<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/NCT03283332</url>
  </required_header>
  <id_info>
    <org_study_id>05/MRE10/43</org_study_id>
    <nct_id>NCT03283332</nct_id>
  </id_info>
  <brief_title>Determinants of Adolescent, Now Young Adults, Social Well-being and Health: Longitudinal Follow-up</brief_title>
  <acronym>DASH</acronym>
  <official_title>Determinants of Adolescent Social Well-being and Health: a London Based Longitudinal Study of Young People From Different Ethnic Groups</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>King's College London</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Medical Research Council</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Chief Scientist Office of the Scottish Government</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>
      Black and ethnic minority groups living in the UK experience high rates of chronic diseases&#xD;
      such as diabetes, hypertension and heart disease, general morbidity and poor mental health.&#xD;
      The cause of these excess rates is unknown but obesity, smoking, diet and deprivation are&#xD;
      important contributing factors. There is also global evidence of the association of these&#xD;
      diseases in adulthood with health and deprivation in early life and childhood. Persisting&#xD;
      social deprivation over the lifecourse is disproportionately borne by some ethnic minorities&#xD;
      (Harding and Balarajan 2001) but the impact on the health of their children is virtually&#xD;
      unknown. Least is known about the health of Black Caribbean young people. It is important to&#xD;
      examine risk factor differences by social predictors within the ethnic minority groups as&#xD;
      well as between them. The DASH Study started as a school-based cohort study of adolescents&#xD;
      from the main ethnic groups (White British, Black Caribbean, Black African, Indian, Pakistani&#xD;
      and Bangladeshi) in 10 London boroughs. Wave 1 took place in 2002/03 (MREC Ref:&#xD;
      MREC/2/10/12), when participants were aged 11-13 years (school years 7 and 8). Wave 2 took&#xD;
      place in 2005/06 (MREC Ref: 05/MRE10/43) when they were 14-16 years (school years 9 and 10).&#xD;
      Wave 3 took place in 2010/2011, when participants were aged 19-21 years and involved a postal&#xD;
      follow-up complemented by telephone interview and on-line questionnaires. The current&#xD;
      proposal is for a feasibility study, using a small sample of the DASH cohort, to inform the&#xD;
      design of the next full face-to-face follow-up. DASH will be the first large scale UK&#xD;
      longitudinal cohort of ethnic minority youths with both social and biological measures from&#xD;
      childhood to early adulthood. It will allow detailed examination of ethnic differences in the&#xD;
      social patterning of biological mechanisms and pre-clinical disease in young adulthood.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Background:&#xD;
&#xD;
      Black and ethnic minority groups living in the UK experience high rates of chronic diseases&#xD;
      such as diabetes, hypertension and heart disease, general morbidity and poor mental health.&#xD;
      The cause of these excess rates is unknown but obesity, smoking, diet and deprivation are&#xD;
      important contributing factors. There is also global evidence of the association of these&#xD;
      diseases in adulthood with health and deprivation in early life and childhood. Persisting&#xD;
      social deprivation over the lifecourse is disproportionately borne by some ethnic minorities&#xD;
      (Harding and Balarajan 2001) but the impact on the health of their children is virtually&#xD;
      unknown. Least is known about the health of Black Caribbean young people. It is important to&#xD;
      examine risk factor differences by social predictors within the ethnic minority groups as&#xD;
      well as between them. The DASH Study started as a school-based cohort study of adolescents&#xD;
      from the main ethnic groups (White British, Black Caribbean, Black African, Indian, Pakistani&#xD;
      and Bangladeshi) in 10 London boroughs. Wave 1 took place in 2002/03 (MREC Ref:&#xD;
      MREC/2/10/12), when participants were aged 11-13 years (school years 7 and 8). Wave 2 took&#xD;
      place in 2005/06 (MREC Ref: 05/MRE10/43) when they were 14-16 years (school years 9 and 10).&#xD;
      Wave 3 took place in 2010/2011, when participants were aged 19-21 years and involved a postal&#xD;
      follow-up complemented by telephone interview and on-line questionnaires. The current&#xD;
      proposal is for a feasibility study, using a small sample of the DASH cohort, to inform the&#xD;
      design of the next full face-to-face follow-up. DASH will be the first large scale UK&#xD;
      longitudinal cohort of ethnic minority youths with both social and biological measures from&#xD;
      childhood to early adulthood. It will allow detailed examination of ethnic differences in the&#xD;
      social patterning of biological mechanisms and pre-clinical disease in young adulthood.&#xD;
&#xD;
      Aims:&#xD;
&#xD;
      (i) To conduct a feasibility study to establish the best methods for data collection,&#xD;
      including the collection of physical and biological measurements, for subsequent face to face&#xD;
      follow-up of the entire cohort.&#xD;
&#xD;
      (ii) To generate a proposal for subsequent follow-up of the entire cohort for submission to&#xD;
      MRC, dependent on the findings of the postal and telephone surveys and proposed feasibility&#xD;
      study.&#xD;
&#xD;
      Objectives:&#xD;
&#xD;
      I. What are the advantages and disadvantages of conducting the study in the two settings - GP&#xD;
      surgeries and homes?&#xD;
&#xD;
        1. Do participants' response rates vary by setting?&#xD;
&#xD;
        2. What are the challenges faced by the nurses in clinics and home visits?&#xD;
&#xD;
        3. Will the quality of data collected (e.g. extent of missing data) vary by setting?&#xD;
&#xD;
