The table shows the number of people receiving social security benefits. These persons can live both in the Netherlands and abroad. These are persons receiving benefits for incapacity for work, unemployment, old age, social assistance and social assistance-related benefits. Persons receiving disability, unemployment, social assistance and assistance-related benefits will be available from 2007. The number of people receiving an old-age benefit has been included in the table since 2013. It is possible for a person to claim multiple benefits. These may be benefits of the same type (e.g. two disability benefits: WIA, WAZ, Wajong or WAO) or benefits of different types (such as benefits under the Unemployment Act (WW) and social assistance benefits). In the latter case, the person is included in both types of benefits. In the first case, only once (in the case of invalidity benefits). In the total counts, the person is of course only counted once. As of October 2021, there has been an increase in the number of WGA benefits. The reason for this is a quality improvement of the process so that a group of self-risk carriers that were previously missing are now included. This is not an increase in the regular number of WGA benefits, but an increase in "persons with a WGA benefit". The figures are broken down by different regions in the Netherlands and refer to the last day of the reporting period.

The figures on numbers of people receiving benefits per neighbourhood, district or municipality may differ slightly from figures published elsewhere on StatLine, because the most recent data from the Personal Records Database (BRP) is used. Because different StatLine tables are updated at different times, it may happen that a different version of the BRP is used for one table than for another table. In this case, the most recent published figures are the most accurate. The figures refer to the last day of the reporting month.

Status of figures The figures can be both provisional and definitive. The monthly figures are end-of-year figures. After one to two years, the figures become final.

Changes as of 29 March 2024: Added are: Further preliminary figures from July to September 2023.

When will there be new figures? New figures will come in July 2024.

Abstract copyright UK Data Service and data collection copyright owner.The Family Resources Survey (FRS) has been running continuously since 1992 to meet the information needs of the Department for Work and Pensions (DWP). It is almost wholly funded by DWP. The FRS collects information from a large, and representative sample of private households in the United Kingdom (prior to 2002, it covered Great Britain only). The interview year runs from April to March.The focus of the survey is on income, and how much comes from the many possible sources (such as employee earnings, self-employed earnings or profits from businesses, and dividends; individual pensions; state benefits, including Universal Credit and the State Pension; and other sources such as savings and investments). Specific items of expenditure, such as rent or mortgage, Council Tax and water bills, are also covered.Many other topics are covered and the dataset has a very wide range of personal characteristics, at the adult or child, family and then household levels. These include education, caring, childcare and disability. The dataset also captures material deprivation, household food security and (new for 2021/22) household food bank usage. The FRS is a national statistic whose results are published on the gov.uk website. It is also possible to create your own tables from FRS data, using DWP’s Stat Xplore tool. Further information can be found on the gov.uk Family Resources Survey webpage. Safe Room Access FRS data In addition to the standard End User Licence (EUL) version, Safe Room access datasets, containing unrounded data and additional variables, are also available for FRS from 2005/06 onwards - see SN 7196, where the extra contents are listed. The Safe Room version also includes secure access versions of the Households Below Average Income (HBAI) and Pensioners' Incomes (PI) datasets. The Safe Room access data are currently only available to UK HE/FE applicants and for access at the UK Data Archive's Safe Room at the University of Essex, Colchester. Prospective users of the Safe Room access version of the FRS/HBAI/PI will need to fulfil additional requirements beyond those associated with the EUL datasets. Full details of the application requirements are available from Guidance on applying for the Family Resources Survey: Secure Access.FRS, HBAI and PIThe FRS underpins the related Households Below Average Income (HBAI) dataset, which focuses on poverty in the UK, and the related Pensioners' Incomes (PI) dataset. The EUL versions of HBAI and PI are held under SNs 5828 and 8503 respectively. The secure access versions are held within the Safe Room FRS study under SN 7196 (see above). The FRS aims to: support the monitoring of the social security programme; support the costing and modelling of changes to national insurance contributions and social security benefits; provide better information for the forecasting of benefit expenditure. From April 2002, the FRS was extended to include Northern Ireland. Detailed information regarding anonymisation within the FRS can be found in User Guide 2 of the dataset documentation. For the second edition (October 2014) the data have been re-grossed following revision of the FRS grossing methodology to take account of the 2011 Census mid-year population estimates. New variable GROSS4 has been added to the dataset. Main Topics: Household characteristics (composition, tenure type); tenure and housing costs including Council Tax, mortgages, insurance, water and sewage rates; welfare/school milk and meals; educational grants and loans; children in education; informal care (given and received); childcare; occupation and employment; health restrictions on work; children's health; National Health Service treatment; wage details; self-employed earnings; personal and occupational pension schemes; income and benefit receipt; income from pensions and trusts, royalties and allowances, maintenance and other sources; income tax payments and refunds; National Insurance contributions; earnings from odd jobs; children's earnings; interest and dividends; investments; National Savings products; assets; vehicle ownership. Standard Measures Standard Occupational Classification Multi-stage stratified random sample Face-to-face interview Computer Assisted Personal Interviewing 2005 2006 ABSENTEEISM ACADEMIC ACHIEVEMENT ADMINISTRATIVE AREAS AGE APARTMENTS APPLICATION FOR EMP... APPOINTMENT TO JOB ATTITUDES BANK ACCOUNTS BEDROOMS BONDS BONUS PAYMENTS BUILDING SOCIETY AC... BUSES BUSINESS RECORDS CARE OF DEPENDANTS CARE OF THE DISABLED CARE OF THE ELDERLY CARS CHARITABLE ORGANIZA... CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILD MINDERS CHILD MINDING CHILD SUPPORT PAYMENTS CHILD WORKERS CHILDREN CHRONIC ILLNESS COHABITATION COLOUR TELEVISION R... COMMERCIAL BUILDINGS CONCESSIONARY TELEV... CONSUMPTION CONTACT LENSES COUNCIL TAX CREDIT UNIONS Consumption and con... DAY NURSERIES DEBILITATIVE ILLNESS DEBTS DENTISTS DISABILITIES DISABILITY DISCRIMI... DISABLED CHILDREN DISABLED PERSONS DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATION EDUCATIONAL BACKGROUND EDUCATIONAL FEES EDUCATIONAL GRANTS EDUCATIONAL INSTITU... EDUCATIONAL VOUCHERS ELDERLY EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ETHNIC GROUPS EXPENDITURE EYESIGHT TESTS FAMILIES FAMILY MEMBERS FINANCIAL DIFFICULTIES FINANCIAL INSTITUTIONS FINANCIAL RESOURCES FINANCIAL SUPPORT FOOD FREE SCHOOL MEALS FRIENDS FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION Family life and mar... GENDER GIFTS GRANDPARENTS GRANTS HEADS OF HOUSEHOLD HEALTH HEALTH SERVICES HEARING IMPAIRED PE... HEARING IMPAIRMENTS HIGHER EDUCATION HOLIDAY LEAVE HOME BASED WORK HOME OWNERSHIP HOME SHARING HOURS OF WORK HOUSEHOLD BUDGETS HOUSEHOLD HEAD S OC... HOUSEHOLDS HOUSING HOUSING FACILITIES HOUSING FINANCE HOUSING TENURE INCOME INCOME TAX INDUSTRIES INSURANCE INSURANCE PREMIUMS INTEREST FINANCE INVESTMENT INVESTMENT RETURN Income JOB DESCRIPTION JOB HUNTING JOB SEEKER S ALLOWANCE LANDLORDS LEAVE LOANS LODGERS MANAGERS MARITAL STATUS MARRIED WOMEN MARRIED WOMEN WORKERS MATERNITY LEAVE MATERNITY PAY MEDICAL PRESCRIPTIONS MORTGAGE PROTECTION... MORTGAGES MOTORCYCLES NEIGHBOURS Northern Ireland OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS ONE PARENT FAMILIES OVERTIME PARENTS PART TIME COURSES PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PASSENGERS PATERNITY LEAVE PENSION CONTRIBUTIONS PENSIONS PHYSICALLY DISABLED... PHYSICIANS POVERTY PRIVATE EDUCATION PRIVATE PERSONAL PE... PRIVATE SCHOOLS PROFITS QUALIFICATIONS RATES REBATES REDUNDANCY REDUNDANCY PAY RENTED ACCOMMODATION RENTS RESIDENTIAL MOBILITY RETIREMENT ROOM SHARING ROOMS ROYALTIES SAVINGS SAVINGS ACCOUNTS AN... SCHOLARSHIPS SCHOOL MILK PROVISION SCHOOLCHILDREN SCHOOLS SEASONAL EMPLOYMENT SECONDARY EDUCATION SECONDARY SCHOOLS SELF EMPLOYED SEWAGE DISPOSAL AND... SHARES SHIFT WORK SICK LEAVE SICK PAY SICK PERSONS SOCIAL CLASS SOCIAL HOUSING SOCIAL SECURITY SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIAL SERVICES SOCIAL SUPPORT SOCIO ECONOMIC STATUS SPECIAL EDUCATION SPECTACLES SPOUSES STATE EDUCATION STATE HEALTH SERVICES STATE RETIREMENT PE... STUDENT HOUSING STUDENT LOANS STUDENTS STUDY SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS Social stratificati... TAXATION TELEVISION LICENCES TELEVISION RECEIVERS TEMPORARY EMPLOYMENT TENANCY AGREEMENTS TENANTS HOME PURCHA... TERMINATION OF SERVICE TIED HOUSING TIME TOP MANAGEMENT TRAINING UNEARNED INCOME UNEMPLOYED UNEMPLOYMENT BENEFITS UNFURNISHED ACCOMMO... UNWAGED WORKERS VEHICLES VISION IMPAIRMENTS VISUALLY IMPAIRED P... VOCATIONAL EDUCATIO... VOLUNTARY WORK WAGES WIDOWED WORKING MOTHERS WORKING WOMEN property and invest...

