Background

Several studies have examined maternal health behavior during pregnancy and child outcomes. Negative control variables have been used to address unobserved confounding in such studies. This approach assumes that confounders affect the exposure and the negative control to the same degree. The current study introduces a novel latent variable approach that relaxes this assumption by accommodating repeated measures of maternal health behavior during pregnancy.

Methods

Monte Carlo simulations were used to examine the performance of the latent variable approach. A real-life example is also provided, using data from the Norwegian Mother, Father, and Child Study (MoBa).

Results

Simulations: Regular regression analyses without a negative control variable worked poorly in the presence of unobserved confounding. Including a negative control variable improved result substantially. The latent variable approach provided unbiased results in several situations where the other analysis models worked poorly. Real-life data: Maternal alcohol use in the first trimester was associated with increased ADHD symptoms in the child in the standard regression model. This association was not present in the latent variable approach.

Conclusion

The current study showed that a latent variable approach with a negative control provided unbiased estimates of causal associations between repeated measures of maternal health behavior during pregnancy and child outcomes, even when the effect of the confounder differed in magnitude between the negative control and the exposures. The real-life example showed that inferences from the latent variable approach were incompatible with those from the standard regression approach. Limitations of the approach are discussed.

中文翻译：

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处理产前危险因素与儿童结局之间关系中未观察到的混杂：一种潜在变量策略

背景

几项研究检查了孕期孕产妇健康行为和儿童结局。负控制变量已用于解决此类研究中未观察到的混杂问题。这种方法假设混杂因素对暴露和阴性对照的影响程度相同。目前的研究引入了一种新的潜在变量方法，通过适应怀孕期间孕产妇健康行为的重复测量来放宽这一假设。

方法

蒙特卡洛模拟被用来检查潜在变量方法的性能。还提供了一个真实的例子，使用来自挪威母亲、父亲和儿童研究 (MoBa) 的数据。

结果

模拟：没有负控制变量的常规回归分析在存在未观察到的混杂情况下效果不佳。包括负控制变量可以显着改善结果。在其他分析模型效果不佳的几种情况下，潜在变量方法提供了无偏的结果。真实数据：在标准回归模型中，孕早期母亲饮酒与儿童 ADHD 症状增加有关。这种关联不存在于潜在变量方法中。

结论

目前的研究表明，即使混杂因素的影响在阴性对照和暴露之间的幅度不同，带有阴性对照的潜变量方法也可以无偏地估计孕期孕产妇健康行为重复测量与儿童结局之间的因果关系。现实生活中的例子表明，潜在变量方法的推论与标准回归方法的推论不相容。讨论了该方法的局限性。