Multiple Indicator Cluster Survey, Punjab 2011

Pakistan, 2011

Get Microdata

Reference ID

PAK_2011_MICS-PUN_v01_M

Producer(s)

Bureau of Statistics, Planning and Development Department

Collection(s)

UNICEF Multiple Indicator Cluster Surveys (MICS)

Metadata

Documentation in PDF DDI/XML JSON

Study website

Created on

Jan 05, 2015

Last modified

Jan 05, 2015

Page views

59218

Downloads

7306

Tehsil Code (Cluster information file FBS) (HH1BCo)

Data file: ch

Overview

Valid: 74126

Invalid: 0

Minimum: 1

Maximum: 150

Type: Discrete

Decimal: 0

Start: 313

End: 315

Width: 3

Range: 1 - 150

Format: Numeric

Questions and instructions

Categories

Value	Category	Cases
1	Ahmadpur East	671	0.9%
2	Bahawalpur City	411	0.6%
3	Bahawalpur Sadar	359	0.5%
4	Hasilpur	403	0.5%
5	Khairpur Tammewali	376	0.5%
6	Yazman	773	1%
7	Bahawalnagar	535	0.7%
8	Chishtian	500	0.7%
9	Fortabbas	440	0.6%
10	Haroonabad	432	0.6%
11	Minchinabad	442	0.6%
12	Khanpur	722	1%
13	Liaquat Pur	873	1.2%
14	R.Y. Khan	907	1.2%
15	Sadiqabad	904	1.2%
16	D.G.Khan	1125	1.5%
17	Taunsa	467	0.6%
18	Choubara	648	0.9%
19	Karor Lal Esan	535	0.7%
20	Layyah	711	1%
21	Alipur	470	0.6%
22	Jatoi	508	0.7%
23	Kot Addu	858	1.2%
24	Muzaffar Garh	829	1.1%
25	Jampur	646	0.9%
26	Rajanpur	508	0.7%
27	Rojhan	461	0.6%
28	Chak Jhumra	428	0.6%
29	Allama Iqbal	635	0.9%
30	Jinnah	582	0.8%
31	Lyallpur	613	0.8%
32	Madina	511	0.7%
33	Jaranwala	793	1.1%
34	Sammundri	546	0.7%
35	Tandlian Wala	662	0.9%
36	Chiniot	550	0.7%
37	Bhawana	350	0.5%
38	Lalian	430	0.6%
39	Ahmadpur Sial	479	0.6%
40	18-Hazari	543	0.7%
41	Jhang	881	1.2%
42	Shorkot	455	0.6%
43	Gojra	488	0.7%
44	Kamalia	493	0.7%
45	T.T.Singh	587	0.8%
46	Cantonment Area	267	0.4%
47	Arup	541	0.7%
48	Khiali Shahpur	636	0.9%
49	Nandi Pur	489	0.7%
50	Qila Didar Singh	658	0.9%
51	Nowshera Virkan	483	0.7%
52	Kamoke	546	0.7%
53	Wazirabad	684	0.9%
54	Gujrat	833	1.1%
55	Kharian	692	0.9%
56	Sarai Alamgir	359	0.5%
57	Hafizabad	535	0.7%
58	Pindi Bhattian	412	0.6%
59	Malakwal	324	0.4%
60	Mandi Bahaudin	420	0.6%
61	Phalia	385	0.5%
62	Narowal	644	0.9%
63	Shakargarh	804	1.1%
64	Zafarwal	441	0.6%
65	Daska	586	0.8%
66	Pasrur	755	1%
67	Sambrial	432	0.6%
68	Sialkot	795	1.1%
69	Aziz Bhatti Town	449	0.6%
70	Data Baksh Town	309	0.4%
71	Gulberg Town	176	0.2%
72	Allama Iqbal Town	449	0.6%
73	Nishter Town	561	0.8%
74	Ravi Town	235	0.3%
75	Samanabad Town	229	0.3%
76	Shalimar Town	339	0.5%
77	Wahga Town	485	0.7%
78	Chunian	614	0.8%
79	Kasur	703	0.9%
80	Kot Radha Kishan	388	0.5%
81	Pattoki	684	0.9%
82	Shah Kot	358	0.5%
83	Sangla Hill	344	0.5%
84	Nankana Sahib	580	0.8%
85	Ferozewala	755	1%
86	Muridkay	626	0.8%
87	Safdarabad	340	0.5%
88	Sharq Pur Sharif	367	0.5%
89	Sheikhupura	630	0.8%
90	Bosan	416	0.6%
91	Mumtazabad (Mousa Pak)	609	0.8%
92	Shah Rukn-E-Alam	497	0.7%
93	Sher Shah	484	0.7%
94	Jalalpur Pirwala	484	0.7%
95	Shujabad	427	0.6%
96	Jahanian	351	0.5%
97	Kabirwala	644	0.9%
98	Khanewal	550	0.7%
99	Mian Channu	623	0.8%
100	Dunyapur	276	0.4%
101	Karoor Pacca	304	0.4%
102	Lodhran	492	0.7%
103	Burewala	549	0.7%
104	Mailsi	627	0.8%
105	Vehari	589	0.8%
106	Gujar Khan	464	0.6%
107	Kahuta	269	0.4%
108	Kallar Sayaddan	295	0.4%
109	Kotli Sattian	264	0.4%
110	Murree	251	0.3%
111	Taxila	460	0.6%
112	Potohar	301	0.4%
113	Rawal Town	386	0.5%
114	Attock	270	0.4%
115	Fateh Jang	300	0.4%
116	Hazro	243	0.3%
117	Hasan Abdal	291	0.4%
118	Jand	228	0.3%
119	Pindi Gheb	273	0.4%
120	Chakwal	423	0.6%
121	Choa Saidan Shah	236	0.3%
122	Kallar Kahar	229	0.3%
123	Talagang	235	0.3%
124	Dina	337	0.5%
125	Jhelum	401	0.5%
126	Pind Dadan Khan	314	0.4%
127	Sohawa	284	0.4%
128	Chichawatni	582	0.8%
129	Sahiwal	617	0.8%
130	Depalpur	763	1%
131	Okara	656	0.9%
132	Renala Khurd	383	0.5%
133	Arif Wala	557	0.8%
134	Pakpattan	733	1%
135	Bhalwal	552	0.7%
136	Kot Momen	383	0.5%
137	Sahiwal	353	0.5%
138	Sargodha	767	1%
139	Shahpur	320	0.4%
140	Sillanwali	386	0.5%
141	Bhakkar	445	0.6%
142	Darya Khan	368	0.5%
143	Kalur Kot	317	0.4%
144	Mankera	381	0.5%
145	Khushab	516	0.7%
146	Noorpur	290	0.4%
147	Quaidabad	297	0.4%
148	Essa Khel	223	0.3%
149	Mianwali	363	0.5%
150	Piplan	316	0.4%

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.

Back to Catalog