Disparities in spatiotemporal clustering of maternal mental health conditions before and during the COVID-19 pandemic.

Mounting evidence indicates the worsening of maternal mental health conditions during the COVID-19 pandemic. Mental health conditions are the leading cause of preventable death during the perinatal and postpartum periods. Our study sought to detect space-time patterns in the distribution of maternal mental health conditions in pregnant women before (2016-2019) and during (2020-2021) the COVID-19 pandemic in North Carolina, USA. Using the space-time Poisson model in SaTScan, we performed univariate and multivariate cluster analysis of emergency department (ED) visits for perinatal mood and anxiety disorders (PMAD), severe mental illness (SMI), maternal mental disorders of pregnancy (MDP), suicidal thoughts, and suicide attempts during the pre-pandemic and pandemic periods. Clusters were adjusted for age, race, and insurance type. Significant multivariate and univariate PMAD, SMI, and MDP clustering persisted across both periods in North Carolina, while univariate clustering for both suicide outcomes decreased during the pandemic. Local relative risk (RR) for all conditions increased drastically in select locations. The number of zip code tabulation areas (ZCTAs) included in clusters decreased, while the proportion of urban locations included in clusters increased for non-suicide outcomes. Average yearly case counts for all maternal mental health outcomes increased during the pandemic. Results provide contextual and spatial information concerning at-risk maternal populations with a high burden of perinatal mental health disorders before and during the pandemic and emphasize the necessity of urgent and targeted expansion of mental health resources in select communities.

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.

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.

Crisis response in Texas youth impacted by Hurricane Harvey: A difference-in-differences analysis.

BACKGROUND: Hurricane Harvey was the second costliest storm to impact the U.S. More research is needed to understand the mental health consequences of these extreme events in children and adolescents extending beyond the acute recovery period. METHODS: Daily anonymized Crisis Text Line (CTL) conversations were used to understand patterns in crisis responses for youth one year before and after Harvey's landfall. A quasi-experimental difference-in-differences analysis compared changes in texts for stress/anxiety, depression, thoughts of suicide, and self-harm following Harvey between exposed and unexposed youth in Texas. RESULTS: CTL users with Texas-based area codes (N = 23,016) were compriesd largely of youth who self-identified as female (78.1 %), 14-17 year old (50.4 %), white (38.9 %), and LGBTQ+ (51.2 %). We observed parallel increases in crisis texts for depression and thoughts of suicide in most months following Harvey among exposed and unexposed youth. However, non-impacted youth had significantly larger increases in texts for depression up to three months post-Harvey and thoughts of suicide one year after Harvey compared to directly impacted communities. LIMITATIONS: Sample size was restricted to texters who completed the post-conversation demographics survey, who may fundamentally differ from those who declined to respond. Harvey exposure was determined using texter area code and county-level disaster declarations, limiting our ability to guarantee individual-level exposure. CONCLUSIONS: Texas youth traditionally considered unexposed experienced nearly identical increases in concerns of depression and thoughts of suicide to those directly exposed. Findings suggest spillover effects (e.g., economic concerns, media exposure) may contribute to statewide impacts on youth mental health after natural disasters.

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.

Advancing Understanding on Greenspace and Mental Health in Young People.

Mental distress among young people has increased in recent years. Research suggests that greenspace may benefit mental health. The objective of this exploratory study is to further understanding of place-based differences (i.e., urbanity) in the greenspace-mental health association. We leverage publicly available greenspace data sets to operationalize greenspace quantity, quality, and accessibility metrics at the community-level. Emergency department visits for young people (ages 24 and under) were coded for: anxiety, depression, mood disorders, mental and behavioral disorders, and substance use disorders. Generalized linear models investigated the association between greenspace metrics and community-level mental health burden; results are reported as prevalence rate ratios (PRR). Urban and suburban communities with the lowest quantities of greenspace had the highest prevalence of poor mental health outcomes, particularly for mood disorders in urban areas (PRR: 1.19, 95% CI: 1.16-1.21), and substance use disorders in suburban areas (PRR: 1.35, 95% CI: 1.28-1.43). In urban, micropolitan, and rural/isolated areas further distance to greenspace was associated with a higher prevalence of poor mental health outcomes; this association was most pronounced for substance use disorders (PRRUrban: 1.31, 95% CI: 1.29-1.32; PRRMicropolitan: 1.47, 95% CI: 1.43-1.51; PRRRural 2.38: 95% CI: 2.19-2.58). In small towns and rural/isolated communities, poor mental health outcomes were more prevalent in communities with the worst greenspace quality; this association was most pronounced for mental and behavioral disorders in small towns (PRR: 1.29, 95% CI: 1.24-1.35), and for anxiety disorders in rural/isolated communities (PRR: 1.61, 95% CI: 1.43-1.82). The association between greenspace metrics and mental health outcomes among young people is place-based with variations across the rural-urban continuum.

