Data from the ASU Arizona Insulin Registry (AIR) registry and the USC Study of Latino Adolescents at Risk for diabetes project were used to test the cross-sectional and prospective utility of novel biomarkers to identify youth at risk for type 2 diabetes. Pediatric and adult data from the ASU AIR registry were assessed to examine the association of single nucleotide polymorphisms (SNPs) with type 2 diabetes risk. Three KCNQ1 SNPs (rs151290; rs2237892; rs2237895) were examined as novel genetic variants for type 2 diabetes in Latinos.
Latino youth with a biphasic response in the AIR registry exhibited significantly better β-cell function (P < 0.05) compared to youth with a monophasic response. Additionally, Latino youth with a 1-hr glucose ≥155 mg/dL exhibited a significantly greater decline in β-cell function over 8 years compared with the <155 mg/dL group (β=-327.8±126.2, P = 0.01). Moreover, a 1-hr glucose ≥155 mg/dL was associated with a 2.5 times greater risk for developing prediabetes over time (P = 0.0001). 1-hr glucose was the most powerful predictor of prediabetes (area under the receiver operating characteristic curve=0.73) when compared to the traditional biomarkers including HbA1c (0.58), fasting (0.67), and 2-hr glucose (0.64). Two KCNQ1 SNPs (rs151290 and rs2237892) exhibited significant associations with type 2 diabetes risk factors. For the novel glycemic markers, 15 SNPs were associated with the glucose response curve, while 18 SNPs were associated with 1-hr glucose.
These data suggest that glucose response curve and 1-hr glucose during an OGTT independently differentiate type 2 diabetes risk among Latino youth. Furthermore, it was successful to replicate the association of type 2 diabetes risk with 2 KCNQ1 SNPs in a Latino population. Data suggest that novel glycemic biomarkers are influenced by genetic background in this high-risk population.
ormoglycemic controls (NC), dyslipidemic
ormoglycemic (DN), dyslipidemic/prediabetic (DPD) and dyslipidemic/diabetic (DD). Total cholesterol (TC) was 30% higher among DD than in NC participants (p<0.0001). The DPD group had 27% and 12% higher LDL-C concentrations than the NC and DN groups, respectively. Similarly, LDL-C was 29% and 13% higher in DD than in NC and DN participants (p=0.013). An increasing trend was observed in %10-year CVD risk with increasing degree of hyperglycemia (p<0.0001). The NC group had less cholesterol in sdLDL particles than dyslipidemic groups, regardless of glycemic status (p<0.0001). When hyperglycemia was part of the phenotype (DPD and DD), there was a greater proportion of total and HDL-C in sHDL particles in dyslipidemic individuals than in NC (p=0.023; p<0.0001; respectively). Percent 10-year CVD risk was positively correlated with triglyceride (TG) (r=0.384, p<0.0001), TC (r=0.340, p<0.05), cholesterol in sdLDL(r=0.247; p<0.05), and TC to HDL-C ratio (r=0.404, p<0.0001), and negatively correlated with HDL-C in intermediate and large HDL(r=-0.38, p=0.001; r=0.34, p=0.002, respectively). The TC/HDL-C was positively correlated with cholesterol in sdLDL particles (r=0.698, p<0.0001) and HDL-C in sHDL particles (r=0.602, p<0.0001), and negatively correlated with cholesterol in small (r=-0.35, p=0.002), intermediate (r=-0.91, p<0.0001) and large (r=-0.84, p<0.0001) HDL particles, and HDL-C in the large HDL particles (r=-0.562, p<0.0001). No significant association was found between %10-year CVD risk and hsCRP. Collectively, these results corroborate that dyslipidemic Mexican-American adults have higher CVD risk than normolipidemic individuals. Hyperglycemia may further affect CVD risk by modulating cholesterol in LDL and HDL subfractions.