        4. Will the delivery of blood samples to the laboratory be reasonably straight forward in&#xD;
           each setting? II. What percentage of participants will agree to undertake bio-marker&#xD;
           measures? III. Are mental health measures for this age group, typically used with White&#xD;
           European populations, culturally appropriate? IV. How will DASH participants' view&#xD;
           feedback on their medical results (e.g. blood pressure, weight, blood lipids)? V. Were&#xD;
           participants satisfied with the different components of the survey process - contact,&#xD;
           consent, data collection? VI. What is the estimated length of time and the resources&#xD;
           required for subsequent full follow-up of DASH study members?&#xD;
&#xD;
      Outcome measures:&#xD;
&#xD;
      These will be examined by setting (home visit, GP surgery) using a mixture of quantitative&#xD;
      and qualitative methods and are as follows:&#xD;
&#xD;
      I. Percentage response rates - overall, per item/physical measure; II. Percentage consistency&#xD;
      of answers to questionnaire items; III. Percentage physical measures within expected range&#xD;
      e.g. spirometric measures; IV. Mean length of time for interview; V. Mean length of time for&#xD;
      taking physical/biological measures; VI. Qualitative appraisal of cultural appropriateness of&#xD;
      mental health measures and of respondents' satisfaction with survey processes.&#xD;
&#xD;
      Sample At the recent telephone survey, respondents were asked if they would be willing to&#xD;
      take part in a small feasibility study to prepare for a later full face to face follow-up.&#xD;
      Almost all agreed and of those, a sample of 300 (40-50 in each of the main ethnic groups-&#xD;
      White British, Black Caribbean, Black African, Pakistani, Bangladeshi, Indian) will be&#xD;
      invited to complete a questionnaire, and have physical and physiological measures taken.&#xD;
      Interviews will be conducted in respondents' own homes or GP surgeries dependent on the&#xD;
      preference of the respondent. As this is a feasibility study, the sample size has been chosen&#xD;
      pragmatically to give a reasonable spread, with equal gender representation across the 10&#xD;
      London boroughs that the whole sample was in at wave 2.&#xD;
&#xD;
      Specially trained nurses will conduct the survey in homes or General Practitioners'&#xD;
      surgeries, supervised by a nurse manager in the General Practice Research Framework. Nurses&#xD;
      will be attached either to the General Research Practice Framework or the Primary Care&#xD;
      Research Network.&#xD;
&#xD;
      Main Questionnaire The content reflects mainly questions that were asked in previous waves&#xD;
      (general health; health behaviours; psychological well-being; SEC; social support; and&#xD;
      relationship with parents). New items include parenthood; age appropriate mental health&#xD;
      measures; own education, economic activity and occupation; job strain; caring; 'romantic'&#xD;
      relationships; positive and negative emotions; views on their parents being invited to&#xD;
      participate in DASH in order to examine generational influences. The investigators will&#xD;
      explore two methods of delivery of the questionnaires - self complete questionnaires done&#xD;
      prior to visit and computer assisted interviews. If the questionnaire is not completed by the&#xD;
      time of the interview, respondents will be asked if they would like to complete a computer&#xD;
      assisted interview. Completion of the questionnaire is expected to take about 40 minutes.&#xD;
&#xD;
      Physical/physiological measures As in waves 1/and 2, height, weight, arm, waist and hip&#xD;
      circumference, lung function, blood pressure will be measured.&#xD;
&#xD;
      New measures include:&#xD;
&#xD;
      (i)Hand to foot bio-impedance (ii) Bio-markers - HbA1c, total cholesterol, HDL-cholesterol&#xD;
      (iii) Dietary assessment - 24 hour recall interviews Qualitative assessment - focus groups&#xD;
      and semi-structured interviews. For the new mental health/cognitive measures, the&#xD;
      investigators will conduct focus group vignette assessment, based on explanatory model and&#xD;
      illness perception theories. This will be carried out in a small sub-sample (6 participants&#xD;
      per ethnic group and allowing for 2 gender-specific groups; n=48). Analysis of these data&#xD;
      will focus on narratives about the signs and symptoms of different aspects of mental health&#xD;
      in the different ethnic groups. These data will provide valuable insights about the&#xD;
      appropriateness of measures, usually validated with European populations, for ethnic minority&#xD;
      groups.&#xD;
&#xD;
      A research scientist will conduct semi-structured interviews with respondents to obtain&#xD;
      feedback on the process of follow-up - what worked well, how best to improve the process,&#xD;
      what was un/acceptable etc. The investigators will also enquire about the usefulness of&#xD;
      feedback of results. A similar evaluation will take place with the nurses with the aim of&#xD;
      identifying best practice in clinics and homes.&#xD;
&#xD;
      Data analysis Descriptive statistics will be used to look at the general distributions and&#xD;
      quality of the data collected. Outcomes measured as rates will be examined by data collection&#xD;
      setting (GP surgeries vs. home visits), ethnic group and socio-demographic characteristics&#xD;
      using standard comparisons technique such as Chi-square test or logistic regression. Mean&#xD;
      length of time and any continuous outcomes will be compared using linear regression. In&#xD;
      addition, although the sample size of each ethnic group is small, the total sample will allow&#xD;
      analyses of the potential social patterning of biological mechanisms in a diverse sample in&#xD;
      young adulthood.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">December 1, 2011</start_date>
