<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04465721</url>
  </required_header>
  <id_info>
    <org_study_id>AAAS7791</org_study_id>
    <secondary_id>R01AG065569</secondary_id>
    <nct_id>NCT04465721</nct_id>
  </id_info>
  <brief_title>TREAT to Improve Cardiometabolic Health</brief_title>
  <acronym>NY-TREAT</acronym>
  <official_title>New York TREAT (Time Restricted EATing) to Improve Cardiometabolic Health Study</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Columbia University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>New York University</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Salk Institute for Biological Studies</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>National Institute on Aging (NIA)</agency>
      <agency_class>NIH</agency_class>
    </collaborator>
  </sponsors>
  <source>Columbia University</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
    <is_us_export>No</is_us_export>
  </oversight_info>
  <brief_summary>
    <textblock>
      Over half of American adults have overweight or obesity and are at high risk of developing&#xD;
      type 2 diabetes and cardiovascular diseases. Although caloric restriction has many health&#xD;
      benefits, it is difficult to sustain overtime for most people. Time restricted eating (TRE),&#xD;
      a novel type of intermittent fasting, facilitates adherence to the intervention and results&#xD;
      in weight loss and improvement of metabolism. The investigators propose to to examine the&#xD;
      efficacy of self monitoring and TRE (10-h/d) vs. self-monitoring and habitual prolonged&#xD;
      eating duration ( HABIT) (13 hours/d) on weight loss and body composition, metabolic function&#xD;
      and circadian biology, in metabolically unhealthy adults aged 50 to 75 y old, with overweight&#xD;
      or obesity. The investigators hypothesize that TRE, compared to habitual long duration of&#xD;
      eating, will decrease cardiovascular risk burden.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      American adults have a high prevalence of overweight, obesity and prediabetes. Small weight&#xD;
      loss delays the progression to type 2 diabetes and decrease cardiovascular risk, yet&#xD;
      adherence to long term calorie restriction is difficult to sustain. There is an urgency to&#xD;
      find effective, easy-to implement and sustain, and affordable life style interventions.&#xD;
      Restricting the food intake interval, or time restricted eating (TRE) has been shown in&#xD;
      small-scale pilot studies to result in weight loss and improve metabolism, while being less&#xD;
      challenging than calorie count. We propose to rigorously assess the efficacy and&#xD;
      sustainability of self-monitoring with and without TRE, administered via a smartphone&#xD;
      application, on weight loss and decreased cardiovascular risk. To achieve this goal,&#xD;
      metabolically unhealthy mid-life adults with overweight or obesity who habitually eat for&#xD;
      more than 13h/day, will be randomized to a self monitoring and restricted eating window to&#xD;
      10h/d (TRE) or to a self-monitoring and habitual eating window (13h, HABIT), and followed up&#xD;
      to 12 months. Ambulatory measures of food intake, sleep, physical activity and glucose, and&#xD;
      outpatient well controlled studies will be done to determine the effect of TRE versus&#xD;
      habitual eating duration (HABIT), as well as the mediators of these effects. Hypotheses: 1)&#xD;
      TRE vs. HABIT will result in decreased fat mass, measured by quantitative magnetic resonance,&#xD;
      and effect mediated via decreased daily total energy intake, measured by double labeled&#xD;
      water; 2) TRE vs. HABIT will result in lower insulin resistance, lower glycemia and shift in&#xD;
      fuel utilization preferentially to lipid mobilization; 3) Adherence to the TRE intervention&#xD;
      will be associated with greater weight loss at 3 months and weight maintenance at 12 months.&#xD;
      Results from this study will provide important insights into understanding the physiological&#xD;
      and molecular interactions between restricting daily eating interval and metabolic function,&#xD;
      and could provide evidence for using TRE interventions to improve metabolic health and&#xD;
      decrease cardiovascular risk in the large number of mid-life and older Americans in great&#xD;
      need of life style intervention.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Recruiting</overall_status>
  <start_date type="Actual">June 14, 2021</start_date>
  <completion_date type="Anticipated">June 30, 2025</completion_date>
  <primary_completion_date type="Anticipated">January 31, 2025</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <intervention_model_description>Metabolically unhealthy mid-life adults with overweight or obesity who habitually eat for more than 13h/day, will be randomized to a restricted eating window to 10h/d (TRE group) or to their habitual eating window (≥ 13h, HABIT group), and followed up to 12 months.</intervention_model_description>