Investigation one revealed a moderate-to-large effect size for school-based interventions (n=10) increasing CVF (g=0.75; 95%CI [0.40-1.11]). Multi-level interventions (g=.79 [0.34-1.25]) were more effective than interventions focused on the individual (g=0.67 [0.12-1.22]). In investigations two and three children (78.3% Hispanic; mean ± SD age 53.2±4.5 months) completed a mean ± SD 3.7±2.3 PACER laps and 19.0±5.5 CSMP criteria. Individual and family factors associated with PACER laps included child sex (B=-0.96, p=0.03) and age (B=0.17, p<0.01), parents’ promotion of inactivity (B=0.66, p=0.08) and screen time (B=0.65, p=0.05), and parents’ concern for child’s safety during physical activity (B=-0.36, p=0.09). Child age (B=0.47, p<0.01) and parent employment (B=2.29, p=0.07) were associated with CMSP criteria. At the ECEC level, policy environment quality (B=-0.17; p=0.01) was significantly associated with number of PACER laps completed. Outdoor play environment quality (B=0.18; p=0.03), outdoor play equipment total (B=0.32; p<0.01) and screen time environment quality (B=0.60; p=0.02) were significantly associated with CMSP criteria. Researchers, ECEC teachers and policy makers should promote positive environmental changes to preschool-aged children’s family and ECEC environments, as these environments have the potential to improve CVF and GLS more than programs focused on the child alone.
Purpose: To evaluate the acute effects of a 15-min postmeal walk on glucose control and markers of oxidative stress following a high-carbohydrate meal.
Methods: Ten obese subjects (55.0 ± 10.0 yrs) with impaired fasting glucose (107.1 ± 9.0 mg/dL) participated in this repeated measures trial. Subjects arrived at the laboratory following an overnight fast and underwent one of three conditions: 1) Test meal with no walking or fiber (CON), 2) Test meal with 10g fiber and no walking (FIB), 3) Test meal with no fiber followed by a 15-min treadmill walk at preferred walking speed (WALK). Blood samples were taken over four hours and assayed for glucose, insulin, thiobarbituric reactive substances (TBARS), catalase, uric acid, and total antioxidant capacity (TAC). A repeated measures ANOVA was used to compare mean differences for all outcome variables.
Results: The 2hr and 4hr incremental area under the curve (iAUC) for glucose was lower in both FIB (2hr: -93.59 mmol∙120 min∙L-1, p = 0.006; 4hr: -92.59 mmol∙240 min∙L-1; p = 0.041) and WALK (2hr: -77.21 mmol∙120 min∙L-1, p = 0.002; 4hr: -102.94 mmol∙240 min∙L-1; p = 0.005) conditions respectively, compared with CON. There were no differences in 2hr or 4hr iAUC for glucose between FIB and WALK (2hr: p = 0.493; 4hr: p = 0.783). The 2hr iAUC for insulin was significantly lower in both FIB (-37.15 μU ∙h/mL; p = 0.021) and WALK (-66.35 μU ∙h/mL; p < 0.001) conditions, compared with CON, and was significantly lower in the WALK (-29.2 μU ∙h/mL; p = 0.049) condition, compared with FIB. The 4hr iAUC for insulin in the WALK condition was significantly lower than both CON (-104.51 μU ∙h/mL; p = 0.001) and FIB (-77.12 μU ∙h/mL; p = 0.006) conditions. Markers of oxidative stress were not significantly different between conditions.
Conclusion: A moderate 15-minute postmeal walk is an effective strategy to reduce postprandial hyperglycemia. However, it is unclear if this attenuation could lead to improvements in postprandial oxidative stress.
Vegetarian diets are associated with factors that may not support bone health, such as low body mass and low intakes of protein; yet, these diets are alkaline, a factor that favors bone mineral density (BMD). This study compared the correlates of BMD in young, non-obese adults consuming meat-based (n = 27), lacto-ovo vegetarian (n = 27), or vegan (n = 28) diets for ≥1 year. A 24 h diet recall, whole body DXA scan, 24 h urine specimen, and fasting blood sample were collected from participants. BMD did not differ significantly between groups. Protein intake was reduced ~30% in individuals consuming lacto-ovo and vegan diets as compared to those consuming meat-based diets (68 ± 24, 69 ± 29, and 97 ± 47 g/day respectively, p = 0.006); yet dietary protein was only associated with BMD for those following vegan diets. Urinary pH was more alkaline in the lacto-ovo and vegan groups versus omnivores (6.5 ± 0.4, 6.7 ± 0.4, and 6.2 ± 0.4 respectively, p = 0.003); yet urinary pH was associated with BMD in omnivores only. These data suggest that plant-based diets are not detrimental to bone in young adults. Moreover, diet prescriptions for bone health may vary among diet groups: increased fruit and vegetable intake for individuals with high meat intakes and increased plant protein intake for individuals who follow a vegetarian diet plan.