Sleep is a vital biological function, and sleep disorders are a major risk factor for cardiovascular disease, metabolic disorders, and premature mortality. Chronic sleep disorders impair neurological functions such as memory, concentration, and higher cognitive processes. They are also closely linked to the development of Alzheimer’s. In children and young adults, sleep disorders are associated with mental health issues, depression, and poor academic performance. Currently, 4 out of 10 Australians suffer from sleep disorders, resulting in a significant social, financial and health burden. The rise in sleep disorders correlates with the global spread of mobile phones, which now number in the billions. However, studying the relationship between radiofrequency electromagnetic fields (RF-EMFs) and sleep disturbances is challenging. Epidemiological surveys are prone to respondent bias and rarely assess clinically relevant endpoints. Experimental studies should ideally be conducted outside of sleep laboratories, as unfamiliar environments may affect sleep, especially over a single night. In addition, EMFs should be generated by real sources rather than artificial ones, as real-world signals vary greatly in intensity and waveform, making them more biologically active. The aim of this study was to investigate the effects of radiofrequency EMFs in a real-world setting (using a commercially available baby monitor in the participants' own bedrooms) on clinically relevant sleep parameters in healthy adults.
This pilot study was a four-week, randomized, double-blind, crossover trial involving 12 healthy adults (3 males, 9 females). After a one-week familiarization period, participants were randomly assigned to be exposed to either an active baby monitor or a placebo (turned-off) device for seven consecutive nights. After a one-week washout period, the conditions were reversed: participants previously exposed to the placebo were now exposed to the active baby monitor, and vice versa. The baby monitor operated at a power level of 15 dBm, using a frequency range of 2.4 to 2.4835 GHz with frequency modulation to avoid interference. The monitor and camera units were placed within 2 meters of the participants' headboards, depending on the bedroom layout. Dosimetry measurements showed field strengths ranging from 2.2 to 7 mW/m², well below the ICNIRP limits for far-field exposure (10 W/m²). Background electromagnetic noise was kept below 0.1 µT for magnetic fields and below 0.02 mW/m² for radiofrequency EMF. Subjective sleep quality was assessed using the Pittsburgh Insomnia Rating Scale (PIRS-20). Objective sleep measures were obtained by portable polysomnography (PSG), wrist-worn actigraphy, and sleep diaries. Heart rate variability (HRV) was also measured.
The PIRS-20 results showed a statistically significant deterioration in sleep quality for participants exposed to the active baby monitor compared to the placebo condition. Three participants (27.3%) scored above the threshold of 20, indicating a risk of clinical sleep disorders. Electroencephalography (EEG) also revealed statistically significant differences between the active exposure and placebo conditions. Specifically, the EEG power density of higher frequency bands (theta, beta, and gamma) increased significantly during non-rapid eye movement (NREM) sleep. No statistically significant changes were observed during rapid eye movement (REM) sleep. No differences were found between the groups for HRV and actigraphy measurements. Due to technical issues, actigraphy data were missing for 4 participants (n = 8) and PSG data were missing for 2 participants (n = 10). One participant exhibited cold symptoms during the fourth week, and their PIRS-20 data were excluded from the analysis (n = 11).
Despite the small sample size, statistically significant results were obtained, indicating both subjective and objective deterioration in sleep quality, potentially reaching the threshold for clinical sleep disorders. The results suggest a large effect size (d = 0.75) compared to background EMF exposure. While the basic design was highlighted as a strength, the small sample size and technical issues leading to reduced usable data (n = 8-12) were acknowledged as major limitations. A follow-up study with a larger sample might detect potential effects with smaller effect sizes.
Editor's note:
Interpretation of these results in the context of the existing scientific literature is challenging because most studies of mobile phone effects on sleep are based on short-term exposures, simulated laboratory conditions, or epidemiological surveys. However, several reviews (Hamblin & Wood, 2002; Rubin et al., 2011; Zhang et al., 2017) have concluded that mobile phone EMFs can affect selective EEG power bands, especially when exposure occurs just before or during sleep. (RH)
References:
Hamblin DL, Wood AW (2002): Effects of mobile phone emissions on human brain activity and sleep variables. International Journal of Radiation Biology, 78(8), 659-669. https://doi.org/10.1080/09553000210132298
Rubin GJ, Hillert L, Nieto-Hernandez R, van Rongen E, Oftedal G (2011): Do people with idiopathic environmental intolerance attributed to electromagnetic fields display physiological effects when exposed to electromagnetic fields? A systematic review of provocation studies. Bioelectromagnetics, 32(8), 593-609. https://doi.org/https://doi.org/10.1002/bem.20690
Zhang J, Sumich A, Wang GY (2017): Acute effects of radiofrequency electromagnetic field emitted by mobile phone on brain function. Bioelectromagnetics, 38(5), 329-338. https://doi.org/https://doi.org/10.1002/bem.22052