xml: <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/NCT05994313</url>
    </required_header>
    <id_info>
      <org_study_id>RCT-DNS-SS-2023</org_study_id>
      <nct_id>NCT05994313</nct_id>
    </id_info>
    <brief_title>STARchy Staples: a Randomised Controlled Trial on Cardiometabolic Health</brief_title>
    <acronym>STARCHy</acronym>
    <official_title>STARchy Staples: a Randomised Controlled Trial on Cardiometabolic Health</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>King's College London</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Alliance for Potato Research and Education</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Maastricht University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>King's College London</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        An investigation into habitual potato consumption (mashed, boiled, baked) on sleep quality&#xD;
        and chronic glycaemic control, established risk factors for cardiometabolic diseases, versus&#xD;
        habitual consumptions of non-nutrient-dense starchy staples (white rice, pasta, and&#xD;
        couscous).&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        In the last few years, researchers have undergone efforts to conduct well-controlled trials&#xD;
        to investigate the cardiometabolic health effect of consuming potatoes as part of a healthy&#xD;
        diet. None to our knowledge, however, have investigated the harmful dyad of poor sleep and&#xD;
        adverse glycaemic control, 2 interrelated factors which can exacerbate cardiometabolic (CM)&#xD;
        health outcomes. The nutrient density of potatoes, namely being the single richest source of&#xD;
        potassium per serving, provides a plausible mechanism in which the potatoes may act to&#xD;
        improve health markers.&#xD;
  &#xD;
        The primary objective of this study is to investigate whether consuming a portion of&#xD;
        nutrient-dense potatoes in the evening meal, in place of other refined carbohydrates, can&#xD;
        improve sleep quality, and improve nocturnal, and 24-hour, glycaemic control, both risk&#xD;
        factors for CM diseases. Secondly, this study aims to investigate the effects of potato&#xD;
        consumption on endothelium-dependent vasodilation, which can further interrelate to this web&#xD;
        of interactions, and other measures of CM health.&#xD;
  &#xD;
        Study design: A randomised, two-parallel arm, in-clinic and remote, 12-week dietary&#xD;
        intervention study.&#xD;
  &#xD;
        Study population: Healthy male and female 40-80-year-olds, who consume ≤4 fruits and&#xD;
        vegetables per day and have sub-optimal sleep quality.&#xD;
  &#xD;
        The study aims to recruit a total of 80 participants, allowing for an estimated 15% dropout&#xD;
        rate, to reach 80% power at a significance level of 0.025 (based on two outcomes). The&#xD;
        allocation ratio is 1:1 intervention to control.&#xD;
  &#xD;
        Locations:&#xD;
  &#xD;
        Metabolic Research Unit, 4th floor, Franklin Wilkins Building, Waterloo campus, Kings College&#xD;
        London, SE1 9NH.&#xD;
  &#xD;
        Screening assessment: Participants will be initially assessed for suitability against the&#xD;
        inclusion-exclusion criteria via an online questionnaire. The outputs of the questionnaire&#xD;
        will be assessed by the study team. Some exclusion criteria will be assessed at the baseline&#xD;
        clinic visit before any baseline measures are provided.&#xD;
  &#xD;
        Study duration: There will be a 2-week run-in period, followed by a 12-week dietary&#xD;
        intervention.&#xD;
  &#xD;
        Dietary intervention: The intervention (potato group) will consume at least 220 g of white&#xD;
        potatoes (25% of energy intake from carbohydrates, or 12.5% of total energy intake, including&#xD;
        fresh and frozen baked, boiled, and mashed potato products) in their evening meal, providing&#xD;
        ~800 mg potassium, enough to increase national median intakes up to recommended intakes. The&#xD;
        control group will consume isoenergetic amounts of non-nutrient-dense starchy staples (white&#xD;
        pasta, white rice, or couscous).&#xD;
  &#xD;
        Although participants cannot be blinded to what they're consuming, they will be blinded to&#xD;
        whether they are in the control or the intervention group, to reduce the risk of bias.&#xD;
  &#xD;
