DOES GSM 1800 MHz AFFECT THE PUBLIC HEALTH IN SWEDEN?

Örjan Hallberg, M.Sc. E.E.Polkavägen 14B, 142 65 Trångsund Sweden

Olle Johansson, Assoc. ProfessorExperimental Dermatology Unit, Department of Neuroscience, Karolinska InstituteStockholm, Sweden

The purpose of the study

To see if changes in health characteristics fit the roll-out of GSM 1800 in Sweden - Does it fit in time? - Does it fit geographically?

How much do we talk by the mobile phone each year?

0

5000

10000

15000

20000

25000

1975 1980 1985 1990 1995 2000 2005

Sp

eech

tim

e/ye

ar (

year

s)

NMT+GSM years Dual-band years

What is the average output pulse power from the phones?

0,0

0,5

1,0

1,5

2,0

1 10 100 1000

Population density (pers/km2)

Av

era

ge

ou

tpu

t p

ow

er

(W)

Telia/Ericsson: Mean W Median W

A GSM coverage model was tuned to the data from Telia/Ericsson

0,0

0,5

1,0

1,5

2,0

1 10 100 1000

Population density (pers/km2)

Av

era

ge

ou

tpu

t p

ow

er

(W)

Coverage model Telia/Ericsson: Mean W Median W

Sick-days statistics from 1981 looks different...

R2 = 0,1073

0,0

0,5

1,0

1,5

2,0

1 10 100 1000

Population density (pers/km2)

Av

era

ge

ou

tpu

t p

ow

er

(W)

15

20

25

30

35

Sic

k-d

ay

s

Coverage model Telia/Ericsson: Mean W Median W sick-days 1981

But the sick-days statistics from 2002 fits very well

R2 = 0,6574

0,0

0,5

1,0

1,5

2,0

1 10 100 1000

Population density (pers/km2)

Av

era

ge

ou

tpu

t p

ow

er

(W)

15

20

25

30

35

Sic

k-d

ay

s

Coverage model Telia/Ericsson: Mean W Median W sick-days 2002

So, the sickness in Sweden seems to relate to the GSM coverage

R2 = 0,7894

0

5

10

15

20

25

30

35

0 20 40 60 80 100

GSM fully covered (% of area)

Sic

kd

ay

s 2

00

2

And, funny enough, so it does also in Denmark and Norway

R2 = 0,4926

R2 = 0,4913

0

20

40

60

80

100

0 20 40 60 80 100

Fully covered area (%)Copyright Hallberg Independent Research, 2004

Hea

lth

co

st i

ncr

ease

(%

)

No Dk

Some drugs sell like hell…e.g. Antidepressives

Pain killers on the rise...

0

50

100

150

200

250

1999 2000 2001 2002 2003 2004 2005

Da

y-d

os

es

/ye

ar

(M)

The mortality trend for the age group 10-39 years was broken in 1997

Mortality relative year 1950, age 10-39 years

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

1985 1990 1995 2000 2005

Rel

ativ

e m

ort

alit

y

The number of sick-registered started to increase in 1997

0

50

100

150

200

250

300

350

1985 1990 1995 2000 2005

Sic

k r

eg

iste

red

(k

)

0

2

4

6

8

10

12

14

1800

MH

z ea

r m

inu

tes

(10

9 )

On sick leave Long term sick 1800 GEM

The trend-break is noticed all over Sweden...

0%

50%

100%

150%

200%

250%

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

Stockholm

Uppsala

Södermanland

Östergötland

Jönköping

Kronoberg

Kalmar

Gotland

Blekinge

Kristianstad

Malmöhus

Halland

Bohuslän

Älvsborg

Skaraborg

Värmland

Örebro

Västmanland

Kopparberg

Gävleborg

Västernorrland

Jämtland

Västerbotten

Norrbotten

For each county a specific break point was identified.

