<?xml version='1.0' encoding='UTF-8'?>
<codeBook version="1.2.2" ID="MWI-MEIRU-All-anthro-data-2020-v1" 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>
          all_anthro_data
        </titl>
        <IDNo>
          DDI-MWI-MEIRU-All-anthro-data-2020-v1
        </IDNo>
      </titlStmt>
      <prodStmt>
        <producer abbr="CK" affiliation="MEIRU" role="Documentation planning and supervision">
          Chifundo Kanjala
        </producer>
        <producer abbr="EM" affiliation="MEIRU" role="Metadata entry and editing">
          Elizabeth Munthali
        </producer>
        <producer abbr="EM" affiliation="LSHTM" role="Production of the documentation used to create this DDI document">
          Estelle McLean
        </producer>
        <prodDate date="2020-06-18">
          2020-06-18
        </prodDate>
        <software version="4.0.9" date="2013-04-23">
          Nesstar Publisher
        </software>
      </prodStmt>
      <distStmt>
        <depositr/>
      </distStmt>
    </citation>
    <docSrc>
      <titlStmt>
        <titl>
          all_anthro_data
        </titl>
      </titlStmt>
      <distStmt>
        <depositr/>
      </distStmt>
    </docSrc>
  </docDscr>
  <stdyDscr>
    <citation>
      <titlStmt>
        <titl>
          All anthropometry data
        </titl>
        <IDNo>
          MWI-MEIRU-All-anthro-data-2020-v1
        </IDNo>
      </titlStmt>
      <rspStmt>
        <AuthEnty affiliation="London School of Hygein and Tropical Medicine">
          Malawi Epidemiology and Intervention Research Unit
        </AuthEnty>
        <othId>
          <p>
            MEIRU Core datamanagement team
          </p>
        </othId>
      </rspStmt>
      <prodStmt>
        <prodDate date="2020-06-18">
          2020-06-18
        </prodDate>
        <software version="4.0.9" date="2013-04-23">
          Nesstar Publisher
        </software>
      </prodStmt>
      <distStmt>
        <depositr/>
      </distStmt>
      <serStmt>
        <serName>
          Demographic Surveillance
        </serName>
      </serStmt>
      <verStmt>
        <version date="2020-06-18"/>
      </verStmt>
    </citation>
    <stdyInfo>
      <abstract>
        Anthropometric measurements have been taken in many studies in Karonga: this dataset combines and harmonises all these sources.
      </abstract>
      <sumDscr>
        <nation abbr="MWI">
          Malawi
        </nation>
        <anlyUnit>
          Individual
        </anlyUnit>
      </sumDscr>
    </stdyInfo>
    <method>
      <dataColl>
        <dataCollector abbr="MEIRU">
          Malawi Epidemiology and Intervention Research Unit
        </dataCollector>
        <collMode>
          Face-to-face [f2f]
        </collMode>
        <sources/>
      </dataColl>
    </method>
    <dataAccs>
      <setAvail>
        <origArch>
          Karonga District
        </origArch>
      </setAvail>
      <useStmt>
        <contact>
          Malawi Epidemiology and Intervention Research Unit
        </contact>
        <conditions>
          <![CDATA[These data are made available for licensed access under the following conditions:

1. Data and other material provided by MEIRU will not be redistributed or sold to other individuals, institutions or organisations without MEIRU's written agreement.

2. In the case of multi-centre datasets, data originating from a single contributing member centre of the collaboration may not be analysed or reported on in isolation without the express permission of the member centre concerned.

3. No attempt will be made to re-identify respondents, and there will be no use of the identity of any person or establishment discovered inadvertently. Any such discovery will be reported immediately to MEIRU.

4. No attempt will be made to produce links between datasets provided by MEIRU or between MEIRU data and other datasets that could identify individuals.

5. Any books, articles, conference papers, theses, dissertations, reports or other publications employing data obtained from MEIRU will cite the source, in line with the citation requirement provided with the dataset.

6. An electronic copy of all publications based on the requested data will be sent to MEIRU.]]>
        </conditions>
      </useStmt>
    </dataAccs>
  </stdyDscr>
  <fileDscr ID="F1" URI="all_anthro_data.Nesstar?Index=0&amp;Name=all_anthro_data">
    <fileTxt>
      <fileName>
        all_anthro_data.NSDstat
      </fileName>
      <fileCont>
        <![CDATA[This data file is all anthropometry measurements carried out in Karonga in any study. Each record can be linked to the rest of Karonga's database through the ident.
				
Users should be aware that some studies were looking only at specific subgroups, or ill people so whole dataset should not be used to draw conclusions about the general population: those marked in the list below can be considered population-representative (notwithstanding non-response issues).				
				
source      	description	                                   type	
ARK	            Kidney disease study                      selected	
ART	           ART clinic	                                             selected	
BFUP	           Baby follow-up                 	              population-representative	
BIS	          Baby immunology study  	              selected	
CBR	         CRS birth registration	                              population-representative	
CPT	                                                                	selected	
FHS	        Family health study	                              selected	
FIS	        Fertility intentions study                  	selected	
GAP	        Adolescent study	                           population-representative	
GP 	        General form	                                          selected	
IIS                   Immunology study	                           selected	
KDU	        Kidney disease study	                                selected	
NCD	        Non-communicable disease study    	population-representative	
PHD	        Pre-diabetes/hypertension               	               selected	
SEI	        Socio-economic survey                    	population-representative	
STS	        Stroke/TIA study	                                selected	
TBH	        TB household study                                        selected	
TBI	        TB immunology study	                                selected	
TBO	        TB controls	                                                selected	
TBS	        TB spouse study                	                selected	
TBX	        TB cases	                                                selected	
TMT	        Transmission of TB study                 	selected	
				
In the variable labels (S) indicates that the variable is unchanged from the original source and (D) indicates that it is a 'derived' variable, often using more than one source variable. For both types information on where the data come from and how they are processed is found in the 'Recoding and Derivation' section]]>
      </fileCont>
      <dimensns>
        <caseQnty>
          152783
        </caseQnty>
        <varQnty>
          21
        </varQnty>
      </dimensns>
      <fileType>
        Nesstar 200801
      </fileType>
      <filePlac>
        Malawi Epidemiology and Interventions Research Unit
      </filePlac>
    </fileTxt>
    <notes>
      <![CDATA[ Exported from EpiData Manager 4.0.0.95 [TRUNK]
On: 2017/03/14 16:21:26
Title: 24 hour food recall - GAP study
Version: 1
On: 2017/01/25 07:59:45]]>
    </notes>
  </fileDscr>
  <dataDscr>
    <var ID="V1" name="examdate" files="F1" intrvl="discrete">
      <location StartPos="1" EndPos="10" width="10" RecSegNo="1"/>
      <labl>
        date of measurement (S)
      </labl>
      <sumStat type="vald">
        152782
      </sumStat>
      <sumStat type="min">
        1996-11-19
      </sumStat>
      <sumStat type="max">
        2020-02-25
      </sumStat>
      <txt>
        date of measurement
      </txt>
      <codInstr>
        <![CDATA[variable: examdate (table[s]: css_fis1)