        Participants will be required to source the potatoes and make these meals themselves,&#xD;
        however, they will be provided with rotating 4-weekly recipe cards, with instructions on how&#xD;
        to prepare meals.&#xD;
  &#xD;
        Participants will be required to attend several virtual one-to-ones with the study team,&#xD;
        including an introductory call, a virtual run-in induction where they will be run through the&#xD;
        study equipment, and 2 in-person clinic visits. Participants will be responsible for applying&#xD;
        some study equipment from home, to reduce clinic visits and improve study retention.&#xD;
  &#xD;
        Compliance: Compliance will be monitored via several methods. Firstly, 24 h urinary potassium&#xD;
        excretion, which is shown to recover 75% of potassium intake, secondly self-reported&#xD;
        compliance will be measured through evening meal checklists. We also plan to use dietary&#xD;
        recalls at weeks 2, 4, and 8 to reinforce dietary advice, and to make adaptations to rotating&#xD;
        menus based on individual needs, if participants are struggling with adherence. Detailed&#xD;
        dietary intake will be assessed through 4-day food diaries at weeks 0, 6, and 12- this data&#xD;
        will be used for analysis.&#xD;
  &#xD;
        Flow-mediated dilation: A Doppler ultrasound will be utilised to capture continuous&#xD;
        ultrasound videos to measure flow-mediated dilation. These will be analysed with automated&#xD;
        software provided by Maastricht University.&#xD;
  &#xD;
        Anthropometry: Weight, height, waist and hip circumference, blood pressure, and body fat will&#xD;
        be taken using standard procedures, in duplicates by a trained researcher at baseline and&#xD;
        endline clinic visits.&#xD;
  &#xD;
        Blood samples: Fasting blood samples will be collected from a superficial antecubital vein&#xD;
        via venepuncture before and after the dietary intervention, by a trained researcher.&#xD;
  &#xD;
        Participants will be asked to record and monitor the following information:&#xD;
  &#xD;
        Self-reported compliance with dietary intervention, weekly weight (data diaries), and&#xD;
        habitual dietary intake (4-day diet diaries).&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Recruiting</overall_status>
    <start_date type="Anticipated">August 14, 2023</start_date>
    <completion_date type="Anticipated">August 1, 2025</completion_date>
    <primary_completion_date type="Anticipated">December 1, 2024</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>12-week Randomised controlled trial</intervention_model_description>
      <primary_purpose>Basic Science</primary_purpose>
      <masking>Single (Outcomes Assessor)</masking>
      <masking_description>Participants will be blinded to whether they are receiving the intervention or control, but it is not possible to blind them to the food itself. The researcher conducting the statistical analysis will be blinded prior to analysis, using a second set of unique study ID codes.</masking_description>
    </study_design_info>
    <primary_outcome>
      <measure>Change in 7-day sleep efficiency</measure>
      <time_frame>12 weeks</time_frame>
      <description>Differences in % sleep efficiency at endline vs baseline. Sleep efficiency % is described as the total time spent asleep/ total time spent in bed x 100.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Change in 12-day nocturnal glycaemic control</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Differences in glycaemic variability, time in range and continuous glucose data, calculated using the total area under the curve (tAUC) model. Measured with a continuous glucose monitor.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Change in 12-day daytime glycaemic control</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Differences in glycaemic variability, time in range and continuous glucose data, calculated using the total area under the curve (tAUC) model. Measured with a continuous glucose monitor.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in 24-hour nocturnal glycaemic control</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Differences in glycaemic variability, time in range and continuous glucose data, calculated using the total area under the curve (tAUC) model. Measured with a continuous glucose monitor.