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          zaf-ana-wits-hiva40-2010-2019-v1
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    <citation>
      <titlStmt>
        <titl>
          HIV After 40 2010-2019
        </titl>
        <altTitl>
          HIVA40 2010-2019
        </altTitl>
        <IDNo>
          zaf-ana-wits-hiva40-2010-2019-v1
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      </titlStmt>
      <rspStmt>
        <AuthEnty affiliation="American University">
          Nicole Angotti
        </AuthEnty>
        <AuthEnty affiliation="Ohio State University">
          Samuel Clark
        </AuthEnty>
        <AuthEnty affiliation="University of the Witwatersrand">
          F. Xavier Gómez-Olivé
        </AuthEnty>
        <AuthEnty affiliation="Australian National University">
          <![CDATA[Brian Houle    ]]>
        </AuthEnty>
        <AuthEnty affiliation="University of the Witwatersrand">
          Chodziwadziwa Kabudula Whiteson
        </AuthEnty>
        <AuthEnty affiliation="University of Colorado Boulder">
          Jane Menken
        </AuthEnty>
        <AuthEnty affiliation="Princeton University">
          Sanyu Mojola
        </AuthEnty>
        <AuthEnty affiliation="University of Missouri ">
          Enid Schatz
        </AuthEnty>
        <AuthEnty affiliation="University of Oxford">
          Andrea Tilstra
        </AuthEnty>
        <AuthEnty affiliation="University of Colorado Boulder">
          Jill Williams
        </AuthEnty>
        <AuthEnty affiliation="University of Maryland, College Park">
          Vusi Dlamini
        </AuthEnty>
        <AuthEnty affiliation="University of Michigan">
          Erin Ice
        </AuthEnty>
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          Wellcome Trust
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        <fundAg role="Funding Agency">
          University of Colorado Boulder Innovative Seed Grant
        </fundAg>
        <fundAg abbr="WFHF" role="Funding Agency">
          William and Flora Hewlett Foundation
        </fundAg>
        <fundAg role="Funding Agency">
          SPARC Fellowship, Wits
        </fundAg>
        <grantNo agency="NIA" role="Funding Agency">
          AG049634/AG032112-05
        </grantNo>
        <grantNo agency="Wellcome Trust" role="Funding Agency">
          058893/Z/99/A, 069683/Z/02/Z/085477/Z/08/Z
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        <grantNo agency="University of Colorado Boulder Innovative Seed Grant" role="Funding Agency">
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        <grantNo agency="WFHF" role="Funding Agency">
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        <grantNo agency="SPARC Fellowship, Wits" role="Funding Agency">
          058893/Z/99/A, 069683/Z/02/Z/085477/Z/08/Z
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      <distStmt>
        <contact affiliation="University of Cape Town" URI="www.support.data1st.org" email="support@data1st.org">
          DataFirst Support
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      </distStmt>
      <serStmt>
        <serName>
          Demographic and Health Surveillance System
        </serName>
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      <verStmt>
        <version date="2022">
          v1. Edited, anonymised data for public distribution
        </version>
      </verStmt>
    </citation>
    <stdyInfo>
      <subject>
        <keyword>
          HIV
        </keyword>
        <keyword>
          Non-Communicable Diseases
        </keyword>
        <keyword>
          Behavioral Risk Assessment
        </keyword>
        <keyword>
          Chronic Disease Risk Factors
        </keyword>
      </subject>
      <abstract>
        <![CDATA[The HIVafter40 data file is the basis for the research publication:

Houle B., Kabudula C.W., Tilstra A.M., Mojola S.A., Schatz E., Clark S.J., Angotti N., Gómez-Olivé F.X., and Menken J. 2022. Twin epidemics: the effects of HIV and systolic blood pressure on mortality risk in rural South Africa, 2010-2019. BMC Public Health 22 (1):387. DOI: 10.1186/s12889-022-12791-z. PMID: 35209881; PMCID: PMC8866551.