    <primary_purpose>Other</primary_purpose>
    <masking>Single (Outcomes Assessor)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Fat mass</measure>
    <time_frame>0, 3, and 12 months</time_frame>
    <description>Changes in fat mass (kg) will be measured by quantitative magnetic resonance (QMR) on day 0 and day 13 of ambulatory assessments at the 0 and 3 month study period, and again at 12 months.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Energy intake</measure>
    <time_frame>0, 3 months</time_frame>
    <description>Energy intake (EI) will be calculated from total daily energy expenditure (EE) measured by doubly labeled water (DLW), and changes in body energy stores (ΔES), measured by QMR over the 2-wk ambulatory assessments of the 0 and 3 month study periods: EI (kcal/d) = EEDLW + ΔES.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Body weight</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>Changes in body weight (kg) will be measured to the nearest 0.01 kg with a digital scale at 0 and 3 months, and again at 12 months.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Insulin resistance (HOMA-IR)</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>Fasting serum insulin and plasma glucose concentrations will be used to calculate changes in insulin resistance (HOMA-IR): [fasting insulin (mU/mL) x fasting glucose (mmol/L)]/22.5 at 0 and 3 months, and again at 12 months.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Glucose levels</measure>
    <time_frame>0, 3,12 months</time_frame>
    <description>Glucose changes will be assessed by the total and incremental 24-hour glucose AUC, from ambulatory CGM at 0 and 3 months.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Glucose variability</measure>
    <time_frame>0, 3,12 months</time_frame>
    <description>CGM data will be used to calculate standard measures of glucose variability (GV), including mean amplitude of glycemic excursion (MAGE) changes at 0 and 3 months.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Sleep assessment</measure>
    <time_frame>0, 3,12 months</time_frame>
    <description>Sleep duration will be assessed by changes in bedtime, waketime, and total sleep time, recorded by actigraphy during the 2-wk ambulatory assessments at 0, 3, and 12 months.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Adherence</measure>
    <time_frame>0, 3,12 months</time_frame>
    <description>Adherence will be assessed by % of days with at least 2 or more entries logged at least 5h apart/day</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Diet composition by ASA24</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>% of carbs, fat and protein in diet by ASA24 on 3 non-consecutive days (2 weekdays and one weekend day) during each ambulatory assessment and during the 3 months intervention.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Matsuda Index (Insulin resistance)</measure>
    <time_frame>0, 3 months</time_frame>
    <description>Fasting and OGTT glucose and insulin levels are used to calculate the Matsuda index:&#xD;
10,000/([fasting insulin (mU/mL)x fasting glucose (mmol/L)]x [mean OGTT insulin (mU/mL) x mean OGTT glucose (mmol/L)])</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Insulinogenic Index</measure>
    <time_frame>0, 3 months</time_frame>
    <description>Calculated by the AUC insulin/AUC glucose during OGTT.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Free fatty acids (FFA)</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>Measured from a fasting blood sample</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Ketones</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>The concentration of ketones (beta-OH-butyrate) will be measured from a fasting blood sample.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Physical activity</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>Assessed by step count during 14 day ambulatory assessment periods at 0,3, and 12 months.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Inflammation markers</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>Measured from a fasting blood sample.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Oxidative stress</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>Measured from a fasting blood sample</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Lipid profile</measure>
    <time_frame>0, 3, 12 months</time_frame>
    <description>Measured from a fasting blood sample</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Anticipated">52</enrollment>
  <condition>Overweight and Obesity</condition>
  <condition>Prediabetes</condition>
  <arm_group>