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in heart rate variability during mental stress</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>A combination of time domain, frequency domain and non-linear methods (NN intervals, Heart rate, rMSSD, SDNN, SD1/SD2, High frequency, Low frequency: high frequency ratio) will be compared from pre- to post-mental stress. The differences will be compared to pre- and post-intervention.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in 24-hour heart rate variability</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>A combination of time domain, frequency domain and non-linear methods (NN intervals, Heart rate, rMSSD, SDNN, SD1/SD2, High frequency, Low frequency: high frequency ratio) will be compared to pre- and post-intervention.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in Endothelial function</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Mean differences in flow mediated dilation.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>12-week nighttime continuous blood pressure</measure>
      <time_frame>Whole 12 week period.</time_frame>
      <description>Measured with an Aktiia Photoplethysmography watch.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>12-week daytime continuous blood pressure</measure>
      <time_frame>Whole 12 week period.</time_frame>
      <description>Measured with an Aktiia Photoplethysmography watch.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in blood pressure</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Diastolic and systolic blood pressure, measured by oscillometry.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in plasma lipids</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Including: total lipids, HDL and LDL-cholesterol, and Triacylglycerols.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in fasting plasma glucose</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Fasting plasma glucose concentration</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in fasting insulin</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Fasting insulin concentration</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in fasting HbA1C</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Fasting HbA1C concentration</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in sleep duration, in minutes</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Sleep duration (minutes)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in sleep duration, in %</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Sleep duration (%)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in sleep latency</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Sleep latency is defined as the time it takes to fall asleep from the time intended to fall asleep.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in body fat %</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Body fat % measured using TANITA bioelectrical impedance scales</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in waist circumference (cm)</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Waist circumference (cm)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in BMI kg/m2</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>BMI kg/m2, measured using a stadiometer and TANITA scales</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Change in diet quality</measure>
      <time_frame>Pre- and post-intervention: 12 weeks</time_frame>
      <description>Measured by several indices: plant-based diet index, alternative Mediterranean score, alternative healthy eating index and high-fat index.</description>
    </secondary_outcome>
    <other_outcome>
      <measure>Change in meal satiety</measure>
      <time_frame>Total of 15 satiety scales: 1 pre- and 4 postprandial scales (-1, 1, 2, 3 hours after), in 3 in food diaries (week 0, week 6 and week 12).</time_frame>
      <description>Mean difference in area under the satiety curve (exploratory)</description>
    </other_outcome>
    <number_of_arms>2</number_of_arms>
    <enrollment type="Anticipated">80</enrollment>
    <condition>Cardiometabolic Health</condition>
    <arm_group>
      <arm_group_label>Habitual potato consumption</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>At least 220g of white potatoes, including fresh and frozen, baked, boiled, and mashed potatoes, will be consumed in the evening meal, in replacement of non-nutrient-dense starchy staples, for 12 weeks.</description>
    </arm_group>
    <arm_group>
      <arm_group_label>Habitual non-nutrient-dense staple consumption</arm_group_label>
      <arm_group_type>Active Comparator</arm_group_type>
