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The linear excess relative risk (ERR) is the most commonly reported measure of association in radiation epidemiological studies, when individual dose estimates are available. While the asymptotic properties of the ERR estimator are well understood, there is evidence of small sample bias in case-control studies of treatment-related radiation exposure and second cancer risk. Cohort studies of cancer risk after exposure to low doses of radiation from diagnostic procedures, e.g., computed tomography (CT) examinations, typically have small numbers of cases and risks are small. Therefore, understanding the properties of the estimated ERR is essential for interpretation and analysis of such studies. We present results of a simulation study that evaluates the finite-sample bias of the ERR estimated by time-to-event analyses and its confidence interval using simulated data, resembling a retrospective cohort study of radiation-related leukemia risk after CT examinations in childhood and adolescence. Furthermore, we evaluate how the Firth-corrected estimator reduces the finite-sample bias of the classical estimator. We show that the ERR is overestimated by about 30% for a cohort of about 150,000 individuals, with 42 leukemia cases observed on average. The bias is reduced for higher baseline incidence rates and for higher values of the true ERR. As the number of cases increases, the ERR is approximately unbiased. The Firth correction reduces the bias for all cohort sizes to generally around or under 5%. Epidemiological studies showing an association between radiation exposure from pediatric CT and cancer risk, unless very large, may overestimate the magnitude of the relationship, while there is no evidence of an increased chance for false-positive results. Conducting large studies, perhaps by pooling individual studies to increase the number of cases, should be a priority. If this is not possible, Firth correction should be applied to reduce small-sample bias. [ABSTRACT FROM AUTHOR]

Purpose: Childhood cancer survivors, in particular those treated with radiation therapy, are at high risk of long-term iatrogenic events. The prediction of risk of such events is mainly based on the knowledge of the radiation dose received to healthy organs and tissues during treatment of childhood cancer diagnosed decades ago. We aimed to set up a standardized organ dose table to help former patients and clinicians in charge of long-term follow-up clinics., Methods and Materials: We performed whole body dosimetric reconstruction for 2646 patients from 12 European countries treated between 1941 and 2006 (median, 1976). Most plannings were 2- or 3-dimensional. A total of 46% of patients were treated using Cobalt 60, and 41%, using a linear accelerator. The median prescribed dose was 27.2 Gy (IQ1-IQ3, 17.6-40.0 Gy). A patient-specific voxel-based anthropomorphic phantom with more than 200 anatomic structures or substructures delineated as a surrogate of each subject's anatomy was used. The radiation therapy was simulated with a treatment planning system based on available treatment information. The radiation dose received by any organ of the body was estimated by extending the treatment planning system dose calculation to the whole body, by type and localization of childhood cancer., Results: The integral dose and normal tissue doses to most of the 23 considered organs increased between the 1950s and 1970s and decreased or plateaued thereafter. Whatever the organ considered, the type of childhood cancer explained most of the variability in organ dose. The country of treatment explained only a small part of the variability., Conclusions: The detailed dose estimates provide very useful information for former patients or clinicians who have only limited knowledge about radiation therapy protocols or techniques, but who know the type and site of childhood cancer, sex, age, and year of treatment. This will allow better prediction of the long-term risk of iatrogenic events and better referral to long-term follow-up clinics., (Copyright © 2024. Published by Elsevier Inc.)

