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.

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.

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.

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.

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.

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.

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.

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.

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; RR_isolation: 1.15, CI: 1.09, 1.21) and adolescents (RR_abuse: 1.17, CI: 1.11, 1.24; RR_isolation: 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 (RR_isolation: 1.09, CI: 1.06, 1.11; RR_bereavement: 1.21, CI: 1.13, 1.28) or nonconforming youth (RR_isolation: 1.19, CI: 1.08, 1.32; RR_bereavement: 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.

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.

Inequalities in Life Expectancy Across North Carolina: A Spatial Analysis of the Social Determinants of Health and the Index of Concentration at Extremes

Health inequalities are characterized by spatial patterns of social, economic, and political factors. Life expectancy (LE) is a commonly used indicator of overall population health and health inequalities that allows for comparison across different spatial and temporal regions. The objective of this study was to examine geographic inequalities in LE across North Carolina census tracts by comparing the performance of 2 popular geospatial health indices: Social Determinants of Health (SDoH) and the Index of Concentration at Extremes (ICE). A principal components analysis (PCA) was used to address multicollinearity among variables and aggregate data into components to examine SDoH, while the ICE was constructed using the simple subtraction of geospatial variables. Spatial regression models were employed to compare both indices in relation to LE to evaluate their predictability for population health. For individual SDoH and ICE components, poverty and income had the strongest positive correlation with LE. However, the common spatial techniques of adding PCA components together for a final SDoH aggregate measure resulted in a poor relationship with LE. Results indicated that both metrics can be used to determine spatial patterns of inequities in LE and that the ICE metric has similar success to the more computationally complex SDoH metric. Public health practitioners may find the ICE metric's high predictability matched with lower data requirements to be more feasible to implement in population health monitoring.

Racial and ethnic disparities in pregnancy complications and the protective role of greenspace: A retrospective birth cohort study

Greenspace may positively impact pregnancy health for racially and economically minoritized populations; few studies have examined local availability and accessibility of green/park space in reducing maternal morbidity. The objective of this retrospective birth cohort study was to examine the association between residential exposure to greenspace and adverse pregnancy health outcomes in a Southern US state characterized by high poverty and racial disparities in maternal health (2013-2017). National data from the Protected Area database - United States (PAD-US) and ParkServe estimated three publicly available and accessible residential greenspace measures-a more direct proxy than using remotely-sensed greenness indicators (e.g., normalized difference vegetation index (NDVI))-(a) percent area of greenspace (M1), (b) area of available greenspace per person (M2), (c) total population within a 10-minute walk (M3). Generalized Estimating Equations with logistic regression were used to examine the association between individual greenspace metrics and South Carolina hospital deliveries (n = 238,922 deliveries) for women with correlated maternal health outcomes for gestational hypertension (GHTN), gestational diabetes (GD), severe maternal morbidity (SMM), preeclampsia (PRE), mental disorders (MD), depressive disorders (DD), and preterm birth (PTB). Lowest compared to highest tertiles of all three metrics were associated with increased risk for MD, DD, and a monotonic increase in GD, particularly for black women. Women with the lowest access to M2 and M3 were more at risk for PRE, PTB, and MD. We observed that women in low-income, majority-black communities in the lowest versus highest tertile of M2 were more likely to experience a DD, MD, SMM, or PTB compared to primarily high-income majority-white communities. Available and accessible green/park space may present as an effective nature-based intervention to reduce maternal complications, particularly for gestational diabetes and other pregnancy health risks for which there are currently few known evidence-based primary prevention strategies.

