Question 6: Why might there be a difference between the population and the sample from the Framingham Study? Assuming that all these statements are true - what are possible explanations for the higher diabetes prevalence in the Framingham population? Assign the name framingham_diabetes_explanations to an array of the following explanations that are possible and consistent with the trends we observe in the data and our hypothesis test results.

1-Regarding the first question, there could be a difference since the study sample is only a group of people that make up the population, the ideal of an epidemiological study is that there are no differences between the study sample and the population, since considers that the study sample is a collection or selection of people who are more demonstrative and representative of the population to be analyzed.

2-The annualized rates of diabetes per 1,000 individuals were 2.6, 3.8, 4.7, and 3.0 (women) and 3.4, 4.5, 7.4, and 7.3 (men) in the 1970s, 1980s, 1990s, and 2000s, respectively. Compared to the 1970s, the relative risks of diabetes adjusted for age and sex were 1.37 (95% CI 0.87–2.16; P = 0.17), 1.99 (95% CI 1.30–3.03; P = 0.001) and 1.81 (95 % CI 1.16–2.82; P = 0.01) in the 1980s, 1990s, and 2000s, respectively. Compared to the 1990s, the relative risk of diabetes in the 2000s was 0.85 (95% CI 0.61 to 1.20; P = 0.36).

In these data we can see that the prevalence (different from the incidence) increases in those people who live in the United States and have bad eating habits and obesity. It is important to emphasize that he highlights the prevalence relationship between obesity and type 2 diabetes mellitus, which is strongly related to the intake of a bad diet

Explanation:

1-In real-world studies, obtaining a truly representative random sample of the population is often incredibly difficult. Even to accurately represent all Americans, a truly random sample would need to examine people across geographic, socioeconomic, and community lines. class (just name a few) .For a study like this, scientists would also need to make sure that medical examinations were standardized and consistent across different people examined. In other words, there is a tradeoff between taking a more representative random sample and the cost of collecting all the sample data. The Framingham study collected high-quality medical data from its subjects, even if the subjects may not be a perfect representation of the population of all Americans. This is a common problem they face data scientists: although l The available data is not perfect, it is the best we have.

2-The prevalence would be the risk of contracting this disease over time, different from the incidence that would be the number of new cases as time progresses, indirectly they are related ...

The population with the highest percentage of fats in their diet has a higher risk of contracting or prevailing the disease.

Adults

Explanation:

The Framingham Heart Study is a long ongoing cardiovascular cohort study of residents of the city of Framingham. The reason that could explain the difference between the population and the Framingham is the fact that only adults participated. A population is not age-restricted.

Likewise, diabetes is a disease commonly found among adults.

The Framingham Heart Study was famous for coming up with the term risk factor and showed that a healthy diet, regular exercise and so on, can lower the risk factor of heart diseases.

thomas jefferson

explanation: