As of 10/22/2020, this dataset is no longer being updated and has been replaced with a new dataset, which can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2 This dataset includes the average daily COVID-19 case rate per 100,000 population by town over the last two MMWR weeks (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). These counts do not include cases among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities. This dataset will be updated weekly.

DPH note about change from 7-day to 14-day metrics: As of 10/15/2020, this dataset is no longer being updated. Starting on 10/15/2020, these metrics will be calculated using a 14-day average rather than a 7-day average. The new dataset using 14-day averages can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2

As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

This dataset includes a weekly count and weekly rate per 100,000 population for COVID-19 cases, a weekly count of COVID-19 PCR diagnostic tests, and a weekly percent positivity rate for tests among people living in community settings. Dates are based on date of specimen collection (cases and positivity).

A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case.

These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities.

These data are updated weekly; the previous week period for each dataset is the previous Sunday-Saturday, known as an MMWR week (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). The date listed is the date the dataset was last updated and corresponds to a reporting period of the previous MMWR week. For instance, the data for 8/20/2020 corresponds to a reporting period of 8/9/2020-8/15/2020.

Notes: 9/25/2020: Data for Mansfield and Middletown for the week of Sept 13-19 were unavailable at the time of reporting due to delays in lab reporting.

Analysis of ‘COVID-19 case rate per 100,000 population and percent test positivity in the last 7 days by town - ARCHIVE’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ceb31b99-df28-4d47-bfc9-dd3ab1896172 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

DPH note about change from 7-day to 14-day metrics: As of 10/15/2020, this dataset is no longer being updated. Starting on 10/15/2020, these metrics will be calculated using a 14-day average rather than a 7-day average. The new dataset using 14-day averages can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/hree-nys2

As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

This dataset includes a weekly count and weekly rate per 100,000 population for COVID-19 cases, a weekly count of COVID-19 PCR diagnostic tests, and a weekly percent positivity rate for tests among people living in community settings. Dates are based on date of specimen collection (cases and positivity).

A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case.

These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities.

These data are updated weekly; the previous week period for each dataset is the previous Sunday-Saturday, known as an MMWR week (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf). The date listed is the date the dataset was last updated and corresponds to a reporting period of the previous MMWR week. For instance, the data for 8/20/2020 corresponds to a reporting period of 8/9/2020-8/15/2020.

Notes: 9/25/2020: Data for Mansfield and Middletown for the week of Sept 13-19 were unavailable at the time of reporting due to delays in lab reporting.