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.

Acute Health Effects of Wildfire Smoke Exposure During a Compound Event: A Case-Crossover Study of the 2016 Great Smoky Mountain Wildfires.

In 2016, unprecedented intense wildfires burned over 150,000 acres in the southern Appalachian Mountains in the United States. Smoke from these fires greatly impacted the region and exposure to this smoke was significant. A bidirectional case-crossover design was applied to assess the relationship between PM2.5 (a surrogate for wildfire smoke) exposure and respiratory- and cardiovascular-related emergency department (ED) visits in Western North Carolina during these events. For 0-, 3-, and 7-day lags, findings indicated a significant increase in the odds of being admitted to the ED for a respiratory (ORs: 1.055, 95% CI: 1.048-1.063; 1.083, 1.074-1.092; 1.066, 1.058-1.074; respectively) or cardiovascular event (ORs: 1.052, 95% CI: 1.045-1.060; 1.074, 1.066-1.081; 1.067, 1.060-1.075; respectively) for every 5 µg/m3 increase in PM2.5 over a chosen cutpoint of 20.4 µg/m3. For all endpoints assessed except for emphysema, there were statistically significant increases in odds from 5.1% to 8.3%. In general, this increase was most pronounced 3 days after exposure. Additionally, individuals aged 55+ generally experience higher odds of heart disease at the 3- and 7-day lag points, and Black/African Americans generally experience higher odds of asthma at the 3-day lag point. In general, larger fires and increased numbers of fires within counties resulted in higher health burden at same day exposure. In a secondary analysis, the odds of an ED visit increased by over 40% in several cases among people exposed to days above the Environmental Protection Agency 24-hr PM2.5 standard of 35 µg/m3. Our findings provide new understanding on the health impacts of wildfires on rural populations in the southeastern US.

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.

Association between urban greenspace, tree canopy cover and intentional deaths: An exploratory geospatial analysis.

Greenspaces can provide restorative experiences, offer opportunities for outdoor recreation, and reduce mental fatigue; all of which may improve community health and safety. Yet few studies have examined the neighborhood-level benefits of greenspace in reducing violent deaths. This study explored the association between three distinct greenspace metrics: public greenspace quantity, public greenspace accessibility, neighborhood tree canopy cover, and intentional deaths (i.e., homicides and suicides). Generalized linear models and spatial error models investigated the association between greenspace, tree canopy and intentional deaths in three geographically distinct cities in North Carolina. Results revealed that increased neighborhood greenspace accessibility and tree canopy cover were associated with reduced intentional deaths in all three urban areas. Neighborhood greenspace accessibility was the most protective factor across all study areas. The relationship between neighborhood greenspace accessibility and intentional deaths was more significant for non-firearm deaths as compared to firearm deaths, indicating that weapon type may be an important consideration for neighborhood greenspace interventions. Compared to predominantly White neighborhoods, predominantly Black neighborhoods had higher rates of homicide in Asheville and Durham and higher rates of suicide in Charlotte. Future policy and research should focus on improving equitable access to existing and future greenspaces, especially in primarily Black neighborhoods.

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.

Spatial Analysis of Greenspace and Mental Health in North Carolina: Consideration of Rural and Urban Communities.

Greenspace positively impacts mental health. Previous research has focused on the greenspace-mental health relationship in urban areas. Yet, little work has looked at rural areas despite rural communities reporting similar rates of poor mental health outcomes and higher rates of suicide mortality compared with urban areas. This ecological research study examined the following research questions: (1) Do public and/or private greenspaces affect the spatial distribution of mental health outcomes in North Carolina? (2) Does this relationship change with rurality? Emergency department data for 6 mental health conditions and suicide mortality data from 2009 to 2018 were included in this analysis. Spatial error and ordinary least squares regressions were used to examine the influence of public and private greenspace quantity on mental health in rural and urban communities. Results suggest greenspace benefits mental health in rural and urban communities. The strength of this relationship varies with urbanity and between public and private greenspaces, suggesting a more complex causal relationship. Given the high case counts and often lower density of mental health care facilities in rural areas, focusing attention on low-cost mental health interventions, such as greenspace, is important when considering rural mental health care.

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.

Association Between Perinatal Mental Health and Pregnancy and Neonatal Complications: A Retrospective Birth Cohort Study.

