The Proposal
Vulnerability increases the likelihood of particular persons acquiring illnesses. The susceptibility may arise due to genes, poverty, cultural practices, environmental factors, etc. In this particular case, this essay conceptualizes on the risks factors that make diabetes prevalent amongst minority populations. The burden of the illness is much greater amongst the disadvantaged groups. What increases their chances of suffering from diabetes? What measures can alleviate the groups’ vulnerability to the disease? The illness also presents a challenge to health care providers who are aiming to enhance the medical outcomes of diabetes and prevent the disease. Diabetes management and prevention require individuals to engage in multiple health practices and behaviors involving physical activity as well as various practices that are shaped by a person’s values and culture (Chow, Foster, Gonzalez & McIver, 2012).
The appropriate mechanisms to improve health results need the incorporation of sound knowledge concerning cultural differences. The strategies are reasonable because health behaviors and beliefs thrive on cultural foundations. The integration of traditional beliefs is fundamental, especially when dealing with diverse populations. Medical practitioners often view the patients’ backgrounds as barriers to suitable care. With this proposal, the mindset of health professionals will change to realize that health disparities are culturally-based. Hence, if they aim to promote health equity, they should assess the different proportions of medical outcomes amongst various ethnical and racial groups within the population (Schneiderman, Llabre, Cowie, Barnhart, Carnethon, Gallo, & Teng, 2014).
Literature Review
Diabetes entails a devastating illness that erupts due to interdependent historical, cultural, social, genetic, and economic factors. The disease not only affects the life quality of a person, but also poses an enormous economic problem to the health care system. Much of the financial burden is related to the complications of diabetes like stroke, blindness, kidney failure, heart attack, and amputation. Ethnic and racial minorities such as Hispanics, African Americans, Pacific Islanders, Asian-Americans, and American Indians have a higher susceptibility to diabetes than the Whites. Also, within these minority groups, some have a higher prevalence of the illness than others (Zeh, Sandu, Cannaby & Sturt, 2014).
Study literature from the 1960s reports concerning ethnic and racial disparities in diabetes prevalence, quality of care, self-management behaviors, the presence of complications, and access to the care. Multiple disciplines proceed to evaluate underlying contextual, psychosocial, and biological explanations for the disparities for the purpose of formulating interventions and mechanisms that can promote health equity. Recently, the socioeconomic status has been identified as a strong determinant of the outcomes and status of diabetes. Hence, it can act as the underlying mechanism of eliminating the ethnic and racial disparities. In America and other countries, the ethnic and racial minorities have a higher susceptibility to the illness due to less education and low incomes (Chow, Foster, Gonzalez & McIver, 2012).
With the information on diabetes incidence among minority groups being larger, generally consistent and well-characterized literature of the long-term complications of the disease is not. Fewer reviews have been carried out concerning the complication of diabetes. They make general presumptions that the complication rates vary based on the type and the minority group. For instance, the prevalence of end-stage and early kidney illness is 4 times higher amongst the Blacks and 2.5 times higher in Hispanic populations than in Whites. Retinopathy rates are 3 times higher in Latinos and 2 times in African Americans than in the Whites. The primary limitation of adopting the socioeconomic status as a determinant is the oversimplification of the variable into crude indicators such as education and income. The socioeconomic status must be treated as a multidimensional aspect with several dimensions (Zimmet, Magliano, Herman & Shaw, 2014).
According to Schneiderman, Llabre, Cowie, Barnhart, Carnethon, Gallo & Teng (2014), estimations project that by 2025 over 300 million individuals in the globe will be suffering from diabetes with the largest proportions coming from the developing nations. The impacts of unmanaged diabetes can be detrimental to a person’s life. Based on the evaluation from the Centers for Disease Control and Prevention (CDC), diabetes is the primary cause of health issues due to the complications it introduces. Heath disparities are quite expensive, and their expense burdens should never be overlooked. The deviations of health care provisions in the minority groups have cost private insurers and Medicaid billions of dollars annually. Insurance is the basic reason for most medical disparities since the low-income communities cannot afford the services. The minorities also live in the rural regions that have fewer hospitals and health centers. Also, because of their poor state they cannot afford quality and adequate health care.