--- Original source retains full ownership of the source dataset ---

Abstract copyright UK Data Service and data collection copyright owner. The Wealth and Assets Survey (WAS) is a longitudinal survey, which aims to address gaps identified in data about the economic well-being of households by gathering information on level of assets, savings and debt; saving for retirement; how wealth is distributed among households or individuals; and factors that affect financial planning. Private households in Great Britain were sampled for the survey (meaning that people in residential institutions, such as retirement homes, nursing homes, prisons, barracks or university halls of residence, and also homeless people were not included). The WAS commenced in July 2006, with a first wave of interviews carried out over two years, to June 2008. Interviews were achieved with 30,595 households at Wave 1. Those households were approached again for a Wave 2 interview between July 2008 and June 2010, and 20,170 households took part. Wave 3 covered July 2010 - June 2012, Wave 4 covered July 2012 - June 2014 and Wave 5 covered July 2014 - June 2016. Revisions to previous waves' data mean that small differences may occur between originally published estimates and estimates from the datasets held by the UK Data Service. Data are revised on a wave by wave basis, as a result of backwards imputation from the current wave's data. These revisions are due to improvements in the imputation methodology.Note from the WAS team - November 2023:“The Office for National Statistics has identified a very small number of outlier cases present in the seventh round of the Wealth and Assets Survey covering the period April 2018 to March 2020. Our current approach is to treat cases where we have reasonable evidence to suggest the values provided for specific variables are outliers. This approach did not occur for two individuals for several variables involved in the estimation of their pension wealth. While we estimate any impacts are very small overall and median pension wealth and median total wealth estimates are unaffected, this will affect the accuracy of the breakdowns of the pension wealth within the wealthiest decile, and data derived from them. We are urging caution in the interpretation of more detailed estimates.” Survey Periodicity - "Waves" to "Rounds" Due to the survey periodicity moving from “Waves” (July, ending in June two years later) to “Rounds” (April, ending in March two years later), interviews using the ‘Wave 6’ questionnaire started in July 2016 and were conducted for 21 months, finishing in March 2018. Data for round 6 covers the period April 2016 to March 2018. This comprises of the last three months of Wave 5 (April to June 2016) and 21 months of Wave 6 (July 2016 to March 2018). Round 5 and Round 6 datasets are based on a mixture of original wave-based datasets. Each wave of the survey has a unique questionnaire and therefore each of these round-based datasets are based on two questionnaires. While there may be some changes in the questionnaires, the derived variables for the key wealth estimates have not changed over this period. The aim is to collect the same data, though in some cases the exact questions asked may differ slightly. Detailed information on Moving the Wealth and Assets Survey onto a financial years’ basis was published on the ONS website in July 2019. A Secure Access version of the WAS, subject to more stringent access conditions, is available under SN 6709; it contains more detailed geographic variables than the EUL version. Users are advised to download the EUL version first (SN 7215) to see if it is suitable for their needs, before considering making an application for the Secure Access version.Further information and documentation may be found on the ONS Wealth and Assets Survey webpage. Users are advised to the check the page for updates before commencing analysis.Occupation data for 2021 and 2022 data files The ONS have 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. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. For further information on this issue, please see: https://www.ons.gov.uk/news/statementsandletters/occupationaldatainonssurveys.Latest edition informationFor the 18th edition (May 2023), the inheritance variables 'ivalb1r7' and 'ivalb1r7_i' which had been omitted in error have been added. Main Topics: The WAS questionnaire is divided into two parts with all adults aged 16 years and over (excluding those aged 16 to 18 currently in full-time education) being interviewed in each responding household. Household schedule: This is completed by one person in the household (usually the head of household or their partner) and predominantly collects household level information such as the number, demographics and relationship of individuals to each other, as well as information about the ownership, value and mortgages on the residence and other household assets. Individual schedule: This is given to each adult in the household and asks questions about economic status, education and employment, business assets, benefits and tax credits, saving attitudes and behaviour, attitudes to debt, insolvency, major items of expenditure, retirement, attitudes to saving for retirement, pensions, financial assets, non-mortgage debt, investments and other income. Multi-stage stratified random sample Telephone interview Face-to-face interview 2006 2020 ADOPTION PAY AGE AIRCRAFT ASSETS ATTITUDES TO SAVING BANK ACCOUNTS BICYCLES BOATS BONDS BUSINESS OWNERSHIP BUSINESS RECORDS BUSINESSES CARAVANS CARE OF DEPENDANTS CARERS BENEFITS CARS CHILD BENEFITS CHILD SUPPORT PAYMENTS CHILD TRUST FUNDS COHABITING COMMERCIAL BUILDINGS COST OF LIVING COSTS CREDIT CARD USE DEBILITATIVE ILLNESS DEBTS DISABILITIES EARLY RETIREMENT ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EDUCATIONAL FEES EDUCATIONAL STATUS EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ESTATES ETHNIC GROUPS FAMILY BENEFITS FAMILY INCOME FAMILY MEMBERS FINANCIAL ADVICE FINANCIAL COMPENSATION FINANCIAL DIFFICULTIES FINANCIAL SERVICES FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GIFTS Great Britain HEALTH HEALTH STATUS HIRE PURCHASE HOME BUILDINGS INSU... HOME BUYING HOME CONTENTS INSUR... HOME OWNERSHIP HOUSE PRICES HOUSEHOLD BUDGETS HOUSEHOLD HEAD S EC... HOUSEHOLD HEAD S SO... HOUSEHOLD INCOME HOUSEHOLDERS HOUSEHOLDS HOUSING AGE HOUSING ECONOMICS HOUSING FINANCE HOUSING TENURE ILL HEALTH INCOME INCONTINENCE INFORMAL CARE INHERITANCE INSOLVENCIES INSURANCE CLAIMS INTELLECTUAL IMPAIR... INVESTMENT Income JOB HUNTING JOB SEEKER S ALLOWANCE LAND OWNERSHIP LANDLORDS LOANS Labour and employment MAIL ORDER SERVICES MARITAL STATUS MATERNITY BENEFITS MATERNITY PAY MATHEMATICS MOBILE HOMES MORTGAGE ARREARS MORTGAGE PROTECTION... MORTGAGES MOTOR VEHICLE VALUE MOTOR VEHICLES MOTORCYCLES OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS OLD AGE BENEFITS ONE PARENT FAMILIES OVERDRAFTS PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PATERNITY BENEFITS PATERNITY PAY PENSION BENEFITS PENSION CONTRIBUTIONS PENSIONS PERSONAL DEBT REPAY... PERSONAL FINANCE MA... PHYSICAL MOBILITY PLACE OF BIRTH PRIVATE PENSIONS PRIVATE PERSONAL PE... PROFIT SHARING PROFITS QUALIFICATIONS REDUNDANCY PAY RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RENTED ACCOMMODATION RENTS RESIDENTIAL BUILDINGS RETIREMENT AGE SAVINGS SAVINGS ACCOUNTS AN... SECOND HOMES SELF EMPLOYED SELLING SHARED HOME OWNERSHIP SHARES SICK PAY SICKNESS AND DISABI... SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SPOUSES STAKEHOLDER PENSIONS STATE RETIREMENT PE... STATUS IN EMPLOYMENT STUDENT LOANS SUBSIDIARY EMPLOYMENT SUPERVISORY STATUS TAX RELIEF TENANTS HOME PURCHA... TIED HOUSING TOP MANAGEMENT TRANSPORT FARES TRUSTS UNEARNED INCOME UNEMPLOYED UNFURNISHED ACCOMMO... UNWAGED WORKERS WAGES WEALTH WILLS WINNINGS WORKPLACE property and invest...