  <completion_date type="Actual">December 1, 2012</completion_date>
  <primary_completion_date type="Actual">December 1, 2012</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Response rate</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Percentage response rates - overall, per item/physical measure</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Interview duration</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Mean length of time for interview</description>
  </primary_outcome>
  <primary_outcome>
    <measure>physical measures duration</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Mean length of time for physical/biological measures</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Weight</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Body weight, kg</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Height</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Height, cm</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>waist circumference</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Waist circumference, cm</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>blood pressure</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>systolic and diastolic blood pressure, mmHg</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Body fat</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>body fat measured by bioelectrical impedence, %</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>HbA1c</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Glycated haemoglobin, %</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Total cholesterol</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Serum total cholesterol, mmol/l</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>HDL-cholesterol</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Serum high-density-lipoprotein cholesterol, mmol/l</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Energy intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Dietary energy intake, kcal/day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Fat intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Dietary fat intake, % of total energy intake</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Saturated fat intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Dietary saturated fat intake, % of total energy intake</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Carbohydrate intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Dietary carbohydrate intake, % of total energy intake</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Sugar intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Dietary sugar intake, g/day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Fibre intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Dietary fibre intake, g/day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Sodium intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Dietary sodium intake, mg/day</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Skipping breakfast</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Questionnaire measure of regularity of skipping breakfast</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Fruit intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Questionnaire measure of regularity of fruit consumption</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Vegetable intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Questionnaire measure of regularity of vegetable consumption</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Fizzy drink intake</measure>
    <time_frame>Through study completion, on average 10 years</time_frame>
    <description>Questionnaire measure of regularity of fizzy drink consumption</description>
  </secondary_outcome>
  <enrollment type="Actual">6643</enrollment>
  <condition>Cardiovascular Risk Factor</condition>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>No intervention</intervention_name>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        School children, aged 11-13 years, representing the main UK ethnic groups (White-European,&#xD;
        Black African, Black Caribbean, Indian, Pakistani/Bangladeshi, Other, mainly mixed race).&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  provision of informed consent&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  none&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>11 Years</minimum_age>
    <maximum_age>13 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Seeromanie Harding, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>King's College London</affiliation>
  </overall_official>
  <results_reference>
    <citation>Harding S, Whitrow M, Maynard MJ, Teyhan A. Cohort profile: The DASH (Determinants of Adolescent Social well-being and Health) Study, an ethnically diverse cohort. Int J Epidemiol. 2007 Jun;36(3):512-7. doi: 10.1093/ije/dym094. Epub 2007 Jul 30. No abstract available.</citation>
    <PMID>17664225</PMID>
  </results_reference>
  <results_reference>
    <citation>Lu Y, Sooky L, Silva MJ, Molaodi OR, Karamanos A, Cruickshank JK, Harding S. Longitudinal study of the influence of lung function on vascular health from adolescence to early adulthood in a British multiethnic cohort. J Hypertens. 2017 Nov;35(11):2185-2191. doi: 10.1097/HJH.0000000000001455.</citation>
    <PMID>28661960</PMID>
  </results_reference>
  <results_reference>
    <citation>Harding S, Silva MJ, Molaodi OR, Enayat ZE, Cassidy A, Karamanos A, Read UM, Cruickshank JK. Longitudinal study of cardiometabolic risk from early adolescence to early adulthood in an ethnically diverse cohort. BMJ Open. 2016 Dec 14;6(12):e013221. doi: 10.1136/bmjopen-2016-013221.</citation>
    <PMID>27979836</PMID>
  </results_reference>
  <results_reference>
    <citation>Faconti L, Silva MJ, Molaodi OR, Enayat ZE, Cassidy A, Karamanos A, Nanino E, Read UM, Dall P, Stansfield B, Harding S, Cruickshank KJ. Can arterial wave augmentation in young adults help account for variability of cardiovascular risk in different British ethnic groups? J Hypertens. 2016 Nov;34(11):2220-6. doi: 10.1097/HJH.0000000000001066.</citation>
