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The STAMINA study examined the nutritional risks of low-income peri-urban mothers, infants and young children (IYC), and households in Peru during the COVID-19 pandemic. The study was designed to capture information through three, repeated cross-sectional surveys at approximately 6 month intervals over an 18 month period, starting in December 2020. The surveys were carried out by telephone in November-December 2020, July-August 2021 and in February-April 2022. The third survey took place over a longer period to allow for a household visit after the telephone interview.The study areas were Manchay (Lima) and Huánuco district in the Andean highlands (~ 1900m above sea level).In each study area, we purposively selected the principal health centre and one subsidiary health centre. Peri-urban communities under the jurisdiction of these health centres were then selected to participate. Systematic random sampling was employed with quotas for IYC age (6-11, 12-17 and 18-23 months) to recruit a target sample size of 250 mother-infant pairs for each survey.Data collected included: household socio-demographic characteristics; infant and young child feeding practices (IYCF), child and maternal qualitative 24-hour dietary recalls/7 day food frequency questionnaires, household food insecurity experience measured using the validated Food Insecurity Experience Scale (FIES) survey module (Cafiero, Viviani, & Nord, 2018), and maternal mental health.In addition, questions that assessed the impact of COVID-19 on households including changes in employment status, adaptations to finance, sources of financial support, household food insecurity experience as well as access to, and uptake of, well-child clinics and vaccination health services were included.This folder includes the dataset and dictionary of variables for survey 3 (English only).The survey questionnaire for survey 3 is available at 10.17028/rd.lboro.21740921.
For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.
Occupation data for 2021 and 2022
The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022
APS Well-Being Datasets
From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.
APS disability variables
Over time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage.
The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.
Latest edition information
For the second edition (June 2025) updated versions of the weighting variables NPWT22, PIWTA22 and PWTA22 were added to the study. The reason for the adjustment is an issue ONS identified during a recent review of the weighting method, related to the application of the non-response adjustment for boost cases. In addition, the variable YLESS20 was also updated, and DIFFHR6 was replaced with DIFFHR20. Previously missing imputed values for 'IOUTCOME=6' cases have been added.
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Demographic questions: differences in response.
The fourth in a series of surveys instituted by the Home Office in 1982, this survey examines levels of victimization in Great Britain and offers attitudinal data on issues relating to crime. The 1992 survey was intended to replicate the 1982, 1984, and 1988 surveys (ICPSR 8672, 8685, and 9850) in methodology and content as much as possible. In 1992, a "core" sample of 10,059 adults along with booster samples of 1,650 ethnic minority adults and 1,350 young people aged 12-15 resident in the same households as adult respondents were interviewed. The 1988 survey had also included an ethnic minority booster sample employing the same sampling method. Respondents were asked a series of screening questions to establish whether they had been the victims of crime during the reference period, and another series of detailed questions about the incidents they reported. Basic descriptive background information, such as sex, age, employment, education, and number of children, was also collected on the respondents and their households. Other information was elicited on fear of crime, contact with the police, lifestyle, and self-reported offending. Part 1, Demographic File, consists of data captured on the Demographic Questionnaire. Parts 2 and 3 represent data collected via Follow-Up Questionnaire A and Follow-Up Questionnaire B, respectively. Each respondent completed one of the two Follow-Up Questionnaires, with all respondents in the ethnic minority booster sample completing Follow-Up Questionnaire A. Part 4, Main File, consists of data from the Main Questionnaire. Each respondent completed a Main Questionnaire that included some attitudinal questions and a large number of screening questions to identify crime victims. Data in Part 5, Victim File, were collected from the Victim Form. Only respondents reporting incidents of victimization on the Main Questionnaire have Victim Forms, with up to four Victim Forms per respondent. The unit of analysis for this collection is the individual.
This statistic displays the results of a survey of individuals in the United Kingdom (UK) in 2012, regarding their agreement with the statement, "My family is more important to me than my career." Two percent of male respondents reported they strongly disagreed with the statement.
