Occupational exposure to electromagnetic fields, dietary and genetics factors and the risk of brain tumours: a UK case-control study.
MPhil thesis, University of Nottingham.
Nowadays, very little is known of the aetiology of brain tumours in adults and despite all efforts from scientists there is still a limited understanding of this disease. However, previous studies suggest that there is association between some genetic and environmental factors and adults’ brain tumours. Risk factors that have been considered to play a role in brain tumours aetiology are exposure to electromagnetic fields (EMF), diet, genetics, ionizing radiation, radio frequency exposure, occupational chemical exposure (pesticides and solvents), head trauma, viruses and it has also been suggested that factors such as allergies or influenza may be important. In this study a detailed literature review obtained for three risk factors; exposure to electromagnetic fields (EMF), diet and genetics.
The current evidence on electromagnetic fields (EMF) as an aetiological factor for brain tumours is inconclusive, existing data suggest weak or no association. We have to consider that exposure to electromagnetic fields is difficult to measure, therefore exposure assessment, particularly in occupation settings, varies from one study to another.
There is currently only limited data for the relation between diet and brain cancer and a number of nutrients have been suggested as potential risk factors. One suggested nutrient is N-nitroso compounds as potential central nervous system (CNS) carcinogens. In addition, there is some evidence of a protective effect of consumption of antioxidants (vitamin C, vitamin E and carotenoids). Other nutrients and foods seem to play a role in brain cancer include zinc and aspartame. According to some studies, the blood-brain barrier in relation with diet might play a role in brain tumour genesis or treatment.
Very little is known for the association of genetics with brain tumours. Many mutated or altered genes, such as p53, Rb1, CDKN2A, p16INK4A, and CDK4, seem to have an involvement in the development of brain tumours, but still the role they play in the formatting of the tumour is not identified. Only about 5% of primary brain tumours are known to be associated with hereditary factors. Common variations in the structure of specific genes are known to be associated with basic cellular metabolic processes such as oxidation, detoxification, DNA stability and repair, and immune functioning. Such genetic polymorphisms may well be associated with the development of brain tumours in the presence or absence of environmental carcinogens.
To better understand the potential risk factors for brain cancer a population based case-control study was conducted in four regions in the UK; Central Scotland, West Yorkshire, West Midlands and Trent was established collecting a wide variety of information including information on occupational sources of electromagnetic fields. This study investigated the link between cumulative electromagnetic field (EMF) exposure that reflected lifetime exposure, rather than electromagnetic field (EMF) exposure from any specific job and glioma, meningioma and acoustic neuroma. Cumulative exposure to electromagnetic fields was determined by generic geometric means assigning to each job coded using Standard Industry Classification (SIC) and Standard Occupation Classification (SOC).
Data were obtained from 970 cases of brain tumours (gliomas n=588; meningiomas n=247; acoustic neuromas n=135) and 1097 controls. For all brain tumour cases, exposures to electromagnetic fields estimated using Standard Industry Classification (SIC) in the 3rd and 4th quartile had a statistically significant decreased risk compared to the first quartile (Q3: OR 0.73, 95% CI 0.55-0.97 and Q4: OR 0.70, 95% CI 0.52-0.94, p for trend 0.019). Similar results were observed with gliomas. No association was found between exposure to electromagnetic fields (by SIC) and meningiomas or acoustic neuromas. No statistically significant associations were found between exposure to electromagnetic fields by Standard Occupational classification (SOC) coding and brain tumours, gliomas and meningiomas. Exposure to electromagnetic fields estimated using SOC was inversely associated with acoustic neuromas (Q2: adjusted OR 0.53, 95% CI 0.31-0.90, Q3: adjusted OR 0.52, 95% CI 0.29-0.93). Nevertheless, there was no clear trend of risk reduction (p for trend 0.287).
The results in this study do not support the hypothesis that occupational exposure to electromagnetic fields (EMF) is associated with an increased risk of brain cancers. In fact, there is some evidence of a protective effect of electromagnetic fields (EMF) exposure. The healthy worker effect (HWE) may entail differential bias towards the results, as healthy individuals gain employment and remain in industry and ill or disable people not remain employed.
Even though, several epidemiological studies were conducted investigating the risk factors of brain tumours the results are inconsistent. There are still many controversies about the environmental and genetic factors that are important in the aetiology of the disease. For dietary factors, further epidemiological studies need to use data from a big sample size, being obtained from food frequency questionnaires, and try to investigate the role that nutrients/food groups play in brain tumours. More attention must be given in specific nutrients, such the N-nitroso compounds, antioxidants and aspartame. In the analysis confounders, like age, sex, deprivation category, and energy intake, must be adjusted.
The evolution of genetic epidemiological methods we face in the last years increase the amount of information for genetics and investigators need to focus on the data management and analysis of these outputs. Large-scale subjects must be designed in order to investigate candidate genes (p53, Rb1, CDKN2A, p16INK4A, and CDK4) and genetic polymorphisms and their association with brain tumours. A new approach of studying gene-environmental interaction should be considered with attention, as it might be the direction of the future.
Finally, for electromagnetic fields further studies must be carried out, with detailed complex job-exposure matrixes (JEMs) that will take into account specific job title, description of the tasks each worker is performing, workplace, accurate time of working and even direct measurements of exposure with individual dosimeters. Better classification of jobs must be done and cases with high illness must be included in our sample size, in order to achieve more accurate and precise results.
Thesis (University of Nottingham only)
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