Tina Crook

Dietary Intake and Plasma Levels of Choline and Betaine in Children with Autism Spectrum Disorders

Abnormalities in folate-dependent one-carbon metabolism have been reported in many children with autism. Because inadequate choline and betaine can negatively affect folate metabolism and in turn downstream methylation and antioxidant capacity, we sought to determine whether dietary intake of choline and betaine in children with autism was adequate to meet nutritional needs based on national recommendations. Three-day food records were analyzed for 288 children with autism (ASDs) who participated in the national Autism Intervention Research Network for Physical Health (AIR-P) Study on Diet and Nutrition in children with autism. Plasma concentrations of choline and betaine were measured in a subgroup of 35 children with ASDs and 32 age-matched control children. The results indicated that 60–93% of children with ASDs were consuming less than the recommended Adequate Intake (AI) for choline. Strong positive correlations were found between dietary intake and plasma concentrations of choline and betaine in autistic children as well as lower plasma concentrations compared to the control group. We conclude that choline and betaine intake is inadequate in a significant subgroup of children with ASDs and is reflected in lower plasma levels. Inadequate intake of choline and betaine may contribute to the metabolic abnormalities observed in many children with autism and warrants attention in nutritional counseling.

Nutrient Intake among Children with Autism

The objective of this study was to examine adequacy of nutrient intake and determine the impact of multivitamin use on nutrient intake in children with autism. This was a retrospective analysis of food frequency questionnaire data collected from 54 children, ages 2-8 years, in the Autism Integrated Metabolic and Genomic Endeavor Study at Arkansas Children’s Hospital Research Institute, Little Rock, AR. The average percent of Kilocalories from carbohydrate, protein and fat fell within the acceptable macronutrient distribution ranges at 56%, 14% and 33%, respectively. Mean intakes for calcium, potassium, vitamin E, vitamin D and fiber were below the dietary reference intake (DRI) levels at 75%, 57%, 77%, 25% and 41%, respectively. Mean intakes of vitamin A, thiamin, riboflavin, vitamin C, and vitamin B6 exceeded the DRI at 216%, 233%, 270%, 452% and 228%, respectively. No differences were found in vitamin D, vitamin E, calcium, total kilocalorie, carbohydrate, protein and fat intake between children who were multivitamin users and those who were non-users. These data indicate that children with autism have diets adequate in kilocalories and macronutrients, while imbalances exist in fiber and several micronutrients. Dietary interventions for children with autism should be aimed at addressing these potential nutritional imbalances.

Impact of Menu Labeling on Food Choices of Southern Undergraduate Students

Americans consume more meals away from home at fast-food and dine-in restaurants. The restaurant foods are notorious for their energy density and large portion sizes. The objective of our study was to determine whether or not the addition of calorie information to a restaurant menu affects the calorie content of meals ordered by college students. Study participants were selected from a random sample of 1,025 undergraduate students (≥ 18 years old). Data analyses included descriptive statistics and both paired-samples and independent-samples t-tests. Our data analysis found a significant difference between the number of calories chosen from the first menu (without calorie labels) versus the second menu (with calorie labels) (p=0.001, 2-tailed). Analysis also showed that there was no significant difference in calories ordered from the first menu versus the second menu for those who had taken a college-level nutrition class and those who had not (p=0.051, 2-tailed). Our findings suggest that menu calorie labels can positively affect college students’ meal selections making them lower in calories; however, no particular group of students was more likely than any other to change their menu selections after seeing the calorie labels. Further research is needed to determine if use of calorie labels will decrease the number of calories ordered at fast-food and dine-in restaurants among other populations.

Relationship between level of HbA1C and breast cancer

Background Diabetes and cancer are public health issues worldwide; studies have shown that diabetes is related to increased breast cancer mortality. The purpose of this study was to examine associations between HbA1C and obesity with tumor stage and mortality among breast cancer patients. Methods Data for 82 patients with breast cancer (36–89 years of age, diagnosed /treated 1999–2009) were provided by the University of Arkansas for Medical Sciences (UAMS) Data Trust Warehouse. Survival time was estimated from start date of service to date of last follow-up or date of death. The Kaplan–Meier method provided analysis of survival curves for two groups of HbA1C (HbA1C < 6.5% vs HbA1C ≥ 6.5%) and two groups of BMI (BMI < 30 vs BMI ≥ 30 kg/m2); survival curves were compared using log-rank tests. Associations between HbA1C and BMI, and between HbA1C and tumor stage were determined by chi-square. Results The relationship between tumor stages and HbA1C was not statistically significant (X2 = 0.093, p = 0.47, df = 1). The relationship between obesity and HbA1C was statistically significant (X2 = 6.13, p = 0.013, df = 1). Log-rank tests did not show statistically significant differences between survival curves (HbA1C curves, p = 0.4; Obesity curves, p = 0.09). Conclusion While there was a statistically significant association between HbA1C and obesity, there were no significant associations found with this analysis. However, there are clinically meaningful relationships based on observed trends. Future directions for research may involve exploring a larger sample of patients and the role of therapeutic regimens on blood sugar control and BMI of breast cancer patients and influence on cancer prognosis.