National Panel Survey 2014-2015, Wave 4
Tanzania, 2014 - 2015
Get Microdata
Reference ID
TZA_2014_NPS-R4_v03_M
Producer(s)
National Bureau of Statistics
Collection(s)
Metadata
Created on
Jul 17, 2017
Last modified
Jan 30, 2020
Page views
425358
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- Data files
- ag_filters
- ag_network
- ag_sec_01
- ag_sec_2a
- ag_sec_2b
- ag_sec_3a
- ag_sec_3b
- ag_sec_4a
- ag_sec_4b
- ag_sec_5a
- ag_sec_5b
- ag_sec_6a
- ag_sec_6b
- ag_sec_7a
- ag_sec_7b
- ag_sec_10
- ag_sec_11
- ag_sec_12a
- ag_sec_12b
- ag_sec_a
- hh_filters
- hh_sec_a
- hh_sec_b
- hh_sec_c
- hh_sec_d
- hh_sec_e
- hh_sec_f
- hh_sec_g
- hh_sec_h
- hh_sec_i
- hh_sec_j1
- hh_sec_j3
- hh_sec_j4
- hh_sec_k
- hh_sec_l
- hh_sec_m
- hh_sec_n
- hh_sec_o1
- hh_sec_o2
- hh_sec_p
- hh_sec_q1
- hh_sec_q2
- hh_sec_r
- hh_sec_s
- hh_sec_u2
- hh_sec_v
- lf_filters
- lf_network
- lf_sec_01
- lf_sec_02
- lf_sec_03
- lf_sec_04
- lf_sec_05
- lf_sec_06
- lf_sec_07
- lf_sec_08
- lf_sec_09
- lf_sec_11a
- lf_sec_11b
- lf_sec_12
- lf_sec_13a
- lf_sec_13b
- lf_sec_a
- npsy4.child.anthro
- npsy4.ea.offset
- LF_SEC_10
- com_sec_a1a2
- com_sec_cb
- com_sec_cc
- com_sec_cd
- com_sec_ce
- com_sec_cf
- com_sec_cf_id
- com_sec_cg
- consumptionNPS4
District Name (hh_a02_2)
Data file: hh_sec_a
Overview
Valid:
3352
Invalid:
0
Type:
Discrete
Start:
68
End:
86
Width:
19
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| ARUSHA | 16 |
0.5%
|
|
| ARUSHA MJINI | 16 |
0.5%
|
|
| BABATI | 8 |
0.2%
|
|
| BABATI MJI | 8 |
0.2%
|
|
| BAGAMOYO | 24 |
0.7%
|
|
| BAHI | 8 |
0.2%
|
|
| BARIADI | 40 |
1.2%
|
|
| BIHARAMULO | 16 |
0.5%
|
|
| BUHIGWE | 16 |
0.5%
|
|
| BUKOBA | 24 |
0.7%
|
|
| BUKOBA MANISPAA | 8 |
0.2%
|
|
| BUKOMBE | 16 |
0.5%
|
|
| BUNDA | 16 |
0.5%
|
|
| BUSEGA | 16 |
0.5%
|
|
| BUTIAMA | 16 |
0.5%
|
|
| CHAKE CHAKE | 32 |
1%
|
|
| CHAMWINO | 8 |
0.2%
|
|
| CHATO | 16 |
0.5%
|
|
| CHEMBA | 8 |
0.2%
|
|
| CHUNYA | 8 |
0.2%
|
|
| DODOMA MJINI | 24 |
0.7%
|
|
| GAIRO | 16 |
0.5%
|
|
| GEITA | 40 |
1.2%
|
|
| HAI | 16 |
0.5%
|
|
| HANANG | 16 |
0.5%
|
|
| HANDENI | 8 |
0.2%
|
|
| IGUNGA | 32 |
1%
|
|
| IKUNGI | 8 |
0.2%
|
|
| ILALA | 152 |
4.5%
|
|
| ILEJE | 8 |
0.2%
|
|
| ILEMELA MANISPAA | 16 |
0.5%
|
|
| IRINGA | 16 |
0.5%
|
|
| IRINGA MANISPAA | 16 |
0.5%
|
|
| ITILIMA | 16 |
0.5%
|
|
| KAHAMA | 40 |
1.2%
|
|
| KAHAMA MJI | 16 |
0.5%
|
|
| KAKONKO | 8 |
0.2%
|
|
| KALAMBO | 8 |
0.2%
|
|
| KALIUA | 24 |
0.7%
|
|
| KARAGWE | 32 |
1%
|
|
| KARATU | 8 |
0.2%
|
|
| KASKAZINI A | 32 |
1%
|
|
| KASKAZINI B | 24 |
0.7%
|
|
| KASULU | 16 |
0.5%
|
|
| KASULU MJI | 16 |
0.5%
|
|
| KATI | 16 |
0.5%
|
|
| KIBAHA | 8 |
0.2%
|
|
| KIBAHA MJI | 8 |
0.2%
|
|
| KIBONDO | 8 |
0.2%
|
|
| KIGOMA | 16 |
0.5%
|
|
| KIGOMA MANISPAA | 16 |
0.5%
|
|
| KILINDI | 16 |
0.5%
|
|
| KILOLO | 16 |
0.5%
|
|
| KILOMBERO | 16 |
0.5%
|
|
| KILOSA | 16 |
0.5%
|
|
