Proximity and exposure metric deficiencies.
The authors estimate an increased attribution, if the association
were causal, of about 5 cases of childhood leukaemia per year in England
and Wales, among some 400,000 children with birth address within 600
metres of National Grid powerlines. About half of those five cases would
be within 200 metres.
The NRPB  estimated that about two attributable cases per year in
the UK would be associated with time-weighted average (TWA) magnetic
fields (MF) above 0.4mT (and none below), of which about half a case would
be attributable to exposures from powerlines. MF in excess of 0.4mT from
powerlines would probably all occur well within 200 metres.
The population of the UK is about 13% more than that of England and
Wales. National Grid powerlines include all those at 275 and 400 kV but
exclude almost all those at 132 kV and lower voltages. The Draper study
has a more restricted definition, in terms of both geography and exposure
sources, than the key MF studies. If the only relevant cause were MF above
0.4mT, the estimate from the Draper study of 2.5 attributable cases per
year would at first sight be surprising, compared with only 0.5 from MF
studies, even though both estimates are imprecise.
Does this resurrect the "wire code paradox", said to be resolved in
, in another form? A question arises as to whether inappropriate
metrics in the MF studies tend to suppress any association compared with
proximity to powerlines.
MF exposure metrics in the constituent studies in both  and 
are generally arithmetic averages with respect to time over 24 hours or
more during the year preceding diagnosis. Some are weighted to track the
individual case or control exposure over time.
One quirk in  is the decision "to use geometric means from all
studies, because they are less affected by outliers". For positive numbers
not all the same, the geometric mean G will always be less than the
arithmetic mean A. That will mean G is less affected by high outliers but
more affected by low ones (and critically affected by a zero!). This might
be one deficiency in exposure metric for this seminal pooled MF analysis.
Another possible deficiency, having regard to melatonin hypotheses,
might be the dilution of night-time exposure by 24-hour averaging.
Although MF from powerlines in the UK are lower at night than in daytime,
they may be the dominant night-time source. Analysis of pooled German
studies  found an OR of 4.28 (1.25-14.7) for night-time exposures above
0.4mT. That gives an attributable RR of 3.28, compared with the
attributable RR of 1 from 24-hour TWA, which lies behind the estimate of
half a case per year near powerlines in the UK.
The above figures from ,  and  could be broadly reconciled
as follows, taking proximity to powerlines as a proxy for night-time
exposure. Take the normal (non-attributable) EMF-associated cases to be,
like the NRPB conjectured attributed cases, 0.5 per year from powerlines
sources and 1.5 from non-powerlines sources. Then take the excess
(attributable) cases to be 1.5 from powerlines and 0.5 from non-powerline
sources. This preserves the overall RR of 2 while allowing the night-time
(powerline) RR to be about 4 and incidentally implying a daytime RR of
about 1.3. As the data are so imprecise, such a reconciliation is not to
be taken prescriptively; it merely indicates a possible broad
As well as dilution of night-time exposure above 0.4mT, might there
be dilution above 0.2mT, where UK data suggest there are far more
children? A joint EEA/WHO review  notes "If regression dilution were
concealing a relative risk of 1.5 for children exposed to between 0.2 and
0.4mT, then the annual number of attributable cases might be six or
seven". Metric dilution might also contribute to the concealment of such
an association for night time exposure; Schutz  found OR = 3.21 (1.33-
7.80) above 0.2mT.
For the avoidance of doubt, these comments aim to raise questions,
not to infer conclusions. The questions open possibilities for the
findings of increased hypothetically attributable cases within 200 metres
to be reconciled in terms of exposure metric deficiencies in MF studies.
Other questions, e.g. about the distributions of controls, may point the
other way. I don’t want to exaggerate a marginal consideration, and
acknowledge the perspective in the editorial comparing 5 attributable
cases with 500 others. But given public (and scientific) interest, might
it yet be worth re-analysing MF studies, such as UKCCS, for night-time
 Board of NRPB Response Statement R3/2001.
 Greenland et al, Epidemiology 11(6), 624-634, 2000.
 Ahlbom et al, British Journal of Cancer 83(5), 692-698, 2000.
 Schutz et al, Int J Cancer 91, 728-735, 2001.
 Tamburlini et al, EEA Environmental Issue report No. 29, 2002.
Competing interests: No competing interests