Abstract copyright UK Data Service and data collection copyright owner. The Wealth and Assets Survey (WAS) is a longitudinal survey, which aims to address gaps identified in data about the economic well-being of households by gathering information on level of assets, savings and debt; saving for retirement; how wealth is distributed among households or individuals; and factors that affect financial planning. Private households in Great Britain were sampled for the survey (meaning that people in residential institutions, such as retirement homes, nursing homes, prisons, barracks or university halls of residence, and also homeless people were not included).The WAS commenced in July 2006, with a first wave of interviews carried out over two years, to June 2008. Interviews were achieved with 30,595 households at Wave 1. Those households were approached again for a Wave 2 interview between July 2008 and June 2010, and 20,170 households took part. Wave 3 covered July 2010 - June 2012, Wave 4 covered July 2012 - June 2014 and Wave 5 covered July 2014 - June 2016. Revisions to previous waves' data mean that small differences may occur between originally published estimates and estimates from the datasets held by the UK Data Service. These revisions are due to improvements in the imputation methodology.Note from the WAS team - November 2023:"The Office for National Statistics has identified a very small number of outlier cases present in the seventh round of the Wealth and Assets Survey covering the period April 2018 to March 2020. Our current approach is to treat cases where we have reasonable evidence to suggest the values provided for specific variables are outliers. This approach did not occur for two individuals for several variables involved in the estimation of their pension wealth. While we estimate any impacts are very small overall and median pension wealth and median total wealth estimates are unaffected, this will affect the accuracy of the breakdowns of the pension wealth within the wealthiest decile, and data derived from them. We are urging caution in the interpretation of more detailed estimates."Survey Periodicity - "Waves" to "Rounds"Due to the survey periodicity moving from "Waves" (July, ending in June two years later) to “Rounds” (April, ending in March two years later), interviews using the ‘Wave 6’ questionnaire started in July 2016 and were conducted for 21 months, finishing in March 2018. Data for round 6 covers the period April 2016 to March 2018. This comprises of the last three months of Wave 5 (April to June 2016) and 21 months of Wave 6 (July 2016 to March 2018). Round 5 and Round 6 datasets are based on a mixture of original wave-based datasets. Each wave of the survey has a unique questionnaire and therefore each of these round-based datasets are based on two questionnaires. While there may be some changes in the questionnaires, the derived variables for the key wealth estimates have not changed over this period. The aim is to collect the same data, though in some cases the exact questions asked may differ slightly. Detailed information on Moving the Wealth and Assets Survey onto a financial years’ basis was published on the ONS website in July 2019.Further information and documentation may be found on the ONS Wealth and Assets Survey webpage. Users are advised to the check the page for updates before commencing analysis.Users should note that issues with linking have been reported and the WAS team are currently investigating.Secure Access WAS dataThe Secure Access version of the WAS includes additional, detailed geographical variables not included in the End User Licence (EUL) version (SN 7215). These include:WardsParliamentary Constituency Areas for Wave 1 onlyCensus Output AreasLower Layer Super Output AreasLocal AuthoritiesLocal Education AuthoritiesProspective users of the Secure Access version of the WAS will need to fulfil additional requirements, including completion of face-to-face training, and agreement to the Secure Access User Agreement and Licence Compliance Policy, in order to obtain permission to use that version (see 'Access' section below). Users are