variable: intdate (table[s]: art_artn, arv_amf, arv_scf, bis_mother, fhs_tktaik, fhs_tktcik, iis_mother, gp_gpform, css_sei, tb_tbh, tb_tboto2007, tb_tbx, tb_tbxto2007, tbold_tbpart1, tb_tbs, tb_tbs5, tmt_tmt1, art_arto, art_artx, tb_tbi, cpt_f3, crs_birth, crs_bfup)
variable: epdate (table[s]: art_arte)
variable: intdate3 (table[s]: tb_tbi)
variable: a_intdt (table[s]: gap_combined)
variable: comdate (table[s]: ncd_combined)
variable: consdate (table[s]: ves_vese)
The date of measurement variable for the various tables is renamed to examdate]]>
      </codInstr>
      <varFormat type="character" formatname="Nesstar.date" schema="other" category="date"/>
    </var>
    <var ID="V2" name="ident" files="F1" intrvl="discrete">
      <location StartPos="11" EndPos="17" width="7" RecSegNo="1"/>
      <labl>
        unique identifier (S)
      </labl>
      <sumStat type="vald">
        152783
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <txt>
        unique identifier
      </txt>
      <codInstr>
        All data sources already link to ident
      </codInstr>
      <varFormat type="character" schema="other"/>
    </var>
    <var ID="V3" name="weight" files="F1" dcml="0" intrvl="contin">
      <location StartPos="18" EndPos="20" width="3" RecSegNo="1"/>
      <labl>
        weight in kg (D)
      </labl>
      <valrng>
        <range UNITS="REAL" min="0" max="150"/>
      </valrng>
      <sumStat type="vald">
        124841
      </sumStat>
      <sumStat type="invd">
        27942
      </sumStat>
      <sumStat type="min">
        0
      </sumStat>
      <sumStat type="max">
        150
      </sumStat>
      <sumStat type="mean">
        31.588
      </sumStat>
      <sumStat type="stdev">
        22.6
      </sumStat>
      <txt>
        weight in kg
      </txt>
      <codInstr>
        <![CDATA[variable: weight (table[s]: art_arte, art_artn, arv_amf, arv_scf, bis_mother, fhs_tktaik, fhs_tktcik, iis_mother, gp_gpform, css_sei, tb_tbh, tb_tboto2007, tb_tbx, tb_tbxto2007, tbold_tbpart1, tb_tbs, tb_tbs5, tmt_tmt1, ncd_combined,  css_fis1, arkk_arkq, ves_vese)
variable: weight2 (table[s]: art_arto, art_artx, tb_tbi)
variable: wt (table[s]: cpt_f3)
variable: bweight (table[s]: crs_birth, crs_bfup)
variable: a_wt (table[s]: gap_combined)
variable: weigf/weigs (table[s]: sts_fup, sts_stsf, sts_stsp)
variable: weightf/weights (table[s]: kduk_kduq, phdk_phdq)
Weight from STS, KDU and PHD were collected twice so average of the 2 readings is calculated. All weight variables from the various tables are in kg so if necessary are renamed to weight.]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V4" name="height" files="F1" dcml="0" intrvl="contin">
      <location StartPos="21" EndPos="25" width="5" RecSegNo="1"/>
      <labl>
        height in cm (D)
      </labl>
      <valrng>
        <range UNITS="REAL" min="0" max="224.5"/>
      </valrng>
      <sumStat type="vald">
        126147
      </sumStat>
      <sumStat type="invd">
        26636
      </sumStat>
      <sumStat type="min">
        0
      </sumStat>
      <sumStat type="max">
        224.5
      </sumStat>
      <sumStat type="mean">
        119.524
      </sumStat>
      <sumStat type="stdev">
        40.937
      </sumStat>
      <txt>
        height in cm
      </txt>
      <codInstr>
        <![CDATA[variable: height (table[s]: art_arte, art_artn, arv_amf, arv_scf, bis_mother, fhs_tktaik, fhs_tktcik, iis_mother, gp_gpform, css_sei, tb_tbh, tb_tboto2007, tb_tbx, tb_tbxto2007, tbold_tbpart1, tb_tbs, tb_tbs5, tmt_tmt1, ncd_combined,  css_fis1, arkk_arkq)
variable: height2 (table[s]: art_arto, art_artx, tb_tbi)
variable: wt (table[s]: cpt_f3)
variable: blength (table[s]: crs_birth, crs_bfup)
variable: a_hghtop1 (table[s]: gap_combined)
variable: heigf/heigs (table[s]: sts_fup, sts_stsf, sts_stsp)
variable: heightf/heights (table[s]: kduk_kduq, phdk_phdq)
variable: length (table[s]: ves_vese)
Height from STS, KDU and PHD were collected twice so average of the 2 readings is calculated. All height variables from the various tables are in cm so if necessary are renamed to height]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V5" name="waisc" files="F1" dcml="0" intrvl="contin">
