Families of tax filers; Census families with children by age of children and children by age groups (final T1 Family File; T1FF).

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This project utilized three strategies to investigate the impact of incarceration on families. First, a statewide integrated data system was used to examine impacts of incarceration in a novel way, using administrative data from corrections, juvenile justice, mental health, social services, substance use services, healthcare, and education. Second, researchers linked multi-agency data to address specific research questions regarding impact of incarceration on families, including impact of incarceration on family physical and mental health, children's involvement with the child welfare and juvenile justice systems, family economic status, and school performance. Third, researchers conducted focus groups and family interviews with 77 inmates and 21 inmate family members sampled from three correctional facilities. Researchers identified qualitative themes regarding impact of incarceration in the lives of inmates and their families.Only data from the focus groups is included in this collection. The collection includes two SPSS data files: "Inmate_Demographic_Data.sav" with 15 variables and 77 cases and "Family_Demographic_Data.sav" with 19 variables and 21 cases. The actual focus group interviews with inmates and their family members are not available as part of this collection at this time. Administrative data from the South Carolina Revenue and Fiscal Affairs Office was not made available for archiving. Users interested in obtaining these data should consult the accompanying documentation.

"Enrollment counts are based on the October 31 Audited Register for the 2017-18 to 2019-20 school years. To account for the delay in the start of the school year, enrollment counts are based on the November 13 Audited Register for 2020-21 and the November 12 Audited Register for 2021-22. * Please note that October 31 (and November 12-13) enrollment is not audited for charter schools or Pre-K Early Education Centers (NYCEECs). Charter schools are required to submit enrollment as of BEDS Day, the first Wednesday in October, to the New York State Department of Education." Enrollment counts in the Demographic Snapshot will likely exceed operational enrollment counts due to the fact that long-term absence (LTA) students are excluded for funding purposes. Data on students with disabilities, English Language Learners, students' povery status, and students' Economic Need Value are as of the June 30 for each school year except in 2021-22. Data on SWDs, ELLs, Poverty, and ENI in the 2021-22 school year are as of March 7, 2022. 3-K and Pre-K enrollment totals include students in both full-day and half-day programs. Four-year-old students enrolled in Family Childcare Centers are categorized as 3K students for the purposes of this report. All schools listed are as of the 2021-22 school year. Schools closed before 2021-22 are not included in the school level tab but are included in the data for citywide, borough, and district. Programs and Pre-K NYC Early Education Centers (NYCEECs) are not included on the school-level tab. Due to missing demographic information in rare cases at the time of the enrollment snapshot, demographic categories do not always add up to citywide totals. Students with disabilities are defined as any child receiving an Individualized Education Program (IEP) as of the end of the school year (or March 7 for 2021-22). NYC DOE "Poverty" counts are based on the number of students with families who have qualified for free or reduced price lunch, or are eligible for Human Resources Administration (HRA) benefits. In previous years, the poverty indicator also included students enrolled in a Universal Meal School (USM), where all students automatically qualified, with the exception of middle schools, D75 schools and Pre-K centers. In 2017-18, all students in NYC schools became eligible for free lunch. In order to better reflect free and reduced price lunch status, the poverty indicator does not include student USM status, and retroactively applies this rule to previous years. "The school’s Economic Need Index is the average of its students’ Economic Need Values. The Economic Need Index (ENI) estimates the percentage of students facing economic hardship. The 2014-15 school year is the first year we provide ENI estimates. The metric is calculated as follows: * The student’s Economic Need Value is 1.0 if: o The student is eligible for public assistance from the NYC Human Resources Administration (HRA); o The student lived in temporary housing in the past four years; or o The student is in high school, has a home language other than English, and entered the NYC DOE for the first time within the last four years. * Otherwise, the student’s Economic Need Value is based on the percentage of families (with school-age children) in the student’s census tract whose income is below the poverty level, as estimated by the American Community Survey 5-Year estimate (2020 ACS estimates were used in calculations for 2021-22 ENI). The student’s Economic Need Value equals this percentage divided by 100. Due to differences in the timing of when student demographic, address and census data were pulled, ENI values may vary, slightly, from the ENI values reported in the School Quality Reports. In previous years, student census tract data was based on students’ addresses at the time of ENI calculation. Beginning in 2018-19, census tract data is based on students’ addresses as of the Audited Register date of the g

Families and children in the UK by family type including married couples, cohabiting couples and lone parents. Also shows household size and people living alone.

