Severe Maternal Morbidity in Georgia, 2009-2020.

BACKGROUND: The increasing focus of population surveillance and research on maternal-and not only fetal and infant-health outcomes is long overdue. The United States maternal mortality rate is higher than any other high-income country, and Georgia is among the highest rates in the country. Severe maternal morbidity (SMM) is conceived of as a "near miss" for maternal mortality, is 50 times more common than maternal death, and efforts to systematically monitor SMM rates in populations have increased in recent years. Much of the current population-based research on SMM has occurred in coastal states or large cities, despite substantial geographical variation with higher maternal and infant health burdens in the Southeast and rural regions. METHODS: This population-based study uses hospital discharge records linked to vital statistics to describe the epidemiology of SMM in Georgia between 2009 and 2020. RESULTS: Georgia had a higher SMM rate than the United States overall (189.2 vs. 144 per 10,000 deliveries in Georgia in 2014, the most recent year with US estimates). SMM was higher among racially minoritized pregnant persons and those at the extremes of age, of lower socioeconomic status, and with comorbid chronic conditions. SMM rates were 5 to 6 times greater for pregnant people delivering infants <1500 grams or <32 weeks' gestation as compared with those delivering normal weight or term infants. Since 2015, SMM has increased in Georgia. CONCLUSION: SMM represents a collection of life-threatening emergencies that are unevenly distributed in the population and require increased attention. This descriptive analysis provides initial guidance for programmatic interventions intending to reduce the burden of SMM and, subsequently, maternal mortality in the US South.

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.

Short-term exposure to temperature and mental health in North Carolina: a distributed lag nonlinear analysis.

Adverse mental health outcomes have been associated with high temperatures in studies worldwide. Few studies explore a broad range of mental health outcomes, and to our knowledge, none are specific to NC, USA. This ecological study explored the relationship between ambient temperature and mental health outcomes (suicide, self-harm and suicide ideation, anxiety and stress, mood disorders, and depression) in six urban counties across the state of NC, USA. We applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM) to examine the short-term effects of daily ambient temperature on emergency admissions for mental health conditions (2016 to 2018) and violent deaths (2004 to 2018). The results were predominately insignificant, with some key exceptions. The county with the greatest temperature range (Wake) displays higher levels of significance, while counties with the lowest temperature ranges (New Hanover and Pitt) are almost entirely insignificant. Self-harm and suicidal ideation peak in the warm months (July) and generally exhibit a protective effect at lower temperatures and shorter lag intervals. Whereas anxiety, depression, and major depressive disorders peak in the cooler months (May and September). Suicide is the only outcome that favored a 20-day lag period in the sensitivity analysis, although the association with temperature was insignificant. Our findings suggest additional research is needed across a suite of mental health outcomes to fully understand the effects of temperatures on mental health.

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.

An Exploratory Spatiotemporal Analysis of Socio-Environmental Patterns in Severe Maternal Morbidity.

OBJECTIVES: Severe Maternal Morbidity (SMM) is a group of pregnancy complications in which a woman nearly dies. Despite its increasing prevalence, little research has evaluated geographic patterns of SMM and the underlying social determinants that influence excess risk. This study examined the spatial clustering of SMM across South Carolina, US, and its associations with place-based social and environmental factors. METHODS: Hospitalized deliveries from 2012 to 2017 were analyzed using Kulldorff's spatial scan statistic to locate areas with abnormally high rates of SMM. SMM patients inside and outside risk clusters were compared using Generalized Estimating Equations (GEE) to determine underlying individual and community-level risk factors. RESULTS: GEE models revealed that the odds of living in a high-risk SMM21 (SMM including blood transfusions) cluster was 2.49 times higher among Black patients (p < .001) compared to those outside of a high-risk cluster. Women residing in a high-risk SMM20 (SMM excluding blood transfusions) cluster were 1.38 times more likely to experience the most number of extremely hot days and 1.70 times more likely to present with obesity than women in a low-risk SMM cluster (p < .001). CONCLUSIONS: This study is the first to characterize the geographic clustering of SMM risk in the US. Our geospatial approach contributes a novel understanding to factors which influence SMM beyond patient-level characteristics and identifies the impact of hot ambient temperature on maternal morbidity. Findings address an important literature gap surrounding place-based risk factors by explaining the contextual social and built environmental factors that drive SMM risk.

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.

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.

Heat exposure misclassification: Do current methods of classifying diurnal range in individually experienced temperatures and heat indices accurately reflect personal exposure?

Wearable sensors have been used to collect information on individual exposure to excessive heat and humidity. To date, no consistent diurnal classification method has been established, potentially resulting in missed opportunities to understand personal diurnal patterns in heat exposure. Using individually experienced temperatures (IET) and heat indices (IEHI) collected in the southeastern United States, this work aims to determine whether current methods of classifying IETs and IEHIs accurately characterize "day," which is typically the warmest conditions, and "night," which is typically the coolest conditions. IET and IEHI data from four locations were compared with the closest hourly weather station. Different day/night classifications were compared to determine efficacy. Results indicate that diurnal IET and IEHI ranges are higher than fixed-site ranges. Maximum IETs and IEHIs are warmer and occur later in the day than ambient conditions. Minimum IETs are lower and occur earlier in the day than at weather stations, which conflicts with previous assumptions that minimum temperatures occur at night. When compared to commonly used classification methods, a method of classifying day and night based on sunrise and sunset times best captured the occurrence of maximum IETs and IEHIs. Maximum IETs and IEHIs are often identified later in the evening, while minimum IETs and IEHIs occur throughout the day. These findings support future research focusing on nighttime heat exposure, which can exacerbate heat-related health issues, and diurnal patterns of personal exposure throughout the entire day as individual patterns do not necessarily follow the diurnal pattern seen in ambient conditions.

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.

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.

Wearable sensors for personal temperature exposure assessments: A comparative study.

The impacts of heat on human health has sparked research on different approaches to measure, map, and predict heat exposure at more accurate and precise spatiotemporal scales. Personal heat sensor studies rely on small sensors that can continuously measure ambient temperatures as individuals move through time and space. The comparison between different types of sensors and sensor placements have yet to be fully researched. The objective of this study is to assess the validity of personal ambient temperature sensors. To accomplish this objective, we evaluated the performance of multiple low-cost wearable sensors (HOBOs, iButton Thermochrons, iButton Hygrochrons, and Kestrel DROP D3FW Fire) for measuring ambient temperature in a (1) field exposure study by varying the placement on human subjects and in a (2) field calibration study by co-locating sensors with fixed site weather station monitors. A secondary aim involved investigating consensus between validation metrics that can be used in future sensor comparison studies. Bland-Altman analysis, correlation coefficients, and index of agreement statistics were used to quantify the difference between sensor and weather station ambient temperature measurements. Results demonstrated significant differences in measured temperatures for sensors based on sensor type and placement on participants. Future research should account for the differences in personal ambient temperature readings based on sensor type and placement.

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.

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.

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.

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.

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.

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.

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.