This study was conducted to investigate the nutritional status and nutrition diagnosis based on nutrition care process of type 2 diabetic patients according to carbohydrate intake levels. An interview was conducted with patients with type diabetes. A total of 61 subjects were selected for the study,...
This study was conducted to investigate the nutritional status and nutrition diagnosis based on nutrition care process of type 2 diabetic patients according to carbohydrate intake levels. An interview was conducted with patients with type diabetes. A total of 61 subjects were selected for the study, except one who did not respond to the second telephone survey. Subjects were divided into two groups according to carbohydrate intake levels(≤ 60% and > 60%). The nutritional status was assessed by examining the general characteristics, clinical characteristics, anthropometric parameters, blood biochemical parameters, and nutrient intake of the subjects, and the correlation with glycated hemoglobin, and nutritional diagnosis was prepared based on the nutrition care process. The main results of this study are as follows.
1. The average age of the subjects was significantly higher in the > 60% carbohydrate intake levels group compared with ≤ 60% carbohydrate intake levels group (p=0.020). More than 60% of the diabetic patients had more than 6 hours of sleep in the 60% or less group (p=0.037).
2. The clinical characteristics of diabetic patients was compared according to the carbohydrate intake levels. There were no significant differences in the family history, duration, complications, and complication types between groups. There were no significant differences between the two groups in the diet therapy, medicine, exercise, and self-monitoring of blood glucose.
3. There were no significant differences in height, weight, BMI, body fat percentage, body fat mass, muscle mass, abdominal circumference, and WHR. Blood component analysis showed significantly higher AST levels in the > 60% group than ≤ 60% group (p=0.018). Dividing blood component analysis by fractions above or below the norm showed no significant differences in carbohydrate intake levels.
4. As a result of examining the usual eating habits of the study subjects, the frequency of eating out was investigated to be less than once a week (31.0%),
1~ 2 times a week (20.7%), 3 ~ 5 times a week (27.6%) more than 6 times a week (20.7%). The frequency of eating out in the > 60% group was investigated less than once a week (59.4%), 1 ~ 2 times a week (25.0 %), 3 ~ 5 times a week (3.1%), 6 times or more (12.5%) and there was a difference between groups (p=0.023). The frequency of late night intake was less than once a week 62.1%, 1 ~ 2 times a week (17.2%), 3 ~ 5 times a week (20.7%), more than 6 times a week (0%) in the ≤ 60% group and less than once a week (78.1%), 1 ~ 2 times a week (6.3%), 3 ~ 5 times a week (0%), 6 times a week or more (15.6%) in the > 60% group (p=0.004).
5. There were significant differences in the ratio of macronutrient intake according to the carbohydrate intake levels. Carbohydrate intake levels ≤ 60% group showed carbohydrate: protein: fat ratio of 51:18:31, and > 60% group showed significant difference of 67:14:19 (p<0.001) Carbohydrate intake levels ≤ 60% of total protein (p<0.001), animal protein (p<0.001), animal fat (p60 % group.
6. As a result of calculating the NAR based on the nutrient intake status of the study subjects, the NAR of protein (p=0.001), riboflavin (p=0.007), niacin (p=0.045), phosphorus (p=0.005) and zinc (p=0.038) was significantly higher than the ≤ 60% group. The NAR of folic acid of > 60% group was significantly higher than ≤ 60% group (p=0.049).
7. To analyze the correlation between glycated hemoglobin and anthropometric parameters, blood biochemical parameters, partial correlation
analysis was performed by adjusting gender, age, family history, duration, smoking, drinking, physical activity, exercise, energy, medicine, and education level. However, there were no significant correlations in all items of anthropometric and blood biochemical parameters analysis.
8. Total protein (r=0.294, p=0.025), animal protein (r=0.297, p=0.024) and niacin (r=0.378, p=0.003) were positively correlated with glycated hemoglobin. In addition, NAR of vitamin B12 also showed a significant negative correlation with glycated hemoglobin (r=-0.269, p=0.041).
9. When the nutrition problems of the subjects were diagnosed based on the nutrition care process, there were carbohydrate (54.1%), sodium (14.8), alcohol (13.1%), fat (11.5%) and protein (6.6%) intake problems. The causes of nutrition problems were preference of food (65.6%), knowledge/beliefs/attitudes (29.5%), and situational, cultural, and/or environmental problem (4.9%). Signs and symptoms include 'intake of carbohydrates at least 60% of total energy’, ‘Monosaccharide intake in excess of 10% of total energy’, 'over 6.5% glycated hemoglobin', ‘Sodium intake in excess of intake goal (2000 mg)’ ‘alcohol intake in excess of male (40 g/day) and female (20 g/day)’, ‘fat intake of at least 25% of total energy, ‘total cholesterol over 200 mg/dL’, and ‘low protein intake relative to recommended nutrient intakes’.
10. According to the survey of nutrition diagnosis according to carbohydrate intake levels, 34.5% of ‘excessive of carbohydrate intake’, 24.1% of 'excessive fat intake’, 20.7% of ' excessive sodium intake' and 'excessive alcohol intake' in the group ≤ 60% group. In contrast, it was investigated 71.9% of 'carbohydrate intake problems', 12.5% of ‘inadequate protein intake’, 9.4% of ‘excessive sodium intake’ and 6.3% of ‘excessive alcohol intake’ in the > 60% group.
In this study, the intake of total protein, animal protein, animal fat, thiamin, riboflavin, phosphorus, animal iron, and zinc were different according to carbohydrate intake levels. As the carbohydrate intake decreased, the fat intake increased relatively, which seems to be different depending on the frequency of eating out. The diagnosed nutrition problems of the study subjects are believed to cause macronutrient intake problems according to carbohydrate intake levels. Therefore, this study identified nutritional diagnosis based on nutritional assessment and nutritional management of type 2 diabetic patients due to carbohydrate intake levels. Therefore, it is necessary to find out the measures that can be applied to the management of diabetes and prevention of complications through the study analyzing the effects of nutrition intervention applying the nutrition management process to patients with type 2 diabetes.
This study was conducted to investigate the nutritional status and nutrition diagnosis based on nutrition care process of type 2 diabetic patients according to carbohydrate intake levels. An interview was conducted with patients with type diabetes. A total of 61 subjects were selected for the study, except one who did not respond to the second telephone survey. Subjects were divided into two groups according to carbohydrate intake levels(≤ 60% and > 60%). The nutritional status was assessed by examining the general characteristics, clinical characteristics, anthropometric parameters, blood biochemical parameters, and nutrient intake of the subjects, and the correlation with glycated hemoglobin, and nutritional diagnosis was prepared based on the nutrition care process. The main results of this study are as follows.
1. The average age of the subjects was significantly higher in the > 60% carbohydrate intake levels group compared with ≤ 60% carbohydrate intake levels group (p=0.020). More than 60% of the diabetic patients had more than 6 hours of sleep in the 60% or less group (p=0.037).
2. The clinical characteristics of diabetic patients was compared according to the carbohydrate intake levels. There were no significant differences in the family history, duration, complications, and complication types between groups. There were no significant differences between the two groups in the diet therapy, medicine, exercise, and self-monitoring of blood glucose.
3. There were no significant differences in height, weight, BMI, body fat percentage, body fat mass, muscle mass, abdominal circumference, and WHR. Blood component analysis showed significantly higher AST levels in the > 60% group than ≤ 60% group (p=0.018). Dividing blood component analysis by fractions above or below the norm showed no significant differences in carbohydrate intake levels.