A national review or survey conducted between 2007 and 2009 indicates that for Americans who are above the age of 20, 8 percent Asian Americans, 13 percent Blacks, 7 percent Whites, and 12 percent Hispanos have diabetes. In the year 2010, of the 2.5 million individuals with diabetes, more than 8 percent were not diagnosed. In 2010, 18.7 percent Blacks and 10.3 percent Whites had diabetes. Diabetes is currently the sixth leading cause of deaths in the United States. In a healthy man or woman, blood sugar levels change with exercise, food intake, and many other factors. The levels are kept within an acceptable range by a fluid in the body that is produced by the pancreas called insulin. The insulin assists in the absorption of the sugars into the bloodstream. A person ailing from diabetes does not have adequate insulin to control the levels of blood sugar. Various research centers in the US focus on highlighting the disparities that prevent quality health outcomes and care of individuals from different ethnic and minority groups (Zeh, Sandu, Cannaby & Sturt, 2014).
The literature from the medical centers contributes a better comprehension of the types of complications and the prevalence of diabetes amongst minority populations. The identification of the elements that increase a person’s susceptibility to the illness will assist the health care system to reduce the disparities and barriers that limit suitable care processes amongst minorities. Medical interventions that consider population and cultural-specific characteristics can reduce the severity and spread of diabetes and its complications. Another factor that affects adequate access to healthcare is the rising ages and population in America. The population and age limit people from acquiring insurance, better services, and incomes. It is critical to address the risk factors, but what is even more important is the creation and investment in management and prevention initiatives that can help the underserved societies. Type 2 of diabetes is prevalent in the minority populations. Attempts should be made to evaluate the intervention programs to provide evidence concerning their effectiveness (Zimmet, Magliano, Herman & Shaw, 2014).
Methods
The volunteers include a convenient sample of adults who have self-reports of suffering from diabetes. The individuals were picked while attending Diabetes association fairs in the Northeastern part of the United States from 2013 to 2015. The project set up a booth with learning material concerning diabetes and a small space where the individuals could take part in filling in questionnaires. Trained study assistants handled the administration of the questionnaires, answered clarification questions, and compensated the volunteer a fee of 5$ for their time. The participants were also required to fill in consent forms before taking part in the exercise. Several measures were utilized to assess the participants and the information obtained from the questionnaires. The self-identified reports of the respondents were categorized into the following options: White, African American, European American, Hispanic, Asian American, American Indian, and Pacific Islander (Schneiderman, Llabre, Cowie, Barnhart, Carnethon, Gallo, & Teng, 2014).
The project also selected various socio-economic indicators to measure the participants. They include assets, education, engagement with the economic or financial system, financial strain, economic stability, and income. The examination of the socio-economic indicators required the respondents to provide estimates of their yearly income based on several ranges such as 0 to 10, 000 dollars, 40000 to 60000, etc. They had to record their highest learning attainments. The queries also involved whether the participants owned property, have ever had challenges paying electric bills, and their current financial statuses. The third measure in the study evaluates the diabetes complications. The questionnaires asked in layman dialect concerning physician diagnosis of medical conditions such as cardiovascular diseases, retinopathy, and nephropathy. The queries were retrieved from the U.S Disease Control and Prevention of Behavioral Risk Factor Surveillance System (Chow, Foster, Gonzalez & McIver, 2012).
The demographic characteristics were controlled by classifying age as a continuous variable, and insurance status and sex as the dichotomous indicators. The insurance status is mostly linked to the ethnic and racial disparities in diabetes health outcomes. Age was adjusted and calculated by ethnicity and sex. It was then stratified by BMI. The prevalence ratios obtained were examined using logistic regression while adjusting the indicators that are known to be associated with diabetes. The survey work took place during the weekdays from morning to afternoon when people attended the fairs. The queries also looked at the lifestyle and food consumption behaviors of the respondents. The comparisons of the Cohort structures of Socio-economic indicators and health disparity distribution was compared amongst the states used in the review. The cohorts were then adopted as a representative of the entire population in the United States (Zeh, Sandu, Cannaby & Sturt, 2014).
At the conclusion, the participants’ questionnaires, checklists, and procedures were evaluated for completeness. Additional information to support the results was acquired from health databases such as Center for Disease Control, MEDLINE, and the National Institute of Health. The search procedure involved looking for relevant information concerning diabetes and disparities amongst the ethnic and racial populations. Hence, the key worlds utilized in the databases were Diabetes Health Disparities, Health outcomes of the minority populations, and the risk factors that enhance the disparities amongst ethnic and racial groups. The search also involved identifying interventions instituted by the healthcare system to improve health equity amongst the ethnic and racial populations. The process also limited the information to the journals or articles published within the last five years (Zimmet, Magliano, Herman & Shaw, 2014).