Objectives: Assessing occupational exposure to radiofrequency electromagnetic fields (RF-EMF) presents significant challenges due to the considerable variability in exposure levels within and between occupations. This spatial and temporal variability complicates the reliable evaluation of potential health risks associated with RF-EMF exposure in the workplace. Accurate assessment methods are crucial to understand the extent of exposure and to evaluate potential health risks, especially given the potential for higher exposures in occupational settings compared to the general population. This study compares the historical RF-EMF exposure estimates in the INTEROCC RF-EMF job-exposure matrix (RF-JEM) with recent personal measurement data collected in 2 countries as part of the OccRF-Health study, to assess the broader applicability of the RF-JEM., Methods: Weighted kappa (k  w) coefficients and Spearman rank correlation tests were performed to assess the alignment between RF-JEM estimates and measurements for 8 h time-weighted average exposure intensity and prevalence estimates across various occupations. The comparisons were mainly based on 22 jobs having ≥5 measured workers in the OccRF-Health study., Results: Poor agreement was found for both exposure prevalence and intensity between both methods (k  w < 0.1). RF-JEM values likely overestimated exposure levels for both electric (E) and magnetic (H) fields (mean percentage difference >194%) compared to current personal measurements., Conclusions: Findings suggest that the INTEROCC-JEM likely overestimates current exposure intensity levels in the measured jobs. Adopting a semiquantitative JEM could also mitigate misclassification errors due to exposure variability, improving accuracy in exposure assessment. These findings indicate the need for more targeted personal measurements, including among highly exposed workers, and for potentially considering new exposure metrics to more accurately assess occupational RF-EMF exposures in occupational epidemiological research., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Occupational Hygiene Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Radiofrequency electromagnetic fields (RF-EMF, 100 kHz to 300 GHz) are classified by IARC as possibly carcinogenic to humans (Group 2B). This study evaluates the potential association between occupational RF-EMF exposure and brain tumor risk, utilizing for the first time, a RF-EMF job-exposure matrix (RF-JEM) developed in the multi-country INTEROCC case-control study. Cumulative and time-weighted average (TWA) occupational RF-EMF exposures were estimated for study participants based on lifetime job histories linked to the RF-JEM using three different methods: (1) by considering RF-EMF intensity among all exposed jobs, (2) by considering RF-EMF intensity among jobs with an exposure prevalence ≥ the median exposure prevalence of all exposed jobs, and (3) by considering RF-EMF intensity of jobs of participants who reported RF-EMF source use. Stratified conditional logistic regression models were used, considering various lag periods and exposure time windows defined a priori. Generally, no clear associations were found for glioma or meningioma risk. However, some statistically significant positive associations were observed including in the highest exposure categories for glioma for cumulative and TWA exposure in the 1- to 4-year time window for electric fields (E) in the first JEM application method (odds ratios [ORs] = 1.36, 95% confidence interval [95% CI] 1.08, 1.72 and 1.27, 95% CI 1.01, 1.59, respectively), as well as for meningioma for cumulative exposure in the 5- to 9-year time window for electric fields (E) in the third JEM application method (OR = 2.30, 95% CI 1.11, 4.78). We did not identify convincing associations between occupational RF-EMF exposure and risk of glioma or meningioma., (© 2024 The Author(s). International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Risk of depression increased in the general population after the COVID-19 pandemic outbreak. By examining the interplay between genetics and individual environmental exposures during the COVID-19 lockdown, we have been able to gain an insight as to why some individuals are more vulnerable to depression, while others are more resilient. This study, conducted on a Spanish cohort of 9218 individuals (COVICAT), includes a comprehensive non-genetic risk analysis, the exposome, complemented by a genomics analysis in a subset of 2442 participants. Depression levels were evaluated using the Hospital Anxiety and Depression Scale. Together with Polygenic Risk Scores (PRS), we introduced a novel score; Poly-Environmental Risk Scores (PERS) for non-genetic risks to estimate the effect of each cumulative score and gene-environment interaction. We found significant positive associations for PERS Soc (Social and Household), PERS Life (Lifestyle and Behaviour), and PERS Env (Wider Environment and Health) scores across all levels of depression severity, and for PRS B (Broad depression) only for moderate depression (OR 1.2, 95% CI 1.03-1.40). On average OR increased 1.2-fold for PERS Env and 1.6-fold for PER Life and PER Soc from mild to severe depression level. The complete adjusted model explained 16.9% of the variance. We further observed an interaction between PERS Env and PRS B showing a potential mitigating effect. In summary, stressors within the social and behavioral domains emerged as the primary drivers of depression risk in this population, unveiling a mitigating interaction effect that should be interpreted with caution., (© 2024. The Author(s).)

