Airborne pollen and suicide mortality in Tokyo, 2001-2011

VINDICATE-P: A Mnemonic for the Many Comorbidities of Atopic Dermatitis

Patients with atopic dermatitis (AD) are at increased risk of atopic and non-atopic comorbidities. In fact, the Hanifin and Rajka criteria include allergic and infectious comorbidities as a minor criterion. Despite the well-recognized list of comorbidities, the past 15 years greatly expanded the list of recognized comorbidities of AD. This narrative review focuses on comorbidities of AD using a mnemonic, VINDICATE-P: vascular/cardiovascular, infectious, neoplastic and neurologic, degenerative, iatrogenic, congenital, atopic and autoimmune, traumatic, endocrine/metabolic, and psychiatric. The comorbidities of AD vary by age. More research is needed into the mechanisms of comorbidities and optimal screening strategies in AD patients.

Forecasting daily total pollen concentrations on a global scale

BACKGROUND

There is evidence that global anthropogenic climate change may be impacting floral phenology and the temporal and spatial characteristics of aero-allergenic pollen. Given the extent of current and future climate uncertainty, there is a need to strengthen predictive pollen forecasts.

METHODS

The study aims to use CatBoost (CB) and deep learning (DL) models for predicting the daily total pollen concentration up to 14 days in advance for 23 cities, covering all five continents. The model includes the projected environmental parameters, recent concentrations (1, 2 and 4 weeks), and the past environmental explanatory variables, and their future values.

RESULTS

The best pollen forecasts include Mexico City (R2(DL_7) ≈ .7), and Santiago (R2(DL_7) ≈ .8) for the 7th forecast day, respectively; while the weakest pollen forecasts are made for Brisbane (R2(DL_7) ≈ .4) and Seoul (R2(DL_7) ≈ .1) for the 7th forecast day. The global order of the five most important environmental variables in determining the daily total pollen concentrations is, in decreasing order: the past daily total pollen concentration, future 2 m temperature, past 2 m temperature, past soil temperature in 28-100 cm depth, and past soil temperature in 0-7 cm depth. City-related clusters of the most similar distribution of feature importance values of the environmental variables only slightly change on consecutive forecast days for Caxias do Sul, Cape Town, Brisbane, and Mexico City, while they often change for Sydney, Santiago, and Busan.

CONCLUSIONS

This new knowledge of the ecological relationships of the most remarkable variables importance for pollen forecast models according to clusters, cities and forecast days is important for developing and improving the accuracy of airborne pollen forecasts.

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

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

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

Climate change and allergic diseases: An overview

Climate change has been regarded as a threat to the human species on the earth. Greenhouse gasses are leading to increased temperatures on Earth besides impacting the humanity. These atmospheric conditions have shown to alter the release pattern of pollens and can change the timing and magnitude of pollen release with flowering plants. As pollen is responsible for respiratory allergies in humans, so climate change can adversely affect human health in susceptible individuals. In this review, we highlight the association between climate change, increased prevalence and severity of asthma, and related allergic diseases. Increased air pollution can alter the production of local and regional pollen. This altered pattern depends on bioclimatic parameters. As simulated with a pollen-release model and future bioclimatic data, warmer temperatures lead to an increased pollen count in some specific locations and for longer periods. Thus, anticipation of a future allergic disease burden can help public health agencies in planning to develop strategies in mitigating the unprecedented health challenges expected in future years.

Association of short-term particulate matter exposure with suicide death among major depressive disorder patients: a time-stratified case-crossover analysis

