final paper

In 2015, 30.5 million Americans were diagnosed with diabetes mellitus (American Diabetes Association, 2017). By 2050, the prevalence of Americans with type 2 diabetes is projected to increase from 14% to 33% (Banerji & Dunn, 2013). Diabetes mellitus affects approximately 415 million people worldwide and is estimated to increase to 642 million by 2042, according to the Standards of Medical Care in Diabetes-2016 (Chawla, Chawla and Jaggi, 2016).

To improve the quality of life of an individual with type 2 diabetes and encourage their healthcare visits, recommendations of evidence-based guidelines have suggested several diabetes intervention modules, which if used, can prevent diabetes or further illnesses (Dunkley et al., 2014). This chapter describes the introduction, problem statement, research question, hypothesis, purpose of the study, along with the theoretical framework, significance of the study, as well as the delimitations that all to support the need for intervention, prevention and education for individuals with type 2 diabetes to assist in managing their glycemic levels.

Glycemic level is considered optimal at < 7.0% and suboptimal at > 8.0% or more for adults between the ages of 18-64 years old (Samancioglu, Surucu, Donmez and Cevik, 2017).

A suboptimal glycemic level > 8.0% or more occurs when type 2 diabetics’ insulin levels are lower than the recommended optimal glycemic level. Displaying the associations between glycemic control (optimal versus suboptimal) and healthcare visits will provide the healthcare industry, as well as scholars, with factual information which can assist individuals with type 2 diabetes to maintain control of their glycemic level.

The glycated hemoglobin (HbA1C) test is a blood test measuring glucose levels in the blood stream; the blood test measures glucose level variance over an average period of 3 months (Albers & Pop, 2010). It is imperative for those with type 2 diabetes to monitor their glycemic levels. Maintaining an optimal glycemic level can prevent future complications in individuals with type 2 diabetes (Rodríguez-Gutiérrez and Montori, 2016). A suboptimal glycemic level will be a contributor to mortality and morbidity if those who have the disease are not proactive with their medical responsibilities (Banerji & Dunn, 2013).

Healthcare visits provide individuals with type 2 diabetes mellitus with diabetes information, education, support, prevention tools and medical treatment, including testing, results, medication, medical equipment, therapy, counseling and other treatments, resulting in positive health outcomes (Evert, 2014; Franz, 2010; Group, 2002). Individuals who are diagnosed with diabetes must be monitored by a Physician Assistant (PA), Nurse Practitioner (NP) and/or healthcare professionals who is licensed to assist individuals with diabetes to improve the quality of care (Everett, Thorpe, Palta, Carayon, Bartels & Smith, 2013).

Healthcare visits provide individuals with type 2 diabetes tools to manage the variables that affect diabetes complications. Medication adherence, positive nutrition, and, more importantly, blood glucose monitoring are among some of the variables that must be managed to avoid diabetes complications (Sontakke, Jadhav, Pimpalkhute, Jaiswal & Bajait, 2015). Healthcare is necessary for these vulnerable individuals; however, some individuals cannot afford medical care, causing them to neglect their medical needs (Banerji & Dunn, 2013). Attending healthcare visits is imperative for individuals with type 2 diabetes to receive the assistance needed to maintain control of their glycemic level.

Individuals with type 2 diabetes seem to lack awareness, decision-making, and communication about their medical care (Fürthauer, Flamm & Sönnichsen, 2013). However, research suggests that people with diabetes would like to be included in evidence-based medical treatment decisions regarding their diabetes care (Fürthauer, Flamm & Sönnichsen, 2013). Seeking associations between glycemic control and healthcare visits will provide the healthcare field with factual information that can benefit millions of Americans.

The prevalence of individuals with a suboptimal glycemic level has increased diabetes mortality, as approximately one million Americans are diagnosed with diabetes every year, contributing to over 250,000 deaths per year (American Diabetes Association, 2017). Managing glycemic level can make the difference between life and death for millions of individuals with diabetes worldwide. This study will provide findings to support the need for diabetes policy changes to support intervention, prevention, including diabetes education and self-management tools for individuals with type 2 diabetes which is needed to maintain an optimal glycemic level.

Research Question

What is the association between glycemic control (optimal versus suboptimal) and healthcare visits among individuals diagnosed with type 2 diabetes?

Hypothesis

Ha: There is an association between glycemic control (optimal versus suboptimal) and the number of healthcare visits in people with diabetes mellitus.

Ho: There is no association between glycemic control (optimal versus suboptimal) and the number of healthcare visits in people with diabetes mellitus.

Purpose of the Study

This thesis will assess men and women ages 18-79 years old diagnosed with type 2 diabetes and the dependent variable glycemic control (optimal versus suboptimal) and the independent variable of healthcare visits. Through a quantitative cross-sectional analysis of secondary data the findings will contribute to the knowledge of diabetes research required to battle one of the deadliest diseases of the 21st century.

Significance of the Study

A suboptimal glycemic level contributes to negative health outcomes which remain a barrier for individuals with type 2 diabetes, especially for those who have not adapted to controlling their glycemic level (Banerji & Dunn, 2013). The purpose of the study sought to contribute to diabetes healthcare literature by producing several associations between glycemic control (optimal versus suboptimal) and healthcare visits.

Delimitations

The quantitative study will provide results from 709 individuals diagnosed with type 2 diabetes between the ages of 18-79 years old from the United States. The NHANES 2013-2014 survey was utilized in this research, all other NHANES surveys were excluded from this study. Participants with pre-diabetes or type 1 diabetes were excluded from the survey. Participants were surveyed based on their gender, ethnicity, education and marital status, HbA1C level and number of healthcare visits.

Definitions

Glycemic control - is a medical term referring to positive typical blood sugar (glucose) level; Optimal (<7.0 %) and Suboptimal (>8.0%).