The HIVafter40_Twin_Epidemics_HIV_NCD data was created as part of the HIVafter40 project, the successor to the Ha Nakekela Project, both nested within the Agincourt Health and socio-Demographic System (AHDSS) located in Northeastern South Africa.The projects use mixed methods to measure prevalence and incidence of HIV and NCDs, investigate health and sexual behaviours, and study how people have coped with the abrupt introduction of a new and deadly health threat and efforts to prevent and ameliorate it. The overall goal of HIVafter40 is to examine life course and contextual variation in HIV risk and protective behaviors and mortality in a rural sub-Saharan African population.
The AHDSS has, since 1992, collected an annual census from households in a defined geographic area of Mpumalanga Province. The 2009 census served as the sampling frame for the 2011 Ha Nakekela Project. The AHDSS provides rapid measures of vital statistics and is the basis of a wide range of more detailed studies. As of June 2018, the study site consisted of 31 villages with a population of 116,549 people, living in 22,721 households. Further information is available at <https://www.agincourt.co.za/> and specifically for census data collection, at <https://www.agincourt.co.za/?page_id=1805>

The Ha Nakekela project undertook two data collection efforts:
1. The Ha Nakekela Survey
This survey  is based on an age/sex stratified sample of respondents in the 2009 AHDSS Census. Carried out in 2010-11, the cross-sectional survey included 5,080 respondents, of whom 2,080 are aged 40 - 93. It has 3 parts:
Behavioral Risk Assessment (based on BERIS Sexual Behavior Questionnaire)
Chronic Disease Risk Factor Surveillance (based on STEPS Health Risk Questionnaire)
HIV and Non-Communicable Disease (NCD) biometric data
2. The Izindaba za Badala (Matters that Concern Older People) 
This Study (IZB) is nested within the Ha Nakekela Survey. It consisted of three related interview studies carried out in 2013:
 IZB Life History Interviews: 60 life history interviews with people with and without HIV aged 40-84 who participated in the Ha Nakekela Survey
IZB Community Focus Group Interviews: 9 community focus group interviews with a total of 77 respondents 
IZB Key informant Interviews: 9 health workers interviews in 3 local health clinics

The HIVafter40 project added two follow-up data files:
a. AHDSS_Ha_Nakekela_HIV_Hyp_Sample.dta 
This data file contains information on the Ha Nakekela sample in which individuals were linked to their location/outcome reports in successive AHDSS censuses through 2020. This dataset permits examination of mortality in the nine years subsequent to participation in the Ha Nakekela Survey. HIVafter40_Twin_Epidemics_HIV_NCD.dta is a subset of this dataset.
b. Izindaba za Badala Round 2
IZB Life History Interviews: 25 in-depth follow-up interviews in 2018 
IZB Community Focus Group Interviews: 10 community focus group interviews with a total of 84 participants in 2018 
IZB Key informant Interviews (cancelled due to the COVID-19 epidemic):10 community focus group interviews with a total of 84 participants planned for 2020. 

The website https://hivafter40.princeton.edu/ is regularly updated and contains the most complete information on the projects.]]>
      </abstract>
      <sumDscr>
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        <collDate date="2019" event="end"/>
        <nation>
          South Africa
        </nation>
        <geogCover>
          The study was conducted in the Agincourt Health and socio-Demographic System (AHDSS) site located in Mpumulanga Province, Northeastern South Africa.
        </geogCover>
        <geogUnit>
          The data is at the level of Village.
        </geogUnit>
        <anlyUnit>
          Individuals
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        <dataKind>
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      <notes>
        The projects measured prevalence and incidence of HIV and NCDs, and investigated health and sexual behaviours, as well as how people have coped with the abrupt introduction of a new and deadly health threat and efforts to prevent and ameliorate it. The Ha Nakekela Survey collected Behavioral Risk Assessment data (based on BERIS Sexual Behavior Questionnaire), Chronic Disease Risk Factors (based on STEPS Health Risk Questionnaire), and biometric data on HIV and Non-Communicable Diseases (NCDs)
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    <method>
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          Face-to-face
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        <resInstru>
          <![CDATA[Data was collected using an Interview Schedule for individuals, one for Key Informants, and one for Focus Groups. The BERIS Sexual Behavior Questionnaire and the World Health Organisation's STEPS Health Risk Questionnaire informed the data collection. 
