Evidence map›Paper›PMID 32490302›Full record

ArticleGeoHealth2020

Methods for Estimating Wet Bulb Globe Temperature From Remote and Low-Cost Data: A Comparative Study in Central Alabama.

Anabel W Carter, Benjamin F Zaitchik, Julia M Gohlke, Suwei Wang, Molly B Richardson

Open access · goldAbstract read
In one paragraph

Article in GeoHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.9field-weighted citation impact, top 15% of its field
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

15 citing papers in PubMed, 50 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Anabel W CarterDepartment of Earth and Planetary Sciences Johns Hopkins University Baltimore MD USA.ORCID https://orcid.org/0000-0002-8902-8194
Benjamin F ZaitchikDepartment of Earth and Planetary Sciences Johns Hopkins University Baltimore MD USA.ORCID https://orcid.org/0000-0002-0698-0658
Julia M GohlkeDepartment of Population Health Sciences Virginia Polytechnic Institute and State University Blacksburg VA USA.
Suwei WangDepartment of Population Health Sciences Virginia Polytechnic Institute and State University Blacksburg VA USA.ORCID https://orcid.org/0000-0002-2147-6222
Molly B RichardsonDivision of Preventive Medicine University of Alabama at Birmingham Birmingham AL USA.
Johns Hopkins University · USVirginia Tech · USUniversity of Alabama at Birmingham · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heat stress is a significant health concern that can lead to illness, injury, and mortality. The wet bulb globe temperature (WBGT) index is one method for monitoring environmental heat risk. Generally, WBGT is estimated using a heat stress monitor that includes sensors capable of measuring ambient, wet bulb, and black globe temperature, and these measurements are combined to calculate WBGT. However, this method can be expensive, time consuming, and requires careful attention to ensure accurate and repeatable data. Therefore, researchers have attempted to use standard meteorological measurements, using single data sources as an input (e.g., weather stations) to calculate WBGT. Building on these efforts, we apply data from a variety of sources to calculate WBGT, understand the accuracy of our estimated equation, and compare the performance of different sources of input data. To do this, WBGT measurements were collected from Kestrel 5400 Heat Stress Trackers installed in three locations in Alabama. Data were also drawn from local weather stations, North American Land Data Assimilation System (NLDAS), and low cost iButton hygrometers. We applied previously published equations for estimating natural wet bulb temperature, globe temperature, and WBGT to these diverse data sources. Correlation results showed that WBGT estimates derived from all proxy data sources-weather station, weather station/iButton, NLDAS, NLDAS/iButton-were statistically indistinguishable from each other, or from the Kestrel measurements, at two of the three sites. However, at the same two sites, the addition of iButtons significantly reduced root mean square error and bias compared to other methods.

Indexed as

healthheat stressWBGT

Identifiers

PMID32490302
PMCPMC7240860
OpenAlexW3020172941

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.