Abstract copyright UK Data Service and data collection copyright owner. In 2016 the Centre for Time Use Research developed an online Click and Drag Diary Instrument (CaDDI), collecting population-representative (quota sample) time use diary data from Dynata’s large international market research panel across 9 countries. We fielded the same instrument using the UK panel across the COVID-19 pandemic: in May-June 2020 during the first lockdown; in late August 2020 following the relaxation of social restrictions; in November 2020 during the second lockdown; in January 2021 during the third lockdown; and in August/September 2021 after the lifting of restrictions.Each survey wave collected between 1-3 time use diaries per respondent, recording activities, location, co-presence, device use, and enjoyment across continuous 10-minute episodes throughout the diary day. The accompanying individual screening questionnaire included information on the standard socio-demographic variables, and a diary day questionnaire containing additional health and diary day related questions was added during wave 2. Overall, 6896 diaries were collected across the 6 waves, allowing analysis of behavioural change between a baseline (in 2016), three national lockdowns, and two intervening periods of the relaxation of social restrictions.The deposited data forms part of wider CTUR projects of ESRC-funded time use research - New Frontiers for Time Use Research, and Time Use Research for National Statistics. Information on time spent in the various activities of daily life provides a comprehensive and exhaustive basis for summarising the activities of a society, yet people in general do not know with any accuracy how much time they devote to their daily activities. For this reason, rather than asking a set of survey questions, such as "how much time did you spend last week in X activity", the time use diary instead asks people to record, in sequence, all their activities through the 24-hour day, with their start and end times. Further information both on these projects and the COVID-19 sequence data collection can be found on the CTUR website.Latest edition informationFor the fourth edition (May 2022), the data and documentation files were replaced with updated versions. Amendments include the replacement of questionnaires with final versions; changes to variable ordering in the questionnaires, dataset and codebook; and updated information on the GHQ questions. See the Summary of Changes document for further details.
Understanding Society, the UK Household Longitudinal Study, is a longitudinal survey of the members of approximately 40,000 households (at Wave 1) in the United Kingdom. The overall purpose of Understanding Society is to provide high quality longitudinal data about subjects such as health, work, education, income, family, and social life to help understand the long term effects of social and economic change, as well as policy interventions designed to impact upon the general well-being of the UK population. The Understanding Society main survey sample consists of a large General Population Sample plus three other components: the Ethnic Minority Boost Sample, the former British Household Panel Survey sample and the Immigrant and Ethnic Minority Boost Sample.
For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.
Occupation data for 2021 and 2022
The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022
APS Well-Being Datasets
From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.
APS disability variables
Over time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage.
The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.
Latest edition information
For the fifth edition (July 2023), the variable FDPCH16 was added to the study.
Abstract copyright UK Data Service and data collection copyright owner. The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS) (held at the UK Data Archive under GN 33246), all of its associated LFS boosts and the APS boost. Thus, the APS combines results from five different sources: the LFS (waves 1 and 5); the English Local Labour Force Survey (LLFS), the Welsh Labour Force Survey (WLFS), the Scottish Labour Force Survey (SLFS) and the Annual Population Survey Boost Sample (APS(B) - however, this ceased to exist at the end of December 2005, so APS data from January 2006 onwards will contain all the above data apart from APS(B)). Users should note that the LLFS, WLFS, SLFS and APS(B) are not held separately at the UK Data Archive. For further detailed information about methodology, users should consult the Labour Force Survey User Guide, selected volumes of which have been included with the APS documentation for reference purposes (see 'Documentation' table below). The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples such as the WLFS and SLFS, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom. APS Well-Being data Since April 2011, the APS has included questions about personal and subjective well-being. The responses to these questions have been made available as annual sub-sets to the APS Person level files. It is important to note