Ecological momentary assessment study of exposure to radiofrequency electromagnetic fields and non-specific physical symptoms with self-declared electrosensitives.

The main objective of the study is to determine if non-specific physical symptoms (NSPS) in people with self-declared sensitivity to radiofrequency electromagnetic fields (RF EMF) can be explained (across subjects) by exposure to RF EMF. Furthermore, we pioneered whether analysis at the individual level or at the group level may lead to different conclusions. By our knowledge, this is the first longitudinal study exploring the data at the individual level. A group of 57 participants was equipped with a measurement set for five consecutive days. The measurement set consisted of a body worn exposimeter measuring the radiofrequency electromagnetic field in twelve frequency bands used for communication, a GPS logger, and an electronic diary giving cues at random intervals within a two to three hour interval. At every cue, a questionnaire on the most important health complaint and nine NSPS had to be filled out. We analysed the (time-lagged) associations between RF-EMF exposure in the included frequency bands and the total number of NSPS and self-rated severity of the most important health complaint. The manifestation of NSPS was studied during two different time lags - 0-1 h, and 1-4 h - after exposure and for different exposure metrics of RF EMF. The exposure was characterised by exposure metrics describing the central tendency and the intermittency of the signal, i.e. the time-weighted average exposure, the time above an exposure level or the rate of change metric. At group level, there was no statistically significant and relevant (fixed effect) association between the measured personal exposure to RF EMF and NSPS. At individual level, after correction for multiple testing and confounding, we found significant within-person associations between WiFi (the self-declared most important source) exposure metrics and the total NSPS score and severity of the most important complaint in one participant. However, it cannot be ruled out that this association is explained by residual confounding due to imperfect control for location or activities. Therefore, the outcomes have to be regarded very prudently. The significant associations were found for the short and the long time lag, but not always concurrently, so both provide complementary information. We also conclude that analyses at the individual level can lead to different findings when compared to an analysis at group level.

Lessons learnt on biases and uncertainties in personal exposure measurement surveys of radiofrequency electromagnetic fields with exposimeters.

Personal exposure measurements of radio frequency electromagnetic fields are important for epidemiological studies and developing prediction models. Minimizing biases and uncertainties and handling spatial and temporal variability are important aspects of these measurements. This paper reviews the lessons learnt from testing the different types of exposimeters and from personal exposure measurement surveys performed between 2005 and 2015. Applying them will improve the comparability and ranking of exposure levels for different microenvironments, activities or (groups of) people, such that epidemiological studies are better capable of finding potential weak correlations with health effects. Over 20 papers have been published on how to prevent biases and minimize uncertainties due to: mechanical errors; design of hardware and software filters; anisotropy; and influence of the body. A number of biases can be corrected for by determining multiplicative correction factors. In addition a good protocol on how to wear the exposimeter, a sufficiently small sampling interval and sufficiently long measurement duration will minimize biases. Corrections to biases are possible for: non-detects through detection limit, erroneous manufacturer calibration and temporal drift. Corrections not deemed necessary, because no significant biases have been observed, are: linearity in response and resolution. Corrections difficult to perform after measurements are for: modulation/duty cycle sensitivity; out of band response aka cross talk; temperature and humidity sensitivity. Corrections not possible to perform after measurements are for: multiple signals detection in one band; flatness of response within a frequency band; anisotropy to waves of different elevation angle. An analysis of 20 microenvironmental surveys showed that early studies using exposimeters with logarithmic detectors, overestimated exposure to signals with bursts, such as in uplink signals from mobile phones and WiFi appliances. Further, the possible corrections for biases have not been fully applied. The main findings are that if the biases are not corrected for, the actual exposure will on average be underestimated.

Do car-mounted mobile measurements used for radio-frequency spectrum regulation have an application for exposure assessments in epidemiological studies?

