Recently, potential adverse health effects of mobile phone base stations (MPBS) have been reported (Gulati et al., 2024; see ElektrosmogReport 03/24, editor’s note). The present study investigates the prevalence of non-specific health symptoms in relation to exposure from MPBS and the proximity of residences to these installations. The study is based on reports of an increased frequency of headaches, sleep disturbances, difficulty concentrating, low mood and related complaints following the installation of MPBS. The study was conducted from 2023 to 2024 in the hilly city of Aizawl, in the Indian state of Mizoram.
The authors selected 30 mobile phone base stations, 20 of which operated at 900 MHz and 10 of which operated at 1800 MHz. They recruited a total of 183 highly exposed residents (living within 300 m of a MPBS) and 126 reference residents (living more than 400 m away). The two groups were matched demographically, including lifestyle variables such as alcohol and tobacco use, as well as mobile phone use. Dosimetric measurements of RF power density were performed in 103 households, mainly in living rooms. The measured values ranged from 0.01 to 7.24 mW/m², far below the ICNIRP reference levels for MPBS (4,500 mW/m² for 900 MHz; 9,200 mW/m² for 1800 MHz). Participants were categorized by their distance from the nearest base station (1–50 m, 51–300 m, > 400 m) and by their measured power density (0–3 mW/m², 3–5 mW/m², 5–8 mW/m²). Symptoms were grouped into four categories: (1) mood/energy-related, (2) cognitive/sensory, (3) inflammatory, and (4) anatomical. Data were collected via questionnaire. A four-level severity scale had been planned, but responses were dichotomized (yes/no) since most participants were unable to provide more graded information. The data underwent extensive statistical analysis.
Statistically significant correlations were found between exposure intensity and the prevalence of symptoms (e.g. anxiety disorders, headaches, chest pain, sleep disturbances, difficulty concentrating, and digestive problems) for all four symptom categories. As expected, a strong negative correlation was documented between distance to MPBS and measured power density, that is, mean field strength decreased with increasing distance. However, due to overlapping factors, such as limited line of sight, topography, and buildings, measured power density was found to correlate more strongly with symptom prevalence than distance alone (hierarchical regression analysis). Demographic and lifestyle variables had no significant effect on symptom frequency except for age; participants over 40 reported significantly more anatomical complaints. Remarkably, younger participants (under 40 years of age) in the higher exposure groups reported significantly more inflammatory symptoms, such as allergies and increased infections.
Although the maximum measured power density was only 7.2 mW/m² (well below the ICNIRP limits of 4,500 and 9,200 mW/m²), residents of Aizawl with higher exposures reported significantly more non-specific health symptoms. These symptoms correlated with measured field strengths in a clear dose–response relationship. Of particular concern is the finding that mobile phone base stations may promote inflammatory processes in younger individuals, a phenomenon warranting further investigation. The authors argue that the ICNIRP limits, averaged over 5 or 30 minutes, do not adequately account for cumulative doses in real-world exposure scenarios.
Editor's note:
The study benefits from real-world exposure measurements, consideration of lifestyle factors, and an extensive statistical evaluation. However, several limitations must be noted. Symptom data were self-reported and dichotomized, making them vulnerable to perception and recall bias. Information bias cannot be excluded since the assistants were not blinded with respect to exposure status (distance to MPBS). However interaction during questionnaire completion was minimized. In addition, group sizes between the exposed and reference participants were unequal, and the overall sample size is relatively small for epidemiological research. Unfortunately, there is an absence of biological markers or clinical examinations, especially given the finding of increased inflammatory complaints among younger participants. Such data could have helped establish causal links, as was achieved in the ATHEM-3 study (Gulati et al., 2024). Despite these limitations, the detailed statistical approach makes the study relevant. However, modifications to the study design would have been desirable. However, the same working group has already presented studies in which these requirements are realised. (RH)
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