Short-term effect of apparent temperature on daily emergency visits for mental and behavioral disorders in Beijing, China: A time-series study

Exploring perceived relationships between weather, climate and mental health: biometeorological perspectives of healthcare practitioners

Over the last decade, there has been an increase in research examining the influence of weather and climate in mental health caseloads. Variations in temperature, sunshine hours, cloud cover, precipitation and extreme weather events have been statistically linked to diagnoses and increases in hospital admissions for several mental health conditions. This study aimed to explore whether mental health practitioners perceive there to be a link between mental health and daily, seasonal, or inter-annual shifts in various climate variables in South Africa, and the timing and causal mechanisms thereof. Semi-structured interviews were conducted with 50 practicing healthcare practitioners, and the data was analysed using thematic analysis. The findings of this research show that all 50 participants were aware of the link between weather, climate and mental health, primarily through their awareness of seasonal affective disorder. Of the 50 participants, 38 participants could explain the aetiology of seasonal affective disorder. Participants perceived sunlight and temperature to exert an influence on mental health. All 50 participants perceived exposure to sunlight to exert a positive influence on several mental health conditions. Of the 50 participants, 36 participants perceived increases in temperature to exert an adverse effect on mental health symptomology. A minority of 11 participants perceived precipitation to influence mental health conditions such as seasonal affective disorder, bipolar disorder, and substance abuse disorder. Participants' perceptions of the influence of precipitation on mental health provided a unique potential explanation of this relationship, which, at the time of writing, has not been discussed in formal research.

Global climate change: Effects of future temperatures on emergency department visits for mental disorders in Beijing, China

Rising temperatures can increase the risk of mental disorders. As climate change intensifies, the future disease burden due to mental disorders may be underestimated. Using data on the number of daily emergency department visits for mental disorders at 30 hospitals in Beijing, China during 2016-2018, the relationship between daily mean temperature and such visits was assessed using a quasi-Poisson model integrated with a distributed lag nonlinear model. Emergency department visits for mental disorders attributed to temperature changes were projected using 26 general circulation models under four climate change scenarios. Stratification analyses were then conducted by disease subtype, sex, and age. The results indicate that the temperature-related health burden from mental disorders was projected to increase consistently throughout the 21st century, mainly driven by high temperatures. The future temperature-related health burden was higher for patients with mental disorders due to the use of psychoactive substances and schizophrenia as well as for women and those aged <65 years. These findings enhance our knowledge of how climate change could affect mental well-being and can be used to advance and refine targeted approaches to mitigating and adapting to climate change with a view on addressing mental disorders.

The impact of apparent temperature on the emergency visits for traumatic fractures in Hangzhou, China

BACKGROUND

Traumatic fractures occur frequently worldwide. However, research remains limited on the association between short-term exposure to temperature and traumatic fractures. This study aims to explore the impact of apparent temperature (AT) on emergency visits (EVs) due to traumatic fractures.

METHODS

Based on EVs data for traumatic fractures and the contemporary meteorological data, a generalized Poisson regression model along with a distributed lag nonlinear model (DLNM) were undertaken to determine the impact of AT on traumatic fracture EVs. Subgroup analysis by gender and age and sensitivity analysis were also performed.

RESULTS

A total of 25,094 EVs for traumatic fractures were included in the study. We observed a wide "J"-shaped relationship between AT and risk of traumatic fractures, with AT above 9.5 °C positively associated with EVs due to traumatic fractures. The heat effects became significant at cumulative lag 0-11 days, and the relative risk (RR) for moderate heat (95th percentile, 35.7 °C) and extreme heat (99.5th percentile, 38.8 °C) effect was 1.311 (95% CI: 1.132-1.518) and 1.418 (95% CI: 1.191-1.688) at cumulative lag 0-14 days, respectively. The cold effects were consistently non-significant on single or cumulative lag days across 0-14 days. The heat effects were higher among male and those aged 18-65 years old. The sensitivity analysis results remained robust.

CONCLUSION

Higher AT is associated with cumulative and delayed higher traumatic fracture EVs. The male and those aged 18-65 years are more susceptible to higher AT.

Short-term effects of temperature-related indices on emergency ambulance dispatches due to mental and behavioral disorders in Shenzhen, China

Introduction

The precise associations between temperature-related indices and mental and behavioral disorders (MBDs) have yet to be fully elucidated. Our study aims to ascertain the most effective temperature-related index and assess its immediate impact on emergency ambulance dispatches (EADs) due to MBDs in Shenzhen, China.

