decrease], and with a non-statistically significant increase in the common mental health frequency (PR = 1.012, 95% CI: 0.979 to 1.045).

CONCLUSION

We did not find statistically significant associations between long-term exposure to PM10 and mental well-being or the frequency of probable diagnosis of common mental disorders. These results may be explained by the reduced variability in the exposure values, given the geographical distribution and functioning of the network of air quality monitoring stations. This study contributes with evidence for low levels of air pollutants, being one of the first to adjust for individual and aggregate-level variables. Moreover, to the best of our knowledge, this was the first nationally representative, population-based study conducted on the Portuguese population using real-life data. Maintaining a robust and nationwide air quality monitoring network is essential for obtaining quality exposure data.

Chemical composition of PM10 at a rural site in the western Mediterranean and its relationship with the oxidative potential

A comprehensive chemical characterization (water-soluble ions, organic and elemental carbon, water- and methanol-soluble organic carbon, levoglucosan, and major and trace metals) of PM10 samples collected in a rural area located in the southeast of the Iberian Peninsula was performed. Additionally, the oxidative potential of the samples, used as an indicator of aerosol toxicity, was determined by the ascorbic acid (OPAA) and dithiothreitol (OPDTT) assays. The average concentration of PM10 during the study period, spanning from late winter to early spring, was 20.2 ± 10.8 μg m-3. Nitrate, carbonate and calcium (accounting for 20% of the average PM10 mass concentration) and organic matter (with a contribution of 28%) were the main chemical components of PM10. Average concentrations of traffic tracers such as elemental carbon, copper and zinc (0.31 μg m-3, 3 ng m-3, and 9 ng m-3, respectively) were low compared with those obtained at an urban site in the same region, due to the almost total absence of traffic in the surrounding of the sampling site. Regarding levoglucosan and K+, which can be considered as tracers of biomass burning, their concentrations (0.12 μg m-3 and 55 ng m-3, respectively) were in the lower range of values reported for other rural areas in Europe, suggesting a moderate contribution form this source to PM10 levels. The results of the Pearson's correlation analysis showed that volume-normalised OPAA and OPDTT levels (average values of 0.11 and 0.32 nmol min-1 m-3, respectively) were sensitive to different PM10 chemical components. Whereas OPAA was not strongly correlated with any of the species measured, good correlation coefficients of OPDTT with water-soluble organic carbon (r = 0.81) and K+ (r = 0.73) were obtained, which points to biomass burning as an important driver of the DTT activity.

Commercial determinants of mental ill health: An umbrella review

Mental ill health has complex and interrelated underlying causes, with wider determinants of health often overlooked as risk factors. The 'commercial determinants of health' are gradually receiving more attention and recognition but there is a relative lack of awareness of the commercial determinants of mental health. This aim of this umbrella review was to synthesise systematic review level evidence for the association between commercial determinants and mental health outcomes. This umbrella review included evidence from high, middle, and low-income countries. We included terms related to broader commercial activities and terms focused on six key unhealthy commodities (tobacco, alcohol, ultra-processed foods, gambling, social media, fossil fuels) and the impacts of fossil fuel consumption (climate change, air pollution, wider pollution). We included 65 reviews and found evidence from high quality reviews for associations between alcohol, tobacco, gambling, social media, ultra-processed foods and air pollution and depression; alcohol, tobacco, gambling, social media, climate change and air pollution with suicide; climate change and air pollution with anxiety; and social media with self-harm. There was a lack of evidence examining wider practices of commercial industries. Our umbrella review demonstrates that by broadening the focus on commercial determinants, the influence of commercial products and activities on mental ill health can be better understood. The lack of research examining broader commercial practices on mental ill health is an area that should be addressed. Our review highlights the existing base of high-quality evidence for many of these unhealthy commodities' impacts on mental ill health and indicates that commercial determinants is a valuable framework for understanding the drivers of mental ill health.

Choices of morbidity outcomes and concentration-response functions for health risk assessment of long-term exposure to air pollution

Background

Air pollution health risk assessment (HRA) has been typically conducted for all causes and cause-specific mortality based on concentration-response functions (CRFs) from meta-analyses that synthesize the evidence on air pollution health effects. There is a need for a similar systematic approach for HRA for morbidity outcomes, which have often been omitted from HRA of air pollution, thus underestimating the full air pollution burden. We aimed to compile from the existing systematic reviews and meta-analyses CRFs for the incidence of several diseases that could be applied in HRA. To achieve this goal, we have developed a comprehensive strategy for the appraisal of the systematic reviews and meta-analyses that examine the relationship between long-term exposure to particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5), nitrogen dioxide (NO2), or ozone (O3) and incidence of various diseases.

