Wireless phone use in childhood and adolescence and neuroepithelial brain tumours: Results from the international MOBI-Kids study
Bibliographic record
Abstract
In recent decades, the possibility that use of mobile communicating devices, particularly wireless (mobile and cordless) phones, may increase brain tumour risk, has been a concern, particularly given the considerable increase in their use by young people. MOBI-Kids, a 14-country (Australia, Austria, Canada, France, Germany, Greece, India, Israel, Italy, Japan, Korea, the Netherlands, New Zealand, Spain) case-control study, was conducted to evaluate whether wireless phone use (and particularly resulting exposure to radiofrequency (RF) and extremely low frequency (ELF) electromagnetic fields (EMF)) increases risk of brain tumours in young people. Between 2010 and 2015, the study recruited 899 people with brain tumours aged 10 to 24 years old and 1,910 controls (operated for appendicitis) matched to the cases on date of diagnosis, study region and age. Participation rates were 72% for cases and 54% for controls. The mean ages of cases and controls were 16.5 and 16.6 years, respectively; 57% were males. The vast majority of study participants were wireless phones users, even in the youngest age group, and the study included substantial numbers of long-term (over 10 years) users: 22% overall, 51% in the 20-24-year-olds. Most tumours were of the neuroepithelial type (NBT; n = 671), mainly glioma. The odds ratios (OR) of NBT appeared to decrease with increasing time since start of use of wireless phones, cumulative number of calls and cumulative call time, particularly in the 15-19 years old age group. A decreasing trend in ORs was also observed with increasing estimated cumulative RF specific energy and ELF induced current density at the location of the tumour. Further analyses suggest that the large number of ORs below 1 in this study is unlikely to represent an unknown causal preventive effect of mobile phone exposure: they can be at least partially explained by differential recall by proxies and prodromal symptoms affecting phone use before diagnosis of the cases. We cannot rule out, however, residual confounding from sources we did not measure. Overall, our study provides no evidence of a causal association between wireless phone use and brain tumours in young people. However, the sources of bias summarised above prevent us from ruling out a small increased risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".