The intersection of climate-related health outcomes and urban environmental characteristics using spatiotemporal data science

Abstract

BACKGROUND AND AIM: Cities are home to 80% of Canadians of whom have differential vulnerabilities, in population-specific contexts, to climate change impacts on their health. To identify areas within one city - Edmonton, Alberta - experiencing current climate-susceptible health impacts, we explored spatiotemporal patterns of chronic disease and a combination of urban environmental factors. Identifying areas of convergence may help identify where climate change-related severe weather events and worsened air pollution could magnify cardiovascular, renal, respiratory, neurological, mental health, injury, and pregnancy outcomes. METHODS: We merged 1.2M records of patients (2013-2018) from the National Ambulatory Care Reporting System and the Discharge Abstract Database and classified the relevant conditions into the above seven health outcomes. All variables were aggregated/assigned to 1,196 dissemination areas (DA); environmental variables were sourced from the National Air Pollution Surveillance, National Pollutant Release Inventory, Alberta Climate Information System, vegetation “greenness,” and material-social deprivation indices. We analyzed their respective data distributions accounting for both space and time by transforming the events of each health grouping, using seasonal (3-month) time intervals for each DA, into space-time cubes. Then, we input the space-time cubes into emerging hot spot analysis to calculate statistically significant hot and cold spots. RESULTS:Geovisualization of 3-dimensional cubes and 2-dimensional maps helped us identify urban areas with extreme or unusual patterns in health outcomes. Each of the seven health groupings revealed different patterns, which typically coincided with demographics. Through spatial overlays and statistics, we associated the spatiotemporal health-exposure intersections to aid in variable selection for a future vulnerability index. CONCLUSIONS:Our space-time explorations identify where these exposed populations occur and may help target appropriate climate change adaptive capacity interventions. This research is part of a larger project that is generating deeper insight into multiple factors that affect the climate change vulnerabilities and resilience of Alberta populations. KEYWORDS: Exposures, Multi-pollutant, Air pollution, Temperature extremes and variability, Chronic diseases, Spatial data science