The complexity arises from the multifaceted nature of health and disease. Here are some of the key reasons:
Multifactorial Causation: Diseases are often the result of multiple risk factors interacting in various ways. For example, cardiovascular disease is influenced by genetics, lifestyle, and environmental factors. Temporal Relationships: Establishing a temporal relationship between exposure and outcome can be challenging. Long latency periods and retrospective data collection can complicate this process. Confounding Variables:Confounding variables are other factors that may distort the true relationship between the exposure and outcome. Identifying and adjusting for these confounders require sophisticated statistical methods.
