The community issue addressed is the high prevalence rates of obesity and overweight. In this regard, the challenge is comprehensive, owing to categorizing the aspect as a lifestyle condition. Subsequently, other factors, such as nutrition, inadequate physical exercise, and sedentary lives contribute to the issue. The problem is significant, owing to substantial correlations between obesity, overweight, and other comorbidities. The implication is that obesity is a risk factor for other illnesses, including cardiovascular diseases, obesity, cancer, and other issues. In such a case, programs and initiatives implemented to reduce prevalence should be adequate. Accurate evaluation is critical in attaining the best outcomes, including follow-up, adherence, and addressing elements that require a change to meet emerging needs.
The evaluation structure follows a pre-and post-intervention approach. In this regard, the emphasis is on the initiatives and their ability to meet the set goals. According to the CDC (2016), obesity evaluation measures often employ baseline data to compare progress at the post-implementation phase. In this regard, the structure entails collecting baseline data of the metrics, such as BMI, waistline, and weight, among other anthropometric factors. After the intervention, such as a community education program sensitizing users on the risk factors associated with obesity and overweight, the evaluation will compare the baseline measures to assess any progress. To illustrate, evaluating how the BMI changed after a participant implements recommended steps will help determine efficacy. As a result, the suggested structure focuses on a pre-and post-intervention approach.
The evaluation process will be goal-based. Subsequently, the procedure will focus on specific objectives determined by the set metrics. According to Seral-Cortes et al. (2021), an effective evaluation process should emphasize knowing the goals and project outcomes, testing them against set results. Additionally, precise objectives and measurable data are also vital in promoting an effective process of assessment. Other components or steps incorporate using a logic model to describe the intervention or program, formulating the project’s acceptability criteria, and developing required questions. In the proposed process, a goal-based method will apply. Subsequently, post-intervention, goals will be formulated or indicators of success, such as reducing the prevalence levels by 25% in the first three months. Behavioral changes, including nutritional awareness assessed by selecting at least three healthy diets after four weeks of community education, will be helpful.
The outcomes will focus on behavior and prevalence levels in the long-term from the example of community education and awareness. As described, after three months, disease prevalence at the community level will reduce by 25%. Additionally, behavioral aspects encompass correct exercise uptake, avoiding risky diets, and limiting lifestyle conduct, such a sedentary life that increases the disease’s risk and severity. As determined by the metrics, anthropometric measures, including waistline and weight, are also vital. As a standard and primary measure reducing BMI levels by at least 20% will indicate success and suggest the individual is making progress towards a healthy weight and avoiding obesity. As a result, outcome standards will focus on lifestyle behaviors, disease prevalence, and specific metrics or measures, such as BMI and weight reduction after participation.
CDC. (2019, September 11). Obesity evaluation measures. Centers for Disease Control and Prevention. https://www.cdc.gov/workplacehealthpromotion/health-strategies/obesity/evaluation-measures/index.html
Seral-Cortes, M., De Miguel-Etayo, P., Zapata, P., Miguel-Berges, M. L., & Moreno, L. A. (2021). Effectiveness and process evaluation in obesity and type 2 diabetes prevention programs in children: A systematic review and meta-analysis. BMC Public Health, 21(1). https://doi.org/10.1186/s12889-021-10297-8
Community Health Problem & Improvement Plan
Obesity is a complex community health problem in the United States. The issue results from various behavioral and genetic factors. Behavioral factors contributing to obesity include physical activity and inactivity, medication use, and dietary choices (CDC, 2021). Additional factors such as education and skills, socio-economic conditions can also predispose individuals to obesity. Obesity is a complex and severe community healthcare problem. The complication is associated with cardiovascular diseases. It is also associated with poor mental health and low life quality. Obesity affects every age group in the United States. The US experiences an increasing prevalence among all population segments. The US demographic forms part of developed nations’ populations whose obesity increase is estimated to be 30% higher than the prevalence in developing countries (Çakmur, 2017). Out of the 25% of overweight American children, 11% of them are obese. This increase places obesity at an epidemic level.
Analyzing an obesity healthcare improvement plan requires healthcare authorities to consider various aspects of the program. First, one can examining the physical activity environment to determine barriers and opportunities to accessing social reinforcement. The dietary environment assesses the availability, attractiveness, and affordability of healthy foods. The analysis includes healthcare and work environments where healthy diets, community support, and physical activities can be promoted. Lastly, the study should consist of the school environment where young people receive obesity education and healthy food and physical activity opportunities. Various outcome standards can also be measured. One of the outcomes is increased obesity research. Community obesity management plans should increase research into the causes, effects, and solutions for obesity. The analysis should include the strength of surveillance monitoring systems. Healthcare, government health agencies, and non0profit organizations should have robust programs that measure the prevalence and set solutions for the problem. Lastly, evaluating the plan should consider the problem prevalence within given timelines to determine success.
CDC. (2021). Adult Obesity. Centers for Disease Control and Prevention. Retrieved 28 March 2021, from https://www.cdc.gov/obesity/adult/causes.html.
Green, L., Sim, L., & Breiner, H. (2013). Evaluating obesity prevention efforts. The National Academies Press.
Çakmur, H. (2017). Obesity as a Growing Public Health Problem. Adiposity – Epidemiology and Treatment Modalities, 11-21. https://doi.org/10.5772/65718
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