      <description>Isocaloric amounts of non-nutrient-dense starchy staples, such as white rice, white pasta, and white couscous, will be consumed in the evening meal for 12 weeks.</description>
    </arm_group>
    <intervention>
      <intervention_type>Dietary Supplement</intervention_type>
      <intervention_name>Habitual potato consumption</intervention_name>
      <description>Potatoes are to be consumed in the evening meal, every evening for 12-weeks.</description>
      <arm_group_label>Habitual potato consumption</arm_group_label>
    </intervention>
    <intervention>
      <intervention_type>Dietary Supplement</intervention_type>
      <intervention_name>Habitual non-nutrient-dense staple consumption</intervention_name>
      <description>White rice, white pasta or white couscous are to be consumed in the evening meal, every evening for 12-weeks.</description>
      <arm_group_label>Habitual non-nutrient-dense staple consumption</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Self-reported healthy adults&#xD;
  &#xD;
            -  Aged 40-80 years old&#xD;
  &#xD;
            -  Intake of ≤4 portions of fruits and vegetables (excluding potatoes) per day&#xD;
  &#xD;
            -  Low sleep quality index of &gt;5 (Pittsburgh sleep quality index).&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Shift workers and those with multiple jobs or carers who are required to wake through&#xD;
               the night&#xD;
  &#xD;
            -  Unwilling to refrain from dietary supplements&#xD;
  &#xD;
            -  Unwilling to follow protocol and/or give informed consent&#xD;
  &#xD;
            -  Diagnosed with Cardiovascular Disease (CVD), Type 2 Diabetes, Celiac disease,&#xD;
               Insomnia, Sleep apnoea&#xD;
  &#xD;
            -  Presence of gastrointestinal disorder&#xD;
  &#xD;
            -  Users of drugs that are likely to alter gastrointestinal motility or nutrient&#xD;
               absorption&#xD;
  &#xD;
            -  History of substance abuse or alcoholism&#xD;
  &#xD;
            -  Currently pregnant, planning pregnancy, breastfeeding, or having had a baby 12 months&#xD;
               prior&#xD;
  &#xD;
            -  Weight change of &gt;3kg in the preceding 2 months&#xD;
  &#xD;
            -  BMI &lt;18.5kg/m2 or &gt; 35kg/m2,&#xD;
  &#xD;
            -  Current smokers, or individuals who quit smoking in the last 6-months&#xD;
  &#xD;
            -  Frequently consume wholemeal products (1-2 times per day, in the short screening FFQ)&#xD;
  &#xD;
            -  Never consumed refined starchy staples, such as white pasta or rice (rarely or never,&#xD;
               in the short screening FFQ)&#xD;
  &#xD;
            -  High potato consumption (4-6 times per week, in the short screening FFQ)&#xD;
  &#xD;
            -  High risk of obstructive sleep apnoea (answer yes to &gt;3 questions, in STOP-Bang&#xD;
               questionnaire)&#xD;
  &#xD;
            -  Vegetarian, Vegan, or pescatarian dietary preferences.&#xD;
  &#xD;
            -  Diagnosed with mental health disorders, and/or on medicine for their mental health&#xD;
               (antipsychotics, antidepressants, beta-blockers)&#xD;
  &#xD;
            -  Chronic user of antihistamines&#xD;
  &#xD;
            -  Fasting glucose &gt;7mmol/l (finger prick test at baseline clinic)&#xD;
  &#xD;
            -  Is taking weight loss, or glucose regulating medications.&#xD;
  &#xD;
            -  Has been unstable on blood pressure lowering medications for at least 3-months prior&#xD;
               to enrollment.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>40 Years</minimum_age>
      <maximum_age>80 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Wendy Hall, PhD</last_name>
      <role>Principal Investigator</role>
      <affiliation>King's College London</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Anya Klarner, MSc</last_name>
      <phone>+44(0) 7935861617</phone>
      <email>anya.klarner@kcl.ac.uk</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Wendy Hall, PhD</last_name>
      <phone>+44(0) 20 7848 4197</phone>
      <email>wendy.hall@kcl.ac.uk</email>
    </overall_contact_backup>
    <location>
      <facility>
        <name>Department of Nutritional Sciences, Franklin Wilkins Building, Waterloo campus.</name>
        <address>
          <city>Lambeth</city>
          <state>London</state>
          <zip>SE1 9NH</zip>
          <country>United Kingdom</country>
        </address>
      </facility>