Stockholm

0

10000

20000

30000

40000

50000

60000

70000

jan

-96

ma

j-9

6

sep

-96

jan

-97

ma

j-9

7

sep

-97

jan

-98

ma

j-9

8

sep

-98

jan

-99

ma

j-9

9

sep

-99

jan

-00

ma

j-0

0

sep

-00

jan

-01

ma

j-0

1

sep

-01

jan

-02

ma

j-0

2

Increasing sickness since 1997

0

0,5

1

1,5

2

2,5

3

3,5

4

1985 1990 1995 2000 2005

Mea

sure

rel

. 19

97

Sick-registered Sweden

Stockholm traffic Inj

Stockholm Bus inj

Long term sick registered

Sickness Swedish priv. Comp.

Sickness Telia AB

Sickness E/// White col

Sickness Scania AB

Load inj men

Load inj women

Suicide attempts age 15-24

Prostate cancer Sweden

Stockholm Prostate age 50-59

Sweden Prostate age 50-59

Company health statistics got worse in 1997

0

0,5

1

1,5

2

2,5

1990 1992 1994 1996 1998 2000 2002 2004

Wo

rkfo

rce

sic

kn

es

s r

el t

o 1

99

7

0

3

6

9

12

15

Gig

a E

ar-

he

ati

ng

Min

ute

s 1

80

0 M

Hz

Sw Enterpr. Telia AB Ericsson (white-collar) Scania AB GEM1800

Traffic injuries in Stockholm are increasing

0

200

400

600

800

1000

1200

1400

1985 1990 1995 2000 2005

Se

ve

rely

inju

red

in S

thlm

tra

ffic

0

2

4

6

8

10

12

14

1800

MH

z g

iga

ear

min

ute

s (G

EM

)

Traffic inj Sthlm 1800 GEM

Both handheld and hands-free phones increase the reaction time while driving

Work-load related injuries are increasing

And it takes longer time to recover from a work related sickness or accident in the high power counties!

R2 = 0,3694

R2 = 0,631

0

50

100

150

200

250

0 0,5 1 1,5 2

Average mobile phone output power (W)

Sic

knes

s (d

ays)

0

20

40

60

80

100

Inju

ry r

eco

very

(d

ays)

Sickness Injury

It also takes longer time to recover from a surgery operation in sparsely populated regions

0

100

200

300

400

500

600

0 0,5 1 1,5 2

Average output power (W)

Rec

ove

ry d

ays

afte

r su

rger

y

Heart infarct Breast

The mortality due to external causes is higher in the countryside

R2 = 0,5124p=0,00026

0

20

40

60

80

0 0,5 1 1,5 2

Average handset pulse power (W)

Mo

rtal

ity

(1/1

00,0

00)

Nerve system mortality

R2 = 0,3906p=0,0024

05

10

15202530

354045

0 0,5 1 1,5 2

Average pulse power (W)

Mo

rtal

ity

2001

The number of deaths per year in Alzheimer’s disease is accelerating!

Alzheimer deaths in Sweden

0

200

400

600

800

1000

1200

1960 1970 1980 1990 2000 2010

Dea

ths

And especially so in high power counties

Alzheimer mortality increase 1997-2001 vs mobile phone output power in Sweden

R2 = 0,3717p=0,0033

0

5

10

15

20

0 0,5 1 1,5 2

Average pulse power (W)

Mo

rtal

ity

incr

. (1

/100

,000

)

This is not the case for a completely different neuralgic disease, ALS.

R2 = 0,0072

-5

0

5

10

15

20

0 0,5 1 1,5 2

Average output pulse power (W)

Mo

rtal

ity

chan

ge

(1/1

00 0

00)

And ALS shows no trendbreak

R2 = 0,0355

0

1

2

3

4

1996 1997 1998 1999 2000 2001 2002

Mo

rtal

ity

(1/1

00,0

00)

Prostate cancer has been increasing in Stockholm since 1997

0

50

100

150

200

250

1985 1990 1995 2000 2005

Ne

w p

ros

tate

ca

nc

er

ca

se

s

Prost Sth 50-59

But it has nothing to do with mobile phone output power!

Incidence change 1997-2002

R2 = 0,2088

-50

0

50

100

150

200

0 0,5 1 1,5 2

Average output power (W)

Inci

den

ce c

han

ge

(1/1

00,0

00)

So, if we look at leukemia, is there any trend-break? No - not at all!

