Introduction To Epidemiology: Measures, Study Design And Association

Introduction to Epidemiology

1. Epidemiology-It is the field of the study dealing with the distribution and determinants of diseases and its application to the control of diseases. It can be done by means of epidemiological investigations, surveillance and analytical studies. This information about occurrence of diseases in different age groups helps to plan and evaluated strategies to prevent illness and manage patients (WHO | Epidemiology, 2017). 
2. Epidemiological study plays an important role in public health as epidemiologist are involved in controlling public  health through disease surveillance, observational studies and outbreak investigation to identify risk factors of diseases in a population group. Epidemiology provides public health professionals with the required information to develop and implement intervention programs for prevention of disease and illness (Friis & Sellers, 2013).
3. Observational research- It is related to the field of research where the researcher directly observes a phenomenon in their natural setting. Observational research is mostly done in social sciences and marketing. Multiples methods are used to gather data in observational research particularly by means of writing field notes (Booth & Tannock, 2014). The main advantage of observational research over experimental research is it is cheaper and leads to generalisability of data because of more representative samples from natural setting. It also promotes efficient use of available data compared to other approach. The main limitation of observational research compared to experimental research is it is a time consuming process and data may be too subjective. It is dependent on the role of researcher and has chances of role conflict during the investigation (Bryman, 2015).

4a. Prevalence of high blood pressure at the start of the period- (No. of new cases during the period/ size of population at the start)*100= 20%

4b. Cumulative incidence of blood pressure- (Number of new cases of disease during a period/ number of subjects at risk in the population at the start of the study)= 10/ 20 *100= 50%

4c. Incidence rate of blood pressure- (Number of new cases/ population at the start of study) * 100= 80/100* 100= 80%

5. Different measures of disease frequency is important in epidemiology to identify the association between exposure and outcome. The disease frequency can be measured by incidence rate, cumulative incidence and prevalence rate. Prevalence is the measure of disease occurrence and it is mainly measures the current case of a disease at a particular point of time. This value is used in public health to quantify disease burden and it is calculated by the number of individuals with the disease at a particular time divided by the population at risk of developing the disease midway during the period (Aschengrau & Seage, 2013). 

1. Incidence of disease is related to the measures of the occurrence of new cases of disease during a lifespan. On the other hand, cumulative incidence or incidence proportion is the estimation of risk or chance of developing disease during a specific period of time. Incidence of disease or cumulative incidence can be used in different circumstances (Measures of Disease Frequency, 2017). 

If disease-free people are observed over a period of time for risk of particular disease, in that case cumulative incidence can be used to estimate the probability of developing the disease during that time. On the other hand, incidence is preferred over cumulative incidence, when the main purpose is to identify the distribution of disease in a population group (Barendregt et al., 2013).  

1.  Heirarchy of study design is the classification of research into different methodologies and utilizing each of them according to their best suitability to areas and purpose of investigation. For example in case of research questions related to etiology, prevention and therapy, Randomized controlled trial (RCT) is considered to be the best study design. However, the answer to the research can also be obtained by meta-analysis or systematic review. The quality of research is understood by the level of evidence. The hierarchy of study design is as follows:
2. Properly conducted Randomized controlled trial

II-1 RCT without randomization

II-2 Cohort or case-control study

II-3 Multiple time series study

III- Case reports and opinions (Selvaraj, Borkar, & Prasad, 2014).

1. Analytical study is a type of comparative study designed to reach causal inference about risk factors and outcome of disease. For example to analyse the cause of high prevalence of diabetes in particular group, analytical study is done to quantify association between risk and outcome. Cohort study, randomized-controlled trial and case control study are examples of analytical study (Noble & Smith, 2015).
2. As the purpose of the research is to investigate whether drinking tea is protective for the development of skin cancer, cross sectional study method may help to get answer to the research questions. By this way manipulation of environment can be done to analyze the outcome of the study. By means of randomized experiment, I can take group of participants and randomly assign them to control (Not drinking tea) and treatment group (drinking tea). After the set period, the outcome related to risk of cancer may determine whether drinking tea I protective for developing skin cancer or not.

