Epidemiology And Prospective Observational Study: An Analysis

Prospective Observational Study Design

Discuss about the Epidemiology and Prospective Observational.

The study design used in this study is prospective observational study. In this design, the author observed the nurses’ feeding patterns with relation to the risk of getting the type 2 diabetes mellitus (McKeown et al., 2002). The researcher then collected the information for a period of ten years using a detailed questionnaire with no influence to them. The use of this design enables the observation of some rare exposures to health since a researcher is able to identify a subject who developed a disease at some point. It is also possible to calculate the incidence of a disease which has been exposed to the subjects.

The crude incidence rate is the number of new cases of diabetes mellitus that occurred in one year per one hundred thousand nurses under investigation. Therefore the incidence is arrived at by counting the number of new cases, divides by the total population under study and multiplied by one hundred thousand.

Incidence rates for total grain

Percentiles Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	Counts	Population	Crude rate
1	392	144,698	270.9
2	356	144,403	246.5
3	368	144,438	254.8
4	358	144,471	247.8
5	405	144,409	280.5

Incidence rates for whole grain

Percentiles	Counts	Population	Crude rate
1	426	144,914	2934.0
2	391	147,351	265.4
3	407	143,856	282.9
4	320	145,133	220.5
5	335	144,164	232.4

Incidence rates for refined grain

Percentiles	Counts	Population	Crude rate
1	349	144,742	241.1
2	369	144,817	254.8
3	337	144,095	233.9
4	378	144,252	262.0
5	446	144,512	308.6

These results indicate that the crude rates were not consistent with the quintiles of meal consumption.

Percentiles	Counts	Population	Crude rate
1	349	144,742	0.0024
2	369	144,817	0.0025
3	337	144,095	0.0023
4	378	144,252	0.0026
5	446	144,512	0.0031

The relative ratio of diabetes mellitus reduces with increasing quintile of whole grain. This means that the higher the amount of consumed whole grain, the lower the likelihood of diabetes mellitus type 2 occurring (de Munter et al., 2007). The physical form of the whole grain as well as its high content of the fibers makes them to be digested slowly. Moreover, the low rate of whole grains absorption makes it to have low glycemic levels. The consumption of foods which have low levels of glycemia is linked to low glycosylates hemoglobin excretion. The finely ground fibers cannot produce glucose response to the postprandial blood.

The adjustment of other factors were meant to determine whether there were other factors apart from the composition of meals that were linked to type 2 diabetes. Physical activity for instance is linked to a reduction of the blood glucose levels. This is because during exercises, the muscles use glucose in blood to derive energy. In case an individual is resistant to insulin, physical activities lower the resistance making cells to take up glucose effectively (He et al., 2010). Family history is also linked to diabetes as a result of inheritance of genes for diabetes type 2. Smoking causes damage to the blood vessels complicating the diabetes.

Incidence Rates for Different Grain Types

The biasness in this diabetes type 2 studies among the nurses is the assumption that nurses are closer to the medical care and hence access to treatments. In some instances, the nurses offer services to the patients such that they do not remember that they too need medical services (Egger and Smith, 1998). Moreover, the nurses may have the fear of being stigmatized by their colleagues and escape treatment or diagnosis. The association of diabetes type 2 with other factors apart from the whole grain meal does not have a clear cut line. The study did not include males to determine the effect of gender differences to type 2 diabetes (Fung et al., 2002).

Fat intake	Control	Study cases
High	100	80
Moderate	270	270
Low	130	150

For the control and study groups, there was low number of skin cancer cases i.e. 100 and 80 respectively. On the other hand, for the control and study groups the low fat intake there were high number of skin cancer cases i.e. 130 and 150 respectively. However, moderate intake of fats resulted had similar number of skin cancers of 270. The low number of skin cancer in high fats intake is because the fats raise the prostaglandin E2 levels which function as T cell function immunoregulators and in turn lower the ultraviolet related skin cancers.

Relative risk= the number of subject with a positive or bad outcome divided by the sum of the number of subject with bad and good outcomes in the case study. This figure obtained is then divided by the number of subjects with a positive or bad outcome divided by the sum of the number of subject with bad and good outcomes in the control group.

150/230 divided by 130/230

=0.65/0.57

Relative risk=1.14

This means that the people who take fats in low levels would be approximately 1.14 more times likely to develop skin cancer as compared to those who take high fat levels.

Relative risk=1.3

This means that the people who take fats in moderate levels would be approximately 1.30 more times likely to develop skin cancer as compared to those who take high fat levels (Prochaska et al., 2005).

The association between the parenchymal cells and low fats intake is that low fats intake increases the risk of skin cancer (Black et al., 1995). On the other hand, high fats intake leads to oxidative stress and increase in the number of cytokines responsible for inflammation while at the same time reducing the death of skin cells via apoptosis.

