Evidence map›Paper›PMID 40291791›Full record

ArticleOpen research Europe2024

Determining the relationship between mobile phone network signal strength and radiofrequency electromagnetic field exposure: protocol and pilot study to derive conversion functions.

Nekane Sandoval-Diez, Lea Belácková, Adriana Fernandes Veludo, Hamed Jalilian, Florence Guida, Isabelle Deltour, Arno Thielens, Marco Zahner, Jürg Fröhlich, Anke Huss and 1 more

Abstract read
In one paragraph

Article in Open research Europe, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

11 authors.

Nekane Sandoval-DiezEpidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, 4123, Switzerland.ORCID https://orcid.org/0000-0001-9916-8601
Lea BeláckováInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, 3584, The Netherlands.
Adriana Fernandes VeludoEpidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, 4123, Switzerland.ORCID https://orcid.org/0000-0003-0479-7128
Hamed JalilianEpidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, 4123, Switzerland.ORCID https://orcid.org/0000-0002-5423-9442
Florence GuidaEnvironment and Lifestyle Epidemiology, International Agency for Research on Cancer, Lyon, 69007, France.
Isabelle DeltourEnvironment and Lifestyle Epidemiology, International Agency for Research on Cancer, Lyon, 69007, France.
Arno ThielensGhent University, Ghent, Flanders, 9052, Belgium.ORCID https://orcid.org/0000-0002-8089-6382
Marco ZahnerFields at Work LLC, Zürich, 8032, Switzerland.ORCID https://orcid.org/0000-0001-6162-8860
Jürg FröhlichFields at Work LLC, Zürich, 8032, Switzerland.ORCID https://orcid.org/0000-0002-5923-3410
Anke HussInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, 3584, The Netherlands.
Martin RöösliEpidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, 4123, Switzerland.ORCID https://orcid.org/0000-0002-7475-1531

Funding

World Health Organization 001
6 · The paper itself

Abstract

Mobile phones continuously monitor and evaluate indicators of the received signal strengths from surrounding base stations to optimise wireless services. These signal strength indicators (SSIs) offer the potential for assessing radiofrequency electromagnetic field (RF-EMF) exposure on a population scale, as they can be related to exposure from both base stations and handset devices. Within the ETAIN (Exposure To electromAgnetic fields and plaNetary health) project, an open-access RF-EMF exposure app for smartphones, named "ETAIN 5G-Scientist", has been developed using citizen science. This paper delineates a measurement protocol for deriving formulas to convert the app SSIs into electric field values to estimate RF-EMF exposure. It presents pilot study results from measurements taken at four locations in France (FR), and 14 locations in the Netherlands (NL), using three different phone models and the most common network providers in each country. The measurements were conducted while executing different usage scenarios, such as calls or data transmission. The exposimeter ExpoM-RF4 and on-body electric field probes were used to measure exposure from far-field sources and the handset, respectively. Two-minute aggregates were considered the sample unit for analyses (n=891 in NL, n=395 in FR). Regression analyses showed a positive log-linear relationship between Long Term Evolution (LTE) Received Signal Strength Indicator (RSSI) and far-field RF-EMF exposure when aggregating data by location (coefficients for normalised RSSI: 0.91 [95% CI: 0.55 - 1.28] in FR, 1.09 [95% CI: 0.96 - 1.22] in NL). Negative log-linear trends were observed for handset-related RF-EMF exposure at the ear (-0.31 [95% CI: -0.46 - -0.16]) and chest (-0.20 [95% CI: -0.37 - -0.03]) during data transmission scenarios. These results demonstrate that the ETAIN 5G-Scientist app can be implemented for smartphone-based RF-EMF estimation. However, uncertainties in individual measurement points highlight the need for further data collection and analysis to improve the accuracy of exposure estimates.

Indexed as

conversion functionsmeasurement protocolRadiofrequency electromagnetic field (RF-EMF) exposuresignal strength indicatorssmartphone appspot measurements

Identifiers

PMID40291791
PMCPMC12032521

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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.