There is growing evidence that suggests a potential association between particulate matter (PM) and suicide. However, it is unclear that PM exposure and suicide death among major depressive disorder (MDD) patients, a high-risk group for suicide. We aimed to assess the effect of short-term exposure to PM on the risk of suicide in MDD patients who are at high risk for suicide. We investigated the risk of suicide among 922,062 newly-diagnosed MDD patients from 2004 to 2017 within the Korean National Health Insurance Service (NHIS) database. We identified 3,051 suicide cases from January 1, 2015, to December 31, 2017, within the death statistics database of the Korean National Statistical Office. PMs with aerodynamic diameter less than 2.5 μm (PM2.5), less than 10 μm (PM10), and 2.5–10 μm (PM2.5–10) were considered, which were provided from the National Ambient Air Monitoring System in South Korea. Time-stratified case-crossover analysis was performed to investigate the association of particulate matter exposure to suicide events. The risk of suicide was significantly high upon the high level of exposure to PM2.5, PM2.5–10 (coarse particle) and PM10 on lag 1 (p for trend < 0.05). Short-term exposure to a high level of PM was associated with an elevated risk for suicide among MDD patients. There is a clear dose–response relationship between short-term PM exposures with suicide death among MDD patients. This result will be used as an essential basis for consideration when establishing an air pollution alarm system for reducing adverse health outcomes by PM.

Investigating relationship between particulate matter air concentrations and suicides using geographic information system

Exposure to particulate matter is an important risk factor for mental health disturbances and overall mortality. However, the knowledge on relationship between long-term particulate matter level and suicide rate is limited and requires in-depth study. Population and air pollution data were obtained from the Polish Central Statistics Office and Chief Inspectorate of Environmental Protection for the period 2014-2015. Aspatial multivariate and one factor regression analysis were performed and followed by spatial global regression analysis for district reference units in geographic information system (GIS). At the district level of aggregation, data showed spatial stationarity. The best-fitting spatial global model was based on number of disorders caused by the use of psychoactive substances, number of people treated in psychiatric hospitals, population density, unemployment rate and per capita income. Global spatial model with PM2.5 level parameter was an improvement over the one without it (adj. R2 = 0.87 compared to adj. R2 = 0.83). There is a positive relationship between particular matter concentrations and suicides in Poland. Application of Geographic Information Science analytical functions in medicine can be viewed as a new efficient methodological approach.

Variations in airborne pollen and spores in urban Guangzhou and their relationships with meteorological variables

Airborne pollen causes various types of allergies in humans, and the extent of allergic infection is related to the presence of different types of sporo-pollen and existing meteorological conditions in a certain area. Therefore, an aeropalynological study of 72 airborne samples with a hydrofluoric acid (HF) treatment was conducted in the Haizhu district of Guangzhou, China, in 2016, to identify the temporal variations in airborne sporo-pollen and the relationship between airborne sporo-pollen concentrations and different meteorological variables in Guangzhou, China. Forty-five types of airborne pollen, seven types of airborne spores, and some undetermined sporo-pollen taxa were identified with two separate plant habitats occurring during this period (from January to December 2016): arboreal pollen (tree-based) and non-arboreal pollen (herb, shrub, aquatic, liane, etc.). Furthermore, the daily records of four key meteorological variables (temperature, precipitation, relative humidity, and wind speed) were acquired to distinguish the pollen seasons and correlated with Spearman's rho test to establish a pollen-weather data book with the seasonal variations. The two leading seasons were identified based on pollen abundance: spring and autumn. Among them, the primary dominant sporo-pollen families during the spring season were Poaceae, Pinaceae, Euphorbiaceae, Moraceae, Microlepia sp., and Polypodiaceae. Conversely, Artemisia sp., Asteraceae, Cyperaceae, Poaceae, Alnus sp., Corylus sp., Myrtaceae, and Rosaceae were the dominant pollen species during autumn. However, few pollen grains were identified in January, May-July, and December. The statistical analysis revealed that temperature had both positive and negative correlations with sporo-pollen concentrations. However, precipitation and relative humidity had a strong impact on the sporo-pollen dispersion and exhibited a negative correlation with the sporo-pollen concentrations. The wind speed had a positive but strong correlation with the sporo-pollen concentration during the study period. Some inconsistent results were found due to environmental variations, vegetation type, and climate change around the study area. This study will facilitate the identification of pollen seasons to prevent the occurrence of pollen-related allergies in the Guangzhou city area.