Healthcare visit- medical visit to a doctor, dietitian, endocrinologist, healthcare professional, nutritionist, nurse, nurse practitioner, physician, podiatrist, registered nurse or therapist

HbA1C test - glycated hemoglobin or glycosylated hemoglobin, is a blood test that correlates with a person’s average blood glucose level for an approximate time of 3 months

Self-care behaviors- any activity done deliberately in order to take care of mental, emotional, and/or physical health

Self-management- management of or by oneself; taking of responsibility for one's own behavior and well-being that is acceptable to society

Type 2 diabetes mellitus- a heterogeneous disease, occurring mostly in adults, also called adult-onset or noninsulin-dependent diabetes, an enduring illness affecting the manner a body metabolizes sugar

Summary

This chapter described the foundation of the study by providing background knowledge of glycemic level (optimal versus suboptimal) and healthcare visits. Researching the associations that link the variables of glycemic control and healthcare visits of individuals with type 2 diabetes can prevent complications if glycemic control is achieved and risk factors are avoided. The need to associate glycemic control (optimal versus suboptimal) levels with healthcare visits will allow for individuals factual evidence to make positive decisions regarding their diabetes care.

Literature Review

This chapter will describe how several articles examine the association of glycemic control (optimal versus suboptimal) and healthcare visits of individuals with type 2 diabetes. One significant tool in the research on diabetes is the National Health and Nutrition Examination Survey (NHANES) survey, which provides data on the prevalence and trends of disease (Wang, Lopez, Bolge, Zhu and Stang, 2016). There were several terms- glycemic control (optimal versus suboptimal) and healthcare visits, as well as HbA1C were all searched and utilized in the research.

Prevalence of Type 2 Diabetes

Menke, Casagrande, Geiss, and Cowie (2015), studied several NHANES surveys from 1988- 2012 to assess the trends and prevalence of diabetes. NHANES III, which is an older survey instrument, was used to collect data between the years of 1998-1994. Since 1999 NHANES began collecting data for 2-year periods. Assessments were conducted in 1988-1994, 1999-2000 and 2011-2012 by NHANES III and NHANES, in mobile examination facilities and interviews in the homes of randomly chosen participants (Menke, Casagrande, Geiss & Cowie, 2015). Participants ranged from the ages of 20 to 44 and 45-64 years old, with an overweight bracket of 0.4561 and 0.1766 kilograms, to allow for a standardized sample of the population (Menke, Casagrande, Geiss, & Cowie, 2015).

Researchers found the average percentage hemoglobin HbA1C was 14.3% for individuals diagnosed with diabetes. The results showed an increase of uncontrolled glycemic levels from 9.8% in 1988-1994 to 12.4% in 2011-2012 and a decrease from 12.5% in 2007-2008 to 12.4% in 2011-2012, also results disclosed a direct increase of individuals diagnosed with diabetes from 1988-1994 and 2011-2012, and in 2011-2012 (Menke, Casagrande, Geiss & Cowie, 2015).

Glycemic Complications

Results showed both positive and negative outcomes. From 2006-2007 the majority (70-100%) of articles were in favor of there being a coloration between glycemic levels and micro/macrovascular disease and (95%) of procedures favored an association between variables (Rodríguez-Gutiérrez & Montori, 2016). However, between 2008-2015 only 21%-36% of all literature agreed that glycemic control plays a role with micro/macrovascular disease and changed the direction of studies to come (Rodríguez-Gutiérrez & Montori, 2016). Assisting, monitoring and improving the outcomes of the type 2 diabetes mellitus population can stabilize their glycemic levels (Rodríguez-Gutiérrez and Montori, 2016). Visiting a healthcare facility can avoid such diabetes complications, for this reason the need for additional research on the association of glycemic control and healthcare visits will contribute to limited knowledge if these variables can be connected.

Healthcare Visits

Everett, Thorpe, Palta, Carayon, Bartels and Smith (2013) conducted a study to evaluate the practice of patient diabetes care provided by Physician Assistant (PA), Nurse Practitioner (NP), and physicians, as well as healthcare service procedures. Researchers collected data from Medicare patients’ electronic health records, at one medical facility in a rural area of the Midwestern, United States (Everett et al., 2013). Patients who were chosen for the study included 2,576 individuals with diabetes mellitus between the ages of 23-102 years old; of those 91% were Caucasian and 50% female (Everett et al., 2013). Healthcare professionals included, Residential Physicians (51), Attending Physicians (210), PAs (24), and NPs (28); all of whom cared for patients seen by facility within the medical organization during 2008.

Research examined the participants’ diabetes healthcare visits within a year and their HbA1C test results from their last two medical visits and healthcare service procedures were measured by patient emergency visits and hospitalizations (Everett et al., 2013). The study defined the level of care provided by a PA and NP, who shared the same job duties and provide similar care based on medical involvement in patient care, level of chronic care and severity of patient illness (Everett et al., 2013). Results from the multi-variable and multinomial logistic regression models were used in the study, limiting the analysis as the sample size was too small to suggest results for an entire diabetes population (Everett et al., 2013). Also, the roles of a PA and NP may vary based on the needs of the patient and medical organization for whom they are providing care (Everett et al., 2013).

Findings show that of the 261 medical facilities that were measured, PAs or NPs provided 55% of medical care, while 39% of physician were the sole healthcare provider in the same facilities, the remaining 6% were missing this information (Everett et al., 2013). Sixty-two percent of patients were seen by a PA, NP or physician and had two or more HbA1C test and 50% had an optimal glycemic level. Overall, the study did not show enough evidence that one healthcare provider had a greater impact on the diabetes care of the patient. Everett et al. (2013), suggested the need, for a replicated study with a larger population would potentially provide a broader evaluation of the affects’ health providers have on assisting individuals with diabetes mellitus to become healthier through medical care (Everett et al., 2013).

