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Summary study book Clinical Epidemiology of Grant S. Fletcher - ISBN: 9781975140984, Edition: Sixth, International Edition, Year of publication: - (Epidemiology)

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  • October 30, 2021
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  • 2021/2022
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Week 4: Association and Causation in Epidemiology




Learning Objectives:

Description of the Bradford Hill Causation Criteria

Critical Evaluation of Significance and Application of the Bradford Hill Criteria in

Contemporary Epidemiology

Interpretation of Cause Effect Relationships


Contents
Introduction ............................................................................................................................................ 1
Introduction to the Bradford-Hill criteria ............................................................................................... 3
Strength of Association ....................................................................................................................... 4
Consistency of data ............................................................................................................................. 5
Specificity ............................................................................................................................................ 5
Temporality ......................................................................................................................................... 5
Dose-response .................................................................................................................................... 6
Biological plausibility........................................................................................................................... 6
Coherence ........................................................................................................................................... 6
Experimental evidence........................................................................................................................ 7
Analogy ............................................................................................................................................... 7
Critical evaluation of the Bradford Hill criteria ....................................................................................... 7
Practical example of the Bradford-Hill criteria ..................................................................................... 10
References ............................................................................................................................................ 11



Introduction
Cause and effect is often the next step in science, after a discovery of patterns or events that

occur together with regularity. A search for the underlying cause of a phenomenon has sparked

some of the most compelling and productive scientific investigations. Any hypothesis that A

causes B requires an explanation mechanism for the chain of interactions that connect A and
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, B. For example, the notion that diseases can be transmitted by a person’s touch was initially

treated with scepticism. Today it is well understood that infectious diseases can be transmitted

by the passing of bacteria or viruses between an infected person and another (San Diego County

Office of Education 2020). A principal aim of epidemiology is to uncover such causal

connections, often with the hope that understanding the mechanisms will enable predictions

and the design of preventive measures and treatments.

We have seen in Weeks 2 and 3 that epidemiological studies either observational or

experimental examine association between exposure and outcome.

Experimental studies are rarely available because it is neither ethical nor practical to design

experimental study to examine, for instance, the following associations as the outcome

measure: harms caused by environmental exposure to chemicals (e.g. carcinogenicity of

quinolone) or assessing harms caused by infectious diseases (e.g. assessing the teratogenicity

of Zika) (Wiliamson 2018).

On the other hand, most epidemiological studies are by nature observational, and, as we have

already seen, they apply estimates of association such as: prevalence for cross- sectional

studies, the odds ratio for case- control studies and incidence rate and relative risk for cohort

studies. However, because observational studies involve no control or manipulation, i.e. do not

interfere into uncontrolled conditions of everyday real-life, a number of possible explanations

for an observed (and estimated) association need to be carefully considered before one can

infer a cause-effect relationship. As such, an advantage of observational design is that people

can be observed in their natural environment, however the drawback is that it is usually difficult

to untangle the often complex situation where exposure can be difficult to define (e.g. air

pollution, socioeconomic status or duration and frequency of an exposure etc.) as well as to




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