Short-term exposures to atmospheric evergreen, deciduous, grass, and ragweed aeroallergens and the risk of suicide in Ohio, 2007-2015: Exploring disparities by age, gender, and education level

BACKGROUND

Seasonal trends in suicide mortality are observed worldwide, potentially aligning with the seasonal release of aeroallergens. However, only a handful of studies have examined whether aeroallergens increase the risk of suicide, with inconclusive results thus far. The goal of this study was to use a time-stratified case-crossover design to test associations of speciated aeroallergens (evergreen, deciduous, grass, and ragweed) with suicide deaths in Ohio, USA (2007-2015).

METHODS

Residential addresses for 12,646 persons who died by suicide were linked with environmental data at the 4-25 km grid scale including atmospheric aeroallergen concentrations, maximum temperature, sunlight, particulate matter <2.5 μm, and ozone. A case-crossover design was used to examine same-day and 7-day cumulative lag effects on suicide. Analyses were stratified by age group, gender, and educational level.

RESULTS

In general, associations were null between aeroallergens and suicide. Stratified analyses revealed a relationship between grass pollen and same-day suicide for women (OR = 3.84; 95% CI = 1.44, 10.22) and those with a high school degree or less (OR = 2.03; 95% CI = 1.18, 3.49).

CONCLUSIONS

While aeroallergens were generally not significantly related to suicide in this sample, these findings provide suggestive evidence for an acute relationship of grass pollen with suicide for women and those with lower education levels. Further research is warranted to determine whether susceptibility to speciated aeroallergens may be driven by underlying biological mechanisms or variation in exposure levels.

Toxoplasma gondii, Suicidal Behavior, and Intermediate Phenotypes for Suicidal Behavior

Within the general literature on infections and suicidal behavior, studies on Toxoplasma gondii (T. gondii) occupy a central position. This is related to the parasite's neurotropism, high prevalence of chronic infection, as well as specific and non-specific behavioral alterations in rodents that lead to increased risk taking, which are recapitulated in humans by T. gondii's associations with suicidal behavior, as well as trait impulsivity and aggression, mental illness and traffic accidents. This paper is a detailed review of the associations between T. gondii serology and suicidal behavior, a field of study that started 15 years ago with our publication of associations between T. gondii IgG serology and suicidal behavior in persons with mood disorders. This "legacy" article presents, chronologically, our primary studies in individuals with mood disorders and schizophrenia in Germany, recent attempters in Sweden, and in a large cohort of mothers in Denmark. Then, it reviews findings from all three meta-analyses published to date, confirming our reported associations and overall consistent in effect size [ranging between 39 and 57% elevation of odds of suicide attempt in T. gondii immunoglobulin (IgG) positives]. Finally, the article introduces certain links between T. gondii and biomarkers previously associated with suicidal behavior (kynurenines, phenylalanine/tyrosine), intermediate phenotypes of suicidal behavior (impulsivity, aggression) and state-dependent suicide risk factors (hopelessness/dysphoria, sleep impairment). In sum, an abundance of evidence supports a positive link between suicide attempts (but not suicidal ideation) and T. gondii IgG (but not IgM) seropositivity and serointensity. Trait impulsivity and aggression, endophenotypes of suicidal behavior have also been positively associated with T. gondii seropositivity in both the psychiatrically healthy as well as in patients with Intermittent Explosive Disorder. Yet, causality has not been demonstrated. Thus, randomized interventional studies are necessary to advance causal inferences and, if causality is confirmed, to provide hope that an etiological treatment for a distinct subgroup of individuals at an increased risk for suicide could emerge.

