6 datasets found
  1. Fertility rate in Pakistan 2012-2022

    • statista.com
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    Statista, Fertility rate in Pakistan 2012-2022 [Dataset]. https://www.statista.com/statistics/383207/fertility-rate-in-pakistan/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Pakistan
    Description

    The total fertility rate in Pakistan decreased by 0.1 children per woman (-2.88 percent) compared to the previous year. As a result, the fertility rate in Pakistan saw its lowest number in 2022 with 3.41 children per woman. Total fertility rates refer to the average number of children that a woman of childbearing age (generally considered 15 to 44 years) can expect to have throughout her reproductive years. Unlike birth rates, which are based on the actual number of live births in a given population, fertility rates are hypothetical (similar to life expectancy), as they assume that current patterns in age-specific fertility will remain constant throughout a woman's reproductive years.Find more statistics on other topics about Pakistan with key insights such as male smoking rate, crude birth rate, and number of refugees residing.

  2. M

    Pakistan Fertility Rate 1950-2025

    • macrotrends.net
    • new.macrotrends.net
    csv
    Updated Feb 28, 2025
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    MACROTRENDS (2025). Pakistan Fertility Rate 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/countries/PAK/pakistan/fertility-rate
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    csvAvailable download formats
    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Pakistan
    Description

    Chart and table of the Pakistan fertility rate from 1950 to 2025. United Nations projections are also included through the year 2100.

  3. Total fertility rates APAC 2024, by country

    • statista.com
    Updated Sep 18, 2024
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    Statista (2024). Total fertility rates APAC 2024, by country [Dataset]. https://www.statista.com/statistics/1171367/apac-total-fertility-rates-by-country-or-region/
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    Dataset updated
    Sep 18, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Asia–Pacific
    Description

    With an average of 4.3 births per woman, Afghanistan had the highest fertility rate throughout the Asia-Pacific region in 2024. Pakistan and Papua New Guinea followed with the second and third-highest fertility rates, respectively. In contrast, South Korea and Hong Kong had the lowest fertility rates across the region. Contraception usage Fertility rates among women in the Asia-Pacific region have fallen throughout recent years. A likely reason is an increase in contraception use. However, contraception usage varies greatly throughout the Asia-Pacific region. Although contraception prevalence is set to increase across South Asia by 2030, women in both East Asia and Southeast Asia had higher contraception usage compared to South Asia in 2019. Women in APAC With the rise of feminism and the advancement of human rights, attitudes towards the role of women have changed in the Asia-Pacific region. Achieving gender equality has become a vital necessity for both men and women throughout the region. Alongside changes in traditional gender roles, women in certain Asia-Pacific countries, such as New Zealand, have become more inclined to marry later in life. Furthermore, the focus for younger women appears to be with having stability in their lives and securing an enjoyable job. This was displayed when female high school students in Japan were questioned about their future life aspirations.

  4. i

    Demographic and Health Survey 1990-1991 - Pakistan

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Jul 6, 2017
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    National Institute of Population Studies (NIPS) (2017). Demographic and Health Survey 1990-1991 - Pakistan [Dataset]. https://datacatalog.ihsn.org/catalog/2575
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    Dataset updated
    Jul 6, 2017
    Dataset authored and provided by
    National Institute of Population Studies (NIPS)
    Time period covered
    1990 - 1991
    Area covered
    Pakistan
    Description

    Abstract

    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

  5. w

    Demographic and Health Survey 2017-2018 - Pakistan

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Feb 26, 2019
    + more versions
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    National Institute of Population Studies (NIPS) (2019). Demographic and Health Survey 2017-2018 - Pakistan [Dataset]. https://microdata.worldbank.org/index.php/catalog/3411
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    Dataset updated
    Feb 26, 2019
    Dataset authored and provided by
    National Institute of Population Studies (NIPS)
    Time period covered
    2017 - 2018
    Area covered
    Pakistan
    Description

    Abstract

    The Pakistan Demographic and Health Survey PDHS 2017-18 was the fourth of its kind in Pakistan, following the 1990-91, 2006-07, and 2012-13 PDHS surveys.

