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NCT Number: NCT06782906

Effect of Increased Physical Activity and Stopping Evening Snacking in Metabolic Health in Youth With Prediabetes

Non-healthy eating habits and a lack of exercise contribute to prediabetes and type 2 diabetes (T2D). Evening snacking is linked to abnormal weight gain in adults and healthy adolescents. Most adolescents do not get enough exercise. This study aims to look at the benefits of more exercise and stopping evening snacking in youth with prediabetes. The study lasts 8 weeks, and participants will be randomly assigned to either an intervention group or a standard of care group.

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Key information

Age range

12 year–18 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Texas Children's Hospital / Children's Nutrition Research Center / Baylor College of Medicine

Houston, Texas, 77030, United States

Location status: Recruiting

Location contact

Mustafa Tosur, MD

CONTACT

[email protected]

832-822-3780

About this study

Poor nutrition in addition to a lack of physical activity play significant roles in childhood T2D development, primarily by negatively affecting adiposity and insulin action in concert with other T2D risk factors. Many aspects of nutrition, including frequency of eating, were examined in relation to obesity/increased adiposity and T2D risk. Previous studies suggest increased snacking may cause overeating, and potentially lead to weight gain.

Findings from adolescents in the 2005-2016 National Health and Nutrition Examination Survey (NHANES), showed those with overweight/obesity consume more snacks per day (1.85 and 1.97 snacks per day, respectively) and more calories per snack (305 and 340 kcal/snack, respectively) than their normal-weight peers (1.69 and 262 kcal/snack).Snack consumption in adolescents is also correlated with higher daily energy intake, lower fruit/vegetable intake, along with more frequent fast-food and sugar-sweetened beverage consumptions. The timing of snacking occasions has also emerged as a potential confounder. Among adults, greater evening snacking was associated with higher BMI and higher obesogenic dietary index (e.g., intake of fast food, etc.) while greater morning snacking was associated with increased fruit and vegetable consumption. Having a bedtime snack was associated with increased odds of overweight/obesity (1.47, 95% CI: 1.34-1.62) in Japanese women. Evening snacking was also shown to be independently correlated with overweight/obesity in Italian adolescents (RR 3.12, 95% CI: 1.17-8.34). In the Healthy Growth Study, children who had high-energy intake at dinner and evening snacking were more likely to skip breakfast - a metabolically unhealthy habit.

Also, despite the known metabolic benefits of physical activity, only 1 in 4 adolescents achieve recommended daily physical activity goals (60-min, moderate-to-vigorous physical activity (MVPA)/day).Both snacking and exercise may also affect metabolic health by independently modulating gene expression levels of critical metabolic pathways and subsequently intracellular signaling. Metabolic dysregulation resulting in altered plasma concentrations of several amino acids (e.g., higher branch-chain amino acid and lower glycine concentrations, etc.) was associated with insulin resistance.

Therefore, targeted interventions towards evening snacking and increased physical activity may prove beneficial in adolescents with prediabetes by preventing progression to T2D.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 12-18 years of age
  • Having a diagnosis of prediabetes
  • Engaging in frequent evening snacking
  • Inadequate physical activity

Exclusion criteria

  • Diagnosis of diabetes
  • Significant history of chronic disease
  • Evidence of significant liver or kidney disease;
  • Any hormone replacement therapy; and
  • Pregnancy.

Treatment and study plan

≥10,000 daily steps (≥5 days/week) and stopping evening snacking

Behavioral

Participants in the intervention arm will be asked to perform ≥10,000 daily steps (≥5 days/week) and omit evening snacking after 8:00 p.m.

Primary outcomes

  1. Insulin sensitivity index for glucose disposal (ISI [Gly]) during oral glucose tolerance test

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    Insulin sensitivity index for glycemia (ISI [Gly]) will be calculated with a formula using insulin and glucose area under the curves during oral glucose tolerance tests (OGTT) as described previously (Belfiore et al., Metabolism, 2001):

    ISI (Gly) = 2 / [INSp x GLYp) + 1]

    INSp: insulinemic area during OGTT with 3 (0, 1h and 2h) or 5 sampling (0, 30, 60, 90 and 120 min) GLYp: glycemic area during OGTT (0, 1h and 2h) or 5 sampling (0, 30, 60, 90 and 120 min)

    INSp and GLYp are expressed by taking the mean normal value as 1, i.e., by dividing the value observed in the person under study by the mean normal value so that, if INSp (or GLYp) is 1.5-fold the mean normal values, it will be considered as equal to 1.5, and so on. We will use appropriate "mean normal values," which will be derived from data obtained in our laboratory.

Secondary outcomes

  1. index for fat disposal (ISI [FFA]) during oral glucose tolerance test

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    Insulin sensitivity index for fat disposal (ISI [FFA]) will be calculated with a formula using insulin and free fatty acid area under the curves during oral glucose tolerance tests (OGTT) as described previously (Belfiore et al., Metabolism, 2001):

    ISI (FFA) = 2 / [INSp x FFAp) + 1]

    INSp: insulinemic area during OGTT with 3 (0, 1h and 2h) or 5 sampling (0, 30, 60, 90 and 120 min) FFAp: glycemic area during OGTT (0, 1h and 2h) or 5 sampling (0, 30, 60, 90 and 120 min)

    INSp and FFAp are expressed by taking the mean normal value as 1, i.e., by dividing the value observed in the person under study by the mean normal value so that, if INSp or FFAp) is 1.5-fold the mean normal values, it will be considered as equal to 1.5, and so on. We will use appropriate "mean normal values," which will be derived from data obtained in our laboratory.

  2. HbA1c

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    Hemoglobin A1c (HbA1c) as measured in the plasma.

  3. Percentage of adiposity (percent body fat)

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    Percent body fat as measured by DXA scan

  4. Amino acid concentrations

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    Fasting amino acid concentrations as measured in the plasma

  5. Adiponectin

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    Fasting adiponectin concentration as measured in the plasma

  6. C-reactive protein (CRP)

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    CRP concentration as measured in the plasma

  7. TNF-alpha

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    TNF-alpha concentrations as measured in the plasma

  8. Interleukin 6 (IL-6)

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    IL-6 level as measured in the plasma

  9. Gene expression levels of critical pathways

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    RNA sequencing for gene expression levels of critical metabolic pathways

  10. Total energy expenditure

    Time frame: At week 9-10 following completion of 8 weeks of intervention period

    In a subset of cohort (n=20), free-living total energy expenditure (TEE) will be measured by the doubly labeled water (DLW) over a 14-d period using multiple urine collections at different time points. This optional part will be offered to all participants, and similar number of participants will be selected randomly from both arms (intervention and standard of care arm) by balancing gender and age categories.

Study contacts

Contact information is provided by the study sponsor or research team.

Lori Malone

CONTACT

[email protected]

713-798-1070

Mustafa Tosur, MD

CONTACT

[email protected]

832-822-3780

Sponsors and collaborators

Lead sponsor

Baylor College of Medicine

Other

Registry information

Important dates

Study start
2025
Primary completion
2029
Study completion
2029
First posted
Jan 20, 2025
Registry last updated
Jun 2, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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