BACKGROUND: Maternal mental health as an important precursor to reproductive and neonatal complications remains understudied in the United States, particularly in the Southeastern region, despite high medical costs, maternal morbidity, and infant burden. This study sought to estimate the incidence of perinatal mental health disorders and the associated increased risk of leading pregnancy and infant complications. METHODS: A population-based retrospective birth cohort of childbirth hospitalizations and readmissions was constructed for women in South Carolina, 1999 to 2017. Prevalence rates were calculated for perinatal mood and anxiety disorders (PMAD), severe mental illness, and mental disorders of pregnancy (MDP). Poisson regression models using generalized estimating equations were used to estimate adjusted relative risks for the association between mental health conditions and severe maternal morbidity, hypertensive disorders of pregnancy, gestational diabetes, cesarean section, preterm birth, and low birthweight. RESULTS: The most prevalent maternal mental condition was MDP (3.9%), followed by PMAD (2.7%) and severe mental illness (0.13%). PMAD was associated with a higher risk of severe maternal morbidity, hypertensive disorders of pregnancy, and cesarean section, as well as a higher risk of preterm birth and low birthweight infants. Severe mental illness was associated with low birthweight, hypertensive disorders of pregnancy, and cesarean section. Pregnant populations with MDP were more at risk for severe maternal morbidity, preterm birth, hypertensive disorders of pregnancy, low birthweight, and cesarean section. Each maternal mental health outcome was associated with an increased risk for hospital readmissions up to 45 days after childbirth. CONCLUSIONS: Results demonstrate the escalating burden of PMAD and MDP for pregnant populations over time, with important consequences related to maternal and infant morbidity.

Crisis Response and Suicidal Behaviors of Essential Workers and Children of Essential Workers During the COVID-19 Pandemic.

OBJECTIVE: The COVID-19 pandemic has put unprecedented stress on essential workers and their children. Limited cross-sectional research has found increases in mental health conditions from workload, reduced income, and isolation among essential workers. Less research has been conducted on children of essential workers. We examined trends in the crisis response of essential workers and their children from April 2020 through August 2021. METHODS: We investigated the impact during 3 periods of the pandemic on workers and their children using anonymized data from the Crisis Text Line on crisis help-seeking texts for thoughts of suicide or active suicidal ideation (desire, intent, capability, time frame), abuse (emotional, physical, sexual, unspecified), anxiety/stress, grief, depression, isolation, bullying, eating or body image, gender/sexual identity, self-harm, and substance use. We used generalized estimating equations to study the longitudinal change in crisis response across the later stages of the pandemic using adjusted odds ratios (aORs) for worker status and crisis outcomes. RESULTS: Results demonstrated higher odds of crisis outcomes for thoughts of suicide (aOR = 1.06; 95% CI, 1.00-1.12) and suicide capability (aOR = 1.14; 95% CI, 1.02-1.27) among essential workers than among nonessential workers. Children of essential workers had higher odds of substance use than children of nonessential workers (aOR = 1.33; 95% CI, 1.08-1.65), particularly for Indigenous American children (aOR = 2.76; 95% CI, 1.35-5.36). Essential workers (aOR = 1.17; 95% CI, 1.07-1.27) and their children (aOR = 1.18; 95% CI, 1.07-1.30) had higher odds of grief than nonessential workers and their children. CONCLUSION: Essential workers and their children had elevated crisis outcomes. Immediate and low-cost psychologically supportive interventions are needed to mitigate the mental health impacts of the COVID-19 pandemic on these populations.

Real-Time Mental Health Crisis Response in the United States to COVID-19.

Background: Data are scarce on assessing the impact of the COVID-19 pandemic on young people. Aim: To examine changes in crisis text patterns in the United States during the pandemic compared to the prepandemic period. Method: Nonintrusive data from a national digital crisis texting platform were analyzed using an interrupted time series design. Poisson regression with repeated-measures examined help-seeking patterns for stress, anxiety, depression, suicidal thoughts, and other mental health concerns in the pandemic (March 13 to July 20, 2020) compared to the prepandemic period (March 13 to July 20, 2019). Results: An abrupt increase in national crisis response texts occurred during the pandemic for stress and anxiety, substance abuse, bereavement, isolation, and abuse compared to the prepandemic period. Similar trends of excess texts for isolation and abuse were reported among children (relative risk [RR]abuse: 1.16, CI: 1.03, 1.31; RRisolation: 1.15, CI: 1.09, 1.21) and adolescents (RRabuse: 1.17, CI: 1.11, 1.24; RRisolation: 1.08, CI: 1.05, 1.11), bereavement among Black (RR: 1.31, CI: 1.12, 1.54) and Hispanic (RR: 1.28, CI: 1.10, 1.49) texters, and isolation and bereavement in female (RRisolation: 1.09, CI: 1.06, 1.11; RRbereavement: 1.21, CI: 1.13, 1.28) or nonconforming youth (RRisolation: 1.19, CI: 1.08, 1.32; RRbereavement: 1.50, CI: 1.08, 2.09) texters. Conversely, the risks of reporting bullying, depression, relationship issues, and suicidal thoughts as reasons for texting were significantly lower during COVID-19. Limitations: Results may underestimate crisis support-seeking in some groups because demographic data were not captured on all texters. Conclusion: Findings illuminated the real-time crisis response of young people across the United States and can inform more responsive interventions to alleviate the mental health consequences brought on by the COVID-19 pandemic.