    The primary objective of the 2017-18 PDHS is to provide up-to-date estimates of basic demographic and health indicators. The PDHS provides a comprehensive overview of population, maternal, and child health issues in Pakistan. Specifically, the 2017-18 PDHS collected information on:

    • Key demographic indicators, particularly fertility and under-5 mortality rates, at the national level, for urban and rural areas, and within the country’s eight regions
    • Direct and indirect factors that determine levels and trends of fertility and child mortality
    • Contraceptive knowledge and practice
    • Maternal health and care including antenatal, perinatal, and postnatal care
    • Child feeding practices, including breastfeeding, and anthropometric measures to assess the nutritional status of children under age 5 and women age 15-49
    • Key aspects of family health, including vaccination coverage and prevalence of diseases among infants and children under age 5
    • Knowledge and attitudes of women and men about sexually transmitted infections (STIs), including HIV/AIDS, and potential exposure to risk
    • Women's empowerment and its relationship to reproductive health and family planning
    • Disability level
    • Extent of gender-based violence
    • Migration patterns

    The information collected through the 2017-18 PDHS is intended to assist policymakers and program managers at the federal and provincial government levels, in the private sector, and at international organisations in evaluating and designing programs and strategies for improving the health of the country’s population. The data also provides information on indicators relevant to the Sustainable Development Goals.

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Individual
    • Children age 0-5
    • Woman age 15-49
    • Man age 15-49

    Universe

    The survey covered all de jure household members (usual residents), children age 0-5 years, women age 15-49 years and men age 15-49 years resident in the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling frame used for the 2017-18 PDHS is a complete list of enumeration blocks (EBs) created for the Pakistan Population and Housing Census 2017, which was conducted from March to May 2017. The Pakistan Bureau of Statistics (PBS) supported the sample design of the survey and worked in close coordination with NIPS. The 2017-18 PDHS represents the population of Pakistan including Azad Jammu and Kashmir (AJK) and the former Federally Administrated Tribal Areas (FATA), which were not included in the 2012-13 PDHS. The results of the 2017-18 PDHS are representative at the national level and for the urban and rural areas separately. The survey estimates are also representative for the four provinces of Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan; for two regions including AJK and Gilgit Baltistan (GB); for Islamabad Capital Territory (ICT); and for FATA. In total, there are 13 secondlevel survey domains.

    The 2017-18 PDHS followed a stratified two-stage sample design. The stratification was achieved by separating each of the eight regions into urban and rural areas. In total, 16 sampling strata were created. Samples were selected independently in every stratum through a two-stage selection process. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units at different levels, and by using a probability-proportional-to-size selection at the first stage of sampling.

    The first stage involved selecting sample points (clusters) consisting of EBs. EBs were drawn with a probability proportional to their size, which is the number of households residing in the EB at the time of the census. A total of 580 clusters were selected.

    The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 28 households per cluster was selected with an equal probability systematic selection process, for a total sample size of approximately 16,240 households. The household selection was carried out centrally at the NIPS data processing office. The survey teams only interviewed the pre-selected households. To prevent bias, no replacements and no changes to the pre-selected households were allowed at the implementing stages.

    For further details on sample design, see Appendix A of the final report.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Six questionnaires were used in the 2017-18 PDHS: Household Questionnaire, Woman’s Questionnaire, Man’s Questionnaire, Biomarker Questionnaire, Fieldworker Questionnaire, and the Community Questionnaire. The first five questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Pakistan. The Community Questionnaire was based on the instrument used in the previous rounds of the Pakistan DHS. Comments were solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. The survey protocol was reviewed and approved by the National Bioethics Committee, Pakistan Health Research Council, and ICF Institutional Review Board. After the questionnaires were finalised in English, they were translated into Urdu and Sindhi. The 2017-18 PDHS used paper-based questionnaires for data collection, while computerassisted field editing (CAFE) was used to edit the questionnaires in the field.

