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. Professor Experimental Dermatology Unit, Department of Neuroscience, Karolinska Institute Stockholm, Sweden
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DOES GSM 1800 MHz AFFECT THE PUBLIC HEALTH IN SWEDEN?
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. Professor Experimental Dermatology Unit, Department of Neuroscience, Karolinska Institute Stockholm, Sweden. The purpose of the study. - PowerPoint PPT Presentation
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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
400
600
800
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?