Increased brain vitamin D receptor expression and decreased expression of cathelicidin antimicrobial peptide in individuals who died by suicide

Vitamin D deficiency is associated with immune dysregulation, increased vulnerability to infections, depression, and suicidal behavior. One mediator of vitamin D-dependent immune regulation and antimicrobial defense is the cathelicidin antimicrobial peptide (LL-37), encoded by the cathelicidin-related antimicrobial peptide (CRAMP) gene. We compared the mRNA expression of the CRAMP gene, the vitamin D receptor (VDR) gene, as well as the CYP27B1 and CYP24A1 genes (involved in vitamin D metabolism) in the dorsolateral prefrontal cortex (dlPFC) and anterior cingulate cortex (ACC) between depressed individuals who died by suicide (n = 15) and matched (age, gender, and post-mortem interval) non-psychiatric controls (n = 15). Gene expression was measured through qRT-PCR with TaqMan® primers and probes, with GAPDH and β-actin genes as endogenous controls. Statistical analyses included t-tests and Pearson correlations. CRAMP mRNA expression was downregulated and VDR mRNA expression was upregulated in both dlPFC and ACC in suicides relative to controls, with no significant differences in expression of CYP24A1 and CYP27B1. To our knowledge, this is the first study on brain cathelicidin expression in the human brain in relationship to suicide. Increased VDR and decreased CRAMP expression are consistent with previously reported associations between vitamin D deficiency, immune dysregulation, and suicidal behavior, and should lead to future studies uncovering novel interactive targets for suicide prevention.

Mood Worsening on Days with High Pollen Counts is associated with a Summer Pattern of Seasonality

Background:

Summer/spring-type seasonal affective disorder (S-SAD) is the less common subtype of seasonal affective disorder and evidence regarding potential triggers of S-SAD is scarce. Recent reports support association of airborne-pollen with seasonal exacerbation of depression (mood seasonality) and timing of suicidal behavior. Therefore, we hypothesized that Old Order Amish (OOA) with summer/spring pattern of seasonality (abbreviated as summer pattern) and S-SAD will have significant mood worsening on high pollen days.

Methods:

A seasonal pattern of mood worsening and SAD parameters were estimated using Seasonal Pattern Assessment Questionnaire (SPAQ). Age- and gender-adjusted ANCOVAs and post hoc analyses were conducted to compare mood worsening on days with high pollen counts between summer-pattern vs no-summer-pattern of mood worsening, S-SAD vs no-S-SAD, winter-pattern vs no-winter-pattern of mood worsening, and W-SAD vs no-W-SAD groups.

Results:

The prevalence of S-SAD was 0.4%, while 4.5% of individuals had a summer pattern of mood seasonality. A statistically significant difference for mood worsening on high pollen days was observed between summer-pattern vs no-summer-pattern of mood worsening (p = 0.006). The significant association between S-SAD vs no-SAD groups (p = 0.032) for mood worsening on high pollen days did not withstand Bonferroni adjustment for multiple comparisons. No significant association was found for winter-pattern vs no-winter-pattern of mood worsening (p = 0.61) and for W-SAD vs no-W-SAD (p = 0.19) groups.

Conclusion:

Our results are consistent with previous studies implicating links between aeroallergen exposure and summer pattern of seasonality, but not the winter pattern of seasonality.

Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters

Approximately 50 million Americans have allergic diseases. Airborne plant pollen is a significant trigger for several of these allergic diseases. Ambrosia (ragweed) is known for its abundant production of pollen and its potent allergic effect in North America. Hence, estimating and predicting the daily atmospheric concentration of pollen (ragweed pollen in particular) is useful for both people with allergies and for the health professionals who care for them. In this study, we show that a suite of variables including meteorological and land surface parameters, as well as next-generation radar (NEXRAD) measurements together with machine learning can be used to estimate successfully the daily pollen concentration. The supervised machine learning approaches we used included random forests, neural networks, and support vector machines. The performance of the training is independently validated using 10% of the data partitioned using the holdout cross-validation method from the original dataset. The random forests (R= 0.61, R²= 0.37), support vector machines (R= 0.51, R²= 0.26), and neural networks (R= 0.46, R²= 0.21) effectively predicted the daily Ambrosia pollen, where the correlation coefficient (R) and R-squared (R²) values are given in brackets. Three independent approaches-the random forests, correlation coefficients, and interaction information-were employed to rank the relative importance of the available predictors.

