Answer:
a. Variables interact resulting in higher probability of illness.
Explanation:
Causality is the relationship between an event A (the cause) and a second event B (the effect), provided that the second event is a consequence of the first. Causality is logically identified in "if not A, then not B", provided the empirical occurrence of at least one B. The above expression is not strictly equivalent to the expression "if A then B", but this is not that the one usually linked in common sense to the concept of causality. Many causal models are used to explain phenomena, whether in science or common sense. In biological sciences, the use of chance models asserts that variables interact resulting in a higher probability of a disease.