Difference Between Two Epidemiological Study Designs

Experimental study design and observational study design

Discuss about the Difference Between Two Epidemiological Study Designs.

Epidemiology is the study, which assesses the patterns and cause of a disease and its effect on health of a population. Epidemiology is applied to identify the risk factors of a disease, promotes evidence-based practice (EBP), and shapes the policy decisions. Epidemiologists use many types of study designs to examine a disease, which is still under investigation. There mainly two type of study designs. Experimental study design and observational study design. Here in this essay, two random epidemiology articles have been taken to compare the study designs of both the article. The first article is named Genetic Epidemiology of Major depression: Review and Meta-analysis and the second article is Genetic epidemiology of COPD (COPD gene): study design.

Different type of study designs provides the scientists with different quality information. The main two type of study design which is the Experimental study design and the observational study design can also be further divided into many categories. The experimental study design can be categorized to Randomized controlled trial, and Nonrandomized trial (Quasi-experimental). The observational study design can be further divided into three sub-categories- cross-sectional studies, cohort studies and case-control studies (Verhoeven et al., 2013).

Both of these taken articles used the study design of observation but of two different types. The first article, which discussed about the genetic epidemiology of major depression, used the more practical approach of case-control study. The other article discussing about the genetic epidemiology of COPD gene, used cohort studies to do the research (Twisk, 2013).

The case control study is something in which two different groups with different outcome variable are compared with each other. One of the groups has the disease of interest and the comparison group or the control group does not have the disease. The study is done after considering a risk factor and in the study, it is seen that how frequently the risk factor can be found in both the diseased group and the non-diseased group. In the first article, prior to choosing the groups, a set of criteria was developed, such as-

• Differences between major bipolar disorder and unipolar depression
• Collection of the data from every subject
• Operational diagnostic criteria are used.

Specifically a comparison group was chosen for doing the family study. The first group has major depression and the comparison group has no prior history of battling depression. Both of these groups are matched with some variables such as age and gender. The potential interest outcome is the prevalence of depression amongst the first-degree biological relatives. The advantage of doing a case-control study is that it is a more practical and cheaper than cohort study. In case control study, there is a need of doing a calculation which is called the odd ratio which helps in estimating a relation between the studies (Woodward, 2013).

Types of experimental and observational study design

Five families with the history of major depression are taken for the study. These families matched with all of the inclusion criteria. The study showed that the proband of all these family shows evidence in support to major depression as compared to the reference group. The evidence was strong in support of the association between the major depression of the first-degree relatives and the probands. The homogeneity of the data was assessed first by Breslow chi-square test and was pooled by the Mantel-Haenszel method. The Breslow chi-square method showed that the odd ratios of all five studies were homogeneous (χ2=5.22, df=4, p=0.27). According to the Mantel-Haenszel method, the odd ratios between the five families were 2.84. These data showed that in aggregate there is strong and consistent evidence, which supports the familiality of depression (Ripke et al, 2014).

As the case control study has its limitation, this article has also discussed about the limitation of the study. The major limitation is that, the subjects recruited for the study are recruited from the major clinical sources. If having a family history of depression increases the risk of familiality, then the ratios can be considered as biased (Sullivan, Neale, & Kendler, 2000).

Moreover, these studies shows that major depression is a disorder which runs in the families. However, this study did not distinguish the genetic influence and the environmental influence, which also can be familial. This study can be continued with other methodological approach that can distinguish both of these factors (Stroup et al, 2012).

The second article Genetic epidemiology of COPD (COPD gene): study design, applied the cohort study design. The cohort study can be described as the longitudinal study, in which a cohort or a group of people, who shares the disease of interest or a characteristic within a limited time, is taken. Cross sections are performed in intervals over a definite time period. The advantage of doing a cohort study is that it can help the researchers to determine the risk factors as it longitudinally observes the individuals through a definite time and also the data is collected at regular intervals to reduce the error (Schmidt et al., 2012).

The main disadvantage of conducting the cohort study is that it is very expensive  and takes a long time to do the follow up from time to time. However, if a cohort study is given the required time, the received data should be of superior quality and useful. Cohort studies can be regarded as the most reliable source of data in the field of epidemiology (Jaddoe et al., 2012).