Understanding the concurrent risk of mental health and dangerous wildfire events in the COVID-19 pandemic

Little research has examined the mental health risks of concurrent disasters. For example, disasters like wildfires have been shown to have a strong association with psychological symptoms-the 2020 U.S. Western wildfire season was the worst on record and occurred while the country was still navigating the COVID-19 pandemic. We implemented two quasi-experimental analyses, an interrupted time series analysis, and a difference-in-difference analysis to evaluate the impacts of wildfires and COVID-19 on mental health crisis help-seeking patterns. Both methods showed no statistical association between exposure to wildfires and the seeking of mental health support during the COVID-19 pandemic. Results highlighted that 2020 wildfires were not associated with an acute increase in crisis texts for youth in the two months after the events, likely due to an already elevated text volume in response to the COVID-19 pandemic from March 2020 throughout the fall wildfire season (Aug to Oct 2020). Future research is needed outside of the context of the pandemic to understand the effects of extreme and concurrent climatic events on adolescent mental health, and targeted interventions are required to ensure youth and adolescents are receiving adequate support during these types of crisis events.

Crisis Response and Suicidal Patterns in U.S. Youth Before and During COVID-19: A Latent Class Analysis

PURPOSE

This study characterized the unobserved patterns in crisis response among youth in the U.S. from March to December 2020 and determined the characteristics of vulnerable subgroups who were at increased risk for suicide due to the pandemic.

METHODS

A latent class analysis of crisis support-seeking from a national text-based crisis platform, (n = 179,497, aged 24 years or younger) for 11 crisis concerns (e.g., depression, anxiety/stress, suicidal thoughts, isolation, abuse, bereavement, relationships) was performed on three study periods: (1) January 2017 to December 2020, (2) prepandemic: 1 January 2017 to 12 March 2020, and (3) pandemic: 13 March to 20 December 2020. Demographic characteristics (age, race/ethnicity, sexual orientation, and gender identity) were used as predictors for class membership using the three-step method.

RESULTS

Four latent classes were identified: (1) depression/isolation/self-harm (D/I/S) (18,694 texters, 10.4%), (2) interpersonal stress/mood-anxiety (I/M) (32,640 texters, 18.2%), (3) suicidal thoughts/depressed (S/D) (34,067, 19.0%), and (4) adjustment/stress (A/S) (94,096 texters, 52.4%). During the pandemic, an increase in suicidal thoughts and active rescues occurred in the D/I/S and S/D higher-risk subclasses. Characteristics of vulnerable groups in higher-risk classes since the pandemic included children, LGBTQ, American Indian, White, Black, Asian, female, and gender-nonconforming youth.

CONCLUSIONS

Results identified a strong association with class membership in more severe risk classes during the pandemic and an increase in suicidal help-seeking, particularly among children and LGBTQ youth. Low-cost and targeted crisis text-based platforms for support-seeking in youth may be one potential safety net strategy to address the effects of the COVID-19 pandemic on mental health in youth.

Crisis response among essential workers and their children during the COVID-19 pandemic

Limited research has been conducted on the mental health concerns of frontline and essential workers and their children during the COVID-19 pandemic in the United States (U.S.). This study examined the association between working on the frontlines in the U.S. during the COVID-19 pandemic (March to July 2020) and personal crisis text concerns (e.g., self-harm, suicidal thoughts, anxiety/stress, and substance abuse) for frontline essential workers and the children of frontline workers. We used a novel data set from a crisis texting service, Crisis Text Line (CTL), that is widely used throughout the U.S. Generalized Estimating Equations examined the individual association between eight specific crisis types (Depression, Stress/Anxiety, Self-Harm, Suicidal Thoughts, Substance Abuse, Isolation, Relationship Issues, and Abuse) and being in frontline work or being a child of a frontline worker during the early phase of the pandemic. Using CTL concerns as a proxy for the prevalence of mental health issues, we found that children of workers, specifically the youngest demographic (13 years and under), females, and non-conforming youth had a higher risk of specific crisis events during the COVID-19 pandemic. Additionally, Hispanic children of workers reported higher rates of stress/anxiety, whereas African American children of workers had higher rates of abuse and depression. Frontline workers had a higher risk of suicidal thoughts, and the risk of crisis events was generally highest for non-binary, transgender, and male users. Increases in CTL usage among frontline workers were noted across 7-28 days after spikes in local COVID-19 cases. The research to date has focused on the mental health of frontline essential workers, but our study highlights troubling trends in psychological stress among children of these workers. Supportive interventions and mental health resources are needed not only for frontline essential workers, but for their children too.

