Does response bias influence population studies of thyroid disorders?
BACKGROUND
Monitoring of iodine fortification programs is required for early recognition of oversupply or ineffective supply with iodine. We investigated the potential role of selection bias for studies performed to monitor the iodine supply and prevalence of thyroid disorders.


METHODS
We used the baseline population of 3949 subjects recruited for the Study of Health in Pomerania as a hypothesized source population and associated the information on response behavior from the 5-year follow-up examinations with baseline sociodemographic and thyroid-related characteristics. Due to nonresponse, 649 subjects were lost. The 3300 follow-up respondents were divided into early and late respondents according to their recruitment level.


RESULTS
We found no significant bias in the prevalence estimates of thyroid-related variables in the comparison between all respondents, and the source population after response maximization techniques had been applied. Prevalence estimates of thyroid-related characteristics (prior thyroid disorders, goiter, thyroid nodules, low serum thyrotropin, as well as increased and positive antithyroperoxidase [TPO] levels), however, were biased if we would have only investigated subjects who agreed to participate in our study after first invitation. When analyses were adjusted for sociodemographic variables, differences between early and late respondents were only statistically significant for positive anti-TPO levels.


CONCLUSIONS
We conclude that selection bias likely influences prevalence data for some studies of thyroid epidemiology. This could be diminished by making invitation procedures more rigorous.
Völzke
Henry
H
Institute of Community Medicine, Ernst Moritz Arndt University, Walther Rathenau Strasse 48, Greifswald, Germany. voelzke@uni-greifswald.de
Haring
Robin
R
Schmidt
Carsten O
CO
Alte
Dietrich
D
Kramer
Axel
A
Hoffmann
Wolfgang
W
John
Ulrich
U
Wallaschofski
Henri
H
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003677:Deficiency Diseases / Q000453:epidemiology; D005260:Female; D005858:Germany / Q000453:epidemiology; D006306:Health Surveys; D006801:Humans; D007455:Iodine / Q000008:administration & dosage* / Q000172:deficiency; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D015983:Selection Bias; D013959:Thyroid Diseases / Q000453:epidemiology*
D007455:Iodine