ArticleEpidemiology (Cambridge, Mass.)2012
Conditioning on intermediates in perinatal epidemiology.
Article in Epidemiology (Cambridge, Mass.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 116 papers, 6 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
116 citing papers in PubMed, 6 syntheses or guidelines pooled it, 212 citations in OpenAlex.
- Effects of maternal education on maternal and perinatal outcomes: An individual participant data meta-analysis of 2 356 402 pregnancies.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026Pooled it
- What are the pathways between poverty and malaria in sub-Saharan Africa? A systematic review of mediation studies.Infectious diseases of poverty · 2023Pooled it
- Pooled it
- Maternal smoking during pregnancy and offspring overweight: is there a dose-response relationship? An individual patient data meta-analysis.International journal of obesity (2005) · 2018Pooled it
- Pooled it
- Association between Prenatal and Postnatal Psychological Distress and Toddler Cognitive Development: A Systematic Review.PloS one · 2015Pooled it
- Trial
- Handling of multicohort data in pooled analysis of environmental exposures: confounding by cohort of the relationship between perfluoroalkyl substances and birthweight in the ECHO Program.American journal of epidemiology · 2026Article
- Gestational misalignment with fixed exposure windows: the potential dangers of zero-filling in distributed lag models.International journal of epidemiology · 2026Article
- Contributions of preeclampsia to preterm delivery: a hypothetical interventional cohort study using incremental propensity scores.International journal of epidemiology · 2026Article
- Associations among familism, maternal parenting, and weight-related behaviors in Mexican American adolescents: a cross-sectional structural equation modeling study.BMC public health · 2026Article
- High ambient temperature during pregnancy and offspring cerebral palsy: A population-based case-control study in California.Environmental research · 2026Article
- Covariate adjustment in LGBTQ+ health disparities research: aligning methods with assumptions.American journal of epidemiology · 2026Article
- Intergenerational Effects of Maternal Stressful Life Events Before Pregnancy on Offspring Growth: A Lifecourse Approach from a Prospective Cohort.International journal of women's health · 2026Article
- Tracking vaccine effectiveness in an evolving pandemic, countering misleading hot takes and epidemiologic fallacies.American journal of epidemiology · 2025Article
- Impacts of Vehicle Emission Regulations and Local Congestion Policies on Birth Outcomes Associated with Traffic Air Pollution.Research report (Health Effects Institute) · 2025Article
- Obesity and postpartum hospital use among individuals without additional medical comorbidities.Obesity (Silver Spring, Md.) · 2025Article
- Unmeasured mediator-outcome confounding distorts both indirect and direct effects.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Tocolysis and Neurodevelopment of Children Born Very Preterm.JAMA network open · 2024Article
- Bridging Differences in Cohort Analyses of the Relationship between Secondhand Smoke Exposure during Pregnancy and Birth Weight: The Transportability Framework in the ECHO Program.Environmental health perspectives · 2024Article
56 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
It is common practice in perinatal epidemiology to calculate gestational-age-specific or birth-weight-specific associations between an exposure and a perinatal outcome. Gestational age or birth weight, for example, might lie on a pathway from the exposure to the outcome. This practice of conditioning on a potential intermediate has come under critique for various reasons. First, if one is interested in assessing the overall effect of an exposure on an outcome, it is not necessary to stratify, and indeed, it is important not to stratify, on an intermediate. Second, if one does condition on an intermediate, to try to obtain what might conceived of as a "direct effect" of the exposure on the outcome, then various biases and paradoxical results can arise. It is now well documented theoretically and empirically that, when there is an unmeasured common cause of the intermediate and the outcome, associations adjusted for the intermediate are subject to bias. In this paper, we propose 3 approaches to facilitate valid inference when effects conditional on an intermediate are in view. These 3 approaches correspond to (i) conditioning on the predicted risk of the intermediate, (ii) conditioning on the intermediate itself in conjunction with sensitivity analysis, and (iii) conditioning on the subgroup of individuals for whom the intermediate would occur irrespective of the exposure received. The second and third approaches both require sensitivity analysis, and they result in a range of estimates. Each of the 3 approaches can be used to resolve the "birth-weight paradox" that exposures such as maternal smoking seem to have a protective effect among low-birth-weight infants. The various methodologic approaches described in this paper are applicable to a number of similar settings in perinatal epidemiology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.