therefore strongly encouraged to download the EUL version (SN 7215) to see if it contains sufficient detail for their needs, before considering making an application for the Secure Access version.Latest Edition InformationFor the ninth edition (October 2022), the Round 7 person and household data have been updated. The Round 7 Wave 1 Variable Catalogue Excel file has also been updated. Main Topics: The WAS questionnaire was divided into two parts with all adults aged 16 years and over (excluding those aged 16 to 18 currently in full-time education) being interviewed in each responding household. Household schedule: This was completed by one person in the household (usually the head of household or their partner) and predominantly collected household level information such as the number, demographics and relationship of individuals to each other, as well as information about the ownership, value and mortgages on the residence and other household assets. Individual schedule: This was given to each adult in the household and asked questions about economic status, education and employment, business assets, benefits and tax credits, saving attitudes and behaviour, attitudes to debt, insolvency, major items of expenditure, retirement, attitudes to saving for retirement, pensions, financial assets, non-mortgage debt, investments and other income. Multi-stage stratified random sample Face-to-face interview 2006 2020 ADOPTION PAY AGE AIRCRAFT ALIMONY ASSETS ATTITUDES TO SAVING BANK ACCOUNTS BEDROOMS BICYCLES BOATS BONDS BUSINESS OWNERSHIP BUSINESS RECORDS BUSINESSES CARAVANS CARE OF DEPENDANTS CARERS BENEFITS CARS CHILD BENEFITS CHILD SUPPORT PAYMENTS CHILD TRUST FUNDS COHABITING COMMERCIAL BUILDINGS COST OF LIVING COSTS CREDIT CARD USE DEBILITATIVE ILLNESS DEBTS DISABILITIES EARLY RETIREMENT ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EDUCATIONAL FEES EDUCATIONAL GRANTS EDUCATIONAL STATUS EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ENDOWMENT ASSURANCE ESTATES ETHNIC GROUPS EXPENDITURE FAMILY BENEFITS FAMILY INCOME FAMILY MEMBERS FINANCIAL ADVICE FINANCIAL COMPENSATION FINANCIAL DIFFICULTIES FINANCIAL SERVICES FREQUENCY OF PAY FRINGE BENEFITS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GENDER GIFTS Great Britain HEALTH HEALTH STATUS HIRE PURCHASE HOME BUILDINGS INSU... HOME BUYING HOME CONTENTS INSUR... HOME OWNERSHIP HOUSE PRICES HOUSEHOLD BUDGETS HOUSEHOLD HEAD S EC... HOUSEHOLD HEAD S SO... HOUSEHOLD INCOME HOUSEHOLDERS HOUSEHOLDS HOUSING HOUSING AGE HOUSING ECONOMICS HOUSING FINANCE HOUSING TENURE ILL HEALTH INCOME INCOME TAX INCONTINENCE INFORMAL CARE INHERITANCE INSOLVENCIES INSURANCE CLAIMS INTELLECTUAL IMPAIR... INTEREST FINANCE INVESTMENT Income JOB HUNTING JOB SEEKER S ALLOWANCE LAND OWNERSHIP LAND VALUE LANDLORDS LIFE INSURANCE LOANS Labour and employment MAIL ORDER SERVICES MARITAL STATUS MATERNITY BENEFITS MATERNITY PAY MATHEMATICS MOBILE HOMES MORTGAGE ARREARS MORTGAGE PROTECTION... MORTGAGES MOTOR VEHICLE VALUE MOTOR VEHICLES MOTORCYCLES OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OCCUPATIONS OLD AGE BENEFITS ONE PARENT FAMILIES OVERDRAFTS PART TIME EMPLOYMENT PARTNERSHIPS BUSINESS PATERNITY BENEFITS PATERNITY PAY PENSION BENEFITS PENSION CONTRIBUTIONS PENSIONS PERSONAL DEBT REPAY... PERSONAL FINANCE MA... PHYSICAL MOBILITY PLACE OF BIRTH PRIVATE PENSIONS PRIVATE PERSONAL PE... PROFIT SHARING PROFITS QUALIFICATIONS REDUNDANCY PAY RELIGIOUS AFFILIATION RELIGIOUS ATTENDANCE RENTED ACCOMMODATION RENTS RESIDENTIAL BUILDINGS RETIREMENT RETIREMENT AGE ROYALTIES SAVINGS SAVINGS ACCOUNTS AN... SECOND HOMES SELF EMPLOYED SELLING SHARED HOME OWNERSHIP SHARES SICK PAY SICKNESS AND DISABI... SOCIAL HOUSING SOCIAL SECURITY SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SPOUSES STAKEHOLDER PENSIONS STATE RETIREMENT PE... STATUS IN EMPLOYMENT STUDENT LOANS SUBSIDIARY EMPLOYMENT SUPERVISORY STATUS SURVIVORS BENEFITS TAX RELIEF TAXATION TENANTS HOME PURCHA... TIED HOUSING TOP MANAGEMENT TRANSPORT FARES TRUSTS UNEARNED INCOME UNEMPLOYED UNFURNISHED ACCOMMO... UNWAGED WORKERS WAGES WAR VETERANS BENEFITS WEALTH WILLS WINNINGS WORKPLACE property and invest...