Data collection instruments are provided with the data files and can also be downloaded from https://hivafter40.princeton.edu/study-instruments]]>
        </resInstru>
        <sources/>
        <collSitu>
          The projects used mixed methods which are discussed in the supporting documentation. Data was collected face-to-face with questionnaires and in focus groups.
        </collSitu>
        <actMin>
          <![CDATA[Oversight and Ethics Approval

HIVafter40/Ha Nakekela received IRB approvals from the University of Colorado Boulder, the University of Michigan, Princeton University, the University of the Witwatersrand Human Research Ethics Committee, and the Department of Health, Mpumalanga Provincial Government, South Africa.]]>
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        <contact affiliation="University of Cape Town" URI="support.data1st.org" email="support@data1st.org">
          DataFirst
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        <citReq>
          <![CDATA[Houle, B. et al. HIV After 40 2010-2019 [dataset]. Version 1. Agincourt: HIVafter40 and Ha Nakekela (We Care) Projects [producers], 2022. Cape Town: DataFirst [distributor], 2022. DOI:  https://doi.org/10.25828/vr0p-ch08]]>
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      </useStmt>
    </dataAccs>
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      <![CDATA[Individuals_01.dta Prepping original files for merging sexbehav_clust.do
Individuals_01.dta Prepping original files for merging concurrent.do
merge individuals and STEPS.dta \ clean variables \ cluster.do
stepshiv.dta \ merge HIV \ cluster.do
merge hdss.dta \ merge hdss \ cluster.do
steps-ind-hiv-hdss01 \ merge hdss \ cluster.do
steps-ind-hiv-hdss02 \ additional coding \ cluster.do
steps-ind-hiv-hdss03.dta \ merged clustering \ cluster.do
steps-ind-hiv-hdss03.dta \ merged clustering \ cluster.do
steps-ind-hiv-hdss03.dta \ merged clustering \ cluster.do
SampleCharacteristics_01.dta Prepping original files for merging concurrent.do
STEPS_01.dta Prepping original files for merging concurrent.do
BERIS_01.dta Prepping original files for merging concurrent.do
individuals-wt-samp-steps-beris_merge01.dta Merging all individual-level files Concurrent.do
SampleCharacteristics_01.dta Prepping original files for merging sexbehav_clust.do
STEPS_01.dta Prepping original files for merging sexbehav_clust.do
BERIS_01.dta Prepping original files for merging sexbehav_clust.do
BERISPartners_01.dta Prepping original files for merging sexbehav_clust.do
berispartners_partner1only.dta Just the first partner in beris partners sexbehav_clust.do
berispartners_partnersall.dta Summaries of all partners in beris partners sexbehav_clust.do
individuals-wt-samp-steps-beris_merge01.dta Merging all individual-level files sexbehav_clust.do
clusters_01.dta Data coding for LCA sexbehav_clust.do]]>
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      </sumStat>
      <sumStat type="invd">
        9456
      </sumStat>
      <catgry>
        <catValu>
          0
        </catValu>
        <catStat type="freq">
          18693
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          1
        </catValu>
        <catStat type="freq">
          4342
        </catStat>
      </catgry>
      <catgry missing="Y">
        <catValu>
          Sysmiss
        </catValu>
        <catStat type="freq">
          9456
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V36" name="diastolic2" files="F4" dcml="0" intrvl="contin">
      <location width="9"/>
      <labl>
        Mean diastolic mmHg
      </labl>
      <valrng>
        <range UNITS="REAL" min="44" max="170.5"/>
      </valrng>
      <sumStat type="vald">
        22759
      </sumStat>
      <sumStat type="invd">
        9732
      </sumStat>
      <sumStat type="min">
        44
      </sumStat>
      <sumStat type="max">
        170.5
      </sumStat>
      <sumStat type="mean">
        88.624
      </sumStat>
      <sumStat type="stdev">
        15.562
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V37" name="hyp_simple" files="F4" dcml="0" intrvl="discrete">
      <location width="33"/>
      <labl>
        Normotensive/Hypertensive
      </labl>
      <valrng>
        <range UNITS="REAL" min="0" max="1"/>
      </valrng>
      <sumStat type="vald">
        17750
      </sumStat>
      <sumStat type="invd">
        14741
      </sumStat>
      <catgry>
        <catValu>
          0
        </catValu>
        <labl>
          Normotensive
        </labl>
        <catStat type="freq">
          12091
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          Hypertensive: reported or treated
        </labl>
        <catStat type="freq">
          5659
        </catStat>
      </catgry>
      <catgry missing="Y">
        <catValu>
          Sysmiss
        </catValu>
        <catStat type="freq">
          14741
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V38" name="sbp_cat2" files="F4" dcml="0" intrvl="discrete">
      <location width="9"/>
      <labl>
        Systolic cutoffs 120/140/160
      </labl>