4. As a result of examining the usual eating habits of the study subjects, the frequency of eating out was investigated to be less than once a week (31.0%),
1~ 2 times a week (20.7%), 3 ~ 5 times a week (27.6%) more than 6 times a week (20.7%). The frequency of eating out in the > 60% group was investigated less than once a week (59.4%), 1 ~ 2 times a week (25.0 %), 3 ~ 5 times a week (3.1%), 6 times or more (12.5%) and there was a difference between groups (p=0.023). The frequency of late night intake was less than once a week 62.1%, 1 ~ 2 times a week (17.2%), 3 ~ 5 times a week (20.7%), more than 6 times a week (0%) in the ≤ 60% group and less than once a week (78.1%), 1 ~ 2 times a week (6.3%), 3 ~ 5 times a week (0%), 6 times a week or more (15.6%) in the > 60% group (p=0.004).
5. There were significant differences in the ratio of macronutrient intake according to the carbohydrate intake levels. Carbohydrate intake levels ≤ 60% group showed carbohydrate: protein: fat ratio of 51:18:31, and > 60% group showed significant difference of 67:14:19 (p<0.001) Carbohydrate intake levels ≤ 60% of total protein (p<0.001), animal protein (p<0.001), animal fat (p60 % group.
6. As a result of calculating the NAR based on the nutrient intake status of the study subjects, the NAR of protein (p=0.001), riboflavin (p=0.007), niacin (p=0.045), phosphorus (p=0.005) and zinc (p=0.038) was significantly higher than the ≤ 60% group. The NAR of folic acid of > 60% group was significantly higher than ≤ 60% group (p=0.049).
7. To analyze the correlation between glycated hemoglobin and anthropometric parameters, blood biochemical parameters, partial correlation
analysis was performed by adjusting gender, age, family history, duration, smoking, drinking, physical activity, exercise, energy, medicine, and education level. However, there were no significant correlations in all items of anthropometric and blood biochemical parameters analysis.
8. Total protein (r=0.294, p=0.025), animal protein (r=0.297, p=0.024) and niacin (r=0.378, p=0.003) were positively correlated with glycated hemoglobin. In addition, NAR of vitamin B12 also showed a significant negative correlation with glycated hemoglobin (r=-0.269, p=0.041).
9. When the nutrition problems of the subjects were diagnosed based on the nutrition care process, there were carbohydrate (54.1%), sodium (14.8), alcohol (13.1%), fat (11.5%) and protein (6.6%) intake problems. The causes of nutrition problems were preference of food (65.6%), knowledge/beliefs/attitudes (29.5%), and situational, cultural, and/or environmental problem (4.9%). Signs and symptoms include 'intake of carbohydrates at least 60% of total energy’, ‘Monosaccharide intake in excess of 10% of total energy’, 'over 6.5% glycated hemoglobin', ‘Sodium intake in excess of intake goal (2000 mg)’ ‘alcohol intake in excess of male (40 g/day) and female (20 g/day)’, ‘fat intake of at least 25% of total energy, ‘total cholesterol over 200 mg/dL’, and ‘low protein intake relative to recommended nutrient intakes’.
10. According to the survey of nutrition diagnosis according to carbohydrate intake levels, 34.5% of ‘excessive of carbohydrate intake’, 24.1% of 'excessive fat intake’, 20.7% of ' excessive sodium intake' and 'excessive alcohol intake' in the group ≤ 60% group. In contrast, it was investigated 71.9% of 'carbohydrate intake problems', 12.5% of ‘inadequate protein intake’, 9.4% of ‘excessive sodium intake’ and 6.3% of ‘excessive alcohol intake’ in the > 60% group.
In this study, the intake of total protein, animal protein, animal fat, thiamin, riboflavin, phosphorus, animal iron, and zinc were different according to carbohydrate intake levels. As the carbohydrate intake decreased, the fat intake increased relatively, which seems to be different depending on the frequency of eating out. The diagnosed nutrition problems of the study subjects are believed to cause macronutrient intake problems according to carbohydrate intake levels. Therefore, this study identified nutritional diagnosis based on nutritional assessment and nutritional management of type 2 diabetic patients due to carbohydrate intake levels. Therefore, it is necessary to find out the measures that can be applied to the management of diabetes and prevention of complications through the study analyzing the effects of nutrition intervention applying the nutrition management process to patients with type 2 diabetes.
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