      <location StartPos="26" EndPos="41" width="16" RecSegNo="1"/>
      <labl>
        waist circumference in cm (D)
      </labl>
      <valrng>
        <range UNITS="REAL" min="21" max="184.100006103516"/>
      </valrng>
      <sumStat type="vald">
        35730
      </sumStat>
      <sumStat type="invd">
        117053
      </sumStat>
      <sumStat type="min">
        21
      </sumStat>
      <sumStat type="max">
        184.1
      </sumStat>
      <sumStat type="mean">
        77.396
      </sumStat>
      <sumStat type="stdev">
        10.754
      </sumStat>
      <txt>
        waist circumference in cm
      </txt>
      <codInstr>
        <![CDATA[variable: waisc (table[s]: css_sei)
variable: waist_op1 (table[s]: gap_combined)
variable: waist (table[s]: ncd_combined)
variable: waiscf/waiscs (table[s]: sts_fup, sts_stsf, sts_stsp, arkk_arkq, kduk_kduq, phdk_phdq)
Waist circumference from ARK, STS, KDU and PHD were collected twice so average of the 2 readings is calculated. All waist circumference variables from the various tables are in cm so if necessary are renamed to waisc]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V6" name="hipcu" files="F1" dcml="0" intrvl="contin">
      <location StartPos="42" EndPos="57" width="16" RecSegNo="1"/>
      <labl>
        hip circumference in cm (D)
      </labl>
      <valrng>
        <range UNITS="REAL" min="45" max="190.050003051758"/>
      </valrng>
      <sumStat type="vald">
        36628
      </sumStat>
      <sumStat type="invd">
        116155
      </sumStat>
      <sumStat type="min">
        45
      </sumStat>
      <sumStat type="max">
        190.05
      </sumStat>
      <sumStat type="mean">
        90.006
      </sumStat>
      <sumStat type="stdev">
        10.42
      </sumStat>
      <txt>
        hip circumference in cm
      </txt>
      <codInstr>
        <![CDATA[variable: hipcu (table[s]: css_sei)
variable: hip_op1 (table[s]: gap_combined)
variable: hip (table[s]: ncd_combined)
variable: hipcuf/hipcus (table[s]: sts_fup, sts_stsf, sts_stsp, arkk_arkq, kduk_kduq, phdk_phdq)
Hip circumference from ARK, STS, KDU and PHD were collected twice so average of the 2 readings is calculated. All hip circumference variables from the various tables are in cm so if necessary are renamed to hipcu]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V7" name="muac" files="F1" dcml="0" intrvl="contin">
      <location StartPos="58" EndPos="62" width="5" RecSegNo="1"/>
      <labl>
        mid-upper arm circumference in cm (D)
      </labl>
      <valrng>
        <range UNITS="REAL" min="0" max="70.75"/>
      </valrng>
      <sumStat type="vald">
        107651
      </sumStat>
      <sumStat type="invd">
        45132
      </sumStat>
      <sumStat type="min">
        0
      </sumStat>
      <sumStat type="max">
        70.75
      </sumStat>
      <sumStat type="mean">
        21.776
      </sumStat>
      <sumStat type="stdev">
        6.575
      </sumStat>
      <txt>
        mid-upper arm circumference in cm
      </txt>
      <codInstr>
        <![CDATA[variable: muac (table[s]: arv_amf, arv_scf, ncd_combined, gp_gpform, css_sei, tb_tbh, tb_tboto2007, tb_tbs, tb_tbs5, tmt_tmt1, css_fis2, arkk_arkq)
variable: armcirc (table[s]: cpt_f3)
variable: armcircumf (table[s]: fhs_tktaik, fhs_tktcik)
variable: buarm (table[s]: crs_birth, crs_bfup)
variable: a_muacop1 (table[s]: gap_combined)
variable: muacf/muacs (table[s]: kduk_kduq, phdk_phdq)
MUAC from KDU and PHD were collected twice so average of the 2 readings is calculated. Most tables had muac already in cm, but GAP, CPT, FHS, TBH, TBO, TMT had to be converted from mm to cm]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V8" name="source" files="F1" intrvl="discrete">
      <location StartPos="63" EndPos="66" width="4" RecSegNo="1"/>
      <labl>
        source of data (D)
      </labl>
      <sumStat type="vald">
        152783
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <txt>
        source of data
      </txt>
      <codInstr>
