This statistic shows the biggest cities in Pakistan as of 2023. In 2023, approximately ***** million people lived in Karāchi, making it the biggest city in Pakistan.

Population in largest city in Pakistan was reported at 17648555 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

This provincial level data provides population statistics for major cities of Pakistan.

Digital point dataset of Major Cities of Pakistan. This dataset is Basic Vector layer derived from ESRI Map & Data 2001.

Pakistan PK: Population in Largest City data was reported at 15,020,931.000 Person in 2017. This records an increase from the previous number of 14,650,981.000 Person for 2016. Pakistan PK: Population in Largest City data is updated yearly, averaging 6,793,799.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 15,020,931.000 Person in 2017 and a record low of 1,853,325.000 Person in 1960. Pakistan PK: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Population in the largest city (% of urban population) in Pakistan was reported at 18.31 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Pakistan PK: Population in Largest City: as % of Urban Population data was reported at 20.922 % in 2017. This records a decrease from the previous number of 20.928 % for 2016. Pakistan PK: Population in Largest City: as % of Urban Population data is updated yearly, averaging 21.610 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 23.038 % in 1980 and a record low of 18.670 % in 1960. Pakistan PK: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

Major Cities Population

Accessibility to major cities dataset is modelled as raster-based travel time/cost analysis, computed for the 26 largest cities (>250k habitants) in the country. The following cities are included: City - Population Chiniot 278,528 Nawabshah 279,338 Mingora 331,377 Okara 358,146 Kasur 358,296 Mardan 359,024 Wah Cantonment 379,534 Sahiwal 388,795 Gujrat 390,758 Dera Ghazi Khan 397,362 Rahimyar Khan 420,963 Sheikhūpura 473,269 Larkana 488,006 Sukkur 500,401 Sialkot 656,730 Sargodha 658,208 Bahawalpur 762,774 Quetta 999,385 Hyderabad 1,733,622 Multan 1,872,641 Peshawar 1,969,823 Gujranwala 2,028,421 Rawalpindi Islamabad 3,106,827 Faisalabad 3,210,158 Lahore 11,119,985 Karachi 14,884,402 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

This dataset provides information about airbnb listings in Pakistan. The data was taken from airbnb's public websites, for listings in Karachi, Lahore, Islamabad and Rawalpindi. The data is about 3000+ listings and was taken for listings available in the month of February 2023. There are 3 files, for cities Lahore, Karachi and Islamabad/Rawalpindi. And there is a 4th file 'combined', which has the merged data for all of the cities. It also contains spreadsheets for clean data and sheet for listings which are rated.

I created this dataset for a project that I did! Feel free to use it but I would really appreciate if you give credit and cite me :)

Graph and download economic data for Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Commercial Banks for Pakistan (PAKFCBODCLNUM) from 2004 to 2015 about branches, Pakistan, banks, and depository institutions.

The regional cities accessibility dataset is modelled as raster-based travel time/cost analysis. Individual cumulative travel time/cost maps were produced for major regional cities (>850k habitants) less than 500 km from the border.

The following values were assumed: City - Country Delhi 16,349,831

Ahmedabad 5,633,927

Surat 4,591,246

Kabul 4,434,550

Jaipur 3,046,163

Vadodara 1,752,371

Ludhiana 1,618,879

Meerut 1,571,434

Rajkot 1,390,640 Srinagar 1,264,202

Amritsar 1,183,549

Jodhpur 1,138,300

Chandigarh 1,026,459

Kota 1,001,694

Moradabad 889,810

Aligarh 874,408

Dushanbe 863,400

This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location).

Data publication: 2021-10-18

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Dariia Nesterenko

Data lineage:

Produced using OpenStreetMap data for roads, railways, rivers; UN Map country border; The HydroSHEDS 15' resolution GRID for the DEM, GHSL - Global Human Settlement Layer.