    <arm_group_label>HABIT Group</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>Participants randomized to the HABIT group will maintain their habitual eating schedule (≥13-h).</description>
  </arm_group>
  <arm_group>
    <arm_group_label>TRE Group</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Participants randomized to TRE will reduce their eating window to a self-selected eating window (≤10-h).</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>TRE</intervention_name>
    <description>The TRE intervention will be administered and monitored via the study app. It combines self-monitoring behavior, daily eating window reminders, positive reinforcement based on number of log entries or based on meeting eating widow target, and basic lifestyle text messages. It also allows research staff to monitor in real-time, via the backend cloud, adherence to self-monitoring, and to reducing the eating window.</description>
    <arm_group_label>TRE Group</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>HABIT</intervention_name>
    <description>The HABIT intervention will be administered and monitored via the study app. It combines self-monitoring behavior, positive reinforcement based on number of log entries, and basic lifestyle text messages. It also allows research staff to monitor in real-time, via the backend cloud, adherence to self-monitoring.</description>
    <arm_group_label>HABIT Group</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  age: 50-75y old&#xD;
&#xD;
          -  BMI ≥25 and ≤45 kg/m2&#xD;
&#xD;
          -  a diagnosis of prediabetes AND/OR fasting glucose 100 mg/dL and/or HbA1c 5.7% OR Type&#xD;
             2 Diabetes diet-controlled and/or treated with metformin AND meeting 2 or more of the&#xD;
             following metabolic syndrome criteria:&#xD;
&#xD;
               -  diagnosis of hypertension on stable medication regimen&#xD;
&#xD;
               -  blood pressure &gt;120/&gt;80 mmHg&#xD;
&#xD;
               -  A diagnosis of dyslipidemia on stable regimen&#xD;
&#xD;
               -  triglycerides 150 mg/dL&#xD;
&#xD;
               -  HDL cholesterol men &lt;40 mg/dL and women &lt;50 mg/dL&#xD;
&#xD;
               -  waist circumference men: &gt;102 cm (&gt;40 in); women &gt;88 cm (&gt;35 in)&#xD;
&#xD;
          -  in possession of a smart phone (iPhone or Android)&#xD;
&#xD;
          -  70% of days with logging adherence (2 or more log entries/day separated by at least&#xD;
             5h)&#xD;
&#xD;
          -  Sleep duration 6-h, with habitual self-reported wake up time &gt;5AM and before 11 AM and&#xD;
             average self reported bed time &lt;2AM&#xD;
&#xD;
          -  habitually eat breakfast&#xD;
&#xD;
          -  with weight stability within 5% of screening for the last 3 months&#xD;
&#xD;
          -  English speaking (the App has not yet been translated)&#xD;
&#xD;
          -  must live in the New York City metro area&#xD;
&#xD;
        Exclusion criteria:&#xD;
&#xD;
          -  sleep disorder, e.g. known obstructive sleep apnea (OSA) on CPAP, severe OSA with&#xD;
             apnea-hypopnea index &gt;30 events/h, significant daytime symptoms of OSA, periodic limb&#xD;
             movements of sleep, narcolepsy, current shift work or in last 6-mo, travel more than 1&#xD;
             time zone during intervention; severe insomnia with score 15 on Insomnia Severity&#xD;
             Index&#xD;
&#xD;
          -  significant organ system dysfunction/disease: severe pulmonary, kidney or&#xD;
             cardiovascular disease; evidence of active illness (e.g., fever)&#xD;
&#xD;
          -  history of seizure disorder&#xD;
&#xD;
          -  previous bariatric surgery or on weight loss medication&#xD;
&#xD;
          -  history of or current significant food intake or psychiatric disorder&#xD;
&#xD;
          -  use of dietary supplements and/or medications known to affect sleep, circadian rhythms&#xD;
             or metabolic function&#xD;
&#xD;
          -  smoking tobacco or using illegal or recreational drugs&#xD;
&#xD;
          -  consume excessive alcohol (women: &gt;14 drinks/wk; men: &gt;21 drinks/wk)&#xD;
&#xD;
          -  anemia (hemoglobin &lt;10 g/dl and hematocrit &lt;30%)&#xD;
&#xD;
          -  have conditions that render individual unable to complete all testing procedures&#xD;
             [e.g., unable to stay overnight or frequent travel across 1 time zones]&#xD;
&#xD;
          -  extreme early and late chronotypes (&gt; 2AM bed time and wake up time before 5AM and &gt;&#xD;
             11AM)&#xD;
&#xD;
          -  severe food allergies&#xD;
&#xD;
          -  unwilling/unable to provide informed consent&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>50 Years</minimum_age>
    <maximum_age>75 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Blandine Laferrère, M.D., Ph.D.</last_name>
    <role>Principal Investigator</role>
    <affiliation>Columbia University</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Delaney Shaw, MS</last_name>
    <phone>212-851-5576</phone>
