International Journal of Environmental Research and Public Health · 2020 · 54 citations · 25 references
Public HealthMaternal HealthHealth AssessmentPerinatal EpidemiologyWomen's HealthMaternal SmokingTobacco Use Risk AssessmentCohort Study InvestigationPositive Predictive ValuePositive Predictive Value AnalysisPrenatal Tobacco ExposureSelf-administered QuestionnairesSelf-report QuestionnairesSmoking History In PregnancyTobacco Use Among Pregnant Women
Few studies have assessed the accuracy of self-reported questionnaires to determine smoking habits relative to urinary biomarkers. This study investigated urinary cotinine cut-off concentrations distinguishing active, passive and non-smokers among pregnant women who participated in the Japan Environment and Children’s Study, a nationwide birth cohort study. Pregnant participants with measured urinary cotinine concentrations (UCCs) and who completed self-reported questionnaires on smoking status were included (n = 89,895). The cut-off values (COVs) for active and passive smokers were calculated by fitting mixed normal distribution functions to UCCs. The sensitivity and specificity of the questionnaires were subsequently evaluated. The median (interquartile range) UCC was 0.24 (0.083–0.96) µg/g-creatinine, with the detection rate of 89%. The COV for distinguishing active smokers from passive and non-smokers was 36.8 µg/g-creatinine. When this COV was considered to represent the true condition, the questionnaire had a sensitivity of 0.523, a specificity of 0.998, a positive predictive value (PPV) of 0.967 and a negative predictive value (NPV) of 0.957. The COV for distinguishing passive smokers from non-smokers was 0.31 µg/g-creatinine, with the questionnaire having a sensitivity of 0.222, a specificity of 0.977, a PPV of 0.868 and an NPV of 0.644. As many as 78% of passive smokers might be misclassified as non-smokers.
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Smoking During Pregnancy and Newborn Neurobehavior
Karen Law, Laura R. Stroud, Linda L. LaGasse et al. · PEDIATRICS · 2003 · 305 citations
Yuta Yokoyama, Ribeka Takachi, Junko Ishihara et al. · Journal of Epidemiology · 2016 · 297 citations · Full text