Cross-sectional studies
Cross-sectional studies differ from cohort studies and case-control analyses in that they do not follow individuals over time but instead are based on individual-level data from a given point in time.1,9 While cross-sectional studies have inherent limitations, they may be used to identify potential associations or estimate prevalence.
A study of recent cannabis use and history of myocardial infarction (MI) provides an example of a cross-sectional analysis.23 The study was based on survey data on young adults from the American Behavioral Risk Factor Surveillance System. In this study, exposure reflected survey responses on whether a respondent had used cannabis in the 30 days prior to the survey, and the outcome reflected whether a respondent reported that they had ever been told by a health professional they had experienced a heart attack. The study found a potential association between cannabis use and myocardial infarction (adjusted odds ratio 2.07, 95% confidence interval 1.12 to 3.82).
One limitation of cross-sectional studies is that it is often difficult to determine the time order of events, which undermines inference about causality.9 This is reflected in the study just mentioned, which could not determine whether an individual’s cannabis use preceded an MI.23 If an association is observed between an exposure and disease in a cross-sectional study, it may represent an association with survival after the onset of a disease rather than with developing a disease.10 When used to estimate prevalence, cross-sectional studies are subject to the limitation that they will “overrepresent cases with long duration and underrepresent those with a short duration of illness.”9