Allergic rhinitis: Disease characteristics and coping measures in Saudi Arabia

BACKGROUND

Despite allergic rhinitis (AR) being a highly prevalent disease, according to literature, it is often underdiagnosed or undertreated.

AIM

This study explored the disease characteristics of AR in the Saudi community and the non-conventional coping measures used to alleviate symptoms.

METHODS

The study was a nationwide cross-sectional study, using a self-report electronic survey distributed via social media networks in 2018. The survey included an explanatory letter and consent. The sample size comprised 3,458 participants and 2,849 adults had at least one of the four signs of AR, i.e. watery-nose, sneezing, nasal obstruction, itchy nose, watery eyes, in the past year, not related to cold/flu. The outcomes of the study were the triggers, pattern, severity and the classification of AR (2016 ARIA guidelines) and coping measures. Descriptive statistics, univariate analytic statistics and binary logistic regression analyses were conducted. The P-value was considered statistically significant at <0.05.

RESULTS

The leading reported trigger of AR was dust (74%, n = 2118), followed by pollen (17%, n = 477), mold (5%, n = 140) and fur (4%, n = 114). The prevalence of intermittent AR was (54%, n = 1,635), while that of persistent AR was (46%, n = 1,314). Almost one-third (34%, n = 959) complained of mild forms of AR, while others complained of moderate to severe forms (66%, n = 1890). The coping measures were mainly shower/humidification 368(12.9%) and herbal hot drinks 266(9.3%). Older participants (adj.OR = 1.3[1.1-1.5]) and overweight participants, (adj.OR = 1.2[1.1-1.4]) reported more persistent forms of rhinitis compared to their counter groups, (adj.P<0.001 and adj.P = 0.032) respectively. Female participants (adj.OR = 0.8[0.7-0.9]) had significantly milder forms of AR, in comparison to males, adj.P = 0.006.

CONCLUSION

This study presented the disease characteristics of self-reported AR and its associated factors in Saudi Arabia. Special attention should be paid to older age groups and overweight patients who reported persistent forms of AR. Males reported more severe and persistent forms of AR.

Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Ambrosia Pollen

Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely alerts. This study presents a method for the robust estimation of the concentration of airborne Ambrosia pollen using a suite of machine learning approaches including deep learning and ensemble learners. Each of these machine learning approaches utilize data from the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric weather and land surface reanalysis. The machine learning approaches used for developing a suite of empirical models are deep neural networks, extreme gradient boosting, random forests and Bayesian ridge regression methods for developing our predictive model. The training data included twenty-four years of daily pollen concentration measurements together with ECMWF weather and land surface reanalysis data from 1987 to 2011 is used to develop the machine learning predictive models. The last six years of the dataset from 2012 to 2017 is used to independently test the performance of the machine learning models. The correlation coefficients between the estimated and actual pollen abundance for the independent validation datasets for the deep neural networks, random forest, extreme gradient boosting and Bayesian ridge were 0.82, 0.81, 0.81 and 0.75 respectively, showing that machine learning can be used to effectively forecast the concentrations of airborne pollen.

Inflammation as a unique marker of suicide ideation distinct from depression syndrome among U.S. adults

BACKGROUND

Recent evidence suggests that pro-inflammatory states may be independently associated with the risk of suicidality, above and beyond depression. This study assesses whether four indicators of inflammation, circulating levels of C-reactive protein (CRP), white blood cell (WBC) count and immunoglobulin E (IgE), and dietary inflammatory potential, measured using the Dietary Inflammatory Index® (DII), distinguish suicidal ideation (SI) from major depression (MD).

METHODS

Data come from multiple cycles of the US National Health and Nutrition Examination Survey (NCRP&WBC = 13,912; NDII = 17,076; NIgE = 4,060). MD was measured using the Patient Health Questionnaire-9 (PHQ-9); SI was indicated by the last item of the PHQ-9. To assess SI independent from MD, participants were classified into four categories: SI with MD, SI without MD, MD without SI, and neither MD nor SI. Regression models were used to assess the relationship between indicators of inflammation and SI with and without MD.