Methods

To establish the basis for our evaluation, we considered the causality determinations provided by the US Environmental Protection Agency Integrated Science Assessment for PM2.5, NO2, and O3. We developed a list of pollutant/outcome pairs based on these assessments and the evidence of a causal relationship between air pollutants and specific health outcomes. We conducted a comprehensive literature search using two databases and identified 75 relevant systematic reviews and meta-analyses for PM2.5 and NO2. We found no relevant reviews for long-term exposure to ozone. We evaluated the reliability of these studies using an adaptation of the AMSTAR 2 tool, which assesses various characteristics of the reviews, such as literature search, data extraction, statistical analysis, and bias evaluation. The tool's adaptation focused on issues relevant to studies on the health effects of air pollution. Based on our assessment, we selected reviews that could be credible sources of CRF for HRA. We also assessed the confidence in the findings of the selected systematic reviews and meta-analyses as the sources of CRF for HRA. We developed specific criteria for the evaluation, considering factors such as the number of included studies, their geographical distribution, heterogeneity of study results, the statistical significance and precision of the pooled risk estimate in the meta-analysis, and consistency with more recent studies. Based on our assessment, we classified the outcomes into three lists: list A (a reliable quantification of health effects is possible in an HRA), list B+ (HRA is possible, but there is greater uncertainty around the reliability of the CRF compared to those included on list A), and list B- (HRA is not recommended because of the substantial uncertainty of the CRF).

Results

In our final evaluation, list A includes six CRFs for PM2.5 (asthma in children, chronic obstructive pulmonary disease, ischemic heart disease events, stroke, hypertension, and lung cancer) and three outcomes for NO2 (asthma in children and in adults, and acute lower respiratory infections in children). Three additional outcomes (diabetes, dementia, and autism spectrum disorders) for PM2.5 were included in list B+. Recommended CRFs are related to the incidence (onset) of the diseases. The International Classification of Diseases, 10th revision codes, age ranges, and suggested concentration ranges are also specified to ensure consistency and applicability in an HRA. No specific suggestions were given for ozone because of the lack of relevant systematic reviews.

Conclusion

The suggestions formulated in this study, including CRFs selected from the available systematic reviews, can assist in conducting reliable HRAs and contribute to evidence-based decision-making in public health and environmental policy. Future research should continue to update and refine these suggestions as new evidence becomes available and methodologies evolve.

The Association between Exposure to Fine Particulate Air Pollution and the Trajectory of Internalizing and Externalizing Behaviors during Late Childhood and Early Adolescence: Evidence from the Adolescent Brain Cognitive Development (ABCD) Study

BACKGROUND

Exposure to high levels of fine particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) via air pollution may be a risk factor for psychiatric disorders during adulthood. Yet few studies have examined associations between exposure and the trajectory of symptoms across late childhood and early adolescence.

OBJECTIVE

The current study evaluated whether PM 2.5 exposure at 9-11 y of age affects both concurrent symptoms as well as the longitudinal trajectory of internalizing and externalizing behaviors across the following 3 y. This issue was examined using multiple measures of exposure and separate measures of symptoms of internalizing disorders (e.g., depression, anxiety) and externalizing disorders (e.g., conduct disorder), respectively.

METHODS

In a sample of more than 10,000 youth from the Adolescent Brain Cognitive Development (ABCD) Study, we used a dataset of historical PM 2.5 levels and growth curve modeling to evaluate associations of PM 2.5 exposure with internalizing and externalizing symptom trajectories, as assessed by the Child Behavioral Check List. Three distinct measures of PM 2.5 exposure were investigated: annual average concentration during 2016, number of days in 2016 above the US Environmental Protection Agency (US EPA) 24-h PM 2.5 standards, and maximum 24-h concentration during 2016.

RESULTS

At baseline, higher number of days with PM 2.5 levels above US EPA standards was associated with higher parent-reported internalizing symptoms in the same year. This association remained significant up to a year following exposure and after controlling for PM 2.5 annual average, maximum 24-h level, and informant psychopathology. There was also evidence of an association between PM 2.5 annual average and externalizing symptom levels at baseline in females only.

DISCUSSION

Results suggested PM 2.5 exposure during childhood is associated with higher symptoms of internalizing and externalizing disorders at the time of exposure and 1 y later. In addition, effects of PM 2.5 exposure on youth internalizing symptoms may be most impacted by the number of days of exposure above US EPA standards in comparison with annual average and maximum daily exposure. https://doi.org/10.1289/EHP13427.

Differential effects of air pollution exposure on mental health: Historical redlining in New York State

