ObesityMACRONCT00609271
Study of Macronutrients and Heart Disease Risk
A study testing low carbohydrate diet and low fat diet in people with Obesity and Body Composition, run by Tulane University Health Sciences Center at 1 site in United States.
Trial summary
The objective of this trial is to examine the long-term effects of a diet low in carbohydrates, as compared to one low in fat, on cardiovascular disease risk factors, including blood pressure (BP), body weight and composition, serum lipids, plasma glucose, insulin, adipocytokines (adiponectin, leptin, resistin), and… Read more about this study
- Who is it for?
- Ages 22 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Obesity, Body Composition, Blood Pressure
- What is being tested?
- low carbohydrate diet and low fat diet
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 148 participants
- Where
- 1 siteUnited States
- Study dates
- Jan 2008to Jan 2012
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 22 to 75 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Men or women aged 22 - 75 years, any race/ethnicity
- BMI of 30 - 45 k/m2
- Willing and able to provide informed consent
Who cannot join
- History of self-reported clinical CVD (angina/myocardial infarction, coronary revascularization, heart failure, stroke/transient ischemic attack, peripheral arterial disease)
- Medical condition in which a low-carbohydrate diet may not be advised (diabetes, renal disease, cancer requiring treatment during the past year, osteoporosis, untreated thyroid disease, gout)
- Current use of more than 2 antihypertensive or more than 2 cholesterol-lowering medications
- For women, current pregnancy or breastfeeding or plans to become pregnant during the study period
- Consumption of more than 21 alcoholic beverages per week
- Currently on a diet or using prescription weight loss medications, underwent weight loss surgery, and/or experienced weight loss >15 pounds within 6 months of study entry
Show all 10Show fewer
- Plans to move out of the study area (>1 hour from study site) or difficulty to come to the study site
- Participation of another household member in the study; employees or persons living with employees of the study
- Participation in other lifestyle intervention trials currently
- At the discretion of the study coordinator
Trial locations and contacts
1 site in 1 country.
United States1 site
Tulane University, Office of Health Research
New Orleans, Louisiana, 70112
About this study
Official title: Macronutrient Composition of Diet and Risk Factors for Cardiovascular Disease
The objective of this trial is to examine the long-term effects of a diet low in carbohydrates, as compared to one low in fat, on cardiovascular disease risk factors, including blood pressure (BP), body weight and composition, serum lipids, plasma glucose, insulin, adipocytokines (adiponectin, leptin, resistin), and C-reactive protein (CRP) among obese adults.
The investigators will test the following hypotheses:
Hypothesis 1: Compared to a low fat diet, a diet low in carbohydrates will reduce systolic and diastolic BP over 12 months; Hypothesis 2: Compared to a low fat diet, a diet low in carbohydrates will reduce body weight, total percent body fat, and waist circumference over 12 months; Hypothesis 3: Compared to a low fat diet, a diet low in carbohydrates will reduce serum levels of LDL-cholesterol and triglycerides and increase serum levels of HDL-cholesterol over 12 months; Hypothesis 4: Compared to a low fat diet, a diet low in carbohydrates will reduce plasma levels of glucose and insulin levels over 12 months; and Hypothesis 5: Compared to a low fat diet, a diet low in carbohydrates will reduce plasma levels of leptin, resistin, and CRP and increase plasma levels of adiponectin over 12 months.
Read the detailed description
Cardiovascular diseases (CVD) remain the leading cause of death globally as well as here in the United States. Manipulations of the macronutrient (protein, carbohydrate and fat) contents of diet have been used extensively for weight loss and weight control in the past several decades. Low carbohydrate diets, in particular, have gained popularity for weight loss. However, few studies have examined the effects of a diet low in carbohydrates on traditional and novel cardiovascular risk factors in the long term, particularly in contrast to the current dietary recommendations for decreased fat intake to reduce risk of CVD. In this proposal, we plan to conduct a 12-month, parallel-arm, randomized controlled trial of a diet low in carbohydrates versus the currently recommended low fat diet to reduce CVD risk factors among obese adults. The objective of this trial is to examine the long-term effects of a diet low in carbohydrates, as compared to one low in fat, on CVD risk factors, including blood pressure (BP), body weight and composition, serum lipids, plasma glucose, insulin, adipocytokines (adiponectin, leptin, resistin), and C-reactive protein (CRP) among obese adults. In order to accomplish these objectives we will randomize 130 eligible participants (n=65 in each group) to consume either a diet low in carbohydrates (≤40 g/d) or a diet low in fat (<7% saturated fat, <30% total fat). Neither of the diets will be energy-restricted. Participants will meet with a dietitian for one-on-one counseling sessions weekly for the first 4 weeks, then bi-monthly in small group sessions for the next 5 months, and monthly in larger group sessions for the final 6 months of the intervention. Data on both traditional and novel CVD risk factors will be collected at baseline, 3, 6, and 12 months. We hypothesize that a diet low in carbohydrates as compared to a diet low in fat will lower systolic and diastolic BP, body weight, total percent body fat, waist circumference, serum levels of triglycerides, and plasma levels of insulin, glucose, leptin, resistin, and CRP, and increase serum levels of HDL-cholesterol and adiponectin. Because CVD is the most common cause of death here in the U.S. and world-wide, this study has important public health implications. It will provide new information on the potential long-term effects of diets low in carbohydrates on both the traditional risk factors for CVD as well as novel risk factors and inflammatory factors. The results from this study will help to determine if a diet low in carbohydrates as compared to the currently recommended low fat diet can decrease the risk of CVD among obese adults.
