Heat, humidity and health impacts: how causal diagrams can help tell the complex story.

Sivaraj, Sidharth; Zscheischler, Jakob; Buzan, Jonathan R; Martius, Olivia; Brönnimann, Stefan; Vicedo-Cabrera, Ana M (2024). Heat, humidity and health impacts: how causal diagrams can help tell the complex story. Environmental Research Letters, 19(7), 074069. IOP Publishing 10.1088/1748-9326/ad5a25

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The global health burden associated with exposure to heat is a grave concern and is projected to further increase under climate change. While physiological studies have demonstrated the role of humidity alongside temperature in exacerbating heat stress for humans, epidemiological findings remain conflicted. Understanding the intricate relationships between heat, humidity, and health outcomes is crucial to inform adaptation and drive increased global climate change mitigation efforts. This article introduces 'directed acyclic graphs' (DAGs) as causal models to elucidate the analytical complexity in observational epidemiological studies that focus on humid-heat-related health impacts. DAGs are employed to delineate implicit assumptions often overlooked in such studies, depicting humidity as a confounder, mediator, or an effect modifier. We also discuss complexities arising from using composite indices, such as wet-bulb temperature. DAGs representing the health impacts associated with wet-bulb temperature help to understand the limitations in separating the individual effect of humidity from the perceived effect of wet-bulb temperature on health. General examples for regression models corresponding to each of the causal assumptions are also discussed. Our goal is not to prioritize one causal model but to discuss the causal models suitable for representing humid-heat health impacts and highlight the implications of selecting one model over another. We anticipate that the article will pave the way for future quantitative studies on the topic and motivate researchers to explicitly characterize the assumptions underlying their models with DAGs, facilitating accurate interpretations of the findings. This methodology is applicable to similarly complex compound events.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)
08 Faculty of Science > Physics Institute > Climate and Environmental Physics
10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR)
08 Faculty of Science > Institute of Geography

UniBE Contributor:

Sivaraj, Sidharth, Buzan, Jonathan Robert, Romppainen-Martius, Olivia, Brönnimann, Stefan, Vicedo Cabrera, Ana Maria

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services
900 History > 910 Geography & travel
500 Science > 530 Physics
000 Computer science, knowledge & systems

ISSN:

1748-9326

Publisher:

IOP Publishing

Language:

English

Submitter:

Pubmed Import

Date Deposited:

30 Jul 2024 09:45

Last Modified:

09 Aug 2024 12:08

Publisher DOI:

10.1088/1748-9326/ad5a25

PubMed ID:

39070017

Uncontrolled Keywords:

compound events directed acyclic graphs environmental epidemiology wet bulb temperature

BORIS DOI:

10.48350/199363

URI:

https://boris.unibe.ch/id/eprint/199363

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