Spatial Clustering of Adolescent Bereavement in the United States During the COVID-19 Pandemic

PURPOSE

Few studies have examined grief and bereavement in the context of a pandemic, particularly among young people during the ongoing COVID-19 pandemic.

METHODS

The objective of this study is to examine spatiotemporal clustering of bereavement using data from Crisis Text Line, an SMS-based intervention with widespread usage among youth and adolescents in the United States from January 2017 to September 2020.

RESULTS

Results found significant spatial clustering of bereavement during the pandemic period in the late summer months compared with the onset of the pandemic.

CONCLUSION

Our study provides the first evidence of elevated bereavement in adolescents using a technique for rapidly identifying clusters of bereavement risk among this vulnerable subgroup. Findings can be leveraged for targeted interventions and supportive counseling in geographic hotspots.

The driving influences of human perception to extreme heat: A scoping review

Prior research demonstrates a link between heat risk perception and population response to a heat warning. Communicating a precise and understandable definition of "heat" or "heatwaves" can affect how a population perceives and responds to extreme heat. Still, little is known about how heat perception affects behavior changes to heat and heat communication across diverse populations. This scoping review aims to identify and describe the main themes and findings of recent heat perception research globally and map critical research gaps and priorities for future studies. Results revealed risk perception influences a person's exposure to and behavioral response to excessive heat. Risk perception varied geographically along the rural-urban continuum and was typically higher among vulnerable subgroups, including populations who were low-income, minority, and in poor health. A more integrated approach to refining risk communication strategies that result in a behavioral change and incorporates the individual, social, and cultural components of impactful group-based or community-wide interventions is needed. Research employing longitudinal or quasi-experimental designs and advanced statistical techniques are required to tease apart the independent and interacting factors that causally influence risk communication, heat perception, and adaptive behaviors. We advance a framework to conceptualize the structural, environmental, personal, and social drivers of population heat risk perception and how they interact to influence heat perception and adaptive behaviors. Our findings map future research priorities needed for heat perception and a framework to drive future research design.

Analyzing the spatial determinants of local Covid-19 transmission in the United States

The Coronavirus Disease 19 (COVID-19) has quickly spread across the United States (U.S.) since community transmission was first identified in January 2020. While a number of studies have examined individual-level risk factors for COVID-19, few studies have examined geographic hotspots and community drivers associated with spatial patterns in local transmission. The objective of the study is to understand the spatial determinants of the pandemic in counties across the U.S. by comparing socioeconomic variables to case and death data from January 22nd to June 30th 2020. A cluster analysis was performed to examine areas of high-risk, followed by a three-stage regression to examine contextual factors associated with elevated risk patterns for morbidity and mortality. The factors associated with community-level vulnerability included age, disability, language, race, occupation, and urban status. We recommend that cluster detection and spatial analysis be included in population-based surveillance strategies to better inform early case detection and prioritize healthcare resources.

Mapping community-level determinants of COVID-19 transmission in nursing homes: A multi-scale approach

Deaths from the COVID-19 pandemic have disproportionately affected older adults and residents in nursing homes. Although emerging research has identified place-based risk factors for the general population, little research has been conducted for nursing home populations. This GIS-based spatial modeling study aimed to determine the association between nursing home-level metrics and county-level, place-based variables with COVID-19 confirmed cases in nursing homes across the United States. A cross-sectional research design linked data from Centers for Medicare & Medicaid Services, American Community Survey, the 2010 Census, and COVID-19 cases among the general population and nursing homes. Spatial cluster analysis identified specific regions with statistically higher COVID-19 cases and deaths among residents. Multivariate analysis identified risk factors at the nursing home level including, total count of fines, total staffing levels, and LPN staffing levels. County-level or place-based factors like per-capita income, average household size, population density, and minority composition were significant predictors of COVID-19 cases in the nursing home. These results provide a framework for examining further COVID-19 cases in nursing homes and highlight the need to include other community-level variables when considering risk of COVID-19 transmission and outbreaks in nursing homes.

