Background
The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The Annual Population Survey, also held at the UK Data Archive, is derived from the LFS.

The LFS was first conducted biennially from 1973-1983, then annually between 1984 and 1991, comprising a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter. From 1992 it moved to a quarterly cycle with a sample size approximately equivalent to that of the previous annual data. Northern Ireland was also included in the survey from December 1994. Further information on the background to the QLFS may be found in the documentation.

The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.

LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.

LFS response to COVID-19

From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.

Occupation data for 2021 and 2022 data files

The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.

2024 Reweighting

In February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.

End User Licence and Secure Access QLFS data

Two versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).

The Secure Access version contains more detailed variables relating to:

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• finer detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address
• other additional detailed variables may also be included.

The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

This study was deposited in 2008, as a result of the move from seasonal to calendar quarters for the QLFS, and the reweighting process to 2007-2008 population figures. It combines data from previously-available QLFS seasonal quarter datasets. The depositor has advised that small revisions to the data may have been made during this process, but they should not be significant.

For the second edition (April 2010), the variables Caseno (Case identifier) and Regwkr (Region of place of work) have been added to the dataset. Users should note that, due to the retrospective change from seasonal to calendar quarters, Regwkr will only contain data for the months October and November; December data are not available and are coded as missing ('-5') accordingly.

This report shows monthly numbers of NHS Hospital and Community Health Services (HCHS) staff working in NHS Trusts and CCGs in England (excluding primary care staff). Data are available as headcount and full-time equivalents and for all months from 30 September 2009 onwards. These data are an accurate summary of the validated data extracted from the NHS HR and Payroll system. Additional statistics on staff in NHS Trusts and CCGs and information for NHS Support Organisations and Central Bodies are published each: September (showing June statistics) December/January (showing September statistics) March (showing December statistics) June (showing March statistics) Quarterly NHS Staff Earnings, monthly NHS Staff Sickness Absence reports, and data relating to the General Practice workforce and the Independent Healthcare Provider workforce are also available via the Related Links below. Due to changes to the mapping of some HCHS organisations and GP practices from June 2022 at region level (Integrated Care System, NHS England region and Government Office Region), only the June 2022 data in tables 3 and 4 of the Provisional statistics file fully reflects the new health geographies. The 'Annual change' and 'Annual % change' information for affected regions are marked as 'Not applicable' in these tables. Complete comparable regional time series tables will be included next month in the July 2022 Provisional statistics file, released in September 2022. Further information on these changes can be found at https://digital.nhs.uk/services/organisation-data-service/integrated-care-boards We welcome feedback on the methodology and tables within this publication. Please email us with your comments and suggestions, clearly stating Monthly HCHS Workforce as the subject heading, via enquiries@nhsdigital.nhs.uk or 0300 303 5678.

Organisations that provide specialist mental health services currently make four quarterly MHMDS submissions and one annual submission each year. The submission deadlines are approximately 6 weeks after the end of the quarter and some routine quarterly reports are published 6 to 8 weeks later (an annual report is published in November). The Department of Health's NHS Performance Framework for non-FT mental health trusts was implemented in April 2010. These are the indicators in the framework that use Mental Health Minimum Dataset (MHMDS) quarterly data. The indicator values for all organisations that submit MHMDS, including some independent sector organisations, are presented for information, but it should be noted that only non-FT mental health trusts are performance managed by the Department of Health (DH). June 2011:Please note that the DH has announced amendments to the definitions for 2011/12 which will be implemented from Q1 2011/12.

The Statistics of U.S. Businesses (SUSB) provides detailed annual data for all U.S. business establishments with paid employees by geography, industry, and enterprise size. This program covers all NAICS industries except crop and animal production; rail transportation; National Postal Service; pension, health, welfare, and vacation funds; trusts, estates, and agency accounts; private households; and public administration. The SUSB also excludes most government employees. Further, SUSB data for years 1988-1997 were tabulated based on the Standard Industrial Classification (SIC) system. The SUSB features several arts-related NAICS industries, including the following: Arts, entertainment, and recreation (NAICS Code 71) Performing arts companies Spectator sports Promoters of performing arts, sports, and similar events Independent artists, writers, and performers Museums, historical sites, and similar institutions Amusement parks and arcades Professional, scientific, and technical services (NAICS Code 54) Architectural services Graphic Design Services Landscape architectural services Photographic services Retail trade (NAICS Code 44-45) Sporting goods, hobby, and musical instrument stores Sewing, needlework, and piece goods stores Book stores Art dealers Also, the SUSB features several arts related SIC industries, including the following: Commercial photography (SIC Code 7335) Commercial art and graphic design (SIC Code 7336) Museums and art galleries (SIC Code 8412) Dance studios, schools, and halls (SIC Code 7911) Theatrical producers and services (SIC Code 7922) Sports clubs, managers, & promoters (SIC Code 7941) Motion Picture Production & Services (SIC Code 7810) Data compiled for the SUSB are extracted from the Business Register (BR). The BR contains continuously updated data from the Census Bureau's economic censuses and currently business surveys, quarterly and annual Federal tax records and other department and federal statistics. SUSB data are available approximately 24 months after each reference year and are available for the United States, each state, and Metropolitan Statistical Areas (MSA). The annual SUSB consist of number of firms, number of establishments, annual payroll, and employment during the week of March 12. In addition, estimated receipts data are included for years ending in 2 and 7. Dynamic data, which are created from the Business Information Tracking Series (BITS), consist of the number of establishments and corresponding employment change for births, deaths, expansions, and contractions. The SUSB is important because it provides the only source of annual, complete, and consistent enterprise-level data for U.S. businesses, with industry detail. Private businesses use the data for market research, strategic business planning, and managing sales territories. State and local governments, as well as, budget, economic development, and planning offices use the data to assess business changes, develop fiscal policies, and plan future policies and programs. In addition, the data are the standard reference source for small business statistics. Users can view the latest SUSB annual data and employment change data on the main SUSB page. For more detailed industry and employment size classes, users can download additional data in comma-delimited format. Annual data are tabulated back to 1988 and employment change data back to 1989-1990. Data users can find news and updates about the SUSB data via the News & Updates section.

