Relationship Between Health-related Behavioral and Psychological Factors and Cardiovascular and Cerebrovascular Diseases Comorbidity Among Korean Adults With Diabetes

Article Outline

• Summary
• Introduction
• Methods
  • Study population
  • Analytical framework
  • Measurements
  • Statistical analysis
• Results
  • Demographics
  • Behavioral and psychological factors
  • Relationships between health-related behavioral and psychological factors and CCVD-related comorbidity
• Discussion
• Conclusion
• Conflict of interest
• References
• Copyright

Summary 

Purpose

This study aims to explore the relationships between health-related behavioral and psychological factors and cardiovascular and cerebrovascular diseases (CCVD) comorbidities among Korean adults with diabetes mellitus (DM).

Methods

Data included in the Fourth Korean National Health and Nutrition Examination Survey were used. This study compared three groups: those diagnosed with DM only, DM and hypertension, DM, hypertension and CCVD using multinomial logistic regression analyses and the classification and regression tree (CART) model.

Results

Weight control (OR = 4.01) and depression (OR = 2.37) are related with increased odds of having hypertension and CCVD comorbidity in those with DM. The CART model suggested that the high prevalence risk groups for hypertension or CCVD comorbidities were diabetic adults aged between 51 and 69 with a body mass index of 25 and above and those aged 70 and above.

Conclusion

For effective control of CCVD comorbidities among diabetic Korean adults, psychological support for depression and weight control need to be prioritized when managing DM. Weight control intervention needs to be reinforced for DM patients aged between 51 and 69 and that even if BMI is below 25, the occurrence of comorbidities needs to be carefully monitored for DM patients aged 70 or older.

Keywords: cardiovascular diseases, cerebrovascular disorders, health behavior, hypertension, type 2 diabetes mellitus

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Introduction 

Diabetes mellitus (DM) is one of the most prevalent diseases associated with premature mortality worldwide. In particular, the Asia-Pacific region is considered to be the largest region in the emerging DM epidemic (Kim et al., 2006, Zimmet et al., 2001). The prevalence of DM in Korea has rapidly increased from 2% in the 1970s to 9.7% in 2007 (Cho, 2005, Kim and Choi, 2009), and the DM mortality rate in Korea as a proportion of all DM cases is second highest among the Organisation for Economic Co-operation and Development (OECD) countries (OECD Health Data, 2009).

Comorbidity, defined by coexisting diseases with or without any known causal relation to the index diseases (Weel & Schellevis, 2006), are common in those with DM, comprising 50-95% (Deshpande, Harris-Hayes, & Schootman, 2008). Cardiovascular and cerebrovascular diseases (CCVD) such as heart diseases and stroke are one of the most common comorbid diseases for those with DM, accounting for 79% of the total patient population (Kerr et al., 2007). CCVD usually develops after the development of hypertension and are the primary cause of death for those with DM (Adler et al., 2000, Bretzel, 2007, Chyun and Young, 2006). Diabetic patients are twice as likely to have hypertension as those without DM (Okosun, Chandra, Christman, Dever, & Prewitt, 2001), and they are two to six times more likely to have CCVD (Gaede et al., 2003). Moreover, CCVD leads to disability, resulting in a heavy economic burden on the health care system (Deshpande et al., 2008). Comorbid CCVD management should be emphasized for nurses because it helps them achieve effective control of diabetes-specific factors and may provide opportunities for improving the functioning and mortality risk of people with diabetes.

The occurrence of CCVD comorbidities in people with DM, especially type 2 DM, is related to health-related behavioral and psychological factors, including smoking, alcohol consumption, physical inactivity, poor diet (e.g., a high salt diet), increased body weight (e.g., body mass index [BMI] ≥ 25 kg/m²), medical noncompliance related to controlling blood sugar level (uncontrolled blood sugar defined by a hemoglobin A1c ≥6.5%), depression and stress (Chyun and Young, 2006, Collins-McNeil et al., 2007, Deshpande et al., 2008, Yeom et al., 2011).