A. SUMMARY This dataset includes data on a variety of substance use services funded by the San Francisco Department of Public Health (SFDPH). This dataset only includes Drug MediCal-certified residential treatment, withdrawal management, and methadone treatment. Other private non-Drug Medi-Cal treatment providers may operate in the city. Withdrawal management discharges are inclusive of anyone who left withdrawal management after admission and may include someone who left before completing withdrawal management.

This dataset also includes naloxone distribution from the SFDPH Behavioral Health Services Naloxone Clearinghouse and the SFDPH-funded Drug Overdose Prevention and Education program. Both programs distribute naloxone to various community-based organizations who then distribute naloxone to their program participants. Programs may also receive naloxone from other sources. Data from these other sources is not included in this dataset.

Finally, this dataset includes the number of clients on medications for opioid use disorder (MOUD).

The number of people who were treated with methadone at a Drug Medi-Cal certified Opioid Treatment Program (OTP) by year is populated by the San Francisco Department of Public Health (SFDPH) Behavioral Health Services Quality Management (BHSQM) program. OTPs in San Francisco are required to submit patient billing data in an electronic medical record system called Avatar. BHSQM calculates the number of people who received methadone annually based on Avatar data. Data only from Drug MediCal certified OTPs were included in this dataset.

The number of people who receive buprenorphine by year is populated from the Controlled Substance Utilization Review and Evaluation System (CURES), administered by the California Department of Justice. All licensed prescribers in California are required to document controlled substance prescriptions in CURES. The Center on Substance Use and Health calculates the total number of people who received a buprenorphine prescription annually based on CURES data. Formulations of buprenorphine that are prescribed only for pain management are excluded.

People may receive buprenorphine and methadone in the same year, so you cannot add the Buprenorphine Clients by Year, and Methadone Clients by Year data together to get the total number of unique people receiving medications for opioid use disorder.

For more information on where to find treatment in San Francisco, visit findtreatment-sf.org. 

B. HOW THE DATASET IS CREATED This dataset is created by copying the data into this dataset from the SFDPH Behavioral Health Services Quality Management Program, the California Controlled Substance Utilization Review and Evaluation System (CURES), and the Office of Overdose Prevention.

C. UPDATE PROCESS Residential Substance Use Treatment, Withdrawal Management, Methadone, and Naloxone data are updated quarterly with a 45-day delay. Buprenorphine data are updated quarterly and when the state makes this data available, usually at a 5-month delay.

D. HOW TO USE THIS DATASET Throughout the year this dataset may include partial year data for methadone and buprenorphine treatment. As both methadone and buprenorphine are used as long-term treatments for opioid use disorder, many people on treatment at the end of one calendar year will continue into the next. For this reason, doubling (methadone), or quadrupling (buprenorphine) partial year data will not accurately project year-end totals.

E. RELATED DATASETS Overdose-Related 911 Responses by Emergency Medical Services Unintentional Overdose Death Rates by Race/Ethnicity Preliminary Unintentional Drug Overdose Deaths

US Adult COVID-19 Impact Survey Data

Regional, Socio-Economic, and Health Effects

By Meghan Hoyer [source]

About this dataset

The Associated Press is proud to present the COVID Impact Survey, a statistical survey providing data on how the coronavirus pandemic has affected people in the United States. Conducted by NORC at the University of Chicago with sponsorship from the Data Foundation and Federal Reserve Bank of Minneapolis, this probability-based survey offers valuable insight into three core areas related to physical health, economic and financial security, and social and mental health.

Through this vital survey data, we can gain a better understanding of how individuals are dealing with symptoms related to COVID-19, their financial situation during this time period as well as changes in employment or government assistance policies, food security ization (in both nationwide & regional scope), communication with friends and family members, anxiety levels & if people are volunteering more during pandemic restrictions; furthermore gaining an overall comprehensive snapshot into what factors are impacting public perception regarding COVID-19’s effect on US citizens.

Using these insights it's possible to track metrics over time - Observing which issues Americans face everyday but also long-term effects such as mental distress or self sacrificing volunteer activities that appear due to underlying stress factors. It’s imperative that we properly weight our analysis when using this data & never report raw numbers; instead we must apply queries using statistical software such R/SPSS - thus being able to find results nationally as well as within 10 states + metropolitan areas across America whilst utilising margin of error for detecting statistically significant differences between each researched segment!

Let’s open our minds today – digging beneath surface level information so data tells us stories about humanity & our social behavior patterns during these uncertain times!

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How to use the dataset

This dataset contains survey data related to the impact of COVID-19 on US adult residents. The survey covers physical health, mental health, economic security, and social dynamics that have been affected by the pandemic. It is important to remember that this is survey data and must be properly weighted when analyzing it. Raw or aggregated numbers should not be used to generate insights. In order to weight the data appropriately, we recommend using statistical software such as R or SPSS or our provided queries (linked in this guide).

To generate a table relating to a specific topic covered in the survey, use the survey questionnaire and code book to match a question (the variable label) with its corresponding variable name. For instance “How often have you felt lonely in the past 7 days?” is variable “soc5c”. After entering a variable name into one of our provided queries, a sentence summarizing national results can be written out such as “People in some states are less likely to report loneliness than others… nationally 60% of people said they hadn't felt lonely”

When making comparisons for numerical statistics between different regions it is important to consider the margin of error associated with each set of surveys for national and regional figures provided within this document; it will help determine if differences between groups are statistically significant. If differences are: at least twice as large as margin of error then there is clear difference; at least as large as margin then there is slight/apparent difference; less than/equal margin no real difference can be determined

Survey results are generally posted under embargo on Tuesday evenings with data release taking place at 1 pm ET Thursdays afterward under an appropriate title including month & year ie 01_April_30_covid_impact_survey). Data will come in comma-delimited & statistical formats containing necessary inferences regarding sample collection etc outlined within this guide

When citing survey results these should always attributed with qualification— The Covid Impact Survey conducted by NORC at University Chicago for The Data Foundation sponsored by Federal Reserve Bank Minneapolis & Packard Foundation .
Lastly more resources regarding AP’s data journalism& distributions capabilities can found via link here or contact kromanoap.org

Research Ideas

• Comparing mental health outcomes of the pandemic in different states and metropolitan areas, such as rates of anxiety or lonelines...