The outbreak of Coronavirus (COVID-19) in the last quarter of 2019-20 has led to unprecedented changes in the work and behaviour of GP practices and consequently the data in this publication may have been impacted. As such caution should be taken in drawing any conclusions from this data without due consideration of the circumstances both locally and nationally and would recommend that any use of this data is accompanied by an appropriate caveat. The Statement of Fitness for Work (the Med3 form or 'fit note') was introduced in April 2010 across England, Wales and Scotland. It enables healthcare professionals to give advice to their patients about the impact of their health condition on their fitness for work and is used to provide medical evidence for employers or to support a claim to health-related benefits through the Department for Work and Pensions (DWP). A fit note is issued after the first seven days of sickness absence (when patients can self-certify) if the healthcare professional assesses that the patient’s health affects their fitness for work. The healthcare professional can decide the patient is 'unfit for work' or 'may be fit for work subject to the following advice...' with accompanying notes on suggested adjustments or adaptations to the job role or workplace. In 2012, DWP funded a project to provide general practice's with the ability to produce computer-generated fit notes (eMed3) and this included the capability to collect the aggregated data generated. Fit notes are issued to patients by doctors, nurses, physiotherapists, occupational therapists and pharmacists following an assessment of their fitness for work. While they can be written by hand, most fit notes provided by general practice are now computer-generated. This quarterly statistical publication is produced by NHS England in collaboration with The Work and Health Unit, jointly sponsored by the Department for Work and Pensions and the Department of Health. It presents data on electronic fit notes issued in general practices in England for a given period. This is a ‘cumulative’ data collection. Weekly data collected will continue to be added to existing data. All data for all reporting periods is updated in each quarterly publication. From April 2019 all publications will contain data from practices who have TPP as their system supplier (which was not previously available), and accounts for one third of practices in England, consequently publications from this date may not be comparable to previous publications. All GP practices are mapped using current NHS geographies and recent changes may have resulted in a small number of practices not being mapped historically. These are shown as 'Unallocated' but are included in the England total. NHS England will publish data on a quarterly basis in October, January, April and July. 11/07/2024: the summary excel, table 13 was updated with missing text, no data was changed or impacted.

The Statement of Fitness for Work (the Med3 form or 'fit note') was introduced in April 2010 across England, Wales and Scotland. It enables doctors to give advice to their patients about the impact of their health condition on their fitness for work and is used to provide medical evidence for employers or to support a claim to health-related benefits through the Department for Work and Pensions (DWP). A fit note is issued after the first seven days of sickness absence (when patients can self-certify) if the doctor assesses that the patient’s health affects their fitness for work. The doctor can decide the patient is 'unfit for work' or 'may be fit for work subject to the following advice...' with accompanying notes on suggested adjustments or adaptations to the job role or workplace. In 2012, DWP funded a project to provide GPs with the ability to produce computer-generated fit notes (eMed3) and this included the capability to collect the aggregated data generated. Fit notes are issued to patients by doctors following an assessment of their fitness for work. While they can be written by hand, most fit notes provided by a GP are now computer-generated. This quarterly experimental [1] statistical publication is produced by NHS Digital in collaboration with The Work and Health Unit, jointly sponsored by the Department for Work and Pensions and the Department of Health. It presents data on electronic fit notes issued in general practices in England for a given period. This is a ‘cumulative’ data collection. Weekly data collected will continue to be added to existing data. All data for all reporting periods is updated in each quarterly publication. From April 2019 all publications will contain data from practices who have TPP as their system supplier (which was not previously available), and accounts for one third of practices in England, consequently publications from this date may not be comparable to previous publications. All GP practices are mapped using current NHS geographies and recent changes may have resulted in a small number of practices not being mapped historically. These are shown as 'Not allocated' but are included in the England total. NHS Digital will publish data on a quarterly basis in October, January, April and July. [1] Experimental Statistics are series of statistics that are in the testing phase and not yet fully developed and undergoing evaluation

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Households and persons

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes - Special populations: Homeless people, temporarily absent persons, and temporary residents

UNIT DESCRIPTIONS: - Dwellings: Housing stock are living quarters irrespective of ownership, including residential buildings, special houses (like hostels, houses for lonely and old people, children's homes, boarding houses for disabled, school hostels and boarding school), flats, service housings, other living accomodations in other buildings suited for living. - Households: A group of people sharing the same housing unit (or one person living alone), jointly keeping the house, i.e. fully or partially pooling their individual budgets for common expenditures for food and daily living needs or having a common budget who may or may not be related by kinship. - Group quarters: Groups of people living at the same institution (housing unit), sharing meals, without having individual budgets or common consumer expenditures, subject to the same general rules, and usually unelated by kinship.

