Abstract

Incidence rates of adolescents with type 2 diabetes are increasing rapidly; there was an increase of 30% between 2019 and 2009. Even more alarming is that studies show that the most effective treatment, metformin monotherapy, is only effective at maintaining glycemic control in approximately 50% of individuals. Additionally, adolescents with diabetes may experience serious microvascular and macrovascular complications sooner than adults, which can impact the quality of life of young adults across the globe. Therefore, diabetes in adolescents is a public health concern, and there is very little research to guide treatment and prevention. It is widely known that adolescents have a very poor dietary pattern, characterized by increased intakes of added sugars from refined grains, and minimal amounts of fruits, vegetables, and fiber. There is conflicting evidence in the literature connecting increased added sugar intake to insulin resistance and diabetes development. Considering the very poor diets consumed by adolescents, and that nutrition is a modifiable risk factor for diabetes, we aimed to examine the associations between added sugar consumption, glycemic values, and measures of insulin resistance and beta-cell function. This pilot study analyzed dietary and glycemic data from participants that were screened for an ongoing randomized control trial which is an adolescent diabetes prevention program that uses health coaching to improve diet and physical activity behaviors called the Dietary Intervention for Glucose Tolerance in Teens (Dig It) Study. Fasting blood glucose, glycated hemoglobin (HbA1c), and 2-hour glucose concentrations were collected during an oral glucose tolerance test that was used to screen adolescents with obesity for diabetes. Consumption of added sugar and other dietary intake data were collected from food records created by the Technology Assisted Dietary Assessment (TADA) application. The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated from glucose and insulin concentrations in the fasting state (1) obtained from an oral glucose tolerance test (OGTT). Whole-body insulin sensitivity index (WBISI), and the oral disposition index (DI) were calculated from measures obtained during oral glucose tolerance testing(2, 3) Statistical analysis was performed using SPSS software and included independent t-tests and Pearson correlations. Of the 48 participants included in this analysis, 59.2% were female, 32% were African American, 57% were white, and 8.2% were more than one race. The mean age was 16.20 ± 2.7 years, and 42% had prediabetes. Those with normoglycemia consumed 11.0 ± 5.1% of energy from added sugars, compared to 9.4±5.1% energy from added sugars for individuals with prediabetes. There was no significant correlation between HbA1c and percent calories coming from added sugar (R= -0.237, P=0.063), percent calories coming from added sugar and fasting blood glucose (R= 0.208, P= 0.090), or percent calories from added sugar and 2-hour glucose (R= 0.017, P= 0.457). There were no significant correlations found between percent calories from added sugar and HOMA-IR (R= 0.129, P= 0.234), percent calories from added sugar and WBISI (R= -0.069, P= 0.350), or percent calories from added sugar and DI (R= -0.118, P= 0.253). There were also no significant differences between the mean values of HbA1c, fasting glucose, or 2-hour glucose between individuals that consumed high vs. low amounts of added sugar, as measured by an independent t-test. The p-values were 0.634, 0.434, and 0.234 respectively. To examine the extent to which % calories from added sugar predicted variances in glycemic values, hierarchical multiple regression analyses were performed. Once energy, physical activity, BMI Z-Score, and age were entered into the model, % energy from added sugar accounted for an additional 9.6% variance in HbA1c. In conclusion, we did not find significant associations between consumption of added sugar and glycemic and insulin resistance or beta-cell function outcomes in adolescents who are obese, however our study lacked sufficient power. While our findings were not definitive, studies to identify dietary factors that promote or prevent hyperglycemia and insulin resistance are needed to inform dietary intervention strategies that may be effective at decreasing T2D in adolescents. 12

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