Dataset population: Persons in households

NS-SeC of HRP

The National Statistics Socio-economic Classification (NS-SeC) provides an indication of socio-economic position based on occupation. It is an Office for National Statistics standard classification.

To assign a person aged 16 to 74 to an NS-SeC category, their occupation title is combined with information about their employment status, whether they are employed or self-employed and whether or not they supervise other employees. Full-time students are recorded in the 'full-time students' category regardless of whether they are economically active or not.

The rebased version of NS-SeC used in census results uses occupation coded to SOC2010. Information about the classification is available here: NS-SEC rebased on SOC2010.

For 'Long-term unemployed', the year last worked is 2009 or earlier. In 2011 Census results, because the census did not ask a question about the number of employees at a person's workplace, the reduced method of deriving NS-SeC (which does not require this information) is used.

The concept of a Household Reference Person (HRP) was introduced in the 2001 Census (in common with other government surveys in 2001/2) to replace the traditional concept of the 'head of the household'. HRPs provide an individual person within a household to act as a reference point for producing further derived statistics and for characterising a whole household according to characteristics of the chosen reference person.

This file contains original variables from Theme 9 Social Class from Census 2011 and a series of additional variables produced by AIRO such as percentage rates, ratios etc. The file includes data on Social Class, Socio-Economic Group of Persons and Persons in Private Households for the 18,488 Small Areas in the Republic of Ireland.

Dataset population: Persons aged under 65 in households

NS-SeC of HRP

The National Statistics Socio-economic Classification (NS-SeC) provides an indication of socio-economic position based on occupation. It is an Office for National Statistics standard classification.

To assign a person aged 16 to 74 to an NS-SeC category, their occupation title is combined with information about their employment status, whether they are employed or self-employed and whether or not they supervise other employees. Full-time students are recorded in the 'full-time students' category regardless of whether they are economically active or not.

The rebased version of NS-SeC used in census results uses occupation coded to SOC2010. Information about the classification is available here: NS-SEC rebased on SOC2010.

For 'Long-term unemployed', the year last worked is 2009 or earlier. In 2011 Census results, because the census did not ask a question about the number of employees at a person's workplace, the reduced method of deriving NS-SeC (which does not require this information) is used.

The concept of a Household Reference Person (HRP) was introduced in the 2001 Census (in common with other government surveys in 2001/2) to replace the traditional concept of the 'head of the household'. HRPs provide an individual person within a household to act as a reference point for producing further derived statistics and for characterising a whole household according to characteristics of the chosen reference person.

Data showing the National Statistics Socio-economic Classification of residents in Plymouth.

This dataset provides 2011 Census estimates that classify Household Reference Persons aged 16 to 64 living in households by approximated social grade, for the UK, constituent countries and, within England, regions, counties, London boroughs, metropolitan districts, unitary authorities and non-metropolitan districts, unitary authorities within Wales, council areas within Scotland, and local government districts within Northern Ireland. The estimates are as at census day, 27 March 2011. Social grade is a socio-economic classification used by market research industries to analyse spending habits and consumer attitudes.Orignal dataset can be found here.

Dataset population: Household Reference Persons

Age

Age is derived from the date of birth question and is a person's age at their last birthday, at 27 March 2011. Dates of birth that imply an age over 115 are treated as invalid and the person's age is imputed. Infants less than one year old are classified as 0 years of age.

Household Reference Person

The concept of a Household Reference Person (HRP) was introduced in the 2001 Census (in common with other government surveys in 2001/2) to replace the traditional concept of the 'head of the household'. HRPs provide an individual person within a household to act as a reference point for producing further derived statistics and for characterising a whole household according to characteristics of the chosen reference person.

For a person living alone, it follows that this person is the HRP.

If a household contains only one family (with or without ungrouped individuals) then the HRP is the same as the Family Reference Person (FRP).

For families in which there is generational divide between family members that cannot be determined (Other related family), there is no FRP. Members of these families are treated the same as ungrouped individuals.

If there is more than one family in a household the HRP is chosen from among the FRPs using the same criteria used to choose the FRP. This means the HRP will be selected from the FRPs on the basis of their economic activity, in the priority order:

• Economically active: Employed: Full-time: Non-student
• Economically active: Employed: Full-time: Student
• Economically active: Employed: Part-time: Non-student
• Economically active: Employed: Part-time: Student
• Economically active: Unemployed: Non-student
• Economically active: Unemployed: Student
• Economically inactive: Retired
• Economically inactive: Other

If some or all FRPs have the same economic activity, the HRP is the eldest of the FRPs. If some or all are the same age, the HRP is the first of the FRPs from the order in which they were listed on the questionnaire.