Glycemic Control (Optimal Versus Suboptimal)

Rodríguez-Gutiérrez and Montori (2016), researched approximately 15 guidelines in over 328 journals, and articles on testimonials from both individuals with type 2 diabetes, with controlled and uncontrolled glycemic levels and examined the effects of a lack of glycemic control on medical diabetes complications. Additionally data collected through randomized clinical trials (RTCs) along with software from the OpenMeta Analyst and a rating system of low, moderate and high was used to assess the influence of glycemic control on diabetes complications (Rodríguez-Gutiérrez and Montori, 2016). The sample size of all trials consisted of articles from 5 medical journals from January 2006 through March 2015, searching the term glycemic control and excluding articles that did not use contemporary medical treatment (Rodríguez-Gutiérrez and Montori, 2016). Trials such as ADVANCE and ACCORD were used in this study, as well as the Grading of Recommendations Assessment, Development and Evaluation (GRADE) to ensure that the reliability, honesty and unbiased risk factors in the statements were accurate (Rodríguez-Gutiérrez and Montori, 2016). The GRADE trial rated data between the years of 2006-2009, and found that glycemic control had a moderate effect on risk of micro/macrovascular heath. The ADVANCE trial, conducted between the years of 2006-2015, found that those who had glycemic control showed a 65% decrease in end-stage renal disease (ESRD), accepting the theory that glycemic control can reduce diabetes complications (Rodríguez-Gutiérrez and Montori, 2016). In 2008, the ACCORD trial changed the perception of glycemic control and diabetes complications, as those publications agreed that glycemic control had an association specifically to the micro/macrovascular disease decrease to 21%. Glycemic control has a positive effect on reducing the chance of diabetes complications, which can lead to death. As one of more the top ten causes of death in 2015, approximately 79,000 deaths claimed to have been due to complications from diabetes (Statistics about Diabetes, 2017).

Health Behaviors/Treatment Belief

Arx, Gydesen & Skovlund (2016) examined the predictability of health behaviors and the treatment belief outcomes, which display the quality of care provided by healthcare professional to patients. The treatment belief outcomes of individuals with type 2 diabetes mellitus residing in Funens, Denmark were measured by their glycated hemoglobin level, lipid profile and blood pressure (Arx, Gydesaen and Skovlund, 2016).

In 2003, the disease registry Funens Diabetes Database (FDDB) was founded, its registry consisted of 9000 individuals with type 2, who were insulin users and had been treated by ophthalmologists and/or general practitioners. A total of 3,160 where chosen to participate in the survey. Received via postal service, 1031 participated. The researchers sought to identify the differences of behaviors and beliefs the participants possessed regarding their diabetes care through a cross sectional study.

Although more than half were comfortable with their HbA1C level being below 7.5%, results show 4% had no knowledge what their HbA1C level represented. Of those that participated, 34% felt there was a need for concern regarding their treatment beliefs, and 22% felt treatment provided little improvements to their health; 12% felt lack of income resulted in them avoiding health treatment.

The results showed that the average respondent were male, averaging 67 years old and who had been diagnosed with type 2 diabetes for over 10 years; 60% of Danish men responded; more than half had high blood pressure; 69% had a high school degree and 75% earned less than $40,000. Participants of the study were 1/3 of the population limiting the results (Arx, Gydesaen and Skovlund, 2016).

Summary

The literature reviewed in this chapter shows how previous, as well as recent studies utilizing the NHANES surveys, provide factual data on association between glycemic control and healthcare visits. While research has suggested there are associations between glycemic control (optimal versus suboptimal) and healthcare visits, further research will shed light on what factors play a role between variables. In addition, the articles in this literature review bring to light the need for intervention, prevention and education for individuals with type 2 diabetes to manage their glycemic levels.

Methods

This chapter describes the methodology that is used to assess if there is an association between glycemic control (optimal versus suboptimal) and healthcare visits, of individuals with type 2 diabetes mellitus. The chapter describes the individual demographics, the survey instruments for data collection, the procedures, the data analysis plan and ends with the ethical considerations.

Study Design

This is a cross-sectional analysis of secondary data collected in the National Health and Nutrition Examination Survey (NHANES 2013–2014).

Study Sample

The sample consist of data extracted from the NHANES which assessed the health and nutritional status of adults and children in the USA. Each year the survey examines a nationally representative sample across the country. This study will examine a population of males and females who self-reported a type 2 diabetes diagnosis. The study includes those adults who answered the diabetes section (prefix DIQ) which provides personal interview data on demographics of individuals with type 2 diabetes, healthcare visits, and eye exams. The study sample includes those adults ranging from 18-79 years of age. The total population of individuals who were initially given the survey were 9,770. The final sample size consisted of 709 individuals self-reporting being diagnosed with type 2 diabetes.

Exclusion Criteria

Excluded from the DIQ survey were any questions related to prediabetes, impaired fasting glucose, impaired glucose tolerance, borderline diabetes, and questions asking, “is your blood sugar higher than normal but not high enough to be called diabetes or sugar diabetes” (NHANES 2013-2014 Questionnaire Data, 2015). Those excluded from participating in the survey were males and females under the age of 18 and pregnant woman who reported having a diagnosis of gestational diabetes. Based on the survey details participants provided informed consent prior to completing the survey, and were able to read and understand the English language.

Data Collection

Demographical Characteristics and Glycemic Control Assessment. Data was collected from the Hospital Utilization and Access to Care Survey 2013-2014 Survey Questionnaire (NHANES 2013-2014 Questionnaire Data, 2015). The demographic characteristics such as gender, age, ethnicity, education and marital status will be included in the analysis. Healthcare visits related to diabetes will be assessed using the HbA1C test included to assess glycemic control. Glycemic control is defined as optimal at <7.0% versus suboptimal at ≥8.0% or more.