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)

Online resources:

Zipped raster TIF file for Accessibility: Travel Time-Cost to Major Regional Cities (Pakistan- ~ 500m)

Abstract

The Pakistan Social and Living Standards Measurement Survey (PSLM) 2005-06 is aimed to provide detailed outcome indicators on Education, Health, Population Welfare, Water & Sanitation and Income & Expenditure. The data provided by this survey is used by the government in formulating the policies in social sector initiated under Poverty Reduction Strategy Paper (PRSP) and Medium Term Development Framework (MTDF) in the overall context of MDGs.

Geographic coverage

National Coverage

Analysis unit

Households and Individuals.

Universe

The universe of this survey consists of all urban and rural areas of the four provinces and Islamabad excluding military restricted areas

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame:

The Federal Bureau of Statistics (FBS) has developed its own urban area frame, which was up-dated in 2003. Each city/town has been divided into enumeration blocks consisting of 200- 250 households identifiable through sketch map. Each enumeration block has been classified into three categories of income groups i.e. low, middle and high keeping in view the living standard of the majority of the people. List of villages published by Population Census Organization obtained as a consequence of Population Census 1998 has been taken as rural frame.

Stratification Plan:

A. Urban Domain: Islamabad, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Bahawalpur, Sargodha, Sialkot, Karachi, Hyderabad, Sukkur, Peshawar and Quetta, have been considered as large sized cities. Each of these cities constitute a separate stratum and has further been sub-stratified according to low, middle and high-income groups. After excluding population of large sized city (s), the remaining urban population in each defunct Division in all the provinces has been grouped together to form a stratum.

B. Rural Domain: Each district in the Punjab, Sindh and NWFP provinces has been grouped together to constitute a stratum. Whereas defunct administrative Division has been treated as stratum in Balochistan province.

Sample Size and Its Allocation: Keeping in view the objectives of the survey the sample size for the four provinces has been fixed at 15453 households comprising 1109 sample village/ enumeration blocks, which is expected to produce reliable results.

Sample Design: A two-stage stratified sample design has been adopted in this survey.

Selection of Primary Sampling Units (PSUs): Villages and enumeration blocks in urban and rural areas respectively have been taken as Primary Sampling Units (PSUs). Sample PSUs have been selected from strata/sub-strata with PPS method of sampling technique.

Selection of Secondary Sampling Units (SSUs): Households within sample PSUs have been taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 16 and 12 from each sample PSU of rural & urban area have been selected respectively using systematic sampling technique with a random start.

Mode of data collection

Face-to-face [f2f]

Research instrument

At both individual and household level, the PSLM Survey collects information on a wide range of topics using an integrated questionnaire. The questionnaire comprises a number of different sections, each of which looks at a particular aspect of household behavior or welfare. Data collected under Round II include education, diarrhea, immunization, reproductive health, pregnancy history, maternity history, family planning, pre and post-natal care and access to basic services.

Cleaning operations

Data quality in PSLM Survey has been ensured through built in system of checking of field work by the supervisors in the field as well as teams from the headquarters. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried at the FBS headquarter Islamabad and the data entry programme used had a number of in built consistency checks.

Data appraisal

To determine the reliability of the estimates, Coefficient of Variation (CV’s) and confidence Limit of important key indicators have been worked out and are attached as Appendix - C of the survey report (provided under Related Materials).