Knowing the spatial and temporal trends in environmental exposure to radiofrequency electromagnetic fields is important in studies investigating whether there are associated health effects on humans and ecological effects on plants and animals. The main objective of this study is to assess whether the RFeye car-mounted mobile measurement system used for radio frequency spectrum monitoring in The Netherlands and the United Kingdom could be of value in assessing exposure over large areas as an alternative to measuring exposure with personal exposure meters or using complex modelling techniques. We evaluated the responses of various body-worn personal exposure meters in comparison with the mobile measurement system for spectrum monitoring. The comparison was restricted to downlink mobile communication in the GSM900 and GSM1800 frequency bands. Repeated measurements were performed in three areas in Cambridge, United Kingdom and in three areas in Amersfoort, The Netherlands. We found that exposure assessments through the car-mounted measurements are at least of similar quality to exposure modelling and better than the body worn exposimeter data due to the absence of the shielding effect. The main conclusion is that the mobile measurements provide an efficient and low cost alternative particularly in mapping large areas.

Validity of at home model predictions as a proxy for personal exposure to radiofrequency electromagnetic fields from mobile phone base stations.

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.

Everyday exposure to power frequency magnetic fields and associations with non-specific physical symptoms.

The aim of this study was to investigate the association between exposure to extremely low frequency magnetic fields (ELF MF), or power frequency fields, and non-specific physical symptoms (NSPS). In across-sectional study, personal exposure to ELF MF was measured for 99 adults selected in and around Amsterdam, the Netherlands in 2009-2010. They were scored on 16 NSPS. As a cut-off point for the individual 24-h time weighted average exposure the 80-percentile (0.09 mT) was chosen. As only one man scored "moderately high" on the somatisation scale against nine women, we decided to proceed analyses only with the 48 women. The crude odds ratio (OR) for women was 8.50 (CI 95%: 1.73-46.75), suggesting that for women environmental exposure to ELF MF is associated with an increased score on NSPS. As this is an exploratory cross-sectional study in a relatively small sample, no conclusions regarding causality can be drawn.

Investigating short-term exposure to electromagnetic fields on reproductive capacity of invertebrates in the field situation.

Organisms are exposed to electromagnetic fields from the introduction of wireless networks that send information all over the world. In this study we examined the impact of exposure to the fields from mobile phone base stations (GSM 900 MHz) on the reproductive capacity of small, virgin, invertebrates. A field experiment was performed exposing four different invertebrate species at different distances from a radiofrequency electromagnetic fields (RF EMF) transmitter for a 48-h period. The control groups were isolated from EMF exposure by use of Faraday cages. The response variables as measured in the laboratory were fecundity and number of offspring. Results showed that distance was not an adequate proxy to explain dose-response regressions. No significant impact of the exposure matrices, measures of central tendency and temporal variability of EMF, on reproductive endpoints was found. Finding no impact on reproductive capacity does not fully exclude the existence of EMF impact, since mechanistically models hypothesizing non-thermal-induced biological effects from RF exposure are still to be developed. The exposure to RF EMF is ubiquitous and is still increasing rapidly over large areas. We plea for more attention toward the possible impacts of EMF on biodiversity.

Design of an ecological momentary assessment study of exposure to radiofrequency electromagnetic fields and non-specific physical symptoms.

