Dietary Absence of Fruits and Vegetables over a 3-Day Period: An Analysis Comparing Children with Autism Spectrum Disorder (ASD) and Typically Developing (TD) Children

Dietary Absence of Fruits and Vegetables over a 3-Day Period: An Analysis Comparing Children with Autism Spectrum Disorder (ASD) and Typically Developing (TD) Children

TUESDAY, OCTOBER 18 Poster Session: Professional Skills; Nutrition Assessment; Medical Nutrition Therapy Diet Quality among Past, Current, and Never ...

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TUESDAY, OCTOBER 18

Poster Session: Professional Skills; Nutrition Assessment; Medical Nutrition Therapy Diet Quality among Past, Current, and Never Users of Cannabis: Data from NHANES 2007-2012

Dietary Predictors of Fecal Microbiota Transplantation Success

Author(s): A. Gelfand, C. Tangney; Rush University Medical Center

Author(s): S. Thompson1, H. Guetterman1, A. Taylor1, A. Bogner2, D. Martin2, J.J. Farrell3, K.S. Swanson1, H. Holscher1; 1University of Illinois at Urbana-Champaign, 2OSF Saint Francis Medical Center, 3University of Illinois College of Medicine

Learning Outcome: Participants will be able to describe diet quality differences among current, past, and never users of cannabis, using data from the National Health and Nutrition Examination Survey from years 2007-2012.

Learning Outcome: Understand the impact of dietary factors on fecal microbiota transplant (FMT) success in patients undergoing FMT for Clostridium difficile infection.

Background: Currently 23 states have legalized cannabis for medicinal and/or recreational use, but there are limited data on the safety, efficacy, and health effects. While there are a few reports on dietary intakes of cannabis users, to the best of our knowledge, diet quality of users has not been described. Methods: Self-reported data from 8503 participants in the National Health and Nutrition Examination Survey (NHANES) from years 2007-2012 on cannabis use, and the average of two 24-hour diet recalls were used. Diet quality was evaluated using the Healthy Eating Index-2010 (HEI-2010) scoring algorithm. Current users were classified as using cannabis within the last month, past users reported using cannabis but not in the last month, and never users reported never using cannabis. SPSS (version 23) with the Complex Sample module was used to run all general linear models with adjustment for age, sex, education, and race-ethnicity. Results: Current users (n¼1085, (ages, 34.3  0.6y (mean  SE)) were younger than the 4127 never users (ages, 39.2  0.5y) and 3295 past users (ages, 40.30.4y), p<.002). Small differences in total and component HEI scores were observed across groups. When compared to never users, current users had lower total HEI scores (55.60.4 (never) vs 53.50.8 (current), p¼0.22), lower empty calories scores (13.2 0.2 vs 11.80.3, p¼0.26), but higher refined grain scores (6  0.1 vs 7  0.2, p¼0.02). (This means current users consumed less refined grains than never or past users.) Conclusion: Based on these national data, small differences in dietary quality were observed for current cannabis and non-cannabis users with need for much improvement for all.

Background: Fecal microbiota transplantation (FMT) has become a standard treatment for Clostridium difficile infection (CDI) that is unresponsive to conventional therapy. However, the mechanisms and predictors of transplant success are unknown. The presumed mechanism of action for FMT success is restoration of intestinal microbial diversity. As diet affects microbiota stability, diversity, and composition, further research is needed to elucidate the impact of diet on FMT success. We aimed to determine which dietary factors are predictive of FMT success. We hypothesized that patients with higher dietary fiber intakes would experience improved microbiota re-establishment.

Methods: FMT patients completed Diet History Questionnaires (DHQII, Past Month with Portion Size) and provided stool specimens prior to FMT, and at 30 and 90 days post FMT. DHQII data were processed using Diet*Calc software and Healthy Eating Index scores were generated using SAS 9.4. Successful treatment (ST) was defined as CDI symptom resolution following FMT. Failed treatment (FT) was defined as diarrhea with >3 stools/day or retreatment within 30 days of FMT. Results: Two donors and 16 patients completed DHQIIs. ST was observed for 12/16 patients. Total fruit servings and fiber (g/kcal) differed significantly among groups, with donors and ST patients reporting higher fruit and fiber consumption than FT patients (p<0.05). Percentage of energy from carbohydrates was higher (p¼0.04) in ST patients compared to FT patients. Conclusions: The data support our hypothesis that higher consumption of dietary fiber is predictive of microbiota transplantation success among a subset of CDI patients. Funding Disclosure: Partial funding for this study was provided by the USDA National Institute of Food and Agriculture, Hatch project ILLU-538-384