      <status>Recruiting</status>
      <contact>
        <last_name>Anya Klarner, MSc</last_name>
        <phone>+44(0) 7935861617</phone>
        <email>anya.klarner@kcl.ac.uk</email>
      </contact>
      <contact_backup>
        <last_name>Wendy Hall, PhD</last_name>
        <phone>+44(0) 20 7848 4197</phone>
        <email>wendy.hall@kcl.ac.uk</email>
      </contact_backup>
      <investigator>
        <last_name>Wendy Hall, PhD</last_name>
        <role>Principal Investigator</role>
      </investigator>
      <investigator>
        <last_name>Sarah Berry, PhD</last_name>
        <role>Sub-Investigator</role>
      </investigator>
    </location>
    <location_countries>
      <country>United Kingdom</country>
    </location_countries>
    <reference>
      <citation>Robertson TM, Alzaabi AZ, Robertson MD, Fielding BA. Starchy Carbohydrates in a Healthy Diet: The Role of the Humble Potato. Nutrients. 2018 Nov 14;10(11):1764. doi: 10.3390/nu10111764.</citation>
      <PMID>30441846</PMID>
    </reference>
    <reference>
      <citation>McGill CR, Kurilich AC, Davignon J. The role of potatoes and potato components in cardiometabolic health: a review. Ann Med. 2013 Nov;45(7):467-73. doi: 10.3109/07853890.2013.813633. Epub 2013 Jul 15.</citation>
      <PMID>23855880</PMID>
    </reference>
    <reference>
      <citation>Stone MS, Martin BR, Weaver CM. Short-Term RCT of Increased Dietary Potassium from Potato or Potassium Gluconate: Effect on Blood Pressure, Microcirculation, and Potassium and Sodium Retention in Pre-Hypertensive-to-Hypertensive Adults. Nutrients. 2021 May 11;13(5):1610. doi: 10.3390/nu13051610.</citation>
      <PMID>34064968</PMID>
    </reference>
    <reference>
      <citation>Johnston EA, Petersen KS, Kris-Etherton PM. Daily intake of non-fried potato does not affect markers of glycaemia and is associated with better diet quality compared with refined grains: a randomised, crossover study in healthy adults. Br J Nutr. 2020 May 14;123(9):1032-1042. doi: 10.1017/S0007114520000252. Epub 2020 Jan 22.</citation>
      <PMID>31964428</PMID>
    </reference>
    <reference>
      <citation>Macdonald-Clarke CJ, Martin BR, McCabe LD, McCabe GP, Lachcik PJ, Wastney M, Weaver CM. Bioavailability of potassium from potatoes and potassium gluconate: a randomized dose response trial. Am J Clin Nutr. 2016 Aug;104(2):346-53. doi: 10.3945/ajcn.115.127225. Epub 2016 Jul 13.</citation>
      <PMID>27413123</PMID>
    </reference>
    <reference>
      <citation>D'Elia L, Masulli M, Cappuccio FP, Zarrella AF, Strazzullo P, Galletti F. Dietary Potassium Intake and Risk of Diabetes: A Systematic Review and Meta-Analysis of Prospective Studies. Nutrients. 2022 Nov 12;14(22):4785. doi: 10.3390/nu14224785.</citation>
      <PMID>36432472</PMID>
    </reference>
    <verification_date>July 2023</verification_date>
    <study_first_submitted>August 1, 2023</study_first_submitted>
    <study_first_submitted_qc>August 15, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 16, 2023</study_first_posted>
    <last_update_submitted>August 15, 2023</last_update_submitted>
    <last_update_submitted_qc>August 15, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 16, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Sleep efficiency</keyword>
    <keyword>Glycemic control</keyword>
    <keyword>Flow mediated dilation</keyword>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: 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/NCT05994313
  org study id: RCT-DNS-SS-2023
  nct id: NCT05994313
  lead sponsor: 
  collaborator: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  An investigation into habitual potato consumption (mashed, boiled, baked) on sleep quality
        and chronic glycaemic control, established risk factors for cardiometabolic diseases, versus
        habitual consumptions of non-nutrient-dense starchy staples (white rice, pasta, and
        couscous).
  In the last few years, researchers have undergone efforts to conduct well-controlled trials
        to investigate the cardiometabolic health effect of consuming potatoes as part of a healthy
        diet. None to our knowledge, however, have investigated the harmful dyad of poor sleep and
        adverse glycaemic control, 2 interrelated factors which can exacerbate cardiometabolic (CM)
        health outcomes. The nutrient density of potatoes, namely being the single richest source of
        potassium per serving, provides a plausible mechanism in which the potatoes may act to
        improve health markers.
  