If a household is made up entirely of any combination of ungrouped individuals and other related families, the HRP is chosen from among all people in the household, using the same criteria used to chose between FRPs. Students at their non-term-time address and short-term migrants cannot be the HRP.

NS-SeC

The National Statistics Socio-economic Classification (NS-SeC) provides an indication of socio-economic position based on occupation. It is an Office for National Statistics standard classification.

To assign a person aged 16 to 74 to an NS-SeC category, their occupation title is combined with information about their employment status, whether they are employed or self-employed and whether or not they supervise other employees. Full-time students are recorded in the 'full-time students' category regardless of whether they are economically active or not.

The rebased version of NS-SeC used in census results uses occupation coded to SOC2010. Information about the classification is available here: NS-SEC rebased on SOC2010.

For 'Long-term unemployed', the year last worked is 2009 or earlier. In 2011 Census results, because the census did not ask a question about the number of employees at a person's workplace, the reduced method of deriving NS-SeC (which does not require this information) is used.

Tenure

Tenure provides information about whether a household rents or owns the accommodation that it occupies and, if rented, combines this with information about the type of landlord who owns or manages the accommodation.

The data project includes the variables, the questions and the algorithms (in SPSS) required for the derivation of the full European Socio-economic Classification (ESeC). The name of the target variable derived is "euroesec". The European Socio-economic Classification (ESeC) is an occupationally based classification. The term ‘socio- economic classification’ (SEC) has no theoretical or analytic status whatever and so may be applied as a generic term for a variety of different measures designed to reflect how societies are stratified. Social stratification refers to social inequalities that may be attributed to the way a society is organised, to its socio-economic structure.

This survey collected data to generate a comprehensive review of the economic and policy status of the recreational for-hire sector in the U.S. Gulf of Mexico, including charter, head, and guide boats. The survey created a socioeconomic dataset that can be used to analyze future economic, environmental, and policy questions, including those related to natural disturbances and the ongoing regulation of resource utilization in the Gulf. The specific project objectives included a) collecting economic, social, and policy data for all segments of the for-hire sector b) identifying groups of respondents with relatively homogeneous characteristics, thereby defining operational classes that may be the focus of targeted, management-based economic and policy analysis and c) constructing costs, earnings, and attitudinal profiles by operational class and state/region. The survey was conducted by mail, internet, and in-person interviews in 2010.

This data is Statistical Local Areas (SLA) based Socio-Economic Indexes for Areas (SEIFA) Index of Disadvantage (IRSD) - focuses on low-income earners, relatively lower educational attainment, high unemployment and variables reflecting disadvantage. This data is based on the 2006 census and follows the 2006 Australian Standard Geographical Classification (ASGC) boundaries. The Australian Bureau of Statistics (ABS) has developed indexes to allow ranking of regions/areas, providing a method of determining the level of social and economic wellbeing in that region. There are four indexes included in the SEIFA 2006 product. They relate to socio-economic aspects of geographic areas. Each index summarises a different aspect of the socio-economic conditions in an area. The indexes have been obtained by a technique called principal components analysis. This technique summarises the information from a variety of social and economic variables, calculating weights that will give the best summary for the underlying variables. For the SEIFA indexes, each index uses a different set of underlying variables. All the indexes (including the Index of Relative Socio-Economic Disadvantage) have been constructed so that relatively disadvantaged areas (e.g. areas with many low income earners) have low index values. This data is ABS data (catalogue number: 2033.0.55.001) used with permission from the Australian Bureau of Statistics.

Abstract copyright UK Data Service and data collection copyright owner. The two former official measures of social class - Social Class by Occupation (SC), previously known as Registrar General's Social Class (RGSC), and Socio-economic Groups (SEG) - were discontinued in 2001 when the National Statistics Socio-economic Classification (NS-SEC) was adopted as the sole official measure of social class in the UK. Derivation Matrices for the Former Official Measures of Social Class, 2000, 2010 and 2020 provides derivation matrices for SC and SEG from the Standard Occupational Classifications 2000, 2010, and 2020 after their official discontinuation to enable their use in longitudinal data and comparative analyses.Further information is available in the publications detailing the 2010 and 2020 work. Main Topics:

Context

The Philippine Statistics Authority (PSA) spearheads the conduct of the Family Income and Expenditure Survey (FIES) nationwide. The survey, which is undertaken every three (3) years, is aimed at providing data on family income and expenditure, including, among others, levels of consumption by item of expenditure, sources of income in cash, and related information affecting income and expenditure levels and patterns in the Philippines.

