Epidemiology is a scientific discipline that considers the distribution and determinants of disease, a method for evaluating the effect of exposure on health. This type of study monitors groups of people who have had higher or lower RF exposure to determine whether those with higher exposure have an increased risk of disease. Although it is challenging to determine whether exposure causes disease, observational epidemiology has the distinct strength of studying exposures that people actually experience, in contrast to human or animal experimental laboratory research, which is intended to simulate the environmental conditions of concern. For radiofrequency exposures, we may ask whether those who use cell phones for extended periods of time have a higher risk of brain cancer than those who are infrequent users of cell phones.
Epidemiology has the distinctive strength of studying human experience that is directly relevant to public health concerns; there is no need to directly translate findings from laboratory animals or cell cultures to humans, or from extremely high exposures to more typical exposures. However, there are challenges inherent in epidemiologic research as well. It can be difficult to accurately measure exposure and sometimes hard to find substantial enough variation in exposure to evaluate its impact accurately. For example, if nearly everyone uses a cell phone, then we cannot find non cell phone users to be compared to users. If we ask people to recall how much time they used their cell phones, their memory may not be accurate. Another major challenge is that the exposure we are interested in may be correlated with other exposures, so it is hard to separate one from the other. Suppose people living near cellular base stations are more likely to reside in urban areas compared to those living farther away. In that case, factors specific to the urban environment, such as air pollution, may be associated with potential radiofrequency radiation exposure. Therefore, researchers must separate the effects of these two exposures when studying their impact.
Ecological epidemiological studies look at how environmental exposures relate to health outcomes across entire groups—such as communities, cities, or countries—rather than focusing on individuals. These studies use summary data to find large-scale patterns and trends. For example, researchers might compare average cell phone use in different regions with local cancer rates to look for possible connections worth studying further. Ecological studies are useful because they can cover wide populations at a relatively low cost. However, they have drawbacks: results seen at the group level may not apply to individuals (a problem called the ecological fallacy), and it can be difficult to account for other factors that might influence the results.
Cross-sectional studies are used to study concurrent exposure and prevalent health outcomes. A population is identified, and both their exposure to radiofrequency fields (e.g., frequency of cell phone use) and health status (e.g., impaired hearing) are assessed. Because they are measured at the same time, there is the potential for reverse causality in which the health condition influences exposure. For example, hearing loss or other acute symptoms may cause more or less cell phone use. The case-control and cohort studies described below are generally preferable for studying most conditions potentially associated with radiofrequency exposure.
Cohort studies are similar to laboratory experiments, where groups of people are identified based on whether they are exposed or unexposed (or less exposed) to a particular factor. These groups are then followed over time to determine how frequently each group develops a disease. Researchers compare the two groups with a relative risk, which is the risk of disease in the more exposed group divided by the risk of disease in the less exposed group. For example, a relative risk of 2 means that higher exposure is associated with double the risk of lower exposure.
Case-control studies identify two groups: one that has developed a disease we are interested in studying and a healthy comparison group that is free of that disease. Researchers then find out the exposure history of both groups to see whether those with the disease have a history of more exposure than those who did not get the disease. The relative risk measure is called an odds ratio, which indicates the odds of getting the disease among exposed versus unexposed (or less exposed) persons.
A recent example is the time trend study of mobile phone use and glioma incidence among males in the Nordic countries [Deltour 2022]. By following the population through periods of varying cell phone use, they were able to compare groups of people who had never used cell phones in the early periods and the use of cell phones by nearly everyone in the later period. The researchers did not find any association between the prevalence of cell phone use and the incidence of brain cancer, consistent with other types of studies that have addressed this topic.
The recently published Cohort Study of Mobile Phone Use and Health (COSMOS) recruited participants from multiple European countries in 2007-2012. It assessed each participant’s lifetime history of cell phone use when they enrolled in the study [Feychting 2024]. They included 264,574 individuals and followed them over an average of 7.1 years to determine who developed glioma (the most common form of brain cancer), meningioma, or acoustic neuroma during the follow-up time. Over that period, there were 149 glioma cases, 89 meningioma cases, and 29 acoustic neuroma cases. When the researchers analyzed the association between cumulative hours of call time and the incidence of those diseases, they found consistent evidence that the risk did not increase with greater call time. All the relative risks were very close to 1.0.