SA2 based data for Labour Force Status by Sex of Parents by Age of Dependent Children for Couple Families, in General Community Profile (GCP), 2016 Census. Count of dependent children in couple families. Comprises children aged under 15 years and dependent students aged 15-24 years who were present at their usual residence on Census Night. Comprises couple families with both parents present at their usual residence on Census Night. Excludes same-sex couples. G44 is broken up into 6 sections (G44a - G44f), this section contains 'Dependent children Aged 18-20 years Female parent Unemployed looking for Part-time work Male parent Total labour force' - 'Dependent children Aged 21-24 years Female parent Total Male parent Employed Hours worked not stated'. The data is by SA2 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

Children and young persons aged 0-21 and living at home whose families have received economic support at some time during the year by sex, age, background, level of educational attainment of the parent(s), observations and year

LGA based data for Labour Force Status by Sex of Parents by Age of Dependent Children for Couple Families, in General Community Profile (GCP), 2016 Census. Count of dependent children in couple families. Comprises children aged under 15 years and dependent students aged 15-24 years who were present at their usual residence on Census Night. Comprises couple families with both parents present at their usual residence on Census Night. Excludes same-sex couples. G44 is broken up into 6 sections (G44a - G44f), this section contains 'Dependent children Aged 18-20 years Female parent Unemployed looking for Part-time work Male parent Total labour force' - 'Dependent children Aged 21-24 years Female parent Total Male parent Employed Hours worked not stated'. The data is by LGA 2016 boundaries. Periodicity: 5-Yearly. Note: There are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. For more information visit the data source: http://www.abs.gov.au/census.

Children and young persons aged 0-21 and living at home who lives in families with low and high income relative the median, number by sex, age, share of median income, background, level of educational attainment of the parent(s) and year

Abstract

The National Family Health Survey 2019-21 (NFHS-5), the fifth in the NFHS series, provides information on population, health, and nutrition for India, each state/union territory (UT), and for 707 districts.

The primary objective of the 2019-21 round of National Family Health Surveys is to provide essential data on health and family welfare, as well as data on emerging issues in these areas, such as levels of fertility, infant and child mortality, maternal and child health, and other health and family welfare indicators by background characteristics at the national and state levels. Similar to NFHS-4, NFHS-5 also provides information on several emerging issues including perinatal mortality, high-risk sexual behaviour, safe injections, tuberculosis, noncommunicable diseases, and the use of emergency contraception.

The information collected through NFHS-5 is intended to assist policymakers and programme managers in setting benchmarks and examining progress over time in India’s health sector. Besides providing evidence on the effectiveness of ongoing programmes, NFHS-5 data will help to identify the need for new programmes in specific health areas.

The clinical, anthropometric, and biochemical (CAB) component of NFHS-5 is designed to provide vital estimates of the prevalence of malnutrition, anaemia, hypertension, high blood glucose levels, and waist and hip circumference, Vitamin D3, HbA1c, and malaria parasites through a series of biomarker tests and measurements.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 54

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-54, and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

A uniform sample design, which is representative at the national, state/union territory, and district level, was adopted in each round of the survey. Each district is stratified into urban and rural areas. Each rural stratum is sub-stratified into smaller substrata which are created considering the village population and the percentage of the population belonging to scheduled castes and scheduled tribes (SC/ST). Within each explicit rural sampling stratum, a sample of villages was selected as Primary Sampling Units (PSUs); before the PSU selection, PSUs were sorted according to the literacy rate of women age 6+ years. Within each urban sampling stratum, a sample of Census Enumeration Blocks (CEBs) was selected as PSUs. Before the PSU selection, PSUs were sorted according to the percentage of SC/ST population. In the second stage of selection, a fixed number of 22 households per cluster was selected with an equal probability systematic selection from a newly created list of households in the selected PSUs. The list of households was created as a result of the mapping and household listing operation conducted in each selected PSU before the household selection in the second stage. In all, 30,456 Primary Sampling Units (PSUs) were selected across the country in NFHS-5 drawn from 707 districts as on March 31st 2017, of which fieldwork was completed in 30,198 PSUs.

