RT Journal Article
SR Electronic
T1 Occupational exposure of UK adults to extremely low frequency magnetic fields
JF Occupational and Environmental Medicine
JO Occup Environ Med
FD BMJ Publishing Group Ltd
SP 619
OP 627
DO 10.1136/oem.2008.040329
VO 66
IS 9
A1 T Mee
A1 P Whatmough
A1 L Broad
A1 C Dunn
A1 M Maslanyj
A1 S Allen
A1 K Muir
A1 P A McKinney
A1 M van Tongeren
YR 2009
UL http://oem.bmj.com/content/66/9/619.abstract
AB Background: Occupational exposure to extremely low frequency (ELF) magnetic fields (MF) in the UK general population is poorly documented.Aims: To assess levels of occupational exposure to ELF MF in the UK and evaluate the use of a rigid job-exposure matrix (JEM) to assign exposures to subjects in the UK Adult Brain Tumour Study (UKABTS).Methods: Personal ELF MF measurements were carried out. Exposure traces were divided into occupational, travel and elsewhere periods, under differing exposure metrics. Exposure was classified by Standard Occupational Classification (2000), Standard Industrial Classification (1997), and a combined occupation-industry classification. Statistical analyses (mixed effects model) determined the contribution of occupational exposure to the 24 h cumulative exposure and the contribution of occupation and industry to total variance.Results: Data were obtained from 317 individuals, comprising UKABTS subjects (n = 192), occupational proxies for UKABTS subjects (n = 101) and “interest” readings (n = 24). 236 individuals provided occupational data covering 117 different occupations. Average exposure was significantly higher at work than at home. Elevated average occupational exposure was found for welding trades, printers, telephonists and filing and other records assistants. The discrimination of a rigid JEM based on occupation can be improved by linking the classification with industry and by the use of contextual information.Conclusions: This report substantially expands information on adult exposure to ELF MF in the UK. The accuracy of exposure assessments based solely on job codes is improved by linking with either industry code or contextual knowledge of equipment and of power lines or substations in the work environment.