The effect modification of extreme temperatures on mental and behavior disorders by environmental factors and individual-level characteristics in Canada.

OBJECTIVE: Ambient extreme temperatures have been associated with mental and behavior disorders (MBDs). However, few studies have assesed whether vulnerability factors such as ambient air pollution, pre-existing mental health conditions and residential environmental factors increase susceptibility. This study aims to evaluate the associations between short-term variations in outdoor ambient extreme temperatures and MBD-related emergency department (ED) visits and how these associations are modified by vulnerability factors. METHODS: We conducted a case-crossover study of 9,958,759 MBD ED visits in Alberta and Ontario, Canada made between March 1st, 2004 and December 31st, 2020. Daily average temperature was assigned to individual cases with ED visits for MBD using gridded data at a 1 km × 1 km spatial resolution. Conditional logistic regression was used to estimate associations between extreme temperatures (i.e., risk of ED visit at the 2.5th percentile temperature for cold and 97.5th percentile temperature for heat for each health region compared to the minimal temperature risk) and MBD ED visits. Age, sex, pre-existing mental health conditions, ambient air pollution (i.e. PM2.5, NO2 and O3) and residential environmental factors (neighborhood deprivation, residential green space exposure and urbanization) were evaluated as potential effect modifiers. RESULTS: Cumulative exposure to extreme heat over 0-5 days (odds ratio [OR] = 1.145; 95% CI: 1.121-1.171) was associated with ED visits for any MBD. However, cumulative exposure to extreme cold was associated with lower risk of ED visits for any MBD (OR = 0.981; 95% CI: 0.976-0.987). We also found heat to be associated with ED visits for specific MBDs such as substance use disorders, dementia, neurotic disorders, schizophrenia and personality behavior disorder. Individuals with pre-existing mental health conditions, those exposed to higher daily concentrations of NO2 and O3 and those residing in neighborhoods with greater material and social deprivation were at higher risk of heat-related MBD ED visits. Increasing tree canopy coverage appeared to mitigate risks of the effect of heat on MBD ED visits. CONCLUSIONS: Findings provide evidence that the impacts of heat on MBD ED visits may vary across different vulnerability factors.

Vulnerability assessment of heat waves within a risk framework using artificial intelligence.

Current efforts to adapt to climate change are not sufficient to reduce projected impacts. Vulnerability assessments are essential to allocate resources where they are needed most. However, current assessments that use principal component analysis suffer from multiple shortcomings and are hard to translate into concrete actions. To address these issues, this article proposes a novel data-driven vulnerability assessment within a risk framework. The framework is based on the definitions from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, but some definitions, such as sensitivity and adaptive capacity, are clarified. Heat waves that occurred between 2001 and 2018 in Quebec (Canada) are used to validate the framework. The studied impact is the daily mortality rates per cooling degree-days (CDD) region. A vulnerability map is produced to identify the distributions of summer mortality rates in aggregate dissemination areas within each CDD region. Socioeconomic and environmental variables are used to calculate impact and vulnerability. We compared abilities of AutoGluon (an AutoML framework), Gaussian process, and deep Gaussian process to model the impact and vulnerability. We offer advice on how to avoid common pitfalls with artificial intelligence and machine-learning algorithms. Gaussian process is a promising approach for supporting the proposed framework. SHAP values provide an explanation for the model results and are consistent with current knowledge of vulnerability. Recommendations are made to implement the proposed framework quantitatively or qualitatively.