Risk Factors and Health Outcomes Interrelation

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Table of Contents

Introduction
A Case-Control Study
Components of a case-control study
Intended choice of the designs
Conclusion
Reference List

Introduction

Surveys that are used to evaluate medical situations are either experimental or quantitative in nature. They are aimed at determining the relationship between risk factors and health outcomes. This essay examines various researches on the relations between the prevalence of risk factors and outcome.

A Case-Control Study

A case-control study is categorized under analytical examination. The study is conducted to compare “cases” with the “control” to find out if an underlying cause or exposure is related to an outcome. In case-study control, the subjects are used as a control experiment whereby a characterless category is studied (Leske, Warheit-Roberts, & Wu 1996). The outcome of the survey is always pre-determined since they are controlled by specific categories. The researcher is not allowed to use the collected data (Leske et al., 1996).

Components of a case-control study

Cases

Cases are subjects that possess similar characteristics to be studied. For instance, a hospital setting can have many cases of patients with post-operation malignant tissues after a given period. For a case to be considered in the study, it must involve the patients with similar symptoms that occur within a given period. Criteria for clinical diagnosis must be clearly outlined to ensure proper classification. This situation brings about increased accuracy and reliability of the evaluation outcome (Leske et al., 1996).

Control

Control is another component that must exist for the case-control study to be conducted. This component must possess various characteristics such as age, sex, and duration of treatment that are similar to the cases. Control is mainly considered for estimation of the frequency and exposure of the subjects when the study is not conducted (Leske et al., 1996).

Technique for Matching both Cases and Control

An analyst must ensure that cases and controls match perfectly. Although the realization of such conditions is difficult, a variable that suits both components must be identified. Therefore, the analyst should include several controls for each case in the study. Perfect matching of cases and control is paramount to solving confounding issues during the study (Leske et al., 1996).

The reason why Case-Control Study is considered an Analytical Epidemiological Study

Various reasons underpin the use of the study of analytical epidemiological cases. At the outset, case-control studies are used to research rare diseases. In addition, they are suitable where the investigation of the disease is time-bound. The study is analytical because inferences can be made to determine the cause-effect relationships that exist amongst the variables (Leske et al., 1996).

Reasons why Case-Control Study is considered an Observational Study

A case-control study is an example of an observational study since the inferences of the study are mainly derived from various effects that arise from the treatments that are administered to the subjects under investigation. This situation mainly occurs in cases where the treatment applied to the subjects cannot be controlled by the researcher. It is also possible to begin the study from the case categories backward to the initial stages since they have an observational. It is an observational study since the investigator records the activities and characteristics of the samples. The investigator can also describe the situations whilst studying the characteristics of the samples (Leske et al., 1996).

Risk Factor (Exposure) Variable as per Case-Control Study

Risk factor is a variable connected to an enhanced danger of an infection or a disease. It is mostly used as a determinant since these variables only correlate but do not cause a disease. For instance, sedentary lifestyle is usually a risk factor for obesity. However, it does not necessarily cause obesity (Leske et al., 1996).

Outcome/Dependent Variable as Per Case-Control Study

An outcome variable is measured during the case-control study. This variable is the portion that is affected by the research. It is greatly influenced by the independent variable.

Time-frame and diagram of how case-control works

In the case-control scenario, the timeline for the study can be weeks, months, or at most a year. From the diagram, the investigators begin by analyzing the existing evidence of the disease prior to carrying out investigations in an attempt to identify the possible causes of the problem.

Advantages of Case-Control Study

At the outset, case-control studies allow the investigator to conduct research on rare diseases. Secondly, they can be used to study complicated illnesses that a long time to manifest themselves. This research is also inexpensive and can be used to study several cases of diseases simultaneously (Lischko et al., 1989).

Prospective Cohort Study

Prospective cohort study examines subjects of similar characteristics over a certain period. Although most of the subjects are similar in nature, some have differing characters under the study. These characters have impacts on the outcome of the study (Van den Brandt et al., 1990). Most of the prospective cohort studies are used for etiology of diseases among other problems. A clear unique character of a prospective cohort study is that an investigator includes the subjects (Goldberg et al., 2004).