Quasi-experimental evaluation of text-based crisis patterns in youth following Hurricane Florence in the Carolinas, 2018

IMPORTANCE

Crisis text lines have proven to be an effective and low-cost means for delivering texting-based mental health support to youth. Yet there has been limited research examining the use of these services in capturing the psychological impact on youth affected by a weather-related disaster.

OBJECTIVE

This ecologic study examined changes in help-seeking behavior for adolescents and young adults in North and South Carolina, USA, before and after Hurricane Florence (2018).

DESIGN AND MAIN OUTCOMES

A retrospective, interrupted time-series design was used to examine pre- and post-hurricane changes in crisis text volume among youth help seekers in the Carolinas for the following outcomes: (1) text for any reason; (2) stress & anxiety; (3) depression; and (4) suicidal thoughts.

RESULTS

Results showed an immediate and sustained increase in crisis texts for stress/anxiety and suicidal thoughts in the six weeks following Florence. Overall, an immediate 15% increase in crisis texts for anxiety/stress (SE = 0.05, p = .005) and a 17% increase in suicidal thoughts (SE = 0.07, p = .02) occurred during the week of the storm. Text volume for anxiety/stress increased 17% (SE = 0.08, p = .005) and 23% for suicidal ideation (SE = 0.08, p = .01) in the 6-week post-hurricane period. Finally, forecast models revealed observed text volume for all mental health outcomes was higher than expected in the 6 weeks post-Florence.

CONCLUSIONS AND RELEVANCE

A low-cost, crisis texting platform provided 24/7 mental health support available to young people in the Carolinas impacted by Hurricane Florence. These findings highlight a new application for text-based crisis support services to address the mental health consequences in youth following a weather-related disaster, as well as the potential for these types of crisis platforms to measure situational awareness in impacted communities.

Vector-borne Diseases and Climate Change: North Carolina's Policy Should Promote Regional Resilience

Emerging and endemic vector-borne diseases remain significant causes of morbidity and economic burden in North Carolina. Effective policies must promote climate change resilience through public health preparedness at local and regional scales to proactively address the diverse environmental, climatic, and demographic factors amplifying vector-borne disease risk.

Short-term effects of specific humidity and temperature on COVID-19 morbidity in select US cities

Little is known about the environmental conditions that drive the spatiotemporal patterns of SARS-CoV-2. Preliminary research suggests an association with meteorological parameters. However, the relationship with temperature and humidity is not yet apparent for COVID-19 cases in US cities first impacted. The objective of this study is to evaluate the association between COVID-19 cases and meteorological parameters in select US cities. A case-crossover design with a distributed lag nonlinear model was used to evaluate the contribution of ambient temperature and specific humidity on COVID-19 cases in select US cities. The case-crossover examines each COVID case as its own control at different time periods (before and after transmission occurred). We modeled the effect of temperature and humidity on COVID-19 transmission using a lag period of 7 days. A subset of 8 cities were evaluated for the relationship with meteorological parameters and 5 cities were evaluated in detail. Short-term exposure to humidity was positively associated with COVID-19 transmission in 4 cities. The associations were small with 3 out of 4 cities exhibiting higher COVID19 transmission with specific humidity that ranged from 6 to 9 g/kg. Our results suggest that weather should be considered in infectious disease modeling efforts. Future work is needed over a longer time period and across different locations to clearly establish the weather-COVID19 relationship.