Department of Hauts-de-Seine
Reception of people with disabilities in institutions
Support services for social life

Public service
Accommodation for a person with a disability

Data.gouv.fr
https://www.data.gouv.fr/fr/search/?q=%C3%A9tablissements+personnes+handicap%C3%A9es" target="_blank">Datasets relating to establishments for people with disabilities

This round of Euro-Barometer surveys queried respondents on standard Euro-Barometer measures such as public awareness of and attitudes toward the Common Market and the European Community (EC), and also focused on consumer goods, Social Security, health care and health care benefits, the elderly, retirement, and alcohol and drug use. Questions concerning consumer goods asked whether respondents read product information before purchasing, what additional product information they would like to see, what three things other than price were most important in deciding whether to purchase an item, and whether it was necessary to have the same type of product information available for all members of the European Community (EC). Respondents' attitudes and opinions on Social Security were probed with questions that asked whether they agreed that Social Security properly protects the unemployed, the elderly, the sick or disabled, those with work-related injuries or illness, and the poor. Respondents were also asked whether policies on pensions, minimum income, and unemployment should be decided by national governments or by the EC, and whether foreigners should have the same Social Security benefits as citizens. The general health of respondents and their health care benefits were assessed through questions that asked whether they had a long-standing illness, disability, or infirmity, whether they had cut down their activity due to illness or injury, and whether they had taken medicine or talked to a doctor within the last 30 days. Respondents were also queried about which conditions they would see a doctor for and what type of examinations they had had in the past three years. Respondents were asked to rate what they paid for various medical services, the general quality of their health care, and the nature and availability of health insurance. The main problems facing the elderly and the role the elderly play in society were also topics of investigation in this survey. Questions elicited respondents' views toward possible changes in pension terms, whether retirement should occur at a fixed age, what types of discrimination affect the elderly who are working, whether the government should introduce laws to try to stop age discrimination, whether a minimum level of income should be provided to the elderly, and whether the elderly needing personal care should go into residential/nursing homes or should have social services help them remain in their homes for as long as possible. Respondents were also asked whether they provided long-term care to anyone either living with them or not living with them, who was in the best position to decide which services are most important for the elderly, what the best method of financing long-term care for the elderly was, and whether the EC was doing enough with regard to the elderly. Questions on retirement dealt with what ages respondents retired/planned to retire, whether the retired felt their pensions to be adequate, whether working people looked forward to retiring, whether pensions should be extended to widows and dependent children, whether pensions should be reduced for those who work for earned income beyond retirement, and whether pensions should be provided through government taxation, employer/employee contributions, or private contracts between workers and pension companies. Queries about alcohol and drug usage probed the use of beer, wine, spirits, and other forms of alcohol, age at which the respondent began drinking, familiarity with major forms of drugs, age at which drugs were first offered, how difficult it was to get drugs, and the means available for getting drugs. Additional questions focused on how the respondent viewed the drug problem, the top priority in eliminating the drug problem, diminishing the effects of drug use, whether drug use leads to AIDS, prostitution, health problems, social problems, violence, suicide, personality breakdowns, and problems with the law, and the major reasons for alcohol and drug use. Demographic and other background information was gathered on life satisfaction, number of people residing in the home, size of locality, home ownership, trade union membership, region of residence, and occupation of the head of household, as well as the respondent's age, sex, marital status, education, occupation, work sector, religiosity, subjective social class, use of media, left-right political self-placement, and opinion leadership. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR09957.v1. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

Annual data on the amount of reductions in social security contributions by private sector employers by NA38i sector and by broad categories of measures. ► DAYS: end of year + ~200 days.

Source: URSSAF (Pleiade warehouse)

Champ: private sector employer establishments contributing to Urssaf (i.e. excluding agricultural schemes), excluding Mayotte.

Deep: since 2004.

Methodological details:

- The data contained in this set are expressed in the period of employment (period for which the exemption applies).

- They are based on information reported by employers to Urssaf via the Social Declaration Nominative (DSN) and, before it, the contribution slips (BRC).

- The amounts are derived from the aggregated data by personal type code (PSC), except that part of the general reduction relating to supplementary pension contributions, which is derived from the DSN’s nominative data.

- The data cover all the exemption schemes that relate to contributions recovered by Urssaf (including unemployment insurance contributions), as well as the part of the general reduction which concerns supplementary pension contributions since 2019. They also include the amounts of the Employment Competitiveness Tax Credit (between 2013 and 2018): although it is not a reduction in social security contributions stricto sensu, it constitutes a general reduction in labour costs insofar as it consists of the application of a rate to the wage bill.

- The private sector field corresponds to the scope of the quarterly employment estimates produced by Urssaf in partnership with INSEE and Dares (ETS field). It covers all employers’ establishments covered by the general scheme (and thus contributing to the Urssaf) with the exception in particular of those belonging to the public sector within the meaning of the definition adopted by the Directorate-General for Administration and Civil Service (DGAFP). It also excludes the AZ, TZ and UZ sectors.