        The primary objective of this study is to investigate whether consuming a portion of
        nutrient-dense potatoes in the evening meal, in place of other refined carbohydrates, can
        improve sleep quality, and improve nocturnal, and 24-hour, glycaemic control, both risk
        factors for CM diseases. Secondly, this study aims to investigate the effects of potato
        consumption on endothelium-dependent vasodilation, which can further interrelate to this web
        of interactions, and other measures of CM health.
  
        Study design: A randomised, two-parallel arm, in-clinic and remote, 12-week dietary
        intervention study.
  
        Study population: Healthy male and female 40-80-year-olds, who consume ≤4 fruits and
        vegetables per day and have sub-optimal sleep quality.
  
        The study aims to recruit a total of 80 participants, allowing for an estimated 15% dropout
        rate, to reach 80% power at a significance level of 0.025 (based on two outcomes). The
        allocation ratio is 1:1 intervention to control.
  
        Locations:
  
        Metabolic Research Unit, 4th floor, Franklin Wilkins Building, Waterloo campus, Kings College
        London, SE1 9NH.
  
        Screening assessment: Participants will be initially assessed for suitability against the
        inclusion-exclusion criteria via an online questionnaire. The outputs of the questionnaire
        will be assessed by the study team. Some exclusion criteria will be assessed at the baseline
        clinic visit before any baseline measures are provided.
  
        Study duration: There will be a 2-week run-in period, followed by a 12-week dietary
        intervention.
  
        Dietary intervention: The intervention (potato group) will consume at least 220 g of white
        potatoes (25% of energy intake from carbohydrates, or 12.5% of total energy intake, including
        fresh and frozen baked, boiled, and mashed potato products) in their evening meal, providing
        ~800 mg potassium, enough to increase national median intakes up to recommended intakes. The
        control group will consume isoenergetic amounts of non-nutrient-dense starchy staples (white
        pasta, white rice, or couscous).
  
        Although participants cannot be blinded to what they're consuming, they will be blinded to
        whether they are in the control or the intervention group, to reduce the risk of bias.
  
        Participants will be required to source the potatoes and make these meals themselves,
        however, they will be provided with rotating 4-weekly recipe cards, with instructions on how
        to prepare meals.
  
        Participants will be required to attend several virtual one-to-ones with the study team,
        including an introductory call, a virtual run-in induction where they will be run through the
        study equipment, and 2 in-person clinic visits. Participants will be responsible for applying
        some study equipment from home, to reduce clinic visits and improve study retention.
  
        Compliance: Compliance will be monitored via several methods. Firstly, 24 h urinary potassium
        excretion, which is shown to recover 75% of potassium intake, secondly self-reported
        compliance will be measured through evening meal checklists. We also plan to use dietary
        recalls at weeks 2, 4, and 8 to reinforce dietary advice, and to make adaptations to rotating
        menus based on individual needs, if participants are struggling with adherence. Detailed
        dietary intake will be assessed through 4-day food diaries at weeks 0, 6, and 12- this data
        will be used for analysis.
  
        Flow-mediated dilation: A Doppler ultrasound will be utilised to capture continuous
        ultrasound videos to measure flow-mediated dilation. These will be analysed with automated
        software provided by Maastricht University.
  
        Anthropometry: Weight, height, waist and hip circumference, blood pressure, and body fat will
        be taken using standard procedures, in duplicates by a trained researcher at baseline and
        endline clinic visits.
  
        Blood samples: Fasting blood samples will be collected from a superficial antecubital vein
        via venepuncture before and after the dietary intervention, by a trained researcher.
  
        Participants will be asked to record and monitor the following information:
  
