In a cross-sectional survey, a significant association is found between high waist circumference and Type 2 diabetes. The MOST important limitation in inferring causality from this study is:
- A The study cannot establish temporal sequence (which came first) ✓
- B Cross-sectional studies cannot calculate prevalence
- C Selection bias is higher in cross-sectional than cohort studies
- D Cross-sectional studies always underestimate true disease prevalence
Explanation
The fundamental limitation of cross-sectional studies for causal inference is the inability to establish temporal sequence (temporality is a Bradford Hill criterion for causation). Since exposure and disease are measured simultaneously, it cannot be determined whether high waist circumference preceded diabetes or vice versa (reverse causation). Cross-sectional studies CAN calculate prevalence (that is their primary purpose). They are subject to Neyman (prevalence-incidence) bias, not necessarily more selection bias than cohorts. Their inability to determine temporality makes them hypothesis-generating rather than causal-proving designs.
Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.
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