To go further: Stat’Ur n°366

To deepen our methodology

Abstract copyright UK Data Service and data collection copyright owner.The General Household Survey (GHS), ran from 1971-2011 (the UKDS holds data from 1972-2011). It was a continuous annual national survey of people living in private households, conducted by the Office for National Statistics (ONS). The main aim of the survey was to collect data on a range of core topics, covering household, family and individual information. This information was used by government departments and other organisations for planning, policy and monitoring purposes, and to present a picture of households, families and people in Great Britain. In 2008, the GHS became a module of the Integrated Household Survey (IHS). In recognition, the survey was renamed the General Lifestyle Survey (GLF). The GLF closed in January 2012. The 2011 GLF is therefore the last in the series. A limited number of questions previously run on the GLF were subsequently included in the Opinions and Lifestyle Survey (OPN). Secure Access GHS/GLF The UKDS holds standard access End User Licence (EUL) data for 1972-2006. A Secure Access version is available, covering the years 2000-2011 - see SN 6716 General Lifestyle Survey, 2000-2011: Secure Access. History The GHS was conducted annually until 2011, except for breaks in 1997-1998 when the survey was reviewed, and 1999-2000 when the survey was redeveloped. Further information may be found in the ONS document An overview of 40 years of data (General Lifestyle Survey Overview - a report on the 2011 General Lifestyle Survey) (PDF). Details of changes each year may be found in the individual study documentation. EU-SILC In 2005, the European Union (EU) made a legal obligation (EU-SILC) for member states to collect additional statistics on income and living conditions. In addition, the EU-SILC data cover poverty and social exclusion. These statistics are used to help plan and monitor European social policy by comparing poverty indicators and changes over time across the EU. The EU-SILC requirement was integrated into the GHS/GLF in 2005. After the closure of the GLF, EU-SILC was collected via the Family Resources Survey (FRS) until the UK left the EU in 2020.Reformatted GHS data 1973-1982 - Surrey SPSS Files SPSS files were created by the University of Surrey for all GHS years from 1973 to 1982 inclusive. The early files were restructured and the case changed from the household to the individual with all of the household information duplicated for each individual. The Surrey SPSS files contain all the original variables as well as some extra derived variables (a few variables were omitted from the data files for 1973-76). In 1973 only, the section on leisure was not included in the Surrey SPSS files. This has subsequently been made available, however, and is now held in a separate study, General Household Survey, 1973: Leisure Questions (SN 3982). Records for the original GHS 1973-1982 ASCII files have been removed from the UK Data Archive catalogue, but the data are still preserved and available upon request. For the third edition, a revised version of the education variable EdLev00 was added to the dataset. Main Topics:The main GHS consisted of a household questionnaire, completed by the Household Reference Person (HRP), and an individual questionnaire, completed by all adults aged 16 and over resident in the household. A number of different trailers each year covering extra topics were included in later (post-review) surveys in the series from 2000.The household questionnaire covered the following topics: household information, accommodation type, housing tenure/costs, and consumer durables including vehicle ownership.The individual questionnaire included data from the household dataset, and additional sections on migration/citizenship/national identity/ethnicity, employment, pensions, education, health, child care, smoking, drinking, family information, financial situation, and income. The 2000-2001 GHS included questions asking about periods of cohabitation not leading to marriage, which were first asked in 1998. The trailers for that year covered social capital and informal carers. Multi-stage stratified random sample Face-to-face interview 2000 2001 ACADEMIC ACHIEVEMENT ADOLESCENTS ADOPTED CHILDREN ADULTS AGE ALCOHOL USE ALCOHOLIC DRINKS ALCOHOLISM ANTISOCIAL BEHAVIOUR APPRENTICESHIP ATTITUDES BANK ACCOUNTS BATHROOMS BEDROOMS BONDS BONUS PAYMENTS BOYS BUILDING MAINTENANCE BUILDING SOCIETY AC... BUSINESSES CAR PARKING AREAS CARE OF DEPENDANTS CARE OF THE DISABLED CARE OF THE ELDERLY CENTRAL HEATING CEREMONIES CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILDBIRTH CHILDREN CHIROPODY CHRONIC ILLNESS CLEANING CLUBS COHABITATION COLOUR TELEVISION R... COMMERCIAL BUILDINGS COMMUNITIES COMMUNITY ACTION COMMUNITY BEHAVIOUR COMMUNITY IDENTIFIC... COMMUNITY LIFE COMPACT DISC PLAYERS COMPANY CARS COMPUTERS CONSUMER GOODS CONTRACEPTIVE DEVICES COOKING COOKING FACILITIES CRIME AND SECURITY CRIME VICTIMS CRIMINAL DAMAGE DAY CARE DECISION MAKING DELIVERY PREGNANCY DISABILITIES DISABLED CHILDREN DISABLED PERSONS DISEASES DISTANCE LEARNING DIVORCE DOGS DOMESTIC APPLIANCES DOMESTIC RESPONSIBI... DRUG ABUSE ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EDUCATIONAL FACILITIES EDUCATIONAL GRANTS EDUCATIONAL INSTITU... ELDERLY ELEVATORS EMPLOYEES EMPLOYERS EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENGLISH LANGUAGE ENVIRONMENTAL DEGRA... ETHNIC GROUPS EVERYDAY LIFE EXAMINATIONS EXPECTATION EXPOSURE TO NOISE Education FACILITIES FAMILIES FAMILY INCOME FAMILY MEMBERS FAMILY SIZE FATHER S PLACE OF B... FATHERS FEAR OF CRIME FERTILITY FINANCIAL RESOURCES FINANCIAL SUPPORT FOOD AND NUTRITION FOSSIL FUELS FOSTER CHILDREN FRIENDS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION GENDER GENERAL PRACTITIONERS GIRLS General health and ... HEADS OF HOUSEHOLD HEALTH HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEALTH VISITORS HEARING AIDS HEARING IMPAIRMENTS HEATING SYSTEMS HIGHER EDUCATION HOLIDAYS HOME BASED WORK HOME BUYING HOME HELP HOME OWNERSHIP HOME SHARING HOME VISITS HOSPITAL OUTPATIENT... HOSPITAL SERVICES HOSPITALIZATION HOSPITALIZED CHILDREN HOURS OF WORK HOUSEHOLD INCOME HOUSEHOLDS HOUSEWORK HOUSING HOUSING AGE HOUSING FACILITIES HOUSING TENURE Health care service... Housing IMMIGRATION INCOME INCOME TAX INDUSTRIES INSURANCE INTEREST FINANCE INTERNET ACCESS INTERPERSONAL RELAT... INVESTMENT INVESTMENT RETURN JOB DESCRIPTION JOB HUNTING JOB SEEKER S ALLOWANCE KITCHENS LANDLORDS LEAVE LEISURE TIME ACTIVI... LOCAL COMMUNITY FAC... LOCAL GOVERNMENT SE... LOCAL PRESS LONELINESS Labour and employment MARITAL HISTORY MARITAL STATUS MARRIAGE MARRIAGE DISSOLUTION MATERNITY PAY MATHEMATICS MEALS ON WHEELS MEDICAL CENTRES MEDICAL PRESCRIPTIONS MEDICINAL DRUGS MEMBERSHIP MEN MOBILE HOMES MORTGAGES MOTHER S PLACE OF B... MOTHERS MOTOR PROCESSES MOTOR VEHICLES NEIGHBOURHOODS NEIGHBOURS NURSES OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONAL TRAINING OCCUPATIONS ONE PARENT FAMILIES ORGANIZATIONS OVERTIME PARENTS PART TIME COURSES PART TIME EMPLOYMENT PATIENTS PAYMENTS PENSION CONTRIBUTIONS PENSIONS PERSONAL CONTACT PERSONAL HYGIENE PHYSICAL ACTIVITIES PHYSICIANS PLACE OF BIRTH POLICE SERVICES POLITICAL POWER PREGNANCY PRESCHOOL CHILDREN PRIVATE HEALTH SERV... PRIVATE PERSONAL PE... PRIVATE SECTOR PUBLIC TRANSPORT QUALIFICATIONS REBATES REDUNDANCY PAY REFUSE RENTED ACCOMMODATION RENTS RESIDENTIAL BUILDINGS RESIDENTIAL CARE OF... RESIDENTIAL CARE OF... RESIDENTIAL CARE OF... RESIDENTIAL MOBILITY RESPITE CARE RETIREMENT ROAD TRAFFIC ROOM SHARING ROOMS SANDWICH COURSES SATELLITE RECEIVERS SAVINGS SCHOOL LEAVING AGE SCHOOLCHILDREN SELF EMPLOYED SHARED HOME OWNERSHIP SHARES SHELTERED HOUSING SHOPPING SIBLINGS SICK LEAVE SICK PERSONS SINGLES SMOKING SMOKING CESSATION SOCIABILITY SOCIAL CLASS SOCIAL HOUSING SOCIAL INTEGRATION SOCIAL NEEDS SOCIAL NETWORKS SOCIAL SECURITY BEN... SOCIAL SECURITY CON... SOCIAL SERVICES SOCIAL SUPPORT SOCIAL WORKERS SOCIO ECONOMIC STATUS SPOUSE S AGE SPOUSE S ECONOMIC A... SPOUSES STATE RETIREMENT PE... STEPCHILDREN STUDENTS SUBSIDIARY EMPLOYMENT SUPERVISORY STATUS Social conditions a... Specific social ser... TAX RELIEF TEACHER QUALIFICATIONS TELEPHONES TELEVISION CHANNELS TELEVISION RECEIVERS TIED HOUSING TIME TOBACCO TRAINING COURSES TRANSPORT TRUST UNEARNED INCOME UNEMPLOYED UNEMPLOYMENT UNFURNISHED ACCOMMO... UNWAGED WORKERS VACANT HOUSING VIDEO RECORDERS VISION IMPAIRMENTS VISITS PERSONAL VOCATIONAL EDUCATIO... VOLUNTARY WELFARE O... WAGES WALKING WIDOWED WOMEN WORKING MOTHERS WORKPLACE YOUTH ACTIVITIES

VBA BENEFIT PROGRAM to assist wartime veterans in need whose non-service- connected disabilities are permanent and total preventing them from following a substantially gainful occupation. A Veteran who meets the wartime service requirements is potential eligible if he/she is: • permanently and totally disabled for reasons not necessarily due to service, • age 65 or older, or • is presumed to be totally and permanently disabled for pension purposes because: o he/she is a patient in a nursing home for long-term care due to a disability, or o being disabled, as determined by the Commissioner of Social Security (SS) for purposes of any benefits administered by the Commissioner, such as SS disability benefits or Supplemental Security Income. Income restrictions are prescribed in 38 U.S.C. 1521. Pension is not payable to those whose estates are so large that it is reasonable they use the estate for maintenance. A Veteran meets wartime service requirements if he/she served: • a total of 90 days or more during one or more periods of war; • 90 or more consecutive days that began or ended during a period of war; or • for any length of time during a period of war if he/she was discharged or released for a service-connected disability. Veterans entering service after September 7, 1980, must also meet the minimum active duty requirement of 24 months of continuous service or the full period to which the Veteran was called to active duty. (38 U.S.C.5303(A)).