Methods

EADs data and meteorological data from January 1, 2013, to December 31, 2020, in Shenzhen were collected. Distributed lag non-linear models (DLNMs) were utilized to examine the non-linear and lagged effects of temperature-related indices on EADs due to MBDs. The Quasi Akaike Information criterion (QAIC) was used to determine the optimal index after standardizing temperature-related indices. After adjusting for confounding factors in the model, we estimated the immediate and cumulative effects of temperature on EADs due to MBDs.

Results

The analysis of short-term temperature effects on EADs due to MBDs revealed Humidex as the most suitable index. Referring to the optimal Humidex (3.2th percentile, 12.00°C), we observed a significant effect of Humidex over the threshold (34.6th percentile, 26.80°C) on EADs due to MBDs at lag 0-5. The cumulative relative risks for high temperature (90th percentile, 41.90°C) and extreme high temperature (99th percentile, 44.20°C) at lag 0-5 were 1.318 (95% CI: 1.159-1.499) and 1.338 (95% CI: 1.153-1.553), respectively. No significant cold effect was observed on EADs due to MBDs.

Conclusion

High Humidex was associated with more EADs due to MBDs in subtropical regions. Health authorities should implement effective measures to raise public awareness of risks related to high temperature and protect vulnerable populations.

High ambient temperature may increase the risk of anemia in pregnancy: Identifying susceptible exposure windows

Anemia in pregnancy (AIP) is associated with multiple severe maternal and perinatal adverse outcomes. However, there is a lack of evidence on the association between environmental factors and AIP. Aim to explore the association between ambient temperature and the risk of AIP, and identify susceptible exposure windows, we conducted a matched case-control study from 2013 to 2016 in Xi'an, China, which included 710 women with AIP and 1420 women without AIP. The conditional logistic regression model was used to evaluate the association between ambient temperature and AIP at different gestational weeks and gestational months. The association between extreme temperature and AIP was evaluated using the distributed lag nonlinear model (DLNM). We conducted stratified analyses of age, parity, and season of conception, and estimated the interaction between ambient temperature and air pollutants on AIP. Ambient temperature was significantly positively associated with the risk of AIP, and the susceptible exposure windows were 2-25 gestational weeks and 1-6 gestational months, respectively. The strongest effect was observed in the week 8 and month 2, for each 1 °C increase in weekly and monthly mean temperature, the odds ratio (OR) for AIP was 1.038 (95 % confidence interval (CI): 1.022, 1.055) and 1.040 (95 % CI: 1.020, 1.060), respectively. Extreme heat may increase the risk of AIP. Stratified analyses showed that there was no significant difference among different age, parity, and season of conception groups. No significant interaction effect of ambient temperature with air pollution on AIP was found. In summary, high ambient temperature may increase the risk of AIP, and the first and second trimesters may be susceptible exposure windows. Understanding the effect of temperature on pregnant women will be beneficial to reduce the occurrence of AIP.

The relationship between hot temperatures and hospital admissions for psychosis in adults diagnosed with schizophrenia: A case-crossover study in Quebec, Canada

INTRODUCTION

Some studies have found hot temperatures to be associated with exacerbations of schizophrenia, namely psychoses. As climate changes faster in Northern countries, our understanding of the association between temperature and hospital admissions (HA) for psychosis needs to be deepened.

OBJECTIVES

1) Among adults diagnosed with schizophrenia, measure the relationship between mean temperatures and HAs for psychosis during summer. 2) Determine the influence of individual and ecological characteristics on this relationship.

METHODS

A cohort of adults diagnosed with schizophrenia (n = 30,649) was assembled using Quebec's Integrated Chronic Disease Surveillance System (QICDSS). The follow-up spanned summers from 2001 to 2019, using hospital data from the QICDSS and meteorological data from the National Aeronautics and Space Administration's (NASA) Daymet database. In four geographic regions of the province of Quebec, a conditional logistic regression was used for the case-crossover analysis of the relationship between mean temperatures (at lags up to 6 days) and HAs for psychosis using a distributed lag non-linear model (DLNM). The analyses were adjusted for relative humidity, stratified according to individual (age, sex, and comorbidities) and ecological (material and social deprivation index and exposure to green space) factors, and then pooled through a meta-regression.

RESULTS

The statistical analyses revealed a statistically significant increase in HAs three days (lag 3) after elevated mean temperatures corresponding to the 90th percentile relative to a minimum morbidity temperature (MMT) (OR 1.040; 95% CI 1.008-1.074), while the cumulative effect over six days was not statistically significant (OR 1.052; 95% IC 0.993-1.114). Stratified analyses revealed non statistically significant gradients of increasing HAs relative to increasing material deprivation and decreasing green space levels.