For further details on sample design, see Section 1.2 of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four survey schedules/questionnaires: Household, Woman, Man, and Biomarker were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI).

Cleaning operations

Electronic data collected in the 2019-21 National Family Health Survey were received on a daily basis via the SyncCloud system at the International Institute for Population Sciences, where the data were stored on a password-protected computer. Secondary editing of the data, which required resolution of computer-identified inconsistencies and coding of open-ended questions, was conducted in the field by the Field Agencies and at the Field Agencies central office, and IIPS checked the secondary edits before the dataset was finalized.

Field-check tables were produced by IIPS and the Field Agencies on a regular basis to identify certain types of errors that might have occurred in eliciting information and recording question responses. Information from the field-check tables on the performance of each fieldwork team and individual investigator was promptly shared with the Field Agencies during the fieldwork so that the performance of the teams could be improved, if required.

Response rate

A total of 664,972 households were selected for the sample, of which 653,144 were occupied. Among the occupied households, 636,699 were successfully interviewed, for a response rate of 98 percent.

In the interviewed households, 747,176 eligible women age 15-49 were identified for individual women’s interviews. Interviews were completed with 724,115 women, for a response rate of 97 percent. In all, there were 111,179 eligible men age 15-54 in households selected for the state module. Interviews were completed with 101,839 men, for a response rate of 92 percent.

Children and young persons aged 0-21 and living at home who lives in families with low and high income relative the median by region, sex, age, share of median income and year