Demographic Questions
The questionnaires included demographic questions that are vital to any survey. The queries are designed to assist researchers in determining the factors that may affect the participants’ opinions, interests, and answers. The collection of demographic data is useful in developing comparisons and cross-tabulations to see how the responses vary amongst various groups. For instance, this research involves different variables and populations that must be evaluated regarding the prevalence of diabetes. Hence, the demographic queries will enable the research to obtain the rates of diabetes amongst minority groups and the risk factors that increase their chances of acquiring the illness (Montesi, Caletti & Marchesini, 2016). Demographic study questions involve variables such as ethnicity, age, employment status, household compositions, family status, and education. Other demographic queries may include the geographical location, children in the household, family income, and religion. Since they are sensitive, the respondents should answer the questions privately, and they should not indicate their names on the questionnaires. The confidentiality will allow them to answer the demographic evaluations sincerely. The study adopted the following demographic queries:
At what particular age did you get diagnosed with diabetes?
20-30 years
31-40 years
41-50 years
51-60 years
Above 61 years
Race or ethnic origin: Please provide your ethnicity
White
European American
African American
Hispanic
Asian American
American Indian
Pacific Islander
Other
Education: What is the highest schooling level or educational attainment you have received?
No learning at all
Nursery school
Elementary school
Some section of high school without a diploma
Vocational training
Master’s degree
Doctorate degree
Professional degree
Job Status: Are you working currently?
Employed
Self-employed
Retired
Military
Unable to work
Not working
Marital Status: How can you classify your marital status?
Single
Widowed
Separated
Domestic Relationship
Married
Divorced
Appendices
Questionnaire
For ease of access and distribution, the questionnaire is available via the link below
https://docs.google.com/forms/d/15NeoOaKWlTnpyjCUjJM2SBF3PHSIn12krxycuKhjGzg/viewform
Techniques of Evaluating the Data
Flawed information can direct even the best scholars to realize wrong outcomes. When the success of a project hangs in the balance, one has to be sure that he or she is gathering the appropriate data using the right methods. The responses to the questions provided above will be collected in four primary ways to articulate the four types of information that are necessary to evaluate the results of the review. The data will be classified into four groups: ratio data, interval, ordinal and categorical. Categorical information involves calculating the number of answers and dividing them by the accumulated categories (Montesi, Caletti & Marchesini, 2016). The representation will provide the rough estimation of the success of the survey based on the responses given. The categorical data will be displayed in frequency or contingency table. Also, the project will request for feedback from the respondents to assess the ease of using the questionnaires and their quality. An example of mock frequency table is as follows:
(Relative) Frequency Table
Ordinal data is difficult to retrieve because it involves changing the responses into numerical values. The project will thus only categorize the close-ended questions under ordinal data based on the number of people who answered Yes/No. After that, the information will be grouped into intervals and represented using graphs to assess the number of individuals suffering from diabetes alongside their ethnic or racial origin. An example of a mock chart is as follows:
Research Consent Form
Health Promotion Research
In the acceptance of the consent form and signing of the document, you agree to:
•I have been provided and comprehended the description of the project.
•I have obtained the chance to ask queries and had them explained.
•I comprehend that I can withdraw from the project before the collection of information is finished and that my answers will be discarded immediately.
•I comprehend that my identity will remain secret
•I understand that I have the allowance of acquiring a copy of the proposal for evaluation and will have a week to give my remarks.
•I also comprehend that the project documents will be kept securely for three years after the experiment is concluded and then discarded
I accept to take part in the project.
I want the summary of the review: Yes/ No
Please provide your contact details and address to receive the summary
Recommendations
The proposal sheds lights concerning health disparities amongst minority groups. Suitable interventions are required to manage the health outcomes of the ethnic and racial populations to increase health equity.
References
Chow, E. A., Foster, H., Gonzalez, V., & McIver, L. (2012). The disparate impact of diabetes on racial/ethnic minority populations. Clinical Diabetes, 30(3), 130-133.
Montesi, L., Caletti, M. T., & Marchesini, G. (2016). Diabetes in migrants and ethnic minorities in a changing World. World journal of diabetes, 7(3), 34.
Schneiderman, N., Llabre, M., Cowie, C. C., Barnhart, J., Carnethon, M., Gallo, L. C., & Teng, Y. (2014). Prevalence of diabetes among hispanics/latinos from diverse backgrounds: the hispanic community health study/study of latinos (HCHS/SOL). Diabetes Care, 37(8), 2233-2239.
Zeh, P., Sandu, H. K., Cannaby, A. M., & Sturt, J. (2014). Cultural barriers impeding ethnic minority groups from accessing effective diabetes care services: a systematic review of observational studies. Diversity and equality in health and care, 11(1), 9-33.
Zimmet, P. Z., Magliano, D. J., Herman, W. H., & Shaw, J. E. (2014). Diabetes: a 21st century challenge. The lancet Diabetes & endocrinology, 2(1), 56-64.
