Respond to classmate

Choose one of the causality models in Chapter 9 of the textbook and use it to explain the relationships between the risk factors associated with the leading cause of death you selected in Module Four and the outcome (death from that cause). How do Hill’s criteria for causation apply to these relationships? Remember to cite references where necessary. When responding to your classmates, suggest and discuss other possible factors that could be included in their chosen models.

Response # 1

For this module, I will be utilizing the disease discussed in module four, Alzheimer’s Disease.  While the exact cause of Alzheimer’s Disease is unknown, “scientists believe that many factors influence when Alzheimer’s Disease begins and how it progresses” (What Causes Alzheimer’s Disease, 2017).  Aging appears to be the most known and important factor in the risk of Alzheimer’s Disease.  According to the National Institute on Aging, with every five years past the age of 65, a person’s likelihood of developing Alzheimer’s doubles; and of the population of people over the age of 85, about one-third may already have Alzheimer’s Disease (What Causes Alzheimer’s Disease, 2017).  The contributing factors are: age, genes (genetics), shrinking or atrophy of certain parts of the brain, inflammation, free radicals, a breakdown of the energy produced within the cells of the brain, and environmental factors (What causes Alzheimer’s Disease, 2017).  Rothman and Greenland have created a Pie Model for disease causation, showing the “relationships between suspected disease-causing factors and outcomes” (Friis & Sellers, 2014, p. 425).  The Pie Model “indicates that a disease may be caused by more than one causal mechanism (also called a sufficient cause), which is defined as a set of minimal conditions and events that inevitably produce disease” (Friis & Sellers, 2014, p. 429).  As the text describes, each letter in the pie indicates a single component cause and diseases can be caused by multiple causal mechanisms, and each of these mechanisms work together.  The letter A in the pie will be the single component that can/is common to all the causal mechanisms; in this case A represents age or aging.  The other factors (causal mechanisms) are listed in the charts below with aging as the common component.  In a causal pie, if all component causes are present, sufficient cause is present and the outcome will occur (Wensink, Westendorp, & Baudisch, 2014).

As previously mentioned in module four, Alzheimer’s Disease is the sixth leading cause of death in the United States (Alzheimer’s Disease, 2016).  In 2016, 116,103 deaths occurred due to this disease (Alzheimer’s Disease, 2016).  Because of the environmental factors that have been shown to be a cause for Alzheimer’s Disease, one can apply Sir Austin Bradford Hill’s viewpoints, otherwise known as the Bradford Hill Criteria.  Many advances in technology such as computers and statistics as well as various scientific fields like genetics and genomics have allowed researchers to look at exposure to disease (Fedak, Bernal, Capshaw, & Gross, 2015).  This has allowed epidemiologists to establish causality beyond study designs that were completed when Hill wrote about his criteria 50 years ago (Fedak, Bernal, Capshaw, & Gross, 2015); now over 50 years ago.  The aspects that Hill addressed in his criteria are: strength of association, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy (Fedak, Bernal, Capshaw, & Gross, 2015). While Alzheimer’s is associated with vascular conditions, such as heart disease, stroke, and high blood pressure as well as some metabolic conditions like diabetes and obesity; there is a “great deal of interest” in this area but there is not a strong association (strength of association) between these diseases and Alzheimer’s (What Causes Alzheimer’s Disease, 2017).  When looking at another criterion, such as specificity, these associated conditions do not cause only one disease.  “In modern contexts, experimentation must consider that many diseases result from multifaceted exposures and follow complex progression pathways” (Fedak, Bernal, Capshaw, & Gross, 2015).  And, analogy can be utilized in this disease with age and the associated factors that are thought to be causes of Alzheimer’s; meaning, “that when one causal agent is known, the standards of evidence are lowered for a second causal agent that is similar in some way” (Fedak, Bernal, Capshaw, & Gross, 2015). 

            

 

Below, I have created some pie models that I think would represent samples of what pie models might look like for Alzheimer’s Disease. These are not based on fact. 

Response # 2

Several models of disease causation help researchers understand the disease process.  The web model of causation explores multiple causative factors of diseases. According to the web of causation model, there is no single cause for diseases; instead, various interconnected, interacting factors cause diseases. The web model is just symbolic and used to represent the idea that causal pathways of diseases, especially chronic diseases, are multiple, complex, and tie with each other.

 

Let's consider diabetes, the seventh leading cause of death in the United States. Diabetes is well defined from a clinical standpoint (A1C equal or greater than 6.5 OR a fasting plasma glucose equal or greater than 126 );  however, the etiology of diabetes is complicated. Genetics, age, sedentary lifestyle, diet, weight, place of residence, level of education, and socioeconomic status are some of the known risk factors associated with type 2 diabetes (NIDDK, 2019; CDC, 2017). Using the Web model explanation, diabetes results from the interaction of these multiple behavioral, environmental, and genetic to factors.

 

 

 

Bradford Hill's developed nine criteria that can be used to establish epidemiologic evidence of a causal association between a presumed cause and an observed effect. According to Hill, the strength of association; consistency; specificity; temporality; biological gradient; plausibility; coherence; experiment; and analogy can be used to evaluate hypothesized relationships between exposures ( to risk factors) and disease outcomes. For obesity, a modifiable risk factor for type 2 diabetes, most of Hill's criteria can be applied as follows:

· Strength- Obesity has been highly associated with diabetes. According to a Harvard report, about 30 percent of overweight individuals have type 2 disease, and 85 percent of diabetes patients are overweight.

· Consistency- Numerous research has shown that body mass index has a strong relationship with diabetes and insulin resistance (Al-Gobal et al., 2014).

· Specificity-Obesity is not specific to diabetes alone; but has also been associated with other health conditions such as heart disease, high cholesterol, respiratory, and musculoskeletal diseases. 

· Temporal sequence- In most patients with type 2 diabetes, obesity usually precedes diabetes.

· Dose-response-Studies have shown that higher BMI levels are associated with an increased risk of diabetes.

· Experimental evidence- Observational studies have correlated obesity with diabetes.

· Biological plausibility-Clinical studies have shown that obesity produces increased levels of inflammation and fatty- acids, leading to insulin resistance, which subsequently can cause to type 2 diabetes.

· Coherence- The cause (obesity)-and-effect (diabetes) relationship is not in conflict with the generally accepted facts about the etiology of diabetes.

· Analogy- There have been similarities between the observed association of obesity and diabetes and other health conditions.