CONCLUSIONS

The statistical analyses conducted in this project showed the pattern of admissions for psychosis after hot days. This finding could be useful to better plan health services in a rapidly changing climate.

Association between air temperature and risk of hospitalization for genitourinary disorders: An environmental epidemiological study in Lanzhou, China

OBJECTIVES

The aim of this study was to investigate the relationship between air temperature and the risk of hospitalization for genitourinary disorders.

METHODS

Distributed lag non-linear models (DLNM) were used to estimate the association between air temperature and the risk of hospitalization for genitourinary disorders, with subgroup analysis by gender and age to identify the susceptible population of temperature-sensitive genitourinary system diseases.

RESULTS

Low mean temperature (MT) (RR = 2.001, 95% CI: 1.856~2.159), high MT (RR = 2.884, 95% CI: 2.621~3.173) and low diurnal temperature range (DTR) (RR = 1.619, 95% CI: 1.508~1.737) were all associated with the increased risk of hospitalization for genitourinary disorders in the total population analysis, and the high MT effect was stronger than the low MT effect. Subgroup analysis found that high MT was more strongly correlated in male (RR = 2.998, 95% CI: 2.623~3.427) and those <65 years (RR = 3.003, 95% CI: 2.670~3.344), and low DTR was more strongly correlated in female (RR = 1.669, 95% CI: 1.510~1.846) and those <65 years (RR = 1.643, 95% CI: 1.518~1.780).

CONCLUSIONS

The effect of high MT on the risk of hospitalization for genitourinary disorders is more significant than that of low MT. DTR was independently associated with the risk of hospitalization for genitourinary disorders.

Predictive Value of PRISMA-7, qSOFA, ESI, and CFS for 28-Day Mortality in Elderly Patients in the Emergency Department

Background

To explore the predictive value of the Programme on Research for Integrating Services for the Maintenance of Autonomy 7 (PRISMA-7), quick Sequential Organ Failure Assessment (qSOFA) score, Emergency Severity Index (ESI), and Clinical Frailty Scale (CFS) on the 28-day mortality risk in emergency elderly patients.

Methods

A multicenter prospective observational study was conducted to select elderly patients (≥65 years old) admitted to the emergency department of three Grade-A hospitals in different regions of China from January 2020 to March 2022. Primary data were collected at the time of admission. All patients were followed up for 28 days. The primary outcome was 28-day mortality. The predictive value of four scoring systems for 28-day mortality in elderly emergency patients was assessed by receiver operating characteristic (ROC) and logistic regression analysis.

Results

A total of 687 elderly emergency patients were enrolled, of whom 66 (9.61%) died within 28 days. Age, ICU admission rate, PRISMA-7, qSOFA, and CFS were significantly higher in the death group than in the survival group (P < 0.05), and ESI was lower than in the survival group (P < 0.001). The AUC for CFS was the largest of the four scoring systems at 0.80. According to the Youden index, the optimal cutoff values for PRISMA-7, qSOFA, ESI, and CFS were >3.5, >0.5, <2.5, and >4.5, respectively. Logistic regression revealed that qSOFA and CFS were the primary risk factors for increased 28-day mortality in elderly emergency patients (P < 0.001). The combined predictor L (L=X1+0.50X2, X1 and X2 are qSOFA and CFS values, respectively) had an AUC of 0.86 and a cutoff value >2.75.

Conclusion

PRISMA-7, qSOFA, ESI, CFS, and the combined qSOFA+CFS predictor were all effective predictors of 28-day mortality risk in elderly emergency patients, with the combined qSOFA+CFS predictor having the best predictive power.

Climate Change and Substance-Use Behaviors: A Risk-Pathways Framework

Climate change is undermining the mental and physical health of global populations, but the question of how it is affecting substance-use behaviors has not been systematically examined. In this narrative synthesis, we find that climate change could increase harmful substance use worldwide through at least five pathways: psychosocial stress arising from the destabilization of social, environmental, economic, and geopolitical support systems; increased rates of mental disorders; increased physical-health burden; incremental harmful changes to established behavior patterns; and worry about the dangers of unchecked climate change. These pathways could operate independently, additively, interactively, and cumulatively to increase substance-use vulnerability. Young people face disproportionate risks because of their high vulnerability to mental-health problems and substance-use disorders and greater number of life years ahead in which to be exposed to current and worsening climate change. We suggest that systems thinking and developmental life-course approaches provide practical frameworks for conceptualizing this relationship. Further conceptual, methodological, and empirical work is urgently needed to evaluate the nature and scope of this burden so that effective adaptive and preventive action can be taken.