INTRODUCTION: Idiopathic Environmental Intolerance (IEI) attributed to electromagnetic fields (EMF) refers to self-reported sensitivity mainly characterised by the attribution of non-specific physical symptoms to low-level EMF exposure emitted from sources such as mobile phones. Scientific studies have not provided evidence for the existence of IEI-EMF, but these studies did not resemble the real-life situation or suffered from poor exposure characterisation and biased recall of health symptoms. To improve existing methods for the study of IEI-EMF, an Ecological Momentary Assessment (EMA) study is designed. METHODS AND ANALYSIS: The study is an EMA study in which respondents carry personal exposure metres (exposimeters) that measure radiofrequency (RF) EMF, with frequent assessment of health symptoms and perceived EMF exposure through electronic diary registration during five consecutive days. Participants will be a selection from an epidemiological study who report to be sensitive to RF EMF. The exposimeters measure electric field strength in 12 frequency bands. Diary questions include the occurrence and severity of 10 non-specific physical symptoms, mood states and perceived exposure to (sources of) EMF. The relationship of actual and perceived EMF exposure and mood with non-specific physical symptoms will be analysed using multilevel regression analysis with time-shift models. DISCUSSION: The study has several advantages over previous studies, including assessment of personal EMF exposure and non-specific physical symptoms by an ecological method with a minimised chance of recall bias. The within-person design reduces confounding by time-stable factors (eg, personal characteristics). In the conduct of the study and the analysis and interpretation of its outcomes, some methodological issues including a high participant burden, reactivity, compliance to the study protocol and the potential of chance findings due to multiple statistical testing will be accounted for and limited as much as possible.

Personal radiofrequency electromagnetic field measurements in The Netherlands: exposure level and variability for everyday activities, times of day and types of area.

Knowledge of the exposure to radiofrequency electromagnetic fields is necessary for epidemiological studies on possible health effects. The main goal of this study is to determine the exposure level and spatial and temporal variances during 39 everyday activities in 12 frequency bands used in mobile telecommunication and broadcasting. Therefore, 24 h measurements were gathered from 98 volunteers living in or near Amsterdam and Purmerend, The Netherlands. They carried an activity diary to be kept to the minute, a GPS logger sampling at an interval of 1 s, and an EME Spy exposimeter with a detection limit of 0.0066 mW/m(2) sampling at an interval of 10s in 12 frequency bands. The mean exposure over 24 h, excluding own mobile phone use, was 0.180 mW/m(2). During daytime exposure was about the same, but during night it was about half, and in the evening it was about twice as high. The main contribution to environmental exposure (calling by participant not included) is from calling with mobile phones (37.5%), from cordless DECT phones and their docking stations (31.7%), and from the base stations (12.7%). The exposure to mobile phone base stations increases with the percentage of urban ground use, which is an indication for high people density. In agreement, the highest mean exposure relates to the activities with high people density, such as travelling by public transport, visiting social events, pubs or shopping malls. Exposure at home depends mainly on exposure from people calling in the neighbourhood of the participant and thus on the number of persons in a household. In addition just the possession of DECT docking stations leads to exposure as most models transmit continuously in stand-by. Also wireless internet routers continuously transmit in the WiFi band. Though the highest exposure peaks in the WiFi band, up to 0.265 W/m(2), come from stray radiation of microwave ovens. The mean total exposure largely depends on phone calls of a high exposure level and short duration. These calls lead to potentially high contrasts as well in exposure levels between sessions of the same activity as between persons, thus posing a challenge for personal exposure prediction.

Calibration and uncertainties in personal exposure measurements of radiofrequency electromagnetic fields.

In the past 5 years radiofrequency personal exposure meters have been used to characterize the exposure during daily activities. We found from calibration tests for the 12 frequency bands of the EME Spy 121 exposimeter in a Gigahertz Transverse Electromagnetic cell and an Open Area Test Site, that these measurements tend to underestimate the actual exposure. Therefore, a maximum frequency-dependent correction factor of 1.1-1.6 should be applied to the electric field. This correction factor consists of three multipliers correcting for calibration, elevation arrival angle, and influence of the body. The calibration correction factor should be determined per exposimeter, as the maximum range of response between exposimeters in a frequency band is 2.4 dB. Since the range of response for different elevation angles could reach 10.2 dB, a strict protocol for wearing the exposimeter during fieldwork should be followed to be able to compare and combine measurements made by different persons in the same microenvironments. Because the influence of the body depends on the azimuth angle of arrival, it may lead to an over- or underestimation. Thus, the body correction factor is an average over the angles and should only be applied in activities involving movement through the full 360° range of random angles of arrival.