        Self-reported compliance with dietary intervention, weekly weight (data diaries), and
        habitual dietary intake (4-day diet diaries).
  allocation: Randomized
  intervention model: Parallel Assignment
  intervention model description: 12-week Randomised controlled trial
  primary purpose: Basic Science
  masking: Single (Outcomes Assessor)
  masking description: Participants will be blinded to whether they are receiving the intervention or control, but it is not possible to blind them to the food itself. The researcher conducting the statistical analysis will be blinded prior to analysis, using a second set of unique study ID codes.
  measure: Change in 7-day sleep efficiency
  time frame: 12 weeks
  description: Differences in % sleep efficiency at endline vs baseline. Sleep efficiency % is described as the total time spent asleep/ total time spent in bed x 100.
  measure: Change in 12-day nocturnal glycaemic control
  time frame: Pre- and post-intervention: 12 weeks
  description: Differences in glycaemic variability, time in range and continuous glucose data, calculated using the total area under the curve (tAUC) model. Measured with a continuous glucose monitor.
  measure: Change in 12-day daytime glycaemic control
  time frame: Pre- and post-intervention: 12 weeks
  description: Differences in glycaemic variability, time in range and continuous glucose data, calculated using the total area under the curve (tAUC) model. Measured with a continuous glucose monitor.
  measure: Change in 24-hour nocturnal glycaemic control
  time frame: Pre- and post-intervention: 12 weeks
  description: Differences in glycaemic variability, time in range and continuous glucose data, calculated using the total area under the curve (tAUC) model. Measured with a continuous glucose monitor.
  measure: Change in heart rate variability during mental stress
  time frame: Pre- and post-intervention: 12 weeks
  description: A combination of time domain, frequency domain and non-linear methods (NN intervals, Heart rate, rMSSD, SDNN, SD1/SD2, High frequency, Low frequency: high frequency ratio) will be compared from pre- to post-mental stress. The differences will be compared to pre- and post-intervention.
  measure: Change in 24-hour heart rate variability
  time frame: Pre- and post-intervention: 12 weeks
  description: A combination of time domain, frequency domain and non-linear methods (NN intervals, Heart rate, rMSSD, SDNN, SD1/SD2, High frequency, Low frequency: high frequency ratio) will be compared to pre- and post-intervention.
  measure: Change in Endothelial function
  time frame: Pre- and post-intervention: 12 weeks
  description: Mean differences in flow mediated dilation.
  measure: 12-week nighttime continuous blood pressure
  time frame: Whole 12 week period.
  description: Measured with an Aktiia Photoplethysmography watch.
  measure: 12-week daytime continuous blood pressure
  time frame: Whole 12 week period.
  description: Measured with an Aktiia Photoplethysmography watch.
  measure: Change in blood pressure
  time frame: Pre- and post-intervention: 12 weeks
  description: Diastolic and systolic blood pressure, measured by oscillometry.
  measure: Change in plasma lipids
  time frame: Pre- and post-intervention: 12 weeks
  description: Including: total lipids, HDL and LDL-cholesterol, and Triacylglycerols.
  measure: Change in fasting plasma glucose
  time frame: Pre- and post-intervention: 12 weeks
  description: Fasting plasma glucose concentration
  measure: Change in fasting insulin
  time frame: Pre- and post-intervention: 12 weeks
  description: Fasting insulin concentration
  measure: Change in fasting HbA1C
  time frame: Pre- and post-intervention: 12 weeks
  description: Fasting HbA1C concentration
  measure: Change in sleep duration, in minutes
  time frame: Pre- and post-intervention: 12 weeks
  description: Sleep duration (minutes)
  measure: Change in sleep duration, in %
  time frame: Pre- and post-intervention: 12 weeks
  description: Sleep duration (%)
  measure: Change in sleep latency
  time frame: Pre- and post-intervention: 12 weeks
  description: Sleep latency is defined as the time it takes to fall asleep from the time intended to fall asleep.
  measure: Change in body fat %
