Numbers of homes near National Grid lines
Information on numbers of homes near National Grid overhead lines (275 kV and 400 kV) is available from a number of sources. National Grid has performed analyses for all England and Wales homes based on postcodes and augmented by data on individual addresses and from aerial photography for the closer properties. The UKCCS has published data on its subjects and estimates have appeared as part of other epidemiological studies. Fortunately all the answers seem fairly similar whether based on postcodes, addresses, or children, and as the number presumably increases over time, approximate answers are all that can be expected anyway. The best estimates available are given in the graph.
Numbers of homes near National Grid overhead lines in England and Wales.
Numbers for some of the key distances are given in this table:
Distance from centreline
Number of homes
% of total homes in England and Wales
Building oversailed by conductors
Number of homes near lower-voltage lines
The data from the CCRG study suggests that twice as many children live near 132 kV lines as near National Grid lines. Little if anything is known about homes near even lower-voltage lines (e.g. 33 kV, 11 kV).
Value of homes near lines
There is some evidence that homes near lines may be slightly less valuable than the average for the country as a whole. In summer 2003, according to the property website Hometrack, the average value of homes in a random sample of postcodes within 50 m of National Grid lines was £115k. On this basis, the value of residential property within 50 m of National Grid lines would be £2bn. That will have increased in the intervening years!
Socioeconomic status of homes near lines
In both the UK and the USA, there is some evidence that areas close to high-voltage power lines may actually be of higher socioeconomic status on average than the country as a whole.
In the UK, we think there are two opposite trends. In urban areas, power lines often enter through industrial areas or along existing transport corridors. The area close to the power line will then usually be of lower socioeconomic status. But in rural areas, high-voltage power lines usually skirt round towns and villages. This means that the homes closest to the power line are the ones on the outskirts of towns, which often have higher socioeconomic status. Although when power lines enter urban areas there is a high density of homes near them, they do so relatively rarely, so over the country as whole, it is the latter effect which dominates.
In the USA, high-voltage power lines are routed along rights of way, strips of land where no development is permitted. Therefore, the homes nearest the power line have a guaranteed outlook onto non-built-up land, which may make them more valuable.
These results are sometimes seen as counter-intuitive because often, infrastructure which has an effect on the surrounding environment is concentrated in poorer areas or among minority ethic communities, an issue known as "environmental justice".
J Expo Sci Environ Epidemiol. 2009 Apr 8. [Epub ahead of print]
Wartenberg D, Greenberg MR, Harris G.
Environmental justice is the consideration of whether minority and/or lower-income residents in a geographic area are likely to have disproportionately higher exposures to environmental toxins than those living elsewhere. Such situations have been identified for a variety of factors, such as air pollution, hazardous waste, water quality, noise, residential crowding, and housing quality. This study investigates the application of this concept to high-voltage electric power transmission lines (HVTL), which some perceive as a health risk because of the magnetic fields they generate, and also as esthetically unpleasing. We mapped all 345 kV and higher voltage HVTL in New York State and extracted and summarized proximate US Census sociodemographic and housing characteristic data into four categories on the basis of distances from HVTL. Contrary to our expectation, people living within 2000 ft from HVTL were more likely to be exposed to magnetic fields, white, of higher income, more educated and home owners, than those living farther away, particularly in urban areas. Possible explanations for these patterns include the desire for the open space created by the rights-of-way, the preference for new homes/subdivisions that are often located near HVTL, and moving closer to HVTL before EMFs were considered a risk. This study suggests that environmental justice may not apply to all environmental risk factors and that one must be cautious in generalizing. In addition, it shows the utility of geographical information system methodology for summarizing information from extremely large populations, often a challenge in epidemiology.
Soc Sci Med. 2008 Nov;67(10):1612-29. Epub 2008 Sep 9. Environmental inequity in England: small area associations between socio-economic status and environmental pollution.
Briggs D, Abellan JJ, Fecht D.
Recent studies have suggested that more deprived people tend to live in areas characterised by higher levels of environmental pollution. If generally true, these environmental inequities may combine to cause adverse effects on health and also exacerbate problems of confounding in epidemiological studies. Previous studies of environmental inequity have nevertheless indicated considerable complexity in the associations involved, which merit further investigation using more detailed data and more advanced analytical methods. This study investigates the ways in which environmental inequity in England varies in relation to: (a) different environmental pollutants (measured in different ways); (b) different aspects of socio-economic status; and (c) different geographical scales and contexts (urban vs. rural). Associations were analysed between the Index of Multiple Deprivation (IMD2004) and its domains and five sets of environmental pollutants (relating to road traffic, industry, electro-magnetic frequency radiation, disinfection by-products in drinking water and radon), measured in terms of proximity, emission intensity and environmental concentration. Associations were assessed using bivariate and multivariate correlation, and by comparing the highest and lowest quintiles of deprivation using Student's t-test and Hotelling's T2. Associations are generally weak (R(2) < 0.10), and vary depending on the specific measures used. Strongest associations occur with what can be regarded as contingent components of deprivation (e.g. crime, living environment, health) rather than causative factors such as income, employment or education. Associations also become stronger with increasing level of spatial aggregation. Overall, the results suggest that any triple jeopardy for health, and problems of confounding, associated with environmental inequities are likely to be limited.