ArticleStatistical journal of the IAOS2025
Climate change and global health outcome indicators: A scoping review.
Article in Statistical journal of the IAOS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Background: The impact of climate change on human health is not evenly distributed and is affected by regional geography and vulnerability of the local population. Official statistics that report these uneven impacts are needed to facilitate strategic planning and resource allocation. Purpose: Identify globally defined indicators of the impacts of climate change on human health to inform the design of official statistics. Methods: We followed recognized methods guidance for scoping reviews. Results: Reviewing 4415 unique records, we extracted 73 unique and 33 repeated indicators from 20 sources. Temperature-related indicators were the most common (27%, 29/106), but many were repeated. Injury or illness indicators were more frequent than mortality indicators, with 59% (43/73) and 37% (27/73) respectively. Following breakdown of the categories into smaller, more specific outcomes, mortality from extreme weather events (n = 10) and illness due to zoonoses/vector-borne diseases (n = 9) were the most prevalent indicators. There was an absence/gap of indicators for five secondary categories. Conclusion: Synthesis of climate-sensitive health indicators is crucial for establishing a cohesive official statistics framework to monitor the health impacts of climate change-related events. The abundance (and gaps) of indicators across categories of health effects aids in prioritization of developing new indicators and improving data availability.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.