Case-control study on major depression

The COPD (Chronic Obstructive Pulmonary Disease) is a heterogeneous genetic condition, which comes with many phenotypes that are disease related. COPD is very much smoking related as many smokers develop this condition but not all smokers ever develop COPD. It is assumed that there is a genetic difference between the individuals who develops COPD and who do not. It is found that the relatives of the smoker COPD patients show the characteristic of airflow obstruction. This study also further supported the hypothesis of a genetic factor causing COPD. COPD is said to be caused by the action of multiple genes, which interacts with the environmental risk factors. The study design is made to identify the genetic factors, which are causing COPD (Regan et al., 2010).

The chosen cohort is of 10000 different individuals with 33.33% of African-Americans and 66.66% people of non-Hispanic descent commonly distributed through the full disease severity spectrum of both genders. The cohorts are chosen for a GWAS (genome-wide association study) analysis that is big enough to provide the scientists with adequate results. The GWAS was designed to have four different phases. The initial phase was with 4000 subjects, who may be current smoker or a former smoker. The control subject group of the first phase was comprises of 2600 white and 1400 African-Americans. The second phase would comprise of 2000 smokers and 2000 control subjects. The phase three the SNP array regions, which are identified in the first two phases, will further be investigated. The Phase 4 will be the repeated process of phase 1 and 2 with the remaining candidate (Regan et al., 2010).

The scientists had anticipated that the COPD gene would provide them with a large cohort to further investigate the result.

To conclude that, both study designs are extremely competent in the field of epidemiology. The case control study which is used in the first article, is more of a practical approach as it deals with very less number of subjects and has very minimum amount of budget (Deo, & Albert, 2012). Nevertheless, the data received is not always error free and can be biased. The errors can be mitigated with finding the odd-ratios. However, the cohort study is a time consuming and a long method, which deals with very large number of subjects. However, the data received is more or less error free.

References:

Deo, R., & Albert, C. M. (2012). Epidemiology and genetics of sudden cardiac death. Circulation, 125(4), 620-637.

Jaddoe, V. W., van Duijn, C. M., Franco, O. H., van der Heijden, A. J., van IIzendoorn, M. H., de Jongste, J. C., … & Rivadeneira, F. (2012). The Generation R Study: design and cohort update 2012. European journal of epidemiology, 27(9), 739-756.

Regan, E. A., Hokanson, J. E., Murphy, J. R., Make, B., Lynch, D. A., Beaty, T. H., … Crapo, J. D. (2010). Genetic Epidemiology of COPD (COPDGene) Study Design. COPD, 7(1), 32–43. https://doi.org/10.3109/15412550903499522

Ripke, S., Neale, B. M., Corvin, A., Walters, J. T., Farh, K. H., Holmans, P. A., … & Pers, T. H. (2014). Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511(7510), 421.

Schmidt, R. J., Tancredi, D. J., Ozonoff, S., Hansen, R. L., Hartiala, J., Allayee, H., … & Hertz-Picciotto, I. (2012). Maternal periconceptional folic acid intake and risk of autism spectrum disorders and developmental delay in the CHARGE (CHildhood Autism Risks from Genetics and Environment) case-control study. The American journal of clinical nutrition, 96(1), 80-89.

Stroup, D. F., Berlin, J. A., Morton, S. C., Olkin, I., Williamson, G. D., Rennie, D., … & Thacker, S. B. (2012). Meta-analysis of observational studies in epidemiology: a proposal for reporting. Jama, 283(15), 2008-2012.

Sullivan, P. F., Neale, M. C., & Kendler, K. S. (2000). Genetic epidemiology of major depression: review and meta-analysis. American Journal of Psychiatry, 157(10), 1552-1562.

Twisk, J. W. (2013). Applied longitudinal data analysis for epidemiology: a practical guide. Cambridge University Press.

Verhoeven, V. J., Hysi, P. G., Wojciechowski, R., Fan, Q., Guggenheim, J. A., Höhn, R., … & Yonova-Doing, E. (2013). Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia. Nature genetics, 45(3), 314-318.

Woodward, M. (2013). Epidemiology: study design and data analysis. CRC press.