The main question determining an optimal glycemic level is “What was your last A1C level?” Other questions in the survey were designed to knowledge level and association to glycemic control define such, “Has a healthcare professional told you that retinopathy has affected your eyes diabetes?” (see Appendix A).

Healthcare Visits Assessment. Included in the survey were questions on the independent variable, healthcare visits, which searched for the answer to “Is there one doctor or other health professional you usually see for your diabetes?” (NHANES 2013-2014 Questionnaire Data, 2015). This question assessed if healthcare visits can potentially have an association on individuals being able to maintain an optimal glycemic level.

Studies show individuals with type 2 diabetes that visit a hospital are at a higher risk to be hospitalized due to concern of their noncompliance to diabetes care (Korbel & Spencer, 2015). These findings will provide data to suggest tools that if applied, will assist individuals with type 2 diabetes to control their glycemic levels, especially for those that do not usually see a doctor or healthcare professional for their diabetes.

Covariates. The secondary variables or covariates which may influence the results of the study are age, gender, ethnicity, educational background, and marital status.

Research Design

A total of 709 subjects were obtained from the National Health and Nutrition Examination Survey (NHANES) from 2013-2014. Men and women between the ages of 18-79 years old residing in the United States were chosen from various races and locations across the United States.

Data Analysis

All the data was organized in an excel file and then exported to SPSS (v. 24.0) to provide the results to ten questions asked in an organized questionnaire. The dependent variables of glycemic control optimal at <7.0% versus suboptimal at ≥8.0% or more and the independent variable healthcare visits, along with several demographic variables such as age, gender, ethnicity, education and marital status will be used to describe the sample of individualities.

The data collected in 2013-2014 by NHANES survey, will assist in calculating diabetes prevalence, also, will be utilized to explore if there are any associations between glycemic control (optimal versus suboptimal) and healthcare visits among people with type 2 diabetes. The quantitative analysis will interpret the findings of the demographic variables, the dependent variable of glycemic control (optimal versus suboptimal) and the independent variable of healthcare visits have on those that were chosen to participate in this study.

First, the demographical characteristics of the sample will be assessed. For example, males and females, will be coded as (male = 1) and (female = 2), all categorical variables on the questionnaire are numerically coded, questions as, “Is there one doctor or other health professional you usually see for your diabetes yes = 1, no = 2, refused = 7 and don’t know = 9. The sample size ranges between the ages of 18-79, which are included as a continuous category.

Individuals completed a standardized survey on healthcare utilization, information provided by a healthcare visits, HbA1C test and glycemic levels. The steps needed to complete the study will be analyzing each category of the survey.

Ethical Considerations

The ethical ramifications were limited due to the type of data that was obtained. Data was extracted from the website of Center for Disease Control and Prevention- National Center for health Statistics (2017). The data extracted from the internet was secured on a USB drive and stored in the office of the thesis advisor.

Results

Presented in this chapter are the results of an analysis of secondary data from NHANES 2013-2014, which assessed the association between glycemic control (optimal versus suboptimal) and healthcare visits among individuals diagnosed with type 2 diabetes mellitus. This chapter will detail the results of the individuals’ glycemic control levels (optimal versus suboptimal) and the association between healthcare visits and their demographic characteristics. All individuals who participated were questioned on their demographics included gender, age (range of 18-79 years old), educational background, and marital status.

The sample size of ethnicity was divided into two categories: Minority (Mexican American/ Hispanic/Black/Asian/Other Multi-Race) and White. Also, questioned was their HbA1C level to determine if they had glycemic control (optimal versus suboptimal) present during the survey. Included in the criteria were significant questions that examined the associations between their demographic covariates, their glycemic control (optimal versus suboptimal) while attending recommended annual healthcare visits.

Demographical Characteristics

The demographic characteristics of male and females led to a sample size of 709, comprised of the male population 336 (49.2%) and female 347 (50.8%) with 26 (3.8%) missing as shown in Table 1. The age range of the chosen participants was between 18 and 79 years old (M=61.67 and SD= 9.47). The ethnicity of the individuals were 434 (63.5%) Minority and 249 (36.5%) White, with 26 (3.8%) missing. The educational category consists of 102 (14.9%) who had less than a 9th grade education, 113 (16.5%) who attended 9th to 11th grade, 163 (23.9%) who graduated High School/ GED, 197 (28.8%) who had some college, 106 (15.5%) who graduated college, 2 (.3%) and were missing from the results. The sample by marital status 383 (56.1%) married, 102 (14.9%) widowed, 95 (13.9%) divorced, 24 (3.5%) separated, 62 (9.1%) had never been married, and 17 (2.5%) were living with a partner and 26 (3.8%) missing.

Also illustrated in Table 1 is the HbA1C level representing an optimal < 7.0% and a suboptimal level >8.0% or more for adults over 18 years old. The laboratory outcomes of individuals’ HbA1C level produced 254 (35.8%) optimal glycemic control (optimal) and 429 (60.5%) uncontrolled glycemic levels (suboptimal), with 26 (3.7%) missing. The majority of individuals with type 2 diabetes who were surveyed had suboptimal glycemic levels and require intervention, education, and supportive preventive measures to become healthier individuals.

Table 1

Demographical Characteristics of Individuals Diagnosed with Type 2 Diabetes (n=709)

Note: n=26 variable for Missing*, Gender (n=26), Ethnicity (n=26), Education (n=2), Marital Status (n=26), A1C level (n=26)

Healthcare Visits

Table 2 provides specific results from the survey’s five questions related to healthcare visits within a year among participants to seek if any association can be correlated to glycemic control and healthcare visits.