The 1996 Nepal Family Health Survey (NFHS) is a nationally representative survey of 8,429 ever- married women age 15-49. The survey is the fifth in a series of demographic and health surveys conducted in Nepal since 1976. The main purpose of the NFHS was to provide detailed information on fertility, family planning, infant and child mortality, and matemal and child health and nutrition. In addition, the NFHS included a series of questions on knowledge of AIDS. The primary objective of the Nepal Family Health Survey (NFHS) is to provide national level estimates of fertility and child mortality. The survey also provides information on nuptiality, contraceptive knowledge and behaviour, the potential demand for contraception, other proximate determinants of fertility, family size preferences, utilization of antenatal services, breastfeeding and food supplementation practices, child nutrition and health, immunizations, and knowledge about Acquired Immune Deficiency Syndrome (AIDS). This information will assist policy-makers, administrators and researchers to assess and evaluate population and health programmes and strategies. The NFHS is comparable to Demographic and Health Surveys (DHS) conducted in other developing countries. MAIN RESULTS FERTILITY Survey results indicate that fertility in Nepal has declined steadily from over 6 births per woman in the mid-1970s to 4.6 births per woman during the period of 1994-1996. Differentials in fertility by place of residence are marked, with the total fertility rate (TFR) for urban Nepal (2.9 births per woman) about two children less than for rural Nepal (4.8 births per woman). The TFR in the Mountains (5.6 births per woman) is about one child higher than the TFR in the Hills and Terai (4.5 and 4.6 births per woman, respectively). By development region, the highest TFR is observed in the Mid-western region (5.5 births per woman) and the lowest TFR in the Eastern region (4.1 births per woman). Fertility decline in Nepal has been influenced in part by a steady increase in age at marriage over the past 25 years. The median age at first marriage has risen from 15.5 years among women age 45-49 to 17.1 years among women age 20-24. This trend towards later marriage is supported by the fact that the proportion of women married by age 15 has declined from 41 percent among women age 45-49 to 14 percent among women age 15-19. There is a strong relationship between female education and age at marriage. The median age at first marriage for women with no formal education is 16 years, compared with 19.8 years for women with some secondary education. Despite the trend towards later age at marriage, childbearing begins early for many Nepalese women. One in four women age 15-19 is already a mother or pregnant with her first child, with teenage childbearing more common among rural women (24 percent) than urban women (20 percent). Nearly one in three adolescent women residing in the Terai has begun childbearing, compared with one in five living in the Mountains and 17 percent living in the Hills. Regionally, the highest level of adolescent childbearing is observed in the Central development region while the lowest is found in the Western region. Short birth intervals are also common in Nepal, with one in four births occurring within 24 months of a previous birth. This is partly due to the relatively short period of insusceptibility, which averages 14 months, during which women are not exposed to the risk of pregnancy either because they are amenorrhoeic or abstaining. By 12-13 months after a birth, mothers of the majority of births (57 percent) are susceptible to the risk of pregnancy. Early childbearing and short birth intervals remain a challenge to policy-makers. NFHS data show that children born to young mothers and those born after short birth intervals suffer higher rates of morbidity and mortality. Despite the decline in fertility, Nepalese women continue to have more children than they consider ideal. At current fertility levels, the average woman in Nepal is having almost 60 percent more births than she wantsthe total wanted fertility rate is 2.9 births per woman, compared with the actual total fertility rate of 4.6 births per woman. Unplanned and unwanted births are often associated with increased mortality risks. More than half(56 percent) of all births in the five-year period before the survey had an increased risk of dying because the mother was too young (under 18 years) or too old (more than 34 years), or the birth was of order 3 or higher, or the birth occurred within 24 months of a previous birth. Nevertheless, the percentage of women who want to stop childbearing in Nepal has increased substantially, from 40 percent in 1981 to 52 percent in 1991 and to 59 percent in 1996. According to the NFHS, 41 percent of currently married women age 15-49 say they do not want any more children, and an additional 18 percent have been sterilized. Furthermore, 21 percent of married women want to wait at least two years for their next child and only 13 percent want to have a child soon, that is, within two years. FAMILY PLANNING Knowledge of family planning is virtually universal in Nepal, with 98 percent of currently married women having heard of at least one method of family planning. This is a five-fold increase over the last two decades (1976-1996). Much of this knowledge comes from media exposure. Fifty-three percent of ever-married women had been exposed to family planning messages on the radio and/or the television and 23 percent have been exposed to messages through the print media. In addition, about one in four women has heard at least one of three specific family planning programmes on the radio. There has been a steady increase in the level of ever use of modern contraceptive method over the past 20 years, from 4 percent of currently married women in 1976, to 27 percent in 1991 and 35 percent in 1996. Among ever-users, female sterilization and male sterilization are the most popular methods (37 percent), indicating that contraceptive methods have been used more for limiting than for spacing births. The contraceptive prevalence rate among currently married women is 29 percent, with the majority of women using modern methods (26 percent). Again, the most widely used method is sterilization (18 percent, male and female combined), followed by injectables (5 percent). Although current use of modern contraceptive methods has risen steadily over the last two decades, the pace of change has been slowest in the most recent years (1991-1996). Current use among currently married non-pregnant women increased from 3 percent in 1976 to 15 percent in 1986 to 24 percent in 1991 and to 29 percent in 1996. While female sterilization increased by only 3 percent from 45 percent of modern methods in 1986 to 46 percent in 1996, male sterilization declined by almost 50 percent from 41 percent to 21 percent over the same period. The level of current use is nearly twice as high in the urban areas (50 percent) as in rural areas (27 percent). Only 18 percent of currently married women residing in the Mountains are currently using contraception, compared with 30 percent and 29 percent living in the Hills and Terai regions, respectively. There is a notable difference in current contraceptive use between the Far-western region (21 percent) and all the other regions, especially the Central and Eastern regions (31 percent each). Educational differences in current use are large, with 26 percent of women with no education currently using contraception, compared with 52 percent of women who have completed their School Leaving Certificate (SLC). In general, as women's level of education rises, they are more likely to use modem spacing methods. The public sector figures prominently as a source of modem contraceptives. Seventy-nine percent of modem method users obtained their methods from a public source, especially hospitals and district clinics (32 percent) and mobile camps (28 percent). The public sector is the predominant source of sterilizations, 1UDs, injectables, and Norplant, and both the public and private sectors are equally important sources of the pill and condoms. Nevertheless, the public sector's share of the market has fallen over the last five years from 93 percent of current users in 1991 to 79 percent in 1996. There is considerable potential for increased family planning use in Nepal. Overall, one in three women has an unmet need for family planning14 percent for spacing and 17 percent for limiting. The total demand for family planning, including those women who are currently using contraception, is 60 percent. Currently, the family planning needs of only one in two women is being met. While the increase in unmet need between 1991 (28 percent) and 1996 (31 percent) was small, there was a 14 percent increase in the percentage of women using any method of family planning and, over the same period, a corresponding increase of 18 percent in the demand for family planning. MATERNAL AND CHILD HEALTH At current mortality levels, one of every 8 children born in Nepal will die before the fifth birthday, with two of three deaths occurring during the first year of life. Nevertheless, NFHS data show that mortality levels have been declining rapidly in Nepal since the eighties. Under-five mortality in the period 0-4 years before the survey is 40 percent lower than it was 10-14 years before the survey, with child mortality declining faster (45 percent) than infant mortality (38 percent). Mortality is consistently lower in urban than in rural areas, with children in the Mountains faring much worse than children living in the Hills and Terai. Mortality is also far worse in the Far-western and Mid-western development regions than in the other regions. Maternal education is strongly related to mortality, and children of highly educated mothers are least likely to die young. For example, infant mortality is nearly