Content

Inside this data set is some selected variables from the latest Family Income and Expenditure Survey (FIES) in the Philippines. It contains more than 40k observations and 60 variables which is primarily comprised of the household income and expenditures of that specific household

Acknowledgements

The Philippine Statistics Authority for providing the publisher with their raw data

Inspiration

Socio-economic classification models in the Philippines has been very problematic. In fact, not one SEC model has been widely accepted. Government bodies uses their own SEC models and private research entities uses their own. We all know that household income is the greatest indicator of one's socio-economic classification that's why the publisher would like to find out the following:

1) Best model in predicting household income 2) Key drivers of household income, we want to make the model as sparse as possible 3) Some exploratory analysis in the data would also be useful

Abstract copyright UK Data Service and data collection copyright owner.

The Great Britain Historical Database has been assembled as part of the ongoing Great Britain Historical GIS Project. The project aims to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain at sub-county scales. Further information about the project is available on A Vision of Britain webpages, where users can browse the database's documentation system online.

These data were originally collected by the Censuses of Population for England and Wales, and for Scotland. They were computerised by the Great Britain Historical GIS Project and its collaborators. They form part of the Great Britain Historical Database, which contains a wide range of geographically-located statistics, selected to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain, generally at sub-county scales.

The first census report to tabulate social class was 1951, but this collection also includes a table from the Registrar-General's 1931 Decennial Supplement which drew on census occupational data to tabulate social class by region. In 1961 and 1971 the census used a more detailed classification of Socio-Economic Groups, from which the five Social Classes are a simplification.

This is a new edition. Data from the Census of Scotland have been added for 1951, 1961 and 1971. Wherever possible, ID numbers have been added for counties and districts which match those used in the digital boundary data created by the GBH GIS, greatly simplifying mapping.

Main Topics:

Social Class Statistics from the 1931 Decennial Supplement for regions.

Social Class Statistics from the 1951, 1961 and 1971 Censuses (including Scotland), mainly for men and type of occupation.

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

This dataset is about book series and is filtered where the books is The OPCS socio-economic area classifications : an evaluation of their effectiveness for vital statistics, featuring 10 columns including authors, average publication date, book publishers, book series, and books. The preview is ordered by number of books (descending).

Dataset population: Persons aged 16 and over

General health

General health is a self-assessment of a person's general state of health. People were asked to assess whether their health was very good, good, fair, bad or very bad.

For England and Wales, this assessment is not based on a person's health over any specified period of time.

NS-SeC

The National Statistics Socio-economic Classification (NS-SeC) provides an indication of socio-economic position based on occupation. It is an Office for National Statistics standard classification.

To assign a person aged 16 to 74 to an NS-SeC category, their occupation title is combined with information about their employment status, whether they are employed or self-employed and whether or not they supervise other employees. Full-time students are recorded in the 'full-time students' category regardless of whether they are economically active or not.

The rebased version of NS-SeC used in census results uses occupation coded to SOC2010. Information about the classification is available here: NS-SEC rebased on SOC2010.

For 'Long-term unemployed', the year last worked is 2009 or earlier. In 2011 Census results, because the census did not ask a question about the number of employees at a person's workplace, the reduced method of deriving NS-SeC (which does not require this information) is used.

Dataset population: Persons aged 16 and over

NS-SeC

The National Statistics Socio-economic Classification (NS-SeC) provides an indication of socio-economic position based on occupation. It is an Office for National Statistics standard classification.

To assign a person aged 16 to 74 to an NS-SeC category, their occupation title is combined with information about their employment status, whether they are employed or self-employed and whether or not they supervise other employees. Full-time students are recorded in the 'full-time students' category regardless of whether they are economically active or not.

The rebased version of NS-SeC used in census results uses occupation coded to SOC2010. Information about the classification is available here: NS-SEC rebased on SOC2010.