Of the questions asked, “Was there one doctor or healthcare professional you usually see for your diabetes”, those with an optimal level 174 (68.5 %) answered yes and 80 (31.5%) answered no. Individuals with a suboptimal level 347 (80.9%) answered yes and 82 (19.1%) answered no, 26 (3.8%) were missing.

Results from the question, “Have you had one or more healthcare visits in the past year”, showed those with an optimal level 173 (68.1%) had a visit and 80 (31.5%) did not, 1 (.4%) was missing from the sample. Those that had a suboptimal level 339 (79.0%) had a visit within the year and 82 (19.1%) did not, the remaining 8 (1.9%) individuals were missing.

This research asked, “Has a doctor ever told you that diabetes has affected your eyes or that you had retinopathy”? Individuals who had an optimal level, 41 (16.1%) said yes and 211 (83.1%) said no, 2 (0.8%) were missing. Of those with a suboptimal level, 103 (24.0%) said yes and 322 (75.1%) said no, 4 (0.9%) were missing.

Also asked, “When was the last time you had an eye exam in which the pupils were dilated”? Notably, of those who had a visit within a year with an optimal level, 192 (75.6%) had an exam where their eyes were dilated while 62 (24.4%) had an eye exam where their eyes were dilated more than two years ago. Individuals having a suboptimal level, 326 (76.0) had an exam where their eyes were dilated while 103 (24.0%) had an eye exam where their eyes were dilated more than two years ago.

The question “When was the last time you visited a diabetes specialist, nurse educator, dietitian, or nutritionist for your diabetes, but not a physician”? generate the following results: Individuals with an optimal level who had a visit, 81 (31.9%) one year ago or less, 28 (11.0%) more than one year ago but no more than two years were, 28 (11.0%) more than two years ago but no more than five years were, 33 (13.0%) more than five years and 84 (33.1%) never. Individuals who had a suboptimal level, 174 (40.6%) one year ago or less, 30 (7.0%) more than one year ago but no more than two years were, 40 (9.3%) more than two years ago but no more than five years were, 60 (14.0%) more than five years, 122 (28.4%) never and 3 (0.7%) were missing.

Table 2

Healthcare Visits of Individuals Diagnosed with Diabetes Mellitus (n=709)

Note: Usual Visits (made recommended diabetes healthcare annual visits), n=26 variable for Missing/ Never/*

Bivariate Association between Glycemic Control (optimal versus suboptimal)

Presented in the following tables are the bivariate analyses results of the individuals demographic characteristics and the association with glycemic control (optimal versus suboptimal) among those who had a healthcare visit within a year.

Table 3 reveals the demographics of the individuals with type 2 diabetes who were chosen for this study, those with an optimal level 103 (40.6%) male and 151 (59.4%) female participated as well as those with a suboptimal level 233 (54.3%) male and 196 (45.7%) female. Illustrating a 12.088 chi-square result and p-value of 0.001 rejecting the null hypothesis, resulting in a high significance.

Minorities lead in both optimal and suboptimal levels, 163 (64.2%) had an optimal level and 271 (63.2%) had a suboptimal level. 91 (35.8%) Whites had an optimal level and 158 (36.8%) had a suboptimal level, showing a far lower level by almost more than half of Minorities. The value of insignificance between the two glycemic levels categories were 0.69, with a chi-square value of 0.792 and a degree of freedom of 1.

The educational portion of the results varied, of those with an optimal level, 33 (13.0%) had less than a 9th grade education; 47 (18.5%) attended 9th to 11th grade; 61 (24.0%); graduated High School/ GED; 75 (29.5%) had some college; 37 (14.6%) were college graduates; and the percentage of those missing were 1 (0.4%). Of the individuals with suboptimal level, 69 (16.1%) had less than a 9th grade education; 66 (15.4%) had attended 9th to 11th grade; 102 (23.8%) graduated High School/ GED; 122; (28.4%) had some college; 69 (16.1%) were college graduates and 1 person at 1 (0.2%) was missing. A chi-square test value of 2.406, a statistically insignificance of 0.791 and degree of freedom = 5.

Table 3

Association between Demographical Characteristics and Glycemic Control (Control Versus Uncontrolled) of Individuals Diagnosed with Type 2 Diabetes n=709

Note: Never (n=0.4%) variable for Missing*

Table 4 displays the bivariate results which shows the association among the five questions related to glycemic control (optimal versus suboptimal) and healthcare visits. A total of 521 (76.3%) individuals said yes to usually being seen by a doctor or healthcare professional (2-3 times a year) healthcare visits for their diabetes, while 162 (23.7%) said no. Of those that had an optimal level, 25.5% responded yes and 11.7% responded no. Individuals with a suboptimal level 50.8% answered yes and 12.0% answered no. Results showed X2 = 13.519, rejecting the null hypothesis, as results show a high significant of 0.000 and degree of freedom of 1.

A third of the individuals, 512 (75.0%), had a healthcare visit within a year, as opposed to 163 (23.7%) who did not. Those with an optimal level, 25.3% had a visit within the year and 11.7% did not. Those with a suboptimal level, 49.6% had a visit and 12% did not. The value of the chi-square test score, 15.466, with a high value of significant 0.000 and degree of freedom =2 Therefore, accepting the null hypothesis.

Of those who responded to being told diabetes has affected their eyes/retinopathy; 144 (21.1%) said yes, 533 (78.0%) said no, and 6 (0.9%) were missing. The optimal level of respondents, 6.0% stated yes and 30.9% said no with 0.3% missing. The suboptimal level, 15.1% stated yes, 47.1% said no, while 0.6% were missing. The chi-square results displayed a probability of 6.035, significant value of 0.049 and degree to vary of 2. Notably there were association between healthcare visits and glycemic control (optimal versus suboptimal) rejecting the null hypothesis.

