ClimaBrain : Impacts of extreme weather events on people living with Alzheimer’s disease or related disorders

Over the past decade, France has experienced worsening impacts of climate change, notably through an increase in the frequency and intensity of heatwaves. These episodes of extreme heat are often accompanied by pollution peaks, particularly ozone peaks, which may have immediate joint adverse effects on health. People living with Alzheimer’s disease and related dementias (ADRD) may be particularly vulnerable to these extreme climate events due to multiple comorbidities, medication use, cognitive impairment, communication difficulties, reduced mobility, or social isolation. However, the health effects of heatwaves and pollution peaks in this specific population remain largely understudied.

Certain subgroups among people living with ADRD may be especially vulnerable and at higher risk of hospitalization and mortality (e.g., depending on gender or socioeconomic status). It is therefore crucial to identify vulnerability profiles that account for a wide range of individual and contextual factors in order to optimize adaptation measures and target those most susceptible to the effects of climate change.

The overall objective of the project is to quantify the magnitude and heterogeneity of the effects of extreme climate events on people living with ADRD in France, with the aim of strengthening warning systems and guiding prevention measures toward the populations and geographic areas at highest risk.

Our project will be based on the use of data collected from French medico-administrative databases (French National Health Data System, SNDS) over the period 2013–2023. The health outcomes studied will include home hospitalizations, emergency department visits, hospital admissions, and deaths.

An algorithm will be used to identify cases of ADRD receiving care within the healthcare system, based on three criteria (medication use, long-term disease status, and hospital admission with an ADRD diagnosis). The extreme events studied will include pollution peaks and heatwaves. 

Several robust statistical approaches will be used to examine the temporal relationships between exposure to extreme climate events and health outcomes (e.g., hospitalizations, deaths). Novel methods based on machine learning algorithms will be applied to identify vulnerability profiles by accounting for numerous individual and environmental factors.

Finally, various qualitative methods will be employed (consultation with an advisory expert committee and four focus groups) to formulate new recommendations tailored to this specific population and refine both the content and format of prevention messages.

This project will provide key results to better understand the impact of environmental exposures related to climate change on people living with ADRD. These findings may help inform public policies in the context of the climate crisis and support the implementation of effective preventive measures to protect people living with ADRD.