Can Cross-Sectional Studies Contribute to Causal Inference? It Depends - Savitz, David A; Wellenius, Gregory A (American journal of epidemiology, 2023)
Cross-sectional studies-often defined as those in which exposure and outcome are assessed at the same point in time-are frequently viewed as minimally informative for causal inference. While cross-sectional studies may be susceptible to reverse causality, may be limited to assessment of disease prevalence rather than incidence, or may only provide estimates of current rather than past exposures, not all cross-sectional studies suffer these limitations. Moreover, none of these concerns are unique to or inherent in the structure of a cross-sectional study. Regardless of when exposure and disease were ascertained relative to one another, a cross-sectional study may provide insights into the causal effects of exposure on disease incidence. Simply labeling a study as "cross-sectional" and assuming that 1 or more of these limitations exist and are materially important fails to recognize the need for a more nuanced assessment and risks discarding evidence that may be useful in assessing causal relationships.