RESULTS

None of the inflammatory indicators were able to distinguish SI status among MD cases. DII was associated with SI among individuals without MD. CRP, DII, and WBC were associated with MD. No associations were found for IgE.

LIMITATIONS

Cross-section data prevent drawing causal conclusions. Underreporting of MD and suicidal ideation and measurement of habitual diet using 24 h dietary recalls are also weaknesses.

CONCLUSION

Dietary inflammatory potential was associated with suicide ideation among US adults with and without depression. Diet may play a role in suicide ideation and more empirical evidence is needed to determine whether nutritional protocols could aid in the treatment of suicidal behaviors. Findings did not support inflammatory factors having a relationship with suicide ideation distinct from depression.

Seasonal Allergies and Psychiatric Disorders in the United States

Seasonal allergies have been associated with mental health problems, though the evidence is still emergent, particularly in the United States. We analyzed data from the National Comorbidity Survey Replication and the National Latino and Asian American Survey (years 2001–2003). Multivariable logistic regression models were used to examine the relations between lifetime allergies and lifetime psychiatric disorders (each disorder in a separate model), adjusting for socio-demographic variables (including region of residence) and tobacco use. Analyses were also stratified to test for effect modification by race and sex. A history of seasonal allergies was associated with greater odds of mood disorders, anxiety disorders, and eating disorders, but not alcohol or substance use disorders, after adjusting for socio-demographic characteristics and tobacco use. The associations between seasonal allergies and mood disorders, substance use disorders, and alcohol use disorders were particularly strong for Latino Americans. The association between seasonal allergies and eating disorders was stronger for men than women. Seasonal allergies are a risk factor for psychiatric disorders. Individuals complaining of seasonal allergies should be screened for early signs of mental health problems and referred to specialized services accordingly.

Toward dynamic urban environmental exposure assessments in mental health research

It is increasingly recognized that mental disorders are affected by both personal characteristics and environmental exposures. The built, natural, and social environments can either contribute to or buffer against metal disorders. Environmental exposure assessments related to mental health typically rely on neighborhoods within which people currently live. In this article, I call into question such neighborhood-based exposure assessments at one point in time, because human life unfolds over space and across time. To circumvent inappropriate exposure assessments and to better grasp the etiologies of mental disease, I argue that people are exposed to multiple health-supporting and harmful exposures not only during their daily lives, but also over the course of their lives. This article aims to lay a theoretical foundation elucidating the impact of dynamic environmental exposures on mental health outcomes. I examine, first, the possibilities and challenges for mental health research to integrate people's environmental exposures along their daily paths and, second, how exposures over people's residential history might affect mental health later in life. To push the borders of scientific inquiries, I stress that only such mobility-based approaches facilitate an exploration of exposure duration, exposure sequences, and exposure accumulation.

Air pollution, aeroallergens and suicidality: a review of the effects of air pollution and aeroallergens on suicidal behavior and an exploration of possible mechanisms

OBJECTIVE

Risk factors for suicide can be broadly categorized as sociodemographic, clinical and treatment. There is interest in environmental risk and protection factors for suicide. Emerging evidence suggests a link between environmental factors in the form of air pollution and aeroallergens in relation to suicidality.

METHODS

Herein, we conducted a systematic review of 15 articles which have met inclusion criteria on the aforementioned effects.

RESULTS

The majority of the reviewed articles reported an increased suicide risk alongside increased air pollutants or aeroallergens (i.e. pollen) increase; however, not all environmental factors were explored equally. In specific, studies that were delimited to evaluating particulate matter (PM) reported a consistent association with suicidality. We also provide a brief description of putative mechanisms (e.g. inflammation and neurotransmitter dysregulation) that may mediate the association between air pollution, aeroallergens and suicidality.

CONCLUSION

Available evidence suggests that exposure to harmful air quality may be associated with suicidality. There are significant public health implications which are amplified in regions and countries with greater levels of air pollution and aeroallergens. In addition, those with atopic sensitivity may represent a specific subgroup that is at risk.