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...

The average number of years care home residents aged 65 years and over are expected to live beyond their current age in England and Wales. Classified as Experimental Statistics.

Care Homes provide a residential setting for people that require 24 hour care. The majority of Care Homes provide services for older people, but some offer services to Children and those with Mental or Sensory Impairments.

All Care Homes in the UK are registered, inspected and listed by the relevant authority, which in England and Wales is currently the Care Quality Commission (CQC) There are two main categories of care home; those which provide only personal care and those which also provide nursing care. In addition, some Care Homes provide specialist care, eg for Dementia or Terminal Illness

Care Homes are often run by groups. In these instances we provide the group name and details and record a link from each home to its parent organisation, but we list each home as separate entities due to each having their own considerations/services.

Type of ownership:

The database details the type of ownership of the Homes

Private Homes run by individuals, partnerships and public and private limited companies.

Voluntary Homes that are run by Charities such as The Leonard Cheshire Foundation or Mencap.

Public Homes that are run by Local Authorities and NHS Trusts

Number of beds:

We list the number of Beds for each organisation. The average size of home is approximately 20 beds, whilst only 10% have more than 50 beds. There are almost 3,000 homes with five or fewer beds. These usually provide very specific types of care, including provision for Care in the Community and, if privately owned, should not normally be regarded as commercial undertakings.

This map service displays healthcare resources supply and demand per state, congressional district, and county in the United States. It shows the number of people per geography (state, congressional district and county), from the U.S. Census Bureau’s 2010 census, divided by the number of health care facilities (hospitals, medical centers, federally qualified health centers, and home health services), provided by the U.S. Department of Health Human Services. The health care system capacity is calculated as the number of facilities in the area multiplied by the national average (number of people per facility). The number of facilities of each type needed is calculated by dividing the area's population by the national average (number of people per facility). The facility surplus or need is calculated by subtracting the number of facilities needed (based on the population size) from the number of existing facilities. Number of hospital beds, accessibility and travel time are not considered in these calculations as this data is not available here.We recommend this service be viewed with a 40% transparency. Other data source include Data.gov._Other Health Datapalooza focused content that may interest you: Health Datapalooza Health Datapalooza

Number of council-supported permanent admissions of younger adults (aged 18-64) to residential and nursing care divided by the size of the younger adult population (aged 18-64) in the area multiplied by 100,000. People counted as a permanent admission include: Residents where the local authority makes any contribution to the costs of care, no matter how trivial the amount and irrespective of how the balance of these costs are metSupported residents in: Local authority-staffed care homes for residential careIndependent sector care homes for residential careRegistered care homes for nursing careResidential or nursing care which is of a permanent nature and where the intention is that the spell of care should not be ended by a set date. For people classified as permanent residents, the care home would be regarded as their normal place of residence. Where a person who is normally resident in a care home is temporarily absent at 31 March (e.g. through temporary hospitalisation) and the local authority is still providing financial support for that placement, the person should be included in the numerator. Trial periods in residential or nursing care homes where the intention is that the stay will become permanent should be counted as permanent. Whether a resident or admission is counted as permanent or temporary depends on the intention of the placement at the time of admission. The transition from ASC-CAR to SALT resulted in a change to which admissions were captured by this measure, and a change to the measure definition. 12-week disregards and full cost clients are now included, whereas previously they were excluded from the measure. Furthermore, whilst ASC-CAR recorded the number of people who were admitted to residential or nursing care during the year, the relevant SALT tables record the number of people for whom residential/nursing care was planned as a sequel to a request for support, a review, or short-term support to maximise independence Only covers people receiving partly or wholly supported care from their Local Authority and not wholly private, self-funded care. Data source: SALT.Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

BackgroundFor the oldest-old residents around their 90s living in facilities, quality end-of-life care is crucial. While an association between reduced food intake and death is known, specific patterns of intake changes before death are not well-documented.AimsThis study aims to classify food intake changes among residents in Japan’s special nursing homes during the 6 months before death, enabling precision care for each group using routinely recorded data.MethodsSixty-nine deceased older adults from five special nursing homes were studied over 3.5 years (January 2016 to June 2020). Criteria included: at least six months’ residency before death, ability to eat orally during the study period, and death within the facility. We created a time-series dataset for 69 participants, documenting their average weekly food intake (on a scale of 0-10). Subsequently, we used cluster analysis to identify clusters of change in the average weekly food intake from the 6 months before death.ResultsEligible residents’ mean age was 89.7 ±  6.7 years, and 79.7% were female. Cluster analysis classified 4 clusters of decline in food intake changes during the last 6 months before death: immediate decrease (n = 14); decrease from 1 month before death (n = 24); decrease from 3 months before death (n = 7); and gradual decrease for 6 months before death (n = 24).ConclusionThis study identified four groups of food intake prior to death. Recognizing food intake clusters in practical settings can help manage and provide appropriate end-of-life care in facilities with few medical providers but many care providers.

This table provides estimated data for the second quarter of 2023 on the average and estimated standard deviation of the weekly hours spent caring for persons with disabilities or limitations living at home in the population aged 18 and over in the Canary Islands caring for them by sex and age group.