    Cleaning operations

    The processing of the 2017-18 PDHS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via IFSS to the NIPS central office in Islamabad. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors. Secondary editing was carried out in the central office, which involved resolving inconsistencies and coding the openended questions. The NIPS data processing manager coordinated the exercise at the central office. The PDHS core team members assisted with the secondary editing. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage as it maximised the likelihood of the data being error-free and accurate. The secondary editing of the data was completed in the first week of May 2018. The final cleaning of the data set was carried out by The DHS Program data processing specialist and completed on 25 May 2018.

    Response rate

    A total of 15,671 households were selected for the survey, of which 15,051 were occupied. The response rates are presented separately for Pakistan, Azad Jammu and Kashmir, and Gilgit Baltistan. Of the 12,338 occupied households in Pakistan, 11,869 households were successfully interviewed, yielding a response rate of 96%. Similarly, the household response rates were 98% in Azad Jammu and Kashmir and 99% in Gilgit Baltistan.

    In the interviewed households, 94% of ever-married women age 15-49 in Pakistan, 97% in Azad Jammu and Kashmir, and 94% in Gilgit Baltistan were interviewed. In the subsample of households selected for the male survey, 87% of ever-married men age 15-49 in Pakistan, 94% in Azad Jammu and Kashmir, and 84% in Gilgit Baltistan were successfully interviewed.

    Overall, the response rates were lower in urban than in rural areas. The difference is slightly less pronounced for Azad Jammu and Kashmir and Gilgit Baltistan. The response rates for men are lower than those for women, as men are often away from their households for work.

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017-18 Pakistan Demographic and Health Survey (2017-18 PDHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017-18 PDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

    Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that

  6. w

    Multiple Indicator Cluster Survey, Punjab 2011 - Pakistan

    • microdata.worldbank.org
    • datacatalog.ihsn.org
    • +1more
    Updated Jan 5, 2015
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    Bureau of Statistics, Planning and Development Department (2015). Multiple Indicator Cluster Survey, Punjab 2011 - Pakistan [Dataset]. https://microdata.worldbank.org/index.php/catalog/2211
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    Dataset updated
    Jan 5, 2015
    Dataset authored and provided by
    Bureau of Statistics, Planning and Development Department
    Time period covered
    2011
    Area covered
    Pakistan
    Description

    Abstract

    The primary objectives of the MICS Punjab 2011 are to: - provide up-to-date information for assessing the situation of children and women in Punjab, including the identification of vulnerable groups/ disparities and formulation of policies and interventions - furnish data needed for monitoring progress toward goals established in the Millennium Declaration and other international commitments as a basis for future action - contribute to the improvement of data and monitoring systems in Punjab and to strengthen technical expertise in the design, implementation, and analysis of such systems - update snapshots of social development - provide data for time series analysis and to ascertain achievements compared to previous MICS surveys - provide benchmark position for new indicators and to develop strong advocacy tools - provide up-to-date data for social sector researchers/ academia

    Geographic coverage

    National

    Analysis unit

    • Household
    • Women aged 15–49 years
    • Children under 5 years

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for the MICS Punjab 2011 was designed by Pakistan Bureau of Statistics (PBS), to provide estimates on a large number of indicators on the situation of women and children including the socio-economic indicators at the provincial level for 9 divisions, 36 districts, 150 tehsils /towns, major cities, other urban and rural areas. The sample design was reviewed for adequacy and soundness by international consultants engaged by UNICEF Pakistan.