Leukemia, annual new cases

0

200

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1000

1200

1993 1995 1997 1999 2001 2003 2005

New

cas

es

0

4000

8000

12000

16000

20000

24000

Sp

eech

tim

e p

er y

ear

(yea

rs)

Does the incidence increase by mobile output power? No!

R2 = 0,0635

0

2

4

6

8

10

12

14

16

0 0,5 1 1,5 2

Average output power (W)

Leu

kem

ia i

nci

den

ce (

1/10

0,00

0)

So, to summarize

Which health characteristics do fit with GSM1800?

And which ones don’t?

Can the mobile system possibly be accountable for all these problems?

Problem Trend break in 1997? Is it worse where highhandset power is used?

Logical explanation

Leukemia No No Not caused by RF-EMF

Population Sickness Yes Yes Impaired recovery

Traffic injuries Yes Yes - inside cars Delayed reaction timewhile driving

Surgery recoverytimes

Don't know Yes Impaired recovery

Work relatedaccidents

Yes Yes Impaired recovery

Externally causeddeaths

Increasing, most in2001

Yes Psychiatric, suicide,murders, accidents,reaction times etc

Prostate cancer Yes No This needs to be looked at.

Alzheimer deaths Yes, but also before Yes Damaged BBB will speedup the death of the patient

ALS deaths No No Not caused by RF-EMF

Conclusions

The data shows that the health of the whole Swedish population is threatened

Sparsely populated counties are worse off

The responsible authorities must seriously consider possible health implications from the GSM 1800 MHz system

Download graphs at:

http://hir.nu/1800

Sick-days and cancer incidence in Sweden

R2 = 0,6574

R2 = 0,708p=0,000008

0

100

200

300

400

500

0 0,5 1 1,5 2 2,5 3

Population density (10x/km2)Copyright Hallberg Independent Research 2004

Inci

den

ce (

1/10

0,00

0)

0

10

20

30

40

50

Sic

kday

s

Cancer Sickdays 2002

The problem we see

Health care costs are boomingThe mortality improvement among

young people has come to an endSparsely populated areas are

unhealthyIllness recovery times are increasingAccidents happen more frequently...

So, sick-days seem to relate to the output power from the mobile phone

R2 = 0,7903

0

5

10

15

20

25

30

35

0 0,5 1 1,5 2

Average output power (W)

Sic

k-d

ay

s

sick-days 2002

Two questions regarding GSM

When did the mobile phone use really take off?

Where in the country do mobile phones radiate the highest average output power?

Let’s now look at some health related facts

Drug salesMortalitySickness

And so it does for all of Sweden

Prostate cancer incidence, Sweden 50-59 years of age

0

20

40

60

80

100

120

140

1965 1970 1975 1980 1985 1990 1995 2000 2005

Inci

den

ce, A

SI

(1/1

00,0

00)

So, the sickness trend-break fits with GSM 1800 ramp up

What about the different counties in Sweden?

Exact when? August 1997 (?)

0

50 000

100 000

150 000

200 000

250 000

300 000

350 000

19

92

12

19

93

12

19

94

12

19

95

12

19

96

12

19

97

12

19

98

12

19

99

12

20

00

12

20

011

2

20

02

12

Sic

k-r

eg

iste

red

The average handset output power and sickness varies over the country

R2 = 0,9417

0

1

2

3

4

5

6

7

0 0,5 1 1,5 2

Average pulse power (W)

Sic

kn

es

s %

Telia/Ericsson measurement

The sickness break-points and GSM 1800 roll-out

Sickness break-points: Oct-97 to Jan-98

GSM 1800 roll-out: Autumn -97 to Jan-98

The number of injured drivers in Sweden is increasing

What about work related injuries and sickness?

Is there a trend break?Is it worse in counties with low

population density?

The sickness varies among the counties in Sweden

R2 = 0,8223

0,00

1,00

2,00

3,00

4,00

5,00

6,00

7,00

8,00

0 0,5 1 1,5 2

Average pulsepower (W)

Sic

kn

es

s %