Association and Causation
Description
Differentiate between association and causation using the causal guidelines. Discuss which
of the guidelines you think is the most difficult to establish. Discuss the four types of causal
relationships and use an example not listed in the textbook to describe each relationship.
Association and Causation
Epidemiologically, the cause-effect relationship is based on two distinct factors, association, and
causation, which follow the causal guidelines in assessing the source of different illnesses. Most
fundamentally, before making inferences to the existence of a cause-effect relationship, the two
factors provide different explanations for an observed association. Firstly, association describes
the connection between variables such as the exposure to disease and the possible outcome likely
to occur as a result of the effects of bias, chance, reverse or true causality, and the confounding
factors in the study (Glazier, 2018). Conversely, causation differs from causation by the fact it
entails the changes that occur in one of the variables mentioned above due to alteration in the
other. Similarly, the difference between the factors entails the fact that some of the measures
outlined in the causal guidelines cannot be applied in the determination of the changes that occur
among subjects as that would make it unethical (Glazier, 2018). As such, the experimentation
process is one of the causal guidelines I consider the most difficult to establish as it necessitates
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the annihilation of the exposure to a disease, thereby leading to significant changes in the
frequency of the possible outcome.
Nonetheless, there are four types of causal relationships that include the necessary by
sufficient, necessary but not sufficient, sufficient but not necessary, and neither sufficient nor
necessary category. The necessary but sufficient relationship refers to the occurrence of a disease
based on the causative factor and exposure to it culminates in the affirmation of the first premise
(Glazier, 2018). For instance, the spread of disease within a community increase the exposure
rate among numerous people due to various risk factors. However, among the population, there a
few people remain immune due to variables such as low infectivity rate. Similarly, the necessary
but not sufficient relationship involves the occurrence of a disease based on various factors that
occur in temporal sequence. For instance, the occurrence of diseases such as type 2 diabetes is
based on the existence of necessary factors such as a family history of its prevalence.
Nevertheless, the presence of such factors may not suffice the outcome of the condition in all
individuals.
The third type of relationship, sufficient but not necessary, refers to the correlation
between specific factors that lead to the development of an illness and other elements (risk
factors) associated with its occurrence and prevalence. For instance, the occurrence of diabetes is
associated with specific factors such as obesity, but other risk factors such as a family history of
its prevalence may lead to its development among individuals. Lastly, neither sufficient nor
necessary relationship describes a combination of risk factors that lead to the development of a
particular disease (Glazier, 2018). However, the condition may occur in the absence of these risk
factors. For instance, the development of cardiac disorders is associated with various risk factors.
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References
Glazier, R. H. (2018). Association versus causation. Canadian Medical Association
Journal, 190(28), E863-E863.