Purpose: The purpose of this study was to investigate the knowledge and learning needs on coronary artery disease in diabetic patients by glycemic control. Methods: The subjects consisted of 188 patients at the hospital who had diabetes mellitus. Data was obtained using a knowledge and learning needs questionnaire from January to April 2006. Results: Treatment method, the levels of fasting blood glucose(FBG), and 2-hour postprandial blood glucose(PP2hr) showed meaningful differences between normo-glycemic group(HbA1c < 7%) and hyper-glycemic group($HbA1c{\geq}7%$). The levels of knowledge on coronary artery disease by glycemic control tend to show higher in normo-glycemic group. Etiology and prevention of coronary artery disease were significantly higher in normo-glycemic group than in hyper-glycemic group. The levels of learning needs on coronary artery disease by glycemic control tend to show higher in normo-glycemic group. The learning needs on items of diet control were higher in normo-glycemic group than in hyper-glycemic group. Conclusion: On the base of these results, we should focus on the coronary artery disease education for hyper-glycemic group. Also individual coronary artery disease educational program should be developed for the patients with different level of knowledge and learning needs.
Background: Bone fractures are high in elderly patients with type 2 diabetes mellitus (T2DM). Hyperglycemia and chronic kidney disease may increase the risk of fracture prevalence via altered bone metabolism, but whether glycemic control and kidney function are associated with the risk of fracture prevalence remains unclear. This study evaluated the relationship between glycemic control and baseline estimated glomerular filtration rate (eGFR) and risk of fracture prevalence in older and middle-aged patients with T2DM. Methods: Patients who underwent a general medical check-up between 2009 and 2013 were selected from the Korean National Health Insurance Sharing Service records. Chi-square test and multiple logistic regression analysis were used to assess the relationship between glycemic control and eGFR and risk of fracture prevalence. Results: Cumulative fracture prevalence were higher in patients with T2DM, irrespective of whether they had tight or less stringent glycemic control (fasting blood glucose [FBG] ${\geq}110mg/dL$). After adjustment for baseline age and FBG, tight and less stringent glycemic control was significantly associated with increased adjusted risk of fracture prevalence in middle-aged patients with T2DM (OR=1.13, 95% CI, 1.05-1.21, p=0.0005 vs OR=1.13, 95% CI, 1.06-1.20, p=0.0001), but not in older patients. Baseline eGFR was not significantly related to fracture prevalence in either older or middle-aged patients. Conclusion: Less stringent glycemic control significantly increased the adjusted risk of fracture prevalence in middle-aged patients with T2DM. Further studies are needed to confirm the effect of tight glycemic control on fracture prevalence.
Background: We aimed to estimate the proportion of patients with diabetes who achieved target glycemic control, to estimate diabetes-related costs attributable to poor control, and to identify factors associated with them in the United Arab Emirates. Methods: This retrospective cohort study used administrative claims data handled by Abu Dhabi Health Authority (January 2010 to June 2012) to determine glycemic control and diabetes-related treatment costs. A total of 4,058 patients were matched using propensity scores to eliminate selection bias between patients with glycosylated hemoglobin (HbA1c) <7% and HbA1c ${\geq}7%$. Diabetes-related costs attributable to poor control were estimated using a recycled prediction method. Factors associated with glycemic control were investigated using logistic regression and factors associated with these costs were identified using a generalized linear model. Results: During the 1-year follow-up period, 46.6% of the patients achieved HbA1c <7%. Older age, female sex, better insurance coverage, non-use of insulin in the index diagnosis month, and non-use of antidiabetic medications during the follow-up period were significantly associated with improved glycemic control. The mean diabetes-related annual costs were $2,282 and $2,667 for patients with and without glycemic control, respectively, and the cost attributable to poor glycemic control was $172 (95% confidence interval [CI], $164-180). The diabetes-related costs were lower with mean HbA1c levels <7% (cost ratio, 0.94; 95% CI, 0.88-0.99). The costs were significantly higher in patients aged ${\geq}65$ years than those aged ${\leq}44$ years (cost ratio, 1.45; 95% CI, 1.25-1.70). Conclusion: More than 50% of patients with diabetes had poorly controlled HbA1c. Poor glycemic control may increase diabetes-related costs.
Journal of Korean Academy of Fundamentals of Nursing
/
v.18
no.2
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pp.152-159
/
2011
Purpose: This study was done to identify factors related to glycemic control in men with diabetes. Methods: Data from the Korean National Health and Nutrition Examination Survey 2007 2008 collected by the Korean Center for Disease Control were analyzed using chi-square test and t-test. Results: There was a difference in glycemic control according to the individual factor of economic status. Differences in glycemic control according to health related factors were as follows: fasting blood sugar, cholesterol, triglyceride, sleep duration, experience of depression and suicidal thoughts. Conclusion: The results of this study will contribute to improvements in management for men with diabetes through comprehensive identification of factors related to glycemic control.
