Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 19

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

Time trends in mobile phone use and glioma incidence among males in the Nordic Countries, 1979–2016

Deltour, Isabelle, Poulsen, Aslak Harbo, Johansen, Christoffer, Feychting, Maria, Johannesen, Tom Børge, Auvinen, Anssi, Schüz, Joachim·2022·Environment International
DOI 10.1016/j.envint.2022.107487PMC PMC9463632
Open this paper in CoChat — free account

Abstract

INTRODUCTION: In the Nordic countries, the use of mobile phones increased sharply in the mid-1990s especially among middle-aged men. We investigated time trends in glioma incidence rates (IR) with the perspective to inform about the plausibility of brain tumour risks from mobile phone use reported in some case-control studies. METHODS: We analysed IR of glioma in Denmark, Finland, Norway, and Sweden among men aged 40-69 years, using data from national cancer registries and population statistics during 1979-2016, using log-linear joinpoint analysis. Information on regular mobile phone use and amount of call-time was obtained from major studies of mobile phones in these countries. We compared annual observed incidence with that expected under various risk scenarios to assess which of the reported effect sizes are compatible with the observed IR. The expected numbers of cases were computed accounting for an impact of other factors besides mobile phone use, such as improved cancer registration. RESULTS: Based on 18,232 glioma cases, IR increased slightly but steadily with a change of 0.1% (95 %CI 0.0%; 0.3%) per year during 1979-2016 among 40-59-year-old men and for ages 60-69, by 0.6 % (95 %CI 0.4; 0.9) annually. The observed IR trends among men aged 40-59 years were incompatible with risk ratios (RR) 1.08 or higher with a 10-year lag, RR ≥ 1.2 with 15-year lag and RR ≥ 1.5 with 20-year lag. For the age group 60-69 years, corresponding effect sizes RR ≥ 1.4, ≥2 and ≥ 2.5 could be rejected for lag times 10, 15 and 20 years. DISCUSSION: This study confirms and reinforces the conclusions that no changes in glioma incidence in the Nordic countries have occurred that are consistent with a substantial risk attributable to mobile phone use. This particularly applies to virtually all reported risk increases reported by previous case-control studies with positive findings.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.envint.2022.107487

Cites

30 of 30 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Observed annual IR of gliomas among 40–59 years old men in Denmark, Finland, Norway and Sweden (dots), and in the combined dataset (thin brown line), and best fitting join-point regression lines.
Fig. 1 Observed annual IR of gliomas among 40–59 years old men in Denmark, Finland, Norway and Sweden (dots), and in the combined dataset (thin brown line), and best fitting join-point regression lines.CC BY-NC-ND · PubMed Central
Fig. 2 Observed annual IR of gliomas among 60–69 years old men in Denmark, Finland, Norway and Sweden (dots), and in the combined dataset (thin brown line), and best fitting join-point regression lines.
Fig. 2 Observed annual IR of gliomas among 60–69 years old men in Denmark, Finland, Norway and Sweden (dots), and in the combined dataset (thin brown line), and best fitting join-point regression lines.CC BY-NC-ND · PubMed Central
Fig. 3 Proportion of users among men aged 40–59 years old and 60–69 years old in the Nordic Interphone (NI) and in the Cosmos Denmark (CD) studies.
Fig. 3 Proportion of users among men aged 40–59 years old and 60–69 years old in the Nordic Interphone (NI) and in the Cosmos Denmark (CD) studies.CC BY-NC-ND · PubMed Central
Fig. 4 Proportion of users having accumulated at least 1640 years of mobile phone use, among men aged 40–59 years old and 60–69 years old in the Nordic Interphone (NI) and in the Cosmos Denmark (CD) studies. In the Cosmos questionnaire, responses were elicited using categorical answers (including 30–59 minutes / week, 1–3 hours / week, 4–6 hours /week, >6 hours / week). For this reason, only approximate definition of heavy users could be abstracted and conservative assumptions were used. We assumed that on average, subjects kept the same use between data points and we used the midpoint of the interval as representative of the interval’s range of values. For example, subjects who reported that they used their phone 1–3 hours per week in 2000, were assumed to have accumulated 339 hours of use or more by 2002.
Fig. 4 Proportion of users having accumulated at least 1640 years of mobile phone use, among men aged 40–59 years old and 60–69 years old in the Nordic Interphone (NI) and in the Cosmos Denmark (CD) studies. In the Cosmos questionnaire, responses were elicited using categorical answers (including 30–59 minutes / week, 1–3 hours / week, 4–6 hours /week, >6 hours / week). For this reason, only approximate definition of heavy users could be abstracted and conservative assumptions were used. We assumed that on average, subjects kept the same use between data points and we used the midpoint of the interval as representative of the interval’s range of values. For example, subjects who reported that they used their phone 1–3 hours per week in 2000, were assumed to have accumulated 339 hours of use or more by 2002.CC BY-NC-ND · PubMed Central
Fig. 5 Graphical illustration of SIR analyses. Graphs of observed numbers of cases and expected number of cases over time when half of the baseline increase is explained by the mobile phone related risk and the other half is unexplained, for scenarios of exposure based on the Nordic Interphone controls male 40–59 years old, with a RR of 1.1, and 5 (top left), 10 (top right), 15 (low left), and 20 (low right) years of lag time. Observed (respectively Expected) indicates the observed (respectively expected) number of cases, and “Exp. if no risk” indicates the expected number of cases if the RR was equal to 1. The expected number of cases were statistically significantly different and higher from the observed number of cases in the upper panel, and were not statistically significantly different in the lower panels. It can be seen that towards the end of the period of observation, the expected number of cases was higher than the observed for the upper panels, while observed and expected aligned better in the lower panels.
Fig. 5 Graphical illustration of SIR analyses. Graphs of observed numbers of cases and expected number of cases over time when half of the baseline increase is explained by the mobile phone related risk and the other half is unexplained, for scenarios of exposure based on the Nordic Interphone controls male 40–59 years old, with a RR of 1.1, and 5 (top left), 10 (top right), 15 (low left), and 20 (low right) years of lag time. Observed (respectively Expected) indicates the observed (respectively expected) number of cases, and “Exp. if no risk” indicates the expected number of cases if the RR was equal to 1. The expected number of cases were statistically significantly different and higher from the observed number of cases in the upper panel, and were not statistically significantly different in the lower panels. It can be seen that towards the end of the period of observation, the expected number of cases was higher than the observed for the upper panels, while observed and expected aligned better in the lower panels.CC BY-NC-ND · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 30 references

Cited by

See all 19

Metadata

Authors
Deltour, I., Poulsen, A. H., Johansen, C., Feychting, M., Johannesen, T. B., Auvinen, A., & Schüz, J.
Venue
Environment International
Publisher
Elsevier BV
Published
2022-10
Volume
168
Pages
107487
ISSN
0160-4120
DOI
10.1016/j.envint.2022.107487
PMC
PMC9463632
Cited by
19
References
30
Language
en
Licence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Time trends in mobile phone use and glioma incidence among males in the Nordic Countries, 1979–2016. https://app.cochat.ai/papers/10.1016/j.envint.2022.107487
The paper
Deltour, I., Poulsen, A. H., Johansen, C., Feychting, M., Johannesen, T. B., Auvinen, A., & Schüz, J. (2022). Time trends in mobile phone use and glioma incidence among males in the Nordic Countries, 1979–2016. Environment International. https://doi.org/10.1016/j.envint.2022.107487

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.