Components of a Prospective Cohort Study

Various components of a prospective cohort study include the outcome of interest, which should not occur before or at the beginning of the study. Another component is the time of accomplishing the study. This study focuses on a longitudinal design to assess the situations of the subjects (Van den Brandt et al., 1990). A significant aspect that a researcher must consider while conducting this kind of study is that the subjects must be free of any existing conditions or diseases to enable identification of the exposure conditions simultaneously. This situation increases the chances of obtaining accurate information.

Reason Why Prospective Study Is Considered Analytical Type of Study

At the outset, it has the ability to monitor the etiology of a condition. It clearly indicates the relationship between the risk factors and outcome variables. It can also measure relative risk factors (Van den Brandt et al., 1990). Furthermore, the study is considered analytical because the characteristics of a condition can be measured at various phases; hence, changes can be determined easily.

Exposure or Risk Factor Variable with Respect to Prospective Study

A risk factor variable with respect to the prospective cohort study is that refers to the probability of a subject to be infected with a new disease under predetermined conditions. In this case, it is termed as the independent variable in the study. The variables under the study can be directly measured; hence, they are referred to as relative risk factors (Van den Brandt et al., 1990).

Outcome or Disease Variable with Respect to Prospective Cohort Study

The outcome or dependent variable in the prospective study is the result due to exposure. For example, when a person is exposed to smoke from cigarettes, he may be infected by lung cancer disease. The lung cancer is an outcome variable (Van den Brandt et al., 1990).

Timeline and diagram of how cohort study works

The timeline of the study is one year and above. Several cases that can be analyzed using this method include cancer cases that or HIV prevalence that take several years. From the diagram, the investigator begins with analyzing the causes of a disease then conduct observations on the occurrence of the infection in relation to the causes or agents of the infection.

Differences between Prospective Cohort and Retrospective Cohort Studies

The main difference between the two cases is that a retrospective study trace backwards and determines exposures to subjects who are suspected to be at risk. The prospective begins with healthy subjects. The retrospective provides estimates of relativity of risk factors; hence, issues of biasness and confounding are frequent in such studies (Van den Brandt et al., 1990).

Disadvantages of cohort studies

Cohort studies have various disadvantages that include their inability to facilitate investigation of rare diseases. There is also a likelihood of increased biasness, especially when a retrospective design is used. In addition, these studies consume a lot of time and are relatively expensive to implement. Lastly, the cohort studies cannot be used to examine cases that involve investigation of long latency diseases (Van den Brandt et al., 1990).

Cross-Sectional Study

A cross-sectional study includes combination of subjects from different groups to form a large sample, which is examined at a specific time. Although these samples differ in many characteristics, they must possess some feature such as social status that bind them together (Cohen et al., 2008). This type of study does not allow manipulation of its variables. It ensures that a researcher examines many characteristics of a study population simultaneously.

Why Cross-Sectional Study is either Analytical or Observational

Cross-sectional studies are considered observational because they entail recording of information on the characteristics of the subjects. They can be applied in description of situations that are subjected to study (Cohen et al., 2008). The research is analytical because various analysis and inferences can be made from examining various observable characteristics of the subjects (Cohen et al., 2008).

Details of Cross-Sectional Design

An important characteristic of cross-sectional design is that the study is based on observations of different subjects combined to form a sample at a given time. The study does not require any experimental procedure; hence, an investigator cannot be in a position to manipulate the variables. Therefore, this type of research is combined with other research designs to develop relevant hypotheses that can be tested (Cohen et al., 2008).

Purpose of Cross-Sectional Design

Cross-sectional study follows a descriptive design in the form of a survey. It is based on the outcome of a risk factor. Its primary purpose is to determine the prevalence of the result amongst the subjects under investigation. It can also be used to examine the relationship between the risk variables and outcomes (Goldberg et al., 2004).

Selection of Samples and their Response

The sample for this study is selected from a given population using various random techniques. However, the sample must be a representation of the population of the subjects under study. Therefore, non-response problems must be minimized at all times (Cohen et al., 2008).

Measure of Exposures and Outcome

To minimize the loss of information about risk factors, relevancy must be maintained through optimization of the expected outcome. The relationship between the outcome and risk factors must be examined within a relatively short time to implement the cross-sectional research design successfully (Cohen et al., 2008).

Disadvantages of Cross-Sectional Research Design

Various disadvantages of cross-sectional research design include its inability make inferences from the causes of diseases. In addition, it fails to provide consistent results when used at different times. A high degree of biasness is evident, especially in cases that require lengthy processes to investigate diseases (Cohen et al., 2008).

