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BACKGROUND: Little is known about the exposure of young children to radiofrequency electromagnetic fields (RF-EMF) and potentially associated health effects. We assessed the relationship of RF-EMF exposure from different sources and screen time exposure with emotional and behavioural problems in 5-year-old children. METHODS: Cross-sectional study including 3102 children aged 5 years from the Amsterdam Born Children and their Development (ABCD) study, in the Netherlands. Residential RF-EMF exposure from mobile phone base stations was estimated with a 3D geospatial radio wave propagation model. Residential presence of RF-EMF indoor sources (cordless phone base stations and Wireless Fidelity (WiFi)), children's mobile phone and cordless phone calls and screen time exposure (computer/video game and television watching) was reported by the mother. Teachers (n = 2617) and mothers (n = 3019) independently reported child emotional and behavioural problems using the Strengths and Difficulties Questionnaire. RESULTS: No associations were found between mobile phone and cordless phone calls and emotional and behavioural problems. Children exposed to higher RF-EMF levels from mobile phone base stations showed higher odds of maternal-reported emotional symptoms (OR 1.82, 95%CI 1.07 to 3.09). Children with cordless phone at home had lower odds of teacher-reported problematic prosocial behaviour (OR 0.68, 95%CI 0.48 to 0.97) and of maternal-reported peer relationship problems (OR 0.61, 95% CI 0.39 to 0.96). Children who watched television ≥1.5 h/day had higher odds of maternal-reported hyperactivity/inattention (OR 3.13, 95%CI 1.43 to 6.82). CONCLUSION: Mobile phone and cordless phone calls, which lead to peak RF-EMF exposures to the head, were not associated with any emotional and behavioural problems in 5-year-old children. Environmental RF-EMF exposure from mobile phone base stations and from indoor sources and television watching, which both contribute very little to RF-EMF exposure, were associated with specific emotional and behavioural problems but mainly when reported by the mothers. We cannot, however, discard residual confounding or reverse causality. Further longitudinal research in particular as children will increase the use of telecommunication devices with the age may help to better understand the exact contribution of the different RF-EMF exposure sources if any. Moreover, a thorough control for confounding is essential for a correct interpretation of the studies on screen time and emotional and behavioural problems.

Background Little is known about the exposure of young children to radiofrequency electromagnetic fields (RF-EMF) and potentially associated health effects. We assessed the relationship between residential RF-EMF exposure from mobile phone base stations, residential presence of indoor sources, personal cell phone and cordless phone use, and children's cognitive function at 5–6 years of age. Methods Cross-sectional study on children aged 5–6 years from the Amsterdam Born Children and their Development (ABCD) study, the Netherlands (n=2354). Residential RF-EMF exposure from mobile phone base stations was estimated with a 3D geospatial radio wave propagation model. Residential presence of indoor sources (cordless phone base stations and Wi-Fi) and children's cell phone and cordless phone use was reported by the mother. Speed of information processing, inhibitory control, cognitive flexibility, and visuomotor coordination was assessed using the Amsterdam Neuropsychological Tasks. Results Residential presence of RF-EMF indoor sources was associated with an improved speed of information processing. Higher residential RF-EMF exposure from mobile phone base stations and presence of indoor sources was associated with an improved inhibitory control and cognitive flexibility whereas we observed a reduced inhibitory control and cognitive flexibility with higher personal cordless phone use. Higher residential RF-EMF exposure from mobile phone base stations was associated with a reduced visuomotor coordination whereas we observed an improved visuomotor coordination with residential presence of RF-EMF indoor sources and higher personal cell phone use. Conclusions We found inconsistent associations between different sources of RF-EMF exposure and cognitive function in children aged 5–6 years.

Introduction Geospatial models have been demonstrated to reliably and efficiently estimate RF-EMF exposure from mobile phone base stations (downlink) at stationary locations with the implicit assumption that this reflects personal exposure. In this study we evaluated whether RF-EMF model predictions at the home address are a good proxy of personal 48 h exposure. We furthermore studied potential modification of this association by degree of urbanisation. Method We first used an initial NISMap estimation (at an assumed height of 4.5 m) for 9563 randomly selected addresses in order to oversample addresses with higher exposure levels and achieve exposure contrast. We included 47 individuals across the range of potential RF-EMF exposure and used NISMap to re-assess downlink exposure at the home address (at bedroom height). We computed several indicators to determine the accuracy of the NISMap model predictions. We compared residential RF-EMF model predictions with personal 48 h, at home, and night-time (0:00–8:00 AM) ExpoM3 measurements, and with EME-SPY 140 spot measurements in the bedroom. We obtained information about urbanisation degree and compared the accuracy of model predictions in high and low urbanised areas. Results We found a moderate Spearman correlation between model predictions and personal 48 h (rSp = 0.47), at home (rSp = 0.49), at night (rSp = 0.51) and spot measurements (rSp = 0.54). We found no clear differences between high and low urbanised areas (48 h: high rSp = 0.38, low rSp = 0.55, bedroom spot measurements: high rSp = 0.55, low rSp = 0.50). Discussion We achieved a meaningful ranking of personal downlink exposure irrespective of degree of urbanisation, indicating that these models can provide a good proxy of personal exposure in areas with varying build-up.

