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Welsh Government
Data Provider: Welsh Government Experimental Statistics Sexual identity by year
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Measure[Filtered]
Measure2
Sexual Identity[Filter]
Year[Filter]
Click here to sortHeterosexualClick here to sortGay/LesbianClick here to sortBisexualClick here to sortOtherClick here to sortNo response
2014 (r)Data for this year was revised on 28/05/2020.95.7(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.1(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.0.5*The data item is disclosive or not sufficiently robust for publication(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.2.2
2015 (r)Data for this year was revised on 28/05/2020.95.9(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.0(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.0.6*The data item is disclosive or not sufficiently robust for publication(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.9
2016 (r)Data for this year was revised on 28/05/2020.96.0(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.0(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.0.7(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.0.4(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.9
2017 (r)Data for this year was revised on 28/05/2020.95.8(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.3(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.0.7(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.0.5(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.7
201895.2(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.5(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.0.8(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.0.8(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.7
201994.4(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.9(!!) The data item has a coefficient of variation (CV) of between 10% and 20% and is therefore categorised as only \'acceptable.\' Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 5% and 10% are considered ‘reasonably precise.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.0(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.0(!) The data item has a coefficient of variation (CV) of between 5% and 10% and is therefore categorised as only \'reasonably precise.\’ Only estimates with a CV of less than 5% are considered \'precise\', whilst estimates with a CV of between 10% and 20% are considered ‘acceptable.\’ Estimates with a CV of above 20% are considered unacceptable and suppressed. Note that CVs for this purpose are calculated using the standard algorithms in SAS. Typically these CVs are slightly lower than those calculated by ONS when they publish the data.1.7

Metadata

Title

Annual Population Survey: Sexual Identity

Last update

June 2021 June 2021

Next update

June 2022

Publishing organisation

Welsh Government

Source 1

Annual Population Survey, Office for National Statistics

Contact email

stats.inclusion@gov.wales

Designation

Experimental statistics

Lowest level of geographical disaggregation

Wales

Geographical coverage

Wales

Languages covered

English and Welsh

Data licensing

You may use and re-use this data free of charge in any format or medium, under the terms of the Open Government License - see http://www.nationalarchives.gov.uk/doc/open-government-licence

Statistical quality

Figures for 2014-2016 and 2015-2017 were revised on 28/05/2020 following revisions by the Office for National Statistics. For more information on these revisions and the statistical quality of this release, see the links on the Weblinks tab.

General description

This table presents data on all people aged 16 and over in Wales.

Data collection and calculation

The data is based on Welsh Government analysis of Annual Population Survey datasets provided by the Office for National Statistics.

Frequency of publication

Annual

Data reference periods

Figures shown relate to either calendar years or multi-year averages, as indicated.

Users, uses and context

See the links on the Weblinks tab

Rounding applied

Figures are rounded to the nearest 100 and so there may be some apparent slight discrepancies between the sum of constituent items and the totals as shown.

Keywords

Sexual Identity; Sexual Orientation; Equality & Diversity.

Name

EQU1020