Perceptions and experiences of outdoor occupational workers using digital devices for geospatial biometeorological monitoring

Wearable devices have the potential to track and monitor a wide range of biometeorological conditions (e.g., temperature, UV, air quality) and health outcomes (e.g., mental stress, physical activity, physiologic strain, and cognitive impairments). These sensors provide the potential for personalized environmental exposure information that can be harnessed for at-risk populations. Personalized environmental exposure information is of particular importance for populations that are continuously exposed to hazardous environmental conditions or with underlying health conditions. Yet, for these devices to be effective, individuals must be willing to monitor their health and, if prompted, adhere to warnings or notifications. To date, no study has examined the perceptions and use of digital devices and wearable sensors among vulnerable outdoor working populations. This study evaluated digital device use and perceptions among a population of groundworkers in three diverse geographic sites in the southeastern USA (Boone, NC, Raleigh, NC, and Starkville, MS). Our results demonstrate that biometeorological health interventions should focus on smartphone technology as a platform for monitoring environmental exposure and associated health outcomes. It was encouraging to find that those study participants were very likely to wear sensors and utilize global positioning system technology despite potential privacy issues. In addition, 3 out of 4 workers indicated that they would change their behavior if given a personalized heat preventive warning. Future development of wearable sensors and smartphone applications should integrate personalized weather warnings and ensure privacy to facilitate the use of these technologies among vulnerable populations.

Evaluation of wearable sensors for physiologic monitoring of individually experienced temperatures in outdoor workers in southeastern U.S

Climate-related increases in global mean temperature and the intensification of heat waves present a significant threat to outdoor workers. Limited research has been completed to assess the potential differences in heat exposures that exist between individuals within similar microenvironments. Yet, there is a paucity of individual data characterizing patterns of individually experienced temperatures in workers and the associated physiologic heat strain response. The objective of this study was to apply a wearable sensor-based approach to examine the occupational, environmental, and behavioral factors that contribute to individual-level variations in heat strain in grounds maintenance workers. Outdoor workers from three diverse climatic locations in the southeastern United States - high temperature, high temperature + high humidity, and moderate temperature environments - participated in personal heat exposure monitoring during a 5-day work period in the summer. We performed Cox proportional hazards modeling to estimate associations between multiple heat strain events per worker and changes in individually experienced temperatures. Heat strain risk was higher among workers with a place to cool-off, higher education, and who worked in hotter temperatures. A mismatch was observed between workers' perceptions of heat strain and actual heat strain prevalence across exposure groups. We also used a quasi-Poisson regression with distributed lag non-linear function to estimate the non-linear and lag effects of individually experienced temperatures on risk of heat strain. The association between increasing temperature and heat strain was nonlinear and exhibited an U-shaped relationship. Heat strain was less common during issued heat warnings demonstrating behavioral adaptive actions taken by workers. This study is one of the first temperature monitoring studies to quantify the individual-level exposure-response function in this vulnerable population and highlights the elevated risk of heat strain both immediately and several days after worker exposure to high temperatures.

Crisis support-seeking behavior and temperature in the United States: Is there an association in young adults and adolescents?

BACKGROUND

Mounting evidence demonstrates the relationship between high temperatures and adverse mental health outcomes. Yet, no study has examined the influence of temperature on crisis support-seeking behavior among youth in large urban areas.

METHODS

Crisis Text Line (CTL) is a text messaging service that provides crisis interventions for support-seeking individuals for a range of mental-health outcomes in the United States. We applied a distributed lag non-linear modeling technique to assess the short-term impacts of daily maximum and minimum temperature on crisis-related events in four metropolitan locations in the USA.

RESULTS

There were multiple positive associations in three of the four study locations that demonstrate crisis help-seeking behavior increased during anomalously warm conditions.

CONCLUSIONS

This study suggests that there is a significant association between high minimum or maximum temperatures and crisis help-seeking behaviors in young adults and adolescents in urban areas in the United States.