Relative Risk Calculation

The exposure to low fats leads to melanoma because the skin cells are not able to counter the effects of oxidative damage. In the long run the skin cells begin dividing uncontrollably leading to the cancer of the skin.

There is no association between rare exposure and development of a disease. This is because there when there is a rare exposure, sixty people develop the disease while one hundred and eighty of them do not. On the other hand when there is no exposure, the same effect is observed as when there is a rare exposure.

Relative risk in younger adults

30/30+90 divided by 40/40+80

= 0.76

Relative risk in older adults

40/120 divided by 30/120

=1.32

The relative risk of 0.76 observed in the younger adult’s means that the people who are exposed to a disease are about 0.76 times less likely to develop a disease as compared to those who have been exposed. The relative ratio of 1.32 in the older adults indicates that the older exposed adults are about 1.32 times more likely to develop a disease when they are exposed than those who are not exposed.

Bias in cohort studies can occur especially in the process of making of a selection of the study subjects. This means that the selection method is based on the exposure as well as the outcomes of the exposure (Greenland, 1977). In some cases, it can be easy to view the relationship between exposure and selection of subjects. However, it is difficult for the researcher to determine how the awareness of an outcome can influence the outcomes of a study.  For instance in a study to determine the effects of the emission of some chemicals like sulfur to the people for a period of seven years, there were beliefs that employees who worked in that factory were the most affected.

However, there was no data to support this assumption. At the time of enrollment, the health records which existed by then were used while many of the old records had been misplaced or lost. Therefore there was a likelihood of either underestimation or overestimation of the association between exposure to sulfur and disease development.

Occurs when the subjects selected for the control are not a true representative of the population hence cannot estimate the distribution of exposure.

	case	Controls
Exposed	5	8
unexposed	4	54

On the other hand, taking two hypothetical situations, the researchers chose similar controls which had a high probability of having the exposure as shown below.

	Case	Controls
Exposed	5	14
unexposed	4	48

Limitations and Biasness in Cohort Studies

The loss of some participants during a follow up represents data biasness in a study. This is because there is an introduction of a deviation in the observed values during follow up as compared to the observation if all the subjects were present. In some cases, the loss of participants by about five percent is acceptable but more losses are likely to cause alarm because they have a different prognosis as compared to those who make it to the follow up. In the end, the validity and accuracy of the study is not acceptable in this study. As a result of this, the researchers do their best to lower the number of loss of participants during follow ups.

Such measures include maintaining regular contacts by making calls or sending emails, maintaining baseline information which enables them to track the subjects easily and using the participants who are easy to track.

References

Black, H.S., Thornby, J.I., Wolf, J.E., Goldberg, L.H., Herd, J.A., Rosen, T., Bruce, S., Tschen, J.A., Scott, L.W., Jaax, S. and Foreyt, J.P., 1995. Evidence that a lowâ€Âfat diet reduces the occurrence of nonâ€Âmelanoma skin cancer. International Journal of Cancer, 62(2), pp.165-169.

de Munter, J.S., Hu, F.B., Spiegelman, D., Franz, M. and van Dam, R.M., 2007. Whole grain, bran, and germ intake and risk of type 2 diabetes: a prospective cohort study and systematic review. PLoS Med, 4(8), p.e261.

Egger, M. and Smith, G.D., 1998. Bias in location and selection of studies. BMJ: British Medical Journal, 316(7124), p.61.

Fung, T.T., Hu, F.B., Pereira, M.A., Liu, S., Stampfer, M.J., Colditz, G.A. and Willett, W.C., 2002. Whole-grain intake and the risk of type 2 diabetes: a prospective study in men. The American journal of clinical nutrition, 76(3), pp.535-540.

Greenland, S., 1977. Response and follow-up bias in cohort studies. American journal of epidemiology, 106(3), pp.184-187.

He, M., van Dam, R.M., Rimm, E., Hu, F.B. and Qi, L., 2010. Whole-grain, cereal fiber, bran, and germ intake and the risks of all-cause and cardiovascular disease–specific mortality among women with type 2 diabetes mellitus. Circulation, 121(20), pp.2162-2168.

McKeown, N.M., Meigs, J.B., Liu, S., Wilson, P.W. and Jacques, P.F., 2002. Whole-grain intake is favorably associated with metabolic risk factors for type 2 diabetes and cardiovascular disease in the Framingham Offspring Study. The American journal of clinical nutrition, 76(2), pp.390-398.

Prochaska, J.O., Velicer, W.F., Redding, C., Rossi, J.S., Goldstein, M., DePue, J., Greene, G.W., Rossi, S.R., Sun, X., Fava, J.L. and Laforge, R., 2005. Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms. Preventive medicine, 41(2), pp.406-416.