Association between High Ambient Temperatures and Road Crashes in an Australian City with Temperate Climate: A Time-Series Study, 2012-2021

(1) Background: High ambient temperatures are associated with increased morbidity and mortality rates, and some evidence suggests that high temperatures increase the risk of road crashes. However, little is known regarding the burden of road crashes attributable to no-optimal high temperatures in Australia. Therefore, this study examined the effects of high temperatures on road crashes using Adelaide in South Australia as a case study. (2) Methods: Ten-year daily time-series data on road crashes (n = 64,597) and weather during the warm season (October-March) were obtained between 2012 and 2021. A quasi-Poisson distributed lag nonlinear model (DLNM) was used to quantify the cumulative effect of high temperatures over the previous five days. The associations and attributable burden at moderate and extreme temperature ranges were computed as relative risk (RR) and attributable fraction. (3) Results: There was a J-shaped association between high ambient temperature and the risk of road crashes during the warm season in Adelaide, and pronounced effects were observed for minimum temperatures. The highest risk was observed at a 1 day lag and lasting for 5 days. High temperatures were responsible for 0.79% (95% CI: 0.15-1.33%) of road crashes, with moderately high temperatures accounting for most of the burden compared with extreme temperatures (0.55% vs. 0.32%). (4) Conclusions: In the face of a warming climate, the finding draws the attention of road transport, policy, and public health planners to design preventive plans to reduce the risk of road crashes attributable to high temperatures.

Short-term effect of apparent temperature on daily hospitalizations for osteoporotic fractures in Beijing, China: A retrospective observational study

BACKGROUND

Studies on the associations between temperature and osteoporotic fractures (OF) hospitalizations are limited. This study aimed to assess the short-term effect of apparent temperature (AT) on the risk of OF hospitalizations.

METHODS

This retrospective observational study was conducted in Beijing Jishuitan Hospital from 2004 to 2021. Daily OF hospitalizations, meteorological variables and fine particulate matter were collected. A Poisson generalized linear regression model combined with a distributed lag non-linear model was applied to analyze the lag-exposure-response relationship between AT and the number of OF hospitalizations. Subgroup analysis by gender, age and fracture type was also conducted.

RESULTS

Total daily hospitalization visits for OF during the studied period were 35,595. The exposure-response curve of AT and OF presented a non-linear relationship, with optimum apparent temperature (OAT) at 28.40 °C. Taking OAT as the reference, the cold effect (-10.58 °C, 2.5th percentage) on single lag day had statistical significance from the current day of exposure (RR = 1.18, 95 % CI: 1.08-1.28) to lag 4 day (RR = 1.04, 95 % CI: 1.01-1.08), while the cumulative cold effect increased the risk of OF hospitalization visits from lag 0 to 14 days, with the maximum RR over lag 0-14 days (RR = 1.84, 95 % CI: 1.21-2.79). There were no significant risks of OF hospitalizations for warm effects (32.53 °C, 97.5th percentage) on single or cumulative lag days. The cold effect might be more evident among females, patients aged 80 years or older, and patients with hip fractures.

CONCLUSION

Exposure to cold temperatures is associated with an increased risk of OF hospitalizations. Females, patients aged 80 years or older and patients with hip fractures might be more vulnerable to the cold effect of AT.

The effect modification of extreme temperatures on mental and behavior disorders by environmental factors and individual-level characteristics in Canada

OBJECTIVE

Ambient extreme temperatures have been associated with mental and behavior disorders (MBDs). However, few studies have assesed whether vulnerability factors such as ambient air pollution, pre-existing mental health conditions and residential environmental factors increase susceptibility. This study aims to evaluate the associations between short-term variations in outdoor ambient extreme temperatures and MBD-related emergency department (ED) visits and how these associations are modified by vulnerability factors.

METHODS

We conducted a case-crossover study of 9,958,759 MBD ED visits in Alberta and Ontario, Canada made between March 1st, 2004 and December 31st, 2020. Daily average temperature was assigned to individual cases with ED visits for MBD using gridded data at a 1 km × 1 km spatial resolution. Conditional logistic regression was used to estimate associations between extreme temperatures (i.e., risk of ED visit at the 2.5th percentile temperature for cold and 97.5th percentile temperature for heat for each health region compared to the minimal temperature risk) and MBD ED visits. Age, sex, pre-existing mental health conditions, ambient air pollution (i.e. PM_2.5, NO₂ and O₃) and residential environmental factors (neighborhood deprivation, residential green space exposure and urbanization) were evaluated as potential effect modifiers.