        three-letter study code is added when each data source is processed
      </codInstr>
      <varFormat type="character" schema="other"/>
    </var>
    <var ID="V9" name="bthweight" files="F1" dcml="0" intrvl="contin">
      <location StartPos="67" EndPos="70" width="4" RecSegNo="1"/>
      <labl>
        birthweight (S)
      </labl>
      <valrng>
        <range UNITS="REAL" min="1" max="99.9"/>
      </valrng>
      <sumStat type="vald">
        7742
      </sumStat>
      <sumStat type="invd">
        145041
      </sumStat>
      <sumStat type="min">
        1
      </sumStat>
      <sumStat type="max">
        99.9
      </sumStat>
      <sumStat type="mean">
        8.641
      </sumStat>
      <sumStat type="stdev">
        22.463
      </sumStat>
      <txt>
        birthweight
      </txt>
      <codInstr>
        variable: bthweight (table[s]: crs_birth)
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V10" name="bthwt_date" files="F1" intrvl="discrete">
      <location StartPos="71" EndPos="80" width="10" RecSegNo="1"/>
      <labl>
        date of birthweight (S)
      </labl>
      <sumStat type="vald">
        7300
      </sumStat>
      <sumStat type="min">
        2012-04-08
      </sumStat>
      <sumStat type="max">
        2020-02-21
      </sumStat>
      <txt>
        date of birthweight
      </txt>
      <codInstr>
        variable: bthwt_date (table[s]: crs_birth)
      </codInstr>
      <varFormat type="character" formatname="Nesstar.date" schema="other" category="date"/>
    </var>
    <var ID="V11" name="headc" files="F1" dcml="0" intrvl="contin">
      <location StartPos="81" EndPos="84" width="4" RecSegNo="1"/>
      <labl>
        head circumference (S)
      </labl>
      <valrng>
        <range UNITS="REAL" min="0" max="99.9"/>
      </valrng>
      <sumStat type="vald">
        14652
      </sumStat>
      <sumStat type="invd">
        138131
      </sumStat>
      <sumStat type="min">
        0
      </sumStat>
      <sumStat type="max">
        99.9
      </sumStat>
      <sumStat type="mean">
        38.605
      </sumStat>
      <sumStat type="stdev">
        4.372
      </sumStat>
      <txt>
        head circumference
      </txt>
      <codInstr>
        variable: bhead (table[s]: crs_birth)
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V12" name="sex" files="F1" dcml="0" intrvl="discrete">
      <location StartPos="85" EndPos="85" width="1" RecSegNo="1"/>
      <labl>
        sex (S)
      </labl>
      <valrng>
        <range min="0" max="9"/>
      </valrng>
      <invalrng>
        <item VALUE="9"/>
      </invalrng>
      <sumStat type="vald">
        152783
      </sumStat>
      <sumStat type="invd">
        0
      </sumStat>
      <txt>
        sex
      </txt>
      <catgry>
        <catValu>
          0
        </catValu>
        <labl>
          Male
        </labl>
        <catStat type="freq">
          62991
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          Female
        </labl>
        <catStat type="freq">
          89792
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          8
        </catValu>
        <labl>
          Unknown
        </labl>
        <catStat type="freq">
          0
        </catStat>
      </catgry>
      <catgry missing="Y">
        <catValu>
          9
        </catValu>
        <labl>
          Missing
        </labl>
        <catStat type="freq">
          0
        </catStat>
      </catgry>
      <codInstr>
        variable: sex (table[s]: gen_identity)
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V13" name="birth_date" files="F1" intrvl="discrete">
      <location StartPos="86" EndPos="95" width="10" RecSegNo="1"/>
      <labl>
        birth date (D)
      </labl>
      <sumStat type="vald">
        152783
      </sumStat>
      <sumStat type="min">
        1898-06-15
      </sumStat>
      <sumStat type="max">
        2020-02-21
      </sumStat>
      <txt>
        birth date
      </txt>
      <codInstr>
        <![CDATA[variable: birthdd (table[s]: gen_identity)
