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Sub-Optimal Eating Behaviors in Older Adults with Diabetes
SUNDAY, NOVEMBER 7
POSTER SESSION: PROFESSIONAL SKILLS; NUTRITION ASSESSMENT; MEDICAL NUTRITION THERAPY The Quality of Nutritional Intake in Children with Autism Author(s): J. Altenburger,1 M. E. Geraghty,1 K. Wolf,1 C. A. Taylor,1 A. E. Lane2; 1Medical Dietetics, The Ohio State University, Columbus, OH, 2Occupational Therapy, The Ohio State University, Columbus, OH Learning Outcome: The participant will be able to discuss deficient nutrient intakes in children with autism. Background: Autism is a neurodevelopmental disorder that affects 1 in every 91 US children. The nutritional status of children with autism may be compromised by common behaviors, such as aberrant mealtime behaviors, food aversions or selectivity, and gastrointestinal pathology. Methods: This prospective study investigated the dietary intakes of children with autism aged 3-9 years (n⫽24). Three-day food records were analyzed to determine 1) macro and micronutrient intakes before and after self-supplementation of vitamins and minerals (SSVM) and 2) trends in the MyPyramid’s food group selection. Descriptive statistics were used to derive mean nutrient intakes and the proportion with intakes ⱖ 80% of Dietary Reference Intake (DRI). Results: Nutrients commonly inadequate were those that are important for bone health (vitamins A, D, and K, with 58.3%, 58.3%, and 91.7% consuming intakes ⬍80% DRI, respectively), digestion and metabolic pathways (pantothenic acid and biotin, with 54.2% and 54.2% consuming intakes ⬍80% DRI), and brain health (choline and vitamin D with 95.8% and 58.3% consuming intakes ⬍80% DRI). Vegetables and dairy were most frequently absent, with only 5 of 24 participants meeting recommended intakes for either group. Nutrient-contributing dietary supplements were reported as used daily by 45.8% of the sample (n⫽11). However, SSVM showed only marginal benefits in improving the proportion meeting reference intake levels. Conclusion: Great variation and areas of concern in nutrient intakes and food selection patterns were documented in this sample. Individualized nutrition assessment and counseling, especially regarding the use of appropriate supplementation, may be useful for children with Autism. Funding Disclosure: Maternal and Child Health Bureau- Association of University Centers on Disabilities- LEND Program grant
Effects of Exercise Training and/or Metformin for 12 weeks on Body Weight and Energy Intake in Individuals with Prediabetes Author(s): S. K. Malin,1 S. Choi,2 L. J. Thistle,1 B. Braun1; Department of Kinesiology, University of Massachusetts, Amherst, MA, 2Department of Family, Nutrition and Exercise Sciences, Queens College, CUNY, Flushing, NY 1
Learning Outcome: To understand how exercise and/or metformin influence body weight and food intake in individuals with prediabetes. Weight loss is one effective mechanism for opposing Type-2 diabetes. Metformin, a common oral medication prescribed for Type-2 diabetes commonly induces slight weight loss. Increased physical activity can also result in weight loss if the energy expended is not compensated for by increased caloric intake. The purpose of this study was to examine the effects of 12 weeks of exercise training and/or metformin on body weight and food intake in individuals with prediabetes. Twenty-seven men (m) and women (f) with prediabetes participated in a double-blind, longitudinal study. Subjects were randomized to placebo (P; 4f, 2m), metformin (Met; 5f, 2m), exercise training and placebo (EP; 3f, 4m), or exercise training and metformin (EMet; 5f, 2m) groups. Body weight (BW), energy intake (3-day food records), perceived appetite and habitual physical activity (PA) were measured at baseline, 6-weeks, and 12-weeks. Data were analyzed using a 2 way ANOVA. Metformin, with or without training, lowered BW by approximately 4% (p ⬍0.05) but there was no change with EP or P. Compared to baseline, EMet reduced caloric intake at week 6 (p ⬍0.05) and 12 (p ⬍0.05). Although not statistically significant, Met tended to lower caloric intake at week 6 and 12 (p ⫽0.1). These data suggest that metformin, with or without exercise reduces food intake and lowers body weight. Combining exercise with metformin is more effective at causing weight loss than exercise alone. The role of body weight changes in mediating improved metabolic health in these subjects remains to be determined. Funding Disclosure: NIH 5 R56 DK081038