For 'Long-term unemployed', the year last worked is 2009 or earlier. In 2011 Census results, because the census did not ask a question about the number of employees at a person's workplace, the reduced method of deriving NS-SeC (which does not require this information) is used.

Religion

This is a person's current religion, or if the person does not have a religion, 'No religion'. No determination is made about whether a person was a practicing member of a religion. Unlike other census questions where missing answers are imputed, this question was voluntary and where no answer was provided, the response is categorised as 'Not stated'.

A more recent web map on this same topic is available for ArcGIS Online subscribers here.This map shows the socioeconomic status of each census tract. Data come from the US Census Bureau's 2011-2015 American Community Survey. Neighborhood Socioeconomic Status, over and above individual socioeconomic status, is a predictor of many health outcomes. The Neighborhood Socioeconomic Status (NSES) Index is on a scale from 0 to 100 with 50 being the national average around 2010. The Index incorporates the following indicators (fields in this layer's attribute table):Median Household Income (from Table B19013)Percent of individuals with income below the Federal Poverty Line (from Table S1701)The educational attainment of adults (age 25+) (from Table B15003)Unemployment Rate (from Table S2301)Percent of households with children under the age of 18 that are "female-headed" (no male present) (from Table B11005)NSES = log(median household income) + (-1.129 * (log(percent of female-headed households))) + (-1.104 * (log(unemployment rate))) + (-1.974 * (log(percent below poverty))) + .451*((high school grads)+(2*(bachelor's degree holders)))To learn more about how the NSES Index was developed, please explore this journal articleMiles, Jeremy and Weden, Margaret; Lavery, Diana; Escarce, José; Kathleen Cagney; Shih, Regina. 2016. “Constructing a Time-Invariant Measure of the Socio-Economic Status of U.S. Census Tracts.” Journal of Urban Health, vol. 93, issue no.1, pp. 213-232. or this PPT presentation presented at the University of Texas at San Antonio's Applied Demography Conference in 2014.

Abstract copyright UK Data Service and data collection copyright owner.

The Integrated Household Survey (IHS), which ran from 2009-2014, was a composite survey combining questions asked on a number of social surveys conducted by the Office for National Statistics (ONS) to produce a dataset of 'core' variables. The ONS stopped producing IHS datasets from 2015 onwards; variables covering health, smoking prevalence, forces veterans, sexual identity and well-being will be incorporated into the Annual Population Survey - see the Which surveys (or modules) are included in the IHS? and What is the IHS? FAQ pages for further details.

Background and history of the IHS
The aim of the IHS was to produce high-level estimates for particular themes to a higher precision and lower geographic level than current ONS social surveys. The 'core' set contained around 100 questions, but a respondent was only asked a proportion of those depending on routing from answers to questions. The core questions were asked, where possible, at the beginning of the component surveys.
In January 2008, a set of core questions was introduced within three ONS surveys in the General Lifestyle Survey, Living Costs and Food Survey, and the Opinions and Lifestyle Survey. In April 2008 the IHS core questions were also introduced on the English Housing Survey, bringing the family of modules on the IHS up to four. The IHS dataset for 2008-2009 was used as a pilot for the concept, developing the systems and designing the weighting methodology. The IHS data for that period have not been published as they do not provide better quality information than that within existing surveys. Hence, the earliest IHS data currently available cover 2009-2010. In April 2009 the IHS core questions were introduced on the Labour Force Survey (LFS) and Annual Population Survey (APS) questionnaires and from June 2009 the Life Opportunities Survey (LOS, which also ran from 2009-2014) was included in the IHS family of modules. With the inclusion of these new surveys the IHS became complete, with an achieved annual sample size of approximately 450,000 individuals from interviews undertaken in Great Britain and Northern Ireland. Therefore, the first IHS dataset released covers the period April 2009-March 2010, starting the IHS data series from the point that all surveys were included. The large sample size and UK-wide coverage meant that various geographical breakdowns were possible in the IHS, and it is possible to use a geographical hierarchy to drill down to lower level detail within an area. The IHS also contained data collected from the following surveys: General Lifestyle Survey; Living Costs and Food Survey; Opinions and Lifestyle Survey; English Housing Survey; Labour Force Survey; Annual Population Survey; and Life Opportunities Survey. All questions had been removed from the component surveys by 2014 and the IHS closed that year. Further information is available from the ONS Integrated Household Survey (Experimental statistics): January to December 2014 webpage.

