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
In naturalistic studies, Global Positioning System (GPS) data and date/time stamps can link driver exposure to specific environments (e.g., road types, speed limits, night driving, etc.), providing valuable context for analyzing critical events, such as crashes, near crashes, and breaches of accelerometer limits. In previous work, we showed how to automate this contextualization, using GPS data obtained at 1 Hz and merging this with Geographic Information Systems (GIS) databases maintained by the Iowa Department of Transportation (DOT). Here we further demonstrate our methods by analyzing data from 80 drivers with obstructive sleep apnea (OSA) and 48 controls, and comparing the two groups with respect to several factors of interest. The majority of comparisons found no difference between groups, suggesting similar patterns of exposures to driving environments in OSA and control drivers. However, OSA drivers appeared to spend slightly more time on roads with annual traffic counts of 500-10,000 and less time driving on wider highways, during twilight, and on roads with 10,000-25,000 annual traffic counts.
ABSTRACT
In naturalistic studies, it is vital to give appropriate context when analyzing driving behaviors. Such contextualization can help address the hypotheses that explore a) how drivers perform within specific types of environment (e.g., road types, speed limits, etc.), and b) how often drivers are exposed to such specific environments. In order to perform this contextualization in an automated fashion, we are using Global Positioning System (GPS) data obtained at 1 Hz and merging this with Geographic Information Systems (GIS) databases maintained by the Iowa Department of Transportation (DOT). In this paper, we demonstrate our methods of doing this based on data from 43 drivers with obstructive sleep apnea (OSA). We also use maps from GIS software to illustrate how information can be displayed at the individual drive or day level, and we provide examples of some of the challenges that still need to be addressed.
