Journal of Health Care and Prevention
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  • Research Article   
  • J Health Care Prev 1: 103, Vol 1(1)

Does General Health Differ by Routine Check-Up in Diabetic, Middle-Aged Females?

Micah Bowman, Haylee Moore, Meredith Allen, Tierney P Gonzales, America McGuffee and Jessica L. Hartos*
Department of Physician Assistant Studies, University of North Texas Health Science Center, USA
*Corresponding Author: Jessica L. Hartos, Department of Physician Assistant Studies, University of North Texas Health Science Center, 3500 Camp Bowie Dr., Fort Worth, TX, 76107, USA, Tel: (817) 735-2454, Fax: (817) 735-2529, Email: jessica.hartos@unthsc.edu

Received: 23-May-2018 / Accepted Date: 31-May-2018 / Published Date: 07-Jun-2018

Abstract

Objective: Given limited evidence that routine check-ups improves quality of life, the purpose of this study is to assess whether general health differs by routine check-up in diabetic, middle-aged females in the general population. Methods: This cross-sectional analysis used 2016 data from the Behavioral Risk Factor Surveillance System (BRFSS) for diabetic females ages 45-65 from Alabama (N=370), Georgia (N=256), Kentucky (N=485), Mississippi (N=275), and West Virginia (N=268). The relationship between general health and routine check-ups was assessed separately by state using multiple logistic regression analysis while controlling for comorbid health conditions, weight status, physical activity, tobacco and alcohol use, age, ethnicity, educational level, income level and employment status. Results: Across states, about half of diabetic females reported fair or poor general health (50-53%), while most reported having a routine check-up within the past year (90-93%). Adjusted analysis indicated that general health was not significantly related to routine check-up but was inversely related to having diabetes plus two or more health conditions and positively related to physical activity. Conclusion: The results of this study indicated that general health was not related to routine check-up in diabetic middle-aged females in the general population. However, general health showed strong inverse relations with multiple health conditions and a moderate positive relation with physical activity. Therefore, with diabetic, middle-aged females, practitioners should automatically screen for and optimize care of additional health conditions and encourage physical activity in order to improve general health in these patients.

Keywords: Diabetes; General Health; Routine check-up; BRFSS; Multiple health conditions; Physical activity

Introduction

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.

Methods

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).

Results

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%).

Variable Alabama N = 370 Georgia N = 256 Kentucky N = 485 Mississippi N = 275 West Virginia N = 268
N % N % N % N % N %
General Health Status 368 99 255 100 483 100 275 100 266 99
Good or better 173 47 127 50 234 48 130 47 124 47
Fair or poor 195 53 128 50 249 52 145 53 142 53
Routine Check-up 363 98 255 100 474 98 271 99 265 99
Yes 336 93 234 92 433 91 243 90 244 92
No 27 7 21 8 41 9 28 10 21 8
Health Conditions 357 96 250 98 461 95 257 93 251 94
Diabetes only 59 16 54 22 69 15 57 22 51 20
Diabetes plus one 81 23 75 30 113 25 76 30 68 27
Diabetes plus two or more 217 61 121 48 279 61 124 48 132 53
Weight Status 333 90 224 88 431 89 255 93 259 97
Overweight or obese 297 89 195 87 384 89 223 87 241 93
Not overweight or obese 36 11 29 13 47 11 32 13 18 7
Physical Activity 370 100 256 100 485 100 274 100 268 100
Yes 187 51 137 54 261 54 133 49 157 59
No 183 49 119 47 224 46 141 51 111 41
Tobacco Use 356 96 250 98 469 97 267 97 262 93
Current smoker 63 18 55 22 92 20 50 19 54 21
Not current smoker 293 82 195 78 377 80 217 81 208 79
Alcohol Use 354 96 248 97 470 97 263 96 262 98
Yes 82 23 63 26 89 19 57 22 81 31
No 272 77 185 75 381 81 206 78 181 69
Age 370 100 256 100 485 100 275 100 268 100
45-54 123 33 95 37 158 33 75 27 78 29
55-60 110 30 81 32 170 35 103 37 89 33
61-65 137 37 80 31 157 32 97 35 101 38
Ethnicity/Race 366 99 251 98 480 99 274 100 268 100
White, non-Hispanic 197 54 129 51 406 85 123 45 246 94
Other 169 46 122 49 74 15 151 55 17 6
Educational Level 369 100 255 100 484 100 275 100 268 100
Did not graduate high school 57 16 49 19 61 12 48 17 48 18
Graduated high school 119 32 86 34 175 36 84 31 102 38
Some college/technical school 122 33 60 24 134 28 81 29 68 25
Graduated college/technical school 71 19 60 24 114 24 62 23 50 19
Income level 290 78 210 82 391 81 219 80 234 87
$0 to less than $25,000 157 54 102 49 185 47 118 54 86 37
$25,000 to less than $50,000 56 19 54 26 91 23 47 21 59 25
$50,000 or more 77 27 54 26 115 30 54 25 89 38
Employment Status 368 99 254 99 484 100 274 100 268 100
Employed 108 29 71 28 168 35 105 38 113 42
Not Employed 260 71 183 72 316 65 169 62 155 58