- Conditions
- Obesity, Body Composition, Blood Pressure, Cardiovascular Diseases
- Being tested
- low carbohydrate diet, low fat diet
- Medical subject headings
- Obesity, Cardiovascular Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
low carbohydrate dietBehavioural
<40 grams carbohydrate/day
low fat dietBehavioural
<30% fat, <7% saturated fat
| Study group | Role | What they receive |
|---|---|---|
| 1 | Experimental | low carbohydrate diet Receives: Behavioral: low carbohydrate diet |
| 2 | Active comparator | low fat diet Receives: Behavioral: low fat diet |
What is being measured
The primary outcome is the main question the study is designed to answer.
Predicted Mean Difference in Body Weight From Baseline, by Assigned Dietary Group
Predicted mean difference from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in Lean Mass From Baseline, by Assigned Dietary Group
Mean Difference in Lean Mass predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in Fat Mass From Baseline, by Assigned Dietary Group
Mean Difference in Fat Mass predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences of Waist Circumference From Baseline, by Assigned Dietary Group
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in Total Cholesterol Level From Baseline by Assigned Dietary Group
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in LDL Cholesterol Level From Baseline, by Assigned Dietary Group
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in HDL Cholesterol From Baseline, by Assigned Dietary Group
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in Total-HDL Cholesterol Ratio From Baseline, by Assigned Dietary Group
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in Triglycerides From Baseline, by Assigned Dietary Group
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in Systolic Blood Pressure From Baseline, by Assigned Dietary Group
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Difference in Diastolic Blood Pressure, by Assigned Dietary Group
Mean Difference in Diastolic Blood Pressure predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values
Measured: 12 Months
Predicted Mean Difference in Plasma Glucose Level, by Assigned Dietary Group
Mean Difference in Plasma Glucose Level predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in Serum Insulin Level From Baseline, by Assigned Dietary Group
Mean Difference in Serum Insulin Level predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 months
Predicted Mean Differences in C-reactive Protein Level From Baseline, by Assigned Dietary Group
Mean Difference in C-reactive Protein Level predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values
Measured: 12 Months
Predicted Mean Differences in Serum Creatinine Level From Baseline, by Assigned Dietary Group
Mean Difference in Serum Creatinine Level predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 Months
Predicted Mean Differences of 10-y Framingham Risk Score From Baseline, by Assigned Dietary Group
Mean Difference in 10-y Framingham Risk Score predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Measured: 12 Months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Feb 2008 (estimated)
- Study startJan 2008
- Primary completionJan 2011
- Study completionJan 2012
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for ObesityStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 148 participants (actual)
Sponsor and investigators
- Lead sponsor
- Tulane University Health Sciences Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Lydia A. Bazzano, Tulane University Health Sciences Center
- Investigators
- Lydia A Bazzano, MD, PhD, Principal investigator, Tulane University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT00609271
- Sponsor's protocol ID
- 07-00111
- Acronym
- MACRO
- Status last verified
- Apr 2018
- First submitted
- 24 Jan 2008
- Last updated
- 19 Nov 2018
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Hu T, Yao L, Reynolds K, Niu T, Li S, Whelton P, He J, Bazzano L. The effects of a low-carbohydrate diet on appetite: A randomized controlled trial. Nutr Metab Cardiovasc Dis. 2016 Jun;26(6):476-88. doi: 10.1016/j.numecd.2015.11.011. Epub 2015 Dec 12.
