Epidemiology and Population Health – Health System Example

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"Epidemiology and Population Health" is a great example of a paper on the health system. In January 2001, 4,500 men aged 45-54 years joined a new health insurance plan and were offered a free health check, 1000 of the men were found to be overweight or obese. Ten years later the men were checked again and 700 men who were normal weight in 2001 were now overweight or obese, while 200 of those who were overweight or obese in 2001 had lost weight and were now in the normal range. a) What was the prevalence of overweight and obesity in the group of men in (i)January 2001?

(ii) January 2011? (i) Prevalence= a/(a+b)  i.e  prevalence=  1000/4500 = 0.222 (ii)  January 2011, prevalence= 1500/4500 =0.333b) What was the incidence of overweight/ obesity in this group over the 10 years? The incidence proportion is 700 per 2500 persons. i.e (700/2500)*100= 28% Incident rate = 70 per 2500 persons i. e  (70/2500)*100= 2.8%c) What was the incidence of weight loss among overweight/obese men? The incident proportion is 200 per 1000 persons i. e    (200/1000)*100= 20% Incident rate is 20 persons per 1000 persons i. e  (20/1000)*100= 2%   Question 2  In a Cape York community with a population of 31,357 (male: female ratio= 49:51), at the beginning of 2003, there were 5,908 female types II diabetics and 4,093 male type II diabetics.

At the beginning of 2005, there were an additional 504 female type 2 diabetics and an additional 313 male type II diabetics. a) What was the sex-specific prevalence of type II diabetes in the community? At the beginning of 2003: male= 4093/15365= 0.27% female =5908/15922 =0.37%b) What is the most appropriate measure of disease rate in this scenario?

Provide your reason(s). Pedigree risk assessment is the most appropriate since the question involves two independent events. c) What were the risks (an ie measure of disease identified in part b) of type II diabetes in different gender groups in the community (Please calculate the risks among males and females). Probability of type II diabetes in: Male is (1/2)*(49/100) = 49/200 Female is (1/2)*(51/100) =51/200 Male and female together = (49/200)*(51/200) = 2499/40000   Question 3  A) High cholesterol levels: 45 out of 6000=0.0075 Low cholesterol levels: 100 out of 4000=0.025 Rate= sick /total*100               = 145/10000*100= 1.45%B) =0.0075 Chances of a high cholesterol patient to be having a heart attack is higher than the person who has low cholesterol.

This is because, for every forty people with high cholesterol, three of them have heart attacks. On the other hand, for every forty people with low cholesterol one of them has a problem of a heart attack. C) High cholesterol 6000/40=150heart attacks     Low cholesterol 4000/40=100heart attacks     Total 250heart attacks Without high cholesterol 10000/40=250heart attacks in this context, it means that the total number of people suffering from a heart attack would be the same even without people with high cholesterol. Question 4    In a case-control study looking at the relationship between having freckles and risk of melanoma, 136 of 183 cases and 61 of 183 controls had freckles. If you have freckles how much more likely are you to develop melanoma than someone who does not have freckles?

(Please draw up a 2x2 table and show working out in your answer) (4 marks) 136 183 61 183   136-61/183=75/183   Question 5  The most applicable epidemiological study design for quality of life from a random telephone directory is an Ecological study. This is because the results that come out do not reflect on individual quality of life.

The study involves group analysis thus not narrowing down to the individual level of life. The study deals with other factors that make life comfortable. It is not possible to identify the cause of good or bad quality of life for individuals. Case-control study. A case-control study can be used to determine the cause of long-term disease, for example, cancer. This study can help in decision-making whether cancer can be reduced by taking in vitamin E. The other reason is that the case study deals with individuals who have either suffered from the disease or not.

Therefore it gives chance to individuals to give their own experience before testing. This allows first-hand information to reach the researchers.       Question 6 The research question is “ does estrogen replacement treatment protect against death due to stroke? Several study factors were used in the study. They are as follows; age, gender, and use of or lack of use of estrogen by participants. The findings indicate that estrogen protects women against death due to stroke. The study factor is directly linked to the results.

During the study, it was found that twenty women who used estrogen died out of the total number of 4962. On the other hand, forty-three women died out of 3845. Basing on this, it is true to say that women who used estrogen have greater protection against stroke than those who did not use estrogen. There is a great business that exists in the study. First, the young girls were treated differently from the other group of participants. This was done by adjustment in other areas just because of the confounding factors.

It is unfair to carry out research then give preference to a specific group and leave the other. Automatically it brings changes if the young girls could have been treated the same as other women. The other business comes in the sense that 34 members of the group did not have any knowledge on estrogen use. This is a critical issue in an experiment since all the members should be aware of the underlying concepts. There could be great changes in the results if this group had information on estrogen use. There are several confounding factors that were identified by the author.

For instance, the author makes it clear that young girls received special attention due to the following; smoking, hypertension, exercise, and mass index. It really affected the results since the number of girls who were not included in most of the computations. The results findings from a statistical point of view indicate significant differences in mortality rate. At 95% CI, the effect of HRT on death from stroke was calculated to be 0.31. although the results were not affected by hypertension, BMI, smoking, and exercise, all the above factors have an effect on mortality.      

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