Association of Psychiatric Emergency Visits and Warm Ambient Temperature during Pregnancy: A Time-Stratified Case-Crossover Study.

BACKGROUND: Acute exposure to high ambient temperature and heat waves during the warm season has been linked with psychiatric disorders. Emerging research has shown that pregnant people, due to physiological and psychological changes, may be more sensitive to extreme heat, and acute exposure has been linked to increased risk of pregnancy complications; however, few studies have examined psychiatric complications. OBJECTIVE: Our objective was to examine the association between acute exposure to warm ambient temperatures and emergency department (ED) visits for mental disorders during pregnancy. METHODS: A time-stratified case-crossover design with conditional logistic regression was performed on ∼206,000 psychiatric ED visits for pregnant patients in North Carolina, from May to September 2016 to 2019. Daily average ambient temperature was the main exposure and was linked to daily visits by maternal zip code of residence for prenatal mood and anxiety disorders (PMAD), severe mental illness (SMI), mental disorder of pregnancy (MDP), suicidal thoughts (SUIC), and any psychiatric disorder (Any). Effect modification by trimester, residential segregation, economic segregation, urbanicity, and availability of greenspace was also investigated. RESULTS: Each 5°C increase in same-day exposure to warm ambient temperature on case days was associated with an increase in incidence rate ratio (IRR) for any psychiatric disorder [IRR = 1.07; 95% confidence interval (CI): 1.01, 1.14] including anxiety (IRR = 1.14; 95% CI: 1.00, 1.30), bipolar disorder (IRR = 1.28; 95% CI: 0.98, 1.67), and suicidal thoughts (IRR = 1.28; 95% CI: 1.00, 1.65) compared to control days. In general, the associations were strongest for warm season temperatures on the same day of exposure or for temperatures averaged over the 3 or 6 d preceding the ED visit. The greatest risk of an incident ED admission for PMAD (RR = 1.20; 95% CI: 1.04, 1.39), particularly for anxiety (RR = 1.30; 95% CI: 1.07, 1.59), and any psychiatric disorder (RR = 1.17; 95% CI: 1.07, 1.28) occurred following cumulative exposure to hot temperatures the week before admission. Higher psychiatric burden from temperature was observed in urban areas and on extreme heat days. CONCLUSIONS: For this pregnant population in the southeastern United States, short-term exposure to high ambient temperatures during the warm season was associated with a greater risk of ED visits for an array of psychiatric disorders. Findings show that climate-related increases in ambient temperature may contribute to psychiatric morbidity in pregnant people. https://doi.org/10.1289/EHP13293.

Place-Based Differences in the Association Between Greenspace and Suicide-Related Outcomes Among Young People.

PURPOSE: This study investigated place-based differences in the association between greenspace and suicide-related outcomes (SROs) among young people, guided by the following two objectives: (1) Contextualize place-based differences in the association between greenspace and SRO prevalence among young people at the community level in five different urbanities (urban, suburban, micropolitan, small towns, and rural/isolated communities) and (2) identify which greenspace metrics (quantity, quality, or accessibility) are most protective for SROs at the community level. METHODS: Publicly available greenspace datasets were used to derive greenspace quantity, quality, and accessibility metrics. SRO emergency department visits for young people were identified from 2016-2019 in North Carolina, USA. Generalized linear models investigated the association between greenspace metrics and community-level drivers of SRO prevalence. Shapely additive explanations confirmed the most important greenspace variables in accurately predicting community-level SRO prevalence. RESULTS: The prevalence of SROs was highest in communities with the least amount of public greenspace; this association was most pronounced in suburban communities, with SROs 27% higher in suburban communities with low quantities of greenspace (PRRUrban: 1.11, confidence interval [CI]: 1.08-1.13; PRRSuburban: 1.27, CI: 1.10-1.46; PRRSmallTowns: 1.21, CI: 1.05-1.39), and in communities with the worst greenspace accessibility (i.e., furthest distance to nearest greenspace) (PRRUrban: 1.07, CI: 1.04-1.10; PRRRural&Isolated: 1.95, CI: 1.54-2.49). DISCUSSION: Our analysis provides place-based, community-specific findings to guide targeted greenspace interventions aimed at addressing the rising prevalence of SROs among young people. Our findings suggest that greenspace quantity interventions may be most effective in urban, suburban, and small-town communities, and greenspace accessibility interventions may be most useful in urban and rural/isolated communities.

Short-term changes in mental health help-seeking behaviors following exposure to multiple social stressors and a natural disaster.

In 2020, unprecedented circumstances led to significant mental health consequences. Individuals faced mental health stressors that extended beyond the devastating impact of the COVID-19 pandemic, including widespread social unrest following the murder of George Floyd, an intense hurricane season in the Atlantic, and the politically divisive 2020 election. The objective of this analysis was to consider changes in help-seeking behavior following exposure to multiple social stressors and a natural disaster. Data from Crisis Text Line (CTL), a national text-based mental health crisis counseling service, was used to determine how help-seeking behavior changed in the wake of each event. Wilcoxon rank sum tests assessed changes in help-seeking behavior for each event in 2020 as compared to the same period in 2019. AutoRegressive Integrated Moving Average (ARIMA) models examined if changes in crisis conversation volumes following each event differed. Higher median conversation volumes noted for the COVID-19 pandemic (+1 to +5 conversations), Hurricane Laura (+1 to +7 conversations) and the 2020 Election (+1 to +26 conversations). ARIMA models show substantial increases in help-seeking behavior following the declaration of a national emergency for the COVID-19 pandemic (+4.3 to +38.2%) and following the 2020 election (+3 to +24.44%). Our analysis found that the mental health response following social stressors may be distinct from natural events, especially when natural disasters occur in the context of multiple social stressors. This analysis adds to the growing body of literature considering the mental health impact of exposure to multiple co-occurring societal stressors, like police violence and a global pandemic.

Evaluating co-occurring space-time clusters of depression and suicide-related outcomes before and during the COVID-19 pandemic.

Rapidly emerging research on the mental health consequences of the COVID-19 pandemic shows increasing patterns of psychological distress, including anxiety and depression, and self-harming behaviors, particularly during the early months of the pandemic. Yet, few studies have investigated the spatial and temporal changes in depressive disorders and suicidal behavior during the pandemic. The objective of this retrospective analysis was to evaluate geographic patterns of emergency department admissions for depression and suicidal behavior in North Carolina before (March 2017-February 2020) and during the COVID-19 pandemic (March 2020 - December 2021). Univariate cluster detection examined each outcome separately and multivariate cluster detection was used to examine the co-occurrence of depression and suicide-related outcomes in SatScan; the Rand index evaluated cluster overlap. Cluster analyses were adjusted for age, race, and sex. Findings suggest that the mental health burden of depression and suicide-related outcomes remained high in many communities throughout the pandemic. Rural communities exhibited a larger increase in the co-occurrence of depression and suicide-related ED visits during the pandemic period. Results showed the exacerbation of depression and suicide-related outcomes in select communities and emphasize the need for targeted and sustained mental health interventions throughout the many phases of the COVID-19 pandemic.

Socio-Environmental Determinants of Mental and Behavioral Disorders in Youth: A Machine Learning Approach.

Growing evidence indicates that extreme environmental conditions in summer months have an adverse impact on mental and behavioral disorders (MBD), but there is limited research looking at youth populations. The objective of this study was to apply machine learning approaches to identify key variables that predict MBD-related emergency room (ER) visits in youths in select North Carolina cities among adolescent populations. Daily MBD-related ER visits, which totaled over 42,000 records, were paired with daily environmental conditions, as well as sociodemographic variables to determine if certain conditions lead to higher vulnerability to exacerbated mental health disorders. Four machine learning models (i.e., generalized linear model, generalized additive model, extreme gradient boosting, random forest) were used to assess the predictive performance of multiple environmental and sociodemographic variables on MBD-related ER visits for all cities. The best-performing machine learning model was then applied to each of the six individual cities. As a subanalysis, a distributed lag nonlinear model was used to confirm results. In the all cities scenario, sociodemographic variables contributed the greatest to the overall MBD prediction. In the individual cities scenario, four cities had a 24-hr difference in the maximum temperature, and two of the cities had a 24-hr difference in the minimum temperature, maximum temperature, or Normalized Difference Vegetation Index as a leading predictor of MBD ER visits. Results can inform the use of machine learning models for predicting MBD during high-temperature events and identify variables that affect youth MBD responses during these events.

Cascading disasters and mental health: The February 2021 winter storm and power crisis in Texas, USA.

