Causal Criteria Report - Analyzing Causal Criteria in Public Health

This report delves into the realm of causal criteria within public health, examining the fundamental concepts of association and causation. The report begins by outlining the nine causal criteria as defined by Hill (1965), including strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy. Subsequently, the report differentiates between the need for statistical evidence and the substantial association in epidemiology, highlighting the reliance on observational data. Furthermore, it discusses the significance of the causal pie model by Dr. Rothman, contrasting it with the Bradford Hill criteria and elucidating how both frameworks contribute to understanding cause-and-effect relationships based on observational evidence. The analysis underscores the importance of these criteria in evaluating the factors that determine the relationship between cause and effect in public health contexts.

Running head: CAUSAL CRITERIA
CAUSAL CRITERIA
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Author Note

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CAUSAL CRITERIA
PART 1
According to Hill (1965), there are 9 causal criteria present which would be defined in
the following section:
Strength: The apparent amount of the effect associated with the cause would be defined
as the strength of the association. This factor can be measured by the comparison between the
samples with and without the cause.
Consistency: The association between the cause and the effect would be observed by
several techniques in different situations and this is known as the consistency of association.
Specificity: This phenomenon refers to the specificity of the association only with one
causal effect or to several putative causes.
Temporality: The putative cause would be seen with temporary effects over the
association and this is the term refers to that situation.
Biological Gradient: The gradient refers to the relation between the dose of the cause and
the response level of the association towards the cause as well.
Plausibility: This is the phenomenon of the conceptual and sensible biological
explanation that explains the causal effect on an association.
Coherence: This is the phenomenon that refers to the supportive evidences for the cause-
effect relation and the evidences would be known facts or the laboratory evidences.
Experiment: Results of experiments that support the cause-effect relation and this would
be used in the experimental manipulation of the causes.
Analogy: This is the phenomenon that would be referring to the argument of the cause-
effect relation.

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PART 2
A) Substantial association is an observation based explanation of the epidemiological field
and there is no need of the experimental evidences for this aspect. Thus it can clearly be
seen that the evidences of the association in epidemiology are dependent on the
observation only. Thus the statistical significance would not be associated in this context
and these experimental evidences should not be mistaken as the evidence for the
substantial association. According to Phillips and Goodman (2004), the context of the
substantial epidemiology is solely dependent on the physical observations and this is the
field of the relationship determinant of the cause and the association. Thus the need of
statistical evidences is likely to be nil in this context and the comparison between the
observation data are the primary evidence on this field.
B) According to Dr. Rothman causal pie model is the model which depicts and
conceptualises the causality factor. Causal pie leads to the outcome on the basis of the
sufficient cause and component cause. However, on the basis of Dr. Rothman’s view life
depends on causes and every single aspect needs a cause. On this view it can be said that
the causal pie model would be able to determine causes and the effects of the causes as
well. On the other hand According to Hill (1965), the causal criteria are the factors that
determine the cause and effect relation thus the relation between the causal pie and the
causal criteria of Bradford Hill is significant and that can be seen as both determine the
cause-effect relationship in the concept of the observational evidences.

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References
Hill, A. B. (1965). The environment and disease: association or causation?. Retrieved from
https://journals.sagepub.com/doi/pdf/10.1177/003591576505800503
Phillips, C. V., & Goodman, K. J. (2004). The missed lessons of sir Austin Bradford Hill.
Epidemiologic Perspectives & Innovations, 1(1), 3. doi:10.1186/1742-5573-1-3