This study was intended to assess the effects of low glycemic index (LGI) nutrition education on dietary management and glycemic control of patients with type 2 diabetes mellitus. The subjects were 48 sex-matched patients with type 2 diabetes mellitus, aged $66.5\;{\pm}\;6.2$ years, visiting a public health center. They were divided into two groups: the control group (males 10, females 14) and the educated group (males 10, females 14). The educated group was provided with a LGI nutrition education program for 7 weeks. The control group was educated only one time for general diabetic education. Anthropometric indices, knowledge and perception of efficacy of low glycemic index carbohydrates, dietary glycemic index (DGI) and glycemic load (DGL), fasting blood glucose, and HbA1c were assessed. In the educated group body weight, body mass index and systolic blood pressure (from $138.0\;{\pm}\;18.9\;mmHg$ to $130.6\;{\pm}\;15.0\;mmHg$) were significantly reduced after the nutrition education (p < 0.05). The scores of knowledge and perception of efficacy of low glycemic index carbohydrates increased significantly in the educated group. Dietary glycemic index and glycemic load of the educated group decreased significantly from $103.4\;{\pm}\;67.6$ to $45.4\;{\pm}\;27.1$ (p < 0.001), and from $173.3\;{\pm}\;135.9$ to $66.8\;{\pm}\;50.4$ (p < 0.001), respectively. Also fasting blood glucose and HbA1c levels of the educated group significantly decreased from $124.5\;{\pm}\;28.8\;mg/dL$ to $96.7\;{\pm}\;21.6\;mg/dL$ (p < 0.001) and from $7.1\;{\pm}\;1.3%$ to $6.4\;{\pm}\;1.2%$ (p < 0.05), respectively. The score of knowledge and perception of efficacy of low glycemic index significantly correlated with fasting blood glucose and HbA1c levels negatively. DGI, DGL and duration of diabetes significantly correlated with HbA1c level positively. From stepwise multiple linear regression analysis, DGI, DGL and the duration of diabetes were extracted as factors influencing HbA1c level of the subjects. The results of this study suggest that low glycemic index nutrition education programs is an effective intervention measure for the glycemic control in type 2 diabetic patients.
Purpose: This study was performed to assess the level of blood glucose and to identify poor glycemic control groups among patients with type 2 diabetes mellitus (DM). Methods: Data of 1,022 Korean type 2 DM patients aged 30-64 years were extracted from the Korea National Health and Nutrition Examination Survey VII. Complex samples analysis and a decision-tree analysis were performed using the SPSS WIN 26.0 program. Results: The mean level of hemoglobin A1c (HbA1c) was 7.22±0.25%, and 69.0% of the participants showed abnormal glycemic control (HbA1c≥6.5%). The characteristics of participants associated with poor glycemic control groups were presented with six different pathways by the decision-tree analysis. Poor glycemic control groups were classified according to the patients' characteristics such as period after DM diagnosis, awareness of DM, sleep duration, gender, alcohol drinking, occupation, income status, low density lipoprotein-cholesterol, abdominal obesity, and number of walking days per week. Period of DM diagnosis with a cut-off point of 6 years was the most significant predictor of the poor glycemic control group. Conclusion: The findings showed the predictable characteristics of the poor glycemic control groups, and they can be used to screen the poor glycemic control groups among adults with type 2 DM.
BACKGROUND/OBJECTIVES: Over the past 10 yrs, the prevalence of diabetes in Korea has continued to incline, and the importance of lifestyle modification to manage diabetes has been highlighted. For patients with diabetes, carbohydrate intake reduction is effective in improving glycemic control; thus, we aimed to analyze the effect of carbohydrate intake ratio and suggest an appropriate carbohydrate intake ratio. SUBJECTS/METHODS: Using the 8th Korea National Health and Nutrition Examination Survey (2019-2021), we analyzed the data including participants aged 30 yrs or older with diabetes, and they were stratified into good and poor glycemic control groups. To analyze the correlation between the dietary behavior characteristics of participants with diabetes and the carbohydrate intake ratio, sociodemographic characteristics, dietary behavior, and health behavior were adjusted, and multivariate logistic regression analysis was conducted to present the adjusted odds ratio and 95% confidence interval (CI). RESULTS: In the unadjusted crude model, when carbohydrate intake ratio in total energy intake increased by 1%, the likelihood of poor glycemic control increased by 1.007-fold (95% CI, 0.998-1.016; P = 0.121). In model 1, which uses age and sex as adjustment variables, an increase of up to 1.011-fold was possible (95% CI, 1.001-1.021; P = 0.008). In model 2, which added variables such as diabetes duration, frequency of fruit consumption, frequency of lunch and, frequency of dinner, the risk of poor glycemic control increased by 1.010-fold as the carbohydrate intake ratio increased (95% CI, 0.998-1.022; P < 0.001). CONCLUSION: This study confirmed that as the ratio of carbohydrate intake to total energy intake increases the likelihood of poor glycemic control also increases in patients with diabetes. Therefore, to improve glycemic control in patients with diabetes, controlling the carbohydrate intake may be helpful.
