Reevaluating the protective effect of smoking on preeclampsia risk through the lens of bias

Abstract

Preeclampsia is a hypertensive disorder that is usually diagnosed after 20 weeks' gestation. Despite the deleterious effect of smoking on cardiovascular disease, it has been frequently reported that smoking has a protective effect on preeclampsia risk and biological explanations have been proposed. However, in this manuscript, we present multiple sources of bias that could explain this association. First, key concepts in epidemiology are reviewed: confounder, collider, and mediator. Then, we describe how eligibility criteria, losses of women potentially at risk, misclassification, or performing incorrect adjustments can create bias. We provide examples to show that strategies to control for confounders may fail when they are applied to variables that are not confounders. Finally, we outline potential approaches to manage this controversial effect. We conclude that there is probably no single epidemiological explanation for this counterintuitive association.

Fig. 1. Basic structure of the relationships between variables within a causal framework perspective.

Arrows indicate the direction of causality. Confounder, mediator, and collider refer to the exposure-outcome association.

Fig. 2. Potential losses of women at risk during pregnancy.

The number of arrows moving out from horizontal lines represent the loss of follow-up among smokers and non-smokers. Left- (below 20 weeks of gestational age) and right-hand sides (above 20 weeks of gestational age) draw two potential mechanisms of bias: the left side shows that losses before 20 weeks create a study cohort that is depleted of cases susceptible to the effect of smoking, while the right side shows that competing events, which are known to be more frequent among smokers, preclude the incidence of PE in that subgroup.

Fig. 3. Collider bias occurs when the selection of the study population is restricted to pregnancies which survive the effect of tobacco.

A During the first trimester (B) During the third Trimester. Arrows indicate the direction of causality. Gray line represents the association of interest.

Fig. 4. Collider bias occurs when adjusting the analysis for a variable that is a common effect both of the exposure and of a cause of the outcome.

Arrows indicate the direction of causality. Gray line represents the association of interest.

Fig. 5. Collider bias occurs when stratifying or adjusting the analysis for a variable that is a common effect both of the exposure and of a cause of the outcome.

Arrows indicate the direction of causality. Gray line represents the association of interest.