    <email>ds3936@cumc.columbia.edu</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Blandine Laferrere, MD, PhD</last_name>
    <phone>212-851-5562</phone>
    <email>bbl14@columbia.edu</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Columbia University</name>
      <address>
        <city>New York</city>
        <state>New York</state>
        <zip>10032</zip>
        <country>United States</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Blandine Laferrere</last_name>
      <phone>212-851-5562</phone>
      <email>bbl14@columbia.edu</email>
    </contact>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>August 2023</verification_date>
  <study_first_submitted>July 1, 2020</study_first_submitted>
  <study_first_submitted_qc>July 6, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 10, 2020</study_first_posted>
  <last_update_submitted>August 10, 2023</last_update_submitted>
  <last_update_submitted_qc>August 10, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">August 14, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Columbia University</investigator_affiliation>
    <investigator_full_name>Blandine Laferrere</investigator_full_name>
    <investigator_title>Professor of Medicine</investigator_title>
  </responsible_party>
  <keyword>Overweight</keyword>
  <keyword>Obesity</keyword>
  <keyword>Metabolic syndrome</keyword>
  <keyword>Time restricted eating</keyword>
  <keyword>Diabetes</keyword>
  <keyword>Prediabetes</keyword>
  <keyword>Lifestyle intervention</keyword>
  <keyword>Smartphone app</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Overweight</mesh_term>
    <mesh_term>Prediabetic State</mesh_term>
    <mesh_term>Glucose Intolerance</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>Columbia University is committed to the open and timely dissemination of research outcomes. Investigators in this proposed project are aware of and agree to abide by the principles for sharing research resources, as described by NIH in &quot;Principles and Guidelines for Recipients of NIH Research Grants and Contracts on Obtaining and Disseminating Biomedical Research Programs.&quot; All data used in this proposal will de-identified, and accessed using a secure data area using a shared drive, protected by password only to be accessed by those directly involved in the clinical research. All transfer of data will use encrypted methods. Wherever applicable, fully de-identified data will be deposited to appropriate public repositories, following the Federal Health Insurance Privacy and Portability Act (HIPAA).</ipd_description>
    <ipd_time_frame>This will occur no longer than 6 months after publications of the data generated by this application, or, 18 months after completion of the funding period, should no data had been published.</ipd_time_frame>
    <ipd_access_criteria>The data generated in this grant will be presented at national or international conferences and published in a timely fashion. All final peer-reviewed manuscripts that arise from this proposal will be submitted upon acceptance for publication to the digital archive NIH National Library of Medicine PubMed Central (PMC) database, according to the NIH Policy on Enhancing Public Access to Archived Publications Resulting from NIH Funded Research. Any data released for publication will be for research purposes only and will not include identifiable data on any of the participants.</ipd_access_criteria>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04465721
org study id: AAAS7791
secondary id: R01AG065569
nct id: NCT04465721
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
is us export: No
Over half of American adults have overweight or obesity and are at high risk of developing
      type 2 diabetes and cardiovascular diseases. Although caloric restriction has many health
      benefits, it is difficult to sustain overtime for most people. Time restricted eating (TRE),
      a novel type of intermittent fasting, facilitates adherence to the intervention and results
      in weight loss and improvement of metabolism. The investigators propose to to examine the
      efficacy of self monitoring and TRE (10-h/d) vs. self-monitoring and habitual prolonged
      eating duration ( HABIT) (13 hours/d) on weight loss and body composition, metabolic function
      and circadian biology, in metabolically unhealthy adults aged 50 to 75 y old, with overweight
      or obesity. The investigators hypothesize that TRE, compared to habitual long duration of
      eating, will decrease cardiovascular risk burden.
American adults have a high prevalence of overweight, obesity and prediabetes. Small weight
      loss delays the progression to type 2 diabetes and decrease cardiovascular risk, yet
      adherence to long term calorie restriction is difficult to sustain. There is an urgency to
      find effective, easy-to implement and sustain, and affordable life style interventions.