Universe

All population inside the country, including private and institutional households and their housing conditions

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Statistical Committee of the Kyrgyz Republic

SAMPLE DESIGN: 20% sample drawn by the country: systematic sample of every 5th household or every 5th individual in collective household 10% sample drawn by MPC from the 20% sample: systematic sample of every 2nd household

SAMPLE UNIT: Households

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 476,886 (persons in private and selected households only)

Mode of data collection

Face-to-face [f2f]

Research instrument

There are two forms: "List of residents and their housing conditions" (Form 1) and "Census questionnaire" (Form 2).

Response rate

COVERAGE: 100%

Please note: Data for the period 01 April 2021 to 30 September 2021 for GP practices with Cegedim Healthcare Systems as a system supplier have been under-reported due to a technical issue, therefore suppression may have been applied to CCGs where only 1 practice does not have Cegedim Healthcare Systems as their system supplier. Cegedim accounted for less than 1.5% of practices during this period. The outbreak of Coronavirus (COVID-19) in the last quarter of 2019-20 has led to unprecedented changes in the work and behaviour of GP practices and consequently the data in this publication may have been impacted. As such caution should be taken in drawing any conclusions from this data without due consideration of the circumstances both locally and nationally and would recommend that any use of this data is accompanied by an appropriate caveat. The Statement of Fitness for Work (the Med3 form or 'fit note') was introduced in April 2010 across England, Wales and Scotland. It enables doctors to give advice to their patients about the impact of their health condition on their fitness for work and is used to provide medical evidence for employers or to support a claim to health-related benefits through the Department for Work and Pensions (DWP). A fit note is issued after the first seven days of sickness absence (when patients can self-certify) if the doctor assesses that the patient’s health affects their fitness for work. The doctor can decide the patient is 'unfit for work' or 'may be fit for work subject to the following advice...' with accompanying notes on suggested adjustments or adaptations to the job role or workplace. In 2012, DWP funded a project to provide GPs with the ability to produce computer-generated fit notes (eMed3) and this included the capability to collect the aggregated data generated. Fit notes are issued to patients by doctors following an assessment of their fitness for work. While they can be written by hand, most fit notes provided by a GP are now computer-generated. This quarterly statistical publication is produced by NHS Digital in collaboration with The Work and Health Unit, jointly sponsored by the Department for Work and Pensions and the Department of Health. It presents data on electronic fit notes issued in general practices in England for a given period. This is a ‘cumulative’ data collection. Weekly data collected will continue to be added to existing data. All data for all reporting periods is updated in each quarterly publication. From April 2019 all publications will contain data from practices who have TPP as their system supplier (which was not previously available), and accounts for one third of practices in England, consequently publications from this date may not be comparable to previous publications. All GP practices are mapped using current NHS geographies and recent changes may have resulted in a small number of practices not being mapped historically. These are shown as 'Unallocated' but are included in the England total. NHS Digital will publish data on a quarterly basis in October, January, April and July.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: Place in which people are living/ being sheltered, or are present on census day like a detached house; an apartment flat; a prefabricated house; a tent, a shack, etc.; a hotel, motel, hostel; a train, a boat, a bus, a terminal, etc.; a hospital, a health clinic; a military post, garrison, an officer's club, etc.; a boarding school, a dormitory; a child daycare facility, an orphanage, a nursing home; a prison, a reform school, or other places (a factory, an official office, an embassy, etc.). - Households: Social entities made up of one or more persons, whether bound by kinship or not, living in the same dwelling or in a portion of the same dwelling, participating in the provision of service or management to the household, who make no distinctions among themselves in terms of their income or expenses. - Group quarters: Places such as a hotel, a motel, a hostel, a train, a boat, a bus, a train station, a terminal, a port, a hospital, a health clinic, a military post, a garrison, an officer's club, a boarding school, a dormitory, a nursing home, a child daycare facility, an orphanage, a jail, a reform school, and others (a factory, an official office, an embassy, etc.).

Universe

All the persons present at places that constitute a household, that do not constitute a household like dormitories, military quarters, prisons, hospitals, hotels, etc., and the nomadic population (thus all the population within the boundaries of the country on the census day).

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: State Institute of Statistics of Turkey

SAMPLE SIZE (person records): 3388218.

SAMPLE DESIGN: Systematic random sampling by province

Mode of data collection

Face-to-face [f2f]

Research instrument

Single form with 4 sections: address information, dwelling type information, household questions, and personal characteristics.