that the size of the achieved sample of the well-being questions within the dataset is approximately 165,000 people. This reduction is due to the well-being questions being only asked of persons aged 16 and above, who gave a personal interview and proxy answers are not accepted. As a result some caution should be used when using analysis of responses to well-being questions at detailed geography areas and also in relation to any other variables where respondent numbers are relatively small. It is recommended that for lower level geography analysis that the variable UACNTY09 is used. As well as annual datasets, three-year pooled datasets are available. When combining multiple APS datasets together, it is important to account for the rotational design of the APS and ensure that no person appears more than once in the multiple year dataset. This is because the well-being datasets are not designed to be longitudinal e.g. they are not designed to track individuals over time/be used for longitudinal analysis. They are instead cross-sectional, and are designed to use a cross-section of the population to make inferences about the whole population. For this reason, the three-year dataset has been designed to include only a selection of the cases from the individual year APS datasets, chosen in such a way that no individuals are included more than once, and the cases included are approximately equally spread across the three years. Further information is available in the 'Documentation' section below. Secure Access APS Well-Being data Secure Access datasets for the APS Well-Being include additional variables not included in either the standard End User Licence (EUL) versions (see under GN 33357) or the Special Licence (SL) access versions (see under GN 33376). Extra variables that typically can be found in the Secure Access version but not in the EUL or SL versions relate to:geography, including:Postcodes Census Area Statistics (CAS) WardsCensus Output AreasNomenclature of Units for Territorial Statistics (NUTS) level 2 and 3 areasLower and Middle Layer Super Output AreasTravel to Work AreasUnitary authority / Local Authority District of place of work (main job)region of place of work for first and second jobsqualifications, education and training including level of highest qualification, qualifications from Government schemes, qualifications related to work, qualifications from school, qualifications from university of college and qualifications gained from outside the UK detailed ethnic group for Scottish respondentsdetailed religious denomination for Northern Irish respondentslength health problem has limited activity learning difficulty or learning disabilityoccupation in apprenticeship or second job number of bedrooms number of dependent children in household aged under 19Prospective users of the Secure Access version of the APS Well-Being will need to fulfil additional requirements, commencing with the completion of an extra application form to demonstrate to the data owners exactly why they need access to the extra, more detailed variables, in order to obtain permission to use that version. Secure Access data users must also complete face-to-face training and agree to the Secure Access User Agreement and Licence Compliance Policy (see 'Access' section below). Therefore, users are encouraged to download and inspect the EUL version of the data prior to ordering the Secure Access (or SL) version. Further details and links to all APS studies available from the UK Data Archive can be found via the APS Key Data series webpage. APS Well-Being Datasets: Information, July 2016 From 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Users should no longer use the bespoke well-being datasets (SNs 6994, 6999, 7091, 7092, 7364, 7365, 7565, 7566 and 7961, but should now use the variables included on the April-March APS person datasets instead. Further information on the transition can be found on the Personal well-being in the UK: 2015 to 2016 Documentation and coding frames The APS is compiled from variables present in the LFS. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation (e.g. coding frames for education, industrial and geographic variables, which are held in LFS User Guide Vol.5, Classifications), users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages. May 2018 Update Due to a change in the Travel-to-Work Area coding structure from 2001 to 2011, the variable TTWA9D has been relabelled in the pooled data file for 2012-2015. Main Topics: Topics covered include: household composition and relationships, housing tenure, nationality, ethnicity and residential history, employment and training (including government schemes), workplace and location, job hunting, educational background and qualifications. Many of the variables included in the survey are the same as those in the LFS. Multi-stage stratified random sample Face-to-face interview Telephone interview 2011 2015 ACADEMIC ACHIEVEMENT ADULT EDUCATION ADVANCED LEVEL EXAM... ADVANCED SUPPLEMENT... AGE ANXIETY APPLICATION FOR EMP... APPRENTICESHIP ARMED FORCES ATTITUDES BEDROOMS BUSINESS AND TECHNO... CARE OF