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Kenya National Micronutrient Survey 2011, First Round

Kenya, 2011
Kenya National Bureau of Statistics (KNBS), Division of Nutrition, Ministry of Public Health and Sanitation (MOPHS), Kenya Medical Research Institute (KEMRI)
Created on June 01, 2022 Last modified June 01, 2022 Page views 161238 Download 7574 Documentation in PDF Metadata DDI/XML JSON
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Division (DIVISION)

Data file: HHold

Overview

Valid: 10684
Invalid: 0
Type: Discrete
Width: 15
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
AINABKOI 75
0.7%
AINAMOI 68
0.6%
ALDAI 46
0.4%
AMUKURA 47
0.4%
ANGURAI 51
0.5%
ASEGO 45
0.4%
AWENDO 18
0.2%
BANISA 41
0.4%
BARAGOI 48
0.4%
BELGUT 26
0.2%
BOMET CENTRAL 27
0.3%
BONDO 92
0.9%
BORABU 50
0.5%
BUMULA 57
0.5%
BURET 53
0.5%
BUTERE 58
0.5%
BUTULA 30
0.3%
BUURI 26
0.2%
CENTRAL 791
7.4%
CENTRAL THARAKA 13
0.1%
CHANGAMWE 55
0.5%
CHEPARERIA 35
0.3%
CHEPKORIO 47
0.4%
CHEPTAIS 97
0.9%
CHONYI 58
0.5%
DAGORETTI 46
0.4%
E. KARACHUONYO 46
0.4%
EKERENYO 32
0.3%
ELDAMA RAVINE 32
0.3%
EMBAKASI 157
1.5%
EVURORE 41
0.4%
GACHOKA 36
0.3%
GALOLE 44
0.4%
GATANGA 21
0.2%
GATUNDU 29
0.3%
GICHUGU 41
0.4%
GILGIL 12
0.1%
GITHUNGURI 63
0.6%
GOLBO 40
0.4%
HADADO 49
0.5%
IGAMBANG'OMBE 28
0.3%
IGEMBE CENTRAL 21
0.2%
IGEMBE EAST 28
0.3%
IGOJI 28
0.3%
IKOLOMANI 34
0.3%
ISLAND 88
0.8%
KABARNET 34
0.3%
KABATI 42
0.4%
KABRAS 56
0.5%
KADIBO 55
0.5%
KAINUK 44
0.4%
KAKUMA 52
0.5%
KALOLENI 41
0.4%
KAMARA 43
0.4%
KAMARINY 85
0.8%
KAMWANGI 31
0.3%
KANDARA 34
0.3%
KANDUYI 91
0.9%
KANGEMA 39
0.4%
KANGUNDO 18
0.2%
KAPCHEROP 42
0.4%
KAPENGURIA 20
0.2%
KAPLAMAI 47
0.4%
KAPSABET 77
0.7%
KAPSOWAR 20
0.2%
KAPTAMA 49
0.5%
KAREMO 55
0.5%
KASARANI 42
0.4%
KASIPUL 75
0.7%
KATHIANI 42
0.4%
KATHONZWENI 51
0.5%
KEHANCHA 54
0.5%
KEIYAN 50
0.5%
KENYENYA 48
0.4%
KEUMBU 28
0.3%
KIAMBAA 42
0.4%
KIBERA 141
1.3%
KIENI EAST 39
0.4%
KIENI WEST 23
0.2%
KIGUMO 30
0.3%
KIHARU 39
0.4%
KIKAMBALA 36
0.3%
KIKUYU 36
0.3%
KILGORIS 91
0.9%
KILIBWONI 41
0.4%
KILOME 39
0.4%
KIMILILI 25
0.2%
KIMULOT 24
0.2%
KINANGO 43
0.4%
KINNA 48
0.4%