RESULTS

Cumulative exposure to extreme heat over 0-5 days (odds ratio [OR] = 1.145; 95% CI: 1.121-1.171) was associated with ED visits for any MBD. However, cumulative exposure to extreme cold was associated with lower risk of ED visits for any MBD (OR = 0.981; 95% CI: 0.976-0.987). We also found heat to be associated with ED visits for specific MBDs such as substance use disorders, dementia, neurotic disorders, schizophrenia and personality behavior disorder. Individuals with pre-existing mental health conditions, those exposed to higher daily concentrations of NO₂ and O₃ and those residing in neighborhoods with greater material and social deprivation were at higher risk of heat-related MBD ED visits. Increasing tree canopy coverage appeared to mitigate risks of the effect of heat on MBD ED visits.

CONCLUSIONS

Findings provide evidence that the impacts of heat on MBD ED visits may vary across different vulnerability factors.

A Systematic Literature Review of the Impact of Climate Change on the Global Demand for Psychiatric Services

Climate Change (CC) imposes important global health risks, including on mental health (MH). They are related mostly to psychological suffering caused by climate-related events and to the heat-vulnerability caused by psychiatric disorders. This growing burden may press MH services worldwide, increasing demand on public and private systems in low-, middle-, and high-income countries. According to PRISMA, two independent reviewers searched four databases for papers published before May 2022 that associated climate-related events with healthcare demand for psychiatric conditions. Of the 7432 papers retrieved, we included 105. Only 29 were carried out in low- and middle-income countries. Twelve related the admission numbers to (i) extreme events, while 93 to (ii) meteorological factors-mostly heat. Emergency visits and hospitalizations were significantly higher during hot periods for MH disorders, especially until lag 5-7. Extreme events also caused more consultations. Suicide (completed or attempted), substance misuse, schizophrenia, mood, organic and neurotic disorders, and mortality were strongly affected by CC. This high healthcare demand is evidence of the burden patients may undergo. In addition, public and private services may face a shortage of financial and human resources. Finally, the increased use of healthcare facilities, in turn, intensifies greenhouse gas emissions, representing a self-enforcing cycle for CC. Further research is needed to better clarify how extreme events affect MH services and, in addition, if services in low- and middle-income countries are more intensely demanded by CC, as compared to richer countries.

Identifying joint impacts of sun radiation, temperature, humidity, and rain duration on triggering mental disorders using a high-resolution weather monitoring system

BACKGROUND

Mental disorders (MDs) are behavioral or mental patterns that cause significant distress or impairment of personal functioning. Previously, temperature has been linked to MDs, but most studies suffered from exposure misclassification due to limited monitoring sites. We aimed to assess whether multiple meteorological factors could jointly trigger MD-related emergency department (ED) visits in warm season, using a highly dense weather monitoring system.

METHODS

We conducted a time-stratified, case-crossover study. MDs-related ED visits (primary diagnosis) from May-October 2017-2018 were obtained from New York State (NYS) discharge database. We obtained solar radiation (SR), relative humidity (RH), temperature, heat index (HI), and rainfall from Mesonet, a real-time monitoring system spaced about 17 miles (126 stations) across NYS. We used conditional logistic regression to assess the weather-MD associations.

RESULTS

For each interquartile range (IQR) increase, both SR (excess risk (ER): 4.9%, 95% CI: 3.2-6.7%) and RH (ER: 4.0%, 95% CI: 2.6-5.4%) showed the largest risk for MD-related ED visits at lag 0-9 days. While temperature presented a short-term risk (highest ER at lag 0-2 days: 3.7%, 95% CI: 2.5-4.9%), HI increased risk over a two-week period (ER range: 3.7-4.5%), and rainfall hours showed an inverse association with MDs (ER: -0.5%, 95% CI: 0.9-(-0.1)%). Additionally, we observed stronger association of SR, RH, temperature, and HI in September and October. Combination of high SR, RH, and temperature displayed the largest increase in MDs (ER: 7.49%, 95% CI: 3.95-11.15%). The weather-MD association was stronger for psychoactive substance usage, mood disorders, adult behavior disorders, males, Hispanics, African Americans, individuals aged 46-65, or Medicare patients.

CONCLUSIONS

Hot and humid weather, especially the joint effect of high sun radiation, temperature and relative humidity showed the highest risk of MD diseases. We found stronger weather-MD associations in summer transitional months, males, and minority groups. These findings also need further confirmation.

