Geospatial indicators of exposure, sensitivity, and adaptive capacity to assess neighbourhood variation in vulnerability to climate change-related health hazards

Abstract

Background Although the frequency and magnitude of climate change-related health hazards (CCRHHs) are likely to increase, the population vulnerabilities and corresponding health impacts are dependent on a community’s exposures, pre-existing sensitivities, and adaptive capacities in response to a hazard’s impact. To evaluate spatial variability in relative vulnerability, we: 1) identified climate change-related risk factors at the dissemination area level; 2) created actionable health vulnerability index scores to map community risks to extreme heat, flooding, wildfire smoke, and ground-level ozone; and 3) spatially evaluated vulnerability patterns and priority areas of action to address inequity. Methods A systematic literature review was conducted to identify the determinants of health hazards among populations impacted by CCRHHs. Identified determinants were then grouped into categories of exposure, sensitivity, and adaptive capacity and aligned with available data. Data were aggregated to 4188 Census dissemination areas within two health authorities in British Columbia, Canada. A two-step principal component analysis (PCA) was then used to select and weight variables for each relative vulnerability score. In addition to an overall vulnerability score, exposure, adaptive capacity, and sensitivity sub-scores were computed for each hazard. Scores were then categorised into quintiles and mapped. Results Two hundred eighty-one epidemiological papers met the study criteria and were used to identify 36 determinant indicators that were operationalized across all hazards. For each hazard, 3 to 5 principal components explaining 72 to 94% of the total variance were retained. Sensitivity was weighted much higher for extreme heat, wildfire smoke and ground-level ozone, and adaptive capacity was highly weighted for flooding vulnerability. There was overall varied contribution of adaptive capacity (16–49%) across all hazards. Distinct spatial patterns were observed – for example, although patterns varied by hazard, vulnerability was generally higher in more deprived and more outlying neighbourhoods of the study region. Conclusions The creation of hazard and category-specific vulnerability indices (exposure, adaptive capacity and sensitivity sub-scores) supports evidence-based approaches to prioritize public health responses to climate-related hazards and to reduce inequity by assessing relative differences in vulnerability along with absolute impacts. Future studies can build upon this methodology to further understand the spatial variation in vulnerability and to identify and prioritise actionable areas for adaptation.

Protecting Cardiovascular Health From Wildfire Smoke

“…Exposure maps could be integrated into electronic medical records to provide clinicians with exposure forecasts at the patients' home addresses. 96 Alerts can be sent by phone, email, social media, or medical record services (eg, MyChart), or posted on the provider's website. The US Centers for Disease Control and Prevention provides additional guidance on how to use social media for health messaging.…”

“…Improved forecasting tools are needed to estimate smoke exposures for the coming season. Historical data on smoke exposures can be used to identify high-risk areas, 96 although this approach requires prospective validation. These forecasts could be integrated with data on social vulnerability to identify areas at highest risk.…”

Investigating suicide related behaviours across sexual orientation and neighbourhood deprivation levels: A cohort study using linked health administrative data

“…The ON-Marg indices were joined based on historical postal code data linked by Statistics Canada. The DA has been used as a proxy for residential neighbourhoods [70][71][72][73][74][75] and it is the smallest geographic unit for which Canadian census data are available, with an average population of 400 to 700 residents [76]. The material deprivation measure was created using the following variables from the Census: proportion of the population aged 20+ without a high-school diploma, proportion of families who are single parent families, proportion of total income from government transfer payments for population aged 15+, proportion of the population aged 15+ who are unemployed, proportion of the population considered low-income, and proportion of households living in dwellings that are in need of major repair [28].…”

Suicide-related behaviours across sexual orientation and neighbourhood deprivation levels: a retrospective cohort study using linked health administrative data

“…The material deprivation measure was obtained from the Ontario Marginalisation Index (ON-Marg, 2011 and 2016) at the dissemination area (DA) level. The DA has been used as a proxy for residential neighbourhoods (59)(60)(61)(62)(63)(64), and it is the smallest geographic unit for which Canadian census data are available, with an average population of 400 to 700 residents (65). The material deprivation measure was created using the following variables from the Census: proportion of the population aged 20+ without a high-school diploma, proportion of families who are lone parent families, proportion of total income from government transfer payments for population aged 15+, proportion of the population aged 15+ who are unemployed, proportion of the population considered low-income, and proportion of households living in dwellings that are in need of major repair (28).…”