The Pakistan Demographic and Health Survey (PDHS) was fielded on a national basis between the months of December 1990 and May 1991. The survey was carried out by the National Institute of Population Studies with the objective of assisting the Ministry of Population Welfare to evaluate the Population Welfare Programme and maternal and child health services. The PDHS is the latest in a series of surveys, making it possible to evaluate changes in the demographic status of the population and in health conditions nationwide. Earlier surveys include the Pakistan Contraceptive Prevalence Survey of 1984-85 and the Pakistan Fertility Survey of 1975. The primary objective of the Pakistan Demographic and Health Survey (PDHS) was to provide national- and provincial-level data on population and health in Pakistan. The primary emphasis was on the following topics: fertility, nuptiality, family size preferences, knowledge and use of family planning, the potential demand for contraception, the level of unwanted fertility, infant and child mortality, breastfeeding and food supplementation practices, maternal care, child nutrition and health, immunisations and child morbidity. This information is intended to assist policy makers, administrators and researchers in assessing and evaluating population and health programmes and strategies. The PDHS is further intended to serve as a source of demographic data for comparison with earlier surveys, particularly the 1975 Pakistan Fertility Survey (PFS) and the 1984-85 Pakistan Contraceptive Prevalence Survey (PCPS). MAIN RESULTS Until recently, fertility rates had remained high with little evidence of any sustained fertility decline. In recent years, however, fertility has begun to decline due to a rapid increase in the age at marriage and to a modest rise in the prevalence of contraceptive use. The lotal fertility rate is estimated to have fallen from a level of approximately 6.4 children in the early 1980s to 6.0 children in the mid-1980s, to 5.4 children in the late 1980s. The exact magnitude of the change is in dispute and will be the subject of further research. Important differentials of fertility include the degree ofurbanisation and the level of women's education. The total fertility rate is estimated to be nearly one child lower in major cities (4.7) than in rural areas (5.6). Women with at least some secondary schooling have a rate of 3.6, compared to a rate of 5.7 children for women with no formal education. There is a wide disparity between women's knowledge and use of contraceptives in Pakistan. While 78 percent of currently married women report knowing at least one method of contraception, only 21 percent have ever used a method, and only 12 percent are currently doing so. Three-fourths of current users are using a modem method and one-fourth a traditional method. The two most commonly used methods are female sterilisation (4 percent) and the condom (3 percent). Despite the relatively low level of contraceptive use, the gain over time has been significant. Among married non-pregnant women, contraceptive use has almost tripled in 15 years, from 5 percent in 1975 to 14 percent in 1990-91. The contraceptive prevalence among women with secondary education is 38 percent, and among women with no schooling it is only 8 percent. Nearly one-third of women in major cities arc current users of contraception, but contraceptive use is still rare in rural areas (6 percent). The Government of Pakistan plays a major role in providing family planning services. Eighty-five percent of sterilised women and 81 percent of IUD users obtained services from the public sector. Condoms, however, were supplied primarily through the social marketing programme. The use of contraceptives depends on many factors, including the degree of acceptability of the concept of family planning. Among currently married women who know of a contraceptive method, 62 percent approve of family planning. There appears to be a considerable amount of consensus between husbands and wives about family planning use: one-third of female respondents reported that both they and their husbands approve of family planning, while slightly more than one-fifth said they both disapprove. The latter couples constitute a group for which family planning acceptance will require concerted motivational efforts. The educational levels attained by Pakistani women remain low: 79 percent of women have had no formal education, 14 percent have studied at the primary or middle school level, and only 7 percent have attended at least some secondary schooling. The traditional social structure of Pakistan supports a natural fertility pattern in which the majority of women do not use any means of fertility regulation. In such populations, the proximate determinants of fertility (other than contraception) are crucial in determining fertility levels. These include age at marriage, breastfeeding, and the duration of postpartum amenorrhoea and abstinence. The mean age at marriage has risen sharply over the past few decades, from under 17 years in the 1950s to 21.7 years in 1991. Despite this rise, marriage remains virtually universal: among women over the age of 35, only 2 percent have never married. Marriage patterns in Pakistan are characterised by an unusually high degree of consangninity. Half of all women are married to their first cousin and an additional 11 percent are married to their second cousin. Breasffeeding is important because of the natural immune protection it provides to babies, and the protection against pregnancy it gives to mothers. Women in Pakistan breastfeed their children for an average of20months. Themeandurationofpostpartumamenorrhoeais slightly more than 9 months. After tbebirth of a child, women abstain from sexual relations for an average of 5 months. As a result, the mean duration of postpartum insusceptibility (the period immediately following a birth during which the mother is protected from the risk of pregnancy) is 11 months, and the median is 8 months. Because of differentials in the duration of breastfeeding and abstinence, the median duration of insusceptibility varies widely: from 4 months for women with at least some secondary education to 9 months for women with no schooling; and from 5 months for women residing in major cities to 9 months for women in rural areas. In the PDHS, women were asked about their desire for additional sons and daughters. Overall, 40 percent of currently married women do not want to have any more children. This figure increases rapidly depending on the number of children a woman has: from 17 percent for women with two living children, to 52 percent for women with four children, to 71 percent for women with six children. The desire to stop childbearing varies widely across cultural groupings. For example, among women with four living children, the percentage who want no more varies from 47 percent for women with no education to 84 percent for those with at least some secondary education. Gender preference continues to be widespread in Pakistan. Among currently married non-pregnant women who want another child, 49 percent would prefer to have a boy and only 5 percent would prefer a girl, while 46 percent say it would make no difference. The need for family planning services, as measured in the PDHS, takes into account women's statements concerning recent and future intended childbearing and their use of contraceptives. It is estimated that 25 percent of currently married women have a need for family planning to stop childbearing and an additional 12 percent are in need of family planning for spacing children. Thus, the total need for family planning equals 37 percent, while only 12 percent of women are currently using contraception. The result is an unmet need for family planning services consisting of 25 percent of currently married women. This gap presents both an opportunity and a challenge to the Population Welfare Programme. Nearly one-tenth of children in Pakistan die before reaching their first birthday. The infant mortality rate during the six years preceding the survey is estimaled to be 91 per thousand live births; the under-five mortality rate is 117 per thousand. The under-five mortality rates vary from 92 per thousand for major cities to 132 for rural areas; and from 50 per thousand for women with at least some secondary education to 128 for those with no education. The level of infant mortality is influenced by biological factors such as mother's age at birth, birth order and, most importantly, the length of the preceding birth interval. Children born less than two years after their next oldest sibling are subject to an infant mortality rate of 133 per thousand, compared to 65 for those spaced two to three years apart, and 30 for those born at least four years after their older brother or sister. One of the priorities of the Government of Pakistan is to provide medical care during pregnancy and at the time of delivery, both of which are essential for infant and child survival and safe motherhood. Looking at children born in the five years preceding the survey, antenatal care was received during pregnancy for only 30 percent of these births. In rural areas, only 17 percent of births benefited from antenatal care, compared to 71 percent in major cities. Educational differentials in antenatal care are also striking: 22 percent of births of mothers with no education received antenatal care, compared to 85 percent of births of mothers with at least some secondary education. Tetanus, a major cause of neonatal death in Pakistan, can be prevented by immunisation of the mother during pregnancy. For 30 percent of all births in the five years prior to the survey, the mother received a tetanus toxoid vaccination. The differentials are about the same as those for antenatal care generally. Eighty-five percent of the births occurring during the five years preceding the survey were delivered

