Wireless phones and brain tumour risk in young people: results of the multi-national MOBI-Kids study
Bibliographic record
Abstract
Background and aim. The possibility that wireless (mobile and cordless) phone use might increase brain tumour (BT) risk, has long been a concern, particularly in young people. We studied the association between wireless phone use and subsquently radiofrequency (RF) and extremely low frequency (ELF) electromagnetic fields (EMF) exposure) in childhood/adolescence with BT risk. Methods. MOBI-Kids, a 14-country case-control study, recruited 899 BT cases and 1910 hospital controls aged 10-24 years. Each participant answered a questionnaire on history of mobile communication devices use. Analyses were conducted both in relation to the history of use of wireless phones and to estimated RF and ELF dose from use of wireless phones (based on algorithms developed in the project), adjusting for parental education. Numerous substudies and sensitivity analyses were conducted to address potential biases. Results. Mean ages of cases and controls were 16.5 and 16.6 years, respectively. The vast majority of participants were wireless phones users, with substantial numbers of long-term (>10 years) users. Most tumours were neuroepithelial (NBT; n=671). The adjusted 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. These decreasing trends are attributable mainly to differential recall by proxies and prodromal symptoms affecting phone use before case diagnosis. Results remain unchanged despite the large number of sensitivity analyses we conducted. Conclusions. Our study provides no evidence of a causal association between wireless phone use and brain tumours in young people. However, possible residual biases prevent us from ruling out a small increased risk. Keyworks: brain tumours, young people, wireless phones
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".