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.

Exploring Place-Based Differences in Suicide and Suicide-Related Outcomes Among North Carolina Adolescents and Young Adults.

PURPOSE: Suicide is an ongoing public health crisis among youth and adolescents, and few studies have investigated the spatial patterning in the United States among this subpopulation. Potential precursors to suicide in this vulnerable group are also on the rise, including nonfatal self-injury. METHODS: This study uses emergency department data, death certificates, and violent death reporting system data for North Carolina from 2009 to 2018 to investigate spatial clusters of self-injury and suicide. RESULTS: Findings show that the demographic characteristics of individuals committing fatal and nonfatal self-injury are quite different. Self-injury and completed suicides exhibited different geographical patterns. Area-level measures like micropolitan status and measures of racial and income segregation predicted the presence of high-risk suicide clusters. Suicides among Native Americans and veteran status/military personnel also were associated with higher risk suicide clusters. DISCUSSION: Future interventions should target these specific high-risk locations for immediate reductions in adolescent and youth suicides.

Mapping high-risk clusters and identifying place-based risk factors of mental health burden in pregnancy.

Purpose: Despite affecting up to 20% of women and being the leading cause of preventable deaths during the perinatal and postpartum period, maternal mental health conditions are chronically understudied. This study is the first to identify spatial patterns in perinatal mental health conditions, and relate these patterns to place-based social and environmental factors that drive cluster development. Methods: We performed spatial clustering analysis of emergency department (ED) visits for perinatal mood and anxiety disorders (PMAD), severe mental illness (SMI), and maternal mental disorders of pregnancy (MDP) using the Poisson model in SatScan from 2016 to 2019 in North Carolina. Logistic regression was used to examine the association between patient and community-level factors and high-risk clusters. Results: The most significant spatial clustering for all three outcomes was concentrated in smaller urban areas in the western, central piedmont, and coastal plains regions of the state, with odds ratios greater than 3 for some cluster locations. Individual factors (e.g., age, race, ethnicity) and contextual factors (e.g., racial and socioeconomic segregation, urbanity) were associated with high risk clusters. Conclusions: Results provide important contextual and spatial information concerning at-risk populations with a high burden of maternal mental health disorders and can better inform targeted locations for the expansion of maternal mental health services.

Individually experienced heat index in a coastal Southeastern US city among an occupationally exposed population.

Recent studies have characterized individually experienced temperatures or individually experienced heat indices, including new exposure metrics that capture dimensions of exposure intensity, frequency, and duration. Yet, few studies have examined the personal thermal exposure in underrepresented groups, like outdoor workers, and even fewer have assessed corresponding changes in physiologic heat strain. The objective of this paper is to examine a cohort of occupationally exposed grounds and public safety workers (n = 25) to characterize their heat exposure and resulting heat strain. In addition, a secondary aim of this work is to compare individually heat index exposure (IHIE) across exposure metrics, fixed-site in situ weather stations, and raster-derived urban heat island (UHI) measurements in Charleston, SC, a humid coastal climate in the Southeastern USA. A Bland-Altman (BA) analysis was used to assess the level of agreement between the personal IHIE measurements and weather-station heat index (HI) and Urban Heat Island (UHI) measurements. Linear mixed-effect models were used to determine the association between individual risk factors and in situ weather station measurements significantly associated with IHIE measurements. Multivariable stepwise Cox proportional hazard modeling was used to identify the individual and workplace factors associated with time to heat strain in workers. We also examined the non-linear association between heat strain and exposure metrics using generalized additive models. We found significant heterogeneity in IHIE measurements across participants. We observed that time to heat strain was positively associated with a higher IHIE, older age, being male, and among Caucasian workers. Important nonlinear associations between heat strain occurrence and the intensity, frequency, and duration of personal heat metrics were observed. Lastly, our analysis found that IHIE measures were significantly similar for weather station HI, although differences were more pronounced for temperature and relative humidity measurements. Conversely, our IHIE findings were much lower than raster-derived UHI measurements. Real-time monitoring can offer important insights about unfolding temperature-health trends and emerging behaviors during thermal extreme events, which have significant potential to provide situational awareness.