    The sample was selected in two stages. Within each of the 287 sampling domains, Enumeration Areas (EA) (enumeration blocks in urban areas or village/ mouzas/ dehs in rural areas) were selected with probability proportional to size. Prior to the survey implementation, a complete listing of households in all the selected EAs was conducted. Based on the total number of households in each EA a systematic sample of 12 households in urban and 16 households in rural areas was randomly drawn. This formed the second stage of sampling. In selected households, all females aged 15-49 years and children under five years were identified for individual interviews. The total sample size for the survey was 102,048 households. The sample was not self-weighting and sample weights were used to report results.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Questionnaires for the MICS Punjab, 2011 were based on MICS4 set of following three model Questionnaires, modified/customised to local conditions and to accommodate additional indicators approved by the Steering Committee.

    1. A Household Questionnaire which was used to collect information on all de jure household members (usual residents), the household, and the dwelling
    2. A Women Questionnaire administered in each household to all women aged 15-49 years
    3. A Child Questionnaire administered to mothers or caretakers for all children under 5 years living in the household

    Cleaning operations

    The data entry and cleaning operation was organized at a central location i.e. Lahore under the supervision of a qualified data management organization. Data were entered using Census and Survey Processing System (CSPro). In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programmes developed under the global MICS4 programme and adapted to the MICS Punjab, Questionnaire were used throughout. The procedures followed for ensuring double data entry and cleaning is depicted in the Flow Chart at Annexure-I. Data processing began almost simultaneously with data collection and was completed within 15 days of completion of field work. Data were analysed using the Statistical Package for Social Sciences (SPSS) software, and the model syntax and tabulation plans developed by UNICEF.

    The data management team produced data quality tables on weekly basis which were shared with BOS on each Friday and discussed on each Saturday. The quality tables included descriptive statistics on key variables for each team based on number of questionnaires entered up to that time. In the light of performance shown by the teams in the quality tables instructions were immediately issued to the teams performing below average. Moreover, to enhance data quality, other corrective steps were also taken including reshuffling of team(s) member(s) reporting inadequately and arranging additional trainings in the field where felt necessary.

    Initial analysis, for cleaning purpose, was carried out by examining frequency distribution of all variables and looking at possible errors in data entry and otherwise. Dummy tables reflecting cross-tables between dependent and independent variables were generated focusing on presenting frequencies and simple bivariate tables. Finally, data was exported from CSPro to SPSS software tabulation programme for construction of analysis files (comprising HH: Household, HL: Household listing, WM: Women and CH: Children); production of tabulations; analysis of sampling errors/ confidence intervals; and production of datasets and tabulations for report writing.

    Response rate

    All 7,250 sampled clusters were successfully surveyed. Out of 102,545 households selected for the survey, 97,995 were found to be occupied. 95,238 were successfully interviewed with a response rate of 97 percent. In interviewed households, 150,814 women aged 15-49 years were identified and 137,938 were successfully interviewed, i.e. response rate of 92 percent. Of the 74,126 children under 5 years listed in household questionnaires, 66,666 child questionnaires were answered with a response rate of 90 percent.The overall response rates for women and children under-five were 89 and 87 percent respectively.

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Statista, Fertility rate in Pakistan 2012-2022 [Dataset]. https://www.statista.com/statistics/383207/fertility-rate-in-pakistan/
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Fertility rate in Pakistan 2012-2022

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Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Pakistan
Description

The total fertility rate in Pakistan decreased by 0.1 children per woman (-2.88 percent) compared to the previous year. As a result, the fertility rate in Pakistan saw its lowest number in 2022 with 3.41 children per woman. Total fertility rates refer to the average number of children that a woman of childbearing age (generally considered 15 to 44 years) can expect to have throughout her reproductive years. Unlike birth rates, which are based on the actual number of live births in a given population, fertility rates are hypothetical (similar to life expectancy), as they assume that current patterns in age-specific fertility will remain constant throughout a woman's reproductive years.Find more statistics on other topics about Pakistan with key insights such as male smoking rate, crude birth rate, and number of refugees residing.

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