KIPKELION 79
0.7%
KIRISIA 44
0.4%
KISAUNI 41
0.4%
KOMBEWA 59
0.6%
KOPSIRO 51
0.5%
KOTULO 48
0.4%
KUBO 45
0.4%
KURESOI 33
0.3%
KWANZA 52
0.5%
KYENI 45
0.4%
LAISAMIS 29
0.3%
LAMURIA 25
0.2%
LARI 29
0.3%
LIKONI 31
0.3%
LIKUYANI 90
0.8%
LOITOKITOK 41
0.4%
LOKICHOGGIO 44
0.4%
LONGISA 63
0.6%
LUANDA 43
0.4%
LUGARI 92
0.9%
MADIANY 28
0.3%
MAGARINI 66
0.6%
MAIKONA 30
0.3%
MAKADARA 43
0.4%
MAKUYU 51
0.5%
MALAKISI 55
0.5%
MALINDI 158
1.5%
MANYATTA 34
0.3%
MARAFA 73
0.7%
MARAGUA 59
0.6%
MARANI 50
0.5%
MASALANI 58
0.5%
MASENO 17
0.2%
MASHURU 29
0.3%
MATAYOS 44
0.4%
MATHIOYA 27
0.3%
MAVOKO 22
0.2%
MBITA 91
0.9%
MERTI 36
0.3%
MIGWANI 40
0.4%
MIRIGA MIERU W. 50
0.5%
MIWANI 39
0.4%
MOCHONGOI 67
0.6%
MOGOTIO 55
0.5%
MOIBEN 63
0.6%
MOSOCHO 39
0.4%
MPEKETONI 43
0.4%
MSAMBWENI 96
0.9%
MTITO-ANDEI 15
0.1%
MUHORONI 27
0.3%
MUKURWE-INI 33
0.3%
MULOT 58
0.5%
MUMBERES 56
0.5%
MUMIAS 90
0.8%
MUNICIPALITY 90
0.8%
MUTHAMBI 34
0.3%
MUTOMO 42
0.4%
MUTUATI 35
0.3%
MWALA 42
0.4%
MWAMBIRWA 26
0.2%
MWATATE 42
0.4%
MWEA 57
0.5%
MWIMBI 27
0.3%
NAIVASHA 28
0.3%
NAKURU MUNI. 28
0.3%
NDARAGWA 34
0.3%
NDIA 48
0.4%
NGINYANG 60
0.6%
NGONG 36
0.3%
NGUNI 42
0.4%
NJORO 18
0.2%
NKUENE 43
0.4%
NORTH THARAKA 32
0.3%
NTIMARU 32
0.3%
NYAHURURU 62
0.6%
NYAMACHE 35
0.3%
NYAMIRA 36
0.3%
NYANDO 52
0.5%
NYARONGI 39
0.4%
NYATIKE 55
0.5%
OGEMBO 21
0.2%
OL JORO OROK 26
0.2%
OL KALOU 16
0.1%
OSUPUKO 37
0.3%
OTHAYA 9
0.1%
PUMWANI 39
0.4%
RANGWE 40
0.4%
RONGAI 41
0.4%
RONGO 32
0.3%
RUIRU 24
0.2%
RUNYENJES 27
0.3%
S. KINANGOP 21
0.2%
SABATIA 29
0.3%
SALAWA 56
0.5%
SAMETA 41
0.4%
SHANT-ABAK 44
0.4%
SIGOR 32
0.3%
SIONGIROI 55
0.5%
SIRISIA 47
0.4%
SOTIK 23
0.2%
SOUTH THARAKA 36
0.3%
SUBA EAST 51
0.5%
TAMBACH 15
0.1%
TARBAJ 57
0.5%
TETU 41
0.4%
TIGANIA WEST 42
0.4%
TIMAU 26
0.2%
TIRAP 38
0.4%
TOWNSHIP 24
0.2%
TURBO 102
1%
UGUNJA 44
0.4%
UKWALA 40
0.4%
URAN 39
0.4%
URIRI 56
0.5%
USIGU 31
0.3%
VIHIGA 56
0.5%
VITENGENI 49
0.5%
VOI 36
0.3%
W. KARACHUONYO 44
0.4%
WAGAI 47
0.4%
WAMBA 43
0.4%
WESTLANDS 131
1.2%
WINAM 151
1.4%
WUNDANYI 39
0.4%
YATTA 53
0.5%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
Question pretext
CLUSTER (EA) NAME