This table contains figures on the number of people with social security benefits per municipality, district and neighborhood (classification 2022). It concerns people with a benefit for disability, unemployment, old age and social assistance. It is possible for a person to claim more than one benefit. These may be benefits of the same type (for example, two benefits under the Disability Insurance Act (WAO)) or two benefits of different types (such as a benefit under the Unemployment Insurance Act and a social assistance benefit). In the latter case, the person is included in both types of benefits, in the first case only once (in the WAO). From October 2021, there will be an increase in the number of WGA benefits. The cause of this is an improvement in the quality of the process, which means that a group of self-insurers that were previously missing is now included. It is not about an increase in the regular number of WGA benefits, but an increase in "people with a WGA benefit". In the category of people on benefits (total), the person is of course only counted once. The figures on the number of people receiving benefits per neighbourhood, district or municipality may deviate slightly from figures published elsewhere on StatLine, because use is made of the most recent data from the Municipal Personal Records Database (BRP). Because different StatLine tables are updated at different times, it is possible that a different version of the BRP is used for one table than for another table. In that case, the most recently published figures are the most accurate. The figures relate to the last day of the reporting month. Data available from: March 2022. Status of the figures: The figures for 2022 are more provisional. Changes as of: 31 July 2023 Have been added - the more detailed provisional figures for December 2022 Have become more provisional - the figures for the period March, June and September 2022 When will new figures be released? These figures per municipality, district and neighborhood with a breakdown for 2022 appear in a new table.

Welfare and Services in Finland is a panel survey that combines telephone and face-to-face interviews, postal surveys and register data. The aim of the study is to offer up-to-date, reliable and extensive research data on Finnish welfare and the use of welfare services. This dataset contains a face-to-face survey aimed at the elderly. Main topics included housing, financial circumstances, health and health services, need for care and assistance, informal care, social networks, and quality of life. Relating to housing, questions charted housing tenure, number of rooms, floor area, satisfaction with various aspects of the housing and the neighbourhood, satisfaction with distances to different services (e.g. grocery shop, bank), and difficulties with the home. The respondents' economic circumstances were surveyed by asking whether they were able to save money after expenses and whether they had run out of money for food in the previous 12 months. Relating to health and health services, questions were asked about health status, limiting long-term illnesses or disabilities and their impact on daily life, exercise habits, alcohol consumption, smoking, and visits to a doctor or nurse in the previous 12 months. Further questions probed where the respondents would primarily try to get a doctor's appointment during daytime, whether they had been in hospital as an inpatient in the previous 12 months, whether certain things (e.g. lack of money) had prevented them from receiving treatment, and whether they had had to wait unreasonably long to receive treatment (e.g. to get a doctor's appointment in a health centre). Perceptions of the quality of public and private health services were surveyed. Visits to a dentist were charted. Need for care and assistance was charted by asking about managing with daily activities without help, help received for different activities, sufficiency of and satisfaction with the assistance received, person or organisation who helped the respondents the most, services applied for in the previous 12 months, the most important services in terms of daily life, and financial problems caused by service fees. With regard to informal care, social networks, and participation, the respondents were asked whether they assisted or looked after a person close to them, how often they were in touch with different people, how satisfied they were with their relationships and support received from other people, whether they had felt lonely in the previous two weeks, whether they had enough time to do things and enough activities during the day, and which activities they had done in the previous two weeks (e.g. participated in the activities of an organisation or association, read books or magazines/newspapers). Perceptions of quality of life were surveyed as well as satisfaction with own health, experiences of physical pain, enjoyment of life, sense of significance, ability to focus on things, sense of security or insecurity in daily life, healthiness of physical environment, ability to do things (in terms of, for instance, money and energy), ability to move, satisfaction with various things in life (e.g. quality of sleep, neighbourhood of residence), and negative feelings. Finally, relating to attitudes, the respondents' views were charted on the best housing alternative for elderly people who require care and assistance, the body that should hold the main responsibility for elderly care in Finland, ways in which the funding for elderly care could be safeguarded, whether the elderly should spend more of their own savings on their treatment, level of social security, preferable ways of providing health and social services, respect of younger age groups for the ageing population, discrimination against the elderly in Finland, and the development of the household's economic situation and own life circumstances in the future. Background variables included, among others, the household size, type of municipality of residence, region of residence, hospital district, and disposable income of the household as well as the respondent's year of retirement, latest occupation, occupational status before retirement, gender, age, marital status, and level of education.

Eligible voters living in private households with telephone.

The study on the future of work was conducted by Kantar Public on behalf of the Press and Information Office of the Federal Government. During the survey period from 13 to 22 June 2023, German-speaking people aged 16 to 67 in Germany, excluding pensioners, were surveyed in online interviews (CAWI) on the following topics: current life and work situation, future expectations, the use of AI and the digitalization of the world of work as well as attitudes towards demographic change and the shortage of skilled workers. The respondents were selected using a quota sample from an online access panel. Future: general life satisfaction; satisfaction with selected aspects of life (working conditions, education, qualifications, health situation, professional remuneration, family situation, financial situation); expectations for the future: rather confident vs. rather worried about the private and professional future; rather confident vs. rather worried about the professional future of younger people or the next generation; rather confident vs. rather worried about the future of Germany; confidence vs. concern regarding the competitiveness of the German economy in various areas (digitalization and automation of the working world, climate protection goals of industry, effects of the Ukraine war on the German economy, access to important raw materials such as rare earths or metals, reliable supply of energy, number of qualified specialists, general price development, development of wages and salaries, development of pensions); probability of various future scenarios for Germany in 2030 (Germany is once again the world export champion, unemployment is at an all-time low - full employment prevails in Germany, the energy transition has already created hundreds of thousands of new jobs in German industry, Germany has emerged the strongest in the EU from the crises of the last 15 years, the price crisis has led to the fact The price crisis has meant that politics and business have successfully set the course for the future, citizens can deal with all official matters digitally from home, German industry is much faster than expected in terms of climate targets and is already almost climate-neutral, Germany is the most popular country of immigration for foreign university graduates, the nursing shortage in Germany has been overcome thanks to the immigration of skilled workers). 2. Importance of work: importance of different areas of life (ranking); work to earn money vs. as a vocation; importance of different work characteristics (e.g. job security, adequate income, development prospects and career opportunities, etc.). 3. Professional situation: satisfaction with various aspects of work (job security, pay/income, development/career opportunities, interesting work, sufficient contact with other people, compatibility of family/private life and work. Work climate/ working atmosphere, further training opportunities, social recognition, meaningful and useful work); job satisfaction; expected development of working conditions in own professional field; recognition for own work from the company/ employer, from colleagues, from other people from the work context, from the personal private environment, from society in general and from politics; unemployed people were asked: currently looking for a new job; assessment of chances of finding a new job; pupils, students and trainees were asked: assessment of future career opportunities; reasons for assessing career opportunities as poor (open). 4. AI: use of artificial intelligence (AI) in the world of work rather as an opportunity or rather as a danger; expected effects of AI on working conditions in their own professional field (improvement, deterioration, no effects); opportunities and dangers of digitization, AI and automation based on comparisons (all in all, digitization leads to a greater burden on the environment, as computers, tablets, smartphones and data centers are major power guzzlers vs. All in all, digitalization protects the environment through less mobility and more efficient management, artificial intelligence and digitalization help to reduce the workload and relieve employees of repetitive and monotonous tasks vs. artificial intelligence and digitalization overburden many employees through further work intensification. Stress and burnouts will increasingly be the result, artificial intelligence and digitalization will primarily lead to job losses vs. artificial intelligence and digitalization will create more new, future-proof jobs than old ones will be lost, our economy will benefit greatly from global networking through speed and efficiency gains vs. our economy is threatened by global networking by becoming more susceptible to cyberattacks and hacker attacks, digitalization will lead to new, more flexible working time models and a better work-life balance vs. digitalization will lead to a blurring of boundaries between work and leisure time and thus, above all, to more self-exploitation by employees). 5. Home office: local focus of own work currently, before the corona pandemic and during the corona pandemic (exclusively/ predominantly in the company or from home, at changing work locations (company, at home, mobile from on the road); Agreement with various statements on the topic of working from home (wherever possible, employers should give their employees the opportunity to work from home, working from home leads to a loss of cohesion in the company, working from home enables a better work-life balance, digital communication makes coordination processes more complicated, home office makes an important contribution to climate protection due to fewer journeys to work, home office leads to a mixture of work and leisure time and thus to a greater workload, home office leads to greater job satisfaction and thus to higher productivity, since many professions cannot be carried out in the home office, it would be fairer if everyone had to work outside the home); attitude towards a general 4-day working week (A four-day week for everyone would increase the shortage of skilled workers vs. a four-day week for everyone would increase motivation and therefore productivity). 6. Demographic change: knowledge of the meaning of the term demographic change; expected impact of demographic change on the future of Germany; opinion on the future in Germany based on alternative future scenarios (in the future, poverty in old age will increase noticeably vs. the future generation of pensioners will be wealthier than ever before, in the future, politics and elections will be increasingly determined by older people vs. the influence of the younger generation on politics will become much more important, our social security systems will continue to ensure intergenerational fairness and equalization in the future vs. the distribution conflicts between the younger and older generations will increase noticeably, future generations will have to work longer due to the shortage of skilled workers vs. people will have to work less in the future due to digitalization and automation and will be able to retire earlier). 7. Shortage of skilled workers: shortage of skilled workers in own company; additional personal burden due to shortage of skilled workers; company is doing enough to counteract the shortage of skilled workers; use of artificial intelligence (AI) in the company could compensate for the shortage of skilled workers; evaluation of various measures taken by the federal government to combat the shortage of skilled workers (improvement of training and further education opportunities, increasing the participation of women in the labor market (e.g. by expanding childcare services, more flexible working hours, offers for older skilled workers to stay in work longer, facilitating the immigration of foreign skilled workers); evaluation of the work of the federal government to combat the shortage of skilled workers; attractiveness (reputation in society) of various professions with a shortage of skilled workers (e.g. social pedagogues/educators); evaluation of the work of the federal government to combat the shortage of skilled workers. B. social pedagogue, nursery school teacher, etc.); job recommendation for younger people; own activity in one of the professions mentioned with a shortage of skilled workers. Demography: sex; age; age in age groups; employment; federal state; region west/east; school education; vocational training; self-placement social class; employment status; occupation differentiated workers, employees, civil servants; industry; household size; number of children under 18 in the household; net household income (grouped); location size; party sympathy; migration background (respondent, one parent or both parents). Additionally coded were: consecutive interview number; school education head group (low, medium, high); weighting factor.

