Prenatal passive smoke exposure raises risk for negative birth outcomes. Legislation regulating public smoking has been shown to impact exposure levels, though fewer studies involving pregnant women have been conducted within the U.S. where bans are inconsistent across regions. This study examined the effect of a ban enacted in the southeastern U.S. on pregnant women’s cotinine levels. Additional analyses compared self-reported exposure to cotinine and identified characteristics associated with passive exposure. Pregnant women (N = 851) were recruited prospectively between 2005 and 2011 in North Carolina. Sociodemographic and health data were collected via surveys; maternal blood samples were assayed for cotinine. Among non-active smokers who provided self-report data regarding passive exposure (N = 503), 20% were inconsistent with corresponding cotinine. Among all non-smokers (N = 668), being unmarried, African American, and less educated were each associated with greater passive exposure. Controlling for covariates, mean cotinine was higher prior to the ban compared to after, F(1, 640) = 24.65, p < 0.001. Results suggest that banning smoking in public spaces may reduce passive smoke exposure for non-smoking pregnant women. These data are some of the first to examine the impact of legislation on passive smoke exposure in pregnant women within the U.S. using a biomarker and can inform policy in regions lacking comprehensive smoke-free legislation.

Introduction: Both prenatal smoke exposure and depression have been linked to lower birth weight, a risk factor for morbidity and mortality. Few studies have looked at the interaction between these risk factors and none have used a biomarker to objectively measure prenatal smoke exposure. The current study sought to examine independent and interactive effects of cotinine and depression on birth weight. The effect of race was also explored.Method: Data were drawn from a prospective study of pregnant women (N = 568) in the southeastern United States. Maternal demographic, health information, depressive symptoms, and birth data were collected via self-report and medical record abstraction. Prenatal blood samples were assayed for cotinine.Results: Controlling for covariates, multiple regression analyses indicated that both cotinine and depressive symptoms independently predicted lower birth weight and a significant interaction was also observed. Upon probing the interaction, a negative association between cotinine levels and birth weight was found in the context of higher depression but not lower depression scores. Similarly, logistic regression analyses revealed a significant interaction between cotinine and depression, such that cotinine predicted having a baby less than 2500 g among women who fell above the indicated cutoff score. African American women had the highest levels of cotinine and lowest weight babies; however, race was not a significant moderator.Conclusions: Results suggest prenatal smoke exposure has a greater negative effect on birth weight for women endorsing co-occurring depressive symptoms. Findings can inform targeted interventions and assist medical providers with identifying women at increased risk for poor perinatal outcomes.Implications: Despite the common occurrence of smoking during pregnancy and prenatal depression, the interaction between these risk factors on birth weight has rarely been examined. Further, the extant results have been mixed, likely due in part to difficulties in measurement. The current study was the first to use prenatal cotinine to assess bias-free, continuous levels of prenatal smoke exposure. Results indicate that prenatal cotinine was a significant predictor of birth weight only in the context of maternal depressive symptoms. These findings have important implications for mitigating negative perinatal outcomes for pregnant women and their children.

Smoke-free home rules restrict smoking in the home, but biomarkers of secondhand smoke exposure are needed to help understand the association between smoke-free homes and child secondhand smoke exposure. Participants (n = 346) were majority Black/African American mother–child dyads from a longitudinal study in North Carolina. Mothers completed questionnaires on household smoking behaviors and rules, and child saliva samples were assayed for secondhand smoke exposure. Regression models used smoke-free home rules to predict child risk for secondhand smoke exposure. Children in households with smoke-free home rules had less salivary cotinine and risk for secondhand smoke exposure. After controlling for smokers in the household, home smoking rules were not a significant predictor of secondhand smoke exposure. Compared to children in households with no smokers, children in households with at least one smoker but a non-smoking mother (OR 5.35, 95% CI: 2.22, 13.17) and households with at least one smoker including a smoking mother (OR 13.73, 95% CI: 6.06, 33.28) had greater risk for secondhand smoke exposure. Results suggest smoke-free home rules are not sufficient to fully protect children from secondhand smoke exposure, especially in homes with smokers. Future research should focus on how household members who smoke can facilitate the prevention of child secondhand smoke exposure.

Many children suffer from secondhand smoke exposure (SHSe), which leads to a variety of negative health consequences. However, there is no consensus on how clinicians can best query parents for possible SHSe among children. We employed a data-driven approach to create an efficient screening tool for clinicians to quickly and correctly identify children at risk for SHSe. Survey data from mothers and biospecimens from children were ascertained from the Neurodevelopment and Improving Children’s Health following Environmental Tobacco Smoke Exposure (NICHES) study. Included were mothers and their children whose saliva were assayed for cotinine (n = 351 pairs, mean child age = 5.6 years). Elastic net regression predicting SHSe, as indicated from cotinine concentration, was conducted on available smoking-related questions and cross-validated with 2015–2016 National Health and Nutrition Examination Survey (NHANES) data to select the most predictive items of SHSe among children (n = 1670, mean child age = 8.4 years). Answering positively to at least one of the two final items (“During the past 30 days, did you smoke cigarettes at all?” and “Has anyone, including yourself, smoked tobacco in your home in the past 7 days?”) showed area under the curve = .82, and good specificity (.88) and sensitivity (.74). These results were validated with similar items in the nationally representative NHANES sample, area under the curve = .82, specificity = .78, and sensitivity = .77. Our data-driven approach identified and validated two items that may be useful as a screening tool for a speedy and accurate assessment of SHSe among children. The current study used a rigorous data-driven approach to identify questions that could reliably predict SHSe among children. Using saliva cotinine concentration levels as a gold standard for determining SHSe, our analysis employing elastic net regression identified two questions that served as good classifier for distinguishing children who might be at risk for SHSe. The two items that we validated in the current study can be readily used by clinicians, such as pediatricians, as part of screening procedures to quickly identify whether children might be at risk for SHSe.

Background: Traditional methods for recruiting and maintaining contact with participants in cohort studies include print-based correspondence, which can be unidirectional, labor intensive, and slow. Leveraging technology can substantially enhance communication, maintain engagement of study participants in cohort studies, and facilitate data collection on a range of outcomes. Objective: This paper provides an overview of the development process and design of a cohort management platform (CMP) used in the Newborn Epigenetic STudy (NEST), a large longitudinal birth cohort study. Methods: The platform uses short message service (SMS) text messaging to facilitate interactive communication with participants; it also semiautomatically performs many recruitment and retention procedures typically completed by research assistants over the course of multiple study follow-up visits. Results: Since February 2016, 302 participants have consented to enrollment in the platform and 162 have enrolled with active engagement in the system. Daily reminders are being used to help improve adherence to the study’s accelerometer wear protocol. At the time of this report, 213 participants in our follow-up study who were also registered to use the CMP were eligible for the accelerometer protocol. Preliminary data show that texters (138/213, 64.8%), when compared to nontexters (75/213, 35.2%), had significantly longer average accelerometer-wearing hours (165.6 hours, SD 56.5, vs 145.3 hours, SD 58.5, P=.01) when instructed to wear the devices for 1 full week. Conclusions: This platform can serve as a model for enhancing communication and engagement with longitudinal study cohorts, especially those involved in studies assessing environmental exposures.