Estimating personal ambient temperature in moderately cold environments for occupationally exposed populations

Despite high mortality and morbidity rates in the winter season, few studies have investigated the health effects from working in moderately cold environments, especially among vulnerable outdoor worker populations in the southeastern US. Yet recent research has shown that the mortality risk from cold events is greatest in southern cities compared to other US locations. We performed repeated personal cold exposure measurements in outdoor grounds management workers in the southeastern US using consumer-based sensors. We recruited outdoor workers from two locations (Raleigh, NC and Boone, NC) each characterized by climatological differences in cold temperature to participate in a 3-week data collection period at the peak of the winter (Jan/Feb 2018). Lower personal ambient temperatures were observed among participants who worked in a warmer climate (Raleigh, NC). The relative risk for cold symptomatology was higher in moderately cold personal ambient temperatures (0 °C to 20 °C) than extremely cold personal ambient temperatures (less than 0 °C). A weak significant relationship was observed between personal ambient temperatures and weather station measurements highlighting that epidemiological researchers should be cautious when investigating the health effects of ambient temperatures based on fixed site measurements. As mobile technology progresses, real-time temperature health monitoring and analysis of environmental conditions at the individual level across multiple occupational-settings will become more feasible and ultimately, we believe, a digitally enhanced workforce will become standard practice in the field.

Crisis Text Line use following the release of Netflix series 13 Reasons Why Season 1: Time-series analysis of help-seeking behavior in youth

The availability of near real-time data from Crisis Text Line (CTL) and other technology-based platforms on crisis events provides an opportunity for targeted interventions prior to serious mental health outcomes (e.g., suicide, self-harm). This study examined the association between the release of the popular Netflix series 13 Reasons Why (13RW) and CTL usage in a national sample of youth in the US. We implemented interrupted time-series, autoregressive integrated moving average (ARIMA) modeling to examine this association at a daily scale. We observed a significant but momentary rise in CTL conversation volume following the release of 13RW on April 5 and 6, 2017 followed by a significant reduction (12.7%) in conversation volume for the overall study period. This reduction in call volume was sustained for 49 days and is the most sustained reduction in conversation volume in the 365 day dataset. This unexpected trough in conversation volume is concerning in light of elevated search engine volume for terms indicating an increase in suicidal thoughts in the days following the release of the show (Ayers et al., 2017). CTL was featured by the show as a resource for viewers in the recently released Season 2, and our results highlight the reasoning and need for such promotion. Future work should explore whether the promotion of CTL in Season 2 positively impacted conversation volume, as there is a clear need to harness the power of these digital technologies to detect population-based trends in mental health and expand the reach of life saving services.

Adolescents in crisis: A geographic exploration of help-seeking behavior using data from Crisis Text Line

Nearly 3 out of 4 all lifelong mental disorders occur by the age of twenty-four. Remote crisis support holds great potential in filling a critical gap in complementing and expanding access to mental health services for acute episodes of mental distress in adolescents and young adults; yet little is understood about the individual factors that influence help-seeking behavior in this group. Recent evidence suggests technology-based mental health services have high acceptability among youth and may be used to treat anxiety and depression. The objective of this study was to examine county-level help-seeking behavior among adolescents and young adults using Crisis Text Line (CTL). CTL is a free, text-based crisis counseling service that has been available nationally since 2013. Spatial error regression was used to (1) identify the individual-level factors that correlate with help-seeking behavior for depression, anxiety, and suicidal thoughts and (2) to explore the geographic trends in text-based help-seeking behavior between adolescents and young adults across the rural-urban continuum. Increased rates of text-based help-seeking occurred in counties with higher mean household incomes, higher divorce rates, and lower residential stability. Rurality was the strongest predictor for low rates of help-seeking, and this finding is particularly concerning in light of elevated rates of suicide among rural counties. Rural communities, particularly those with low support-seeking behavior and comparatively high suicide rates, should be the target of future research and outreach.