DEPENDANTS CERTIFICATE OF SECO... CERTIFICATE OF SIXT... CHILDREN CITY AND GUILDS OF ... COHABITATION Censuses DEBILITATIVE ILLNESS DEGREES DISABILITIES DISABLED PERSONS ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL CERTIFI... EDUCATIONAL COURSES EDUCATIONAL STATUS EMPLOYEES EMPLOYER SPONSORED ... EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES EMPLOYMENT SERVICES ETHNIC GROUPS FAMILIES FIELDS OF STUDY FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... FURTHER EDUCATION GENDER GENERAL CERTIFICATE... GENERAL NATIONAL VO... GENERAL SCOTTISH VO... HAPPINESS HEADS OF HOUSEHOLD HEALTH HEALTH STATUS HIGHER EDUCATION HIGHER NATIONAL CER... HOURS OF WORK HOUSEHOLDS HOUSING HOUSING TENURE ILL HEALTH INCOME INDUSTRIES JOB CHANGING JOB HUNTING LANDLORDS LEARNING DISABILITIES LONGTERM UNEMPLOYMENT Labour and employment MANAGERS MARITAL STATUS NATIONAL IDENTITY NATIONAL VOCATIONAL... NATIONALITY NURSING EDUCATION OCCUPATIONAL QUALIF... OCCUPATIONS ORDINARY LEVEL EXAM... ORDINARY NATIONAL C... OVERTIME PART TIME COURSES PART TIME EMPLOYMENT PLACE OF BIRTH PLACE OF RESIDENCE PRIVATE SECTOR PUBLIC SECTOR QUALIFICATIONS REDUNDANCY RELIGIOUS AFFILIATION RESIDENTIAL MOBILITY ROYAL SOCIETY OF AR... RURAL AREAS SCOTTISH CERTIFICAT... SCOTTISH VOCATIONAL... SCOTTISH VOCATIONAL... SELF EMPLOYED SICK LEAVE SMOKING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS SPOUSES STUDENTS SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS TEMPORARY EMPLOYMENT TERMINATION OF SERVICE TIED HOUSING TRAINING TRAINING COURSES UNEMPLOYED UNEMPLOYMENT UNFURNISHED ACCOMMO... UNWAGED WORKERS URBAN AREAS United Kingdom VOCATIONAL EDUCATIO... WAGES WELL BEING SOCIETY WORKING CONDITIONS WORKPLACE
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These data are from a cohort of over 4000 pregnant women in Mchinji District, Malawi, who were followed up for 6 months after the end of their pregnancy. The women were asked the London Measure of Unplanned Pregnancy (LMUP) and the pregnancy intention question from the Demographic and Health Survey (DHS) at 1 and 6 months postnatally. The order of these two questions was varied in order to be able to investigate whether there was any effect of question order on the reported level of pregnancy intention with either the LMUP or the DHS.
This is a repository for a UKRI Economic and Social Research Council (ESRC) funded project to understand the software used to analyse social sciences data. Any software produced has been made available under a BSD 2-Clause license and any data and other non-software derivative is made available under a CC-BY 4.0 International License. Note that the software that analysed the survey is provided for illustrative purposes - it will not work on the decoupled anonymised data set. Exceptions to this are: Data from the UKRI ESRC is mostly made available under a CC BY-NC-SA 4.0 Licence. Data from Gateway to Research is made available under an Open Government Licence (Version 3.0). Contents Survey data & analysis: esrc_data-survey-analysis-data.zip Other data: esrc_data-other-data.zip Transcripts: esrc_data-transcripts.zip Data Management Plan: esrc_data-dmp.zip Survey data & analysis The survey ran from 3rd February 2022 to 6th March 2023 during which 168 responses were received. Of these responses, three were removed because they were supplied by people from outside the UK without a clear indication of involvement with the UK or associated infrastructure. A fourth response was removed as both came from the same person which leaves us with 164 responses in the data. The survey responses, Question (Q) Q1-Q16, have been decoupled from the demographic data, Q17-Q23. Questions Q24-Q28 are for follow-up and have been removed from the data. The institutions (Q17) and funding sources (Q18) have been provided in a separate file as this could be used to identify respondents. Q17, Q18 and Q19-Q23 have all been independently shuffled. The data has been made available as Comma Separated Values (CSV) with the question number as the header of each column and the encoded responses in the column below. To see what the question and the responses correspond to you will have to consult the survey-results-key.csv which decodes the question and responses accordingly. A pdf copy of the survey questions is available on GitHub. The survey data has been decoupled into: survey-results-key.csv - maps a question number and the responses to the actual question values. q1-16-survey-results.csv- the non-demographic component of the survey responses (Q1-Q16). q19-23-demographics.csv - the demographic part of the survey (Q19-Q21, Q23). q17-institutions.csv - the institution/location of the respondent (Q17). q18-funding.csv - funding sources within the last 5 years (Q18). Please note the code that has been used to do the analysis will not run with the decoupled survey data. Other data files included CleanedLocations.csv - normalised version of the institutions that the survey respondents volunteered. DTPs.csv - information on the UKRI Doctoral Training Partnerships (DTPs) scaped from the UKRI DTP contacts web page in October 