  time frame: Pre- and post-intervention: 12 weeks
  description: Body fat % measured using TANITA bioelectrical impedance scales
  measure: Change in waist circumference (cm)
  time frame: Pre- and post-intervention: 12 weeks
  description: Waist circumference (cm)
  measure: Change in BMI kg/m2
  time frame: Pre- and post-intervention: 12 weeks
  description: BMI kg/m2, measured using a stadiometer and TANITA scales
  measure: Change in diet quality
  time frame: Pre- and post-intervention: 12 weeks
  description: Measured by several indices: plant-based diet index, alternative Mediterranean score, alternative healthy eating index and high-fat index.
  measure: Change in meal satiety
  time frame: Total of 15 satiety scales: 1 pre- and 4 postprandial scales (-1, 1, 2, 3 hours after), in 3 in food diaries (week 0, week 6 and week 12).
  description: Mean difference in area under the satiety curve (exploratory)
  arm group label: Habitual potato consumption
  arm group type: Experimental
  description: At least 220g of white potatoes, including fresh and frozen, baked, boiled, and mashed potatoes, will be consumed in the evening meal, in replacement of non-nutrient-dense starchy staples, for 12 weeks.
  arm group label: Habitual non-nutrient-dense staple consumption
  arm group type: Active Comparator
  description: Isocaloric amounts of non-nutrient-dense starchy staples, such as white rice, white pasta, and white couscous, will be consumed in the evening meal for 12 weeks.
  intervention type: Dietary Supplement
  intervention name: Habitual potato consumption
  description: Potatoes are to be consumed in the evening meal, every evening for 12-weeks.
  arm group label: Habitual potato consumption
  intervention type: Dietary Supplement
  intervention name: Habitual non-nutrient-dense staple consumption
  description: White rice, white pasta or white couscous are to be consumed in the evening meal, every evening for 12-weeks.
  arm group label: Habitual non-nutrient-dense staple consumption
  criteria: 
  gender: All
  minimum age: 40 Years
  maximum age: 80 Years
  healthy volunteers: Accepts Healthy Volunteers
  last name: Wendy Hall, PhD
  role: Principal Investigator
  affiliation: King's College London
  last name: Anya Klarner, MSc
  phone: +44(0) 7935861617
  email: anya.klarner@kcl.ac.uk
  last name: Wendy Hall, PhD
  phone: +44(0) 20 7848 4197
  email: wendy.hall@kcl.ac.uk
  facility: 
  status: Recruiting
  contact: 
  contact backup: 
  investigator: 
  investigator: 
  country: United Kingdom
  citation: Robertson TM, Alzaabi AZ, Robertson MD, Fielding BA. Starchy Carbohydrates in a Healthy Diet: The Role of the Humble Potato. Nutrients. 2018 Nov 14;10(11):1764. doi: 10.3390/nu10111764.
  PMID: 30441846
  citation: McGill CR, Kurilich AC, Davignon J. The role of potatoes and potato components in cardiometabolic health: a review. Ann Med. 2013 Nov;45(7):467-73. doi: 10.3109/07853890.2013.813633. Epub 2013 Jul 15.
  PMID: 23855880
  citation: Stone MS, Martin BR, Weaver CM. Short-Term RCT of Increased Dietary Potassium from Potato or Potassium Gluconate: Effect on Blood Pressure, Microcirculation, and Potassium and Sodium Retention in Pre-Hypertensive-to-Hypertensive Adults. Nutrients. 2021 May 11;13(5):1610. doi: 10.3390/nu13051610.
  PMID: 34064968
  citation: Johnston EA, Petersen KS, Kris-Etherton PM. Daily intake of non-fried potato does not affect markers of glycaemia and is associated with better diet quality compared with refined grains: a randomised, crossover study in healthy adults. Br J Nutr. 2020 May 14;123(9):1032-1042. doi: 10.1017/S0007114520000252. Epub 2020 Jan 22.
  PMID: 31964428
  citation: Macdonald-Clarke CJ, Martin BR, McCabe LD, McCabe GP, Lachcik PJ, Wastney M, Weaver CM. Bioavailability of potassium from potatoes and potassium gluconate: a randomized dose response trial. Am J Clin Nutr. 2016 Aug;104(2):346-53. doi: 10.3945/ajcn.115.127225. Epub 2016 Jul 13.
  PMID: 27413123
  citation: D'Elia L, Masulli M, Cappuccio FP, Zarrella AF, Strazzullo P, Galletti F. Dietary Potassium Intake and Risk of Diabetes: A Systematic Review and Meta-Analysis of Prospective Studies. Nutrients. 2022 Nov 12;14(22):4785. doi: 10.3390/nu14224785.
  PMID: 36432472
  responsible party type: Sponsor
  sharing ipd: No