Quantitative methods for climate change and mental health research: current trends and future directions

The quantitative literature on climate change and mental health is growing rapidly. However, the methodological quality of the evidence is heterogeneous, and there is scope for methodological improvement and innovation. The first section of this Personal View provides a snapshot of current methodological trends and issues in the quantitative literature on climate change and mental health, drawing on literature collected through a previous scoping review. The second part of this Personal View outlines opportunities for methodological innovation concerning the assessment of the relationship between climate change and mental health. We then highlight possible methodological innovations in intervention research and in the measurement of climate change and mental health-related variables. This section draws upon methods from public mental health, environmental epidemiology, and other fields. The objective is not to provide a detailed description of different methodological techniques, but rather to highlight opportunities to use diverse methods, collaborate across disciplines, and inspire methodological innovation. The reader will be referred to practical guidance on different methods when available. We hope this Personal View will constitute a roadmap and launching pad for methodological innovation for researchers interested in investigating a rapidly growing area of research.

Associations of short-term exposure to air pollution and increased ambient temperature with psychiatric hospital admissions in older adults in the USA: a case-crossover study

BACKGROUND

Little is known about the associations between ambient environmental exposures and the risk of acute episodes of psychiatric disorders. We aimed to estimate the link between short-term exposure to atmospheric pollutants, temperature, and acute psychiatric hospital admissions in adults aged 65 years and older in the USA.

METHODS

For this study, we included all people (aged ≥65 years) enrolled in the Medicare programme in the USA who had an emergency or urgent hospital admission for a psychiatric disorder recorded between Jan 31, 2000, and Dec 31, 2016. We applied a case-crossover design to study the associations between short-term exposure to air pollution (fine particulate matter [PM_2·5], ozone, and nitrogen dioxide [NO₂]), ambient temperature, and the risk of acute hospital admissions for depression, schizophrenia, and bipolar disorder in this population. The percentage change in the risk of hospital admission and annual absolute risk differences were estimated.

FINDINGS

For each 5°C increase in short-term exposure to cold season temperature, the relative risk of acute hospital admission increased by 3·66% (95% CI 3·06-4·26) for depression, by 3·03% (2·04-4·02) for schizophrenia, and by 3·52% (2·38-4·68) for bipolar disorder in the US Medicare population. Increased short-term exposure to PM_2·5 and NO₂ was also associated with a significant increase in the risk of acute hospital admissions for psychiatric disorders. Each 5 μg/m³ increase in PM_2·5 was associated with an increase in hospital admission rates of 0·62% (95% CI 0·23-1·02) for depression, 0·77% (0·11-1·44) for schizophrenia, and 1·19% (0·49-1·90) for bipolar disorder; each 5 parts per billion (ppb) increase in NO₂, meanwhile, was linked to an increase in hospital admission rates of 0·35% (95% CI 0·03-0·66) for depression and 0·64% (0·20-1·08) for schizophrenia. No such associations were found with warm season temperature.

INTERPRETATION

In the US Medicare population, short-term exposure to elevated concentrations of PM_2·5 and NO₂ and cold season ambient temperature were significantly associated with an increased risk of hospital admissions for psychiatric disorders. Considering the increasing burden of psychiatric disorders in the US population, these findings suggest that intervening on air pollution and ambient temperature levels through stricter environmental regulations or climate mitigation could help ease the psychiatric health-care burden.

FUNDING

US National Institute of Environmental Health Sciences, US Environmental Protection Agency, and US National Institute on Aging.

Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China

Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However, little is known about local explanations and global understanding on the importance and effect of input features in the complex system of environmental stressors - mental disorders (MDs), especially for exposure to air pollution mixture. In this study, we combined deep learning neural networks (DLNNs) with SHapley Additive exPlanation (SHAP) to predict the illness risk of MDs on the population level, and then provided explanations for risk factors. The modeling system, which was trained on day-by-day hospital outpatient visits of two major hospitals in Nanjing, China from 2013/07/01 through 2019/02/28, visualized the time-varying prediction, contributing factors, and interaction effects of informative features. Our results suggested that NO₂, SO₂, and CO made outstanding contributions in magnitude of feature attributions under circumstances of mixed air pollutants. In particular, NO₂ at high concentration level was associated with an increase in illness risk of MDs, and the maximum and mean absolute SHAP value were approximated to 10 and 2 as a local and global measure of feature importance, respectively. It presented a marginally antagonistic effect for two pairs of gaseous pollutants, i.e., NO₂ vs. SO₂ and CO vs. NO₂. In contrast, CO and SO₂ displayed the opposite direction of feature effects to the rise of observed concentrations, but an apparent synergistic effect was obviously captured. The primary risk factors driving a sharp increase in acute attack or exacerbation of MDs were also identified by depicting prediction paths of time-series samples. We believe that the significance of coupling accurate predictions from DLNNs with interpretable explanations of why a prediction is completed has broad applicability throughout the field of environmental health.