      <valrng>
        <range UNITS="REAL" min="1" max="4"/>
      </valrng>
      <sumStat type="vald">
        22491
      </sumStat>
      <sumStat type="invd">
        10000
      </sumStat>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          &lt;120
        </labl>
        <catStat type="freq">
          6164
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <labl>
          120-139
        </labl>
        <catStat type="freq">
          8506
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          3
        </catValu>
        <labl>
          140-159
        </labl>
        <catStat type="freq">
          5066
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          4
        </catValu>
        <labl>
          160+
        </labl>
        <catStat type="freq">
          2755
        </catStat>
      </catgry>
      <catgry missing="Y">
        <catValu>
          Sysmiss
        </catValu>
        <catStat type="freq">
          10000
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V39" name="hiv_positive" files="F4" dcml="0" intrvl="discrete">
      <location width="9"/>
      <labl/>
      <valrng>
        <range UNITS="REAL" min="0" max="1"/>
      </valrng>
      <sumStat type="vald">
        21548
      </sumStat>
      <sumStat type="invd">
        10943
      </sumStat>
      <catgry>
        <catValu>
          0
        </catValu>
        <labl>
          Negative
        </labl>
        <catStat type="freq">
          16270
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          Positive
        </labl>
        <catStat type="freq">
          5278
        </catStat>
      </catgry>
      <catgry missing="Y">
        <catValu>
          Sysmiss
        </catValu>
        <catStat type="freq">
          10943
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V40" name="vl_simple_400" files="F4" dcml="0" intrvl="discrete">
      <location width="16"/>
      <labl>
        Viral load: Neg/Suppressed&lt;=400/Unsuppressed&gt;400
      </labl>
      <valrng>
        <range UNITS="REAL" min="0" max="2"/>
      </valrng>
      <sumStat type="vald">
        21430
      </sumStat>
      <sumStat type="invd">
        11061
      </sumStat>
      <catgry>
        <catValu>
          0
        </catValu>
        <labl>
          HIV Negative
        </labl>
        <catStat type="freq">
          16270
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          Suppressed&lt;=400
        </labl>
        <catStat type="freq">
          2200
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <labl>
          Unsuppressed&gt;400
        </labl>
        <catStat type="freq">
          2960
        </catStat>
      </catgry>
      <catgry missing="Y">
        <catValu>
          Sysmiss
        </catValu>
        <catStat type="freq">
          11061
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V41" name="vl_simple_2013" files="F4" dcml="0" intrvl="discrete">
      <location width="17"/>
      <labl>
        2013 Viral load: Neg/Suppressed&lt;=1000/Unsuppressed&gt;1000
      </labl>
      <valrng>
        <range UNITS="REAL" min="0" max="2"/>
      </valrng>
      <sumStat type="vald">
        21430
      </sumStat>
      <sumStat type="invd">
        11061
      </sumStat>
      <catgry>
        <catValu>
          0
        </catValu>
        <labl>
          HIV Negative
        </labl>
        <catStat type="freq">
          16270
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          Suppressed&lt;=1000
        </labl>
        <catStat type="freq">
          2642
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <labl>
          Unsuppressed&gt;1000
        </labl>
        <catStat type="freq">
          2518
        </catStat>
      </catgry>
      <catgry missing="Y">
        <catValu>
          Sysmiss
        </catValu>
        <catStat type="freq">
          11061
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V42" name="t0" files="F4" dcml="0" intrvl="contin">
      <location width="10"/>
      <labl>
        analysis time when record begins
      </labl>
      <valrng>
        <range UNITS="REAL" min="31.2388774811773" max="103.137577002053"/>
      </valrng>
      <sumStat type="vald">
        32491
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <sumStat type="min">
        31.239
      </sumStat>
      <sumStat type="max">
        103.138
      </sumStat>
      <sumStat type="mean">
        53.486
      </sumStat>
      <sumStat type="stdev">
        14.067
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V43" name="m" files="F4" dcml="0" intrvl="discrete">
      <location width="9"/>
      <labl/>
      <valrng>
        <range UNITS="REAL" min="1" max="10"/>
      </valrng>
      <sumStat type="vald">
        32491
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          1
        </catValu>
        <catStat type="freq">
          3104
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <catStat type="freq">
          3225
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          3
        </catValu>
        <catStat type="freq">