Table 1: Participant Characteristics by State.

Adjusted Analysis

Predicting General Health Status (good/better vs. fair/poor) Alabama Georgia Kentucky Mississippi West Virginia
AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI
Low High Low High Low High Low High Low High
Routine Check-up                              
No ref - - ref - - ref - - ref - - ref - -
Yes 1.45 0.41 5.12 4.81 1.20 19.30 0.69 0.27 1.77 0.72 0.21 2.40 0.80 0.24 2.68
Health Conditions                              
Diabetes only ref - - ref - - ref - - ref - - ref - -
Diabetes plus one 0.86 0.30 2.45 0.38 0.13 1.13 0.29 0.11 0.76 0.49 0.16 1.52 0.65 0.25 1.69
Diabetes plus two or more 0.16 0.07 0.41 0.27 0.09 0.78 0.18 0.07 0.44 0.17 0.06 0.49 0.31 0.21 0.77
Weight Status                              
Not overweight or obese ref - - ref - - ref - - ref - - ref - -
Overweight or obese 0.76 0.27 2.11 1.48 0.49 4.44 1.01 0.42 2.43 0.77 0.23 2.58 0.59 0.15 2.30
Physical Activity                              
No ref - - ref - - ref - - ref - - ref - -
Yes 2.68 1.45 4.98 2.14 1.06 4.35 2.42 1.40 4.19 2.06 1.00 4.29 2.13 1.06 4.28
Tobacco Use                              
Not current smoker ref - - ref - - ref - - ref - - ref - -
   Current smoker 0.49 0.20 1.20 0.71 0.31 1.63 0.95 0.48 1.86 0.76 0.28 2.05 0.60 0.23 1.55
Alcohol Use                              
No ref - - ref - - ref - - ref - - ref - -
Yes 1.46 0.71 3.04 1.51 0.64 3.55 2.00 1.02 3.93 1.55 0.62 3.90 0.80 0.38 1.68
Age                              
    45-54 ref - - ref - - ref - - ref - - ref - -
    55-60 0.58 0.27 1.25 1.65 0.69 3.94 1.58 0.81 3.07 2.10 0.81 5.46 1.04 0.45 2.37
    61-65 0.65 0.30 1.38 1.45 0.61 3.47 1.46 0.76 2.83 1.71 0.63 4.61 0.88 0.36 2.17
Ethnicity/Race                              
    Other ref - - ref - - ref - - ref - - ref - -
    White, non-Hispanic 1.39 0.68 2.81 1.03 0.50 2.13 1.55 0.75 3.21 1.47 0.68 3.20 1.72 0.30 9.67
Educational Level                              
Did not graduate high school ref - - ref - - ref - - ref - - ref - -
Graduated high school 2.59 0.80 8.37 2.57 0.88 7.49 1.22 0.49 3.04 0.46 0.15 1.41 1.28 0.42 3.89
Some college/technical school 2.76 0.85 8.97 1.36 0.42 4.40 1.44 0.55 3.73 0.49 0.14 1.67 1.72 0.53 5.55
Graduated college/technical school 3.27 0.90 11.90 2.69 0.77 9.28 1.61 0.57 4.52 1.27 0.35 4.65 1.35 0.37 4.93
Income level                              
$0 to less than $25,000 ref - - ref - - ref - - ref - - ref - -
$25,000 to less than $50,000 2.20 0.93 5.20 1.76 0.75 4.12 1.16 0.60 2.25 1.55 0.61 3.92 2.27 0.94 5.48
$50,000 or more 2.34 0.94 5.79 2.66 0.77 9.28 1.31 0.66 2.63 1.87 0.69 5.07 3.30 1.35 8.07
Employment Status                              
    Not Employed ref - - ref - - ref - - ref - - ref - -
    Employed 1.49 0.71 3.10 2.03 0.83 4.95 2.30 1.29 4.12 3.68 1.57 8.67 1.16 0.54 2.53