BACKGROUND: Epidemiological studies on the potential health effects of RF-EMF from mobile phone base stations require efficient and accurate exposure assessment methods. Previous studies have demonstrated that the 3D geospatial model NISMap is able to rank locations by indoor and outdoor RF-EMF exposure levels. This study extends on previous work by evaluating the suitability of using NISMap to estimate indoor RF-EMF exposure levels at home as a proxy for personal exposure to RF-EMF from mobile phone base stations. METHODS: For 93 individuals in the Netherlands we measured personal exposure to RF-EMF from mobile phone base stations during a 24h period using an EME-SPY 121 exposimeter. Each individual kept a diary from which we extracted the time spent at home and in the bedroom. We used NISMap to model exposure at the home address of the participant (at bedroom height). We then compared model predictions with measurements for the 24h period, when at home, and in the bedroom by the Spearman correlation coefficient (rsp) and by calculating specificity and sensitivity using the 90th percentile of the exposure distribution as a cutpoint for high exposure. RESULTS: We found a low to moderate rsp of 0.36 for the 24h period, 0.51 for measurements at home, and 0.41 for measurements in the bedroom. The specificity was high (0.9) but with a low sensitivity (0.3). DISCUSSION: These results indicate that a meaningful ranking of personal RF-EMF can be achieved, even though the correlation between model predictions and 24h personal RF-EMF measurements is lower than with at home measurements. However, the use of at home RF-EMF field predictions from mobile phone base stations in epidemiological studies leads to significant exposure misclassification that will result in a loss of statistical power to detect health effects.

Background We evaluated if exposure to RF-EMF was associated with reported quality of sleep in 2,361 children, aged 7 years. Methods This study was embedded in the Amsterdam Born Children and their Development (ABCD) birth cohort study. When children were about five years old, school and residential exposure to RF-EMF from base stations was assessed with a geospatial model (NISMap) and from indoor sources (cordless phone/WiFi) using parental self-reports. Parents also reported their children’s use of mobile or cordless phones. When children were seven years old, we evaluated sleep quality as measured with the Child Sleep Habits Questionnaire (CSHQ) filled in by parents. Of eight CSHQ subscales, we evaluated sleep onset delay, sleep duration, night wakenings, parasomnias and daytime sleepiness with logistic or negative binomial regression models, adjusting for child’s age and sex and indicators of socio-economic position of the parents. We evaluated the remaining three subscales (bedtime resistance, sleep anxiety, sleep disordered breathing) as unrelated outcomes (negative control) because these were a priori hypothesised not to be associated with RF-EMF. Results Sleep onset delay, night wakenings, parasomnias and daytime sleepiness were not associated with residential exposure to RF-EMF from base stations. Sleep duration scores were associated with RF-EMF levels from base stations. Higher use mobile phones was associated with less favourable sleep duration, night wakenings and parasomnias, and also with bedtime resistance. Cordless phone use was not related to any of the sleeping scores. Conclusion Given the different results across the evaluated RF-EMF exposure sources and the observed association between mobile phone use and the negative control sleep scale, our study does not support the hypothesis that it is the exposure to RF-EMF that is detrimental to sleep quality in 7-year old children, but potentially other factors that are related to mobile phone usage.

One of the key challenges in environmental epidemiology is the exposure assessment of large populations. Spatial exposure models have been developed that predict exposure to the pollutant of interest for large study sizes. However, the validity of these exposure models is often unknown. In this thesis, we present various aspects that are important for quantifying the accuracy and uncertainty of model predictions. We focus on modelling radiofrequency electromagnetic fields (RF-EMF) from mobile phone base stations. Accurate positional information is essential for both model validation and model input, especially for exposures with high spatial variability such as RF-EMF. GPS-device are increasingly used to obtain positional information, but little is known about their performance for epidemiological studies. We assessed the outdoor accuracy of GPS-devices and found that GPS-errors were on average a few meters large, but over 14% of the errors were larger than 10 m. This potential displacement should be considered when using GPS-devices to obtain positional information. Next, the validity and uncertainty in RF-EMF exposure modelling with the radio wave propagation model NISMap was assessed. The outdoor performance was validated with repeated continuous measurements along predefined ~2 km long paths in five different areas, and the indoor performance with 15-minute spot measurements in 263 rooms in 101 primary schools and 30 private homes in Amsterdam, the Netherlands. We found a Spearman correlation between modelled and measured total downlink RF-EMF of 0.69 for outdoor, and 0.73 for indoor model predictions. The model was not able to accurately predict absolute RF-EMF levels, as model predictions were often a few factors off from measured values. As in many epidemiological studies not all input data are available, we compared models with various levels of input data detail with our outdoor measurement data set. Results showed that the model was able to rank exposure when 3D-building data and basic antenna information were available: Spearman correlations were generally larger than 0.6. The model performance was not sensitive to changes in building damping parameters. Antenna specific information about down-tilt, type and output power did not significantly improve model performance compared with using average down-tilt and power values, or assuming one standard antenna type. Exposure models are also dependent on the accuracy of the input data. With Monte Carlo simulation we assessed the effect of input uncertainty on modelled RF-EMF. The uncertainty was large with a median coefficient of variation of 1.5. The largest uncertainties in model output came from those inputs that influence whether there is an unblocked line-of-sight between antenna and receptor site: the antenna location, building height and receptor site x, y, z location. Epidemiologists should be aware of uncertainty in the prediction of exposure models. By quantifying the accuracy and uncertainty of the exposure model predictions, both the potential and limitations of the exposure assessment can be judged, improving the reliability of environmental epidemiological studies.