2021. projectsearch-1646403729132.csv.gz - data snapshot from the UKRI Gateway to Research released on the 24th February 2022 made available under an Open Government Licence. locations.csv - latitude and longitude for the institutions in the cleaned locations. subjects.csv - research classifications for the ESRC projects for the 24th February data snapshot. topics.csv - topic classification for the ESRC projects for the 24th February data snapshot. Interview transcripts The interview transcripts have been anonymised and converted to markdown so that it's easier to process in general. List of interview transcripts: 1269794877.md 1578450175.md 1792505583.md 2964377624.md 3270614512.md 40983347262.md 4288358080.md 4561769548.md 4938919540.md 5037840428.md 5766299900.md 5996360861.md 6422621713.md 6776362537.md 7183719943.md 7227322280.md 7336263536.md 75909371872.md 7869268779.md 8031500357.md 9253010492.md Data Management Plan The study's Data Management Plan is provided in PDF format and shows the different data sets used throughout the duration of the study and where they have been deposited, as well as how long the SSI will keep these records.
Abstract copyright UK Data Service and data collection copyright owner.The Taking Part survey collects data on many aspects of leisure, culture and sport in England, as well as an in-depth range of socio-demographic information on respondents. The survey is commissioned by the Department for Digital, Culture, Media and Sport (DCMS) in partnership with three of its non-departmental public bodies (Sport England, Arts Council England and English Heritage). The survey was first commissioned in 2005 as a face-to-face household survey of adults (16+) in England. Since then it has run annually and has also been developed to include further elements, including a child element and a longitudinal element. Further information can be found on the gov.uk Taking Part web pages. Main topics covered by the survey include: the arts, museums and galleries, libraries, archives, heritage, sport, World War I, the Olympics, volunteering, charitable giving and demographics. These topics appear in the main adult and child datasets, and in the adult longitudinal dataset. The Child Boost dataset only contains questions on sports participation. This study is subject to restrictive Special Licence (SL) access conditions as it contains additional detailed geographic variables (Local Authorities; ACORN Group; ACORN Category; ONS Urban Rural Classification). The End User Licence (EUL) version which is the same, but excludes these detailed variables, is available from the UK Data Service under SN 7872. Users are advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. The SL data have more restrictive access conditions; prospective users of the SL version will need to complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables in order to get permission to use that version. Main Topics: Main topics covered by the survey include: the arts, museums and galleries, libraries, archives, heritage, sport, World War I, the Olympics, volunteering, charitable giving and demographics. These topics appear in the main adult and child datasets, and in the adult longitudinal dataset. The Child Boost dataset only contains questions on sports participation. Multi-stage stratified random sample See documentation for details Face-to-face interview
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The Health Survey for England (HSE) is part of a programme of surveys commissioned by the Health and Social Care Information Centre. It has been carried out since 1994 by the Joint Health Surveys Unit of NatCen Social Research and the Research Department of Epidemiology and Public Health at UCL (University College London). The study provides regular information that cannot be obtained from other sources on a range of aspects concerning the public's health and many of the factors that affect health. The series of Health Surveys for England was designed to monitor trends in the nation's health, to estimate the proportion of people in England who have specified health conditions, and to estimate the prevalence of certain risk factors and combinations of risk factors associated with these conditions. The survey is also used to monitor progress towards selected health targets. Each survey in the series includes core questions and measurements (such as blood pressure, anthropometric measurements and analysis of blood and saliva samples), as well as modules of questions on specific issues that vary from year to year. In some years, the core sample has also been augmented by an additional boosted sample from a specific population subgroup, such as minority ethnic groups, older people or children; there was no boost in 2012. This is the 22nd annual Health Survey for England. All surveys have covered the adult population aged 16 and over living in private households in England. Since 1995, the surveys have included children who live in households selected for the survey; children aged 2-15 were included from 1995, and infants under two years old were added in 2001. Those living in institutions were outside the scope of the survey. This should be borne in mind when considering survey findings, since the institutional population is likely to be older and less healthy than those living in private households. The HSE in 2012 provided a representative sample of the population at both national and regional level. 