This paper is an epidemiologic study that seeks to study the exposure of individuals to causal factors of obesity and how this affects the society. Looking at the existing literature on the same will help uncover various design limitations and useful results, which will act as a guideline to the current study. We believe that obesity could result from many factors including genetics, family lifestyle, unhealthy diet, inactivity, age, medical conditions, social and economic factors, among others. However, an extensive study on the same is yet to be done. We, therefore, seek to study them.
Most appropriate analytic epidemiological study design
We are going to use the cohort study design, which is very useful and common in most diseases. This study is particularly useful because it focuses on a particular group of people who are obese and tries to deduce the health condition from them. It is highly preferred because it first focuses on exposure rather than the health outcome, which is a condition necessary for causation.
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If the cohort study is properly designed, then it can offer very solid results. In this case, a disease-free study population is identified by the event of interest or exposure and then it is followed up until the outcome of interest or disease occurs. Cohort study makes use of a chronological framework in the assessment of causality, which better positions it to deliver the strongest scientific evidence. Besides, it is also less subject to bias (Song & Chung, 2017).
Using the selected study design to identify patterns, causes, and effects of obesity
The cohort study design entails the definition of your cohorts ( a group of study) by their exposure status at the beginning of the investigation. It is critical that the subject selection focuses on both the exposed and unexposed individuals from the same source population while excluding any subjects who are not at-risk. The subject can be sampled from a community, hospital, or any social setting.
Once the subject of study is identified, it is crucial that the investigator ensures intensive follow-up so that no data is missed. The investigator then keeps track of his group of study to observe how the individuals who were prone to the disease react, and how the already affected individuals are progressing. By so doing, it will be possible to identify patterns, causes, and effects of the disease (Sphweb, 2017).
Select an appropriate method of association
In a cohort study, relative risk is the method used to measure the association between exposure and actual disease. Relative risk is defined as the ratio between the incidence rate of index subjects and the control subjects. If the relative risk is 1.0, then the incidence rate among the exposed and non-exposed subjects is the same, and thus there is no association between the disease and its exposure. If the relative risk is less than 1.0, then there is a lower incidence rate of disease occurrence among the exposed compared to the non-exposed, which is evidence that exposure has a protective effect. Also, a relative risk higher than 1.0 indicates that exposed people have a higher risk of being affected by the disease unlike non-exposed people (Meirik, 2017).
Potential interventions for solving the issue of obesity
The complexity of obesity makes it impossible to solve with an independent solution; rather, a multifaceted approach has to be applied. Business and community leaders, policymakers, local and state organizations, healthcare professionals, and all individuals should work hand in hand to foster a healthy lifestyle. Some of the potential interventions that can counter the issue of obesity include:
State and local programs that avail necessary resources to give the appropriate public awareness about their health conditions.
The community should also focus on fostering an active living and healthy eating in various settings such as food service areas, early childhood care, schools, and hospitals.
At the individual level, overall lifestyle changes entailing regular physical activity and healthy eating should also be incorporated (CDC, 2017).
References
CDC. (2017). Strategies to Prevent Obesity | Overweight & Obesity | CDC . Cdc.gov . Retrieved 20 August 2017, from https://www.cdc.gov/obesity/strategies/
Meirik, O. (2017). Cohort and case-control studies . Gfmer.ch . Retrieved 20 August 2017, from http://www.gfmer.ch/Books/Reproductive_health/Cohort_and_case_control_studies.html
Song, J., & Chung, K. (2017). Retrieved 20 August 2017, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2998589/
Sphweb. (2017). Cohort Studies . Sphweb.bumc.bu.edu . Retrieved 20 August 2017, from http://sphweb.bumc.bu.edu/otlt/MPH-Modules/EP/EP713_CohortStudies/EP713_CohortStudies_print.html
