Abstract copyright UK Data Service and data collection copyright owner.

The Health Survey for England, 2000-2001: Small Area Estimation Teaching Dataset was prepared as a resource for those interested in learning introductory small area estimation techniques. It was first presented as part of a workshop entitled 'Introducing small area estimation techniques and applying them to the Health Survey for England using Stata'. The data are accompanied by a guide that includes a practical case study enabling users to derive estimates of disability for districts in the absence of survey estimates. This is achieved using various models that combine information from ESDS government surveys with other aggregate data that are reliably available for sub-national areas. Analysis is undertaken using Stata statistical software; all relevant syntax is provided in the accompanying '.do' files.

The data files included in this teaching resource contain HSE variables and data from the Census and Mid-year population estimates and projections that were developed originally by the National Statistical agencies, as follows:

• The main data file, 'hse_data.dta', is a reduced version of the HSE for 2000 and 2001. In order to combine data from two years of the HSE in a consistent way some changes have been made to the weights in each year. Additionally, some recoding of the limiting long term illness (LLTI), disability and the age variable has also been undertaken.
• File 'practical_1_task_5_data.dta' contains population counts and model mobility disability rates (estimated during practical 1) distinguishing single year of age and sex for the six case study districts.
• File 'practical_2_data.dta' contains the aggregate data required for Practical 2, including age- and sex-specific rates of LLTI (Census) for six UK case study districts, age- and sex-specific rates of mobility disability for England (HSE), and population counts for the six districts.
• File 'pop_data_practical_3.dta' contains population counts for the six districts (by age, sex and LLTI status) required for practical 3

The original HSEs for 2000 and 2001 are held at the UK Data Archive under SNs 4628 and 4912 respectively. Full details of the recoding of HSE variables and how the aggregate data was produced can be found in the data documentation.

This unrestricted access data collection is freely available to download under an Open Government Licence from the UK Data Service. Note that the files should be unzipped/saved to the C: drive of the computer to be used; all syntax assumes files are saved at this location.


Main Topics:

The main HSE file, 'hse_data.dta', contains 12 variables and 28,451 cases. The file includes the boosted sample of older people in care/residential homes from the HSE 2000. All the variables in the file are at individual level and are almost all are categorical, often indicating whether or not a respondent has a limiting illness or a particular type of disability. The disability types covered include mobility, personal care, sight and hearing disability as well as a measure of overall disability.

United Kingdom UK: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data was reported at 4.203 % in 2010. This records an increase from the previous number of 4.196 % for 2000. United Kingdom UK: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data is updated yearly, averaging 4.203 % from Dec 1990 (Median) to 2010, with 3 observations. The data reached an all-time high of 4.206 % in 1990 and a record low of 4.196 % in 2000. United Kingdom UK: Urban Population Living in Areas Where Elevation is Below 5 meters: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Land Use, Protected Areas and National Wealth. Urban population below 5m is the percentage of the total population, living in areas where the elevation is 5 meters or less.; ; Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.; Weighted average;

Abstract copyright UK Data Service and data collection copyright owner.

The dataset was created as part of the Victorian Census Project at Staffordshire University.
The main aims of the project were to computerise the 1861 Census Reports, the Registrar General's Annual Report for 1861 and the Registrar General's Decennial Supplement for 1851-60. Further information about the Victorian Census Project can be found at:
http://www.staffs.ac.uk/census>
http://www.staffs.ac.uk/census
Main Topics:

The dataset consists of two files, each containing data for registration districts in 1861.
The main file contains 114 variables relating to : buildings and dwellings; male and female population; marriages 1851-61; births 1851-61; deaths 1851-61; ages of males and females; marital status of males and females aged 20 and over; disabilities and institutionalised populations; birthplaces of the population; occupations and employment status of males and females aged 20 and over; causes of death 1851-61; and ages at death 1851-61.
The secondary file contains 17 variables relating to: grid references; percentage change in population 1851-61; population density; gender ratio; males employed in textiles per 1000; males employed in metals per 1000; males in the armed forces per 1000; agricultural workers per 1000 males; males in mining and bricks per 1000; males in manufacturing per 1000; women domestic servants per 1000.

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

Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 3.600 % in 2017. Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 3.600 % from Dec 2017 (Median) to 2017, with 1 observations. The data reached an all-time high of 3.600 % in 2017 and a record low of 3.600 % in 2017. Multidimensional Poverty Headcount Ratio: UNDP: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Indonesia – Table ID.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;