Available IHS data: End User Licence and Secure Access
Users should note that there are two versions of the IHS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version (SN 8075). The Secure Access version contains more detailed variables relating to age, age of youngest dependent child, country of birth, family unit type, household and household reference person, industry class, sub-class and division, month left last job, cohabitation, country of residence history, multiple households at address, nationality, New Deal training types, National Statistics Socio-Economic Classification (NS-SEC) long version, qualifications, household relationships, minor Standard Occupational Classification (SOC) groups, sexual identity, training and working age. The more detailed geographic variables present include county, unitary/local authority, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions and Training and Enterprise Councils (TECs). Users should note that the user guide also mentions variables that are not included in either the EUL or Secure Access datasets held at the Archive.

The EUL version contains less detailed variables. For example, the lowest geography available is Government Office Region, only major (3-digit) SOC groups are included for main, second and last job, and only industry sector for main, second and last job. Users are advised to first obtain the standard EUL version of the data before making an application for the Secure Access version to see if they are sufficient for their research requirements.


The SL version of the IHS October 2010 - September 2011 is available under SN 7002.


Main Topics:
The IHS core questions cover several themes. These include:

• economic activity
• education
• health and...

This data set contains human-use resource data for bridges and state boundaries in South Florida (2013), Panhandle Florida (2012), and the rest of Florida (2003). Vector lines in this data set represent human-use site locations that could be put at risk from an oil spill and/or pertinent to oil spill response. This data set comprises a portion of the ESI data for Florida. ESI data characterize the terrestrial, marine, and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. See also the MGT and SOCECON_PT data layers, part of the larger Florida ESI database, for additional human-use information. Environmental Sensitivity Index (ESI) is more properly known as "Sensitivity of Coastal Habitats and Wildlife to Spilled Oil" Atlases. The term "ESI" is often used in reference to the whole dataset, but the term "ESI" is really a reference to the classification system of shoreline types known as Environmental Sensitivity Index, that classifies a shoreline on a scale from 1 to 10 based upon overall sensitivity to spilled oil. FWRI contracted out updates to Florida's ESI data for the Panhandle and South Florida in the years 2010 through early 2013. These datasets were delivered as coverages in region-polygon format that allow for overlapping polygons in the same manner as FWRI's older ESI GIS data (in Gulf-Wide Information System (GWIS) format/specification). Hundreds of new species were added and the regional products were completed and delivered as promised. However, FWRI wanted and needed a statewide product for use within the Marine Resources Geographic Information System (MRGIS) and the Florida Marine Spill Analysis System (FMSAS). This data set is a compilation of the most recent ESI mapping for each area of Florida.

This file contains original variables from Theme 9 Social Class from Census 2006 & 2011 and a series of additional variables produced by AIRO such as percentage rates, ratios etc. The file includes data on Social Class, Socio-Economic Group of Persons and Persons in Private Households for the 3,406 Electoral Divisions in the Republic of Ireland.

Please be advised that there are issues with the Small Area boundary dataset generalised to 20m which affect Small Area 268014010 in Ballygall D, Dublin City. The Small Area boundary dataset generalised to 20m is in the process of being revised and the updated datasets will be available as soon as the boundaries are amended. This feature layer was created using Census 2016 data produced by the Central Statistics Office (CSO) and Small Areas national boundary data (generalised to 20m) produced by Tailte Éireann. The layer represents Census 2016 theme 9.1, population aged 15+ by sex and social class. Attributes include population breakdown by social class and sex (e.g. skilled manual - males, non-manual - females). Census 2016 theme 9 represents Social Class and Socio-Economic Group. The Census is carried out every five years by the CSO to determine an account of every person in Ireland. The results provide information on a range of themes, such as, population, housing and education. The data were sourced from the CSO. The Small Area Boundaries were created with the following credentials. National boundary dataset. Consistent sub-divisions of an ED. Created not to cross some natural features. Defined area with a minimum number of GeoDirectory building address points. Defined area initially created with minimum of 65 – approx. average of around 90 residential address points. Generated using two bespoke algorithms which incorporated the ED and Townland boundaries, ortho-photography, large scale vector data and GeoDirectory data. Before the 2011 census they were split in relation to motorways and dual carriageways. After the census some boundaries were merged and other divided to maintain privacy of the residential area occupants. They are available as generalised and non generalised boundary sets.