Final answer:
A cross-sectional study cannot determine causation due to the lack of temporality that is necessary to establish that a cause precedes an effect. They are also susceptible to confounding, where other variables may influence the observed association.
Step-by-step explanation:
A cross-sectional study is a type of observational study where data is gathered from a population at a single point in time. This design's main shortcoming is the lack of temporality in the data, meaning that the timing of the outcomes and exposures are not clear, rendering it inadequate for determining causation. Without temporality, it is impossible to conclude whether exposure to a certain risk factor preceded the outcome or not. This is critical in establishing causation, as the cause must precede the effect.
Additionally, cross-sectional studies are vulnerable to confounding, where external variables may affect the studied variables, giving a false impression of a relationship. While such studies are useful in identifying possible associations for further investigation, they cannot, by themselves, establish causality due to these limitations.
For instance, if a cross-sectional study observes that people who smoked have higher rates of lung cancer than those who do not, it can suggest a correlation, but cannot establish that smoking causes lung cancer because other factors, such as genetics or environmental exposure, may also be at play.