Arne Wennberg

Occupational exposure to electromagnetic fields in relation to leukemia and brain tumors: a case-control study in Sweden

Occupational exposure to low-frequency electromagnetic fields (EMF) was studied in 250 leukemia patients and 261 brain-tumor cases, diagnosed in 1983–87 and compared with a control group of 1,121 randomly selected men, from the mid-region of Sweden, 1983–87. We based the exposure assessment on measurements from 1,015 different workplaces. On the basis of the job held longest during the 10-year period before diagnosis, we found an association between the average, daily, mean level of EMF and chronic lymphocytic leukemia (CLL). The risk increased with increasing level of exposure. The odds ratios (OR) and the 95 percent confidence interval (CI) for three consecutive levels of exposure were: 1.1 (CI=0.5–2.3); 2.2 (CI=1.1–4.3); 3.0 (CI=1.6–5.8), respectively. No association was observed for acute myeloid leukemia (OR=1.0, CI=0.5–1.8; OR=0.8, CI=0.4–1.6; OR=1.0, CI=0.6–1.9). For brain tumors, the corresponding risk estimates were 1.0 (CI=0.7–1.6); 1.5 (CI=1.0–2.2); 1.4 (CI=0.9–2.1). Different EMF indices were tested. Tasks with frequent or large variations between high and low field-densities (high standard deviation) were more common among CLL subjects. For brain tumors, a prolonged high level (high median values) showed the strongest association. Confounding by place of residence, smoking, benzene, ionizing radiation, pesticides, and solvents was evaluated, and these factors did not seem to have a decisive influence on the associations. We also analyzed other potential sources of bias. For CLL, there were indications of an excess number of low-exposure subjects among non-responders, which, to some extent, may have enhanced but not caused the risk estimates obtained. Our conclusion is that the study supports the hypothesis that occupational EMF exposure is a hazard in the development of certain cancers.

Application of a computer-based model for EEG analysis ☆

Abstract The parameter analysis of EEG is based upon a model that describes its spectral properties in parametric form. The spectrum is divided into several components of two general types, I and II. A component of Type I has its greatest spectral density at zero frequency and is described by one frequency parameter, the bandwidth, and one power parameter, the power content. A component of Type II is described by two frequency parameters, the centre frequency and the bandwidth, and by two power parameters, the power content and a parameter describing spectral asymmetry around the centre frequency. A computer program is available for estimating the EEG parameters and for calculating the statistical uncertainty in these parameters. This study is a first attempt to apply the analysis in practice. In twenty-five healthy young men, EEGs classified as normal on visual evaluation were selected for analysis. Continuous records of 20–120 sec duration were selected for analysis and checked to be free from artefacts. The analysis was carried out with a model of fifth order which, in most cases, resulted in a spectrum with one component of Type I and two components of Type II, called delta, alpha and beta components. The physiological interpretation of these parameters is discussed. The estimated parameters for the whole group are summarized in terms of mean values and standard deviations. The analysis permits an exact determination of the parameters and their relationships. The hypothesis that beta activity is a harmonic of alpha activity is discussed. The relation between the bandwidths for delta and alpha components is investigated. Detailed studies are made on the alpha activity: a comparison of the power content in different regions of the brain, the relation between bandwidth and power content and a comparison of the centre frequency and power content for recordings taken symmetrically on the skull. Variations with time in the centre frequency of the alpha activity have been studied.

Visual evaluation and computer analysis of the EEG—A comparison ☆

Spectral parameter analysis (SPA) of the EEG provides a description of the distribution of spectral power in the EEG signal in the form of a rational spectrum with not more than 8 parameters. The spectrum is divided into 1-3 components described by frequency and power parameters: bandwidth (delta), peak frequency (f) and power (G). These spectral parameters are determined with the aid of a computer. The character of the EEG signal decides whether 1, 2 or 3 components (delta, alpha, beta) are needed to describe the spectrum. To test its practical value, the result of SPA was compared with that of ordinary visual evaluation of the EEG of 65 healthy men between the ages of 18 and 22 years. 20 sec sections from different leads were analysed and evaluated visually. Each EEG section was graded according to the amount of visually evaluated slow activity (VESA). To investigate the relation between the degree of VESA and the SPA result, statistical calculations (variance and regression analyses) were carried out, both for single SPA parameters and for the general type of spectrum, i.e., the number of components composing the spectrum. The SPA results from sections with artefacts were treated separately and compared statistically with results from artefact-free sections. In records with a high degree of VESA, all the leads analysed showed a tendency to have a power spectrum of low order, i.e., with few components. In most leads there was a linear regression between the degree of VESA and the bandwidth and power of the delta and alpha components. In several cases this relation was an expression of a significant linear change of the SPA parameter as a function of the degree of VESA. On the other hand the parameters of the beta component showed no relation to the degree of VESA. It was found that muscle activity could influence any spectral component thereby providing it with a strongly increased bandwidth. This is probably due to the fact that muscle activity resembles white noise in this particular frequency range. Low frequency artefacts affected only the delta component the bandwidth of which was significantly smaller than in the artefact-free sections.

