Introduction to Epidemiology Ashford University Text:Friis, R. H. and Sellers, T. A. (2014). Epidemiology for public health practice.
Imagine that you are an epidemiologist and learned of the misconception that your classmate posted about. Examine the steps that you would take to disprove that assumption.
Explain how you would communicate the new information to disprove the misconception to the public. Your post should be at least 150 words.
Nettye Johnson One of the seven uses of epidemiology is the search for causes for disease (Friis, 2014). An initial step in determining cause is to identify valid associations between exposure and outcome ("What is a Cause?", 2016).
While research can identify and quantify associations, (i.e., show that the exposure and outcome are related), the next step to show cause is more challenging. Kenneth Rothman (2012) defines cause in epidemiology as an "event, condition, or characteristic without which the disease would not have occurred".
Association and causation are not synonymous. Association does not necessarily mean causation, yet history shows this assumption is repeatedly, mistakenly and mistakenly made. The assertion that ice cream causes polio is an example. Present an argument for why ice cream does cause polio and should be banned Dr. Benjamin Sandler studied rates of polio in the 1940s, and he noted an increased rate of polio in children during the summer. Dr. Sandler also observed that consumption of ice cream also increased during the summer.
The correlation between high intake of sugar and increased susceptibility to the polio virus was further substantiated by Dr. Sandler in his study of poliomyelitis in rabbits during insulin hypoglycemia (Sander, 1941). This data indicates that high sugar intake increase risk for polio. To protect the health of children from this disease; it follows that ice cream should be banned. Explain how ideas like that spread, and why people make such assumptions.
Faulty causal relationships like these spread easily because they are based upon data that is misinterpreted. Statistics and epidemiology are detailed and complex fields that the general population does not fully understand. Those who believe a causal relationship exists based upon an association between an exposure and an outcome can inappropriately use and present data of the association as proof of cause.
Those without an understanding of the epidemiology and statistics believe what is presented. Ideas like this also spread because people have an innate desire to see cause and effect. We like clear-cut answers to complex questions and having an answer - even if it is a wrong or incomplete answer brings a bit of comfort.
Provide another real example of a misconception. Another example of a wrong causal relationship can be observed in the historical belief that African Americans health disparities was due to genetic inferiority. Post-slavery health status for African Americans was far below the health status of other races.
Many at the time held the belief that the poor health condition of African Americans was due to genetics.
What is cause?
Cause and Effect. The Little Handbook of Statistical Practice.
Epidemiology for Public Health Practice. Burlington, MA: Jones and Bartlett Learning. Rothman, K. (2012). Epidemiology.
New York, NY: Oxford University Press. Sandler, B. P. (1941). The production of neuronal injury and necrosis with the virus of poliomyelitis in rabbits during insulin hypoglycemia.
The American Journal of Pathology, 17(1), 69-80.5.