Invited Commentary: The Causal Association Between Obesity and Stillbirth—Strengths and Limitations of the Consecutive-Pregnancies Approach. Issue 7 (27th March 2019)

• Record Type: Journal Article
• Authors: Snowden, Jonathan M; Leonard, Stephanie A
• Is Part Of: American journal of epidemiology. Volume 188:Issue 7(2019)
• Page Start: 1337
• Page End: 1342
• Publication Date: 2019-03-27
• Subjects: birth outcomes -- causal inference -- generalizability -- obesity -- pregnancy -- stillbirth; Epidemiology -- Periodicals; Public health -- Periodicals; 614.4
• DOI: 10.1093/aje/kwz079
• Languages: English
• ISSNs: 0002-9262

Abstract

Abstract: There has been a resurgence in analyses of consecutive pregnancies (or similarly, sibling designs) in perinatal and pediatric epidemiology. These approaches have attractive qualities for estimating associations with complex multifactorial exposures like obesity. In an article appearing in this issue of the Journal, Yu et al. ( Am J Epidemiol . 2019;188(7):1328–1336) apply a consecutive-pregnancies approach to characterize the risk of stillbirth among women who develop obesity between pregnancies ("incident obesity"). Working within a causal framework and using parametric and nonparametric estimation techniques, the authors find an increase in stillbirth risk associated with incident obesity. Risk differences varied between 0.4 per 1, 000 births (95% confidence interval (CI): 0.1, 0.7) and 6.9 per 1, 000 births (95% CI: 3.7, 10.0), and risk ratios ranged from 1.12 (95% CI: 1.02, 1.23) to 2.99 (95% CI: 2.19, 4.08). The strengths of this approach include starting from a clearly defined causal estimand and exploring the sensitivity of parameter estimates to model selection. In this commentary, we put these findings in the broader context of research on obesity and birth outcomes and highlight concerns regarding the generalizability of results derived from within-family designs. We conclude that while causal inference is an important goal, in some instances focusing on formulation of a causal question drives results away from broad applicability.