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Using bayesian models to assess the effects of under-reporting of cannabis use on the association with birth defects, national birth defects prevention study, 1997-2005
- Source :
- Paediatric and perinatal epidemiology. 28(5)
- Publication Year :
- 2014
-
Abstract
- Studies on associations between periconceptional cannabis exposure and birth defects have mainly relied on self-reported exposure. Therefore, the results may be biased due to under-reporting of the exposure. The aim of this study was to quantify the potential effects of this form of exposure misclassification.Using multivariable logistic regression, we re-analysed associations between periconceptional cannabis use and 20 specific birth defects using data from the National Birth Defects Prevention Study from 1997-2005 for 13 859 case infants and 6556 control infants. For seven birth defects, we implemented four Bayesian models based on various assumptions concerning the sensitivity of self-reported cannabis use to estimate odds ratios (ORs), adjusted for confounding and under-reporting of the exposure. We used information on sensitivity of self-reported cannabis use from the literature for prior assumptions.The results unadjusted for under-reporting of the exposure showed an association between cannabis use and anencephaly (posterior OR 1.9 [95% credible interval (CRI) 1.1, 3.2]) which persisted after adjustment for potential exposure misclassification. Initially, no statistically significant associations were observed between cannabis use and the other birth defect categories studied. Although adjustment for under-reporting did not notably change these effect estimates, cannabis use was associated with esophageal atresia (posterior OR 1.7 [95% CRI 1.0, 2.9]), diaphragmatic hernia (posterior OR 1.8 [95% CRI 1.1, 3.0]), and gastroschisis (posterior OR 1.7 [95% CRI 1.2, 2.3]) after correction for exposure misclassification.Under-reporting of the exposure may have obscured some cannabis-birth defect associations in previous studies. However, the resulting bias is likely to be limited.
Details
- ISSN :
- 13653016
- Volume :
- 28
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- Paediatric and perinatal epidemiology
- Accession number :
- edsair.pmid..........c30048bd67771a2b8cefac5bcef0fff9