ABSTRACT
BACKGROUND: Concurrent heatwave and drought events may have larger health impacts than each event separately; however, no US-based studies have examined differential mental health impacts of compound drought and heatwave events in pediatric populations. OBJECTIVE: To examine the spatial patterns of mood disorders and suicide-related emergency department (ED) visits in children during heatwave, drought, and compound heatwave and drought events. We tested whether the occurrence of compound heatwave and drought events have a synergistic (multiplicative) effect on the risk of mental health related outcomes in children as compared to the additive effect of each individual climate hazard. Lastly, we identified household and community-level determinants of geographic variability of high psychiatric burden. METHODS: Daily counts of psychiatric ED visits in North Carolina from 2016 to 2019 (May to Sept) for pediatric populations were aggregated at the county scale. Bernoulli cluster analyses identified high-risk spatial clusters of psychiatric morbidity during heatwave, drought, or compound heatwave and drought periods. Multivariate adaptive regression models examined the individual importance of household and community-level determinants in predicting high-risk clustering of mood disorders or suicidality across the three climate threats. RESULTS: Results showed significant spatial clustering of suicide and mood disorder risks in children during heatwave, drought, and compound event periods. Periods of drought were associated with the highest likelihood of spatial clustering for suicide and mood disorders, where the risk of an ED visit was 4.48 and 6.32 times higher, respectively, compared to non-drought periods. Compounding events were associated with a threefold increase in both suicide and mood disorder-related ED visits. Community and household vulnerability factors that most contributed to spatial clustering varied across climate hazards, but consistent determinants included residential segregation, green space availability, low English proficiency, overcrowding, no broadband access, no vehicle access, housing vacancy, and availability of housing units. CONCLUSION: Findings advance understanding on the locations of vulnerable pediatric populations who are disproportionately exposed to compounding climate stressors and identify community resilience factors to target in public health adaptation strategies.
ABSTRACT
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.