    <PMID>27490950</PMID>
  </results_reference>
  <results_reference>
    <citation>Harding S, Read UM, Molaodi OR, Cassidy A, Maynard MJ, Lenguerrand E, Astell-Burt T, Teyhan A, Whitrow M, Enayat ZE. The Determinants of young Adult Social well-being and Health (DASH) study: diversity, psychosocial determinants and health. Soc Psychiatry Psychiatr Epidemiol. 2015 Aug;50(8):1173-88. doi: 10.1007/s00127-015-1047-9. Epub 2015 Apr 11.</citation>
    <PMID>25861790</PMID>
  </results_reference>
  <results_reference>
    <citation>Whitrow MJ, Harding S. Asthma in Black African, Black Caribbean and South Asian adolescents in the MRC DASH study: a cross sectional analysis. BMC Pediatr. 2010 Mar 25;10:18. doi: 10.1186/1471-2431-10-18.</citation>
    <PMID>20334698</PMID>
  </results_reference>
  <results_reference>
    <citation>Harding S, Teyhan A, Maynard MJ, Cruickshank JK. Ethnic differences in overweight and obesity in early adolescence in the MRC DASH study: the role of adolescent and parental lifestyle. Int J Epidemiol. 2008 Feb;37(1):162-72. doi: 10.1093/ije/dym252. Epub 2008 Jan 19.</citation>
    <PMID>18204089</PMID>
  </results_reference>
  <results_reference>
    <citation>Maynard MJ, Harding S, Minnis H. Psychological well-being in Black Caribbean, Black African, and White adolescents in the UK Medical Research Council DASH study. Soc Psychiatry Psychiatr Epidemiol. 2007 Sep;42(9):759-69. doi: 10.1007/s00127-007-0227-7. Epub 2007 Jun 29.</citation>
    <PMID>17603738</PMID>
  </results_reference>
  <results_reference>
    <citation>Harding S, Maynard MJ, Cruickshank K, Teyhan A. Overweight, obesity and high blood pressure in an ethnically diverse sample of adolescents in Britain: the Medical Research Council DASH study. Int J Obes (Lond). 2008 Jan;32(1):82-90. doi: 10.1038/sj.ijo.0803662. Epub 2007 Jun 19.</citation>
    <PMID>17579635</PMID>
  </results_reference>
  <results_reference>
    <citation>Harding S, Maynard M, Cruickshank JK, Gray L. Anthropometry and blood pressure differences in black Caribbean, African, South Asian and white adolescents: the MRC DASH study. J Hypertens. 2006 Aug;24(8):1507-14. doi: 10.1097/01.hjh.0000239285.20315.4d.</citation>
    <PMID>16877952</PMID>
  </results_reference>
  <verification_date>September 2017</verification_date>
  <study_first_submitted>September 8, 2017</study_first_submitted>
  <study_first_submitted_qc>September 12, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">September 14, 2017</study_first_posted>
  <last_update_submitted>September 12, 2017</last_update_submitted>
  <last_update_submitted_qc>September 12, 2017</last_update_submitted_qc>
  <last_update_posted type="Actual">September 14, 2017</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Ethnicity</keyword>
  <keyword>adolescents</keyword>
  <keyword>cohort</keyword>
  <keyword>longitudinal</keyword>
  <keyword>health inequalities</keyword>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>The DASH data are available to researchers via a data request to the MRC Social and Public Health Science Unit. Applications and the data sharing policy for DASH can be found at http://dash.sphsu.mrc.&#xD;
ac.uk/DASH_dsp_v1_November-2012_draft.pdf. It reflects the MRC guidance on data sharing with the aim of making the data as widely and freely available as possible while safeguarding the privacy of participants, protecting confidential data, and maintaining the reputation of the study. All potential collaborators work with a link person, an experienced DASH researcher-to support their access to and analysis of the data. The variable-level metadata is available from the study team and also via the MRC Data Gateway.</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_info_type>Informed Consent Form (ICF)</ipd_info_type>
    <ipd_time_frame>Data available from 2014 for 10 years.</ipd_time_frame>
    <ipd_url>http://dash.sphsu.mrc.ac.uk</ipd_url>
  </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/NCT03283332
org study id: 05/MRE10/43
nct id: NCT03283332
lead sponsor: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Black and ethnic minority groups living in the UK experience high rates of chronic diseases
      such as diabetes, hypertension and heart disease, general morbidity and poor mental health.
      The cause of these excess rates is unknown but obesity, smoking, diet and deprivation are
      important contributing factors. There is also global evidence of the association of these
      diseases in adulthood with health and deprivation in early life and childhood. Persisting
      social deprivation over the lifecourse is disproportionately borne by some ethnic minorities
      (Harding and Balarajan 2001) but the impact on the health of their children is virtually
      unknown. Least is known about the health of Black Caribbean young people. It is important to
      examine risk factor differences by social predictors within the ethnic minority groups as
      well as between them. The DASH Study started as a school-based cohort study of adolescents
      from the main ethnic groups (White British, Black Caribbean, Black African, Indian, Pakistani
      and Bangladeshi) in 10 London boroughs. Wave 1 took place in 2002/03 (MREC Ref:
      MREC/2/10/12), when participants were aged 11-13 years (school years 7 and 8). Wave 2 took
      place in 2005/06 (MREC Ref: 05/MRE10/43) when they were 14-16 years (school years 9 and 10).
      Wave 3 took place in 2010/2011, when participants were aged 19-21 years and involved a postal
      follow-up complemented by telephone interview and on-line questionnaires. The current
      proposal is for a feasibility study, using a small sample of the DASH cohort, to inform the
      design of the next full face-to-face follow-up. DASH will be the first large scale UK
      longitudinal cohort of ethnic minority youths with both social and biological measures from
      childhood to early adulthood. It will allow detailed examination of ethnic differences in the
      social patterning of biological mechanisms and pre-clinical disease in young adulthood.
Background:

      Black and ethnic minority groups living in the UK experience high rates of chronic diseases
      such as diabetes, hypertension and heart disease, general morbidity and poor mental health.
      The cause of these excess rates is unknown but obesity, smoking, diet and deprivation are
      important contributing factors. There is also global evidence of the association of these
      diseases in adulthood with health and deprivation in early life and childhood. Persisting
      social deprivation over the lifecourse is disproportionately borne by some ethnic minorities
      (Harding and Balarajan 2001) but the impact on the health of their children is virtually
      unknown. Least is known about the health of Black Caribbean young people. It is important to
      examine risk factor differences by social predictors within the ethnic minority groups as
      well as between them. The DASH Study started as a school-based cohort study of adolescents
      from the main ethnic groups (White British, Black Caribbean, Black African, Indian, Pakistani
      and Bangladeshi) in 10 London boroughs. Wave 1 took place in 2002/03 (MREC Ref:
      MREC/2/10/12), when participants were aged 11-13 years (school years 7 and 8). Wave 2 took
      place in 2005/06 (MREC Ref: 05/MRE10/43) when they were 14-16 years (school years 9 and 10).
      Wave 3 took place in 2010/2011, when participants were aged 19-21 years and involved a postal
      follow-up complemented by telephone interview and on-line questionnaires. The current
      proposal is for a feasibility study, using a small sample of the DASH cohort, to inform the
      design of the next full face-to-face follow-up. DASH will be the first large scale UK
      longitudinal cohort of ethnic minority youths with both social and biological measures from
      childhood to early adulthood. It will allow detailed examination of ethnic differences in the
      social patterning of biological mechanisms and pre-clinical disease in young adulthood.