Association between extreme temperatures and emergency room visits related to mental disorders: A multi-region time-series study in New York, USA

BACKGROUND

There is growing evidence suggesting that extreme temperatures have an impact on mental disorders. We aimed to explore the effect of extreme temperatures on emergency room (ER) visits for mental health disorders using 2.8 million records from New York State, USA (2009-2016), and to examine potential effect modifications by individuals' age, sex, and race/ethnicity through a stratified analysis to determine if certain populations are more susceptible.

METHOD

To assess the short-term impact of daily average temperature on ER visits related to mental disorders, we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, as well as long-term and seasonal time trends. We also conducted a meta-analysis to pool the region-specific risk estimates and construct the overall cumulative exposure-response curves for all regions.

RESULTS

We found positive associations between short-term exposure to extreme heat (27.07 ^∘C) and increased ER visits for total mental disorders, as well as substance abuse, mood and anxiety disorders, schizophrenia, and dementia. We did not find any statistically significant difference among any subgroups of the population being more susceptible to extreme heat than any other.

CONCLUSIONS

Our findings suggest that there is a positive association between short-term exposure to extreme heat and increased ER visits for total mental disorders. This extreme effect was also found across all sub-categories of mental disease, although further research is needed to confirm our finding for specific mental disorders, such as dementia, which accounted for less than 1% of the total mental disorders in this sample.

Short-Term Association of Air Pollutant Levels and Hospital Admissions for Stroke and Effect Modification by Apparent Temperature: Evidence From Shanghai, China

The epidemiological evidence on relationships between air pollution, temperature, and stroke remains inconclusive. Limited evidence is available for the effect modification by apparent temperature, an indicator reflecting reactions to the thermal environment, on short-term associations between air pollution and hospital admissions for stroke. We used a generalized additive model with Poisson regression to estimate the relative risk (RR) of stroke admissions in Shanghai, China, between 2014 and 2016 associated with air pollutants, with subgroup analyses by age, sex, apparent temperature, and season. During the study period, changes in the daily number of stroke admissions per 10 μg/m³ increase in nitrogen dioxide (at lags 0, 1, 0–1, and 0–2) ranged from 1.05 (95% CI: 0.82%, 2.88%) to 2.24% (95% CI: 0.84%, 3.65%). For each 10 μg/m³ increase in sulfur dioxide concentrations at lags 1, 2, 0–1, and 0–2, the RR of daily stroke admissions increased by 3.34 (95% CI: 0.955%, 5.79%), 0.32 (95% CI: −1.97%, 2.67%), 3.33 (95% CI: 0.38%, 6.37%), and 2.86% (95% CI: −0.45%, 6.28%), respectively. The associations of same-day exposure to nitrogen dioxide with stroke admissions remained significant after adjustment for ozone levels. These associations were not modified by sex, age, apparent temperature, or season. More research is warranted to determine whether apparent temperature modifies the associations between air pollution and stroke admissions.

Is there an association between hot weather and poor mental health outcomes? A systematic review and meta-analysis

BACKGROUND

Mental health is an important public health issue globally. A potential link between heat exposure and mental health outcomes has been recognised in the scientific literature; however, the associations between heat exposure (both high ambient temperatures and heatwaves) and mental health-related mortality and morbidity vary between studies and locations.

OBJECTIVE

To fill gaps in knowledge, this systematic review aims to summarize the epidemiological evidence and investigate the quantitative effects of high ambient temperatures and heatwaves on mental health-related mortality and morbidity outcomes, while exploring sources of heterogeneity.

METHODS

A systematic search of peer-reviewed epidemiological studies on heat exposure and mental health outcomes published between January 1990 and November 2020 was conducted using five databases (PubMed, Embase, Scopus, Web of Science and PsycINFO). We included studies that examined the association between high ambient temperatures and/or heatwaves and mental health-related mortality and morbidity (e.g. hospital admissions and emergency department visits) in the general population. A range of mental health conditions were defined using ICD-10 classifications. We performed random effects meta-analysis to summarize the relative risks (RRs) in mental health outcomes per 1 °C increase in temperature, and under different heatwaves definitions. We further evaluated whether variables such as age, sex, socioeconomic status, and climate zone may explain the observed heterogeneity.