      Restricting the food intake interval, or time restricted eating (TRE) has been shown in
      small-scale pilot studies to result in weight loss and improve metabolism, while being less
      challenging than calorie count. We propose to rigorously assess the efficacy and
      sustainability of self-monitoring with and without TRE, administered via a smartphone
      application, on weight loss and decreased cardiovascular risk. To achieve this goal,
      metabolically unhealthy mid-life adults with overweight or obesity who habitually eat for
      more than 13h/day, will be randomized to a self monitoring and restricted eating window to
      10h/d (TRE) or to a self-monitoring and habitual eating window (13h, HABIT), and followed up
      to 12 months. Ambulatory measures of food intake, sleep, physical activity and glucose, and
      outpatient well controlled studies will be done to determine the effect of TRE versus
      habitual eating duration (HABIT), as well as the mediators of these effects. Hypotheses: 1)
      TRE vs. HABIT will result in decreased fat mass, measured by quantitative magnetic resonance,
      and effect mediated via decreased daily total energy intake, measured by double labeled
      water; 2) TRE vs. HABIT will result in lower insulin resistance, lower glycemia and shift in
      fuel utilization preferentially to lipid mobilization; 3) Adherence to the TRE intervention
      will be associated with greater weight loss at 3 months and weight maintenance at 12 months.
      Results from this study will provide important insights into understanding the physiological
      and molecular interactions between restricting daily eating interval and metabolic function,
      and could provide evidence for using TRE interventions to improve metabolic health and
      decrease cardiovascular risk in the large number of mid-life and older Americans in great
      need of life style intervention.
allocation: Randomized
intervention model: Parallel Assignment
intervention model description: Metabolically unhealthy mid-life adults with overweight or obesity who habitually eat for more than 13h/day, will be randomized to a restricted eating window to 10h/d (TRE group) or to their habitual eating window (≥ 13h, HABIT group), and followed up to 12 months.
primary purpose: Other
masking: Single (Outcomes Assessor)
measure: Fat mass
time frame: 0, 3, and 12 months
description: Changes in fat mass (kg) will be measured by quantitative magnetic resonance (QMR) on day 0 and day 13 of ambulatory assessments at the 0 and 3 month study period, and again at 12 months.
measure: Energy intake
time frame: 0, 3 months
description: Energy intake (EI) will be calculated from total daily energy expenditure (EE) measured by doubly labeled water (DLW), and changes in body energy stores (ΔES), measured by QMR over the 2-wk ambulatory assessments of the 0 and 3 month study periods: EI (kcal/d) = EEDLW + ΔES.
measure: Body weight
time frame: 0, 3, 12 months
description: Changes in body weight (kg) will be measured to the nearest 0.01 kg with a digital scale at 0 and 3 months, and again at 12 months.
measure: Insulin resistance (HOMA-IR)
time frame: 0, 3, 12 months
description: Fasting serum insulin and plasma glucose concentrations will be used to calculate changes in insulin resistance (HOMA-IR): [fasting insulin (mU/mL) x fasting glucose (mmol/L)]/22.5 at 0 and 3 months, and again at 12 months.
measure: Glucose levels
time frame: 0, 3,12 months
description: Glucose changes will be assessed by the total and incremental 24-hour glucose AUC, from ambulatory CGM at 0 and 3 months.
measure: Glucose variability
time frame: 0, 3,12 months
description: CGM data will be used to calculate standard measures of glucose variability (GV), including mean amplitude of glycemic excursion (MAGE) changes at 0 and 3 months.
measure: Sleep assessment
time frame: 0, 3,12 months
description: Sleep duration will be assessed by changes in bedtime, waketime, and total sleep time, recorded by actigraphy during the 2-wk ambulatory assessments at 0, 3, and 12 months.
measure: Adherence
time frame: 0, 3,12 months
description: Adherence will be assessed by % of days with at least 2 or more entries logged at least 5h apart/day
measure: Diet composition by ASA24
time frame: 0, 3, 12 months
description: % of carbs, fat and protein in diet by ASA24 on 3 non-consecutive days (2 weekdays and one weekend day) during each ambulatory assessment and during the 3 months intervention.