      Aims:

      (i) To conduct a feasibility study to establish the best methods for data collection,
      including the collection of physical and biological measurements, for subsequent face to face
      follow-up of the entire cohort.

      (ii) To generate a proposal for subsequent follow-up of the entire cohort for submission to
      MRC, dependent on the findings of the postal and telephone surveys and proposed feasibility
      study.

      Objectives:

      I. What are the advantages and disadvantages of conducting the study in the two settings - GP
      surgeries and homes?

        1. Do participants' response rates vary by setting?

        2. What are the challenges faced by the nurses in clinics and home visits?

        3. Will the quality of data collected (e.g. extent of missing data) vary by setting?

        4. Will the delivery of blood samples to the laboratory be reasonably straight forward in
           each setting? II. What percentage of participants will agree to undertake bio-marker
           measures? III. Are mental health measures for this age group, typically used with White
           European populations, culturally appropriate? IV. How will DASH participants' view
           feedback on their medical results (e.g. blood pressure, weight, blood lipids)? V. Were
           participants satisfied with the different components of the survey process - contact,
           consent, data collection? VI. What is the estimated length of time and the resources
           required for subsequent full follow-up of DASH study members?

      Outcome measures:

      These will be examined by setting (home visit, GP surgery) using a mixture of quantitative
      and qualitative methods and are as follows:

      I. Percentage response rates - overall, per item/physical measure; II. Percentage consistency
      of answers to questionnaire items; III. Percentage physical measures within expected range
      e.g. spirometric measures; IV. Mean length of time for interview; V. Mean length of time for
      taking physical/biological measures; VI. Qualitative appraisal of cultural appropriateness of
      mental health measures and of respondents' satisfaction with survey processes.

      Sample At the recent telephone survey, respondents were asked if they would be willing to
      take part in a small feasibility study to prepare for a later full face to face follow-up.
      Almost all agreed and of those, a sample of 300 (40-50 in each of the main ethnic groups-
      White British, Black Caribbean, Black African, Pakistani, Bangladeshi, Indian) will be
      invited to complete a questionnaire, and have physical and physiological measures taken.
      Interviews will be conducted in respondents' own homes or GP surgeries dependent on the
      preference of the respondent. As this is a feasibility study, the sample size has been chosen
      pragmatically to give a reasonable spread, with equal gender representation across the 10
      London boroughs that the whole sample was in at wave 2.

      Specially trained nurses will conduct the survey in homes or General Practitioners'
      surgeries, supervised by a nurse manager in the General Practice Research Framework. Nurses
      will be attached either to the General Research Practice Framework or the Primary Care
      Research Network.

      Main Questionnaire The content reflects mainly questions that were asked in previous waves
      (general health; health behaviours; psychological well-being; SEC; social support; and
      relationship with parents). New items include parenthood; age appropriate mental health
      measures; own education, economic activity and occupation; job strain; caring; 'romantic'
      relationships; positive and negative emotions; views on their parents being invited to
      participate in DASH in order to examine generational influences. The investigators will
      explore two methods of delivery of the questionnaires - self complete questionnaires done
      prior to visit and computer assisted interviews. If the questionnaire is not completed by the
      time of the interview, respondents will be asked if they would like to complete a computer
      assisted interview. Completion of the questionnaire is expected to take about 40 minutes.

      Physical/physiological measures As in waves 1/and 2, height, weight, arm, waist and hip
      circumference, lung function, blood pressure will be measured.

