Alexandra N Houston-Ludlam1, Kathleen K Bucholz2, Julia D Grant3, Mary Waldron4, Pamela A F Madden5, Andrew C Heath6. 1. Human and Statistical Genetics, Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, 660 S Euclid, CB 8134, St. Louis, MO 63110, USA; Medical Scientist Training Program, Washington University School of Medicine in St. Louis, 660 S Euclid, CB 8226, St. Louis, MO 63110, USA. Electronic address: ahousto@wustl.edu. 2. Department of Psychiatry, Washington University School of Medicine in St. Louis, 660 S Euclid, CB 8134, St. Louis, MO 63110, USA. Electronic address: bucholzkk@wustl.edu. 3. Department of Psychology, Maryville University of St. Louis, 650 Maryville University Drive, St. Louis, MO 63141, USA. Electronic address: jgrant@maryville.edu. 4. School of Education, Indiana University Bloomington, 201 N. Rose Ave, Bloomington, IN 47405, USA. Electronic address: mwaldron@indiana.edu. 5. Department of Psychiatry, Washington University School of Medicine in St. Louis, 660 S Euclid, CB 8134, St. Louis, MO 63110, USA. Electronic address: pmadden@wustl.edu. 6. Department of Psychiatry, Washington University School of Medicine in St. Louis, 660 S Euclid, CB 8134, St. Louis, MO 63110, USA. Electronic address: aheath@wustl.edu.
Abstract
BACKGROUND: Understanding differences in nicotine dependence assessments' ability to predict smoking cessation is complicated by variation in quit attempt contexts. Pregnancy reduces this variation, as each pregnant smoker receives the same strong cessation incentive. Cigarette smoking during pregnancy (SDP) provides a powerful paradigm for analyzing the interplay between nicotine dependence measures and sociodemographics in predicting cessation failure. METHODS: Data from a female twin cohort (median birth year 1980), assessed in teens and early twenties, were merged with birth records to identify those with smoking history who experienced childbirth (N = 1657 births, N = 763 mothers). Logistic regression predicting SDP, as a function of birth record sociodemographic variables, generated a sociodemographic risk-score. Further analysis incorporated the risk-score with data from research interviews on DSM-IV-Nicotine Dependence symptom count, Heaviness of Smoking Index. RESULTS: Low maternal educational level, younger age at childbirth, and being unmarried all contributed risk for SDP. In addition to sociodemographic risk-score, the best predictors of SDP included HSI-score (OR:1.51), their two-way interaction (OR:0.39; reduced impact of dependence at intermediate-high sociodemographic risk), history of ≥ two failed quit attempts (OR:1.38), and a dummy variable for prior pregnancy at time of assessment (OR:1.82). DSM-IV-Nicotine Dependence symptoms underperformed the Heaviness of Smoking Index and did not improve prediction when added to the best model. CONCLUSIONS: The 2-item Heaviness of Smoking Index measure and report of ≥ two failed quit attempts performed best for predicting SDP. The contribution of either nicotine dependence measure to SDP risk was diminished at increased levels of sociodemographic risk.
BACKGROUND: Understanding differences in nicotine dependence assessments' ability to predict smoking cessation is complicated by variation in quit attempt contexts. Pregnancy reduces this variation, as each pregnant smoker receives the same strong cessation incentive. Cigarette smoking during pregnancy (SDP) provides a powerful paradigm for analyzing the interplay between nicotine dependence measures and sociodemographics in predicting cessation failure. METHODS: Data from a female twin cohort (median birth year 1980), assessed in teens and early twenties, were merged with birth records to identify those with smoking history who experienced childbirth (N = 1657 births, N = 763 mothers). Logistic regression predicting SDP, as a function of birth record sociodemographic variables, generated a sociodemographic risk-score. Further analysis incorporated the risk-score with data from research interviews on DSM-IV-Nicotine Dependence symptom count, Heaviness of Smoking Index. RESULTS: Low maternal educational level, younger age at childbirth, and being unmarried all contributed risk for SDP. In addition to sociodemographic risk-score, the best predictors of SDP included HSI-score (OR:1.51), their two-way interaction (OR:0.39; reduced impact of dependence at intermediate-high sociodemographic risk), history of ≥ two failed quit attempts (OR:1.38), and a dummy variable for prior pregnancy at time of assessment (OR:1.82). DSM-IV-NicotineDependence symptoms underperformed the Heaviness of Smoking Index and did not improve prediction when added to the best model. CONCLUSIONS: The 2-item Heaviness of Smoking Index measure and report of ≥ two failed quit attempts performed best for predicting SDP. The contribution of either nicotine dependence measure to SDP risk was diminished at increased levels of sociodemographic risk.
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