Chart and table of population level and growth rate for the Quetta, Pakistan metro area from 1950 to 2025.

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.

Background: Short tandem repeats (STRs) have gained considerable attention in family search (Y-chromosomal STRs), complex paternity identification (X-chromosomal STRs), routine forensic personal identification (autosomal STRs) and population genetics. Aim: To explore the forensic characteristics of 23 autosomal STRs included in the Huaxia Platinum system in the South Pakistan Hazara population and investigate the genetic similarities and differences between Hazara and 54 worldwide reference populations. Subjects and methods: Variation of the 23 autosomal STRs included in the Huaxia Platinum system was first investigated and reported in a sample of 261 Quetta Hazara in Balochistan Province, Southwest Pakistan. Results: The combined power of discrimination is 0.999999999999999999999999999 and combined power of exclusion is 0.99999999989596 in Quetta Hazara. Comprehensive population comparisons between Hazara and another 13 Eurasian populations based on genotype data, as well as between Hazara and 54 worldwide populations based on the allele frequency distribution, were conducted. Multidimensional scaling plots, principal component analysis, and neighbour-joining phylogenetic trees consistently demonstrated that Pakistan Hazara harbours close affinities with neighbouring Turkic-speaking populations. Model-based genetic structure analysis further suggests that Quetta Hazara derives about half its ancestry directly from the East Asians. Conclusion: Twenty-five forensic-related markers included in the Huaxia Platinum system can be used for forensic practice in the Central Asia Hazara population. Quetta Hazara has a close genetic relationship with the Turkic-speaking populations of Uyghur and Kazakh. Further whole-genome sequencing of Hazara needs to be conducted to validate the observed genetic structure and reconstruct the fine-scale population history of Hazara.

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 study aims to assess the health-related Quality of Life (HRQOL) and its association with socio-demographic factors among the Afghan refugees residing in Quetta, Pakistan. For this purpose, a cross-sectional, descriptive study design by adopting Euro QOL five dimensions questionnaire (EQ-5D) for the assessment of HRQOL was conducted by approaching Afghan refugees from the camp and other areas of Quetta, Pakistan. Furthermore, this study also involved descriptive analysis to expound participant’s demographic characteristics while inferential statistics (Kruskal-Wallis and Mann–Whitney test, P < 0.05) were used to compare EQ-5D scale scores. All analyses were performed using SPSS v 20. Herein, a total of 729 participants were enrolled and were subsequently (n = 246, 33.7%) categorized based on their age of 22–31 years (31.30 ± 15.40). The results of mean EQ-5D descriptive score (0.85 ± 0.20) and EQ-VAS score (78.60 ± 11.10) indicated better HRQOL in the current study respondents as compared to studies conducted in other refugee camps around the globe. In addition, demographic characteristics including age, marital status, locality, years of living as refugees, life as a refugee residing out of Pakistan, place of residence in Afghanistan, educational qualification, occupation, and arrested for crime were the statistically significant predictors (P < 0.05) of EQ-5D index scores. However, gender, living status, monthly income, preferred place of treatment were non-significant predictors (P > 0.05). The results of current study provided evidence for a model that correlated with participant’s socio-demographic information and HRQOL. Moreover, this study also revealed a baseline assessment for the health status of Afghan refugees, interestingly, these results could be applied for improving HRQOL of the given participants. In conclusion, the HRQOL of Afghan refugees residing in Quetta, Pakistan can largely be improved by providing adequate healthcare facilities, education and employment opportunities, mental and social support, and providing adequate housing and basic necessities of life.

The study aims to assess the health-related Quality of Life (HRQOL) and its association with socio-demographic factors among the Afghan refugees residing in Quetta, Pakistan. For this purpose, a cross-sectional, descriptive study design by adopting Euro QOL five dimensions questionnaire (EQ-5D) for the assessment of HRQOL was conducted by approaching Afghan refugees from the camp and other areas of Quetta, Pakistan. Furthermore, this study also involved descriptive analysis to expound participant’s demographic characteristics while inferential statistics (Kruskal-Wallis and Mann–Whitney test, P < 0.05) were used to compare EQ-5D scale scores. All analyses were performed using SPSS v 20. Herein, a total of 729 participants were enrolled and were subsequently (n = 246, 33.7%) categorized based on their age of 22–31 years (31.30 ± 15.40). The results of mean EQ-5D descriptive score (0.85 ± 0.20) and EQ-VAS score (78.60 ± 11.10) indicated better HRQOL in the current study respondents as compared to studies conducted in other refugee camps around the globe. In addition, demographic characteristics including age, marital status, locality, years of living as refugees, life as a refugee residing out of Pakistan, place of residence in Afghanistan, educational qualification, occupation, and arrested for crime were the statistically significant predictors (P < 0.05) of EQ-5D index scores. However, gender, living status, monthly income, preferred place of treatment were non-significant predictors (P > 0.05). The results of current study provided evidence for a model that correlated with participant’s socio-demographic information and HRQOL. Moreover, this study also revealed a baseline assessment for the health status of Afghan refugees, interestingly, these results could be applied for improving HRQOL of the given participants. In conclusion, the HRQOL of Afghan refugees residing in Quetta, Pakistan can largely be improved by providing adequate healthcare facilities, education and employment opportunities, mental and social support, and providing adequate housing and basic necessities of life.

Demographic profile of the study respondents.