If you’re a senior with low income, you may qualify for monthly Guaranteed Annual Income System payments.

Maximum payment and allowable private income amounts for the period from July 1, 2025 to June 30, 2026 are:

• $90 monthly for single seniors (maximum monthly payment amount), your annual private income must be less than $4,320
• $180 monthly for senior couples (maximum monthly payment amount), your annual private income must be less than $8,640

The data is organized by private income levels. GAINS payments are provided on top of the Old Age Security (OAS) pension and the Guaranteed Income Supplement (GIS) payments you may receive from the federal government.

Learn more about the Ontario Guaranteed Annual Income System

This data is related to The Retirement Income System in Canada

The housing situation, concepts of an old people´s home, social contacts and general social situation of older people in Rheine. Topics: current and desired housing conditions; satisfaction with residence; rent costs; housing benefit and rent support; possession of a telephone and willingness to participate in a telephone chain; attitude to old people´s homes; preferred situation for an old people´s home; interest in taking furniture along to the old people´s home; desired institutions in an old people´s home; interest in a residence in an old people´s home facility; ideas about living together by old and young; actual and desired contacts with one´s children and neighbors; assistance and place of residence of one´s children; judgement on personal condition of health and one´s own mobility or need of help; illnesses; utilization of the so-called health and advice center; participation in the meal service; help needed in carrying out housework; interest in acceptance of an honorary welfare task; attitude to an advice center for old people; desired provider and desired services of such a center; knowledge about the brochure with advice for the old from Caritas; membership in clubs and organizations; interest in social and cultural events; knowledge of old people´s clubs and day centers for the old; participation in events of old people´s clubs and attitude to common leisure activities by young and old people; reasons for rejection of old people´s clubs; judgement on policies on old people in Rheine; preparation for retirement; greatest problem for older people; satisfaction with institutions of the social surroundings; receipt of welfare; image of the welfare recipient; evaluation of contacts with the social services office; expectations of the social services office; leisure activities; vacation habits and destinations; media usage; religiousness; local residency. Demography: age; sex; age of spouse; marital status; religious denomination; school education; occupation; employment; occupation of spouse; household income; size of household; composition of household. Interviewer rating: housing situation; length of interview; presence of other persons during interview. Die Wohnsituation, Altersheimvorstellungen, Sozialkontakte und allgemeine soziale Lage von älteren Menschen in Rheine. Themen: Derzeitige und gewünschte Wohnverhältnisse; Zufriedenheit mit der Wohnung; Mietkosten; Wohngeld und Mietzuschuß; Telefonbesitz und Teilnahmebereitschaft an einer Telefonkette; Einstellung zu Altersheimen; präferierte Lage für ein Altersheim; Interesse an Möbelmitnahme ins Altersheim; gewünschte Einrichtungen in einem Altersheim; Interesse an einer Wohnung in einer Altenwohnanlage; Vorstellungen über das Zusammenleben von Alt und Jung; tatsächliche und gewünschte Kontakte zu den Kindern und den Nachbarn; Hilfeleistungen und Wohnort der Kinder; Beurteilung des eigenen Gesundheitszustands und der eigenen Beweglichkeit bzw. Hilfsbedürftigkeit; Krankheiten; Inanspruchnahme der sogenannten Sozialstation; Teilnahme am Mahlzeitendienst; benötigte Hilfe bei der Erledigung von Hausarbeiten; Interesse an der Übernahme einer ehrenamtlichen, fürsorgerischen Aufgabe; Einstellung zu einer Beratungsstelle für alte Menschen; gewünschte Trägerschaft und gewünschte Leistungen einer solchen Stelle; Kenntnis der Altenratgeber-Broschüre der Caritas; Mitgliedschaft in Vereinen und Organisationen; Interesse an geselligen und kulturellen Veranstaltungen; Kenntnis von Altenclubs und Altentagesstätten; Teilnahme an Veranstaltungen von Altenclubs und Einstellung zu gemeinsamen Freizeitaktivitäten von jungen und alten Leuten; Gründe für die Ablehnung von Altenclubs; Beurteilung der Altenpolitik in Rheine; Vorbereitung auf den Ruhestand; größtes Problem für ältere Menschen; Zufriedenheit mit den Einrichtungen des sozialen Umfelds; Bezug von Sozialhilfe; Image der Sozialhilfeempfänger; Bewertung der Kontakte zum Sozialamt; Erwartungen an das Sozialamt; Freizeitaktivitäten; Urlaubsgewohnheiten und Reiseziele; Mediennutzung; Religiosität; Ortsansässigkeit. Demographie: Alter; Geschlecht; Alter des Ehepartners; Familienstand; Konfession; Schulbildung; Beruf; Berufstätigkeit; Beruf des Ehepartners; Haushaltseinkommen; Haushaltsgröße; Haushaltszusammensetzung. Interviewerrating: Wohnsituation; Interviewdauer; Anwesenheit anderer Personen beim Interview.