Growing evidence suggests that ambient air pollution has adverse effects on mental health, yet our understanding of its unequal impact remains limited, especially in areas with historical redlining practices. This study investigates whether the impact of daily fluctuations in ambient air pollutant levels on emergency room (ER) visits for mental disorders (MDs) varies across neighborhoods affected by redlining. Furthermore, we explored how demographic characteristics and ambient temperature may modify the effects of air pollution. To assess the disproportional short-term effects of PM2.5, NO2, and O3 on ER visits across redlining neighborhoods, we used a symmetric bidirectional case-crossover design with a conditional logistic regression model. We analyzed data from 2 million ER visits for MDs between 2005 and 2016 across 17 cities in New York State, where redlining policies were historically implemented. A stratified analysis was performed to examine potential effect modification by individuals' demographic characteristics (sex, age, and race/ethnicity) and ambient temperature. We found that both PM2.5 and NO2 were significantly associated with MD-related ER visits primarily in redlined neighborhoods. Per 10μgm-3 increase in daily PM2.5 and per 10 ppb increase in NO2 concentration were associated with 1.04 % (95 % Confidence Interval (CI): 0.57 %, 1.50 %) and 0.44 % (95 % CI: 0.21 %, 0.67 %) increase in MD-related ER visits in redlined neighborhoods, respectively. We also found significantly greater susceptibility among younger persons (below 18 years old) and adults aged 35-64 among residents in grade C or D, but not in A or B. Furthermore, we found that positive and statistically significant associations between increases in air pollutants (PM2.5 and NO2) and MD-related ER visits exist during medium temperatures (4.90 °C to 21.11 °C), but not in low or high temperature. Exposures to both PM2.5 and NO2 were significantly associated with MD-related ER visits, but these adverse effects were disproportionately pronounced in redlined neighborhoods.

Exploring Gut–Brain Interaction Disorders: Mechanisms and Translational Therapies Crossing Neurology to Gastroenterology

The bidirectional communication network between the gut and the brain, known as the gut–brain axis, plays a crucial role in health and disease. This review explores the mechanisms underlying gut–brain interaction disorders and highlights translational therapies bridging neurology and gastroenterology. Mechanisms encompass anatomical, endocrine, humoral, metabolic, and immune pathways, with the gut microbiota exerting profound influence. Clinical evidence links gut microbiota fluctuations to mood disorders, GI disruptions, and neurodevelopmental conditions, emphasizing the microbiome’s pivotal role in shaping brain–gut interactions. Pharmacological therapies such as amitriptyline and selective serotonin reuptake inhibitors modulate neurotransmitter activity, offering relief in functional gastrointestinal disorders like irritable bowel syndrome (IBS). Non-pharmacological interventions like cognitive–behavioral therapy and hypnotherapy address maladaptive thoughts and induce relaxation, alleviating gastrointestinal symptoms exacerbated by stress. Emerging therapies include gut microbiota modulation, dietary interventions, vagus nerve stimulation, and intestinal barrier modulation, offering novel approaches to manage neurological disorders via the gastrointestinal tract. Understanding and harnessing the gut–brain axis holds promise for personalized therapeutic strategies in neurogastroenterology.

Associations between short-term exposure to air pollution and thyroid function in a representative sample of the Korean population

BACKGROUND

Disruption of thyroid function can profoundly affect various organ systems. However, studies on the association between air pollution and thyroid function are relatively scarce and most studies have focused on the long-term effects of air pollution among pregnant women.

OBJECTIVES

This study aimed to explore the associations between short-term exposure to air pollution and thyroid function in the general population.

METHODS

Data from the Korea National Health and Nutrition Examination Survey (2013-2015) were analyzed (n = 5,626). Air pollution concentrations in residential addresses were estimated using Community Multiscale Air Quality models. The moving averages of air pollution over 7 days were set as exposure variables through exploratory analyses. Linear regression and quantile g-computation models were constructed to assess the effects of individual air pollutants and air pollution mixture, respectively.

RESULTS

A 10-ppb increase in NO2 (18.8-μg/m3 increase) and CO (11.5-μg/m3 increase) was associated with 2.43% [95% confidence interval (CI): 0.42, 4.48] and 0.19% (95% CI: 0.01, 0.36) higher thyroid-stimulating hormone (TSH) levels, respectively. A 10-μg/m3 increase in PM2.5 and a 10-ppb increase in O3 (19.6-μg/m3 increment) were associated with 0.87% (95% CI: 1.47, -0.27) and 0.59% (95% CI: 1.18, -0.001) lower free thyroxine (fT4) levels, respectively. A simultaneous quartile increase in PM2.5, NO2, O3, and CO levels was associated with lower fT4 but not TSH levels.

CONCLUSIONS

As the subtle changes in thyroid function can affect various organ systems, the present results may have substantial public health implications despite the relatively modest effect sizes. Because this was a cross-sectional study, it is necessary to conduct further experimental or repeated-measures studies to consolidate the current results.

Potential Early Effect Biomarkers for Ambient Air Pollution Related Mental Disorders

Air pollution is one of the greatest environmental risks to health, with 99% of the world's population living where the World Health Organization's air quality guidelines were not met. In addition to the respiratory and cardiovascular systems, the brain is another potential target of air pollution. Population- and experiment-based studies have shown that air pollution may affect mental health through direct or indirect biological pathways. The evidence for mental hazards associated with air pollution has been well documented. However, previous reviews mainly focused on epidemiological associations of air pollution with some specific mental disorders or possible biological mechanisms. A systematic review is absent for early effect biomarkers for characterizing mental health hazards associated with ambient air pollution, which can be used for early warning of related mental disorders and identifying susceptible populations at high risk. This review summarizes possible biomarkers involved in oxidative stress, inflammation, and epigenetic changes linking air pollution and mental disorders, as well as genetic susceptibility biomarkers. These biomarkers may provide a better understanding of air pollution's adverse effects on mental disorders and provide future research direction in this arena.