The incorporation of biostatistics into public health helps to demonstrate the prevalence of disease throughout the nation. Biostatistics can be applied to different scenarios to gain an array of information (Bailey, 2012). This paper will explore the application of biostatistics into the field of public health by applying it to cardiovascular disease in the United States to demonstrate why biostatistics are a crucial measure for public health professionals. This paper will further explore the use of new medications to treat illnesses and discuss factors that account for conflicting results.
Cardiovascular disease is the number one cause of death in the United States. According to the Center For Disease Control & Prevention (2012) “about 600,000 people die of heart disease in the United States every year- that’s 1 in every 4 deaths” (pp. 2). Public health professionals often wonder what variables impact the likelihood the individual will develop cardiovascular disease (Jacobsen, 2011). Research has demonstrated that men are more likely than females to die of cardiovascular disease. A research may ponder whether or not physiological differences between men and women account for more men dying from cardiovascular disease or if lifestyle factors that increase the likelihood individuals will develop cardiovascular disease are more prominent in men. In order to explore this, a research would want to gather a sample, consisting of both males and females. Lifestyle factors would be a separate variable that could influence physiological differences. Therefore, the researchers would want to have four groups, a group for males with lifestyle factors that increase the likelihood they will develop cardiovascular disease, a group for females with lifestyle factors that increase the likelihood they will develop cardiovascular disease and two separate groups (one for males and one for females) that do not have lifestyle factors which are associated with cardiovascular disease.
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This scenario identifies the various research outcomes that researchers could achieve through the use of biostatistics when applied to a disease. Researchers could choose to measure an array of different outcomes including the likelihood the individual dies from cardiovascular disease. The research may further choose to measure the extent of a disease in the region. In using cardiovascular disease, the researcher could choose to examine the number of fatalities associated with the disease in each region and compare them. From obtaining the number of individuals that have died from an illness such as cardiovascular disease in a specific region, a researcher could further determine how many deaths this disease will account for in the future. These projections would assume that all other variables remain statistic and would not reflect any interventions that take place in a designated region. Although these projections may change (through interventions, changing lifestyle habits, etc.) the researchers would be able to determine how many individuals will likely die of the illness over the next few years (Jacobsen, 2011).
The effectiveness of a new drug could be evaluated in measuring the spread of disease to other organs in the body. For example, if a group of individuals are taking an experimental drug to slow the progression of Alzheimer’s disease, the researcher would explore how long it takes for individuals to move into the later stages of the disease. The researchers could use an array of techniques in order to supplement this study and show that this medication is effective including brain scans. However, it is likely that not all individuals will experience the same results when administered a medication (Bailey, 2012). Therefore, future research could explore what variables individuals that did not experience the helpful effects of this new drug. This would further help public health professionals to determine whom this medication is best suited for.
Individualistic variables can help to explain why public health researchers obtain different data in different samples. Some medications may be less effective for individuals with certain strains of diseases, biological factors or environmental factors (Bailey, 2012). However, the inability to include of these factors into a research study may produce results that conflict with previous studies. For example, individuals taking more than one medication may find that another medication does not work as well for them, due to the interaction between the two medications.
- Bailey S. (2012) Introduction to Epidemiological Research Methods in Public Health. New York: Pearsons.
- Heart Disease Facts (2012) Retrieved from: http://www.cdc.gov/heartdisease/facts.htm
- Jacobsen K.H. (2011) Introduction to Health Research Methods. New York: SAGE.