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Televisions (Module 177): this module was asked on behalf of the Department of National Heritage, to ascertain how many households have a television that did not work at the time and did not have another TV set that did work, and whether they intended to get the broken television set repaired in the next seven days after the interview took place. ACAS awareness (Module 187): this module was asked on behalf of ACAS, the Advisory, Conciliation and Arbitration Service, who wished to know how many people had heard of them and how many had a realistic idea of what sort of organisation they are and what they do. The module was asked of all respondents in paid employment. Second homes (Module 4): this module was asked on behalf of the Department of Environment, Transport and the Regions (DETR). It has appeared in previous Omnibus surveys in a slightly different form. The module queried respondents on ownership of a second home by any member of the household and reasons for having the second home. Expectation of house price changes (Module 137): this module asks respondents' views on changes to house prices in the next year and next five years. Fire safety (Module 33): this module covers fire safety and was asked in connection with Fire Safety Week. Questions assess awareness of fire risks and fire safety measures the respondent has taken. Lone mothers (Module 184): this module was asked on behalf of the Department of Social Security. The questions were taken from a British attitudes survey and compare attitudes towards mothers living in couples with children of varying ages with attitudes towards lone mothers. Smoking (Module 130): this module assesses people's smoking habits, past and present, attitudes to smoking in different scenarios, and awareness of cigarette advertising. Unemployment risk (Module 183): this module was asked on behalf of the Centre for Research in Social Policy at Loughborough University. The questions were designed to investigate respondents' assessment of the risks of being unemployed, their attitude towards unemployment insurance and their recent experience of unemployment. Contraception (Module 170): the Special Licence version of this module is held under SN 6475. PEPs and TESSAs (Module 185): this module was asked on behalf of the Inland Revenue, to gain more information about the distribution of PEPs and TESSAs and in particular the extent to which the two groups overlap. Multi-stage stratified random sample Face-to-face interview 1997 ACCIDENTS ADULTS ADVERTISING ADVICE AGE ARBITRATION ASTHMA ATTITUDES BANK ACCOUNTS CANCER CARDIOVASCULAR DISE... CAUSES OF DEATH CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILDREN CINEMA COHABITATION COLOUR TELEVISION R... COMPANIES CONFLICT RESOLUTION COOKING EQUIPMENT COSTS COT DEATHS COURTS CREDIT CARD USE CULTURAL EVENTS Consumption and con... DIABETES DISEASES ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATIONAL BACKGROUND ELECTRICAL EQUIPMENT EMPLOYEES EMPLOYMENT EMPLOYMENT CONTRACTS EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ETHNIC GROUPS EXPENDITURE Economic conditions... FAMILY MEMBERS FINANCIAL SERVICES FIRE PROTECTION EQU... FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... Family life and mar... GENDER GENERAL PRACTITIONERS GRANTS HEADS OF HOUSEHOLD HEALTH HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEARING HEATING SYSTEMS HOLIDAYS HOME CONTENTS INSUR... HOME OWNERSHIP HOME SELLING HOSPITAL SERVICES HOURS OF WORK HOUSEHOLDS HOUSES HOUSING TENURE HUMAN SETTLEMENT Health behaviour Housing ILL HEALTH INCOME INCOME TAX INDUSTRIES INFLATION INFORMATION MATERIALS INFORMATION SOURCES INHERITANCE INSURANCE INTEREST FINANCE INVESTMENT Income JOB HUNTING JUDGMENTS LAW LABOUR RELATIONS LANDLORDS Labour relations co... MANAGERS MARITAL STATUS MARRIAGE DISSOLUTION MASS MEDIA MEDICAL CENTRES MEDICAL INSURANCE MEDICAL PRESCRIPTIONS MORTGAGES MOTHERS MOTOR VEHICLES ONE PARENT FAMILIES ORGANIZATIONS PARENTS PART TIME EMPLOYMENT PASSIVE SMOKING PENSIONS PERSONNEL PLACE OF RESIDENCE PRESCHOOL CHILDREN PRICES PRIVATE SECTOR PUBLIC HOUSES PUBLIC INFORMATION PUBLIC SERVICE BUIL... RADIO RECRUITMENT RENTED ACCOMMODATION RESPIRATORY TRACT D... RESTAURANTS RETIREMENT SAVINGS SCHOOLCHILDREN SCHOOLS SECOND HOMES SELF EMPLOYED SHOPS SICK LEAVE SMOKING SMOKING CESSATION SMOKING RESTRICTIONS SOCIAL HOUSING SOCIAL SECURITY BEN... SPORTING EVENTS SPOUSE S ECONOMIC A... SPOUSE S EMPLOYMENT SPOUSES STATE AID SUPERVISORS Social behaviour an... TELEPHONE HELP LINES TELEVISION ADVERTISING TELEVISION RECEIVERS TERMINATION OF SERVICE TIED HOUSING TOBACCO TRAINING TRAVEL UNEMPLOYMENT UNFURNISHED ACCOMMO... UNMARRIED MOTHERS UNWAGED WORKERS Unemployment VOCATIONAL EDUCATIO... WAGES WORKERS RIGHTS WORKING MOTHERS WORKPLACE property and invest...

Abstract copyright UK Data Service and data collection copyright owner.The Family Expenditure Survey (FES), which closed in 2001, was a continuous survey with an annual sample of around 10,000 households. They provided information on household and personal incomes, certain payments that recurred regularly (e.g. rent, gas and electricity bills, telephone accounts, insurances, season tickets and hire purchase payments), and maintained a detailed expenditure record for 14 consecutive days. The original purpose of the FES was to provide information on spending patterns for the United Kingdom Retail Price Index (RPI). The survey was a cost-efficient way of collecting a variety of related data that the government departments required to correlate with income and expenditure at the household, tax unit and person levels. The annual FES began in 1957 (with an earlier large scale survey conducted in 1953/54) and was one of the first Department of Employment (DE) systems to be computerised in the early 1960s. The UKDA holds FES data from 1961-2001. The Northern Ireland Family Expenditure Survey (NIFES), which ran from 1967-1998, was identical to the UK FES and therefore used the same questionnaires and documentation. However, starting in 1988, a voluntary question on religious denomination was asked of those aged 16 and over in Northern Ireland. The UKDA holds NIFES data from 1968-1998, under GN 33240. Significant FES developments over time include: 1968: the survey was extended to include a sample drawn from the Northern Ireland FES and a new computer system was introduced which was used until 1985 1986: DE and the Office of Population Censuses and Surveys (OPCS) converted the FES into a new database system using the SIR package 1989: the Central Statistical Office (CSO) took over responsibility for the survey 1994: in April, computerised personal interviewing was introduced using lap-top computers, the database system changed to INGRES and the survey changed from a calendar year to financial year basis 1996: in April, OPCS and CSO were amalgamated into the Office for National Statistics (ONS), who assumed responsibility for the FES 1998: from April onwards information from expenditure diaries kept by children aged 7 to 15 was included in data, and grossing factors were made available on the database From 2001, the both the FES and the National Food Survey (NFS) (held at the UKDA under GN 33071) were completely replaced by a new survey, the Expenditure and Food Survey (EFS). Prior to the advent of the EFS, there had previously been considerable overlap between the FES and NFS, with both surveys asking respondents to keep a diary of expenditure. Thus, the 2000-2001 FES was the final one in the series. The design of the new EFS was based on the previous FES; further background to its development may be found in the 1999-2000 and 2000-2001 Family Spending reports. From 2008, the EFS became the Living Costs and Food Survey (LCF) (see under GN 33334). Main Topics:Household Schedule: This schedule was taken at the main interview. Information for most of the questions was obtained from the head of household or housewife, but certain questions of a more individual character were put to every spender aged 15 or over (or 16 or over from 1973 onwards). Until the introduction of the community charge, information on rateable value and rate poundage was obtained from the appropriate local authority, as was information on whether the address was within a smokeless zone. Information was collected about the household, the sex and age of each member, and also details about the type and size of the household accommodation. The main part of the questionnaire related to expenditure both of a household and individual nature, but the questions were mainly confined to expenses of a recurring nature, e.g.:Household: housing costs, payment to Gas and Electricity Boards or companies, telephone charges, licences and television rentalIndividual: motor vehicles, season tickets for transport, life and accident insurances, payments through a bank, instalments, refund of expenses by employer, expenditure claimed by self-employed persons as business expenses for tax purposes, welfare foods, education grants and feesIncome Schedule: Data were collected for each household spender. The schedule was concerned with income, national insurance contributions and income tax. Income of a child not classed as a spender was obtained from one or other of his parents and entered on the parent's questionnaire. Information collected included: employment status and recent absences from work, earnings of an employee, self-employed earnings, National Insurance contributions, pensions and other regular allowances, occasional benefits - social security benefits and other types, investment income, miscellaneous earnings of a 'once-only' character, tax paid directly to Inland Revenue or refunded, income of a child. Diary Records: The diary covered fourteen days. Each household member aged 15 or over (or 16 or over from 1973 onwards) was asked to record all expenditure made during the 14 days. Children aged between 7 and 15 were also asked to complete simplified diaries of their daily expenditure. Data from the children's diaries was included in the survey results for the first time in 1998-99. Multi-stage stratified random sample For specific details of the sampling procedures for individual years, please refer to the annual report. Face-to-face interview Diaries