The WHO recommends (Inoue & Zimmet, 2000) basing obesity measures on risk factors and morbidities related to BMI. Such risk factors and morbidities related to BMI arise within a lower range of body measurements for Asians than Westerners. Thus a BMI of 25-29.9 kg/m² is considered overweight for Westerners but signals obesity for Asians, whereas a BMI of greater than 30 kg/m² is defined as obesity for Westerners. Again, these risk factors manifest differently by interacting with race/ethnicity (Miller et al., 2004). For example, the diabetic characteristics of Asians, including Koreans, are different from those of other ethnic groups. Asians develop DM with a lesser degree of obesity and at much younger ages, and they suffer complications of DM longer and die sooner (Yoon et al., 2006). Therefore, a study on the factors related to CCVD comorbidities in Korean patients with diabetes is necessary for eventually identifying the most effective measures to guide these patients. This study seeks to explore the relationships between health-related behavioral and psychological factors and CCVD-related comorbidities among Korean adults with diabetes.

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Methods 

Study population 

This study used the health interview and health examination data from the Fourth Korean National Health and Nutrition Examination Survey (KNHANES IV) conducted by the Korean Centers for Disease Control and Prevention (KCDC) from 2007 to 2008. Data were obtained through “confirmation of plan for raw data use” from KCDC through the KNHANES website as a form of data use permission. To select a representative sample of civilian, noninstitutionalized Koreans, this survey used a stratified, multistage probability sampling design by administrative district, place of residence (urban/rural), and residential pattern (apartment/nonapartment). The respondents’ data were assigned weights to assure the equal probability of being sampled and to cover missing data. The health interview and health examination were performed by trained surveyors.

This particular study was limited to 672 diabetic adults aged 20 and older. Those with DM were separated into three groups: those with DM alone (n = 276); those with DM and hypertension (n = 327); and those with DM, hypertension and CCVD-ischemic heart disease, angina pectoris, or stroke (n = 69).

Analytical framework 

As presented in Fig. 1, those with DM developed cardiovascular disease (CVD) comorbidity after the appearance of hypertension (Adler et al., 2000, Bretzel, 2007, Chyun and Young, 2006, Okosun et al., 2001) even though it was not possible to untangle the causal relation to DM. The occurrence of CVD-related comorbidities for diabetic patients is influenced by health behaviors including smoking, alcohol consumption, physical inactivity, poor diet, increased body weight, and medical noncompliance related to controlling blood sugar level and psychological factors including depression and stress (Chyun & Young; Collins-McNeil et al., 2007, Deshpande et al., 2008). Demographic characteristics, such as sex, age, education, employment status, and economic status, influence the progression from DM to CVD and health-related behavioral and psychological factors.

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• Fig. 1 

  Analytical framework. Note. CCVD = cardiovascular and cerebrovascular diseases; DM = diabetes mellitus.

Measurements 

Prevalence status and other behavioral and psychological variables were identified on the basis of the results of the health interview survey and the health examination survey.

Individuals were categorized as having DM by meeting one of the three criteria: a fasting blood glucose of 126 mg/dL or higher, self-report of a doctor’s diagnosis of DM, or self-report of hypoglycemic medication/insulin treatment. Individuals were categorized as having hypertension by meeting one of the two conditions: a systolic blood pressure of 140 mmHg and above and a diastolic blood pressure of 90 mmHg and above persistently, or self-report of medicinal treatment for hypertension. Individuals were identified as having CCVD based on a self-reported doctor’s diagnosis of ischemic heart disease, angina pectoris, or stroke.

Health behavior variables included smoking, drinking alcohol, exercise, low salt diet, weight control, and glycemic control. Related health behaviors were identified by responses of “yes” or “no” to the following conditions: currently smoking and/or drinking, exercising regularly, that is, at least three times per week, monitoring salt in their diets, body mass index (BMI) of 25 kg/m² and above, and a hemoglobin A1c level of 6.5% and above. BMI was calculated as kilograms per square meter and weight was considered well-controlled when BMI was below 25, in keeping with Asian cut-off standards (KCDC, 2010). Hemoglobin A1c, indicating average blood glucose concentrations over the preceding 3 months, was considered to represent blood glucose control among those with DM. It was rated as well-controlled when it was below 6.5%, in keeping with Asian cut-off standards (KCDC, 2010).