Park, Jinhyun;Lim, Seungji;Yim, Eunshil;Kim, Youngdae;Chung, Woojin
Health Policy and Management
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v.26
no.2
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pp.125-134
/
2016
Background: Glycemic control is an effective way to reduce the cardiovascular complications of diabetes, but more than half of the adults with diabetes in Korea are improperly controlling their glycemic levels. The purpose of this study is to identify the factors associated with poor glycemic control in type 2 diabetes patients. Methods: This study analyzed 1,261 subjects ${\geq}30years$ old diagnosed with type 2 diabetes who participated in the fifth Korean National Health and Nutrition Examination Survey (2010-2012). Poor glycemic control rates were defined as hemoglobin A1c (HbA1c) level ${\geq}7%$. To shed light on the causes of poor glycemic control, socio-demographics, diabetes severity, health status, and health behavior factors were adjusted and logistic regression was done. Results: Of the total 1,261 patients, 53.0% of patients with type 2 diabetes had HbA1c ${\geq}7%$. After running a logistic regression model, the odds ratio of poor glycemic control was higher in high school graduates than elementary school graduates; in people living in Chungcheong and Jeolla/Jeju than those living in Seoul; in the group with diabetes for over 5 years had diabetes less than 5 years; in a group with insulin and oral hypoglycemic agent treatment than non-treatment; in a group with hypertriglyceridemia than without hypertriglyceridemia; and in the group with slept less than 6 hours slept 7-8 hours. Conclusion: We need a comprehensive public health policy to reduce the poor glycemic control rates in type 2 diabetes patients. We should recognize the education levels, duration of diabetes, diabetes treatment, hypertriglyceridemia, and sleep duration were associated with poor glycemic control.
Objectives: This study was conducted to determine factors related to glycemic control among Korean patients with diabetes. Methods: Data was collected from the Fourth (2007-2009) Korea National Health and Nutrition Examination Survey (KNHANES) which was a nationwide, cross-sectional survey. The study participants who are available for hemoglobin A1c (HbA1c) were 1,441 patients with diabetes aged 30 years and older. Poor glycemic control was defined as $HbA1c{\geq}7.0%$. Data were analysed using logistic regression. Results: The proportion of patients with the poor glycemic control ($HbA1c{\geq}7.0%$) was 49.5%. After adjusting for confounding factors, younger aged persons (30-49 years) were less likely to control the blood glucose than older aged persons (60-69 years) (Adjusted OR=0.533, 95% CI [0.295-0.960]) and longer duration of diabetes was positively related to poor glycemic control (Adjusted OR=2.018, 95% CI [1.418-2.873]). Conclusions: Age and duration of diabetes were significantly related to blood glucose control. Therefore, considering these factors is helpful for developing a strategy to improve blood glucose control in diabetes.
Purpose: This study used raw data from the fifth (2010-2012) Korea National Health and Nutrition Examination Survey (KNHANES) to assess the relationship between vitamin D level and glycemic control of diabetes, and to provide basic data about the use of vitamin D for preparation of a treatment plan for diabetes in South Korea. Methods: For this study, data of 1,713 diabetes from KNHANES (2010-2012) were used. The collected data were analyzed using SPSS 18.0 program, and complex sample frequency analysis, descriptive statistics, complex sample cross analysis, complex sample general linear regression, and complex sample logistic regression analysis were performed. Results: It was found that the poor glycemic control group among the diabetes subjects had significantly lower level of blood vitamin D than the good glycemic control group. Factors affecting glycemic control included drinking, vitamin D levels, hypertriglyceridemia, duration of diabetes, and treatment of diabetes. Also, diabetics with vitamin D deficiency or shortage showed 3.55- and 2.61-times higher odds ratios, respectively, to be diagnosed as the poor glycemic control group than diabetics without vitamin D deficiency or shortage. Conclusion: This study is significant because it provides rationale and basic data about the use of vitamin D for preparation of a treatment plan for diabetes in South Korea by assessing the dependence of glycemic control on the vitamin D level of diabetics. Additionally, future studies are necessary to determine the appropriate concentration of vitamin D for diabetes prevention and treatment to prevent the side effects of excessive supplementation.
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