Most indicators throughout Vital Signs are created by acquiring and analyzing data collected from governmental agencies for some public administration purpose, such as 311 calls or housing inspections. However, data from the United States Bureau of the Census remains the best source for demographic and socioeconomic indicators for neighborhoods. The Census Bureau collects a wide variety of information through administration of both the decennial Census and the annual American Community Survey (ACS).

Census Key Statistics Table KS21: Households with limiting long-term illness and dependent children. Note: * A dependent child is a person in a household aged 0 -15 (whether or not in a family) or a person aged 16 - 18 who is a full-time student in a family with parent(s). Cells in this table have been randomly adjusted to avoid the release of confidential data. Census day was 29 April 2001.

This dataset provides Census 2021 estimates that classify households in England and Wales by age of youngest dependent child and by household type. The estimates are as at Census Day, 21 March 2021.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Coverage

Census 2021 statistics are published for the whole of England and Wales. Data are also available in these geographic types:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Dependent children in household and their age

Classifies the number of dependent children in a household, by the age of the youngest child. The age of youngest dependent children is classified as follows:

• Aged 0 to 4 years
• Aged 5 to 9 years
• Aged 10 to 15 years
• Aged 16 to 18 years

Household type

Classifies households in an alternative way to the "household composition" classification used in most standard census results.

The type of family present classifies a household. However, households with more than one family are categorised using this priority order:

• married couple family
• civil partnership couple family
• cohabiting couple family
• lone parent family

Within a family type, a family with dependent children takes priority.

The alternative definitions used in tables that use this classification are:

• married couple household
• same-sex civil partnership couple household
• cohabiting couple household
• lone parent household