Analytical Study Design

This study design is mostly used to test hypotheses that are designed based on the relationships between the exposures and outcomes. Various examples include the case-control and cohort studies (Zeegers, Volovics, Dorant, Goldbohm, & Van den Brandt, 2001).

Experimental Study Designs

The experimental study design is used to test the relationship between the causes and effects of various variables. The investigator must identify both experimental and control groups that are subjected to examination. This design entails randomization of techniques and manipulation of variables (Zeegers et al., 2001).

Controlled Trials

A controlled trial is a study whereby different categories of participants receive treatments based on predetermined factors such as the ‘gold standard’ therapy or placebo treatment. Controlled trials can be categorized as either randomized or non-randomized (Zeegers et al., 2001). Randomized techniques are frequently used to determine the cause-effect relationships between treatment and outcome among the subjects. Controlled trials are cost efficient (Zeegers et al., 2001). This type does not allow for the inclusion of systematic differences among the controlled groups as such may affect the results. The non-randomized controlled trials are used mainly to determine the association or relationships that exist between interventions and results or outcome (Zeegers et al., 2001).

Relationship between analytical, experimental, and controlled trial studies

The existing relationship between the stated research designs is their ability to be used in examining the relationship between the risk factor variables and the outcome or results. These studies can also be implemented in hospital set up by investigators who would like to monitor or study a given disease of condition and its effects on the subjects (Vandenbroucke, 2007). All the three studies are based on controlled variables.

Advantages of randomized, placebo trials

The various advantages of randomized, placebo trials include non-biasness, they give high quality evidences on studies, and their internal validity gives quality outcome among others.

Intended choice of the designs

Two cohort studies

Alcohol Consumption and Bladder Cancer Risk: Results from the Netherlands Cohort study (Zeegers et al., 2001).

One Case-Control Study

Evaluation of prior primary as a determinant of uveal melanoma (Lischko et al., 1989).

One Randomized Control Trial

A randomized controlled trial of fluorouracil plus leucovorin, irinotecan, and oxaliplatin combinations among patients with previously untreated metastatic colorectal cancer (Williamson & Alberts, 2004).

Conclusion

The essay has elaborated on several research designs that can be used to examine the relationship between the risk factor and outcome of a problem of samples. This essay further has elaborated the various disadvantages that are involved and the most relevant designs that can be used for the studies in GHP.

Reference List

Cohen, A., Tapson, V., Bergmann, J., Goldhaber, S., Kakkar, A., Deslandes, B.,…Endorse Investigators. (2008). Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): a multinational cross-sectional study. The Lancet, 371(9610), 387-394.

Goldberg, R., Sargent, D., Morton, R., Fuchs, C., Ramanathan, R., Williamson, S.,…Alberts, S. (2004). A randomized controlled trial of fluorouracil plus leucovorin, irinotecan, and oxaliplatin combinations in patients with previously untreated metastatic colorectal cancer. Journal of Clinical Oncology, 22(1), 23-30.

Leske, C., Warheit-Roberts, L., & Wu, S. (1996). Open-angle glaucoma and ocular hypertension: the Long Island Glaucoma Case-control Study. Ophthalmic Epidemiology, 3(1), 85-96.

Lischko, A., Seddon, J., Gragoudas, E., Egan, K., & Glynn, R. (1989). Evaluation of prior primary malignancy as a determinant of uveal melanoma. A case-control study. Ophthalmology, 96(12), 1716-21.

Van den Brandt, P., Goldbohm, R., Veer, P., Volovics, A., Hermus, R., & Sturmans, F. (1990). A large-scale prospective cohort study on diet and cancer in The Netherlands. Journal of clinical epidemiology, 43(3), 285-295.

Vandenbroucke, J., Von Elm, E., Altman, D., Gøtzsche, P., Mulrow, C., Pocock, S.,…Egger, M. (2007). Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration. Annals of internal medicine, 147(8), 163.

Zeegers, M., Volovics, A., Dorant, E., Goldbohm, R., & Van den Brandt, P. (2001). Alcohol consumption and bladder cancer risk: results from The Netherlands Cohort Study. American journal of epidemiology, 153(1), 38-41.

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