A cross-sectional study measures both exposure and outcome at the same point in time. The major limitation of this design for causal inference is:

• A It cannot measure prevalence
• B It always overestimates the prevalence of chronic diseases
• C It cannot be used for rare diseases due to low power
• D Temporal relationship between exposure and outcome cannot be established ✓

Explanation

The primary limitation of cross-sectional studies for causal inference is the inability to establish temporal sequence (whether exposure preceded outcome). Since both are measured simultaneously, it is impossible to determine if the exposure preceded or followed the disease. This is the fundamental criterion of causality. Additionally, prevalent cases in cross-sectional studies may have changed their exposure after diagnosis (reverse causality).

Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.

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