American Diabetes Association Guide to Nutrition Therapy for Diabetes. Marion J. Franz

or case-controlled studies. The literature search identified 251 articles. Fifteen articles were retrieved for more detailed evaluation, and two articles were identified from reference lists. Of these, 10 met inclusion criteria and are included in Table 5.5.

      Table 5.5 Studies on Nutrition Therapy for Adults with Type 1 Diabetes: Carbohydrate-Counting Meal-Planning Approach

      Nutrition Therapy Interventions

      Based on the results of the DCCT, ADA recommends intensive insulin therapy for type 1 diabetes, using basal and bolus insulin to reproduce or mimic normal physiological insulin secretion: 1) use of multiple-dose insulin injections (three to four injections per day of basal and prandial insulin) or insulin pump therapy; 2) matching prandial insulin-to-carbohydrate intake, premeal blood glucose, and anticipated activity; and 3) for many people (especially if hypoglycemia is a problem), use of insulin analogs (ADA 2012). The use of basal and prandial insulin replaces insulin in a way that closely approximates normal physiological patterns.

      Insulin therapy should be integrated into the individual’s usual eating and physical activity pattern; individuals using rapid-acting insulin by injection or insulin pump should adjust the meal and snack insulin doses on the basis of carbohydrate content of the meals and snacks. In individuals using fixed daily doses, carbohydrate intake on a day-to-day basis should be kept consistent with respect to time and amount. For planned exercise, insulin doses can be adjusted; for unplanned exercise, extra carbohydrate may be needed (ADA 2008).

      Achieving nutrition-related goals requires a coordinated team effort that includes the person with diabetes and involves the patient in the decision-making process. Because of the complexity of nutrition issues, it is recommended that an RD who is knowledgeable and skilled in implementing nutrition therapy into diabetes management and education be the team member who plays the leading role in providing nutrition therapy (ADA 2012). However, all team members, including physicians and nurses, should be knowledgeable about nutrition therapy and support its implementation (ADA 2008).

      The Acad Nutr Diet EBNPG state the following: “Medical nutrition therapy (MNT) plays a crucial role in managing diabetes and reducing the potential complications related to poor glycemic, lipid, and blood pressure control” (Franz 2010; Acad Nutr Diet 2008). Carbohydrate intake and available insulin are the primary determinants of postprandial glucose levels. Therefore, management of carbohydrate intake is the primary strategy for achieving glycemic control. For individuals who adjust mealtime (prandial) insulin or who are on CSII, insulin doses should be adjusted to match carbohydrate intake (ICRs). Comprehensive nutrition education and counseling should be provided that includes instruction on interpretation of blood glucose monitoring patterns and nutrition-related medication management. Specifically, people using “flexible” insulin dosing to manage their diabetes need to understand the relationship and coordination of their basal-bolus insulin plan (insulin action) with the blood glucose–raising effect of their carbohydrate intake.

      In people with type 1 (or type 2) diabetes using “fixed” insulin doses, meal and snack carbohydrate intake should be consistently distributed throughout the day on a daily basis, since consistency in carbohydrate has been shown to result in improved glycemic control (Acad Nutr Diet 2008). It is recommended that individuals using “fixed” daily doses of insulin use a carbohydrate-counting meal-planning approach or some other method of quantifying carbohydrate intake to maintain day-to-day consistency, both in the timing and quantity of food intake.

      Food Factors Affecting Glycemic Control

      There is more to controlling postprandial hyperglycemia than knowing how to “count carbohydrates.” Many people with type 1 (and type 2) diabetes struggle to comprehend how their blood glucose levels can dramatically fluctuate on a daily basis despite eating the same number of grams of carbohydrate at meals.

      One reason may be a lack of adequate education on how to accurately dose prandial insulin and quantify carbohydrate intake (Boukhors 2003). The CDC reports that only 55.7% of people with diabetes participate in a diabetes self-management education class, suggesting that many people with type 1 (and type 2) are never formally instructed on a meal-planning approach, such as carbohydrate counting, to enable them to accurately quantify their carbohydrate intake (CDC 2011). Consequently, these individuals may either underdose or overdose prandial insulin requirements. Accurate dosing of prandial insulin to actual food (grams of carbohydrate) intake is a key component of basal-bolus insulin therapy.

      Another reason may be that in addition to determining the number of grams of carbohydrate consumed at meals, several extrinsic and intrinsic variables may influence the impact of carbohydrates on the postprandial response (ADA 2008). Extrinsic variables that may influence glucose response include macronutrient distribution of the meal, fasting or preprandial blood glucose level, available insulin, antecedent exercise, and degree of insulin resistance.

      Intrinsic variables that influence the effect of the carbohydrate-containing foods on blood glucose response include type and source of carbohydrate, the physical form of the food (e.g., whole food versus juice), type of starch (e.g., amylopectin versus amylose), method of food preparation (e.g., baking versus frying), cooking time and amount of heat and moisture used, degree of processing, and ripeness of food (ADA 2008). Individuals can use information from SMBG and continuous glucose sensors to learn how specific foods affect their glycemic control.

      Meal-Planning Approaches and Tools

      Type 1 diabetes. Meal-planning approaches other than carbohydrate counting, such as the glycemic index, also have been studied. A food insulin index, a physiological basis for ranking foods according to insulin “demand,” was developed by a group of researchers in Australia for 120 single foods (Bao 2009). They concluded that the relative insulin demand evoked by mixed meals consumed by lean healthy subjects is best predicted by a physiological index (food insulin index) based on integrating insulin responses to isoenergetic portions of single foods and that eating patterns that provoke less insulin secretion may be helpful in preventing and managing diabetes. In 2011, Bao compared a novel algorithm based on the food insulin index for estimating mealtime insulin dose with carbohydrate counting in adults with type 1 diabetes using CSII (Bao 2011). They concluded that when compared with carbohydrate counting, the food insulin index algorithm improved acute postprandial glycemia in well-controlled subjects with type 1 diabetes. The authors acknowledge that implementation of these findings outside the laboratory setting is not practical at this time, since the food insulin index does not currently appear on food labels and the food insulin index database includes only ~120 foods.

      Another group collected data on food intake, physical activity, insulin administration, and blood glucose test results in patients with type 1 diabetes using self-administered questionnaires (Ahola 2010). A total of 64% of the participants inappropriately estimated their prandial insulin, and the authors concluded that optimal prandial insulin dosing is not easy, even after a long duration of diabetes.

      Insulin dosing aids such as bolus insulin calculation cards and dosing guides have been developed to assist people with diabetes in reducing potential calculation errors (Anderson 2009; Chiarelli 1990; Kaufman 1999). Bolus calculators with personalized insulin-dosing algorithms can be programmed for use in a wide range of devices, such as personal digital assistants (PDAs), Smartphone applications, or insulin pumps (Gross 2003; Błazik 2010).

      The use of a Diabetes Interactive Diary, an automatic carbohydrate/insulin bolus calculator installed on a mobile phone, also using patient-physician communication via text messages, was compared with a standard carbohydrate-counting education program (Rossi 2010). The Diabetes Interactive Diary was as effective as a traditional carbohydrate-counting education program, without an increased risk of hypoglycemia. The authors concluded that use of this type of technology reduces education time while significantly improving treatment satisfaction and several quality-of-life dimensions. These types of adaptive aids are popular with the tech-savvy, but can also be useful for people who have health literacy and numeracy concerns, such as young children or adults