          3319
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          4
        </catValu>
        <catStat type="freq">
          3362
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          5
        </catValu>
        <catStat type="freq">
          3425
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          6
        </catValu>
        <catStat type="freq">
          3479
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          7
        </catValu>
        <catStat type="freq">
          3485
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          8
        </catValu>
        <catStat type="freq">
          3507
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          9
        </catValu>
        <catStat type="freq">
          3491
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          10
        </catValu>
        <catStat type="freq">
          2094
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V44" name="V20" files="F4" dcml="0" intrvl="discrete">
      <location width="9"/>
      <labl/>
      <valrng>
        <range UNITS="REAL" min="1" max="10"/>
      </valrng>
      <sumStat type="vald">
        32491
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          1
        </catValu>
        <catStat type="freq">
          20
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <catStat type="freq">
          174
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          3
        </catValu>
        <catStat type="freq">
          308
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          4
        </catValu>
        <catStat type="freq">
          410
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          5
        </catValu>
        <catStat type="freq">
          535
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          6
        </catValu>
        <catStat type="freq">
          593
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          7
        </catValu>
        <catStat type="freq">
          735
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          8
        </catValu>
        <catStat type="freq">
          1103
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          9
        </catValu>
        <catStat type="freq">
          11243
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          10
        </catValu>
        <catStat type="freq">
          17370
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V45" name="EndYear" files="F4" dcml="0" intrvl="discrete">
      <location width="9"/>
      <labl/>
      <valrng>
        <range UNITS="REAL" min="0" max="1"/>
      </valrng>
      <sumStat type="vald">
        32491
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          0
        </catValu>
        <catStat type="freq">
          31859
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          1
        </catValu>
        <catStat type="freq">
          632
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V46" name="agecat" files="F4" dcml="0" intrvl="discrete">
      <location width="9"/>
      <labl/>
      <valrng>
        <range UNITS="REAL" min="2" max="4"/>
      </valrng>
      <sumStat type="vald">
        32491
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          2
        </catValu>
        <catStat type="freq">
          19864
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          3
        </catValu>
        <catStat type="freq">
          8149
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          4
        </catValu>
        <catStat type="freq">
          4478
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V47" name="wt_new" files="F4" dcml="0" intrvl="contin">
      <location width="9"/>
      <labl/>
      <valrng>
        <range UNITS="REAL" min="0.00152363744564354" max="110.597366333008"/>
      </valrng>
      <sumStat type="vald">
        31156
      </sumStat>
      <sumStat type="invd">
        1335
      </sumStat>
      <sumStat type="min">
        0.00152
      </sumStat>
      <sumStat type="max">
        110.597
      </sumStat>
      <sumStat type="mean">
        5.06
      </sumStat>
      <sumStat type="stdev">
        5.794
      </sumStat>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V48" name="agegroups" files="F4" dcml="0" intrvl="discrete">
      <location width="9"/>
      <labl>
        Age groups
      </labl>
      <valrng>
        <range UNITS="REAL" min="1" max="3"/>
      </valrng>
      <sumStat type="vald">
        32491
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          40-55
        </labl>
        <catStat type="freq">
          17399
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <labl>
          56-65
        </labl>
        <catStat type="freq">
          6030
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          3
        </catValu>
        <labl>
          66+
        </labl>
        <catStat type="freq">
          9062
        </catStat>
      </catgry>
      <varFormat type="numeric" schema="other"/>
    </var>
  </dataDscr>
</codeBook>
