The Epidemiologic Principles and Measures
The CDC addresses poor glucose control in diabetes type II patients over 45 who do not get self-management approaches by using several epidemiologic principles and measurements. The report includes information on risk factors, complications, and diabetes-related mortality, in addition to statistics on the incidence of diabetes in the United States. The report also includes recommendations for diabetes prevention and management.
At the national level, The CDC addresses the practice issue of poor glucose control in diabetes type II patients over 45 who do not get self-management approaches by using several epidemiologic principles and measurements. One of the key principles used is surveillance, which involves collecting, analyzing, and interpreting data on diabetes cases and deaths (Barros et al., 2020). This allows the CDC to identify trends and patterns in diabetes rates and monitor interventions’ effectiveness.
Another principle used is descriptive epidemiology, which describes the distribution of diabetes cases and deaths by demographic characteristics such as age, sex, race/ethnicity, and geographic location. This information is used to identify populations at the greatest risk for diabetes and to target interventions for these populations.
Measures used to address the practice problem include the prevalence and incidence of diabetes, which estimate the number of people in the United States who have diabetes and the number of new cases that occur yearly. The CDC also uses measures of diabetes-related morbidity and mortality, such as hospitalization rates and death rates, to comprehend how diabetes affects people’s health as a whole.
At the specific geographic level, the report provides data on diabetes by state and by county. This allows for identifying specific areas where diabetes rates are particularly high and interventions may be needed. For example, the report shows that diabetes rates are higher in southern states and some rural areas. This information can be used to target diabetes prevention and management efforts in these areas.
The use of Descriptive and Analytic Epidemiology
Descriptive epidemiology is used to identify patterns and trends in the occurrence of a disease or health condition in a specific population (Cataldo et al., 2019). This type of epidemiology is often used to identify the characteristics of a population that are associated with a higher or lower risk of a particular health outcome. When diabetes type II people over 45 years old have poor glycemia, descriptive epidemiology could be used to identify the demographic characteristics (such as age, gender, and socioeconomic status) of this population that are associated with poor glycemic control.
On the other hand, analytical epidemiology is used to investigate the relationship between a specific exposure (self-management techniques) and a specific health outcome, such as improved glycemic control (Cataldo et al., 2019). Analytic epidemiology could be applied to the PICOT question to determine whether self-management strategies enhance glucose control in diabetes type II patients over 45. This could be done through a randomized controlled trial, where patients are assigned to either a self-management technique group or a control group (receiving usual care). Their glycemic control is then measured over eight weeks.
The National Practice Problems that most affect the population selected in this project would likely include diabetes and cardiovascular disease, as these are major health concerns for older adults with diabetes. In terms of specific epidemiological reports published by the CDC, the “National Diabetes Surveillance System” (NDSS) provides data on diabetes prevalence and related health outcomes in the United States (CDC, 2022).
Using descriptive statistics can provide valuable insights into the individuals most affected by diabetes and other chronic conditions. One effective strategy for obtaining this information is analyzing surveillance systems data. By examining this data, it is possible to develop, implement, and evaluate programs that focus on diabetes. Additionally, analyzing correlational data can provide additional insights into how diabetes is impacting subpopulations. This information can then be used to develop specific interventions for these subgroups.
How you Might Use Surveillance to Influence the Determinants of Health
To use surveillance to change the factors that determine health and enhance the health of people with type II diabetes over 45, one approach would be to collect and analyze data on the prevalence of poor glycemic control in this population (Barros et al., 2020). This data could be collected through regular monitoring of patients’ blood sugar levels and HbA1c levels, as well as through surveys and interviews that gather information on patients’ self-management techniques and adherence to treatment regimens. Once this data is collected, it can be used to identify the specific determinants of poor glycemic control in this population, such as lack of access to self-management education, lack of access to appropriate medical care, and poor adherence to treatment regimens.
Based on this data, interventions can be developed and implemented to address these determinants and improve health outcomes. For example, educational programs and support groups could be developed to teach patients about self-management techniques and how to better adhere to their treatment regimens (Barros et al., 2020). Additionally, programs could be implemented to improve access to medical care, such as through telemedicine or community health clinics.
Regular population surveillance would then evaluate these interventions’ effectiveness and identify areas where additional interventions may be needed. In order to address the determinants of health and improve health outcomes in this demographic, it is essential to continue this process of data collecting, analysis, and intervention development.
Ethical Concerns Related to the Use of Surveillance Data
One potential ethical concern that might arise in using surveillance data for diabetes type II patients above 45 years of age is the issue of privacy and confidentiality. Patients may be hesitant to share personal information about their health status, particularly if they fear that their data could be used for purposes beyond improving their care (Mello & Wang, 2020). Additionally, surveillance data may raise concerns about discrimination or stigmatization if certain individuals or groups are disproportionately affected by the disease. To address these concerns, it will be important to ensure that patient data is collected and used in a manner that complies with all relevant privacy laws and regulations and that patients are fully informed about how their data will be used and who will have access to it.
PART B: RESPONSE
Reflect: The article uses epidemiological principles and metrics to present a thorough strategy for addressing Hialeah’s obesity rates. They recommend using analytical epidemiology to look into the connections between risk factors and obesity and descriptive epidemiology to determine the patterns, causes, and distribution of obesity in the population. The author also emphasizes the significance of culturally appropriate interventions that consider the particular requirements of the Hispanic community in Hialeah, including language barriers.
Inquire: I am interested in the methods used to collect data on the prevalence of obesity and risk factors such as diet and physical activity. Furthermore, I would like to know how the interventions will be tailored to the specific needs of the Hialeah Hispanic community, as well as what specific steps will be taken to address language barriers.
Suggest: More detailed information about the specific data collection methods that will be used in the descriptive and analytical epidemiology studies, as well as the specific steps that will be taken to implement the proposed interventions, could be outlined. This could include details on how the interventions will be tailored to the specific needs of the Hialeah Hispanic community, as well as how language barriers will be addressed.
Elevate: The author’s strategy for reducing obesity rates in Hialeah is commendable because it recognizes the importance of cultural specificity in any public health intervention. However, it would be beneficial to consider how environmental factors, such as urban planning and the presence of green spaces, affect obesity, as these are also very important. The author might also consider how obesity and other illnesses like diabetes, hypertension, and heart disease interact. The author may also consider how social determinants of health affect obesity rates and how to address them. Interventions that target the entire community rather than just a few individuals could also be included in the author’s plan.
References
Barros, J. M., Duggan, J., & Rebholz-Schuhmann, D. (2020). The application of internet-based sources for public health surveillance (infoveillance): systematic review. Journal of medical internet research, 22(3), e13680. DOI: 10.2196/13680. https://pubmed.ncbi.nlm.nih.gov/32167477/
Cataldo, R., Arancibia, M., Stojanova, J., & Papuzinski, C. (2019). General concepts in biostatistics and clinical epidemiology: Observational studies with cross-sectional and ecological designs. DOI: 10.5867/medwave.2019.08.7698. https://pubmed.ncbi.nlm.nih.gov/31596838/
CDC. (2022). Home – Access the United States diabetes surveillance system, an interactive web app that allows you to view diabetes surveillance data at national, state, and County levels. https://gis.cdc.gov/grasp/diabetes/diabetesatlas.html
Mello, M. M., & Wang, C. J. (2020). Ethics and governance for digital disease DOI: 10.1126/science.abb9045surveillance. Science, 368(6494), 951–954. https://pubmed.ncbi.nlm.nih.gov/32393527/
write