      New measures include:

      (i)Hand to foot bio-impedance (ii) Bio-markers - HbA1c, total cholesterol, HDL-cholesterol
      (iii) Dietary assessment - 24 hour recall interviews Qualitative assessment - focus groups
      and semi-structured interviews. For the new mental health/cognitive measures, the
      investigators will conduct focus group vignette assessment, based on explanatory model and
      illness perception theories. This will be carried out in a small sub-sample (6 participants
      per ethnic group and allowing for 2 gender-specific groups; n=48). Analysis of these data
      will focus on narratives about the signs and symptoms of different aspects of mental health
      in the different ethnic groups. These data will provide valuable insights about the
      appropriateness of measures, usually validated with European populations, for ethnic minority
      groups.

      A research scientist will conduct semi-structured interviews with respondents to obtain
      feedback on the process of follow-up - what worked well, how best to improve the process,
      what was un/acceptable etc. The investigators will also enquire about the usefulness of
      feedback of results. A similar evaluation will take place with the nurses with the aim of
      identifying best practice in clinics and homes.

      Data analysis Descriptive statistics will be used to look at the general distributions and
      quality of the data collected. Outcomes measured as rates will be examined by data collection
      setting (GP surgeries vs. home visits), ethnic group and socio-demographic characteristics
      using standard comparisons technique such as Chi-square test or logistic regression. Mean
      length of time and any continuous outcomes will be compared using linear regression. In
      addition, although the sample size of each ethnic group is small, the total sample will allow
      analyses of the potential social patterning of biological mechanisms in a diverse sample in
      young adulthood.
observational model: Cohort
time perspective: Prospective
measure: Response rate
time frame: Through study completion, on average 10 years
description: Percentage response rates - overall, per item/physical measure
measure: Interview duration
time frame: Through study completion, on average 10 years
description: Mean length of time for interview
measure: physical measures duration
time frame: Through study completion, on average 10 years
description: Mean length of time for physical/biological measures
measure: Weight
time frame: Through study completion, on average 10 years
description: Body weight, kg
measure: Height
time frame: Through study completion, on average 10 years
description: Height, cm
measure: waist circumference
time frame: Through study completion, on average 10 years
description: Waist circumference, cm
measure: blood pressure
time frame: Through study completion, on average 10 years
description: systolic and diastolic blood pressure, mmHg
measure: Body fat
time frame: Through study completion, on average 10 years
description: body fat measured by bioelectrical impedence, %
measure: HbA1c
time frame: Through study completion, on average 10 years
description: Glycated haemoglobin, %
measure: Total cholesterol
time frame: Through study completion, on average 10 years
description: Serum total cholesterol, mmol/l
measure: HDL-cholesterol
time frame: Through study completion, on average 10 years
description: Serum high-density-lipoprotein cholesterol, mmol/l
measure: Energy intake
time frame: Through study completion, on average 10 years
description: Dietary energy intake, kcal/day
measure: Fat intake
time frame: Through study completion, on average 10 years
description: Dietary fat intake, % of total energy intake
measure: Saturated fat intake
time frame: Through study completion, on average 10 years
description: Dietary saturated fat intake, % of total energy intake
measure: Carbohydrate intake
time frame: Through study completion, on average 10 years
description: Dietary carbohydrate intake, % of total energy intake
measure: Sugar intake
time frame: Through study completion, on average 10 years
description: Dietary sugar intake, g/day
measure: Fibre intake
time frame: Through study completion, on average 10 years
description: Dietary fibre intake, g/day
measure: Sodium intake
time frame: Through study completion, on average 10 years
description: Dietary sodium intake, mg/day
measure: Skipping breakfast
time frame: Through study completion, on average 10 years
description: Questionnaire measure of regularity of skipping breakfast
measure: Fruit intake
time frame: Through study completion, on average 10 years