Background Identification of active or sedentary modes of transport is of relevance for studies assessing physical activity or addressing exposure assessment. We assessed in a proof-of-principle study if speed as logged by GPSs could be used to identify modes of transport (walking, bicycling, and motorized transport: car, bus or train). Methods 12 persons commuting to work walking, bicycling or with motorized transport carried GPSs for two commutes and recorded their mode of transport. We evaluated seven speed metrics: mean, 95th percentile of speed, standard deviation of the mean, rate-of-change, standardized-rate-of-change, acceleration and deceleration. We assessed which speed metric would best identify the transport mode using discriminant analyses. We applied cross validation and calculated agreement (Cohen’s Kappa) between actual and derived modes of transport. Results Mode of transport was reliably classified whenever a person used a mode of transport for longer than one minute. Best results were observed when using the 95th percentile of speed, acceleration and deceleration (kappa 0.73). When we combined all motorized traffic into one category, kappa increased to 0.95. Conclusions GPS-measured speed enable the identification of modes of transport. Given the current low costs of GPS devices and the built-in capacity of GPS tracking in most smartphones, the use of such devices in large epidemiological studies may facilitate the assessment of physical activity related to transport modes, or improve exposure assessment using automated travel mode detection. Electronic supplementary material The online version of this article (doi:10.1186/1476-072X-13-40) contains supplementary material, which is available to authorized users.

Background: Concerns of the general public about potential adverse health effects caused by radio-frequency electromagnetic fields (RF-EMFs) led authorities to introduce precautionary exposure limits, which vary considerably between regions. It may be speculated that precautionary limits affect the base station network in a manner that mean population exposure unintentionally increases. Aims: The objectives of this multicentre study were to compare mean exposure levels in outdoor areas across four different European cities and to compare with regulatory RF-EMF exposure levels in the corresponding areas. Methods: We performed measurements in the cities of Amsterdam (the Netherlands, regulatory limits for mobile phone base station frequency bands: 41–61 V/m), Basel (Switzerland, 4–6 V/m), Ghent (Belgium, 3–4.5 V/m) and Brussels (Belgium, 2.9–4.3 V/m) using a portable measurement device. Measurements were conducted in three different types of outdoor areas (central and non-central residential areas and downtown), between 2011 and 2012 at 12 different days. On each day, measurements were taken every 4 s for approximately 15 to 30 min per area. Measurements per urban environment were repeated 12 times during 1 year. Results: Arithmetic mean values for mobile phone base station exposure ranged between 0.22 V/m (Basel) and 0.41 V/m (Amsterdam) in all outdoor areas combined. The 95th percentile for total RF-EMF exposure varied between 0.46 V/m (Basel) and 0.82 V/m (Amsterdam) and the 99th percentile between 0.81 V/m (Basel) and 1.20 V/m (Brussels). Conclusions: All exposure levels were far below international reference levels proposed by ICNIRP (International Commission on Non-Ionizing Radiation Protection). Our study did not find indications that lowering the regulatory limit results in higher mobile phone base station exposure levels. Keywords: Portable exposure meter, Radio-frequency electromagnetic fields (RF-EMFs), Regulatory limits, Exposure assessment

OBJECTIVES: There is an ongoing debate regarding environmental health risks of exposures to dust and microbial agents from livestock farming in the Netherlands. The aims of the study were (1) to investigate associations between indicators of air pollution from livestock farms and asthma, allergic rhinitis and chronic obstructive pulmonary disease (COPD) among neighbouring residents; and (2) to assess associations between farm exposures and endotoxin levels in participants' homes. METHODS: Electronic medical records of all 92 548 patients of 27 general practices in a rural area with a high density of animal farms were analysed, followed up by a case-control component using a subsample of the full population. Distance between livestock farms and home address, presence of livestock within 500 m, and particulate matter (PM)10 emissions from farms within 500 m were computed as proxies for farm exposure. Potential confounding was investigated through a case-control questionnaire study in 269 adult patients with asthma and 546 controls. Endotoxin levels were assessed in 493 homes. RESULTS: Modelled PM10 emission was inversely associated with asthma, allergic rhinitis and COPD (p

Background The large increase in mobile communication has led to concern about potential health effects of radio frequency electromagnetic fields (RF-EMF) from mobile phone base stations. Different...