Psychological variables included depression and stress. To evaluate these variables, individuals were asked whether they had been sad or depressed enough to affect their daily living continuously for more than 2 weeks in the preceding year (“yes” or “no”) and whether they perceived themselves to be experiencing more stress than they normally did (“yes” or “no”).

Demographic data included sex, age, education, employment status, and economic status (as measured by the household’s economic status, lower 25%, 25-49%, 50-74%, and upper 75%).

Statistical analysis 

Descriptive statistics and chi-square tests were used to compare demographic, health-related behavioral, and psychological variables for the three diagnostic groups—those with DM only, those with DM and hypertension, and those with DM, hypertension, and CCVD. After univariate analysis, multinomial logistic regression analyses were performed to explore the relationships between the health-related factors and CCVD comorbidities, with the DM only group as the reference group after adjustment for demographic variables and with the health-related behavioral and psychological variables as the independent variables. The classification and regression tree (CART) model was used to predict the occurrence of hypertension or CCVD comorbidities among those with DM by dividing the individuals into subgroups with variables that exhibited significant differences as shown in Table 1, Table 2—age, smoking, alcohol drinking, weight control, and depression, and with age and weight control as continuous variables. Individuals with missing data were excluded from all analyses. All statistical evaluations were conducted using SPSS 16.0 (SPSS Inc., Chicago, IL, USA).

Table 1. Demographic Characteristics by Groups.

Note. DM = diabetes mellitus; CCVD = cardiovascular and cerebrovascular diseases.

Table 2. Health-related Behavioral and Psychological Factors by Groups.

Note. DM = diabetes mellitus; CCVD = cardiovascular and cerebrovascular diseases; BMI = body mass index; HbA1c = hemoglobin A1c.

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Results 

Demographics 

Table 1 provides demographic data for the three diagnostic groups: DM only; DM with hypertension; and DM, hypertension, and CCVD. According to Table 1, there were significant group differences with regard to age, education, employment status, and economic status. Compared to the DM only group, individuals in the DM, hypertension, and CCVD group were found to be significantly older (χ² = 58.50, p < .001), less educated (χ² = 27.52, p < .001), less employed (χ² = 26.46, p < .001), and in a lower economic status (χ² = 13.13, p = .041). In contrast, individuals in the DM with hypertension group fell significantly within the middle of the above characteristics. No group differences were found with regard to sex.

Behavioral and psychological factors 

Table 2 illustrates the health-related behavioral and psychological factors of the three diagnostic groups. Significant group differences were found with regard to smoking, drinking alcohol, weight control, and depression. Compared to those with DM only, individuals with DM, hypertension, and CCVD were found to smoke less (χ² = 16.22, p < .001), drink less (χ² = 10.18, p = .006), be more obese (χ² = 27.52, p < .001), and be more depressed (χ² = 9.01, p = .011). Individuals in the DM with hypertension group fell significantly within the middle of the above characteristics except for weight control; they (60.6%) were slightly more obese than the DM, hypertension and CCVD group (58.0%). There were no group differences found with regard to exercise, low salt diet, glycemic control, or stress.

Relationships between health-related behavioral and psychological factors and CCVD-related comorbidity 

Table 3 presents the odds ratios of related factors in the three diagnostic groups adjusted for demographic factors, including age, education, employment status, and economic status. This model aimed at investigating the relationship between the dependent variable and a combination of independent variables was statistically valid based on “Model Fitting Information” in SPSS (χ² = 100.99, p < .001 for DM and hypertension group, χ² = 150.79, p < .001 for DM, hypertension, and CCVD group with DM group as a reference group each). Compared to the DM only group, the only significant factor found in the DM and hypertension group was weight control; individuals with DM who were obese were found to be more likely to have hypertension (OR = 3.49). The related factors for hypertension and CCVD comorbidity among those with DM were weight control and depression; DM only individuals who were obese had higher odds of having both hypertension and CCVD (OR = 4.01); those being depressed were more likely to have both hypertension and CCVD (OR = 2.37). Even with all the related factors in the model, age remained a significant factor in increasing the odds of having hypertension (OR = 1.06) or both hypertension and CCVD (OR = 1.08).

Table 3. Multinomial Logistic Regression of Health-related Behavioral and Psychological Factors by Groups.