PK：最大城市人口占城市总人口的百分比在12-01-2017达20.922%，相较于12-01-2016的20.928%有所下降。PK：最大城市人口占城市总人口的百分比数据按年更新，12-01-1960至12-01-2017期间平均值为21.610%，共58份观测结果。该数据的历史最高值出现于12-01-1980，达23.038%，而历史最低值则出现于12-01-1960，为18.670%。CEIC提供的PK：最大城市人口占城市总人口的百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的巴基斯坦 – 表 PK.世行.WDI：人口和城市化进程统计。

Background: The parasitic disease, cystic echinococcosis (CE), is a serious health problem in Pakistan. Risk of disease transmission is increased by economic and political instability, poor living conditions, and limited awareness of hygienic practices. The current study aimed to investigate the community perception and awareness regarding the risk factors of CE in Pakistan, from a One Health perspective.Methods: We conducted a community-based survey involving 454 participants in the major cities of Pakistan. Quantitative data based on knowledge, attitude, and practices (KAP), the One Health concept, risk factors, and community perception of CE among the general population of the major cities of Pakistan were collected. The questions included those related to knowledge, attitude, practices, One Health concept, risk factors, and community perception. The Chi-squared test was applied to determine the associations regarding KAPs across socio-demographic parameters.Results: KAPs had no significant associations with sociodemographic aspects such as age, sex, religion, ethnicity, education, marital status, occupation, or financial status of the participants. The findings indicated a lack of awareness about CE among the participants. Respondents were unaware of the risk factors and the One Health concept of CE. However, the community attitude and perception were positive toward the control of CE.Conclusion: Illiteracy, deficient sanitation systems and lack of awareness are the contributing factors to CE in Pakistan. It is necessary to make the community aware regarding CE and its importance. Increasing this awareness represents an important step toward the eradication and control of CE.

