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Effect of millet consumption on metabolic responses responses in adult subjects

Effect of millet (Pennisetum glaucum (L.) R. Br.) consumption on metabolic responses responses in adult subjects

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
REBEC
Registry ID
RBR-2tx7m8v
Enrollment
Unknown
Registered
2023-06-26
Start date
2022-06-01
Completion date
Unknown
Last updated
2025-10-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Metabolic Phenomena

Interventions

Sensory analysis of beverages developed with pearl millet (Pennisetum glaucum (L.) R. Br.): Participants will be randomly recruited on the Viçosa campus of UFV through advertisements, flyers, and post
B01.875.800.575.912.250.822.755

Sponsors

Universidade Federal de Viçosa - Departamento de Nutrição e Saúde
Lead Sponsor
Embrapa Agroindústria de Alimentos
Collaborator

Eligibility

Age
18 Years to 60 Years

Inclusion criteria

Inclusion criteria: Have normal blood glucose levels (fasting capillary glucose ranging from 70 to 99 mg/dL); regular breakfast intake; have a Body Mass Index (BMI) between 18.5 and 24.9 kg/m² and a body fat percentage between 20 and 30% for females and between 12 and 20% for males; are between 18 and 60 years old; engage in light physical activity

Exclusion criteria

Exclusion criteria: Smokers; alcohol consumption exceeding 2 drinks per day (> 50g of ethanol/day); presence of type 1 or type 2 diabetes or prediabetes (fasting blood glucose between 100 and 125 mg/dL); first-degree family history of diabetes mellitus; use of medications that affect blood glucose, energy metabolism, or appetite; use of medications, herbs, or diets for appetite and weight reduction; weight instability (gain or loss of approximately 3 kg in the 3 months prior to the start of the study); recent change in level of physical activity; aversion or intolerance to the foods provided in the study; presence or history of digestive, hepatic, renal, cardiovascular, thyroid, or recent inflammatory diseases; diagnosis of cancer in the previous year; history of eating disorders; and being pregnant or lactating

Design outcomes

Primary

MeasureTime frame
To evaluate postprandial glycemic control, assessed using the trapezoidal method, by determining a variation with a significance level of 0.05 in blood glucose concentration measured through capillary fingerstick at -5 and 0 minutes (fasting state), as well as at 15, 30, 45, 60, 90, and 120 minutes after consuming each beverage or glucose load;To evaluate postprandial insulinemic control, using the trapezoidal method, by determining a variation with a significance level of 0.05 in blood insulin concentration measured through blood collection at 0 minutes (fasting state), as well as at 30, 60, and 120 minutes after consuming each beverage or glucose load

Secondary

MeasureTime frame
To evaluate appetite control, using the Visual Analogue Scale (VAS) method to assess variations with a significance level of 0.05 in sensations of hunger, satiety, fullness, desire for salty, sweet, fatty, or tasty foods, and food consumption perspective. These sensations will be scored by measuring the distance (in cm) from the 0 point using a ruler at different time points, such as 0 minutes (fasting state), as well as at 15, 30, 45, 60, 90, and 120 minutes after consuming each beverage or glucose load. Additionally, the Composite Satiety Score (CSS) will be calculated at each measurement moment using the following equation: CSS (cm) = (satiety + fullness + (100 - PFC) + (100 - hunger))/4;To evaluate food consumption control, a specific form will be used, which consists of a 24-hour food record after the beverage consumption. This form will record information including the time and location of meals, as well as the types and quantities of foods consumed, which can be measured in grams or household measurements. The data on grams, calorie intake, macronutrients, and dietary fibers recorded in the forms will be analyzed using the Avanutri® software (Rio de Janeiro, Brazil) and will be considered statistically different with a significance level of 0.05

Countries

Brazil

Contacts

Public ContactThauana Magalhães

Universidade Federal de Viçosa - Departamento de Nutrição e Saúde

thauana.magalhaes@ufv.br+55(31)3612-5182

Outcome results

None listed

Source: REBEC (via WHO ICTRP)