An example is the INTERPHONE study, a case-control study that examined the association between cell phone use and brain cancer. A large group, 2708 people with brain tumors, were interviewed to determine their history of cell phone use and compared to 2972 population-based controls without brain tumors. The goal was to see if people with brain tumors had more exposure to RF from cell phones. The results indicated that the history of cell phone use was similar for those with and without brain tumors, which suggests that cell phone use is not likely to be a cause of brain tumors. However, some specific results for those who reported extremely high levels of cell phone use raised concerns that some have interpreted as hints of a possible association.
A study by Hatch and colleagues [Hatch 2021] showed that carrying a phone in the front pants pocket was not associated with a change in male fertility. However, men with a Body Mass Index (BMI) under 25 showed a moderate decrease in fertility with phone exposure in the front pocket, while men with a BMI of 25 or higher did not. Despite earlier studies suggesting a connection between phone exposure and lower sperm movement, the study found few consistent links to sperm quality.
A recent World Health Organization (WHO) meta-analysis of 7 eligible studies [Kenny, 2024] found that most studies focused on how mobile phone use affects male fertility, with few studies looking at phone placement. One of the studies looked at other public sources of RF exposure and their impact on male fertility, while two other studies examined workplace exposure (from radar or microwaves) and its effects on male fertility. Overall, the evidence of the effects of RF-EMF exposure from phones on sperm health is unclear.
A separate WHO meta-analysis of 18 eligible studies on RF exposure and female reproductive outcomes in the workplace from radar, short or microwave diathermy, surveillance and welding equipment and in the general population from mobile phone use [Johnson, 2024]. The evidence was mixed, and some studies were at risk of bias making an assessment of the overall effects of RF exposure on female reproduction unclear.In Denmark, 420,095 residential cellular telephone users were identified from subscriber lists of two Danish cell phone companies [Johansen 2001]. Follow-up of the cohort began on the date that subscriptions started in the 1980s or 1990s and ended when the subscribers died or left the country or at the end of the first period of follow-up. There have been two additional follow-ups of the original cohort using the same methods, [Schüz 2006, Frei 2011]. The personal identification number assigned toncrp every person was linked with the Danish nationwide cancer registry to determine if the person was diagnosed with cancer. For those who developed cancer, information was provided about the date of diagnosis and the type and extent (stage) of the cancer. This study is of high quality because it is a nationwide cohort, the comparison group is the entire population of Denmark, the ‘exposure’ is based on cell phone subscriber information, the cancer outcome is based on linkage with the Danish nationwide cancer registry, and both exposure and outcome information are quite likely to be close to 100% complete. The studies found no indication of dose-response relation (more years of cell phone use was not associated with a greater likelihood of developing cancer) either by years since the first subscription for a mobile phone or by anatomical location of the tumor.
Like all epidemiologic cohort studies, this one has limitations, including a lack of information about the number of calls per week, the length of the calls, and whether the person used earbuds/headphones or other similar gear or texts instead of holding the phone next to their head. Further, some exposure misclassification has been identified because of a lack of data about users of business subscriptions.
To overcome the limitations of single epidemiologic studies, researchers conduct systematic reviews to identify all studies that meet pre-determined eligibility requirements. The studies are described and examined for quality in the same consistent and rigorous way individually and then combined statistically in a procedure called meta-analysis. Recent WHO Radiation Program-sponsored systematic reviews and meta-analyses have concluded that cell phone use does not increase risk of malignant or benign brain and other central nervous system tumors or other cancers in adults or brain tumors in children [Karipidis 2024, Karipidis 2025].
People are concerned that cell phones may cause cancer or other health problems because these phones emit radiofrequency radiation, and their use is widespread. Brain tumors (including cancer and benign tumors) are the main worry because cell phones are held close to the head and because ionizing radiation, a higher energy form than non-ionizing radiation, is associated with some brain tumors.
Both cohort and case-control studies and the recent WHO Radiation Program-sponsored systematic reviews and meta-analyses generally show no link between cell phone use and these cancers, although a few specific studies reported mixed results. Studies tracking trends over the past 30 years, during which time cell phone use has increased from minimal to widespread, have not shown an increase in these diseases, supporting the absence of detrimental effects from cell phone use. Two large case-control studies on childhood and adolescent brain tumors found no associations. Similarly, two large cohort studies with long-term follow-up in Denmark and the UK also reported no associations. Other potential health effects, such as adult cancers, developmental problems in children, sleep disturbances, and reproductive issues, have been studied, but the research is limited and shows no clear evidence of increased risks [Karipidis 2024; Karipidis 2025; Johnson 2024; Kenny 2024; Benke 2024; Röösli 2024].
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