Results from the question regarding the last time they had a healthcare visit for an eye exam where their eyes were dilated; 518 (75.8%) had eyes dilated and 165 (24.2%) did not have their eyes dilated in more than two years. Of those with an optimal level, 28.1% had an eye exam where they eyes were dilated, 9.1% had not had an eye exam in more than two years. The suboptimal results show 47.7% had their eyes dilated within the year and 15.1% had not. The chi-square test results, showed a value of .014, an insignificant value of 0.906 and degree to vary of one.

Table 4 also shows the total participants who had a diabetes related visit with a diabetes specialist, nurse educator, dietitian, or nutritionist, excluding a physician. Of those 255 (37.3%) who had a healthcare visit within one year or less; 58 (8.5 %) more than one year ago, but no more than two years; 68 (10.0%) more than two years ago, but no more than five years, 93 (13.6%) more than five years; 206 (30.2%) never had a visit and 3 (0.4%) were missing responses for. Individuals with optimal level who had a visit, 11.9% had one visit year ago or less; 4.1% more than one year ago, but no more than two years; 4.1% more than two years ago, but no more than five years; 4.8% more than five years; 12.3% never had a visit. The suboptimal results show, 25.5% had a visit one year ago or less; 4.4% more than one year ago but no more than two years; 5.9% more than two years ago but no more than five years; 8.8% more than five years; 17.9% never had a visit and 0.4% were missing. Resulting in a chi-square test result of 9.754 and an insignificant value of 0.083 and a degree of freedom 5, accepting the null hypothesis.

Table 4

Association between Healthcare Visit and Glycemic Levels (Control Versus Uncontrolled) of Individuals Diagnosed with Type 2 Diabetes n=709

Note: Usual Visits (made recommended diabetes healthcare visits every 3 months), Diabetes and Eyesight (n=0.3%) variable for Missing*, Last Visited a Diabetes Specialist/Nurse Educator/ Dietitian or Nutritionist (excluding physician)*, 206 (n=12.3%) (17.9%) variable for Don’t Know *, 3 (n= 0.0%) (0.04%) variable for Never *, Significance (n=<0.05)*

Association between Glycemic Control and Healthcare Visits

The results of the study illustrate a variation of association between glycemic control (optimal versus suboptimal) among individuals who had a healthcare visit within a year. Of the gender category, females had a greater level of glycemic control than males by 18.8% and males had a greater level of uncontrolled glycemic levels than females by 8.6%. Minorities had a greater level in both optimal and suboptimal levels, with an optimal level 28.4% greater than whites and a suboptimal level (26.4%) also greater than Whites.

In every educational category, the difference among optimal and suboptimal levels was less than 4% with no consistent evidence of any level of significance. Within each marital status category the majority show optimal glycemic levels, except for those that were married. There is a higher level of suboptimal glycemic level than an optimal level by 7.8%.

The healthcare visits data shows that, overall, most individuals had their usual healthcare visits by 52.6% over those that did not; (588) half of the participants had their usual healthcare visit and had suboptimal levels. Within the last 12 months, the majority (75%) had healthcare visits. Also, 56.9% of individuals had not been told diabetes has affected their eyesight or had retinopathy. Those who had their eyes dilated within a year surpassed those who had not had an eye exam where their eyes were dilated in over two years by 51.6%. Those who had visited a diabetes specialist/ nurse educator/ dietitian or nutritionist excluding a physician within a year surpassed all other timing categories by more than 23.0%. 30.2% of participants had never had a visit with a diabetes specialist.

Summary

This study set out to find the association between glycemic control (optimal versus suboptimal) and healthcare visits among individuals diagnosed type 2 diabetes, it is evident that individuals waited till they became ill to visit a healthcare professional for their diabetes. Of the ten questions, four rejected the null hypothesis and the other six accepted the null hypothesis. The demographic question regarding gender and three healthcare visits questions, usual diabetes visits, healthcare visit within a year and retinopathy eye exam, showed a significant score. An alpha level of <0.05 was established as the level of significance utilized in all hypotheses testing.

Overall, of the 709 individuals with type 2 diabetes, regardless if they had a healthcare visits, still had a far greater percentage of a suboptimal level than those that did have optimal levels. Findings suggesting that overall men had a higher suboptimal level than females. The difference of percentage among individuals with optimal glycemic levels who did not have the usual recommended annual visits was more than 60%. Similar results showed in the percentage of individuals who had at least one diabetes healthcare visits with optimal glycemic levels, resulted in 37% more than those that didn’t not have a healthcare visit. Of the eye exams, most individuals had not been told diabetes had affected their eyes, still had a higher suboptimal level by 9.1% and those that had their eyes dilated within a year had a 32% increase over those that had not had their eyes dilated in over two years.

Discussion Conclusion and Recommendations

Discussed in this chapter is a description of the results along with evidence-based programs recommended for prevention, diabetes/medical coverage, education, diabetes policies and future studies to seek if more associations can be made to glycemic control and healthcare visits. If applied, the lives of many individuals will improve by assisting with glycemic control as well as prevention of the diabetes disease. Summarized in the conclusion section are all pertinent information provided in Chapter 5.

The research provides data on several questions regarding glycemic control to answer the research question: What is the association between glycemic control (optimal versus suboptimal) and healthcare visits among individuals diagnosed with type 2 diabetes. The purpose of the study provides association between variables that can be managed for positive health outcomes. By seeking to find any association between glycemic control and healthcare visits can potential reduce the chances of individuals with diabetes of acquiring diabetic complications, as well as assist them in glycemic control management for a prolonged healthier life.

