Project 4 - Low Nicotine Content Cigarettes in Vulnerable Populations: Pregnant Women

Grants and Contracts Details


The 2009 Family Smoking Prevention and Tobacco Control Act (FSPTCA) gives the Food and Drug Administration (FDA) regulatory authority over tobacco products, including nicotine levels in cigarettes. That is an exciting development as it creates the opportunity to examine the Benowitz and Henningfield (1994) hypothesis that smoking prevalence, nicotine dependence, and smoking-related morbidity and mortality can be lowered substantially by reducing the nicotine content of cigarettes to non-addictive levels. Computer modeling predicts that reducing nicotine levels in cigarettes would produce substantial improvements in population health (Tengs et al., 2005). An essential initial step towards the implementation of such a policy is to thoroughly investigate its safety and potential unintended adverse consequences. Indeed, the FDA’s Center for Tobacco Products seeks to establish research centers to assist with the mission of investigating such regulatory matters related to the FSPTCA (see RFA-DA-13-003). The FDA explicitly notes that researching tobacco regulatory questions in vulnerable populations is a crosscutting agency priority, listing women of childbearing age (15-44) and pregnant women among the vulnerable populations of interest. Approximately 23% of U.S. women of childbearing age are regular cigarette smokers, with prevalence being considerably higher among socioeconomically disadvantaged women. Indeed, disadvantaged women are at increased risk for smoking, nicotine dependence, using high nicotine yield cigarettes, and, perhaps most importantly, for smoking during pregnancy. Not surprisingly, disadvantaged female smokers are also at significantly increased risk for smoking-related adverse health consequences, including cervical cancer, thrombosis related to hormone-based contraception, infertility, and early menopause. Specific to smoking during pregnancy, disadvantaged women are at substantially increased risk for catastrophic pregnancy complications, fetal growth restriction, and adverse birth and neonatal outcomes. Studies testing an innovative regulatory strategy of reducing the nicotine content of cigarettes to a non-addictive level (i.e., <0.2 mg nicotine) have shown promising beneficial effects (decreased smoking rate, reduced toxicant exposure, and increased cessation) in the general population of smokers. However, these studies have uniformly excluded vulnerable populations, especially pregnant women, who may respond differently considering their greater vulnerability to smoking and nicotine dependence. Thus, little is known scientifically about how this highly vulnerable subgroup of smokers might respond to a nicotine reduction policy. The primary overall objective of this study is to evaluate the use and effects of cigarettes varying in nicotine content. This study will examine the two lowest doses (0.12 mg and 0.03 mg) compared to the pregnant smokers’ usual brand. The study conducted under the University of Kentucky subaward will evaluate the effects of extended exposure to cigarettes differing in nicotine content in pregnant smokers with < an Associate’s degree. This study will be limited to two conditions: usual brand versus the 0.03 mg dose. After a baseline period in which daily smoking rate and other baseline assessments are completed, participants will be randomly assigned to usual brand or the VLNC condition and followed weekly for 12 weeks. To examine these Aims, repeated measures analysis of variance (ANOVA) will be used for outcomes ((1) number of cigarettes smoked per day, and 2) measure of exposure) that are measured repeatedly from baseline to the end of the treatment phase. Each repeated measures ANOVA model consists of five terms: cigarette condition effect, visit effect, interaction effect between cigarette condition and visit, random subject effect (between-subject error), and random error (within-subject error). The variance-covariance structure will be specified as the first-order autoregressive, and variance parameters will be estimated using restricted maximum likelihood method with the Satterthwaite approximation.
Effective start/end date10/1/218/31/22


  • University of Vermont: $200,000.00


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