ArticleAmerican journal of epidemiology2026
What Are We Estimating? Revisiting Standard Nutritional Models Through the Target Trial Framework.
Article in American journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Cardiovascular disease risk under low-fat, Mediterranean, and American Heart Association diets: a target trial emulation in United States adults.The American journal of clinical nutrition · 2026Article
- Best (but oft forgotten) practices: Applying the target trial framework in nutrition research.The American journal of clinical nutrition · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Nutritional epidemiology has long relied on standard nutritional models to examine associations between dietary exposures and health outcomes, often interpreting model coefficients with causal intent. In this paper, we use the target trial framework to clarify common causal questions in nutritional research and connect them to established tools from causal inference. Using chicken and fish as motivating examples, we define two key causal estimands relevant to dietary strategies: the total effect of chicken consumption and the comparative effect of fish versus chicken. We then use the g-formula to estimate average causal effects of the target trials and examine how common nutritional models relate to the conditional outcome model used in the g-formula estimation. We show that several standard models are re-parameterizations of the same conditional outcome model used in g-formula estimation. We also caution that standard multivariate and residual models should not be used directly within g-formula implementations without updating total energy intake under each intervention, as doing so leads to inaccurate conditional mean counterfactual outcome predictions. By providing a unified framework that links traditional models to a causal framework, our findings offer guidance on models that yield valid estimates and align with actionable dietary interventions.
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What OpenQuestion holds
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.