Nutrition Registry Assists with Data Collection Determining Results of a Dietitian’s Intervention for Patients with a Diagnosis of Diabetes after Three Counseling Sessions Author(s): M. A. Zeller, S. Kent, A. Saldivar; Nutrition Therapy -, The Cleveland Clinic, Solon, OH Learning Outcome: Increased awareness for participants of tools available for quality nutrition research. An electronic medical record (EMR) can serve as a resource tool for data collection when performing outcomes research. In the summer of 2009 a grant was received to develop a nutrition database. The database accepts documented information from the EMR including medical diagnoses, lab results, anthropometrics, appointment records and documentation of the nutrition care process using standardized language. The impact of nutrition counseling by a registered dietitian related to diabetes care was investigated. Patients counseled by a registered dietitian for 3 appointments between January 2008 and January 2010 with a diagnosis of Diabetes were identified. EMR search data points selected include name of the practitioner and diagnosis of diabetes. Once the cohort (207) was determined data points were obtained for pre and post weight, BMI, and HgA1c. Selection for 3 appointments with coordinated HgA1c labs resulted in 88 patients (females 46, males 42) with an average age 62 years. Results were: Weight: baseline average of 101.63Kg and at third visit 97.63Kg (Avg change -4 Kg/stnd dev 3.9). BMI: baseline 34.95 Kg/m2 and third visit 33.49Kg/m2 (Avg change 1.38Kg/m2 Stnd dev 1.34 Kg/m2). HgA1c: baseline 7.85% after third visit 6.82 % (change 1.04% /stnd dev 1.44%). HgA1c reduction results in reduced coronary heart disease risk and all cause mortality. Using a nutrition database assists with data documentation and collection without extensive use of a clinician’s time. The process initially requires time investment to learn how to filter the information for quality research, but once mastered, information can be retrieved with relative ease. Funding Disclosure: None
Sub-Optimal Eating Behaviors in Older Adults with Diabetes Author(s): E. Suhl, J. Giusti, A. Sternthal, R. McCartney, Y. Lee, K. Weinger, M. Munshi; Research Division, Joslin Diabetes Center, Boston, MA Learning Outcome: The participant will be able to identify older adults at risk for poor diabetes outcomes during assessment of participant’s eating behaviors. As part of an ongoing study to identify barriers to diabetes management in older adults, we assessed community-living adults age ⱖ 70 years with diabetes, with hemoglobin A1C (A1C) ⬎8 %, randomized into the intervention-arm. Fifty-four participants (average age 75.5⫾4.7years, duration of diabetes19.8⫾12years, A1C 9.3⫾1.2%, 70% type 2 diabetes, 58% female) were evaluated. A registered dietitian/certified diabetes educator conducted a thorough clinical assessment of participants’ eating behaviors via semistructured interview to ascertain whether participants skipped meals or consumed meals without significant carbohydrate (ⱕ 5 grams/meal). These behaviors are contrary to standard medical nutrition therapy for patients with diabetes. Glycemic control was measured by A1C and diabetes-related distress was measured by Problem Areas in Diabetes (PAID) survey. Patients were divided into 2 groups: “Carb Skippers” (skipped meals and/or sometimes ate ⱕ 5 grams carbohydrate/meal, n⫽35) and “Carb Non-skippers” (did not skip meals and usually ate ⬎5 grams carbohydrate/meal, n⫽19). Logistic regression analysis showed that “Carb Skippers” were at higher risk of elevated A1C (Odds Ratio (OR)⫽ 2.32 for each 1-point increase in A1C, p⫽0.04), higher BMI (OR⫽1.26, p⫽0.01) and higher PAID score (OR⫽ 1.08, p⫽0.05), and showed a trend for lower selfreported exercise score (OR⫽ 0.51, p⫽0.06). These data suggest that, in elderly patients with diabetes, behaviors such as skipping meals or eating inadequate carbohydrate are frequent. Assessment of this issue, especially in patients with poor glycemic control, high BMI or high diabetes-related distress should be considered. Funding Disclosure: American Diabetes Association; Department of Defense