Abstract copyright UK Data Service and data collection copyright owner.The Family Expenditure Survey (FES), which closed in 2001, was a continuous survey with an annual sample of around 10,000 households. They provided information on household and personal incomes, certain payments that recurred regularly (e.g. rent, gas and electricity bills, telephone accounts, insurances, season tickets and hire purchase payments), and maintained a detailed expenditure record for 14 consecutive days. The original purpose of the FES was to provide information on spending patterns for the United Kingdom Retail Price Index (RPI). The survey was a cost-efficient way of collecting a variety of related data that the government departments required to correlate with income and expenditure at the household, tax unit and person levels. The annual FES began in 1957 (with an earlier large scale survey conducted in 1953/54) and was one of the first Department of Employment (DE) systems to be computerised in the early 1960s. The UKDA holds FES data from 1961-2001. The Northern Ireland Family Expenditure Survey (NIFES), which ran from 1967-1998, was identical to the UK FES and therefore used the same questionnaires and documentation. However, starting in 1988, a voluntary question on religious denomination was asked of those aged 16 and over in Northern Ireland. The UKDA holds NIFES data from 1968-1998, under GN 33240. Significant FES developments over time include: 1968: the survey was extended to include a sample drawn from the Northern Ireland FES and a new computer system was introduced which was used until 1985 1986: DE and the Office of Population Censuses and Surveys (OPCS) converted the FES into a new database system using the SIR package 1989: the Central Statistical Office (CSO) took over responsibility for the survey 1994: in April, computerised personal interviewing was introduced using lap-top computers, the database system changed to INGRES and the survey changed from a calendar year to financial year basis 1996: in April, OPCS and CSO were amalgamated into the Office for National Statistics (ONS), who assumed responsibility for the FES 1998: from April onwards information from expenditure diaries kept by children aged 7 to 15 was included in data, and grossing factors were made available on the database From 2001, the both the FES and the National Food Survey (NFS) (held at the UKDA under GN 33071) were completely replaced by a new survey, the Expenditure and Food Survey (EFS). Prior to the advent of the EFS, there had previously been considerable overlap between the FES and NFS, with both surveys asking respondents to keep a diary of expenditure. Thus, the 2000-2001 FES was the final one in the series. The design of the new EFS was based on the previous FES; further background to its development may be found in the 1999-2000 and 2000-2001 Family Spending reports. From 2008, the EFS became the Living Costs and Food Survey (LCF) (see under GN 33334). Main Topics:Household Schedule: This schedule was taken at the main interview. Information for most of the questions was obtained from the head of household or housewife, but certain questions of a more individual character were put to every spender aged 15 or over (or 16 or over from 1973 onwards). Until the introduction of the community charge, information on rateable value and rate poundage was obtained from the appropriate local authority, as was information on whether the address was within a smokeless zone. Information was collected about the household, the sex and age of each member, and also details about the type and size of the household accommodation. The main part of the questionnaire related to expenditure both of a household and individual nature, but the questions were mainly confined to expenses of a recurring nature, e.g.:Household: housing costs, payment to Gas and Electricity Boards or companies, telephone charges, licences and television rentalIndividual: motor vehicles, season tickets for transport, life and accident insurances, payments through a bank, instalments, refund of expenses by employer, expenditure claimed by self-employed persons as business expenses for tax purposes, welfare foods, education grants and feesIncome Schedule: Data were collected for each household spender. The schedule was concerned with income, national insurance contributions and income tax. Income of a child not classed as a spender was obtained from one or other of his parents and entered on the parent's questionnaire. Information collected included: employment status and recent absences from work, earnings of an employee, self-employed earnings, National Insurance contributions, pensions and other regular allowances, occasional benefits - social security benefits and other types, investment income, miscellaneous earnings of a 'once-only' character, tax paid directly to Inland Revenue or refunded, income of a child. Diary Records: The diary covered fourteen days. Each household member aged 15 or over (or 16 or over from 1973 onwards) was asked to record all expenditure made during the 14 days. Children aged between 7 and 15 were also asked to complete simplified diaries of their daily expenditure. Data from the children's diaries was included in the survey results for the first time in 1998-99. Multi-stage stratified random sample For specific details of the sampling procedures for individual years, please refer to the annual report. Face-to-face interview Diaries

Abstract copyright UK Data Service and data collection copyright owner.The Family Expenditure Survey (FES), which closed in 2001, was a continuous survey with an annual sample of around 10,000 households. They provided information on household and personal incomes, certain payments that recurred regularly (e.g. rent, gas and electricity bills, telephone accounts, insurances, season tickets and hire purchase payments), and maintained a detailed expenditure record for 14 consecutive days. The original purpose of the FES was to provide information on spending patterns for the United Kingdom Retail Price Index (RPI). The survey was a cost-efficient way of collecting a variety of related data that the government departments required to correlate with income and expenditure at the household, tax unit and person levels. The annual FES began in 1957 (with an earlier large scale survey conducted in 1953/54) and was one of the first Department of Employment (DE) systems to be computerised in the early 1960s. The UKDA holds FES data from 1961-2001. The Northern Ireland Family Expenditure Survey (NIFES), which ran from 1967-1998, was identical to the UK FES and therefore used the same questionnaires and documentation. However, starting in 1988, a voluntary question on religious denomination was asked of those aged 16 and over in Northern Ireland. The UKDA holds NIFES data from 1968-1998, under GN 33240. Significant FES developments over time include: 1968: the survey was extended to include a sample drawn from the Northern Ireland FES and a new computer system was introduced which was used until 1985 1986: DE and the Office of Population Censuses and Surveys (OPCS) converted the FES into a new database system using the SIR package 1989: the Central Statistical Office (CSO) took over responsibility for the survey 1994: in April, computerised personal interviewing was introduced using lap-top computers, the database system changed to INGRES and the survey changed from a calendar year to financial year basis 1996: in April, OPCS and CSO were amalgamated into the Office for National Statistics (ONS), who assumed responsibility for the FES 1998: from April onwards information from expenditure diaries kept by children aged 7 to 15 was included in data, and grossing factors were made available on the database From 2001, the both the FES and the National Food Survey (NFS) (held at the UKDA under GN 33071) were completely replaced by a new survey, the Expenditure and Food Survey (EFS). Prior to the advent of the EFS, there had previously been considerable overlap between the FES and NFS, with both surveys asking respondents to keep a diary of expenditure. Thus, the 2000-2001 FES was the final one in the series. The design of the new EFS was based on the previous FES; further background to its development may be found in the 1999-2000 and 2000-2001 Family Spending reports. From 2008, the EFS became the Living Costs and Food Survey (LCF) (see under GN 33334). Main Topics:Household Schedule: This schedule was taken at the main interview. Information for most of the questions was obtained from the head of household or housewife, but certain questions of a more individual character were put to every spender aged 15 or over (or 16 or over from 1973 onwards). Until the introduction of the community charge, information on rateable value and rate poundage was obtained from the appropriate local authority, as was information on whether the address was within a smokeless zone. Information was collected about the household, the sex and age of each member, and also details about the type and size of the household accommodation. The main part of the questionnaire related to expenditure both of a household and individual nature, but the questions were mainly confined to expenses of a recurring nature, e.g.:Household: housing costs, payment to Gas and Electricity Boards or companies, telephone charges, licences and television rentalIndividual: motor vehicles, season tickets for transport, life and accident insurances, payments through a bank, instalments, refund of expenses by employer, expenditure claimed by self-employed persons as business expenses for tax purposes, welfare foods, education grants and feesIncome Schedule: Data were collected for each household spender. The schedule was concerned with income, national insurance contributions and income tax. Income of a child not classed as a spender was obtained from one or other of his parents and entered on the parent's questionnaire. Information collected included: employment status and recent absences from work, earnings of an employee, self-employed earnings, National Insurance contributions, pensions and other regular allowances, occasional benefits - social security benefits and other types, investment income, miscellaneous earnings of a 'once-only' character, tax paid directly to Inland Revenue or refunded, income of a child. Diary Records: The diary covered fourteen days. Each household member aged 15 or over (or 16 or over from 1973 onwards) was asked to record all expenditure made during the 14 days. Children aged between 7 and 15 were also asked to complete simplified diaries of their daily expenditure. Data from the children's diaries was included in the survey results for the first time in 1998-99. Multi-stage stratified random sample For specific details of the sampling procedures for individual years, please refer to the annual report. Face-to-face interview Diaries