PubMed 26803589Bazzano LA, Hu T, Reynolds K, Yao L, Bunol C, Liu Y, Chen CS, Klag MJ, Whelton PK, He J. Effects of low-carbohydrate and low-fat diets: a randomized trial. Ann Intern Med. 2014 Sep 2;161(5):309-18. doi: 10.7326/M14-0180.
PubMed 25178568
Study at a glance
From the registry record, last updated by the sponsor on 19 Nov 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Macronutrient Composition of Diet and Risk Factors for Cardiovascular Disease
- ClinicalTrials.gov ID
- NCT00609271
- Acronym / sponsor ID
- MACRO / 07-00111
- Conditions
- Obesity, Body Composition, Blood Pressure, Cardiovascular Diseases
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 148 participants (actual)
- Lead sponsor
- Tulane University Health Sciences CenterUniversity, hospital or other
- Study start
- Jan 2008
- Primary completion
- Jan 2011 (actual)
- Study completion
- Jan 2012 (actual)
- First posted
- 7 Feb 2008 (estimated)
- Results
- Posted 19 Nov 2018
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The objective of this trial is to examine the long-term effects of a diet low in carbohydrates, as compared to one low in fat, on cardiovascular disease risk factors, including blood pressure (BP), body weight and composition, serum lipids, plasma glucose, insulin, adipocytokines (adiponectin, leptin, resistin), and C-reactive protein (CRP) among obese adults.
The investigators will test the following hypotheses:
Hypothesis 1: Compared to a low fat diet, a diet low in carbohydrates will reduce systolic and diastolic BP over 12 months; Hypothesis 2: Compared to a low fat diet, a diet low in carbohydrates will reduce body weight, total percent body fat, and waist circumference over 12 months; Hypothesis 3: Compared to a low fat diet, a diet low in carbohydrates will reduce serum levels of LDL-cholesterol and triglycerides and increase serum levels of HDL-cholesterol over 12 months; Hypothesis 4: Compared to a low fat diet, a diet low in carbohydrates will reduce plasma levels of glucose and insulin levels over 12 months; and Hypothesis 5: Compared to a low fat diet, a diet low in carbohydrates will reduce plasma levels of leptin, resistin, and CRP and increase plasma levels of adiponectin over 12 months.
Detailed description
Cardiovascular diseases (CVD) remain the leading cause of death globally as well as here in the United States. Manipulations of the macronutrient (protein, carbohydrate and fat) contents of diet have been used extensively for weight loss and weight control in the past several decades. Low carbohydrate diets, in particular, have gained popularity for weight loss. However, few studies have examined the effects of a diet low in carbohydrates on traditional and novel cardiovascular risk factors in the long term, particularly in contrast to the current dietary recommendations for decreased fat intake to reduce risk of CVD. In this proposal, we plan to conduct a 12-month, parallel-arm, randomized controlled trial of a diet low in carbohydrates versus the currently recommended low fat diet to reduce CVD risk factors among obese adults. The objective of this trial is to examine the long-term effects of a diet low in carbohydrates, as compared to one low in fat, on CVD risk factors, including blood pressure (BP), body weight and composition, serum lipids, plasma glucose, insulin, adipocytokines (adiponectin, leptin, resistin), and C-reactive protein (CRP) among obese adults. In order to accomplish these objectives we will randomize 130 eligible participants (n=65 in each group) to consume either a diet low in carbohydrates (≤40 g/d) or a diet low in fat (<7% saturated fat, <30% total fat). Neither of the diets will be energy-restricted. Participants will meet with a dietitian for one-on-one counseling sessions weekly for the first 4 weeks, then bi-monthly in small group sessions for the next 5 months, and monthly in larger group sessions for the final 6 months of the intervention. Data on both traditional and novel CVD risk factors will be collected at baseline, 3, 6, and 12 months. We hypothesize that a diet low in carbohydrates as compared to a diet low in fat will lower systolic and diastolic BP, body weight, total percent body fat, waist circumference, serum levels of triglycerides, and plasma levels of insulin, glucose, leptin, resistin, and CRP, and increase serum levels of HDL-cholesterol and adiponectin. Because CVD is the most common cause of death here in the U.S. and world-wide, this study has important public health implications. It will provide new information on the potential long-term effects of diets low in carbohydrates on both the traditional risk factors for CVD as well as novel risk factors and inflammatory factors. The results from this study will help to determine if a diet low in carbohydrates as compared to the currently recommended low fat diet can decrease the risk of CVD among obese adults.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| 1 | Experimental | Behavioral: low carbohydrate dietlow carbohydrate diet |
| 2 | Active comparator | Behavioral: low fat dietlow fat diet |
Who may qualify
- Ages
- 22 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Men or women aged 22 - 75 years, any race/ethnicity
