ISEE/ISEA 2006 Conference Abstracts Supplement: Symposium Abstracts: Abstracts
*Department of Health Sciences, University of York; †Department of Health Studies, University of Chicago; and ‡Department of Psychiatry, University of Illinois at Chicago
Our research program focuses on modeling pathways from maternal smoking during pregnancy to problem behaviors in exposed offspring with an emphasis on establishing whether exposure plays a causal role or whether it is a marker for other risk factors. Because the timing, intensity, and duration of fetal exposure may be critical in such etiologic studies, enhancing the quality of exposure measurement is essential. Yet developing an integrated approach to this question is difficult because of intraindividual variations in smoking topography and metabolism, and methodological constraints inherent in even the most meticulous exposure measurement. Our team brings several different disciplinary approaches (epidemiology, biostatistics, developmental psychopathology, pharmacology, and health psychology) and datasets (data from national surveys, small samples with intensive multimethod assessment) to bear on this issue. Our research addresses 3 questions:
1. Do prospective versus retrospective repeated versus single measures and biomarker versus self-report methods provide useful information in characterizing patterns of smoking during pregnancy?
2. Can we combine different methods to enhance the precision of exposure measurement without compromising feasibility in epidemiologic studies?
3. What psychosocial and contextual maternal factors are associated with different patterns of smoking in pregnancy and how might these confound etiologic studies of behavioral outcomes in offspring?
We have demonstrated substantial within-person fluctuations in pregnancy smoking. We have also developed new statistical approaches, including 1) characterizing patterns of smoking during pregnancy based on repeated, prospective self-report, and biologic measures using random-effects models; and 2) using Bayesian methods to create a latent exposure measure through calibration of self-reported smoking based on variability in cotinine levels at various levels of self-reported smoking. In an ongoing prospective study, we are examining associations between prospective and retrospective approaches. We test the use of these new measures by assessing their predictive value in modeling fetal growth parameters and behavioral outcomes during the first years of life.
We have also found that women who quit smoking during pregnancy have a lower prevalence of interpersonal problems, problems with adaptive functioning, and problematic health behaviors than either those who smoked in pregnancy or women who never smoked. We have demonstrated the relevance of this finding in a study of fetal exposure and infant temperament in which pregnancy quitting was protective against behavioral risk.
Smoking during pregnancy is a complex health and maternal behavior. Precision of exposure measurement is critical for disentangling effects related to the “type of women who smoke” from teratologic effects of smoking itself.