An EEG simulator—a means of objective clinical interpretation of EEG

In 1969 Zetterberg presented a method for describing the spectral properties of an EEG signal, starting from the assumption that the signal is essentially stationary during the analysis epoch. The method involves determination of the parameters for a model consisting of a lenear filter with the ability to produce a signal with the same spectral properties as the EEG signal. Zetterberg and Ahlin described in 1975 an analogue simulator based on this model theory. With this simulator it is possible to reproduce practically all types of stationary, as well as a number of non-stationary, EEG signals. We have used this simulator to demonstrate in an illustrative manner the relation between the properties of a signal in the spectral domain and in the time domain. We have also endeavoured to anser the question: if one starts from the frequency spectrum, what does the EEG signal corresponding to this spectrum look like? We also draw attention to the usefulness of the simulator in connection with training and as an instrument for testing computer and other systems of EEG analysis.

Visible and non-visible EEG changes demonstrated by spectral parameter analysis

A change of the heart rate in patients with complete AV-block and externally controllable cardiac pace-makers was earlier shown to influence cerebral function, as measured by psychological tests. To determine whether this influence manifests itself in the EEG, 9 patients aged 43-83 years were examined, all having complete AV-block and externally controllable pace-makers. Their EEGs were recorded at different heart rates between 40 and 100/min at rest and during a mental arithmatic test. The EEG record was evaluated visually and analysed by means of Spectral Parameter Analysis (SPA), introduced by Zetterberg (1969). The changes in the spectral parameters in relation to the heart rates were analysed statistically, In several cases significant changes appeared but the interindividual variations were large. Certain typical patterns could, however, be observed and their importance as a measure of cerebral function due to changes in the cerebral blood flow are discussed. These EEG changes revealed through SPA did not correspond to any visually observable changes in the EEG records. Differences in the spectral parameters between rest and test situations were analysed. Some of the differences found could easily be observed by visual inspection of the EEG. The advantage with SPA was that the changes could be described both qualitatively and quantitavely because SPA separates the spectral properties of the signals into components corresponding to well-known components of the EEG signal.

Electrocortical Responses to ecologically relevant visual stimuli among professional drivers with and without cardiovascular disease

Electrocortical responses were assessed using two simulated aspects of visual signals encountered in traffic: the Glare Pressor Test (GPT) and Event-Related Potential Avoidance Task (ERPAT) among four groups of male professional drivers: 12 with ischemic heart disease (IHD), 12 hypertensives, 10 borderline hypertensives, 34 who were apparently healthy and 23 nonprofessional driver healthy control subjects. The blood pressure (BP) responses immediately after the ERPAT were also measured. There was a significant between groups effect for the amplitude of the target N2 component in the ERPAT (p=0.02), with the lowest means among the drivers with IHD and the highest among those with hypertension. Drivers with IHD also showed the highest diastolic BP reactivity to the ERPAT. Significantly more than the expected number of drivers with IHD failed to recover alpha activity after the first glare impulse of the GPT. Professional drivers who failed to recover baseline levels of alpha activity after the GPT showed a significantly smaller N2 amplitude compared to those who recovered (p=0.01). There was a positive correlation between abundance of alpha activity at rest with P300 amplitude (p=0.02). An inverse relation was found between number of work hours behind the wheel and the amplitude of the target P300 (p=0.04). Results are interpreted in light of recent advances concerning integrative mechanisms of defence versus vigilance response patterns. The findings in this study justify further applications of these psychophysiologic methods to assess the relationship between simulated signals of the work environment and mechanisms of cardiac risk in this occupational group.