- BMI of 30 - 45 k/m2
- Willing and able to provide informed consent
Key exclusion criteria (10 listed)
- History of self-reported clinical CVD (angina/myocardial infarction, coronary revascularization, heart failure, stroke/transient ischemic attack, peripheral arterial disease)
- Medical condition in which a low-carbohydrate diet may not be advised (diabetes, renal disease, cancer requiring treatment during the past year, osteoporosis, untreated thyroid disease, gout)
- Current use of more than 2 antihypertensive or more than 2 cholesterol-lowering medications
- For women, current pregnancy or breastfeeding or plans to become pregnant during the study period
- Consumption of more than 21 alcoholic beverages per week
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| low carbohydrate diet<40 grams carbohydrate/day | Behavioural | 1 |
| low fat diet<30% fat, <7% saturated fat | Behavioural | 2 |
Primary outcome
Predicted Mean Difference in Body Weight From Baseline, by Assigned Dietary Group
Time frame: 12 months
Predicted mean difference from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in Lean Mass From Baseline, by Assigned Dietary Group
Time frame: 12 months
Mean Difference in Lean Mass predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in Fat Mass From Baseline, by Assigned Dietary Group
Time frame: 12 months
Mean Difference in Fat Mass predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences of Waist Circumference From Baseline, by Assigned Dietary Group
Time frame: 12 months
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in Total Cholesterol Level From Baseline by Assigned Dietary Group
Time frame: 12 months
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in LDL Cholesterol Level From Baseline, by Assigned Dietary Group
Time frame: 12 months
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in HDL Cholesterol From Baseline, by Assigned Dietary Group
Time frame: 12 months
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in Total-HDL Cholesterol Ratio From Baseline, by Assigned Dietary Group
Time frame: 12 months
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in Triglycerides From Baseline, by Assigned Dietary Group
Time frame: 12 months
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in Systolic Blood Pressure From Baseline, by Assigned Dietary Group
Time frame: 12 months
Predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Difference in Diastolic Blood Pressure, by Assigned Dietary Group
Time frame: 12 Months
Mean Difference in Diastolic Blood Pressure predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values
Predicted Mean Difference in Plasma Glucose Level, by Assigned Dietary Group
Time frame: 12 months
Mean Difference in Plasma Glucose Level predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in Serum Insulin Level From Baseline, by Assigned Dietary Group
Time frame: 12 months
Mean Difference in Serum Insulin Level predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences in C-reactive Protein Level From Baseline, by Assigned Dietary Group
Time frame: 12 Months
Mean Difference in C-reactive Protein Level predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values
Predicted Mean Differences in Serum Creatinine Level From Baseline, by Assigned Dietary Group
Time frame: 12 Months
Mean Difference in Serum Creatinine Level predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Predicted Mean Differences of 10-y Framingham Risk Score From Baseline, by Assigned Dietary Group
Time frame: 12 Months
Mean Difference in 10-y Framingham Risk Score predicted from random-effects models that included diet, time, and diet-by-time interaction term. Markov-chain Monte Carlo techniques were used to impute missing values.
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Nov 2018.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Derived from this study: PubMed 26803589Hu T, Yao L, Reynolds K, Niu T, Li S, Whelton P, He J, Bazzano L. The effects of a low-carbohydrate diet on appetite: A randomized controlled trial. Nutr Metab Cardiovasc Dis. 2016 Jun;26(6):476-88. doi: 10.1016/j.numecd.2015.11.011. Epub 2015 Dec 12.
- Derived from this study: PubMed 25178568Bazzano LA, Hu T, Reynolds K, Yao L, Bunol C, Liu Y, Chen CS, Klag MJ, Whelton PK, He J. Effects of low-carbohydrate and low-fat diets: a randomized trial. Ann Intern Med. 2014 Sep 2;161(5):309-18. doi: 10.7326/M14-0180.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Lydia A Bazzano, MD, PhD principal investigator
Tulane University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing low carbohydrate diet and low fat diet in people with Obesity and Body Composition, run by Tulane University Health Sciences Center at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 19 Nov 2018. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 19 Nov 2018). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Predicted Mean Difference in Body Weight From Baseline, by Assigned Dietary Group (time frame: 12 months). The study lists 16 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT00609271, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Nov 2018.