A-40 / September 2010 Suppl 2—Abstracts Volume 110 Number 9
POSTER SESSION: PROFESSIONAL SKILLS; NUTRITION ASSESSMENT; MEDICAL NUTRITION THERAPY The Quality of Nutritional Intake in Children with Autism Author(s): J. Altenburger,1 M. E. Geraghty,1 K. Wolf,1 C. A. Taylor,1 A. E. Lane2; 1Medical Dietetics, The Ohio State University, Columbus, OH, 2Occupational Therapy, The Ohio State University, Columbus, OH Learning Outcome: The participant will be able to discuss deficient nutrient intakes in children with autism. Background: Autism is a neurodevelopmental disorder that affects 1 in every 91 US children. The nutritional status of children with autism may be compromised by common behaviors, such as aberrant mealtime behaviors, food aversions or selectivity, and gastrointestinal pathology. Methods: This prospective study investigated the dietary intakes of children with autism aged 3-9 years (n⫽24). Three-day food records were analyzed to determine 1) macro and micronutrient intakes before and after self-supplementation of vitamins and minerals (SSVM) and 2) trends in the MyPyramid’s food group selection. Descriptive statistics were used to derive mean nutrient intakes and the proportion with intakes ⱖ 80% of Dietary Reference Intake (DRI). Results: Nutrients commonly inadequate were those that are important for bone health (vitamins A, D, and K, with 58.3%, 58.3%, and 91.7% consuming intakes ⬍80% DRI, respectively), digestion and metabolic pathways (pantothenic acid and biotin, with 54.2% and 54.2% consuming intakes ⬍80% DRI), and brain health (choline and vitamin D with 95.8% and 58.3% consuming intakes ⬍80% DRI). Vegetables and dairy were most frequently absent, with only 5 of 24 participants meeting recommended intakes for either group. Nutrient-contributing dietary supplements were reported as used daily by 45.8% of the sample (n⫽11). However, SSVM showed only marginal benefits in improving the proportion meeting reference intake levels. Conclusion: Great variation and areas of concern in nutrient intakes and food selection patterns were documented in this sample. Individualized nutrition assessment and counseling, especially regarding the use of appropriate supplementation, may be useful for children with Autism. Funding Disclosure: Maternal and Child Health Bureau- Association of University Centers on Disabilities- LEND Program grant
Effects of Exercise Training and/or Metformin for 12 weeks on Body Weight and Energy Intake in Individuals with Prediabetes Author(s): S. K. Malin,1 S. Choi,2 L. J. Thistle,1 B. Braun1; Department of Kinesiology, University of Massachusetts, Amherst, MA, 2Department of Family, Nutrition and Exercise Sciences, Queens College, CUNY, Flushing, NY 1
Learning Outcome: To understand how exercise and/or metformin influence body weight and food intake in individuals with prediabetes. Weight loss is one effective mechanism for opposing Type-2 diabetes. Metformin, a common oral medication prescribed for Type-2 diabetes commonly induces slight weight loss. Increased physical activity can also result in weight loss if the energy expended is not compensated for by increased caloric intake. The purpose of this study was to examine the effects of 12 weeks of exercise training and/or metformin on body weight and food intake in individuals with prediabetes. Twenty-seven men (m) and women (f) with prediabetes participated in a double-blind, longitudinal study. Subjects were randomized to placebo (P; 4f, 2m), metformin (Met; 5f, 2m), exercise training and placebo (EP; 3f, 4m), or exercise training and metformin (EMet; 5f, 2m) groups. Body weight (BW), energy intake (3-day food records), perceived appetite and habitual physical activity (PA) were measured at baseline, 6-weeks, and 12-weeks. Data were analyzed using a 2 way ANOVA. Metformin, with or without training, lowered BW by approximately 4% (p ⬍0.05) but there was no change with EP or P. Compared to baseline, EMet reduced caloric intake at week 6 (p ⬍0.05) and 12 (p ⬍0.05). Although not statistically significant, Met tended to lower caloric intake at week 6 and 12 (p ⫽0.1). These data suggest that metformin, with or without exercise reduces food intake and lowers body weight. Combining exercise with metformin is more effective at causing weight loss than exercise alone. The role of body weight changes in mediating improved metabolic health in these subjects remains to be determined. Funding Disclosure: NIH 5 R56 DK081038