This dataset, released December 2017, contains data relating to the Home and Community Care Program 2014-2015 where the number of: Clients living alone, Clients with carer, Clients with co-resident carer, Indigenous clients (as a proportion of total clients), Indigenous clients (as a proportion of the Indigenous population), Non-English speaking clients, Total clients, Allied health care instances at home, Allied health care instances at centre, Care received in support instances, Case management instances, Centre based day care instances, Client care coordination instances, Domestic assistance instances, Home maintenance and modification instances, Meals at centre plus meals at home instances, Nursing care at centre plus nursing care at home instances, Personal care instances, Respite care instances, Social support instances, Transport instances, Total instances of assistance. The data is by Local Government Area (LGA) 2016 geographic boundaries. For more information please see the data source notes on the data. Source: Compiled by PHIDU using data from the Australian Institute of health and Welfare, 2014/15; and the average of the ABS Estimated Resident Population, 30 June 2014 and 30 June 2015. AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

This dataset, released December 2017, contains data relating to the Home and Community Care Program 2014-2015 where the number of: Clients living alone, Clients with carer, Clients with co-resident …Show full descriptionThis dataset, released December 2017, contains data relating to the Home and Community Care Program 2014-2015 where the number of: Clients living alone, Clients with carer, Clients with co-resident carer, Indigenous clients (as a proportion of total clients), Indigenous clients (as a proportion of the Indigenous population), Non-English speaking clients, Total clients, Allied health care instances at home, Allied health care instances at centre, Care received in support instances, Case management instances, Centre based day care instances, Client care coordination instances, Domestic assistance instances, Home maintenance and modification instances, Meals at centre plus meals at home instances, Nursing care at centre plus nursing care at home instances, Personal care instances, Respite care instances, Social support instances, Transport instances, Total instances of assistance. The data is by Local Government Area (LGA) 2016 geographic boundaries. For more information please see the data source notes on the data. Source: Compiled by PHIDU using data from the Australian Institute of health and Welfare, 2014/15; and the average of the ABS Estimated Resident Population, 30 June 2014 and 30 June 2015. Please note: AURIN has spatially enabled the original data. "*" - Indicates statistically significant, at the 95% confidence level. "**" - Indicates statistically significant, at the 99% confidence level. "~" - Indicates modelled estimates have Relative Root Mean Square Errors (RRMSEs) from 0.25 to 0.50 and should be used with caution. "~~" - Indicates modelled estimates have RRMSEs greater than 0.50 but less than 1 and are considered too unreliable for general use. '?' - Indicates modelled estimates are considered too unreliable. Blank cell - Indicates data was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data). Abbreviation Information: "ASR per #" - Indirectly age-standardised rate per specified population. "SR" - Indirectly age-standardised ratio. Copyright attribution: Torrens University Australia - Public Health Information Development Unit, (2018): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Australia (CC BY-NC-SA 3.0 AU)

This table provides estimated data for the second quarter of 2023 on the average and estimated standard deviation of the weekly hours dedicated to household care tasks in the population aged 18 and over in the Canary Islands that deals with these tasks. The information is disaggregated territorially at the level of Canary Islands.