Abstract

The Pakistan Social and Living Standards Measurement (PSLM) Survey is one of the main mechanisms for monitoring the implementation of the Poverty Reduction Strategy Paper (PRSP). It provides a set of representative, population-based estimates of social indicators and their progress under the PRSP. These include intermediate as well as 'output' measures, which assess what is being provided by the social sectors - enrolment rates in education, for example. They include a range of 'outcome' measures, which assess the welfare of the population - Immunisation Rate, for example.

An important objective of the PSLM Survey is to try to establish what the distributional impact of PRSP has been. Policymakers need to know, for example, whether the poor have benefited from the programme or whether increased government expenditure on the social sectors has been captured by the better off.

Geographic coverage

National, excluding military restricted areas.

Analysis unit

• Individual
• Household

Universe

The universe of this survey consists of all urban and rural areas of the four provinces and Islamabad excluding military restricted areas.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: Pakistan Bureau of Statistics (PBS) has developed its own area sampling frame for both Urban and Rural domains. Each city/town is divided into enumeration blocks. Each enumeration block is comprised of 200 to 250 households on the average with well-defined boundaries and maps. The list of enumeration blocks are updated from field on the prescribed proforma by Quick Count technique for urban domain in 2013 and the updated list of villages/mouzas/dehs or its part (block), based on House Listing 2011 for conduct of Population Census are taken as sampling frames. Enumeration blocks are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively.

Stratification Plan Urban Domain: Large cities Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large cities. Each of these cities constitutes a separate stratum, further substratified according to low, middle and high income groups based on the information collected in respect of each enumeration block at the time of demarcation/ updating of urban area sampling frame. Remaining Urban Areas: In all the four provinces after excluding the population of large cities from the population of an administrative division, the remaining urban population is grouped together to form a stratum. Rural Domain: Each administrative district for all four provinces namely Punjab, Sindh, Khyber Pakhtunkhwa (KP) and Balochistan is considered as an independent stratum.

Selection of primary sampling units (PSUs): Enumeration blocks in both Urban and rural domains are taken as Primary Sampling Units (PSUs). Sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In both Urban and Rural domains, the number of households in an enumeration block is considered as measure of size.

Selection of secondary sampling units (SSUs): The listed households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU and 16 from rural sample PSU are selected with equal probability using systematic sampling technique with a random start.

Sample Size and its Allocation: Keeping in view the objectives of the survey, the sample size for the four provinces has been fixed at 5428 sample blocks (PSU’s) comprising 81,992 households (SSU’s), which is expected to produce reliable results at the district level.

Detailed sampling plan is attached as Appendix A of the survey report.

Sampling deviation

It is worth mentioning here that Panjgur district of Balochistan was dropped from the scope of the survey at the allocation stage due to prevailing situation in Panjgur district. While 7 PSUs from Sindh, 13 PSUs from KP and 82 PSUs from Balochistan province ( including Kech district) were dropped from the scope of the survey during execution of the survey due to law and order situation.

Mode of data collection

Face-to-face [f2f]

Research instrument

At both individual and household level, the PSLM Survey collects information on a wide range of topics using an integrated questionnaire. The questionnaire comprises a number of different sections, each of which looks at a particular aspect of household behavior or welfare. Data collected under Round X includes Education, Health, Water & Sanitation and Household Economic Situation & Satisfaction by facilities and services use.

Cleaning operations

Data quality in PSLM Survey has been ensured through built in system of checking of fieldwork by the supervisors in the field as well as teams from the headquarters. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried out at the PBS headquarter Islamabad and the data entry programme used had a number of in built consistency checks.