| KILWA | 24 |
0.7%
|
|
| KINONDONI | 232 |
6.9%
|
|
| KISARAWE | 8 |
0.2%
|
|
| KISHAPU | 24 |
0.7%
|
|
| KITETO | 8 |
0.2%
|
|
| KONDOA | 8 |
0.2%
|
|
| KONGWA | 8 |
0.2%
|
|
| KOROGWE | 16 |
0.5%
|
|
| KUSINI | 8 |
0.2%
|
|
| KWIMBA | 32 |
1%
|
|
| KYELA | 8 |
0.2%
|
|
| KYERWA | 24 |
0.7%
|
|
| LINDI | 24 |
0.7%
|
|
| LINDI MANISPAA | 8 |
0.2%
|
|
| LIWALE | 8 |
0.2%
|
|
| LONGIDO | 8 |
0.2%
|
|
| LUDEWA | 8 |
0.2%
|
|
| LUSHOTO | 24 |
0.7%
|
|
| MAFINGA MJI | 8 |
0.2%
|
|
| MAGHARIBI | 224 |
6.7%
|
|
| MAGU | 16 |
0.5%
|
|
| MAKAMBAKO MJI | 8 |
0.2%
|
|
| MANYONI | 24 |
0.7%
|
|
| MASASI | 32 |
1%
|
|
| MASASI MJI | 16 |
0.5%
|
|
| MASWA | 24 |
0.7%
|
|
| MBARALI | 24 |
0.7%
|
|
| MBEYA | 16 |
0.5%
|
|
| MBEYA JIJI | 8 |
0.2%
|
|
| MBINGA | 16 |
0.5%
|
|
| MBOGWE | 8 |
0.2%
|
|
| MBOZI | 16 |
0.5%
|
|
| MBULU | 16 |
0.5%
|
|
| MEATU | 24 |
0.7%
|
|
| MERU | 24 |
0.7%
|
|
| MICHEWENI | 32 |
1%
|
|
| MISSENYI | 8 |
0.2%
|
|
| MISUNGWI | 16 |
0.5%
|
|
| MJINI | 48 |
1.4%
|
|
| MKALAMA | 8 |
0.2%
|
|
| MKOANI | 24 |
0.7%
|
|
| MKURANGA | 8 |
0.2%
|
|
| MLELE | 24 |
0.7%
|
|
| MOMBA | 8 |
0.2%
|
|
| MONDULI | 8 |
0.2%
|
|
| MOROGORO | 16 |
0.5%
|
|
| MOROGORO MANISPAA | 24 |
0.7%
|
|
| MOSHI | 32 |
1%
|
|
| MOSHI MANISPAA | 24 |
0.7%
|
|
| MPANDA | 24 |
0.7%
|
|
| MPANDA MJI | 8 |
0.2%
|
|
| MPWAPWA | 8 |
0.2%
|
|
| MTWARA MANISPAA | 8 |
0.2%
|
|
| MTWARA VIJIJINI | 24 |
0.7%
|
|
| MUFINDI | 32 |
1%
|
|
| MUHEZA | 8 |
0.2%
|
|
| MULEBA | 40 |
1.2%
|
|
| MUSOMA | 8 |
0.2%
|
|
| MUSOMA MANISPAA | 8 |
0.2%
|
|
| MVOMERO | 8 |
0.2%
|
|
| MWANGA | 16 |
0.5%
|
|
| NACHINGWEA | 16 |
0.5%
|
|
| NAMTUMBO | 8 |
0.2%
|
|
| NANYUMBU | 16 |
0.5%
|
|
| NEWALA | 24 |
0.7%
|
|
| NGARA | 24 |
0.7%
|
|
| NGORONGORO | 8 |
0.2%
|
|
| NJOMBE | 8 |
0.2%
|
|
| NJOMBE MJI | 8 |
0.2%
|
|
| NKASI | 16 |
0.5%
|
|
| NYAMAGANA MANISPAA | 16 |
0.5%
|
|
| NYANG'HWALE | 8 |
0.2%
|
|
| NYASA | 8 |
0.2%
|
|
| NZEGA | 32 |
1%
|
|
| PANGANI | 16 |
0.5%
|
|
| ROMBO | 16 |
0.5%
|
|
| RORYA | 16 |
0.5%
|
|
| RUANGWA | 8 |
0.2%
|
|
| RUFIJI | 16 |
0.5%
|
|
| RUNGWE | 16 |
0.5%
|
|
| SAME | 16 |
0.5%
|
|
| SENGEREMA | 24 |
0.7%
|
|
| SERENGETI | 16 |
0.5%
|
|
| SHINYANGA MANISPAA | 8 |
0.2%
|
|
| SIHA | 8 |
0.2%
|
|
| SIKONGE | 16 |
0.5%
|
|
| SIMANJIRO | 8 |
0.2%
|
|
| SINGIDA | 8 |
0.2%
|
|
| SINGIDA MJINI | 8 |
0.2%
|
|
| SINYANGA | 24 |
0.7%
|
|
| SONGEA | 8 |
0.2%
|
|
| SONGEA MANISPAA | 16 |
0.5%
|
|
| SUMBAWANGA | 8 |
0.2%
|
|
| SUMBAWANGA MANISPAA | 8 |
0.2%
|
|
| TABORA MANISPAA | 8 |
0.2%
|
|
| TANDAHIMBA | 24 |
0.7%
|
|
| TANGA | 8 |
0.2%
|
|
| TARIME | 8 |
0.2%
|
|
| TEMEKE | 168 |
5%
|
|
| TUNDURU | 16 |
0.5%
|
|
| UKEREWE | 24 |
0.7%
|
|
| ULANGA | 16 |
0.5%
|
|
| URAMBO | 8 |
0.2%
|
|
| UVINZA | 16 |
0.5%
|
|
| UYUI | 24 |
0.7%
|
|
| WANG'ING'OMBE | 16 |
0.5%
|
|
| WETE | 40 |
1.2%
|
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.