Estimating magnetic fields of homes near transmission lines in the California Power Line Study

Abstract

The California Power Line Study is a case-control study investigating the relation between residences near transmission lines and risk of childhood leukemia. It includes 5788 childhood leukemia cases and 5788 matched primary controls born between 1986 and 2007. We describe the methodology for estimating magnetic fields at study residences as well as for characterizing sources of uncertainty in these estimates. Birth residences of study subjects were geocoded and their distances to transmission lines were ascertained. 302 residences were deemed sufficiently close to transmission lines to have non-zero magnetic fields attributable to the lines. These residences were visited and detailed data, describing the physical configuration and dimensions of the lines contributing to the magnetic field at the residence, were collected. Phasing, loading, and directional load flow data for years of birth and diagnosis for each subject as well as for the day of site visit were obtained from utilities when available; when yearly average load for a particular year was not available, extrapolated values based on expert knowledge and prediction models were obtained. These data were used to estimate the magnetic fields at the center, closest and farthest point of each residence. We found good correlation between calculated fields and spot measurements of fields taken on site during visits. Our modeling strategies yielded similar calculated field estimates, and they were in high agreement with utility extrapolations. Phasing was known for over 90% of the lines. Important sources of uncertainty included a lack of information on the precise location of residences located within apartment buildings or other complexes. Our findings suggest that we were able to achieve high specificity in exposure assessment, which is essential for examining the association between distance to or magnetic fields from power lines and childhood leukemia risk.

Residential magnetic fields exposure and childhood leukemia: a population-based case–control study in California

“…We conducted sensitivity analyses that examined various uncertainties: 1) using all subjects regardless of geocode accuracy (i.e including a 10% matched at zip code level and few more at other geography matches); 2) restricting to subjects from the major four utilities; 3) excluding subjects born in 1996, a year during which birth certificates were being transitioned to electronic format and the availability of residential address data was limited to zip code for some; 4) restricting to subjects with site visits; and 5) restricting to site-visit subjects with lower uncertainty in calculated field estimates, defined as having at most one major source of uncertainty out of 3 possible sources [22]. Based on recent publications, we added analysis 6) by the decade of birth year (e.g.…”

“…Our detailed three-stage exposure assessment methodology incorporated several improvements in the assessment of exposure, including more precise measurements of distance and consideration of complex line configurations. This allowed us to achieve high specificity in exposure assessment, which is essential for examining the association between magnetic fields and childhood leukemia risk [22]. …”

“…The study design, including methods of case ascertainment and control selection [21], methods for calculated fields [22], and estimation of distance from birth residence to transmission lines and associated risks [14] have been previously described. We summarize them briefly here.…”

“…Phasing, loading, and directional load flow data for years of birth and diagnosis for each subject were obtained. Details on modeling of load and phasing when utility data were missing are presented elsewhere [22]. Magnetic fields were calculated using the EMF Workstation [EPRI 2013] and were estimated at the center, closest and farthest point of each residence.…”

The sensitivity of reported effects of EMF on childhood leukemia to uncontrolled confounding by residential mobility: a hybrid simulation study and an empirical analysis using CAPS data

“…SES can be related to the type, quality, and number of appliances within a home, as well as the location of the home with regards to overhead powerlines [5,6]. Type of dwelling (single-family home vs. apartment) is also associated with exposure to EMF [7,8] as well as with mobility [3,9].…”