Potential differential and non-differential recall error in mobile phone use (MPU) in the multinational MOBI-Kids case-control study were evaluated. We compared self-reported MPU with network operator billing record data up to 3 months, 1 year, and 2 years before the interview date from 702 subjects aged between 10 and 24 years in eight countries. Spearman rank correlations, Kappa coefficients and geometric mean ratios (GMRs) were used. No material differences in MPU recall estimates between cases and controls were observed. The Spearman rank correlation coefficients between self-reported and recorded MPU in the most recent 3 months were 0.57 and 0.59 for call number and for call duration, respectively. The number of calls was on average underestimated by the participants (GMR = 0.69), while the duration of calls was overestimated (GMR = 1.59). Country, years since start of using a mobile phone, age at time of interview, and sex did not appear to influence recall accuracy for either call number or call duration. A trend in recall error was seen with level of self-reported MPU, with underestimation of use at lower levels and overestimation of use at higher levels for both number and duration of calls. Although both systematic and random errors in self-reported MPU among participants were observed, there was no evidence of differential recall error between cases and controls. Nonetheless, these sources of exposure measurement error warrant consideration in interpretation of the MOBI-Kids case-control study results on the association between children's use of mobile phones and potential brain cancer risk., (© 2024 The Author(s). Bioelectromagnetics published by Wiley Periodicals LLC on behalf of Bioelectromagnetics Society.)

Background: This study aimed to examine the association between risk of brain tumors and radiofrequency (RF) exposure from mobile phones among young people in Korea and Japan., Methods: This case-control study of brain tumors in young people was conducted in Korea and Japan under the framework of the international MOBI-Kids study. We included 118 patients diagnosed with brain tumors between 2011 and 2015 and 236 matched appendicitis controls aged 10-24 years. Information on mobile phone use was collected through face-to-face interviews. A detailed RF exposure algorithm, based on the MOBI-Kids algorithm and modified to account for the specificities of Japanese and Korean phones and networks, was used to calculate the odds ratios (ORs) for total cumulative specific energy using conditional logistic regression., Results: The adjusted ORs in the highest tertile of cumulative call time at 1 year before the reference date were 1.61 (95% confidence interval [CI], 0.72-3.60) for all brain tumors and 0.70 (95% CI, 0.16-3.03) for gliomas, with no indication of a trend with exposure. The ORs for glioma specifically, were below 1 in the lowest exposure category., Conclusion: This study provided no evidence of a causal association between mobile phone use and risk of brain tumors as a whole or of glioma specifically. Further research will be required to evaluate the impact of newer technologies of communication in the future.

Few studies have explored the effects of n utero radiation exposure on human health and cognition and none have taken into account thyroid hormone levels (T3), which have shown to affect cognitive performance. We investigated mechanisms of possible radiation effects on IQ in two cohorts of 250 persons each: exposed n utero after the Chernobyl accident: a 'higher exposure group (HEG)', whose mothers resided in more heavily contaminated territories at the time of the Chernobyl accident, and a 'lesser exposure group (LEG)' whose mothers resided in less contaminated areas. The dataset included information on estimated prenatal thyroid radiation dose, gestation week at the time of the accident (ATA); thyroid hormones: T3 (triiodothyronine) and T4 (thyroxine) levels measured at age 11-12 years and general IQ measured at three time points: t1: 6-7 years old; t2 : 11-12 years old and t3 : 15-16 years old. Descriptive and inference analyses were used to explore the dynamic of changes through time and the associations between key variables at the three time points. Estimated radiation doses to the thyroid gland were substantially higher in the HEG than in the LEG (mean 391 vs 25 mGy respectively). Significant differences in thyroid hormones levels were observed between the two groups, with lower values in T3 (higher in T4) in the LEG. At t1 , the general IQ, as well as verbal and non-verbal IQ scores, were lower in the HEG than in the LEG. In the HEG, analyses adjusting simultaneously for radiation dose, gestational week ATA and T3 levels suggest that all three variables are associated with IQ, with the latter being highest among those exposed later during gestation and decreasing with increasing level of dose and of T3. No significant association was observed between IQ and T4 levels. No effect of exposure on IQ was seen in the LEG. Further investigation of this hypothesis will be important to understand the relation between n utero exposure radiation dose to thyroid, thyroid hormone levels and IQ, taking into account effects of potential confounding factors (physiological stress, maternal anxiety related evacuation).