9b. Strength of randomized controlled trial-

• It helps to allocate intervention to a specific population
• It enhance the credibility of the study
• Observations can be consistent as small changes can be detected.

Weakness of randomized controlled trial

• It requires expenditure in establishing the setting.
• As selection of participant is limited, it may lack applicability to large population group.
• It is hard overcome recruitment biases (Booth & Tannock, 2014).

10 a. The author indicates the cohort study as prospective study because the researcher was watching for the outcome (impact of improvement in housing condition on reduction of illness in indigenous communities) by taking cohort subjects over a long period of time.

1. Outcome variables mainly include risk factors and disease outcomes.
2. The main exposure variables is government funded housing infrastructure for Australian indigenous communities.
3. The limitation in this study is that it requires a lot of time to predict the outcome of interest in selected participants and time constraints may affect the research (Prospective and Retrospective Cohort Studies, 2017).
4. The conclusion is not supported by evidence and supporting the fact of high level of household crowding with poor environmental conditions might have affected the validity of the research.
5. Risk Ratio= Cumulative incidence in exposed group/ unexposed group

Risk Ratio= 0.16/0.26= 0.615

11b. The risk ratio of 0.615 indicates that risk of diabetes is high in people who do not take vegetarian diet compared to those who take vegetarian diet.

11c. Odds ratio = Odd of disease in exposed/ odds of disease in non-exposed

Odds ratio= 40/ 100= 0.4

11d. The odd ratio of less than 1 suggest that odds of exposure are negatively associated with adverse outcome compared with non-exposure.

11e. Odd ratio is related to the association between exposure and outcome, whereas risk-ratio helps to directly analyze relative risk in population.

1. The risk ratio of 0.2 indicates risk of restaurant outbreak is high due to gastrointestinal disease compared to eating berries.

Reference

Aschengrau, A., & Seage, G. R. (2013). Essentials of epidemiology in public health. Jones & Bartlett Publishers.

Barendregt, J. J., Doi, S. A., Lee, Y. Y., Norman, R. E., & Vos, T. (2013). Meta-analysis of prevalence. Journal of epidemiology and community health, 67(11), 974-978.

Booth, C. M., & Tannock, I. F. (2014). Randomised controlled trials and population-based observational research: partners in the evolution of medical evidence. The British Journal of Cancer, 110(3), 551.

Booth, C. M., & Tannock, I. F. (2014). Randomised controlled trials and population-based observational research: partners in the evolution of medical evidence. The British Journal of Cancer, 110(3), 551.

Bryman, A. (2015). Social research methods. Oxford university press.

Friis, R. H., & Sellers, T. (2013). Epidemiology for public health practice. Jones & Bartlett Publishers.

Measures of Disease Frequency. (2017). Sphweb.bumc.bu.edu. Retrieved 25 March 2017, from https://sphweb.bumc.bu.edu/otlt/mph-modules/ep/ep713_diseasefrequency/ep713_diseasefrequency_print.html

Noble, H., & Smith, J. (2015). Issues of validity and reliability in qualitative research. Evidence Based Nursing, 18(2), 34-35.

Prospective and Retrospective Cohort Studies. (2017). Sphweb.bumc.bu.edu. Retrieved 25 March 2017, from https://sphweb.bumc.bu.edu/otlt/mph-modules/ep/ep713_analyticoverview/ep713_analyticoverview3.html

Punch, K. F. (2013). Introduction to social research: Quantitative and qualitative approaches. Sage.

Selvaraj, S., Borkar, D. S., & Prasad, V. (2014). Media coverage of medical journals: do the best articles make the news?. PloS one, 9(1), e85355.

WHO | Epidemiology. (2017). Who.int. Retrieved 25 March 2017, from https://www.who.int/topics/epidemiology/en/ 

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