description: Questionnaire measure of regularity of fruit consumption
measure: Vegetable intake
time frame: Through study completion, on average 10 years
description: Questionnaire measure of regularity of vegetable consumption
measure: Fizzy drink intake
time frame: Through study completion, on average 10 years
description: Questionnaire measure of regularity of fizzy drink consumption
intervention type: Other
intervention name: No intervention
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 11 Years
maximum age: 13 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Seeromanie Harding, PhD
role: Principal Investigator
affiliation: King's College London
citation: Harding S, Whitrow M, Maynard MJ, Teyhan A. Cohort profile: The DASH (Determinants of Adolescent Social well-being and Health) Study, an ethnically diverse cohort. Int J Epidemiol. 2007 Jun;36(3):512-7. doi: 10.1093/ije/dym094. Epub 2007 Jul 30. No abstract available.
PMID: 17664225
citation: Lu Y, Sooky L, Silva MJ, Molaodi OR, Karamanos A, Cruickshank JK, Harding S. Longitudinal study of the influence of lung function on vascular health from adolescence to early adulthood in a British multiethnic cohort. J Hypertens. 2017 Nov;35(11):2185-2191. doi: 10.1097/HJH.0000000000001455.
PMID: 28661960
citation: Harding S, Silva MJ, Molaodi OR, Enayat ZE, Cassidy A, Karamanos A, Read UM, Cruickshank JK. Longitudinal study of cardiometabolic risk from early adolescence to early adulthood in an ethnically diverse cohort. BMJ Open. 2016 Dec 14;6(12):e013221. doi: 10.1136/bmjopen-2016-013221.
PMID: 27979836
citation: Faconti L, Silva MJ, Molaodi OR, Enayat ZE, Cassidy A, Karamanos A, Nanino E, Read UM, Dall P, Stansfield B, Harding S, Cruickshank KJ. Can arterial wave augmentation in young adults help account for variability of cardiovascular risk in different British ethnic groups? J Hypertens. 2016 Nov;34(11):2220-6. doi: 10.1097/HJH.0000000000001066.
PMID: 27490950
citation: Harding S, Read UM, Molaodi OR, Cassidy A, Maynard MJ, Lenguerrand E, Astell-Burt T, Teyhan A, Whitrow M, Enayat ZE. The Determinants of young Adult Social well-being and Health (DASH) study: diversity, psychosocial determinants and health. Soc Psychiatry Psychiatr Epidemiol. 2015 Aug;50(8):1173-88. doi: 10.1007/s00127-015-1047-9. Epub 2015 Apr 11.
PMID: 25861790
citation: Whitrow MJ, Harding S. Asthma in Black African, Black Caribbean and South Asian adolescents in the MRC DASH study: a cross sectional analysis. BMC Pediatr. 2010 Mar 25;10:18. doi: 10.1186/1471-2431-10-18.
PMID: 20334698
citation: Harding S, Teyhan A, Maynard MJ, Cruickshank JK. Ethnic differences in overweight and obesity in early adolescence in the MRC DASH study: the role of adolescent and parental lifestyle. Int J Epidemiol. 2008 Feb;37(1):162-72. doi: 10.1093/ije/dym252. Epub 2008 Jan 19.
PMID: 18204089
citation: Maynard MJ, Harding S, Minnis H. Psychological well-being in Black Caribbean, Black African, and White adolescents in the UK Medical Research Council DASH study. Soc Psychiatry Psychiatr Epidemiol. 2007 Sep;42(9):759-69. doi: 10.1007/s00127-007-0227-7. Epub 2007 Jun 29.
PMID: 17603738
citation: Harding S, Maynard MJ, Cruickshank K, Teyhan A. Overweight, obesity and high blood pressure in an ethnically diverse sample of adolescents in Britain: the Medical Research Council DASH study. Int J Obes (Lond). 2008 Jan;32(1):82-90. doi: 10.1038/sj.ijo.0803662. Epub 2007 Jun 19.
PMID: 17579635
citation: Harding S, Maynard M, Cruickshank JK, Gray L. Anthropometry and blood pressure differences in black Caribbean, African, South Asian and white adolescents: the MRC DASH study. J Hypertens. 2006 Aug;24(8):1507-14. doi: 10.1097/01.hjh.0000239285.20315.4d.
PMID: 16877952
responsible party type: Sponsor
sharing ipd: Yes
ipd description: The DASH data are available to researchers via a data request to the MRC Social and Public Health Science Unit. Applications and the data sharing policy for DASH can be found at http://dash.sphsu.mrc.
ac.uk/DASH_dsp_v1_November-2012_draft.pdf. It reflects the MRC guidance on data sharing with the aim of making the data as widely and freely available as possible while safeguarding the privacy of participants, protecting confidential data, and maintaining the reputation of the study. All potential collaborators work with a link person, an experienced DASH researcher-to support their access to and analysis of the data. The variable-level metadata is available from the study team and also via the MRC Data Gateway.
ipd info type: Study Protocol
ipd info type: Informed Consent Form (ICF)
ipd time frame: Data available from 2014 for 10 years.
ipd url: http://dash.sphsu.mrc.ac.uk