Demographic and Health Survey 2016
Uganda, 2016
Get Microdata
Reference ID
UGA_2016_DHS_v01_M
Producer(s)
Bureau of Statistics (UBOS)
Created on
Sep 19, 2018
Last modified
Sep 19, 2018
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- Data files
- RECH0
- RECH1
- RECH2
- RECH3
- RECH4
- RECH5
- RECH5CS
- RECH6
- RECH6CS
- RECH7
- RECH8
- RECH9
- RECHCD
- RECHMA
- RECHMH
- RECHML
- RECHMS
- REC01
- REC4A
- REC11
- REC21
- REC22
- REC31
- REC32
- REC41
- REC42
- REC43
- REC44
- REC51
- REC61
- REC71
- REC75
- REC80
- REC81
- REC82
- REC83
- REC84
- REC91
- REC94
- REC97
- RECDV
- RECML
- MREC01
- MREC11
- MREC22
- MREC31
- MREC32
- MREC41
- MREC51
- MREC61
- MREC71
- MREC75
- MREC80
- MREC91
- MREC92
- FWRECORD
Region of previous residence (mv105a)
Data file: MREC11
Overview
Type:
Discrete
Decimal:
0
Start:
19
End:
21
Width:
3
Range:
-
Format:
Questions and instructions
Categories
| Value | Category |
|---|---|
| 101 | KALANGALA |
| 102 | KAMPALA |
| 103 | KIBOGA |
| 104 | LUWERO |
| 105 | MASAKA |
| 106 | MPIGI |
| 107 | MUBENDE |
| 108 | MUKONO |
| 109 | NAKASONGOLA |
| 110 | RAKAI |
| 111 | SSEMBABULE |
| 112 | KAYUNGA |
| 113 | WAKISO |
| 114 | LYANTONDE |
| 115 | MITYANA |
| 116 | NAKASEKE |
| 117 | BUIKWE |
| 118 | BUKOMANSIMBI |
| 119 | BUTAMBALA |
| 120 | BUVUMA |
| 121 | GOMBA |
| 122 | KALUNGU |
| 123 | KYANKWANZI |
| 124 | LWENGO |
| 201 | BUGIRI |
| 202 | BUSIA |
| 203 | IGANGA |
| 204 | JINJA |
| 205 | KAMULI |
| 206 | KAPCHORWA |
| 207 | KATAKWI |
| 208 | KUMI |
| 209 | MBALE |
| 210 | PALLISA |
| 211 | SOROTI |
| 212 | TORORO |
| 213 | KABERAMAIDO |
| 214 | MAYUGE |
| 215 | SIRONKO |
| 216 | AMURIA |
| 217 | BUDAKA |
| 218 | BUDUDA |
| 219 | BUKEDEA |
| 220 | BUKWO |
| 221 | BUTALEJA |
| 222 | KALIRO |
| 223 | MANAFWA |
| 224 | NAMUTUMBA |
| 225 | BULAMBULI |
| 226 | BUYENDE |
| 227 | KIBUKU |
| 228 | KWEEN |
| 229 | LUUKA |
| 230 | NAMAYINGO |
| 231 | NGORA |
| 232 | SERERE |
| 301 | ADJUMANI |
| 302 | APAC |
| 303 | ARUA |
| 304 | GULU |
| 305 | KITGUM |
| 306 | KOTIDO |
| 307 | LIRA |
| 308 | MOROTO |
| 309 | MOYO |
| 310 | NEBBI |
| 311 | NAKAPIRIPIRIT |
| 312 | PADER |
| 313 | YUMBE |
| 314 | ABIM |
| 315 | AMOLATAR |
| 316 | AMURU |
| 317 | DOKOLO |
| 318 | KAABONG |
| 319 | KOBOKO |
| 320 | MARACHA |
| 321 | OYAM |
| 322 | AGAGO |
| 323 | ALEBTONG |
| 324 | AMUDAT |
| 325 | KOLE |
| 326 | LAMWO |
| 327 | NAPAK |
| 328 | NWOYA |
| 329 | OTUKE |
| 330 | ZOMBO |
| 401 | BUNDIBUGYO |
| 402 | BUSHENYI |
| 403 | HOIMA |
| 404 | KABALE |
| 405 | KABAROLE |
| 406 | KASESE |
| 407 | KIBAALE |
| 408 | KISORO |
| 409 | MASINDI |
| 410 | MBARARA |
| 411 | NTUNGAMO |
| 412 | RUKUNGIRI |
| 413 | KAMWENGE |
| 414 | KANUNGU |
| 415 | KYENJOJO |
| 416 | BULIISA |
| 417 | IBANDA |
| 418 | ISINGIRO |
| 419 | KIRUHURA |
| 420 | BUHWEJU |
| 421 | KIRYANDONGO |
| 422 | KYEGEGWA |
| 423 | MITOOMA |
| 424 | NTOROKO |
| 425 | RUBIRIZI |
| 426 | SHEEMA |
| 996 | Abroad |
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.