Of the 709 individuals chosen from secondary data from the NHANES 2013-2014 survey, female respondents (50.8%) had a greater optimal level of 59.4% than male respondents, who had an optimal level of (40.6%). Results showed males had less glycemic control as compared to females; this could be due to men lacking medical coverage preventing them from seeking medical attention for their diabetes or an awkwardness to seeking medical attention or not visiting a doctor till they feel ill. A recommendation of an evidence based program, such as the “Power Up for Health” program which offers diabetes education, intervention and preventive to men of minority races, realized their focus was intended to assist, but they were only serving a small population (Gary-Webb et al., 2018).

A study conducted by Juarez et al. (2013), provided a worthy insight of what occurred in Hawaii during the 2006-2009 NHANES survey, those who participated were between the ages of 18-60-year-old both male and female. The research question asked for the reasons individuals felt they could not maintain a normal glycemic level. The results showed individuals who had insurance were 58% more likely to maintain glycemic control versus who did not have health insurance (Juarez et al., 2013). This proves there is a need for further research to be conducted to prove if further association can be made between glycemic control (optimal versus suboptimal) and medical health insurance availability, also, if the lack of health insurance plays a role in how many healthcare visits are made by individuals with type 2 diabetes.

What was evident in this study were minority (63.5%) responded more than white (36.5%) and had higher optimal level (64.2%) and suboptimal level (63.2%) than whites with optimal level (35.8%) and suboptimal (36.8%) level. This could be because a higher percentage of minorities are diagnosed with type 2 diabetes. Educating minorities on diabetes self-management, benefits of a healthier lifestyle and effects diabetes has on an individual can decrease the prevalence of diabetes among minorities.

Powers et al., (2015) concluded in their study, for an individual with diabetes to maintain a healthy life one would require self-management skills to manage diabetes. The study discussed a program called Diabetes Self-Management Education and Support (DSME/S), which provides evidence-based practices by assisting individuals diagnosis with diabetes through community based resources, education and coping skills required for self-management of diabetes, which can be successful if certain barriers, such as lack of individual participation, limited access to medical care and a need for medical resources can be obtained (Powers et al., 2015). Implementing prevention policies that support reducing the prevalence of acquiring the disease will allow for a greater population of individuals with longer-term glycemic control.

The educational status in this study resulted in no association between glycemic control (optimal versus suboptimal) and healthcare visits, as levels varied in each educational status resulting in no association between variables. Those individuals who attended 9th-11th grade, high school graduate/GED and some college had a higher optimal level (72%) than those with a suboptimal level (67.6%). However, after graduating college the tables turned, individuals now had a higher suboptimal level (16.1%) than those with an optimal level (14.6%). This could represent that after individuals graduated they become less active and do not maintain a healthy diet increasing the probability of having uncontrolled glycemic levels. The need for individuals with type 2 diabetes to maintain an optimal glycemic level is of the utmost importance, as recommended by the ADA (Evert et al., 2014). Also discussed by Evert et al. (2014) is the need to provide educational support through Medical Nutrition Therapy (MNT) to individuals with diabetes, as well as providing medical staff with educational skills, nutrition therapy needed to properly treat their diabetes patients. Implementations of such programs will create an environment where individuals with diabetes can make healthier nutritional choices leading to healthier lifestyles and habits.

More than half of the respondents were married, and this population resulted in highest (56.1%) levels of both optimal and suboptimal. The marital subcategory of individuals who participated in the survey displayed an optimal level (51.2%) and suboptimal level (59.0%). Widowed, divorced, separated, never married and living with a partner all had a higher optimal level than suboptimal level by more than .5%. Married individuals may exhibit feelings of resentment as the cost and strain of the disease can place a burden on the relationship and/or the health of the individual diagnosed with diabetes (Dellafiore et al., 2018). Self-efficacy can have an impact on how an individual copes with the demand of the disease, however building the belief to maintain a healthy glycemic level can only be attained if the individual is supported by their spouse (Dellafiore et al., 2018). Being able to share negative and positive experiences in a positive manner can strengthen a marriage, by providing proper intervention assistance to the individual and the spouse can assist in maintaining an optimal glycemic level.

Of those who responded yes to usual healthcare visits 50.8% had an optimal glycemic level, a much greater level than those who had a suboptimal level (12%). While those who responded no 25.5% had an optimal glycemic level and 11.7% had a suboptimal level. There still remains a need for intervention of glycemic control for many individuals with the disease as over 23% of respondents had a suboptimal glycemic level. A publication by CDC (2009), found that educating and talking to patients about their diabetes gave many individuals the support needed to manage their diabetes.

Arx, Gydesen and Skovlund (2016), recognized that although most diabetes outcomes are suboptimal, treatment beliefs and health behaviors can have a positive outcome on glycemic control. In the study the individuals’ health belief had a far stronger association to glycemic control than treatment beliefs, suggesting research and measures must be undertaken to link individual treatment belief to glycemic control. This supports the notion that health behaviors can be manipulated based on one’s belief of begin healthy (Arx, Gydesaen and Skovlund, 2016). Regardless, suboptimal glycemic levels seem to be a universal norm with most individuals with type 2 diabetes, displaying a need for providing preventive measure to reduce the chances of becoming an individual with diabetes.

Respondents who had a healthcare visit within the past 12 months resulting in an optimal level were (25.3%) and those with a suboptimal level (49.6%); individuals who did not have a healthcare visit with an optimal level were (11.7%) and those with a suboptimal level were (12.0%). ADA (2016) discussed approximately 30-50% of patients lack control of their glycemic levels due to noncompliant medical treatment. In this study the percentage of individuals who had an annual visit still had a higher suboptimal glycemic level, proving more needs to be done to assist these individuals with maintaining their glycemic levels. Providing individuals with type 2 diabetes with tools such as the self-management blood glucose test will assist with daily testing to maintain a normal glycemic level (Polonsky & Fisher, 2012).

