Objectives: To estimate the prevalence and factors associated with smoking and misclassification in pregnant women from INMA (INfancia y Medio Ambiente, Environment and Childhood) project, Spain, and to assess the optimal cut-offs for urinary cotinine (UC) that best distinguish daily and occasional smokers with varying levels of second-hand smoke (SHS) exposure.
Design: We used logistic regression models to study the relationship between sociodemographic variables and self-reported smoking and misclassification (self-reported non-smokers with UC >50 ng/ml). Receiver operating characteristic (ROC) curves were used to calculate the optimal cut-off point for discriminating smokers. The cut-offs were also calculated after stratification among non-smokers by the number of sources of SHS exposure. The cut-off points used to discriminate smoking status were the level of UC given by Youden's index and for 50 and 100 ng/ml for daily smokers, or 25 and 50 ng/ml for occasional smokers.
Participants: At the third trimester of pregnancy, 2263 pregnant women of the INMA Project were interviewed between 2004 and 2008 and a urine sample was collected.
Results: Prevalence of self-reported smokers at the third trimester of pregnancy was 18.5%, and another 3.9% misreported their smoking status. Variables associated with self-reported smoking and misreporting were similar, including born in Europe, educational level and exposure to SHS. The optimal cut-off was 82 ng/ml (95% CI 42 to 133), sensitivity 95.2% and specificity 96.6%. The area under the ROC curve was 0.986 (95% CI 0.982 to 0.990). The cut-offs varied according to the SHS exposure level being 42 (95% CI 27 to 57), 82 (95% CI 46 to 136) and 106 ng/ml (95% CI 58 to 227) for not being SHS exposed, exposed to one, and to two or more sources of SHS, respectively. The optimal cut-off for discriminating occasional smokers from non-smokers was 27 ng/ml (95% CI 11 to 43).
Conclusions: Prevalence of smoking during pregnancy in Spain remains high. UC is a reliable biomarker for classifying pregnant women according to their smoking status. However, cut-offs would differ based on baseline exposure to SHS.