Note. DM only = 1, adjusted for age, education, employment status, and economic status. DM = diabetes mellitus; CCVD = cardiovascular and cerebrovascular diseases; OR = odds ratio; CI = confidence interval; BMI = body mass index; HbA1c = hemoglobin A1c.

Fig. 2 shows the CART decision-making model used to identify the determinants of hypertension or CCVD comorbidities among those with DM by dividing them into subgroups by demographic and health-related factors. The variables that exhibited significant differences in Table 1, Table 2—age, smoking, alcohol drinking, weight control and depression—were considered, with age and weight control as continuous variables. Age was identified as the best discriminator of those having hypertension or CCVD from among those with DM. The next best discriminator was weight control, represented by BMI value. The majority of DM individuals aged 50 and below were not found to have hypertension or CCVD. The majority of those with DM who were aged 70 and above or aged between 51 and 69 and with a BMI of 25 and above were found to have hypertension or CCVD.

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• Fig. 2 

  Hypertension or CCVD comorbidity in individuals with DM. Note. BMI = body mass index in kg/m²; CCVD = cardiovascular and cerebrovascular diseases; DM = diabetes mellitus. O indicates combined DM + hypertension and DM + hypertension + CCVD in circles, X indicates DM only.

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Discussion 

The prevalence of CCVD comorbidities and its related mortality among those with DM are affected by race or ethnicity (Chaturvedi et al., 1998, Ferdinand and Ferdinand, 2009, Miller et al., 2004). In order to utilize health-related behavioral and psychological factors for the management of CCVD comorbidities among Korean diabetic adults, the relationships between these factors and CCVD-related comorbidities among Koreans with DM were analyzed based on data from the KNHANES-IV.

The presence of hypertension or CCVD comorbidities among those with DM was found to be related to body weight for Koreans in this study as much as Westerners (Anderson & Konz, 2001). BMI was used for measurement of CCVD-related factors in this study because a previous study supported the idea that BMI provided as much clinical insight as waist circumference in identifying CCVD-related factors for Koreans (Sung, Ryu, & Reaven, 2007). In multinomial logistic regression, the occurrence of hypertension comorbidity among DM patients was 3.5 times higher among those with a BMI of 25 and above, and the occurrence of hypertension and CCVD comorbidities was 4.0 times higher in those with a BMI of 25 and above. Moreover, in the CART model, age and weight control were identified as the discriminators: the high prevalence risk groups for hypertension or CCVD were diabetic adults aged between 51 and 69 with a BMI of 25 and above, and those aged 70 and above regardless of BMI level. This result supported the way obesity was alternatively defined in our study using the definition of the cut-off point for Asians proposed by the WHO (Inoue & Zimmet, 2000). In a meta-analysis (McGee & Diverse Populations Collaboration, 2005) and a cohort study (Wen et al., 2008), relative CCVD-related mortality risks between obesity defined as a BMI of 25 and above in an Asian population and as a BMI of 30 and above in Western populations were similar. This led to the conclusion that a BMI of 25 and above was an appropriate alternative cut-off point for defining obesity among Asians. The reason that the given BMI is associated with higher CCVD risks in Asians than Westerners may be explained by the fact that Asians have a higher percentage of fat compared to Caucasians at the same BMI level, which has been associated with a greater cardiovascular risk in previous studies (Deurenberg-Yap et al., 2002, Guricci et al., 1998). Also, as for diabetic patients with a BMI of 25 and above, the risk of having comorbid hypertension and CCVD is aggravated more than comorbid hypertension (Gaede et al., 2003, Okosun et al., 2001).

