<?xml version='1.0' encoding='UTF-8'?>
<codeBook version="1.2.2" ID="INDEPTH.ZA011.HAALSI.2019.v2" xml-lang="en" xmlns="http://www.icpsr.umich.edu/DDI" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.icpsr.umich.edu/DDI http://www.icpsr.umich.edu/DDI/Version1-2-2.xsd">
  <docDscr>
    <citation>
      <titlStmt>
        <titl>
          Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa [HAALSI] Wave 2 Survey: Agincourt, South Africa, 2018/2019
        </titl>
        <IDNo>
          INDEPTH.ZA011.HAALSI.2019.v2
        </IDNo>
      </titlStmt>
      <rspStmt>
        <AuthEnty affiliation="Harvard T.H. Chan School of Public Health">
          Lisa Berkman
        </AuthEnty>
        <AuthEnty affiliation="MRC/Wits Agincourt Research unit, University of Witwatersrand">
          Stephen Tollman
        </AuthEnty>
        <AuthEnty affiliation="MRC/Wits Agincourt Research unit, University of Witwatersrand">
          Kathleen Kahn
        </AuthEnty>
      </rspStmt>
      <prodStmt>
        <software version="4.0.10" date="2018-05-02">
          Nesstar Publisher
        </software>
      </prodStmt>
    </citation>
  </docDscr>
  <stdyDscr>
    <citation>
      <titlStmt>
        <titl>
          Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa [HAALSI] Wave 2 Survey: Agincourt, South Africa, 2018/2019
        </titl>
        <IDNo>
          INDEPTH.ZA011.HAALSI.2019.v2
        </IDNo>
      </titlStmt>
      <rspStmt>
        <AuthEnty affiliation="Harvard T.H. Chan School of Public Health">
          Lisa Berkman
        </AuthEnty>
        <AuthEnty affiliation="MRC/Wits Agincourt Research unit, University of Witwatersrand">
          Stephen Tollman
        </AuthEnty>
        <AuthEnty affiliation="MRC/Wits Agincourt Research unit, University of Witwatersrand">
          Kathleen Kahn
        </AuthEnty>
      </rspStmt>
      <prodStmt>
        <software version="4.0.10" date="2018-05-02">
          Nesstar Publisher
        </software>
      </prodStmt>
      <verStmt>
        <version>
          Version 2
        </version>
      </verStmt>
    </citation>
    <stdyInfo>
      <subject>
        <keyword>
          South Africa
        </keyword>
        <keyword>
          Aging
        </keyword>
        <keyword>
          Older adults
        </keyword>
        <keyword>
          Cognition
        </keyword>
        <keyword>
          Physical functioning
        </keyword>
        <keyword>
          Social networks
        </keyword>
        <keyword>
          Cardiometabolic
        </keyword>
        <keyword>
          disease
        </keyword>
        <keyword>
          HIV
        </keyword>
        <keyword>
          Economics
        </keyword>
        <keyword>
          Agincourt
        </keyword>
        <keyword>
          HAALSI
        </keyword>
        <topcClas>
          Medicine
        </topcClas>
        <topcClas>
          Health and Life Sciences
        </topcClas>
        <topcClas>
          Social Sciences
        </topcClas>
      </subject>
      <abstract>
        The Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) study is a population-based survey implemented by the Harvard Center for Population and Development Studies and the MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt) of the University of the Witwatersrand. HAALSI aims to examine and characterize a population of older men and women in rural South Africa with respect to health, physical and cognitive function, aging, and well-being, in harmonization with other Health and Retirement Studies. The second wave of data collection was conducted in October 2018-November 2019 among 4,176 members of the Wave 1 HAALSI cohort. The Wave 1 participants included 5,059 men and women aged 40 years or older, who were were randomly sampled from within the existing framework of the Agincourt health and socio-demographic surveillance system (AHDSS), in rural Mpumalanga province, South Africa. The survey was administered by local field workers in Shangaan at the participants' homes using computer-assisted personal interviewing (CAPI). Extensive survey data was collected on cognitive and physical functioning, social networks, cardiometabolic disease and risk factors, HIV and HIV risk, and economic well-being. The survey also included anthropometric measures and point-of-care blood tests for hemoglobin and glucose, as well as collection of dried bloodspots (DBS). An additional round of data collection is planned within the next two years. Future data releases will share results from DBS that were collected during the survey and tested for HIV, HIV viral load, HbA1c and CRP. (2020-07-16)
      </abstract>
      <sumDscr>
	  <timePrd date="2018" event="start"/>
        <timePrd date="2019" event="end"/>
        <collDate date="2018" event="start" cycle="P1"/>
        <collDate date="2019" event="end" cycle="P1"/>
        <nation>
          South Africa
        </nation>
        <geogCover>
          South Africa Mpumalanga
        </geogCover>
        <anlyUnit>
          participants included 5,059 men and women aged 40 years or older, who were were randomly sampled from within the existing framework of the Agincourt health and socio-demographic surveillance system (AHDSS), in rural Mpumalanga province, South Africa.
        </anlyUnit>
      </sumDscr>
    </stdyInfo>
    <method>
      <dataColl>
        <timeMeth>
          The second wave of data collection was conducted in October 2018-November 2019
        </timeMeth>
        <sampProc>
          The second wave of data collection was conducted in October 2018-November 2019 among 4,176 members of the Wave 1 HAALSI cohort.
        </sampProc>
        <collMode>
          The survey was administered by local field workers in Shangaan at the participants' homes using computer-assisted personal interviewing (CAPI).
        </collMode>
        <sources/>
      </dataColl>
    </method>
  </stdyDscr>
  <dataDscr/>
</codeBook>