9,024 addresses were randomly selected in 564 postcode sectors, issued over twelve months from January to December 2012. Where an address was found to have multiple dwelling units, a random selection was made and a single dwelling unit was included. Where there were multiple households at a dwelling unit, again one was selected at random. All adults and children in selected households were eligible for inclusion in the survey. Where there were three or more children aged 0-15 in a household, two of the children were selected at random to limit the respondent burden for parents. A nurse visit was arranged for all participants who consented. A total of 8,291 adults and 2,043 children were interviewed. A household response rate of 64 per cent was achieved. 5,470 adults and 1,203 children had a nurse visit. It should be noted that, as in 2011, there was no child boost sample in 2012. Thus the scope for analyses of some data for children may be limited by relatively small sample sizes.
These are anonymized responses to a survey of 389 members of the UK public on their perceptions towards different maps about the social determinants of health. It was originally collected as part of a study described in the article 'Do personal narratives make thematic maps more persuasive? Integrating concrete examples into maps of the social determinants of health', in the Cartography and Geographic Information Science journal.The responses were collected in September 2024 on Qualtrics, via the recruitment platform Prolific.Participants were shown information on three social determinants of health (public transport, air pollution, youth services). For each topic, they were randomly shown one of three maps with varying levels of personal narratives presented. The type of map shown to each respondent can be found in columns 'transport_condition', 'pollution_condition', and 'youth_condition'. Most of the other variables refer to perceptions about those issues. For example, 'severity_pollution' refers to whether they deem air pollution a severe issue facing the country. Other variables include demographic information, chart literacy measured by four questions, and self-assessed confidence with charts.
The Scottish Government has three large scale cross sectional population surveys (Scottish Crime and Justice Survey (SCJS), Scottish Health Survey (SHeS) and Scottish Household Survey (SHS)). Since the beginning of 2012 each of the surveys has included a set of 20 core harmonised questions. Responses on these questions from all three surveys have been pooled to provide a dataset with a sample size of over 20,000 responses annually. The Scottish Core Survey Questions include socioeconomic and geographic variables and perception questions on health, crime and police performance. This publication provides latest figures from SSCQ, relating to the 2014 collection period
Abstract copyright UK Data Service and data collection copyright owner. The Online Time Use Survey (OTUS) was developed by the Office for National Statistics to help improve the measurement of unpaid household production and caring activities that are not captured within traditional economic measures, and to understand better time use from a well-being and quality of life perspective. The survey collects information from adults aged 18 years and over who are randomly sampled from the NatCen Opinion Panel, which is representative of the UK population. Data collected between March 2020 and March 2021 covers Great Britain and data collected from March 2022 onwards covers the United Kingdom. Participants were issued with two pre-allocated diary days (one on a weekday and one on a weekend day). They were asked to record their main activities (in 10-minute intervals) and up to five secondary activities (in five-minute intervals) in every 24 hours within an online diary tool. Respondents were able to select activities from a pre-defined list. They were also asked to rate how much they enjoyed different activities. In addition, respondents were asked to complete a demographic questionnaire which records personal and household characteristics.Latest edition informationFor the third edition (August 2024), data and documentation for Wave 8 (9 to 17 March 2024) were added to the study. Main Topics: The annual data files include the following variables:main activities (in 10-minute periods) up to five secondary activities (in five-minute periods)count of all 5-minute primary activities total in minutes of all primary activitiescount of all 5-minute secondary activitiestotal in minutes of all secondary activitiesenjoyment level (scale 1-7) for all primary activities (in 10-minute periods) enjoyment level (scale 1-7) for all secondary activities (in five-minute periods)basic demographics, including personal well-being rating variables.
Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (OPN) is an omnibus survey that collects data from respondents in Great Britain. Information is gathered on a range of subjects, commissioned both internally by the Office for National Statistics (ONS) and by external clients (other government departments, charities, non-profit organisations and academia).One individual respondent, aged 16 or over, is selected from each sampled private household to answer questions. Data are gathered on the respondent, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. Each regular OPN survey consists of two elements. Core questions, covering demographic information, are asked together with non-core questions that vary depending on the module(s) fielded.The OPN 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. The OPN has 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 gov.uk OPN Quality and Methodology Information (QMI) webpage.Changes over timeUp to March 2018, the OPN was conducted as a face-to-face survey. From April 2018 to November 2019, the OPN changed 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 module 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 under Secure Access conditions in SN 8635, ONS Opinions and Lifestyle Survey, 2019-2023: Secure Access. (See below for information on other Secure Access OPN modules.)From August 2021, as coronavirus (COVID-19) restrictions were lifted across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remained sustainable. Secure Access OPN modulesBesides SN 8635 (which includes the COVID-19 Module), other Secure Access OPN data includes sensitive modules run at various points from 1997-2019, including 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 the individual studies for further details and information on how to apply to use them. Alongside the usual Classification questions, this study includes the following non-core OPN modules:MAZ Internet Access module, run in January, February and April 2018 (also includes questions on Citizenship (passports), and Higher Education (whether respondent has a degree). This module was conducted on behalf of ONS and covers internet use for work, leisure, purchasing, banking, and other services, via computers, mobile devices and smartphones.MAK Train Satisfaction module, run in February 2018. This module was conducted on behalf of the Department for Transport and covers short- and long-distance train travel and opinions on various aspects of train services. (This module was previously held separately under SN 8576, which is no longer available.) Main Topics: Internet access and use, train travel and satisfaction with rail services, citizenship, higher education, and other demographics. Multi-stage stratified random sample Face-to-face interview
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Percentage of responses in range 0-6 out of 10 (corresponding to 'low wellbeing') for 'Life Satisfaction' in the First ONS Annual Experimental Subjective Wellbeing survey.
The Office for National Statistics has included the four subjective well-being questions below on the Annual Population Survey (APS), the largest of their household surveys.
This dataset presents results from the first of these questions, "Overall, how satisfied are you with your life nowadays?" Respondents answer these questions on an 11 point scale from 0 to 10 where 0 is ‘not at all’ and 10 is ‘completely’. The well-being questions were asked of adults aged 16 and older.
Well-being estimates for each unitary authority or county are derived using data from those respondents who live in that place. Responses are weighted to the estimated population of adults (aged 16 and older) as at end of September 2011.
The data cabinet also makes available the proportion of people in each county and unitary authority that answer with ‘low wellbeing’ values. For the ‘life satisfaction’ question answers in the range 0-6 are taken to be low wellbeing.
This dataset contains the percentage of responses in the range 0-6. It also contains the standard error, the sample size and lower and upper confidence limits at the 95% level.
The ONS survey covers the whole of the UK, but this dataset only includes results for counties and unitary authorities in England, for consistency with other statistics available at this website.
At this stage the estimates are considered ‘experimental statistics’, published at an early stage to involve users in their development and to allow feedback. Feedback can be provided to the ONS via this email address.
The APS is a continuous household survey administered by the Office for National Statistics. It covers the UK, with the chief aim of providing between-census estimates of key social and labour market variables at a local area level. Apart from employment and unemployment, the topics covered in the survey include housing, ethnicity, religion, health and education. When a household is surveyed all adults (aged 16+) are asked the four subjective well-being questions.
The 12 month Subjective Well-being APS dataset is a sub-set of the general APS as the well-being questions are only asked of persons aged 16 and above, who gave a personal interview and proxy answers are not accepted. This reduces the size of the achieved sample to approximately 120,000 adult respondents in England.
The original data is available from the ONS website.