(StatCan Product) Counts of families with children and number of children in these families by family type, age of children and level of after-tax LICO. Counts of persons regardless of family type by level of after-tax LICO. Customization details: Counts of families with children (0-17 years) and number of children in these families by family type, age of children and level of after-tax Low Income Cut-Off (LICO) and counts of persons (18-21 years) regardless of family type by level of after-tax LICO for 2008. This information product has been customized to present information by the 10Children and Family Services Authority Areas (CFSA) (map on page 2). The after-tax income data has been presented in Low-Income Cut-Off (LICO) instead of Low Income Measures (LIM). There are 10 tables all together in 5 excel worksheets: Table 1: Children aged 0-5. Number of children by family type and LICO. Table 2: Families with children aged 0-5. Number of families by family type and LICO. Table 3: Children aged 6-12. Number of children by family type and LICO. Table 4: Families with children aged 6-12. Number of families by family type and LICO. Table 5: Children aged 13-17. Number of children by family type and LICO. Table 6: Families with children aged 13-17. Number of families by family type and LICO. Table 7: Children aged 0-17. Number of children by family type and LICO. Table 8: Families with children aged 0-17. Number of families by family type and LICO. Table 9: Persons aged 18-21. Number of persons aged 18-21 by LICO. Table 10: Persons aged 18-21. Number of families with persons aged 18-21 by LICO.

Children and young persons aged 0-21 and living at home whose parents have separated during the year by sex, age, family type, foreign/Swedish background, parents´ income level, observations and year

(StatCan Product) Counts of families with children and number of children in these families by family type, age of children and level of after-tax LICO. Counts of persons regardless of family type by level of after-tax LICO. Customization details: Counts of families with children (0-17 years) and number of children in these families by family type, age of children and level of after-tax Low Income Cut-Off (LICO) and counts of persons (18-21 years) regardless of family type by level of after-tax LICO for 2010. This information product has been customized to present information by the 10Children and Family Services Authority Areas (CFSA) (map on page 2). The after-tax income data has been presented in Low-Income Cut-Off (LICO) instead of Low Income Measures (LIM). There are 10 tables altogether in 5 excel worksheets: Table 1: Children aged 0-5. Number of children by family type and LICO. Table 2: Families with children aged 0-5. Number of families by family type and LICO. Table 3: Children aged 6-12. Number of children by family type and LICO. Table 4: Families with children aged 6-12. Number of families by family type and LICO. Table 5: Children aged 13-17. Number of children by family type and LICO. Table 6: Families with children aged 13-17. Number of families by family type and LICO. Table 7: Children aged 0-17. Number of children by family type and LICO. Table 8: Families with children aged 0-17. Number of families by family type and LICO. Table 9: Persons aged 18-21. Number of persons aged 18-21 by LICO. Table 10: Persons aged 18-21. Number of families with persons aged 18-21 by LICO.

Abstract copyright UK Data Service and data collection copyright owner.

Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

• to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
• to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
• to collect information on previously neglected topics, such as fathers' involvement in children's care and development
• to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
• to emphasise intergenerational links including those back to the parents' own childhood
• to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available

Additional objectives subsequently included for MCS were:

• to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
• to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.
End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).

Release of Sweeps 1 to 4 to Long Format (Summer 2020)To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

Secure Access versions of the MCS...

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

(StatCan Product) Counts of families with children and number of children in these families by family type, age of children and level of after-tax LICO. Counts of persons regardless of family type by level of after-tax LICO. Customization details: Counts of families with children (0-17 years) and number of children in these families by family type, age of children and level of after-tax Low Income Cut-Off (LICO) and counts of persons (18-21 years) regardless of family type by level of after-tax LICO for 2009. This information product has been customized to present information by the 10Children and Family Services Authority Areas (CFSA) (map on page 2). The after-tax income data has been presented in Low-Income Cut-Off (LICO) instead of Low Income Measures (LIM). There are 10 tables all together in 5 excel worksheets: Table 1: Children aged 0-5. Number of children by family type and LICO. Table 2: Families with children aged 0-5. Number of families by family type and LICO. Table 3: Children aged 6-12. Number of children by family type and LICO. Table 4: Families with children aged 6-12. Number of families by family type and LICO. Table 5: Children aged 13-17. Number of children by family type and LICO. Table 6: Families with children aged 13-17. Number of families by family type and LICO. Table 7: Children aged 0-17. Number of children by family type and LICO. Table 8: Families with children aged 0-17. Number of families by family type and LICO. Table 9: Persons aged 18-21. Number of persons aged 18-21 by LICO. Table 10: Persons aged 18-21. Number of families with persons aged 18-21 by LICO.