Bornehag, Carl-Gustaf, Moniruzzaman, Syed, Larsson, Malin, Boman Lindström, Cecilia, Hasselgren, Mikael, Bodin, Anna, von Kobyletzki, Laura B., Carlstedt, Fredrik, Lundin, Fredrik, Nånberg, Eewa, Jönsson, Bo A. G., Sigsgaard, Torben, Janson, Staffan, Bornehag, Carl-Gustaf, Moniruzzaman, Syed, Larsson, Malin, Boman Lindström, Cecilia, Hasselgren, Mikael, Bodin, Anna, von Kobyletzki, Laura B., Carlstedt, Fredrik, Lundin, Fredrik, Nånberg, Eewa, Jönsson, Bo A. G., Sigsgaard, Torben, and Janson, Staffan
Background: This paper describes the background, aim and study design for the Swedish SELMA study that aimed to investigate the importance of early life exposure during pregnancy and infancy to environmental factors with a major focus on endocrine disrupting chemicals for multiple chronic diseases/disorders in offspring. Methods: The cohort was established by recruiting women in the 10th week of pregnancy. Blood and urine from the pregnant women and the child and air and dust from home environment from pregnancy and infancy period have been collected. Questionnaires were used to collect information on life styles, socio-economic status, living conditions, diet and medical history. Results: Of the 8394 reported pregnant women, 6658 were invited to participate in the study. Among the invited women, 2582 (39%) agreed to participate. Of the 4076 (61%) non-participants, 2091 women were invited to a non-respondent questionnaire in order to examine possible selection bias. We found a self-selection bias in the established cohort when compared with the non-participant group, e.g. participating families did smoke less (14% vs. 19%), had more frequent asthma and allergy symptoms in the family (58% vs. 38%), as well as higher education among the mothers (51% vs. 36%) and more often lived in single-family houses (67% vs. 60%). Conclusions: These findings indicate that the participating families do not fully represent the study population and thus, the exposure in this population. However, there is no obvious reason that this selection bias will have an impact on identification of environmental risk factors.