Detailed information on the APS and the Subjective Wellbeing dataset is available here.
As well as collecting data on well-being, the Office for National Statistics has published widely on the topic of wellbeing. Papers and further information can be found here.
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The Health Survey for England series was designed to monitor trends in the nation's health; estimating the proportion of people in England who have specified health conditions, and the prevalence of risk factors and behaviours associated with these conditions. The surveys provide regular information that cannot be obtained from other sources. The surveys have been carried out since 1994 by the Joint Health Surveys Unit of NatCen Social Research and the Research Department of Epidemiology and Public Health at UCL. Each survey in the series includes core questions, e.g. about alcohol and smoking, and measurements (such as blood pressure, height and weight, and analysis of blood and saliva samples), and modules of questions on topics that vary from year to year. The trend tables show data for available years between 1993 and 2016 for adults (defined as age 16 and over) and for children. The survey samples cover the population living in private households in England. In 2016 the sample contained 8,011 adults and 2,056 children and 5,049 adults and 1,117 children had a nurse visit. We would very much like your feedback about whether some proposed changes to the publications would be helpful and if the publications meet your needs. This will help us shape the design of future publications to ensure they remain informative and useful. Please answer our reader feedback survey on Citizen Space which is open until 18 June 2018.
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Concern has been expressed over societal losses of plant species identification skills. These losses have potential implications for engagement with conservation issues, gaining human wellbeing benefits from biodiversity (such as those resulting from nature-based recreational activities), and early warning of the spread of problematic species. However, understanding of the prevailing level of species identification skills, and of its key drivers, remains poor. Here, we explore socio-demographic factors influencing plant identification knowledge and ability to classify plants as native or non-native, employing a novel method of using real physical plants, rather than photographs or illustrations. We conducted face-to-face surveys at three different sites chosen to capture respondents with a range of socio-demographic circumstances, in Cornwall, UK. We found that survey participants correctly identified c.60% of common plant species, were significantly worse at naming non-native than native plants, and that less than 20% of people recognised Japanese knotweed Fallopia japonica, which is a widespread high profile invasive non-native in the study region. Success at naming plants was higher if participants were female, a member of at least one environmental, conservation or gardening organisation, in an older age group (than the base category of 18–29 years), or a resident (rather than visitor) of the study area. Understanding patterns of variation in plant identification knowledge can inform the development of education and engagement strategies, for example, by targeting sectors of society where knowledge is lowest. Furthermore, greater understanding of general levels of identification of problematic invasive non-native plants can guide awareness and education campaigns to mitigate their impacts.
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The STAMINA study examined the nutritional risks of low-income peri-urban mothers, infants and young children (IYC), and households in Peru during the COVID-19 pandemic. The study was designed to capture information through three, repeated cross-sectional surveys at approximately 6 month intervals over an 18 month period, starting in December 2020. The surveys were carried out by telephone in November-December 2020, July-August 2021 and in February-April 2022. The third survey took place over a longer period to allow for a household visit after the telephone interview.The study areas were Manchay (Lima) and Huánuco district in the Andean highlands (~ 1900m above sea level).In each study area, we purposively selected the principal health centre and one subsidiary health centre. Peri-urban communities under the jurisdiction of these health centres were then selected to participate. Systematic random sampling was employed with quotas for IYC age (6-11, 12-17 and 18-23 months) to recruit a target sample size of 250 mother-infant pairs for each survey.Data collected included: household socio-demographic characteristics; infant and young child feeding practices (IYCF), child and maternal qualitative 24-hour dietary recalls/7 day food frequency questionnaires, household food insecurity experience measured using the validated Food Insecurity Experience Scale (FIES) survey module (Cafiero, Viviani, & Nord, 2018), and maternal mental health.In addition, questions that assessed the impact of COVID-19 on households including changes in employment status, adaptations to finance, sources of financial support, household food insecurity experience as well as access to, and uptake of, well-child clinics and vaccination health services were included.This folder includes the dataset and dictionary of variables for survey 3 (English only).The survey questionnaire for survey 3 is available at 10.17028/rd.lboro.21740921.