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.

Discussion

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.

Limitations

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.

Conclusion

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.

References

  1. (2017) It’s Your Life. Treat Your Diabetes Well. Centers for Disease Control & Prevention (CDC).
  2. (2017) National diabetes statistics report. Centers for Disease Control and Prevention (CDC).
  3. Brown AF, Ettner SL, Piette J, Weinberger M, Gregg E, et al. (2004) Socioeconomic position and health among persons with diabetes mellitus: a conceptual framework and review of the literature. Epidemiol Rev 26: 63-77.
  4. Smith-Palmer J, Bae JP, Boye KS, Norrbacka K, Hunt B, et al. (2016) Evaluating health-related quality of life in type 1 diabetes: A systematic literature review of utilities for adults with type 1 diabetes. Clinicoecon Outcomes Res 8: 559-571.
  5. Solli O, Stavern K, Kristiansen I (2010) Health-related quality of life in diabetes: The associations of complications with EQ-5D scores. Health Qual Life Outcomes 8: 18.
  6. Speight J, Reaney MD, Barnard KD (2009) Not all roads lead to Rome-A review of quality of life measurements in adults with diabetes. Diabet Med 26: 315-327.
  7. Ali S, Stone M, Skinner TC, Robertson N, Davies M, et al. (2010) The association between depression and health-related quality of life in people with type 2 diabetes: A systematic literature review. Diabetes Metab Res Rev 26: 75-89.
  8. Angell B, Muhunthan J, Eades AM, Cunningham J, Garvey G, et al. (2016) The health-related quality of life of indigenous populations: A global systematic review. Qual Life Res 25: 2161-2178.
  9. Magwood GS, Zapka J, Jenkins C (2008) A review of systemic reviews evaluating diabetes interventions. Diabetes Educ 34: 242-265.
  10. Rubin RR, Peyrot M (1999) Quality of life and diabetes. Diabetes Metab Res Rev 15: 205-218.
  11. Wandell PE (2005) Quality of life of patients with diabetes mellitus: An overview of research in primary health care in the Nordic countries. Scand J Prim Health Care 23: 68-74.
  12. Zhang X, Norris SL, Chowdhury FM, Gregg EW, Zhang P (2007) The effects of interventions on health-related quality of life among persons with diabetes: A systematic review. Medical Care 45: 820-834.
  13. Hanninen J, Takala J, Kananen-Klukaanniemi S (2001) Good continuity of care may improve quality of life in type 2 diabetics. Diabetes Res Clin Pract 51: 21-27.
  14. Von Kroff M, Gruman J, Curry S, Wagner EH (1997) Collaborative management of chronic illness. Ann Intern Med 127: 1097-1102.
  15. (2016) Prevalence Data & Data Analysis Tools. Centers for Disease Control & Prevention (CDC).
  16. Reiner M, Niermann C, Jakeuc D, Woll A (2013) Long-term health benefits of physical activity- A systematic review of longitudinal studies. BCM Public Health 13: 813.

Citation: Bowman M, Moore H, Allen M, Gonzales TP, McGuffee A (2018) Does General Health Differ by Routine Check-Up in Diabetic, Middle-Aged Females? J Health Care Prev 1: 103.

Copyright: © 2018 Bowman M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

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