The national study SNAC - The Swedish National Study on Aging and Care, includes four participating areas: SNAC-Blekinge, SNAC Kungsholmen, SNAC Nordanstig and SNAC Skåne (GÅS). In all four areas, a research centre conducts a population study and a health care system study. (Metadata related to the main study SNAC and the other participating areas can be found under the Related studies tab). SNAC-K Kungsholmen SNAC-K is conducted by the Stockholm Gerontology Research Center in collaboration with Aging Research Center (ARC), Karolinska Institutet. SNAC-K population study: The population study consists of a clinical examination of persons over 60 years, who live in the area of Kungsholmen/Essingeöarna. The baseline data collection includes information on present status and past events. The information has been collected through interviews, clinical examinations, and testing. All staff (nurses, psychologists, and physicians) has been trained for data collection. Each subject has been examined for six hours on average; two hours for the social interview and the assessment of physical functioning (performed by a nurse); two hours for clinical examination, including geriatric, neurological and psychiatric assessment (performed by a physician); and two hours for cognitive assessment (performed by a psychologist). SNAC-K care system study: The care system data collection consists of continuous recording of the provision of public eldercare for persons over 65 years. For 2004-2020, data comprise all recipients of municipal eldercare in the district of Kungsholmen. Starting in 2015, data comprise all recipients of municipal eldercare in the whole municipality of Stockholm. Data are based on individual assessments made by the municipal need assessors for each decicison regarding the provision of eldercare services. Data include information about the type and amount of care and services granted, as well as information on need indicators (e.g., disability,physical function, cognitive impairment, mental health, living situation, housing). For specific research questions, data from the care system study can be complemented with register data on health care consumption provided by the Region of Stockholm (VAL-databas). The care system perspective and the population perspective are joined through those elderly persons who participate in both parts of the study. Purpose: Population study: The purpose is to study the transition from normal aging to morbidity and impaired functional ability by identify how social and biological factors, and the environment, affect older people's health, functional ability and life expectancy. The intention is to study the positive and negative events in life that may be relevant to aging. Care system study: The aim of SNAC-K care system study is to continuously monitor the allocation of public eldercare in relation to need indicators. Collected data can be used as a basis for planning, resource allocation and evaluation of the provision of eldercare services and health care among older adults. Available data can also be used in research and development around the issues of the provision of social and heath care. The connection to the SNAC-K population study gives a unique opportunity for comparisons between care recipients and non-recipients. At the baseline study, in 2001-2004, 739 60-year olds participated. The population was followed up in 2007-2009, when 608 individuals participated. Further follow-up is ongoing in 2013-2015. For more information please visit: https://www.snac-k.se/for-researchers/data-description/ https://www.snac-k.se/for-researchers/code-books/ Den nationella äldrestudien SNAC - The Swedish National Study on Aging and Care, innefattar fyra deltagande områden: SNAC-Blekinge, SNAC-Kungsholmen, SNAC-Nordanstig och SNAC-Skåne (GÅS). Vid samtliga fyra områden finns ett forskningscentrum som bedriver en befolkningsstudie och dels en vårdsystemstudie. Under 'Relaterade studier' finns beskrivning om huvudstudien SNAC, samt specifik studiebeskrivning för respektive delstudie inom SNAC. SNAC-K Kungsholmen I Stockholm svarar Äldrecentrum för studien SNAC-K. Den genomförs i Kungsholmens stadsdel som omfattar Kungsholmen och Essingeöarna. Arbetet bedrivs tillsammans med Aging Research Center (ARC). Befolkningsdel: Datainsamlingen i befolkningsdelen avser uppföljning av hälsa, sjukdom, funktionsförmåga, sociala förhållanden och vårdbehov genom upprepade undersökningar, intervjuer, enkäter etc. Denna information kompletteras med olika slag av register data. Datainsamlingen sker genom att deltagarna får träffa en sjuksköterska, en läkare och en psykolog. Vårdsystemdel: Datainsamlingen i vårdsystemdelen består av en fortlöpande kartläggning av biståndsbedömda behov och beviljade insatser från äldreomsorgen för personer över 65 år. För åren 2004-2020 omfattas samtliga omsorgstagare boende på Kungsholmen. Fr.o.m. 2015 omfattas samtliga omsorgstagare i hela Stockholms kommun. För specifika frågeställningar kompletteras data med uppgifter från Region Stockholms patientregister (VAL-databasen). Vårdsystemdelen och befolkningsdelen förenas genom de personer som deltar i båda delarna av SNAC-studien. Syfte: Inom ramen för SNAC har befolkningsdelen i delstudien SNAC-K speciellt inriktats på demens, multisjuklighet samt fysisk och mental funktionsförmåga. Syftet med studien är bland annat att studera övergången från normalt åldrande till sjuklighet och nedsatt funktionsförmåga genom att kartlägga hur sociala och biologiska faktorer, samt miljön, inverkar på de äldres hälsa och funktionsförmåga och förväntad livslängd. Avsikten är att studera negativa och positiva händelser under livet som kan ha betydelse för åldrandet. Syftet med SNAC-K vårdsystemdelen är att över tid studera olika perspektiv på jämlik och behovsstyrd äldreomsorg för personer 65 år och äldre. Detta sker geom att beskriva och analysera hur behov av bistånd bedöms och beviljas enligt Socialtjänstlagen (SoL) bland personer 65 år och äldre. Syftet innefattar även att analysera hur äldreomsorgens insatser samvarierar med konsumtion av hälso- och sjukvård och med stöd och hjälp från anhöriga (informell omsorg), och hur detta förändras över tid. Insamlade data kan användas som underlag för planering, resursfördelning och utvärdering av vården och omsorgen av de äldre. Tillgängliga data kan också användas i forsknings- och utvecklingsarbete kring frågor om vård och omsorg. Genom att kombinera data från befolkningsdelen och vårdsystemdelen ges unika möjligheter att göra jämförelser mellan dem som har och dem som inte har insatser från kommunens äldreomsorg. Vid baslinjeundersökningen, som genomfördes mellan åren 2001-2004, deltog 739 60-åringar. Populationen med 60-åringar har därefter följts upp mellan åren 2007-2009, då 608 individer deltog. Ytterligare uppföljning pågår 2013 - 2015. För mer information vänligen se: https://www.snac-k.se/for-researchers/data-description/ och https://www.snac-k.se/for-researchers/code-books/ The population study: The SNAC-K population consists of a random sample of individuals aged 60˗104 years living both at home and in institutions in Kungsholmen, Stockholm in the central part of Sweden. The random sample was stratified by age cohort and year of assessment and an oversampling of those aged 60 years respectively > 81 years of age was conducted for all the SNAC studies. In SNAC-K, eleven age cohorts were chosen (60, 66, 72, 78, 81, 84, 87, 90, 93, 96, and 99) with six year intervals for the younger cohorts and three years for the older cohorts (≥78 years). During the baseline examination in 2001-04, 3363 individuals were included (response rate 73.3%). Participants who are 78 years of age or older are followed up every three years, while for those aged 60 to 72 years, follow-up will take place every six years. Data have been collected at seven waves over a total of 20 years and is ongoing. The care system study: The care system study includes all eldercare recipients 65 years or older, for the years 2004-2020 in the district of Kungsholmen (annually ~1200-1800 individuals) and from 2015 and onwards in the whole municipality of Stockholm (annually ~21000 individuals). Befolkningsdelen: Ett urval av 3500 personer som är folkbokförda på Kungsholmen kallas när de fyller 60, 66, 72, 78, 81, 84, 87, 90, 93 eller 96 år. Dessa personer följs regelbundet - de yngre vart sjätte år och de äldre vart tredje. Vart sjätte år läggs en ny grupp 60-åringar till studiepopulationen. En första undersökning (baseline) genomfördes mellan åren 2001-2004, då 3363 personer deltog. Vårdsystemdelen: Vårdsystemdelen omfattar samtliga personer 65 år och äldre som beviljats insatser från den kommunala äldreomsorgen. För åren 2004-2020 inkluderas personer bosatta i stadsdelen Kungsholmen (årligen ca. 1200-1800 personer), fr.o.m. 2015 samtliga i Stockholms kommun (årligen ca. 21000 personer).