In February 2021, the state of Texas and large parts of the US were affected by a severe cold air outbreak and winter weather event. This event resulted in large-scale power outages and cascading impacts, including limited access to potable water, multiple days without electricity, and large-scale infrastructure damage. Little is known about the mental health implications of these events, as most research has predominantly focused on the mental health effects of exposure to hurricanes, wildfires, or other natural disasters that are more commonly found in the summer months. This study aimed to analyze the crisis responses from the 2021 winter weather event in Texas using Crisis Text Line, a text-based messaging service that provides confidential crisis counseling nationwide. To date, Crisis Text Line is the largest national crisis text service, with over 8 million crisis conversations since its inception in 2013. We employed multiple analytic techniques, including segmented regression, interrupted time series, autoregressive integrated moving average (ARIMA), and difference-in-difference (DID), to investigate distinct time periods of exposure for all crisis conversations. ARIMA and DID were further utilized to examine specific crisis outcomes, including depression, stress/anxiety, and thoughts of suicide. Results found increases in total crisis conversations and for thoughts of suicide after the initial winter weather event; however, crisis outcomes varied in time. Thoughts of suicide in high-impact regions were higher across multiple time periods (e.g., 4-weeks, 3-months, 6-months, 9-months and 11-months) compared to low-impact regions and were elevated compared to pre-event time periods for 6-months and 11-months from the initial event. Total crisis volume also remained elevated for high-impact regions compared to low-impact regions up to 11-months after the beginning of the winter event. Our work highlights that cascading winter weather events, like the Texas 2021 Winter storm, negatively impacted mental health. Future research is needed across different disaster types (e.g., cascading, concurrent events) and for specific crisis outcomes (e.g., depression, suicidal ideation) to understand the optimal timing of crisis intervention post-disaster.

Examining Hurricane Ida's Impact on Mental Health: Results From a Quasi-Experimental Analysis.

Limited research has evaluated the mental health effects during compounding disasters (e.g., a hurricane occurring during a pandemic), and few studies have examined post-disaster mental health with alternative data sources like crisis text lines. This study examined changes in crisis help-seeking for individuals in Louisiana, USA, before and after Hurricane Ida (2021), a storm that co-occurred during the COVID-19 pandemic. An interrupted time series analysis and difference-in-difference analysis for single and multiple group comparisons were used to examine pre-and post-changes in crisis text volume (i.e., any crisis text, substance use, thoughts of suicide, stress/anxiety, and bereavement) among help-seeking individuals in communities that received US Federal Emergency Management Agency individual and public assistance following a presidential disaster declaration. Results showed a significant increase in crisis texts for any reason, thoughts of suicide, stress/anxiety, and bereavement in the four-week, three-month, and four-month post-impact period. Findings highlight the need for more mental health support for residents directly impacted by disasters like Hurricane Ida.

Spatio-Temporal Clustering of Adolescent Bereavement in the United States During the Extended Response to COVID-19: A Follow-Up Study.

PURPOSE: This follow-up study investigated the spatio-temporal clustering of adolescent bereavement during the extended response to COVID-19 from October 2020-January 2022 in the continental United States. METHODS: Deidentified and anonymized bereavement data from Crisis Text Line (CTL), a text-based crisis intervention service, and SaTScan cluster analysis were used to identify space-time clustering of bereavement among adolescents, aged 24 years and less, during the COVID-19 pandemic. RESULTS: Clustering of bereavement conversations occurred during waves of high COVID-19 case and death counts, with the highest risk occurring in the Southeastern United States during the fall of 2020 (relative risk: 5.86, confidence interval: 3.48-8.24). Of the CTL texters who shared their demographic information, Indigenous American, Black, male, and female adolescents were more likely to seek help for bereavement when compared to the other CTL users. DISCUSSION: Findings show an increased need for bereavement counseling resources during periods of high COVID-19 cases and deaths.

A Difference-In Difference Analysis of the South Carolina 2015 Extreme Floods and the Association with Maternal Health.

Research documenting the public health impacts of natural disasters often focuses on adults and children. Little research has examined the influence of extreme events, like floods, on maternal health, and less has examined the effect of disasters on maternal indicators like severe maternal morbidity (SMM) or unexpected outcomes of labor and delivery that result in significant short-or long-term consequences to a woman's health. The aim of this study is to identify the impacts of the 2015 flood events on maternal health outcomes in South Carolina, USA. We employ a quasi-experimental design using a difference-in-difference analysis with log-binomial regressions to evaluate maternal outcomes for impacted and control locations during the disaster event. Unlike previous studies, we extended our difference-in-difference analysis to include a trimester of exposure to assess the timing of flood exposure. We did not find evidence of statistically significant main effects on maternal health from the 2015 flood events related to preterm birth, gestational diabetes, mental disorders of pregnancy, depression, and generalized anxiety. However, we did find a statistically significant increase in SMM and low birth weight during the flood event for women in select trimester periods who were directly exposed. Our work provides new evidence on the effects of extreme flood events, like the 2015 floods, which can impact maternal health during specific exposure periods of pregnancy. Additional research is needed across other extreme weather events, as the unique context of the 2015 floods limits the generalizability of our findings.