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Gender identity by NS-SEC

Important information:

Particular care must be taken in interpreting census results on gender identity. Please read the Sexual orientation and gender identity quality information for Census 2021 before using this data.

Read more about this quality notice.

Important information:

As Census 2021 was during a unique period of rapid change, take care when using Labour Market data for planning purposes.

Read more about this quality notice.

Summary

This dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales, by gender identity and NS-SEC. The estimates are as at Census Day, 21 March 2021.

Variable and dataset information

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Lower tier local authorities

Lower tier local authorities provide a range of local services. There are 309 lower tier local authorities in England made up of 181 non-metropolitan districts, 59 unitary authorities, 36 metropolitan districts and 33 London boroughs (including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities.

Coverage

Census 2021 statistics are published for the whole of England and Wales. However, you can choose to filter areas by:

  • country - for example, Wales
  • region - for example, London
  • local authority - for example, Cornwall
  • health area – for example, Clinical Commissioning Group
  • statistical area - for example, MSOA or LSOA

Gender identity

Classifies people according to the responses to the gender identity question. This question was voluntary and was only asked of people aged 16 years and over.

National Statistics Socio-economic Classification (NS-SeC)

The National Statistics Socio-economic Classification (NS-SEC) indicates a person's socio-economic position based on their occupation and other job characteristics.

It is an Office for National Statistics standard classification. NS-SEC categories are assigned based on a person's occupation, whether employed, self-employed, or supervising other employees.

Full-time students are recorded in the "full-time students" category regardless of whether they are economically active.

Variables

Population type
All usual residents aged 16 years and over
Area type
Lower tier local authorities
Coverage
England and Wales
Gender identity
7 Categories
  • Gender identity the same as sex registered at birth
  • Gender identity different from sex registered at birth but no specific identity given
  • Trans woman
  • Trans man
  • All other gender identities
  • Not answered
  • Does not apply
National Statistics Socio-economic Classification (NS-SeC)
10 Categories
  • L1, L2 and L3: Higher managerial, administrative and professional occupations
  • L4, L5 and L6: Lower managerial, administrative and professional occupations
  • L7: Intermediate occupations
  • L8 and L9: Small employers and own account workers
  • L10 and L11: Lower supervisory and technical occupations
  • L12: Semi-routine occupations
  • L13: Routine occupations
  • L14.1 and L14.2: Never worked and long-term unemployed
  • L15: Full-time students
  • Does not apply
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Contact us

Protecting personal data

Sometimes we need to make changes to data if it is possible to identify individuals. This is known as statistical disclosure control.

In Census 2021, we:

  • swapped records (targeted record swapping), for example, if a household was likely to be identified in datasets because it has unusual characteristics, we swapped the record with a similar one from a nearby small area (very unusual households could be swapped with one in a nearby local authority)
  • added small changes to some counts (cell key perturbation), for example, we might change a count of four to a three or a five – this might make small differences between tables depending on how the data are broken down when we applied perturbation

Read more in Section 5 of our article Design for Census 2021.

Version history

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