Temporal and spatial variation in personal ambient temperatures for outdoor working populations in the southeastern USA

Excessive ambient temperature exposure can result in significant morbidity and mortality, especially among vulnerable occupational groups like outdoor workers. Average temperatures in the USA are projected to increase in frequency and intensity, placing future worker populations at greater risk for unhealthy levels of exposure. Unlike previous research focused on aggregate-level temperature exposures from in situ weather station data, this study will measure location-based personal ambient temperatures (PAT) at the individual-level by piloting the use of wearable sensor technology. A total of 66 outdoor workers in three geographically and climatologically diverse regions in the Southeast USA were continuously sampled during the workday for a 1-week period throughout July 11 to August 8 2016. Results indicate significant worker variation in temperature exposure within and between study locations; with PAT characterized by less pronounced variability as workers moved between indoor and outdoor environments. Developed land covers, a factor often associated with higher temperatures, were poorly correlated with PAT. Future analysis should focus on a worker's physiological response to PAT and mapping of spatial patterns of PAT for a larger worker population to produce innovative and targeted heat prevention programs.

Impact of Extreme Heat Events on Emergency Department Visits in North Carolina (2007-2011)

Extreme heat is the leading cause of weather-related mortality in the U.S. Extreme heat also affects human health through heat stress and can exacerbate underlying medical conditions that lead to increased morbidity and mortality. In this study, data on emergency department (ED) visits for heat-related illness (HRI) and other selected diseases were analyzed during three heat events across North Carolina from 2007 to 2011. These heat events were identified based on the issuance and verification of heat products from local National Weather Service forecast offices (i.e. Heat Advisory, Heat Watch, and Excessive Heat Warning). The observed number of ED visits during these events were compared to the expected number of ED visits during several control periods to determine excess morbidity resulting from extreme heat. All recorded diagnoses were analyzed for each ED visit, thereby providing insight into the specific pathophysiological mechanisms and underlying health conditions associated with exposure to extreme heat. The most common form of HRI was heat exhaustion, while the percentage of visits with heat stroke was relatively low (<10%). The elderly (>65 years of age) were at greatest risk for HRI during the early summer heat event (8.9 visits per 100,000), while young and middle age adults (18-44 years of age) were at greatest risk during the mid-summer event (6.3 visits per 100,000). Many of these visits were likely due to work-related exposure. The most vulnerable demographic during the late summer heat event was adolescents (15-17 years of age), which may relate to the timing of organized sports. This demographic also exhibited the highest visit rate for HRI among all three heat events (10.5 visits per 100,000). Significant increases (p < 0.05) in visits with cardiovascular and cerebrovascular diseases were noted during the three heat events (3-8%). The greatest increases were found in visits with hypotension during the late summer event (23%) and sequelae during the early summer event (30%), while decreases were noted for visits with hemorrhagic stroke during the middle and late summer events (13-24%) and for visits with aneurysm during the early summer event (15%). Significant increases were also noted in visits with respiratory diseases (5-7%). The greatest increases in this category were found in visits with pneumonia and influenza (16%), bronchitis and emphysema (12%), and COPD (14%) during the early summer event. Significant increases in visits with nervous system disorders were also found during the early summer event (16%), while increases in visits with diabetes were noted during the mid-summer event (10%).

Relationships between maximum temperature and heat-related illness across North Carolina, USA

Heat kills more people than any other weather-related event in the USA, resulting in hundreds of fatalities each year. In North Carolina, heat-related illness accounts for over 2,000 yearly emergency department admissions. In this study, data on emergency department (ED) visits for heat-related illness (HRI) were obtained from the North Carolina Disease Event Tracking and Epidemiologic Collection Tool to identify spatiotemporal relationships between temperature and morbidity across six warm seasons (May-September) from 2007 to 2012. Spatiotemporal relationships are explored across different regions (e.g., coastal plain, rural) and demographics (e.g., gender, age) to determine the differential impact of heat stress on populations. This research reveals that most cases of HRI occur on days with climatologically normal temperatures (e.g., 31 to 35 °C); however, HRI rates increase substantially on days with abnormally high daily maximum temperatures (e.g., 31 to 38 °C). HRI ED visits decreased on days with extreme heat (e.g., greater than 38 °C), suggesting that populations are taking preventative measures during extreme heat and therefore mitigating heat-related illness.