Funding Disclosure: None

Dietary Absence of Fruits and Vegetables over a 3-Day Period: An Analysis Comparing Children with Autism Spectrum Disorder (ASD) and Typically Developing (TD) Children Author(s): A. Swartz1, K. Patton1, S. Phillips2, L. Truex3, M. Weems3, A. Must2, L. Bandini1,3; 1 Boston University, Sargent College of Health & Rehabilitative Sciences, 2Dept. of Public Health & Community Medicine, Tufts University School of Medicine, 3University of Massachusetts Medical School-E.K. Shriver Center

Dietitians in Private Practice: Outstanding Outcomes! Author(s): A. Martin, K. Patalano; Private Practice Learning Objective: Nutrition counseling has a huge impact in changing lifestyle factors, but a lack of documentation limits dietitians from proving their effectiveness. Our objective is to demonstrate the importance of an electronic medical record in documenting the beneficial impact of nutrition counseling.

Learning Outcome: Attendees will recognize the importance of assessing fruit and vegetable intake in children with ASD, and understand the need for tailored interventions to improve fruit and vegetable intake in this population.

Background: Recent studies link low fruit and vegetable intake and chronic disease risk. Feeding behaviors in children with ASD may lead to the exclusion of these foods from the diet. Despite reports of food selectivity in children with ASD, studies that quantify fruit and vegetable intake are limited. Methods: 3-day food records from 48 children with ASD and 56 TD children, aged 3-11, enrolled in the Children’s Mealtime and Activity Patterns Study (CHAMPS), were analyzed for the absence of fruits and vegetables. 100% juice was recorded separately from fruit, and fried potatoes were recorded separately from vegetables. Differences between children with ASD and TD children were evaluated by chi-square tests. Results: Children were mean age 6.7 years; 80% were boys. Over the three-day period, 33% of children with ASD and 4% of TD children had no vegetable on any day (p<0.001). Differences remained significant when fried potatoes were included in the vegetable category, (25% vs. 0%, p<0.001). Seventeen percent of children with ASD had no fruit over the 3-day period compared to 18% of TD children (p¼0.87). Including 100% juice reduced these proportions to 2% and 11%, respectively (p¼0.12). Conclusions: Compared to TD children, a greater proportion of children with ASD did not consume any vegetables over the 3 days. Although a substantial proportion of children in both groups did not consume any fruit over the 3-day period, proportions were similar. Future research should explore the factors associated with reduced fruit and vegetable intake in children with ASD. Funding Disclosure: Grant Funding: NIH R21HD048989 ; HRSA/MCHB UA3MC25735-

The dataset includes 30,719 observations for unique patient visits to dietitians. The data is collected from 148 dietitians and 11,858 de-identified patients. The subset of the data set we focused on for our analysis included 5,923 patients who each had a minimum of 2 visits to the dietitian (dataset had median of 4 visits and average of 8 visits). Our data set contains these variables (columns) for each unique “patient event” (row) by a patient to a dietitian: Anonymous Patient ID, Dietitian ID, Date of Service, numeric biometrics including Weight, Height, Cholesterol, Fasting Blood Sugar, LDL, HDL, TG, %Body Fat, VitD, BMI, descriptive variables including Activity description, Medications and Diagnosis codes used for insurance billing. Our analysis focused on weight as a dependent variable, because it is commonly agreed upon among medical literature to be the primary factor correlated with Type II Diabetes. It is the primary metric that dietitians focus on in their patient care, and it was also the most consistently recorded metric in our dataset, captured on 75% of the patient visits. The most significant variable for predicting weight loss was initial weight; we think this is due to low hanging fruit e it’s easier to lose weight for the more overweight. Our final geographic mapping exercise did reveal fewer dietitians/diabetic capita in states with the highest percentage of diabetes, which could be stretched to suggest a correlation between dietitian care and diabetes prevention. Funding Disclosure: None

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The primary objective for this analysis is to provide data to strengthen the argument for nutrition counseling by registered dietitians in the prevention and treatment of diabetes.

JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

September 2016 Suppl 1—Abstracts Volume 116 Number 9