Epidemiological Studies and Public Health

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Epidemiological Studies and Public Health

Introduction

The wellbeing of humans is a state of health that is subject to various determinants of health and diseases. Often, most epidemiological studies present risk factors as individual non-independent elements due to complex interactions and synergistic associations in practice (Fletcher & Fletcher, 2012). These health-associated conditions naturally fall into two categories comprising of modifiable and non-modifiable elements. Therefore, this essay discusses how epidemiological studies influence interventions and contribute to the reduction of disease risks in the population.

Evaluation of Disease Risks

Disease risk encompasses the existence of typical conditions, including behaviors that precede and associate with a higher likelihood of adverse health outcomes. Chatterjee, Shi, and García-Closas (2016) describe disease risk as aspects of lifestyle (or individual behavior), environmental exposure, or a genetic characteristic associated with an increase in the occurrence of a particular disease, injury, or other health condition. These factors coexist and undergo complex interactions, leading to an increased occurrence of adverse health outcomes.

Fundamentally, risk factors vary in type and strength amongst different individuals and populations. There is a disparity between risk factors for the onset of disorders and the occurrence of relapses. Thus, disease risks have correlational or causal relationships. In this view, essential characteristics of risk factors involve their ability to precede outcomes and divide the population into high-risk and low-risk subgroups (Malilay et al., 2014; Chatterjee et al., 2016).

Principally, distinguishing different risk factors is essential in designing preventive interventions. The intervention aimed at reducing the incidence of health outcomes must focus on causal risks, while those targeting correlate variables result in modification of background conditions (Fletcher & Fletcher, 2012). Overall, the potency of risk factors is critical in developing preventive and treatment interventions effective when matched to the target populations level of risk.

Epidemiological Studies and Interventions to Reduce Risks

Risk factors play a central role in the prediction and prevention of adverse health outcomes. Based on research, identification of risk factors contributes to the discovery of disease agent, host, and environmental factors that affect health. Therefore, epidemiology measures the relationships between hosts and agents, including analyzing the health status of the population living in a given environment with an objective to promote health.

Thus, to improve the well-being of the population, the knowledge produced by epidemiological guides in designing interventions and tackling all three elements of the triangle (Finger et al., 2018). Reducing the risk associated with host characteristics involves designing approaches that improve the immune system, increase knowledge, and motivate behavioral change to make them more resistant to agents.

Similarly, epidemiological findings equip medical experts with knowledge of the presence and distribution of pathogenic agents in a given region. This knowledge provides an opportunity to modify the interaction of risk factors in the environment and minimize adverse health outcomes (Malilay et al., 2014; Finger et al., 2018). Existing evidence of pathogenic agent elimination consists of the adoption of measures to reduce capacity through the improvement of hygiene standards, such as the provision of safe drinking water, proper waste management, adoption of anti-smoking regulations, and physical activity guidelines.

Subsequently, addressing environmental challenges involves assessing and modifying the socio-political and ecological determinants of health. The core objective takes in evaluating the effectiveness of health programs and services in improving population health (Fletcher & Fletcher, 2012). Environmental manipulation encompasses the amendment of projects, interventions, and policies to match the needs of the existing health state. Thus, epidemiological studies influence interventions that reduce risk factors because it helps to modify population and environmental characteristics.

Epidemiology and Evidence-Based Medicine

Evidence-based medicine involves the integration of clinical expertise with the best available external evidence from epidemiological research. The link between these two medical components encompasses the focus on problem-solving and decision-making processes (Galbraith, Ward, & Heneghan, 2017). According to the National Guideline Clearinghouse, randomized controlled trials (RCTs) act as a gold standard employed in providing the best evidence for research.

However, ethical considerations limit their application in clinical practice or health policy. Thus, to resolve this limitation, clinical epidemiology comprising of the results of various studies, including case-control and cohort studies, acts as a new model for clinical research and decision-making that leads to changes in health policy. Population-based data enables the formulation and the application of effective and efficient diagnostic approaches to the care of an individual patient to achieve the ultimate goal of medical research while respecting practitioners clinical expertise.

Additionally, the understanding of the concepts of disease risk aids in the advancement of medical education and facilitates individual patient-level decision-making. Since epidemiology investigates the frequency and determinants of disease, as well as the diagnostic and therapeutic approaches to management in clinical practice, it advances EBM principles in developing and implementing defined therapeutic procedures (Galbraith et al., 2017; Finger et al., 2018).

The threshold arrived at for the presence of the risk factor relates directly to the results of the measure of potency. Epidemiological investigations provide estimates of the magnitude of risk related to a particular level of exposure or dose and facilitate the evaluation of appropriate microbiological quality standards. These processes anchor policy enactment to experimental evidence and promote the best and lowest care for patients.

Conclusion

Epidemiological studies facilitate the understanding of disease risks, distinction of their categories, and measures of potency, which are valuable in the clinical and policy domains. A significant consideration in determining the potency of a risk factor is the relative importance of ensuring the implications of a false negative and positive results. The integration of epidemiological findings into evidence-based medicine brings into focus the alteration of causal risk factors, boost prevention, and eliminate effects that decrease the health status of populations.

References

Chatterjee, N., Shi, J., & García-Closas, M. (2016). Developing and evaluating polygenic risk prediction models for stratified disease prevention. Nature Reviews Genetics, 17(7), 392-406. Web.

Finger, F., Bertuzzo, E., Luquero, F. J., Naibei, N., Touré, B., Allan, M., & Azman, A. S. (2018). The potential impact of case-area targeted interventions in response to cholera outbreaks: A modeling study. PLOS Medicine, 15(2), 1-27. Web.

Fletcher, R., & Fletcher, S. W. (2012). Clinical epidemiology: The essentials (5th ed.). New York, NY: Lippincott.

Galbraith, K., Ward, A., & Heneghan, C. (2017). A real-world approach to evidence-based medicine in general practice: A competency framework derived from a systematic review and Delphi process. BMC Medical Education, 17(1), 1-15. Web.

Malilay, J., Heumann, M., Perrotta, D., Wolkin, A., Schnall, A., Podgornik, M., & Simms, E. (2014). The role of applied epidemiology methods in the disaster management cycle. American Journal of Public Health, 104(11), 2092-2102. Web.

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