|
Variable
|
Category
|
n
|
Coefficient
|
95%-CI
|
p-value
|
|---|
|
Age
|
young adults (20-34 y)
|
56
|
reference
|
-
|
-
|
| |
adults (35-64)
|
69
|
0.77
|
0.59;1.01
|
0.06
|
| |
retired people (>64)
|
6
|
0.75
|
0.39;1.42
|
0.37
|
|
Gender
|
Female
|
74
|
reference
|
-
|
-
|
| |
Male
|
57
|
0.93
|
0.72;1.20
|
0.58
|
|
Place of residence
|
Urban
|
76
|
reference
|
-
|
-
|
| |
Suburban
|
55
|
1.27
|
0.97;1.66
|
0.08
|
|
Ownership of mobile phone
|
Yes
|
119
|
reference
|
-
|
-
|
| |
No
|
12
|
0.70
|
0.44;1.11
|
0.13
|
|
Ownership of cordless phone
|
Yes
|
79
|
reference
|
-
|
-
|
| |
No
|
52
|
0.91
|
0.68;1.21
|
0.51
|
|
Ownership of W-LAN
|
Yes
|
50
|
reference
|
-
|
-
|
| |
No
|
81
|
0.95
|
0.72;1.25
|
0.72
|
|
Socio economic status
|
Low
|
21
|
reference
|
-
|
-
|
| |
Middle
|
17
|
0.87
|
0.54;1.39
|
0.55
|
| |
High
|
93
|
1.10
|
0.77;1.58
|
0.59
|
- Coefficients of a multiple loglinear regression model using data from a Swiss RF-EMF population survey [15]. This model allows predicting average RF-EMF exposure in different population strata
- Intercept of the model: 0.11 mW/m2 (95%-CI: 0.08-0.17) (exposure during the day of a female person aged 20-34 living in an urban environment, owning a mobile phone, a cordless phone and wireless LAN at home, with the lowest socioeconomic status).
- To calculate total exposure of a woman with the same characteristics but who does not own a mobile phone, the value has to be multiplied by 0.70 resulting in an exposure of 0.08 mW/m2. Note that this is only an example to demonstrate the principle of an exposure prediction model. Lack of significance of coefficients for potentially relevant parameters may indicate that a larger sample size is needed for this type of exposure prediction model.
