The article discusses how a causal graph model can help understand the link between diet and health. This model uses prior knowledge to visualize complex relationships and identify factors that may affect the results. By adjusting for confounding variables and using different analysis strategies, researchers can estimate the causal effects of specific dietary factors on health outcomes. This approach aims to improve the quality of nutritional epidemiologic research and provide valuable insights for future studies.