Prevalence is defined as a measure which enables the determination of the chances of a person getting a particular disease. As such, the number of cases of disease present among people is the number of prevalent cases. To calculate the rate of prevalence, the overall number of cases of a disease present among people is divided by the total population (Walters, 2012).

Point Prevalence=Number of Cases in a defined population at one point in time

Number of persons in a defined population at the same point in timePrevalence is a valuable tool especially when it comes to the quantification of the number of cases of a disease in a certain period. It also helps in the planning of health services since it can be used in the calculation and evaluation of prevalence and likelihood of disease contraction across different geographic areas or in different and diverse groups of people in the whole population. However, prevalence cannot be efficiently and effectively used in establishing the causes of that particular disease (Miquel, 2014).

Example: Supposing there are 5000 male residents in a particular town and 500 of them have cancer, prevalence of cancer in that area will be:

5005000 = 0.1, then the result is multiplied by 100 to make it a percentage, therefore the rate is 10%.

Identify a Disease that Has a High Prevalence Rate But a Low Incidence Rate and a Disease that Has a High Incidence Rate But a Low Prevalence Rate. What Characteristic about these Diseases Creates this Interrelationship?

There are certain diseases which have a high prevalence rate, but the incidence rate is relatively low. An example of such a disease is tuberculosis. One of the major characteristics of such diseases is that the period of recovery is very long or the time is taken before the patient person passes away is relatively longer (Walters, 2012). These diseases persist for a very long duration of time; some even take years, and, as such, the rate of prevalence is greater compared to the rate of incidence.

There are also other diseases which have a high incidence rate, but the rate of prevalence is way much lower. Most of these diseases are severe and occur suddenly. Some examples of such diseases include acute leukemia, colds, bronchitis, and diarrhea. These diseases do not last for a long duration of time while their incidence rates are usually high. Consequently, the incidence rate, when compared to the prevalence rate, is higher.

There are several factors which lead to the increase in the rate of prevalence. One such factor is when there is a change in the period of a certain illness; this could be because of the discovery of a treatment method that does not lead to its cure but stops the immediate death of the patient. This will result in high prevalence rates. Malignant and deadly diseases whose recovery period is low tend to have low rates of prevalence. However, for diseases which do not have any cure but are not fatal, will have high rates of prevalence whereas the incidence rates will be low (Dunn et al. 2009).

Define and Give the Formula for an Odds Ratio

Odds ratio (OR) can be defined as the odds of diseases in people who have been exposed divided by the odds among people who have not been exposed. An odds ratio can also be defined as a measure of association between the exposure levels and the outcome (Dunn et al. 2009). Odds ratios are mostly applied in case-control studies. In other instances, they are used in cohort study designs but there are some alterations and assumptions that have to be made. Odds ratio as also applied in Meta-analysis and in logistic regression analysis.

When the odds ratio is equal to one, then the exposure levels will not have any effect on the odds of the outcome. When the odds ratio is greater than one, the levels of exposure will be associated with relatively greater odds of outcome. Lastly, when the odds ratio is less that one, the exposure levels will be associated with relatively lower odds of outcome.

The formula for the calculation of OR is

OR=a/cb/d=adbcA represents the number of exposes cases

B represents the number of exposed non-cases

C represents the number of unexposed cases

D represents the number of unexposed non-cases

Complete the 2 x 2 table below and calculate the Odds Ratio: There were 120 total with lung cancer of which 20 were not exposed to tobacco smoke; 250 total without lung cancer of which 75 were exposed to tobacco smoke. Show your work.

Cases Controls Total

Exposed A b a+b

Unexposed C d C+d

Total A+c B+d A+b+c+d

Cases (ill) Controls (not ill)

Exposed to tobacco smoke Yes 100 75

Unexposed to tobacco smoke No 20 175

A=100

B=75

C=20

D=175

OR = (a/c) /(b/d)

= (ad)/ (b/c)

= (100175) (7520)

= (17500) (1500)

= 11. 67

5) Interpret the odds ratio / what does this finding mean

From the findings above, we can conclude that those who were exposed to tobacco smoke (exposure) were 11.7 times more likely to be ill (outcome), when compared to those who were not exposed to tobacco smoke. The more a person is exposed to the tobacco smoke, the higher the chances of developing the disease.

Â

References

Dunn, Olive Jean and Clark, Virginia A. (2009). Basic statistics: a primer for the biomedical sciences (4th ed.). Hoboken, N.J.: John Wiley & Sons. pp. 35

Walters RW, Kier KL. (2012) .The Application of Statistical Analysis in the Biomedical Sciences. In: Kier KL, Malone PM, Stanovich JE, eds. Drug Information: A Guide for Pharmacists. 4th ed. New York: McGraw-Hill.

Miquel Porta (2014). A Dictionary of Epidemiology (6th ed.). New York: Oxford University Press

Request Removal

If you are the original author of this essay and no longer wish to have it published on the collegeessaywriter.net website, please click below to request its removal:

- Questions on Senior Clinical Practicum - Paper Example
- Cancer Diagnosis and Staging - A Medicine Essay Example
- Definition Incidence, and Prevalence of Maturity Onset Diabetes of Young (MODY)
- Essay on Career in Physical Therapy
- Discussion Questions on Hypothesis Tests - Essay Sample
- Usage of Osteoconductive Graft Materials During Immediate Implant Placement Procedures - Paper Example
- Paper Example on Demographics and Statistics