Evaluating alternative exposure indices in epidemiologic studies on extremely low-frequency magnetic fields.
Choosing the right exposure index for epidemiological studies on 50-60 Hz magnetic fields is difficult due to the lack of knowledge about critical exposure parameters for the biological effects of magnetic fields. This paper uses data from a previously published epidemiological investigation on early pregnancy loss (EPL) to study the methods of evaluating the exposure-response relationship of 50 Hz magnetic fields. Two approaches were used. The first approach was to apply generalized additive modeling to suggest the functional form of the relationship between EPL and magnetic field strength. The second approach evaluated the goodness of fit of the EPL data with eight alternative exposure indices: the 24 h average of magnetic field strength, three indices measuring the proportion of time above specified thresholds, and four indices measuring the proportion of time within specified intensity windows. Because the original exposure data included only spot measurements, estimates for the selected exposure indices were calculated indirectly from the spot measurements using empirical nonlinear equations derived from 24 h recordings in 60 residences. The results did not support intensity windows, and a threshold-type dependence on field strength appeared to be more plausible than a linear relationship. In addition, the study produced data suggesting that spot measurements may be used as surrogates for other exposure indices besides the time average field strength. No final conclusions should be drawn from this study alone, but we hope that this exercise stimulates evaluation of alternative exposure indices in other planned and ongoing epidemiological studies.
Juutilainen
J
J
Department of Environmental Sciences, University of Kuopio, Kuopio, Finland.
Hatfield
T
T
Läärä
E
E
D000022:Abortion, Spontaneous / Q000453:epidemiology* / Q000209:etiology*; D004574:Electromagnetic Fields / Q000009:adverse effects*; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D011247:Pregnancy; D012984:Software