EMR, sleep and diabetes
For more than a decade there’s been convincing evidence that exposure to electromagnetic radiation changes brain wave patterns during sleep.
Now there’s evidence that such changes can be linked to diabetes.
A study published in the January issue of the Proceedings of the National Academy of Science in the US has found that depression of slow-wave sleep affects insulin production and increases risk of diabetes. 1 Slow-wave or deep, non-rapid eye movement sleep, is thought to be the most restorative of all stages of sleep.
“Our data suggest that reduced sleep quality with low levels of SWS [slow-wave sleep] … may contribute to increase the risk of type 2 diabetes,” say the authors.
The researchers, from the University of Chicago Medical Centre, conducted the study on nine healthy volunteers — five men and four women — aged 20 to 31.
In the first phase of the experiment, subjects were monitored for 8.5 hours of undisturbed sleep. In the second phase, over three consecutive nights, subjects were deprived of slow-wave sleep. Every time a volunteer’s brainwave pattern indicated he/she was entering this stage of sleep, a sound was directed to a speaker by the bed sufficient to disturb but not to wake the sleeper.
“This decrease in slow-wave sleep resembles the changes in sleep patterns caused by 40 years of aging,” said Dr Esra Tasali, assistant professor at the Centre. “Young adults spend 80 to 100 minutes per night in slow-wave sleep, while people over age 60 generally have less than 20 minutes.”
The researchers found that depression of slow-wave sleep over three nights caused the volunteers to become about 25% less sensitive to insulin — a change comparable to gaining 20 to 30 pounds. As insulin sensitivity declined, subjects needed more insulin to deal with the same amount of glucose in their bloodstreams. However, because their insulin production did not increase, subjects had a 23% increase in blood-glucose levels, which is comparable to levels in older adults with impaired glucose tolerance and increased diabetes risk.
“These findings demonstrate a clear role for slow-wave sleep in maintaining normal glucose control,” said Dr Tasali.
“A profound decrease in slow-wave sleep had an immediate and significant adverse effect on insulin sensitivity and glucose tolerance.”
One of the factors that has been repeatedly shown to affect sleep quality and brain wave patterns during sleep is electromagnetic radiation — both from electrical and communications sources.
In 1999, for example, a study by T Akerstedt found that volunteers exposed to a 50 Hz field of 10 milliGauss (one hundredth of the allowable Australian limit) showed reductions in sleep time, sleep efficiency, slow-wave sleep and slow-wave brain wave activity. 2
In the same year a study by A Borbely found that subjects exposed to mobile phone radiation of 900 MHz at night also had changes to slow-wave sleep. 3
Several studies have shown a more direct connection between EMR and diabetes from electrical sources. Dr Ivan Beal found an increased risk of diabetes among people living near a high voltage power line in New Zealand.4 Similarly, a Japanese study found that a 60 Hz field changed insulin release from cells. 5
Radiofrequency radiation also appears to affect blood-sugar levels. J Bielski found that the majority of workers exposed to radio waves in his study showed abnormal blood-sugar levels after being given a dose of glucose. 6 Canadian researcher M Havas showed that people exposed to “dirty electricity” (RF signals conducted through the electrical system) also had increased levels of blood-sugar problems. 7
It may be no coincidence, therefore, that the incidence of diabetes has risen dramatically in the last 20 years, a period that correlates with the rapid increase in electrical and telecommunications technologies. In that period the number of people affected has doubled in Australia, with approximately one in every four people affected.
References
1.Tasali, E et al, Proc Natl Acad Sci USA 105(3):1044-9, 2008.
2.Akerstedt, T et al, J Sleep Res 8(1):77-81, 1999.
3.Borbely A et al, Neurosci Lett 275(3):207-10, 1999.
4.Beal, I et al, Bioelectromagnetics 18(8):584-94, 1997.
5.Sakurai, T et al Bioelectromagnetics 25(3):160-6).
6.Bielski J et al, Med Pr 47(3):227-31, 1996.
7.Havas, M, Electromag Biol and Med 25259-68, 2006.
from 'EMR and Health' Mar 2008, vol 4 no 1