Nutrition Registry Assists with Data Collection Determining Results of a Dietitian’s Intervention for Patients with a Diagnosis of Diabetes after Three Counseling Sessions Author(s): M. A. Zeller, S. Kent, A. Saldivar; Nutrition Therapy -, The Cleveland Clinic, Solon, OH Learning Outcome: Increased awareness for participants of tools available for quality nutrition research. An electronic medical record (EMR) can serve as a resource tool for data collection when performing outcomes research. In the summer of 2009 a grant was received to develop a nutrition database. The database accepts documented information from the EMR including medical diagnoses, lab results, anthropometrics, appointment records and documentation of the nutrition care process using standardized language. The impact of nutrition counseling by a registered dietitian related to diabetes care was investigated. Patients counseled by a registered dietitian for 3 appointments between January 2008 and January 2010 with a diagnosis of Diabetes were identified. EMR search data points selected include name of the practitioner and diagnosis of diabetes. Once the cohort (207) was determined data points were obtained for pre and post weight, BMI, and HgA1c. Selection for 3 appointments with coordinated HgA1c labs resulted in 88 patients (females 46, males 42) with an average age 62 years. Results were: Weight: baseline average of 101.63Kg and at third visit 97.63Kg (Avg change -4 Kg/stnd dev 3.9). BMI: baseline 34.95 Kg/m2 and third visit 33.49Kg/m2 (Avg change 1.38Kg/m2 Stnd dev 1.34 Kg/m2). HgA1c: baseline 7.85% after third visit 6.82 % (change 1.04% /stnd dev 1.44%). HgA1c reduction results in reduced coronary heart disease risk and all cause mortality. Using a nutrition database assists with data documentation and collection without extensive use of a clinician’s time. The process initially requires time investment to learn how to filter the information for quality research, but once mastered, information can be retrieved with relative ease. Funding Disclosure: None
Sub-Optimal Eating Behaviors in Older Adults with Diabetes Author(s): E. Suhl, J. Giusti, A. Sternthal, R. McCartney, Y. Lee, K. Weinger, M. Munshi; Research Division, Joslin Diabetes Center, Boston, MA Learning Outcome: The participant will be able to identify older adults at risk for poor diabetes outcomes during assessment of participant’s eating behaviors. As part of an ongoing study to identify barriers to diabetes management in older adults, we assessed community-living adults age ⱖ 70 years with diabetes, with hemoglobin A1C (A1C) ⬎8 %, randomized into the intervention-arm. Fifty-four participants (average age 75.5⫾4.7years, duration of diabetes19.8⫾12years, A1C 9.3⫾1.2%, 70% type 2 diabetes, 58% female) were evaluated. A registered dietitian/certified diabetes educator conducted a thorough clinical assessment of participants’ eating behaviors via semistructured interview to ascertain whether participants skipped meals or consumed meals without significant carbohydrate (ⱕ 5 grams/meal). These behaviors are contrary to standard medical nutrition therapy for patients with diabetes. Glycemic control was measured by A1C and diabetes-related distress was measured by Problem Areas in Diabetes (PAID) survey. Patients were divided into 2 groups: “Carb Skippers” (skipped meals and/or sometimes ate ⱕ 5 grams carbohydrate/meal, n⫽35) and “Carb Non-skippers” (did not skip meals and usually ate ⬎5 grams carbohydrate/meal, n⫽19). Logistic regression analysis showed that “Carb Skippers” were at higher risk of elevated A1C (Odds Ratio (OR)⫽ 2.32 for each 1-point increase in A1C, p⫽0.04), higher BMI (OR⫽1.26, p⫽0.01) and higher PAID score (OR⫽ 1.08, p⫽0.05), and showed a trend for lower selfreported exercise score (OR⫽ 0.51, p⫽0.06). These data suggest that, in elderly patients with diabetes, behaviors such as skipping meals or eating inadequate carbohydrate are frequent. Assessment of this issue, especially in patients with poor glycemic control, high BMI or high diabetes-related distress should be considered. Funding Disclosure: American Diabetes Association; Department of Defense
A-40 / September 2010 Suppl 2—Abstracts Volume 110 Number 9