Beneficial Effects of Quinoa (Chenopodium Quinoa Willd) in the Prevention of Type 2 Diabetes Mellitus

Type 2 Diabetes Clinical Trial

Official title:

Beneficial Effects of Quinoa (Chenopodium Quinoa Willd) in the Prevention of Type 2 Diabetes Mellitus

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04529317
• Other study ID #: Quinoa
• Status: Completed
• Phase: N/A
• Start date: May 2016
• Est. completion date: September 2016

Study information

• Verified date: August 2020
• Source: Institut d'Investigacions Biomèdiques August Pi i Sunyer
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Quinoa is a pseudo-cereal and has potential health benefits and exceptional nutritional value. It is a food rich in proteins of high biological value, in unsaturated fats and fiber, it is also a grain low in carbohydrates and with a low glycemic index. Concretely, quinoa could produce a benefit on postprandial glycemia that would result in lower type 2 diabetes (T2D) incidence.

A cross-over design pilot clinical study with a nutritional intervention for 8 weeks were performed: 4 weeks on a regular diet (RD) and 4 weeks on a quinoa diet (QD). Nine subjects aged ≥65 years with prediabetes were monitored during the first 4 weeks of RD with daily dietary records and FreeStyle Libre®. Subsequently, participants started the DQ where quinoa and 100% quinoa-based products replaced foods rich in complex carbohydrates that they regularly consumed by the first 4 weeks of DR.

The glycemic measurements recorded by the sensors were considered as functions of time and the effects of nutrients consumed at the intended time period were analyzed by means of function on scalar regression (fosr) model.

Description:

The study was a cross-over pilot clinical study consisting of two periods. The first period was only an observational and monitoring phase where participants just continued with their regular diet (RD), for this reason all participants initiated this period and wash-out term was no needed. Subsequently, with the data of the first phase obtained, the subjects began the second period in which they had to undergo a nutritional intervention with a quinoa diet (QD).

A total of six visits plus two quinoa products collection days were programmed. After the pre-study visit (V0) which took place a week before start nutritional intervention and where researchers obtained signed informed consent, participants were summoned for a first visit (V1) where they were explained how they should fill in the dietary records and they were applied with the FreeStyle Libre®.

Subjects then began RD, a period of 4 weeks during which only their normal life was monitored. After the first 14 days of this, a second visit (V2) was made where the dietary record was collected that would serve to account for their usual consumption of cereals, flours, tubers and legumes, the FreeStyle Libre® sensor was also collected.

The last day on RD period, on day 28, they were cited (V3) in consultation where blood samples after an 8 hours fast, anthropometrics measurements and blood pressure measure where obtained and for the placement of the new FreeStyle Libre® sensor. Participants were asked about their physical activity and exercise practice during those past 4 weeks by a short questionnaire adapted from the Minnesota Leisure Time Physical Activity Questionnaire for individuals of advanced age (VREM questionnaire) and a new empty 14-day dietary record was given. In addition, the volunteers received the first foods with quinoa to initiate QD the next day. Products were delivered weekly, for conservation reasons but also to ensure that they followed an adequate consumption, they had to go through consultation to pick up the product and gave the researchers the empty packs where quinoa products had been.

On the next visit the day 42 (V4) the Freestyle Libre® sensor was collected and the filled dietary record was collected. Finally, after 28 days of quinoa diet they were summoned for the last visit the day 56 (V5) where all the determinations were repeated identically as V3.

With the premise that the products created replaced not only grains, legumes or tubers, but also farinaceous commonly consumed by the participants and that only the cereal fraction was modified, similar products based on quinoa flour were created. The creation of these products was necessary, after conducting a market search where it was observed that there was not enough food to replace those consumed since these had percentages of quinoa flour not exceeding 20-30%.

Thus, apart from delivering quinoa, quinoa flakes and quinoa flour to the participants, they were given products created with ≥70% quinoa flour and were biscuits, crackers, brioche, sponge cake, baguette bread, sliced bread and pasta. Moreover, a quinoa-based recipe was delivered with eight commonly consumed recipes that replaced the tuber, legume or grain of the recipe. Each subject received the equivalent of what they consumed according to their RD dietary records. Thus, only if the volunteer had indicated that he consumed sponge cake was the quinoa-based product delivered to him.

Descriptive data are presented as the mean and standard deviation (SD) or median and interquartile range (IQR) for continuous variables, and the frequencies and percentages (%) for categorical variables. Anthropometric measurements, blood test variables and dietary intake were compared at different times using the non-parametric Wilcoxon signed rank test because normality and equality of variance could not be assumed due to small sample size (n=9). In order to compare variables related to dietary patterns, mean value for dietary intake, including all meals, was considered for each participant.

The glucose level monitoring sensor takes measurements at discrete time points for each patient. Therefore, firstly the glucose curves have been linearly interpolated in order to have observations for each patient at equal time points. A first sight to the glucose curves over the day shown that they were more homogeneous around breakfast than around other later meals intakes. Therefore, the glucose concentration values corresponding to the breakfast were considered as a function of time in minutes over the interval t= [-30,120], that begins half an hour before the start of breakfast and ends two hours later. Before constructing a functional model, the functional data were time aligned in order to reduce the differences between different patients and/or different days (for instance, some patients could mark the starting time of breakfast systematically before than others, or spend systematically more time in breakfast than the average). The time alignment has been done by warping functions, using the function WFDA in the R package fdapace.

