Day 1 :
University of Missouri School of Medicine, USA
Keynote: Effect of information technology and informatics on the treatment and control of type 2 diabetes
Time : 09:30-10:15
Eduardo J Simoes is the Chair and a Distinguished Professor in the Department of Health Management and Informatics, University of Missouri School of Medicine (2011-current). He has done his Medical degree from Faculdade de Medicina, Universidade de Pernambuco-Brazil (1976-1981), Diploma and Master of Science degree from the University of London School of Hygiene Tropical Medicine (1986-1987). He has done another Master’s degree in Public Health from Emory University School of Public Health (1989-1991). He is a Fellow of the American College of Epidemiology, Reviewer and Editor for 12 journals. He has published over 100 peer-reviewed publications, 8 book chapters and 18 reports.
Diabetes is the fourth cause of death in the United States. Both IT and HI have been applied in the management of diabetes but their effect have been inconsistent. We used meta-analysis to identify a common effect of HI and IT across multiple studies on estimated average glucose (eAG). We found 370 articles based on search of randomized trials only. We excluded 328 articles, with 23 based on title and 305 based on abstract. We reviewed the full text of 42 articles that fit criteria for inclusion. After discarding 23 studies with incomplete information, we analyzed 19 articles. We estimated an IT and HI combined measure of reduction in eAG per mmol/L across 26 point estimates in 19 studies. We estimated a Hedges’ g effect size across the 26 point estimates. IT- and HI-based strategies for patient engagement or clinical decision support included mobile, computer-based, e-mail and internet approaches. We found reductions in eAG per mmol/L due to combined IT and HI across all 19 studies. Reductions in eAG levels were statistically significant (p-value≤0.05) in 15 out of 26 estimates. The combined HI or IT eAG reductions per mmol/L averaged -0.716 (-0,928, -0.503) with values ranging from -0.08 to a -2.02. This average reduction in eAG values is equivalent to a 1.7% in A1c. We found a standardized effect size (Hedges’ g) of 0.625 (0.434, 0.816) across all studies and estimates. Findings indicated both statistically and clinically significant effects of either IT or HI on diabetes prevention and control.
University of New England, Australia
Keynote: Effect of wine on postprandial serum insulin, plasma glucose, serum IgA and insulin sensitivity as all wines are not the same
Time : 10:15-11:00
Anna Kokavec is a Registered Psychologist and a member of the Australian Psychological Society. She has a PhD in Biological Psychology from La Trobe University, Australia and is currently employed as a Senior Lecturer in the School of Health, University of New England, Australia. She previously held academic positions at La Trobe University (Neuroscience and Research Methods) and University of Newcastle (Health Behavior Science). She has spent the last 20 years investigating the effects of commercially available alcohol on the inter-relationship between hypothalamic-pituitary-adrenal axis, energy metabolism/utilization and immune system activity. Recently, her interests have been extended to include investigation of a possible link between insulin sensitivity, nutrition and migraine. She is the author of more than 20 papers in highly respected international journals and is the listed first author for two original hypotheses aimed at explaining the effect of alcohol on biochemical processes.
Statement of the Problem: The effect of wine on glucose metabolism and utilization in non-diabetic individuals is largely unknown and requires investigation. The purpose of this study is to compare the effect of red and white wine on postprandial glucose metabolism and utilization in non-diabetic individuals.
Methodology & Theoretical Orientation: This study utilized a 3x4 mixed design. The ‘between subjects’ factor was trial (white wine, red wine, placebo) and the ‘within subjects’ factor was time (Food, 45-min, 90-min, 135-min). The experimental procedure required 24 non-diabetic males to consume food for 45-min and then ingest 4x standard units (40 g of alcohol) of white wine (n=8), red wine (n=8) or the equivalent amount of placebo (n=8) over a period of 135 minutes. Measures of serum insulin, plasma glucose and serum immunoglobulin A (IgA) were taken upon arrival (Baseline), after the meal (0 minutes) and during beverage consumption (45 minutes, 90 minutes and 135 minutes).
Findings: Significant trial differences were observed when data was compared. The level of postprandial: Plasma glucose was significantly reduced with red wine at 45 minutes (<13 g of alcohol); serum insulin was significantly reduced with white wine at 45 minutes (<13 g of alcohol); serum IgA became significantly elevated with white wine at 45 minutes (<13 g of alcohol). Moreover, a significant improvement in insulin sensitivity was only noted with white wine at 90 minutes (<30 g of alcohol).
Conclusion & Significance: Both red wine and white wine can alter postprandial glucose metabolism and utilization in non-diabetic individuals. However, the effect of red wine and white wine is not the same: white wine after a meal improves improve insulin sensitivity and promotes the development of a transient pseudo-diabetic condition; red wine after a meal alters the glucose-insulin feedback mechanism, reduces insulin sensitivity and promotes the development of a transient pseudohypoglycemic condition. Thus, consuming wine alone after a meal should not be encouraged in non-diabetics.