variable: birthmm (table[s]: gen_identity)
variable: birthyear (table[s]: gen_identity)
variable: birthest (table[s]: gen_identity)
Birth date is created from individual date elements on gen_identity: if day missing 15 is used, if month missing June is used, if only year estimate the mid-point of the estimate range is used]]>
      </codInstr>
      <varFormat type="character" formatname="Nesstar.date" schema="other" category="date"/>
    </var>
    <var ID="V14" name="age_y" files="F1" dcml="0" intrvl="contin">
      <location StartPos="96" EndPos="98" width="3" RecSegNo="1"/>
      <labl>
        age in years (D)
      </labl>
      <valrng>
        <range min="0" max="117"/>
      </valrng>
      <sumStat type="vald">
        152782
      </sumStat>
      <sumStat type="invd">
        1
      </sumStat>
      <sumStat type="min">
        0
      </sumStat>
      <sumStat type="max">
        117
      </sumStat>
      <sumStat type="mean">
        19.893
      </sumStat>
      <sumStat type="stdev">
        19.435
      </sumStat>
      <txt>
        age in years
      </txt>
      <codInstr>
        <![CDATA[variable: birth_date (table[s]: derived)
variable: examdate (table[s]: [see above])
Age in years is calculated from examdate and birthdate
gen age_y=int((examdate-birth_date)/365.25)]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V15" name="age_m" files="F1" dcml="0" intrvl="contin">
      <location StartPos="99" EndPos="102" width="4" RecSegNo="1"/>
      <labl>
        age in months (D)
      </labl>
      <valrng>
        <range min="-10" max="1406"/>
      </valrng>
      <sumStat type="vald">
        152782
      </sumStat>
      <sumStat type="invd">
        1
      </sumStat>
      <sumStat type="min">
        -10
      </sumStat>
      <sumStat type="max">
        1406
      </sumStat>
      <sumStat type="mean">
        243.283
      </sumStat>
      <sumStat type="stdev">
        233.135
      </sumStat>
      <txt>
        age in months
      </txt>
      <codInstr>
        <![CDATA[variable: birth_date (table[s]: derived)
variable: examdate (table[s]: [see above])
Age in months is calculated from examdate and birthdate
gen age_m=int((examdate-birth_date)/30.5)]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V16" name="wfh" files="F1" dcml="0" intrvl="contin">
      <location StartPos="103" EndPos="114" width="12" RecSegNo="1"/>
      <labl>
        weight for height (D)
      </labl>
      <valrng>
        <range UNITS="REAL" min="0" max="36160.421875"/>
      </valrng>
      <sumStat type="vald">
        122579
      </sumStat>
      <sumStat type="invd">
        30204
      </sumStat>
      <sumStat type="min">
        0
      </sumStat>
      <sumStat type="max">
        36160.422
      </sumStat>
      <sumStat type="mean">
        18.83
      </sumStat>
      <sumStat type="stdev">
        103.936
      </sumStat>
      <txt>
        weight for height
      </txt>
      <codInstr>
        <![CDATA[variable: weight (table[s]: derived)
variable: height (table[s]: derived)
gen wfh=weight/((height/100)*(height/100))]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V17" name="malnut" files="F1" dcml="0" intrvl="discrete">
      <location StartPos="115" EndPos="115" width="1" RecSegNo="1"/>
      <labl>
        <![CDATA[whether  malnourished (D)]]>
      </labl>
      <valrng>
        <range min="0" max="1"/>
      </valrng>
      <sumStat type="vald">
        122579
      </sumStat>
      <sumStat type="invd">
        30204
      </sumStat>
      <txt>
        <![CDATA[whether  malnourished: for children weight for height less that 2 standard deviations below WHO standard for age in months and for adults (18+) BMI<18.5]]>
      </txt>
      <codInstr>
        <![CDATA[variable: wfh (table[s]: derived)
variable: SD2neg (table[s]: who_bmi_z_scores_month)
WHO standards for weight for height in children by month of age are used to assess malnutrition in children
merge m:1 age_m sex using ${nutdata}\who_bmi_z_scores_month, keep(master match)
gen malnut=0 if wfh~=.
