Journal of Health Care and Prevention
Open Access

More than 30 million people have diabetes in the United States [1,2]. In 2014 alone, this disease led to 14 million trips to the emergency room and 76,488 deaths, making diabetes the 7th leading cause of mortality in the United States [2,3]. Furthermore, it affects 12.6% of the population 20 years and older [3] and has the potential to disrupt one’s health-related quality of life by leading to other complications such as heart disease, stroke, blindness, kidney disease, and amputations [1,4]. Although people in the general population typically have a less than perfect view of their health, people with chronic conditions report even lower views of their health [5-7].

Health-related quality of life can be described as mental, physical, emotional, and social well-being [5,7,8-14]. Research has shown that quality of life in diabetic patients is related to health, socioeconomic status, and demographic factors. For example, quality of life is lower in diabetic patients with a declining health status and complications due to diabetes including cardiovascular disease, renal disease and neuropathy [5,6,10-12]. In addition, diabetics with mental health conditions such as depression, anxiety, and other psychiatric disorders reported that their quality of life was negatively impacted [4,7,8,13]. Furthermore, diabetic patients with a lower socioeconomic status including lower income and education levels reported a decreased quality of life compared to patients with a higher socioeconomic status, which may be related to greater access to medical care, exercise facilities and healthier food options [4,6,12,13]. For demographic factors, a lower quality of life has been reported with aging [5,6,12,13], and female diabetic patients report a lower quality of life than males with diabetes [12,13].

Routine check-ups may also be related to quality of life for those with diabetes. Continued care and medical interventions during routine check-ups can improve physical and social functioning as well as encourage positive changes in smoking, medication use, and diet to improve patient health in those with diabetes [15,16]. Furthermore, the motivation to manage chronic illnesses, such as diabetes, through self-care routines can be improved by routine check-ups [16]. Thus, annual visits aimed at advocating for, planning and monitoring diabetic conditions with the support of a knowledgeable provider can improve overall patient outcomes and adherence to treatment [4,11,12]. However, previous research shows limited evidence that continuity of care such as routine check-ups with a medical provider improves quality of life over an extended period of time [11,12,14,15]. As health care providers, it is important to know if the presence of yearly routine check-ups is sufficient to improve the health status of diabetic patients [6-8,13]. Therefore, the purpose of this study was to assess whether general health differs by routine check-up in diabetic, middle-aged females in the general population.

Design

This cross-sectional analysis used 2016 data from the Behavioral Risk Factor Surveillance System (BRFSS) conducted by the Centers for Disease Control and Prevention (CDC, [17]). BRFSS is a nationwide annual survey system used to gather health-related information including chronic health conditions, health risk behaviors, and preventative strategies in adults 18 years of age and older across all 50 states. BRFSS is conducted annually using random-digit dialing methods on both landlines and cell phones. The CDC compiles the data and allows researchers access to de-identified data to conduct secondary data analyses. This study was given exempt status by The University of North Texas Health Science Center.

Sample

The samples included diabetic middle-aged (45-65 years old) females from Alabama (N=370), Georgia (N=256), Kentucky (N=485), Mississippi (N=275), and West Virginia (N=268). We selected these states based on the higher prevalence of (a) diabetic females in the target age range and (b) reported fair or poor health as compared to other states [18].

Data

The outcome, general health, was measured as either “good or better” versus “fair or poor.” The factor of interest, routine check-up, was measured as yes/no to having a routine check-up in the past year.

The control variables included health-related, demographic, and socioeconomic factors. Health conditions was measured as the number of “yes” responses to the following: heart attack, CHD, stroke, skin cancer, cancer, COPD, arthritis, depression, kidney disease, and asthma. This number was then categorized into “diabetes only,” “diabetes plus one other health condition,” and “diabetes plus two or more other health conditions.” Weight status was measured as “overweight or obese” versus “not overweight or obese.” Physical activity was measured as yes/no to “performed physical activity or exercise in the past 30 days.” Tobacco use was measured as “current smoker” versus “non-smoker.” Alcohol use was measured as yes/no to “drank alcohol in past 30 days.” Age was categorized into “45-54,” “55- 60,” or “61-65.” Ethnicity/race was measured as “White, non-Hispanic” versus “other.” Educational level was categorized as “did not graduate high school,” “graduated high school,” “some college/technical school,” or “graduated college/technical school.” Income level was categorized as “$0 to less than $25,000” “$25,000 to less than $50,000” or “$50,000 or more.” Employment status was measured as “not employed” versus “employed.”