RESULTS

The keyword search yielded 4560 citations from which we identified 53 high temperatures/heatwaves studies that comprised over 1.7 million mental health-related mortality and 1.9 million morbidity cases in total. Our findings suggest associations between heat exposures and a range of mental health-related outcomes. Regarding high temperatures, our meta-analysis of study findings showed that for each 1 °C increase in temperature, the mental health-related mortality and morbidity increased with a RR of 1.022 (95%CI: 1.015-1.029) and 1.009 (95%CI: 1.007-1.015), respectively. The greatest mortality risk was attributed to substance-related mental disorders (RR, 1.046; 95%CI: 0.991-1.101), followed by organic mental disorders (RR, 1.033; 95%CI: 1.020-1.046). A 1 °C temperature rise was also associated with a significant increase in morbidity such as mood disorders, organic mental disorders, schizophrenia, neurotic and anxiety disorders. Findings suggest evidence of vulnerability for populations living in tropical and subtropical climate zones, and for people aged more than 65 years. There were significant moderate and high heterogeneities between effect estimates in overall mortality and morbidity categories, respectively. Lower heterogeneity was noted in some subgroups. The magnitude of the effect estimates for heatwaves varied depending on definitions used. The highest effect estimates for mental health-related morbidity was observed when heatwaves were defined as "mean temperature ≥90th percentile for ≥3 days" (RR, 1.753; 95%CI: 0.567-5.421), and a significant effect was also observed when the definition was "mean temperature ≥95th percentile for ≥3 days", with a RR of 1.064 (95%CI: 1.006-1.123).

CONCLUSIONS

Our findings support the hypothesis of a positive association between elevated ambient temperatures and/or heatwaves and adverse mental health outcomes. This problem will likely increase with a warming climate, especially in the context of climate change. Further high-quality studies are needed to identify modifying factors of heat impacts.

Associations of apparent temperature with acute cardiac events and subtypes of acute coronary syndromes in Beijing, China

Limited evidence is available on apparent temperature (AT) and hospital admissions for acute cardiac events. We examined the associations of AT with admissions for acute cardiac events and acute coronary syndrome (ACS), and explored the effect difference between ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction ACS (NSTE-ACS). Poisson regression with distributed lag non-linear model was applied to examine the temperature-lag-admission associations. Stratified analyses were performed by gender and age-groups for acute cardiac events. A total of 11,657 acute cardiac events admissions were collected from hospital-based chest pain centers in Beijing, during 2017-2019. The single day effect of low AT (- 11 °C, 2.5th percentile) appeared on the 2nd day and persisted until the 11th day, with estimated relative risk (RR) ranging from 1.44 (95% CI: 1.159, 1.790) to 1.084 (95% CI: 1.022, 1.150) for acute cardiac events and from 1.034 (95% CI: 1.010, 1.059) to 1.006 (95% CI: 1.000, 1.011) for ACS. The single day effect of high AT (34 °C, 97.5th percentile) was only observed on the current day. The cold effect on acute cardiac events was more pronounced among female and older patients. The cumulative effect of high AT on STEMI admissions and low AT on NSTE-ACS reached a peak RR peak of 2.545 (95% CI: 1.016, 6.375) and 3.71 (95% CI: 1.315, 10.469) on lag 0-6 days, respectively. Both high and low ATs were associated with increased risk of acute cardiac events and ACS admissions. STEMI admissions may be more sensitive to high AT while NSTE-ACS to low AT.

Meteorological Variables and Suicidal Behavior: Air Pollution and Apparent Temperature Are Associated With High-Lethality Suicide Attempts and Male Gender

This study analyzed the impact of meteorological variables and high-lethality suicide attempts (HLSA) to assess a potential time shift of HLSA affected by climate evolution to predict the suicide attempt cases over different periods of the year. After attempting suicide, 225 subjects were admitted to the emergency ward of the IRCCS Ospedale Policlinico San Martino and later to the psychiatric unit from March 2016 to July 2018. Socio-demographic and clinical characteristics as well as the meteorological variables were collected. The Mann-Kendall test as well as redundancy and cross-correlation analyses were performed to analyze the trends, statistically correlations, and correspondence of the trends, respectively between suicidal behaviors and climatic factors. Sixty-seven (29.8%) committed a HLSA. Our findings indicate a significant association between HLSA and male gender and apparent temperature with a strong correlation of 75% with a phase shift of -1 month. Solar radiation and air pollution (PM_2.5) have a positive correlation of 65 and 32%, respectively, with a zero-time lag. Limitations include that the data are limited to a single hospital; psychological factors, or other clinical variables that could be ruled out as a trigger have not been considered. Meteorological variables may not mirror the temperature that the patient is exposed to due to the air conditioning systems. Exploring those environmental factors associated with HLSA in a more detailed manner could lead to early intervention and prevention strategies for such distressing admissions.