replace malnut=1 if wfh<SD2neg & wfh~=. & SD2neg~=.
replace malnut=1 if wfh<18.5 & age_y>=18]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V18" name="agegp" files="F1" dcml="0" intrvl="discrete">
      <location StartPos="116" EndPos="116" width="1" RecSegNo="1"/>
      <labl>
        group age variable (D)
      </labl>
      <valrng>
        <range min="1" max="6"/>
      </valrng>
      <sumStat type="vald">
        152782
      </sumStat>
      <sumStat type="invd">
        1
      </sumStat>
      <txt>
        group age variable
      </txt>
      <catgry>
        <catValu>
          1
        </catValu>
        <labl>
          &lt;1
        </labl>
        <catStat type="freq">
          21149
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          2
        </catValu>
        <labl>
          1-4y
        </labl>
        <catStat type="freq">
          25369
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          3
        </catValu>
        <labl>
          5-9y
        </labl>
        <catStat type="freq">
          22064
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          4
        </catValu>
        <labl>
          10-14y
        </labl>
        <catStat type="freq">
          7317
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          5
        </catValu>
        <labl>
          15-19y
        </labl>
        <catStat type="freq">
          10182
        </catStat>
      </catgry>
      <catgry>
        <catValu>
          6
        </catValu>
        <labl>
          20+y
        </labl>
        <catStat type="freq">
          66701
        </catStat>
      </catgry>
      <catgry missing="Y">
        <catValu>
          Sysmiss
        </catValu>
        <catStat type="freq">
          1
        </catStat>
      </catgry>
      <codInstr>
        recode age_y (0=1 "&lt;1") (1/4=2 "1-4y") (5/9=3 "5-9y") (10/14=4 "10-14y") (15/19=5 "15-19y") (20/max=6 "20+y"), gen(agegp)
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V19" name="examyear" files="F1" dcml="0" intrvl="contin">
      <location StartPos="117" EndPos="120" width="4" RecSegNo="1"/>
      <labl>
        year of examination (D)
      </labl>
      <valrng>
        <range min="1996" max="2020"/>
      </valrng>
      <sumStat type="vald">
        152782
      </sumStat>
      <sumStat type="invd">
        1
      </sumStat>
      <sumStat type="min">
        1996
      </sumStat>
      <sumStat type="max">
        2020
      </sumStat>
      <sumStat type="mean">
        2011.496
      </sumStat>
      <sumStat type="stdev">
        4.497
      </sumStat>
      <txt>
        year of examination
      </txt>
      <codInstr>
        <![CDATA[variable: examdate (table[s]: derived)
gen examyear=year(examdate)]]>
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
    <var ID="V20" name="lastincrs" files="F1" intrvl="discrete">
      <location StartPos="121" EndPos="130" width="10" RecSegNo="1"/>
      <labl>
        last date seen in CRS (D)
      </labl>
      <sumStat type="vald">
        130081
      </sumStat>
      <sumStat type="min">
        2002-11-15
      </sumStat>
      <sumStat type="max">
        2018-12-31
      </sumStat>
      <txt>
        last date seen in CRS
      </txt>
      <codInstr>
        <![CDATA[variable: stopdate (table[s]: crs_memball)
Last date in crs_memball is calculated and merged in]]>
      </codInstr>
      <varFormat type="character" formatname="Nesstar.date" schema="other" category="date"/>
    </var>
    <var ID="V21" name="crs" files="F1" dcml="0" intrvl="discrete">
      <location StartPos="131" EndPos="131" width="1" RecSegNo="1"/>
      <labl>
        whether CRS member (D)
      </labl>
      <valrng>
        <range min="1" max="1"/>
      </valrng>
      <sumStat type="vald">
        130081
      </sumStat>
      <sumStat type="invd">
        22702
      </sumStat>
      <txt>
        whether CRS member
      </txt>
      <codInstr>
        variable: stopdate (table[s]: crs_memball)
      </codInstr>
      <varFormat type="numeric" schema="other"/>
    </var>
  </dataDscr>
</codeBook>
