Descriptive Epidemiology and Epidemiological Research

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Table of Contents

Introduction
Epidemiological research
Conclusion
Case Study Problems
References

Introduction

Descriptive epidemiology consists of epidemiological studies that aim to characterize the distribution of a disease and its possible determinants. Descriptive epidemiology organizes information and data to outline the basic factors of health issues, persons at risk, place, time, and causes, risk factors, or modes of transmission. Descriptive epidemiology can be helpful to determine the patterns and extent of a public health concern, identify vulnerable populations or areas, and derive causes; factors which are vital in implementing treatments and interventions at a large scale (Naito, 2014).

Epidemiology must measure disease impacts and outcomes of a specific population at risk. In this context, a population is any group of people, no matter their current health status, that could be considered as cases if they were to inherit the disease (Coggon, Rose, & Barker, n.d.). Depending on the study, epidemiology may narrow the characteristics of a population to determine any causative factors for disease.

Epidemiological research

Measures of frequency, association, and impact are statistical tools used in epidemiological studies. These can be used to portray distribution, develop causal relationships, and evaluate the impacts of preventive interventions. A ratio attempts to compare two quantities, usually of the same unit. It is an expression meant to measure relative factors. A proportion is a type of ratio. It states a ratio as part of a whole, a fraction, or percentage. Therefore, a proportion sets two fractions as equal to each other. A rate is the comparison of two quantities of uniquely different units. Rates interpret ratios as a quotient and commonly incorporate the dimension of time. In public health, rates can be used for mortality or infection to determine these statistics over some time (Fleming & Holsinger Jr., 2015).

Incidence commonly refers to the rate of newly diagnosed cases of a disease. Incidence is measured as a rate over some time and has significant meaning if reported as part of the total population. The accuracy of incidence is based on the appropriate and accurate diagnosis and reporting data from healthcare providers. Prevalence refers to the number of actual cases of the disease that are alive during the period or a particular point in time.

Prevalence allows us to gain an understanding of the total disease load since it allows us to determine new infections, cases, and deaths. Prevalence is usually reported in several cases in a fraction of the total population at risk (National Institute of Mental Health, 2017). Incidence and prevalence maintain a relationship, but it is not necessarily linear as other factors may come into play. For example, with influenza, while the incidence rate is statistically high, the long-term prevalence is practically non-existent due to high rates of patient improvements. In the case of rare, chronic diseases, the factors may be reversed.

Conclusion

Cumulative incidence (also known as incidence proportion) is a frequency measure that determines probability as part of the total population during a period, but it does not identify when subjects encountered a disease. It considers the proportion of the disease-free population which acquires the disease within the period. The incidence rate is a true rate of the number of new cases during an observation period.

The incidence rate directly includes time in the denominator. Therefore, the rate attempts to portray a ratio of the number of cases to the total time that a population is at risk. Incidence density is a more complex method of incidence calculation. It tracks only the incidence in subjects who have remained with the study or observation over the period and avoids those who may have for any reason be a “loss to follow-up” (Fleming & Holsinger Jr., 2015).

Case Study Problems

Question 5

Ratio: 75:25.
Proportion: 75/50,000 = 0.15%.
Rate: 75 male heart attacks per year.

Question 6

Ratio: 5.2:2.2.

This ratio at first demonstrates that there are more white women with diabetes than black females. The number of white females with the disease exceeds black females by almost twice as much and creates an appearance that diabetes is more prevalent amongst white populations.

Question 7

Proportion: 5.2 million/84.7 million.

The proportion presents that diabetes occurs in white female populations commonly but makes up a relatively minor segment of the population. That is appropriate for a serious chronic disease and remains within standard parameters for the population.

Question 8

The rate for white females: 6.14 per 100
The rate for black females: 15.71 per 100

These rates indicate that despite white females having almost twice as much of numbered diagnosed cases as black females, the proportion of the population and attack rates are much higher amongst black females. Incidence rates are much higher which is an indicator that the disease is more prevalent amongst black populations.

Question 9

Ratio: 27.1 million:5.3 million
Proportion: 27.1 million/81.1 million
Rate: 33.42 per 100 amongst white males
41.73 per 100 amongst black males
Relative risk: 41.73/33.42 = 1.25 indicating that the black population is at an increased risk for hypertension.

Question 12

Risk Factors	Prevalence Rate (per 100)
	White Males	White Females	Black Males	Black Females
Smoking prevalence	16.99	15.09	15.90	10.42
Obesity (>=30 BMI)	24.72	24.44	25.40	37.18
Cholesterol (>200 mg/d²)	29.62	34.44	25.87	28.08
High blood pressure	24.43	23.08	28.55	32.42
Diabetes mellitus	5.63	4.66	9.04	10.62
Total Population	110,941	112,613	18,596	20,333

References

Coggon, D., Rose, G., & Barker, D.J.P. (n.d.). Epidemiology for the uninitiated. Web.

Fleming, S. T., & Holsinger Jr., J. W. (2015). Epidemiology and leadership. In S. T. Fleming (ed.), Managerial epidemiology: Cases and concepts (3rd ed.) (pp. 509-532). Chicago, Illinois: Health Administration Press.

Naito, M. (2014). Utilization and application of public health data in descriptive epidemiology. Journal of Epidemiology, 24(6), 435-436. Web.

National Institute of Mental Health. (2017). What is prevalence? Web.

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