Questions regarding eye exams had very different end results; however, compliant medical intervention persist as individuals’ type 2 diabetes eye care should be maintained. The survey in this study asked, if respondents were told diabetes has affected their eyes or that they had retinopathy? A small portion (6%) of those with an optimal level answered yes with 30.9% answering no. Respondents with a suboptimal level, (15.1%) who answered yes and 47.1% answered no. More than 50% of respondents had not been told diabetes has affected their eyes. Regardless, there is a need of intervention for those 21.1% of individuals who had been told diabetes had affected their eyes or that they had retinopathy. In Yau et al. (2012), researchers found results showing poor glycemic levels has contributed to diabetes retinopathy. Opposite results were found for the additional eye dilation question. Approximately 32 % of individuals had eyes dilated over those that did not. This holds true across both categories, those with an optimal level (28.1%) and (47.7%) with a suboptimal level as opposed to those optimal (9.1%) and suboptimal (15.1%) of those who had not had an eye exam where their eyes were dilated for more than two years. Regardless, most individuals did not have glycemic control and still had eyes dilated. Toy et al. (2016) found that by using a smartphone visual testing application to photograph eyes, as an intervention, it removed the barrier of to having to visit an ophthalmologist and receiving eye care. Results showed through this telemedicine screening, participants were able to be alerted when it was necessary for them to visit an ophthalmologist (Toy et al., 2016).

Lastly, the response from “the last time you visited a diabetes specialist, nurse educator, dietitian, or nutritionist for diabetes but not a physician”, exhibited similar results as the other survey questions. Although most individuals had a healthcare visit within a year, all subcategories had a lower percentage of an optimal level (37.2%) than a suboptimal (62.8%) level. Showing there was no association between the independent and dependent variables. The glycemic level of more than half of the entire population (709) reported to have uncontrolled glycemic levels (62.8%), over those who had control of their glycemic level (37.2%). Evidence also showed individuals had uncontrolled glycemic levels prior to completing the survey.

Recommendations

Further research on glycemic control (optimal versus suboptimal) will contribute to this study, as several significant associations were found between glycemic control and healthcare visits. Although some of the survey questions showed significance among variables, recommendations and future studies related to healthcare utilization and glycemic levels are suggested. By seeking additional associations between individual demographic variables such gender, which showed men had a far higher suboptimal level than females resulting in a significant value of 12.000 and a p-value of 0.001, will help healthcare professionals care for a population with the highest prevalence of diabetes. Respondents answering “Is there one doctor or healthcare professional you usually see for your diabetes” revealed statistical significance (p-value= 0.000) although the majority had an optimal level there remains those that need assistance with managing their glycemic levels. Results also showed a statistical significance (p-value of 0.000) regarding healthcare visits, which asked “Have you had a healthcare visit within 12 months”. The remaining significance results asked, “Has a healthcare professional ever told you that diabetes has affected your eyes or that you had retinopathy”, those with a suboptimal level had a far higher score than those optimal respondents resulting in a significant value of 6.035 and p-value of 0.049.

Juarez et al., (2013) researched the variables of individuals with no medical coverage nor emotional support and lack of personal income, to find associations between poor glycemic control and diabetes. Their study’s main purpose was to show that individuals with type 2 diabetes lacked diabetes self-care habits and emphasized the need to maintain positive glycemic levels. As more men had uncontrolled levels than females, assisting men with self-management tools to lower their chances of presenting suboptimal levels should be a healthcare focus.

The prevalence of individuals contracting diabetes is at an all-time high. Reducing the chances of acquiring the disease can only be obtained by changing diabetes polices, diabetes education, self-management tools, prevention and intervention, which can assist with lowering the probability of uncontrolled glycemic levels. Policies can be implemented on diabetes healthcare practices to increase awareness of diabetes complications and provide health programs that educate self-help techniques that assist individuals with healthy habits. Educating individuals on diabetes retinopathy, insurance coverage and individual counseling, telehealth accessibility, as well as a gym dedicated to individuals with diabetes, can provide for change in how Americans feel and maintain healthy glycemic levels.

Limitations

Missing variables related to healthcare visits where limited in this research. Also, the age range was too wide, by narrowing the age range researchers could pinpoint specific result associated with age. Additional questions regarding healthcare visits such as, do you have diabetes healthcare facilities in your community, could have contributed to this study. Knowing the time of day individuals’ glycemic level were tested would contribute to the study as levels vary due to individual habits and food intake.

Results in this research conclude there are associations between the dependent variable of glycemic control (optimal versus suboptimal) and the independent variable of healthcare visits among the age range of 18-79 year olds. The demographic covariates, healthcare visits and self-reporting were all measured against the participants’ glycemic levels. Four of the 10 questions resulted in a significant score, while the remaining questions had no significance between variables. Evidence based programs have been providing education, intervention, and prevention to many who suffer from the disease. Through these supports individuals have been able to maintain glycemic control.

The rate of individuals being diagnosed can be reduced if many are taught self-management tools for positive diabetes health outcomes. Most importantly including further policies and procedures to existing evidence-based programs encourages individuals with the disease, to maintain glycemic control. The first step in acquiring the lifestyle everyone so deserves. Future research on glycemic control can also assist individuals who have diabetes by researching how variables have an impact on medical coverage, medical education, and telehealth and how to offer help to a much-needed population all can change the current diabetes statistics.

References

Albers, J. W., & Pop-Busui, R. (2010). Epidemiology of Diabetes Interventions and Complications (EDIC). Design, implementation, and preliminary results of a long-term follow-up of the Diabetes Control and Complications Trial cohort. Diabetes Care, 33, 1090-1096.