Once the glucose level curves have been synchronized, a functional regression analysis was conducted to model the effect of diet type, patient and nutrient intake on monitored glucose levels. Three different explanatory variables have been considered: diet type with two categories (regular and Quinoa diets), patient indicator (categorical variable with nine levels) and the contents in different nutrients. The breakfast glucose curves are handled as the functional response variable. To study the relationship between these variables function on scalar regression (fosr) models were used.

Firstly, the univariate effect of the diet type on glucose curves have been analyzed and then more complex fosr models with two factors (diet and patient factors) and scalar variables (nutrients) have been constructed. The most complex model including all effects of the independent variables is defined by a specific-created equation. The functional regression models have been fitted by penalized flexible functional regression, as implemented in the function pffr of the R package refund.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 9
• Est. completion date: September 2016
• Est. primary completion date: September 2016
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 65 Years and older

Eligibility

Inclusion Criteria:

• Glucose levels between 100 and 125 mg/dL and without a previous diagnosis of diabetes

Exclusion Criteria:

• Do not consume a diet with daily presence of grains or cereals derivatives, tubers or/and legumes, or they presented any other health problem that the research staff considered contraindicated:

Treatment with oral antidiabetic drugs Chronic treatment with oral steroids and / or AINES Treatment with oral antidiabetic agents and / or insulin Treatment with immunosuppressive drugs Diagnosis of active neoplasm Diagnosis of HIV or AIDS Abnormal liver profile (> 6 times normal values) Diagnosis of Acute Psychiatric Sdr Presence of serious acute concomitant disease, which it requires more than 7 days of recovery.

Major cardiovascular event (stroke, myocardial infarction) in the month prior to randomization.

Any other condition that the investigator considers to be inoperative so that the subject conducts the study.

Related Conditions & MeSH terms

• Diabetes Mellitus
• Diabetes Mellitus, Type 2
• Type 2 Diabetes

Intervention

Dietary Supplement:
• Quinoa and quinoa-based food
Products created replaced grains, legumes, tubers, also farinaceous commonly consumed by the participants and only the cereal fraction was modified, similar products based on quinoa flour were created. Thus, apart from delivering quinoa, quinoa flakes and quinoa flour to the participants, they were given products created with =70% quinoa flour and were biscuits, crackers, brioche, sponge cake, baguette bread, sliced bread and pasta. Moreover, a quinoa-based recipe was delivered with eight commonly consumed recipes that replaced the tuber, legume or grain of the recipe. Each subject received the equivalent of what they consumed according to their regular diet dietary records.

Locations

Country	Name	City	State
Spain	Diana A. Díaz Rizzolo	Barcelona

Sponsors (1)

Lead Sponsor	Collaborator
Institut d'Investigacions Biomèdiques August Pi i Sunyer

Country where clinical trial is conducted

Spain, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Hs-CRP (high-sensitivity C-reactive protein) in mg/L	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Other	HDL (high-density lipoprotein) in mg/dL	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Other	LDL (low-density lipoprotein) in mg/dL	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Other	Total cholesterol in mg/dL	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Other	Triglycerides in mg/dL	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Other	Serum albumin in g/dL	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Primary	Blood glucose fluctuations	Glucose fluctuations were measured by FreeStyle Libre® Flash Glucose Monitoring System (Abbott Laboratories) which measures interstitial fluid glucose concentrations. The sensor was applied by researchers on to the back of the upper arm of subjects using the applicator and participants were trained to obtain electronically all the glucose records concentrations every 15 minutes so they had to scan at least once every eight hours. The glucose level monitoring sensor takes measurements at discrete time points for each patient Therefore, firstly the glucose curves have been linearly interpolated and has been considered as a function of time in minutes over interval. Then, a functional model analyses were constructed as described in "study protocol and statistical analyses" document attached.	Comparing data obtained during 2 hours per day along 14 days both during regular diet and quinoa diet
Secondary	Weight in kilograms	Subjects were weighed without clothing and shoes.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Secondary	Height in meters	Subjects were measured without clothing and shoes.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Secondary	Body mass index (BMI)	BMI was calculated as weight (kg)/height (m)²	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Secondary	Circumferences in cm	waist circumference was measured at the midpoint between the last rib and the iliac crest and hip circumference at the widest point of the gluteus	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Secondary	Blood pressure	Blood pressure was taken after individuals sat quietly for 5 min in a clinical examination room. The mean of three different measurements, obtained every 3 min using an OMRON M6 AC sphygmomanometer, was recorded.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Secondary	Insulin levels (mU/L)	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Secondary	Glucose homeostasis (mg/dl)	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Secondary	Glycated hemoglobin HbA1c (%)	Fasting blood samples were collected by a nurse and they were analyzed by the Biomedical Diagnosis Centre (CDB) in Hospital Clinic de Barcelona.	Data obtained after 28 days quinoa diet compared to data obtained after 28 days regular diet
Secondary	Nutrient intake recorded	Nutritional patterns were measured using a 14-days dietary record revised corrected by a nutritionist and analyzed by the DIAL nutritional calculation program.	Data obtained during 28 days quinoa diet compared to data obtained during 28 days regular diet