Analysis

Frequency distributions by state were used to describe the samples and determine any problems with the distributions of variables. We analyzed data separately by state to assess patterns in relationships among variables of interest across similar samples. Similar results in 3 or more of the 5 states was considered reliable findings for variable relations. Multiple logistic regression by state was conducted to assess the relationship between general health and routine check-up after controlling for health-related, demographic and socioeconomic factors. Any observations with missing data for any variable were excluded from the adjusted analysis. All analyses were conducted in STATA Version 15.1 (Copyright 1985-2017 StataCorp LLC).

Descriptive Statistics

Table 1 lists participant characteristics for diabetic, middle-aged females in Alabama, Georgia, Kentucky, Mississippi and West Virginia. Across states, about half of the participants reported having good general health in the past month (47-50%) and most reported having a routine check-up within the past year (90-93%). For health conditions, about half to two-thirds reported having diabetes plus two or more health conditions (48-61%), and most reported being overweight or obese (87-93%). Regarding health behaviors, about half performed physical activity or exercise in the past 30 days (49-59%) and most reported not currently smoking (78-82%) or drinking alcohol within in the past 30 days (69-81%). For demographics, about one-third of the participants fell within each age category (45-54: 27-37%; 55-60: 30-37%; and 61-65: 31-38%), and there was a wide variation of the samples across states who reported white, non-Hispanic (45-94%). For socioeconomic status, about one-fourth graduated college or technical school (19-24%); about one-third to half had an income level below $25,000 (37-54%); and the majority of the sample was not employed (58-72%).

Table 1: Participant Characteristics by State.

Adjusted Analysis

Table 2: Adjusted Results by State.

As shown in Table 2, the results of multiple logistic regression analysis for diabetic, middle-aged females in Alabama, Georgia, Kentucky, Mississippi and West Virginia indicated that, after controlling for all other variables in the model, general health status was significantly related to routine check-up in the past year in only one of five states. However, in 5 of 5 states, participants who reported having diabetes plus 2 or more health conditions were about 3-7 times less likely to report good or better general health compared to those with diabetes only. In addition, in 4 of 5 states, participants who performed physical activity in the past 30 days were about 2-3 times more likely to report good or better general health status compared to those who did not perform physical activity in the past 30 days.

The purpose of this study was to assess whether general health differs by routine check-up in diabetic, middle-aged females. Across states, about half of diabetic females reported fair or poor general health, while most reported having a routine check-up within the past year. The results of adjusted analysis across states indicated that general health was not related to having routine check-ups in this target population. These results differ from previous studies that have found that routine check-ups improve the general health of those with diabetes [4,11,12,15,16]. Discrepancies may be related to different measures and target populations. Prior research investigated the collaborative management of chronic diseases between the practitioner and patient [16], while our study assessed routine check-ups within the past year. Furthermore, prior research focused on male and female adults ages 18 years and older with Type 2 diabetes [11,14], while our research focused on diabetic, middle-aged females 45-65 years old.

The results of this study did, however, show that general health among diabetic, middle-aged females is strongly and inversely related to having diabetes plus two or more health conditions, which is similar to the findings from prior research [11]. General health was also significantly and positively related to physical activity within the last 30 days, which is also similar to the results of previous studies [14,19]. When considered together, the findings suggest that general health for this target population may be less related to having routine check-ups and more related to managing comorbidities and engaging in physical activity.

The use of BRFSS data allowed assessment for multiple large samples of middle-aged diabetic females. Although the results determined that multiple health conditions were inversely related to good or better general health, we had no information for the severity of health conditions and how well multiple conditions were being managed to further understand which treatment options may improve overall general health. Furthermore, the results of our study indicated that physical activity in the past 30 days was related to good or better general health; however, there was no information for the frequency, intensity, or duration of physical activity to assess the minimum requirement necessary to improve overall general health in this target population.

Because this was a population-based study, the results may generalize to diabetic females ages 45-65 in diabetic clinics or endocrinology settings. Practitioners may find that approximately half of their diabetic, middle-aged female patients report fair or poor health and that the vast majority will have had a routine medical check-up within the past year; however, these may not be related. Thus, providers should always screen this target population for general health status. In addition, with a moderate prevalence of diabetes plus two or more health conditions and a strong relation with general health, practitioners should automatically screen all diabetic, middle-aged female patients for the presence of multiple comorbidities to ensure the optimization of treatment for each health condition to improve general health status. Furthermore, with a moderate prevalence of the target population not engaging in physical activity, and a moderate relation to general health, practitioners should screen for physical activity in all diabetic, middleaged females and provide education and recommendations for physical activity that may fit within the patient’s lifestyle as well as referrals to physical therapy or exercise physiology as needed.