Evidence map›Paper›PMID 42771258›Full record

ArticleInternational journal of biometeorology2026

Critical engagement on the selection and reporting of biometeorological indices.

Jennifer M Fitchett

Abstract read
In one paragraph

Article in International journal of biometeorology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Jennifer M FitchettSchool of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Witwatersrand, South Africa. Jennifer.Fitchett@wits.ac.za.ORCID http://orcid.org/0000-0002-0854-1720

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past four decades, a plethora of biometeorological indices has emerged. These are enabling the quantification and spatiotemporal comparison of climatic suitabilities and risks for a wide range of activities across indoor and outdoor settings. The relative mathematical simplicity of many of these indices, and the increasing availability of high-quality gridded data, mean that human biometeorological conditions can be computed rapidly and at scale. This is reflected in the literature, with considerable increases in quantitative biometeorological studies over the same period. However, with this computational ease comes a risk of the inadvertent output of spurious results; if the indices have not been carefully selected for their appropriate use for a given location, set of activities, and inherent assumptions. Where these biometeorological index outputs are used in informing policy, which ideally they should be, this risk of misinformation feeding maladaptation needs to be carefully mitigated through a thorough assessment of index applicability, suitability and validity. This paper sets out a conceptual selection framework that is guided by these three variables, following application of this approach in a range of settings, advocating for careful pre-assessment evaluation of indices in their selection. CLINICAL

trial registrationNot applicable.

Indexed as

MeteorologyHumansData availabilityGround-validationMeteorological dataPre-evaluation

Identifiers

PMID42771258
PMCPMC13597613

What OpenQuestion holds

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Registered trials

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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.