The prognosis of weight gain or loss in older adults is controversial; it is different from that of younger adults. In systematic reviews on Westerners, high BMI (≥ 25) was not a significant factor for all-cause or cardiovascular mortality in the elderly. On the other hand, low BMI (< 18.5) was even more associated with mortality in the elderly (Miller & Wolfe, 2008). Most studies have shown that a BMI range of 25-27 kg/m² was not a risk factor for all-cause mortality in the elderly. In fact, Miller and Wolfe (2008) found that no BMI range was specifically associated with all-cause mortality among individuals aged 70 years or older; results from the present study agree with this finding. In addition, weight loss includes changes in body composition, changes in the proportion of lower lean mass compared to fat mass, as well as accelerated muscle and bone loss in the elderly, and it can lead to functional impairment and even disability (Ensrud et al., 2003; Miller & Wolfe). Studies on obese elderly individuals found that regular exercise diminished the percentage of lean mass lost during dieting (Miller & Wolfe). Therefore, weight control for the elderly should be implemented through interventions of regular exercise combined with adequate nutrition, and muscle and bone mass should be monitored as well. From this study, therefore, in order to lower CCVD-related comorbidities among those with DM, it is important to emphasize weight control intervention among DM patients aged between 51 and 69. Furthermore, even if BMI is below 25, in DM patients aged 70 or older, the occurrence of comorbidities needs to be carefully monitored.

In this study, depression was found to be associated with a DM individual’s odds of having both hypertension and CCVD. A meta-analysis (Groot, Anderson, Freedland, Clouse, & Lustman, 2001) of cross-sectional studies also demonstrated a significant and consistent association between diabetes complications and depressive symptoms: an increase in depressive symptoms was associated with an increase in the severity or number of diabetes complications. Based on the present correlational study and the literature on this topic at this stage, it is not possible to determine causal directions or mechanisms behind the association between depression and CCVD comorbidities in those with DM (i.e., depression may precede and/or follow CCVD). However, depression, once established, was reported to negatively affect other health behaviors such as smoking, weight control, and glycemic control by medication or insulin treatment (Ensrud et al., 2003, Groot et al., 2001, Katon et al., 2004, Miller and Wolfe, 2008, Park et al., 2004, Selvin et al., 2004); such behaviors hasten the onset or progression of CCVD (Carney, Freedland, Lustman, & Griffith, 1994). Considering that depression was found to be the main related factor for CCVD and that CCVD is the main cause of mortality for those with DM (Adler et al., 2000, Bretzel, 2007, Chyun and Young, 2006), especially in Koreans compared to other ethnicities, it is likely that depression management for Korean diabetic adults is not being performed well. To reduce the onset or progression of CCVD, therefore, treatment for depression should be emphasized for Korean diabetic adults more than treatment for any other related factors.

This study has several limitations. First, as a cross-sectional study was used to explore the relationships between health-related factors and CCVD-related comorbidities in those with DM, it was difficult to clarify causality. The results of some health-related factors by the different groups in this study represented a reversal relationship between cause and effect because of the cross-sectional nature of the study. That is to say, smoking and alcohol drinking have a casual relationship with CCVD-related comorbidity among those with DM. Therefore, to confirm the relationships, future studies using a longitudinal design are necessary. Second, health-related behavioral and psychological factors were measured by a single question that were part of a larger survey, preventing us from having control over how the variables were defined, measured and reported. As such, this could dilute potential differences in the relationships between the health-related factors and CCVD comorbidity in those with DM by limiting the information on quantity and source. However, those single questions have been reported to have a range of validity and reliability as acceptable as other tools with multiple questions (Mahoney et al., 1994, Wu and Kelly, 2007). Third, CART analysis was conducted for the comparisons between DM only and combining the two groups of DM and hypertension, and DM, hypertension and CCVD because of the small number of DM, hypertension and CCVD individuals. However, since hypertension is one of the most important indicators for developing CCVD, the analysis gives an important clue when managing those with CCVD comorbidity among those with DM.

It is possible to generalize the study results to the Korean population at large since the sample was drawn at random from the general population. In fact, the results found in this study that depression is just as important as weight control in interventions for managing CCVD-related comorbidities, taken together with similar results from studies in other geographical areas (Chyun and Young, 2006, Groot et al., 2001, Miller and Wolfe, 2008) should remind those who care for diabetic patients to be aware of their patients’ mental health.

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Conclusion 

Through this study regarding effective management of CCVD comorbidities for Korean adults with diabetes, we identified that psychological support for depression should be emphasized more than treatment for any other determinants. Also, weight control intervention needs to be reinforced for DM patients aged between 51 and 69 and that even if BMI is below 25, the occurrence of comorbidities needs to be carefully monitored for DM patients aged 70 or older.

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Conflict of interest 

The authors declare no conflict of interest.

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