The Impact of Maternal Smoking During Pregnancy on Childhood Asthma: Adjusted for Exposure Misclassification; Results From the National Health and Nutrition Examination Survey, 2011–2012 Publisher Pubmed



Moradzadeh R¹ ; Mansournia MA² ; Baghfalaki T³ ; Nadrian H⁴ ; Gustafson P⁵ ; Mccandless LC⁶ Show Affiliations
Source: Annals of Epidemiology Published:2018

Abstract

Purpose: We sought to examine the association between childhood asthma and self-reported maternal smoking during pregnancy (MSDP) after adjusting for a range of exposure misclassification scenarios using a Bayesian approach that incorporated exposure misclassification probability estimates from the literature. Methods: Self-reported MSDP and asthma data were extracted from National Health and Nutrition Examination Survey 2011–2012. The association between self-reported MSDP and asthma was adjusted for exposure misclassification using a Bayesian bias model approach. Results: We included 3074 subjects who were 1–15 years of age, including 492 asthma cases. The mean (SD) of age of the participants was 8.5 (4.1) and 7.1 (4.2) years and the number (percentage) of female was 205 (42%) and 1314 (51%) among asthmatic and nonasthmatic groups, respectively. The odds ratio (OR) for the association between self-reported MSDP and asthma in logistic regression adjusted for confounders was 1.28 (95% confidence interval: 0.92, 1.77). In a Bayesian analysis that adjusted for exposure misclassification using external data, we found different ORs between MSDP and asthma by applying different priors (posterior ORs 0.90 [95% credible interval {CRI}: 0.47, 1.60] to 3.05 [95% CRI: 1.73, 5.53] in differential and 1.22 [CRI 95%: 0.62, 2.25] to 1.60 CRI: 1.18, 2.19) in nondifferential misclassification settings. Conclusions: Given the assumptions and the accuracy of the bias model, the estimated effect of MSDP on asthma after adjusting for misclassification was strengthened in many scenarios. © 2018 Elsevier Inc.