Abstract

The 2006-07 Pakistan Demographic and Health Survey (PDHS) was undertaken to address the monitoring and evaluation needs of maternal and child health and family planning programmes. The survey was designed with the broad objective to provide policymakers, primarily in the Ministries of Population Welfare and Health, with information to improve programmatic interventions based on empirical evidence. The aim is to provide reliable estimates of the maternal mortality ratio (MMR) at the national level and a variety of other health and population indicators at national, urban-rural, and provincial levels.

The 2006-07 Pakistan Demographic and Health Survey (PDHS) is the fifth in a series of demographic surveys conducted by the National Institute of Population Studies (NIPS) since 1990. However, the PDHS 2006-07 is the second survey conducted as part of the worldwide Demographic andHealth Surveys programme. The survey was conducted under the aegis of the Ministry of Population Welfare and implemented by the National Institute of Population Studies. Other collaborating institutions include the Federal Bureau of Statistics, the Aga Khan University, and the National Committee for Maternal and Neonatal Health. Technical support was provided by Macro International Inc. and financial support was provided by the United States Agency for International Development (USAID). The United Nations Population Fund (UNFPA) and United Nations Children's Fund (UNICEF) provided logistical support for monitoring the fieldwork for the PDHS.

The 2006-07 PDHS supplements and complements the information collected through the censuses and demographic surveys conducted by the Federal Bureau of Statistics. It updates the available information on population and health issues, and provides guidance in planning, implementing, monitoring and evaluating health and population programmes in Pakistan. Some of the findings of the PDHS may seem at variance with data compiled by other sources. This may be due to differences in methodology, reference period, wording of questions and subsequent interpretation. This fact may be kept in mind while analyzing and comparing PDHS data with other sources. The results of the survey assist in the monitoring of the progress made towards meeting the Millennium Development Goals (MDGs).

The 2006-07 PDHS includes topics related to fertility levels and determinants, family planning, fertility preferences, infant, child and maternal mortality and their causes, maternal and child health, immunization and nutritional status of mothers and children, knowledge of HIV/AIDS, and malaria. The 2006-07 PDHS also includes direct estimation of maternal mortality and its causes at the national level for the first time in Pakistan. The survey provides all other estimates for national, provincial and urban-rural domains. This being the fifth survey of its kind, there is considerable trend information on reproductive health, fertility and family planning over the past one and a half decades.

More specifically, PDHS had the following objectives: - Collect quality data on fertility levels and preference, family planning knowledge and use, childhood—and especially neonatal—mortality levels and awareness regarding HIV/ AIDS and other indicators relevant to the Millennium Development Goals and the Poverty Reduction Strategy Paper; - Produce a reliable national estimate of the MMR for Pakistan, as well as information on the direct and indirect causes of maternal deaths using verbal autopsy instruments; - Investigate factors that impact on maternal and neonatal morbidity and mortality (i.e., antenatal and delivery care, treatment of pregnancy complications, and postnatal care); - Improve the capacity of relevant organizations to implement surveys and analyze and disseminate survey findings.

Geographic coverage

The survey provides estimates at national, urban and rural, and provincial levels (each as a separate domain).

The sample for the 2006-07 PDHS represents the population of Pakistan excluding the Federally Administered Northern Areas (FANA) and restricted military and protected areas. Although the Federally Administered Tribal Areas (FATA) were initially included in the sample, due to security and political reasons, it was not possible to cover any of the sample points in the FATA.

In urban areas, cities like Karachi, Lahore, Gujranwala, Faisalbad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta, and Islamabad were considered as large-sized cities.

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

The 2006-07 PDHS is the largest-ever household based survey conducted in Pakistan. The sample is designed to provide reliable estimates for a variety of health and demographic variables for various domains of interest. The survey provides estimates at national, urban and rural, and provincial levels (each as a separate domain). One of the main objectives of the 2006-07 Pakistan Demographic and Health Survey (PDHS) is to provide a reliable estimate of the maternal mortality ratio (MMR) at the national level. In order to estimate MMR, a large sample size was required. Based on prior rough estimates of the level of maternal mortality in Pakistan, a sample of about 100,000 households was proposed to provide estimates of MMR for the whole country. For other indicators, the survey is designed to produce estimates at national, urban-rural, and provincial levels (each as a separate domain). The sample was not spread geographically in proportion to the population; rather, the smaller provinces (e.g., Balochistan and NWFP) as well as urban areas were over-sampled. As a result of these differing sample proportions, the PDHS sample is not self-weighting at the national level.