Abstract copyright UK Data Service and data collection copyright owner. The United Kingdom Study of Abuse and Neglect of Older People, carried out by the National Centre for Social Research (NatCen) and King’s College London, was commissioned by Comic Relief and the Department of Health. The survey included people aged 66 and over living in private households (including sheltered accommodation). Interviews lasted an average of 50 minutes and were conducted face to face using computer-assisted personal interviewing (CAPI), with a self-completion component for the most sensitive questions on sexual abuse. Respondents from government commissioned health surveys were followed up to obtain large, nationally representative random probability samples. In Wales, no such follow-up sample was available, so a random probability sample was selected from the comprehensive postcode address file. The overall response rate was 65%. The aim of the survey was to provide nationally representative prevalence estimates of elder abuse and neglect in the community. Five types of mistreatment were focused on; financial, physical, psychological and sexual abuse, and neglect. Main Topics: The research primarily focused on mistreatment which occurred within a relationship where there could reasonably be an expectation of trust – this included family members, close friends, and care workers. However, data was also gathered about mistreatment involving a whole range of perpetrators. As well as collecting information on mistreatment, the questionnaire covered a range of topics about older people's health and wellbeing, for example, social contact, general health, long-term illness, mental health, and economic status. Simple random sample Multi-stage stratified random sample Face-to-face interview Self-completion 2006 AGE AGEING BEDROOMS CARE OF THE ELDERLY CHILD BENEFITS CHRONIC ILLNESS CRIME VICTIMS DAY CARE DEBILITATIVE ILLNESS DOMESTIC VIOLENCE DRIVING LICENCES ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL CERTIFI... ELDER ABUSE ELDERLY EMOTIONAL STATES EMPLOYEES ETHNIC GROUPS Elderly FAMILY MEMBERS FINANCIAL CRIME FRIENDS FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GENDER General health and ... HEALTH HEALTH CONSULTATIONS HOME HELP HOME OWNERSHIP HOSPITAL OUTPATIENT... HOSPITALIZATION HOUSEHOLDS HOUSING BENEFITS HOUSING TENURE ILL HEALTH INCOME INFORMAL CARE JOB SEEKER S ALLOWANCE LANDLORDS LEISURE TIME ACTIVI... MEALS ON WHEELS MEDICINAL DRUGS MENTAL HEALTH MOBILITY SCOOTERS NATIONAL IDENTITY NEGLIGENCE LAW NEIGHBOURS OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... OLD AGE OLD PEOPLE S CLUBS PART TIME EMPLOYMENT PENSIONS PERSONAL CONTACT PRESCRIPTION DRUGS PRIVATE PENSIONS PUBLIC TRANSPORT QUALIFICATIONS RENTED ACCOMMODATION RESIDENTIAL CARE OF... RETIREMENT SELF EMPLOYED SOCIAL ACTIVITIES L... SOCIAL CLASS SOCIAL INTERACTION SOCIAL SECURITY BEN... SOCIAL WELFARE SERV... STATE RETIREMENT PE... STATUS IN EMPLOYMENT SUPERVISORY STATUS Specific social ser... TELEPHONE HELP LINES TIED HOUSING UNFURNISHED ACCOMMO... United Kingdom