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    Home / Central Data Catalog / NUHDSS / APHRC-NUHDSS-INMIGRATION-V1.0 / variable [F1]
NUHDSS

NUHDSS-Inmigration Registration 2002-2015

KENYA, 2002 - 2015
Nairobi Urban Health & Demographic Surveillance System
African Population and Health Research Center
Last modified January 26, 2021 Page views 48395 Documentation in PDF Metadata DDI/XML JSON
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  • In-migration_2002-2015
CSV JSON

district in Kenya in which inmigrant was born (img_birth_district)

Data file: In-migration_2002-2015

Overview

vald 165056
invd 0
Interval discrete
Decimal 0
Range 7 - 9999995

Questions and instructions

Literal question
What province and district were you/(NAME) born?
Categories
Value Category Cases
7 4
0%
100 central province-district unknown 0
0%
101 kiambu 2958
1.8%
102 kirinyaga 818
0.5%
103 maragua 1391
0.8%
104 murang'a 10478
6.3%
105 nyandarua 1546
0.9%
106 nyeri 2602
1.6%
107 thika 1843
1.1%
108 nyahururu 0
0%
109 limuru 0
0%
110 nanyuki 0
0%
111 kerugoya 0
0%
200 coast province-district unknown 0
0%
201 kilifi 56
0%
202 kwale 50
0%
203 lamu 28
0%
204 malindi 42
0%
205 mombasa 416
0.3%
206 taita taveta 274
0.2%
207 tana river 24
0%
208 voi 0
0%
209 shinyanga 0
0%
210 changamwe 0
0%
300 eastern province-district unknown 0
0%
301 embu 849
0.5%
302 isiolo 705
0.4%
303 kitui 5751
3.5%
304 machakos 16554
10%
305 makueni 7598
4.6%
306 marsabit 506
0.3%
307 mbeere 392
0.2%
310 meru 1542
0.9%
311 moyale 656
0.4%
312 mwingi 768
0.5%
313 tharaka 65
0%
314 kangundo 0
0%
315 athi river 0
0%
316 matuu 0
0%
317 mwanza 0
0%
318 mbooni 0
0%
319 loitoktok 0
0%
320 kibwezi 0
0%
321 tala 0
0%
322 ndhiwa 0
0%
323 yatta 0
0%
324 garba tula 0
0%
400 nairobi province-district unknown 5160
3.1%
401 central 604
0.4%
402 dagoretti 178
0.1%
403 embakasi 2617
1.6%
404 kasarani 6348
3.8%
405 kibera 280
0.2%
406 makadara 1642
1%
407 pumwani 634
0.4%
408 westlands 89
0.1%
500 north eastern province-district unknown 0
0%
501 garissa 217
0.1%
502 ijara 31
0%
503 mandera 930
0.6%
504 wajir 220
0.1%
505 elwak 3
0%
600 nyanza province-district unknown 0
0%
601 bondo 1014
0.6%
603 homa bay 1244
0.8%
604 kisii central 4446
2.7%
605 kisumu 2883
1.7%
606 kuria 565
0.3%
607 migori 1067
0.6%
608 kisii 5084
3.1%
609 nyando 647
0.4%
610 karachuonyo 590
0.4%
611 siaya 5927
3.6%
612 suba 164
0.1%
613 oyugis 0
0%
614 ugenya 0
0%
615 nyakach 0
0%
616 alego 0
0%
617 gem 0
0%
618 kendu bay 0
0%
619 ahero 0
0%
620 asembo 0
0%
621 gwasi 0
0%
700 rift valley province-district unknown 0
0%
701 baringo 51
0%
702 bomet 261
0.2%
703 bureti 22
0%
704 kajiado 387
0.2%
705 keiyo 48
0%
706 kericho 225
0.1%
707 koibatek 64
0%
708 laikipia 245
0.1%
709 nakuru 2019
1.2%
711 nandi 256
0.2%
712 narok 175
0.1%
713 samburu 30
0%
714 transmara 46
0%
715 trans nzoia 744
0.5%
716 turkana 36
0%
717 uasin gishu 335
0.2%
718 west pokot 8
0%
719 kitale 0
0%
720 molo 0
0%
721 bureti 0
0%
722 kinangop 0
0%
723 nyambene 0
0%
724 maseno 0
0%
725 kapsabet 0
0%
800 western province-district unknown 0
0%
801 bungoma 1864
1.1%
802 busia 3436
2.1%
803 butere/mumias/bunyore 4893
3%
804 kakamega 4702
2.8%
805 lugari 488
0.3%
806 elgon 590
0.4%
807 teso 226
0.1%
808 vihiga 3679
2.2%
809 webuye 0
0%
810 amagoro 0
0%
900 outside Kenya 1012
0.6%
9996 other 0
0%
9997 refused 17
0%
9998 don't know 49
0%
9999 NIU (not in universe) 0
0%
9999995 missing:impute 38648
23.4%
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
na
Question post text
na
Interviewer instructions
Write down the NAME specifying the PROVINCE and DISTRICT where the in migrant was born. The NAME of area where migrant moved from should be recorded on the dotted line.

Description

Text
The district in Kenya in which the inmigrant was born.
Universe
All households that had an in-migrant.
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