The sample for the 2006-07 PDHS represents the population of Pakistan excluding the Federally Administered Northern Areas (FANA) and restricted military and protected areas. Although the Federally Administered Tribal Areas (FATA) were initially included in the sample, due to security and political reasons, it was not possible to cover any of the sample points in the FATA.

In urban areas, cities like Karachi, Lahore, Gujranwala, Faisalbad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta, and Islamabad were considered as large-sized cities. Each of these cities constitutes a stratum, which has further been substratified into low, middle, and high-income groups based on the information collected during the updating of the urban sampling frame. After excluding the population of large-sized cities from the population of respective former administrative divisions, the remaining urban population within each of the former administrative divisions of the four provinces was grouped together to form a stratum.

In rural areas, each district in Punjab, Sindh, and NWFP provinces is considered as an independent stratum. In Balochistan province, each former administrative division has been treated as a stratum. The survey adopted a two-stage, stratified, random sample design. The first stage involved selecting 1,000 sample points (clusters) with probability proportional to size-390 in urban areas and 610 in rural areas. A total of 440 sample points were selected in Punjab, 260 in Sindh, 180 in NWFP, 100 in Balochistan, and 20 in FATA. In urban areas, the sample points were selected from a frame maintained by the FBS, consisting of 26,800 enumeration blocks, each including about 200-250 households. The frame for rural areas consists of the list of 50,588 villages/mouzas/dehs enumerated in the 1998 population census.

The FBS staff undertook the task of a fresh listing of the households in the selected sample points. Aside from 20 sample points in FATA, the job of listing of households could not be done in four areas of Balochistan due to inability of the FBS to provide household listings because of unrest in those areas. Another four clusters in NWFP could not be covered because of resistance and refusal of the community. In other words, the survey covered a total of 972 sample points.

The second stage of sampling involved selecting households. In each sample point, 105 households were selected by applying a systematic random sampling technique. This way, a total of 102,060 households were selected. Out of 105 sampled households, ten households in each sample point were selected using a systematic random sampling procedure to conduct interviews for the Long Household and the Women's Questionnaires. Any ever-married woman aged 12-49 years who was a usual resident of the household or a visitor in the household who stayed there the night before the survey was eligible for interview.

Mode of data collection

Face-to-face

Research instrument

The following six types of questionnaires were used in the PDHS: - Community Questionnaire - Short Household Questionnaire - Long Household Questionnaire - Women’s Questionnaire - Maternal Verbal Autopsy Questionnaire - Child Verbal Autopsy Questionnaire

The contents of the Household and Women’s Questionnaires were based on model questionnaires developed by the MEASURE DHS programme, while the Verbal Autopsy Questionnaires were developed by Pakistani experts and the Community Questionnaire was patterned on the basis of one used by NIPS in previous surveys.

NIPS developed the draft questionnaires in consultation with a broad spectrum of technical experts, government agencies, and local and international organizations so as to reflect relevant issues of population, family planning, HIV/AIDS, and other health areas. A number of meetings were organized

Abstract

The major aim of the survey is to collect a set of comprehensive statistics on the various dimensions of country’s civilian labour force as a means to pave the way for skill development, planning, employment generation, assessing the role and importance of the informal sector and, sizing up the volume, characteristics and contours of employment. The broad objectives of the survey are as follows: - To collect data on the socio-demographic characteristics of the total population i.e. age, sex, marital status, level of education, current enrolment and migration etc; - To acquire current information on the dimensions of national labour force; i.e. number of persons employed, unemployed, and underemployed or out of labour market; - To gather descriptive facts on the engagement in major occupational trades and the nature of work undertaken by the institutions/organizations; - To profile statistics on employment status of the individuals, i.e. whether they are employers, own account workers, contributing family workers or paid employees (regular/casual); - To classify non-agricultural enterprises employing household member(s) as formal and informal; - To quantify the hours worked at main/subsidiary occupations; - To provide data on wages and mode of payment for paid employees; - To make an assessment of occupational health and safety of employed persons by causes, type of treatment, conditions that caused the accident/injury and time of recovery; and - To collect data on the characteristics of unemployed persons i.e. age, sex, level of education, previous experience if any, occupation, industry, employment status related to previous job, waiting time invested in the quest for work, their availability for work and expectations for future employment.