measure: Matsuda Index (Insulin resistance)
time frame: 0, 3 months
description: Fasting and OGTT glucose and insulin levels are used to calculate the Matsuda index:
10,000/([fasting insulin (mU/mL)x fasting glucose (mmol/L)]x [mean OGTT insulin (mU/mL) x mean OGTT glucose (mmol/L)])
measure: Insulinogenic Index
time frame: 0, 3 months
description: Calculated by the AUC insulin/AUC glucose during OGTT.
measure: Free fatty acids (FFA)
time frame: 0, 3, 12 months
description: Measured from a fasting blood sample
measure: Ketones
time frame: 0, 3, 12 months
description: The concentration of ketones (beta-OH-butyrate) will be measured from a fasting blood sample.
measure: Physical activity
time frame: 0, 3, 12 months
description: Assessed by step count during 14 day ambulatory assessment periods at 0,3, and 12 months.
measure: Inflammation markers
time frame: 0, 3, 12 months
description: Measured from a fasting blood sample.
measure: Oxidative stress
time frame: 0, 3, 12 months
description: Measured from a fasting blood sample
measure: Lipid profile
time frame: 0, 3, 12 months
description: Measured from a fasting blood sample
arm group label: HABIT Group
arm group type: Active Comparator
description: Participants randomized to the HABIT group will maintain their habitual eating schedule (≥13-h).
arm group label: TRE Group
arm group type: Experimental
description: Participants randomized to TRE will reduce their eating window to a self-selected eating window (≤10-h).
intervention type: Behavioral
intervention name: TRE
description: The TRE intervention will be administered and monitored via the study app. It combines self-monitoring behavior, daily eating window reminders, positive reinforcement based on number of log entries or based on meeting eating widow target, and basic lifestyle text messages. It also allows research staff to monitor in real-time, via the backend cloud, adherence to self-monitoring, and to reducing the eating window.
arm group label: TRE Group
intervention type: Behavioral
intervention name: HABIT
description: The HABIT intervention will be administered and monitored via the study app. It combines self-monitoring behavior, positive reinforcement based on number of log entries, and basic lifestyle text messages. It also allows research staff to monitor in real-time, via the backend cloud, adherence to self-monitoring.
arm group label: HABIT Group
criteria: 
gender: All
minimum age: 50 Years
maximum age: 75 Years
healthy volunteers: No
last name: Blandine Laferrère, M.D., Ph.D.
role: Principal Investigator
affiliation: Columbia University
last name: Delaney Shaw, MS
phone: 212-851-5576
email: ds3936@cumc.columbia.edu
last name: Blandine Laferrere, MD, PhD
phone: 212-851-5562
email: bbl14@columbia.edu
facility: 
status: Recruiting
contact: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: Columbia University
investigator full name: Blandine Laferrere
investigator title: Professor of Medicine
mesh term: Overweight
mesh term: Prediabetic State
mesh term: Glucose Intolerance
sharing ipd: Yes
ipd description: Columbia University is committed to the open and timely dissemination of research outcomes. Investigators in this proposed project are aware of and agree to abide by the principles for sharing research resources, as described by NIH in "Principles and Guidelines for Recipients of NIH Research Grants and Contracts on Obtaining and Disseminating Biomedical Research Programs." All data used in this proposal will de-identified, and accessed using a secure data area using a shared drive, protected by password only to be accessed by those directly involved in the clinical research. All transfer of data will use encrypted methods. Wherever applicable, fully de-identified data will be deposited to appropriate public repositories, following the Federal Health Insurance Privacy and Portability Act (HIPAA).
ipd time frame: This will occur no longer than 6 months after publications of the data generated by this application, or, 18 months after completion of the funding period, should no data had been published.
ipd access criteria: The data generated in this grant will be presented at national or international conferences and published in a timely fashion. All final peer-reviewed manuscripts that arise from this proposal will be submitted upon acceptance for publication to the digital archive NIH National Library of Medicine PubMed Central (PMC) database, according to the NIH Policy on Enhancing Public Access to Archived Publications Resulting from NIH Funded Research. Any data released for publication will be for research purposes only and will not include identifiable data on any of the participants.