Case-Control Design Study
Atherosclerosis is a lifelong artery condition that is the leading cause of about 50 percent of all Western world fatalities. This disease is primarily a fat-driven cycle that occurs through the deposition of LDL and HDL lipoproteins within the artery. Cardiovascular disorders are the leading cause of health-related deaths in the United States, killing more than 730,000 persons per year. Obesity/overweight is a significant risk factor for arteriosclerosis. Numerous researches have shown a clear correlation to obesity and many cardiac conditions, including acute heart infarction, stable heart disease, heart failure, and ischemic stroke. It has also been shown that the association between obesity and high blood pressure and diabetes mellitus increases the incidence of arteriosclerosis (Aluganti Narasimhulu et al., 2016). This research aims to determine whether obesity as a growing world pandemic is an absolute prerequisite for arteriosclerosis development.
A case-control design study would be appropriate for research relating to the relation between arteriosclerosis and obesity. The nature of the study contrasts patients with the disease with patients who do not have the condition and looks back to compare how much the risk factor exposure is present in each category to investigate the relationship between the disease and the risk factor. Case-control research is also retrospective as it begins with a result and then traces back for exposure analysis. Once the subjects are identified in their groups, and the investigator already knows the outcome of each subject, the study begins.
Case-control studies are particularly useful for the analysis of outbreaks and the research of rare diseases. Since these studies begin with a known outcome, ample numbers of patients with a rare condition can be enrolled. The advantage of providing quick results or studying unexpected results exceeds the limits of case-control research (Mann, 2012). The high level of efficiency makes case-control studies are also ideal for the initial examination of a risk factor that is suspected for a well-known condition; findings may be used in later longitudinal studies.
This study will employ both governmental and private data sources. CDC: National Center for Health Statistics (NCHS) Surveys are one valuable and cost-effective government data source. The National Health Interview Survey is a significant source of knowledge about the civilian U.S. population’s wellbeing and is used to track disease patterns. To achieve representative sampling of households, it is a cross-sectional survey with a multi-stage area probability design (Barros & Blumenberg, 2016). The topics of the questionnaire are essential health, demographics, and present-day health. Depending on the data needs, the existing health issues shift. One advantage of this data source is that the samples used are population-based, so it is possible to determine national estimates for different health problems. Another is that the surveys can be calculated using population-based and regional statistics on various health issues. The drawback of survey usage is that the studies are costly, and there is a substantial time lag.
Registries can also be used as a source of arteriosclerosis data. Registries contain dynamic information, such as coronary stents, about fast-moving technologies. In contrast, the registries also provide information about patients either undergoing a specific procedure or having a particular syndrome of the disease. However, the registries contain minimal detail. A further data source is the Harvard Pilgrim Health Care database. This data source is a fully automated, computerized pharmacy medical recording system that is searchable and marked with health care information. However, the source is not ideal for access to inpatient medications, so only severe conditions should be investigated.
References
Aluganti Narasimhulu, C., Fernandez-Ruiz, I., Selvarajan, K., Jiang, X., Sengupta, B., Riad, A., & Parthasarathy, S. (2016). Atherosclerosis — do we know enough already to prevent it. Current Opinion in Pharmacology, 27, 92-102. doi: 10.1016/j.coph.2016.02.006
Barros, A., & Blumenberg, C. (2016). Electronic data collection in epidemiological research. Applied Clinical Informatics, 07(03), 672-681. doi: 10.4338/aci-2016-02-ra-0028
Mann, C. (2012). Observational research methods—Cohort studies and case-control studies. Journal of Medicine, 2(1), 37-45. doi: 10.1026/j.afjem.2011.12.004