Geographic coverage

National coverage.

The survey covers all urban and rural areas of the four provinces of Pakistan defined as such by1998 Population Census, excluding Federally Administered Tribal Areas (FATA) and military restricted areas. The population of excluded areas constitutes about 2% of the total population.

All sample enumeration blocks in urban areas and mouzas/dehs/villages in rural areas were enumerated except three sample areas (PSUs), due to law & order and recent flood. However, the number of sample households enumerated (36420) is high (equivalent) 99.9% of the total sample size) to the estimated sample size (36464).

Analysis unit

• Individual aged 10 years and above
• Household

Universe

The universe for Labour Force Survey consistsed of all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census excluding FATA and military restricted areas. The population of excluded areas constitutes about 2% of the total population. The following groups were also excluded non-settled population, persons living in institutions and foreigners.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Quarterly.

Sampling procedure

Sample Design: A stratified two-stage sample design is adopted for the survey.

Sampling Frame: Federal Bureau of Statistics (FBS) has developed its own sampling frame for urban areas. Each city/town is divided into enumeration blocks. Each enumeration block is comprised of 200 to 250 households on the average with well-defined boundaries and maps. The list of enumeration blocks as updated through Economic Census 2003 and the list of villages/mouzas/dehs of 1998 Population Census are taken as sampling frames. Enumeration blocks & villages are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively.

Stratification Plan - Urban Domain: Large cities Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large cities. Each of these cities constitutes a separate stratum, further sub-stratified according to low, middle and high income groups based on the information collected in respect of each enumeration block at the time of demarcation/ updating of urban area sampling frame.

• Remaining Urban Areas: In all the four provinces after excluding the population of large cities from the population of an administrative division, the remaining urban population is grouped together to form a stratum.

• Rural Domain: Each administrative district in the Punjab, Sindh and Khyber Pakhtunkhwa (KP) is considered an independent stratum whereas in Balochistan, each administrative division constitutes a stratum.

• Selection of primary sampling units (PSUs): Enumeration blocks in urban domain and mouzas/dehs/villages in rural are taken as Primary Sampling Units (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in an enumeration block as updated through Economic Census 2003 and village population of 1998 Census for rural domain is considered as measure of size.

• Selection of secondary sampling units (SSUs): The listed households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU, 16 from rural sample PSU are selected with equal probability using systematic sampling technique with a random start.

• Sample Size and Its Allocation: A sample of 36,464 households is considered appropriate to provide reliable estimates of key labour force characteristics at National/Provincial level. The entire sample of households (SSUs) is drawn from 2580 Primary Sampling Units (PSUs) out of which 1204 are urban and 1376 are rural. The overall sample has been distributed evenly over four quarters independently. As urban population is more heterogeneous therefore, a higher proportion of sample size is allocated to urban domain. To produce reliable estimates, a higher proportion of sample is assigned to Khyber Pk and Balochistan in consideration to their smallness. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province is made proportionately.

Mode of data collection

Face-to-face [f2f]

Research instrument

Structured questionnaire.

Cleaning operations

Editing and coding is done at headquarter by the subject matter section. Computer edit checks are applied to get even with errors identified at the stage of data entry. The relevant numerical techniques are used to eliminate erroneous data resulting from mistakes made during coding. The survey records are further edited and rectified through a series of computer processing stages.

Response rate

99.9%

Data appraisal

Notwithstanding complete observance of the requisite codes to ensure reliability of data, co-efficient of variations, computed in the backdrop of 5% margin of error exercised for determining sample size, are also given below to affirm the reliability of estimates.