Measurements and determinants of children's exposure to background gamma radiation in Switzerland.

Epidemiological studies of children's cancer risks associated with background gamma radiation exposure have used geographic exposure models to estimate exposure at their locations of residence. We measured personal exposure to background gamma radiation, and we investigated the extent to which it was associated with children's whereabouts. We collected data on whereabouts and exposure to background gamma radiation over a 5-day period among children aged 4-15 years in Switzerland. We used D-Shuttle dosimeters to measure children's exposure, and we asked parents to write their children's activities in diaries. We used Poisson mixed-effects and linear regression models to investigate the association of hourly and overall doses, respectively, with children's reported whereabouts. During the observed time, 149 participating children spent 66% indoors at home; 19% indoors away from home; and 15% outdoors. The mean personal exposure was 85.7 nSv/h (range 52.3 nSv/h-145 nSv/h). Exposure was 1.077 (95% CI 1.067, 1.087) times higher indoors than outdoors and varied by building material and (predicted) outdoor dose rates. Our study provides detailed information about children's patterns of exposure to background gamma radiation in Switzerland. Dwelling building materials and outdoor dose rates are important determinants of children's exposure. Future epidemiological studies may benefit from including information about building materials.

External background ionizing radiation and childhood cancer: Update of a nationwide cohort analysis.

BACKGROUND: Exposure to high doses of ionizing radiation is known to cause cancer. Exposure during childhood is associated with a greater excess relative risk for leukemia and tumors of the central nervous system (CNS) than exposure in later life. Cancer risks associated with low-dose exposure (<100 mSv) are uncertain. We previously investigated the association between the incidence of childhood cancer and levels of exposure to external background radiation from terrestrial gamma and cosmic rays in Switzerland using data from a nationwide census-based cohort study. Here, we provide an update of that study using an extended follow-up period and an improved exposure model. METHODS: We included all children 0-15 years of age registered in the Swiss national censuses 1990, 2000, and 2010-2015. We identified incident cancer cases during 1990-2016 using probabilistic record linkage with the Swiss Childhood Cancer Registry. Exposure to terrestrial and cosmic radiation at children's place of residence was estimated using geographic exposure models based on aerial spectrometric gamma-ray measurements. We estimated and included the contribution from 137Cs deposition after the Chernobyl accident. We created a nested case-control sample and fitted conditional logistic regression models adjusting for sex, year of birth, neighborhood socioeconomic position, and modelled outdoor NO2 concentration. We also estimated the population attributable fraction for childhood cancer due to external background radiation. RESULTS: We included 3,401,113 children and identified 3,137 incident cases of cancer, including 951 leukemia, 495 lymphoma, and 701 CNS tumor cases. Median follow-up in the cohort was 6.0 years (interquartile range: 4.3-10.1) and median cumulative exposure since birth was 8.2 mSv (range: 0-31.2). Hazard ratios per 1 mSv increase in cumulative dose of external background radiation were 1.04 (95% CI: 1.01-1.06) for all cancers combined, 1.06 (1.01-1.10) for leukemia, 1.03 (0.98-1.08) for lymphoma, and 1.06 (1.01-1.11) for CNS tumors. Adjustment for potential confounders had little effect on the results. Based on these results, the estimated population attributable fraction for leukemia and CNS tumors due to external background radiation was 32% (7-49%) and 34% (5-51%), respectively. CONCLUSIONS: Our results suggest that background ionizing radiation contributes to the risk of leukemia and CNS tumors in children.

A Comparative Analysis of the Temperature-Mortality Risks Using Different Weather Datasets Across Heterogeneous Regions.

New gridded climate datasets (GCDs) on spatially resolved modeled weather data have recently been released to explore the impacts of climate change. GCDs have been suggested as potential alternatives to weather station data in epidemiological assessments on health impacts of temperature and climate change. These can be particularly useful for assessment in regions that have remained understudied due to limited or low quality weather station data. However to date, no study has critically evaluated the application of GCDs of variable spatial resolution in temperature-mortality assessments across regions of different orography, climate, and size. Here we explored the performance of population-weighted daily mean temperature data from the global ERA5 reanalysis dataset in the 10 regions in the United Kingdom and the 26 cantons in Switzerland, combined with two local high-resolution GCDs (HadUK-grid UKPOC-9 and MeteoSwiss-grid-product, respectively) and compared these to weather station data and unweighted homologous series. We applied quasi-Poisson time series regression with distributed lag nonlinear models to obtain the GCD- and region-specific temperature-mortality associations and calculated the corresponding cold- and heat-related excess mortality. Although the five exposure datasets yielded different average area-level temperature estimates, these deviations did not result in substantial variations in the temperature-mortality association or impacts. Moreover, local population-weighted GCDs showed better overall performance, suggesting that they could be excellent alternatives to help advance knowledge on climate change impacts in remote regions with large climate and population distribution variability, which has remained largely unexplored in present literature due to the lack of reliable exposure data.

Bayesian spatial modelling of terrestrial radiation in Switzerland.

The geographic variation of terrestrial radiation can be exploited in epidemiological studies of the health effects of protracted low-dose exposure. Various methods have been applied to derive maps of this variation. We aimed to construct a map of terrestrial radiation for Switzerland. We used airborne γ-spectrometry measurements to model the ambient dose rates from terrestrial radiation through a Bayesian mixed-effects model and conducted inference using Integrated Nested Laplace Approximation (INLA). We predicted higher levels of ambient dose rates in the alpine regions and Ticino compared with the western and northern parts of Switzerland. We provide a map that can be used for exposure assessment in epidemiological studies and as a baseline map for assessing potential contamination.

Epidemiological studies of natural sources of radiation and childhood cancer: current challenges and future perspectives.

The empirical estimation of cancer risks in children associated with low-dose ionising radiation (<100 mSv) remains a challenge. The main reason is that the required combination of large sample sizes with accurate and comprehensive exposure assessment is difficult to achieve. An international scientific workshop, 'Childhood cancer and background radiation', organised by the Institute of Social and Preventive Medicine of the University of Bern, brought together researchers in this field to evaluate how epidemiological studies of background radiation and childhood cancer can best improve our understanding of the effects of low-dose ionising radiation. This review summarises and evaluates the findings of these studies with regard to their methodological differences, identifies key limitations and challenges, and proposes ways to move forward. Large childhood cancer registries, such as those in Great Britain, France and Germany, now permit the conducting of studies that should have sufficient statistical power to detect the effects predicted by standard risk models. Nevertheless, larger studies or pooled studies will be needed to investigate disease subgroups. The main challenge is to accurately assess children's individual exposure to radiation from natural sources and from other sources, as well as potentially confounding non-radiation exposures, in such large study populations. For this, the study groups should learn from each other to improve exposure estimation and develop new ways to validate exposure models with personal dosimetry.