There were approximately 124 thousand Chinese nationals residing in the United Kingdom in 2021, an increase from the 103 thousand Chinese nationals residing in the United Kingdom in 2008. The highest number of Chinese nationals residing in the United Kingdom was 147 thousand in 2017.

Among countries with the highest number of overseas Chinese on each continent, the largest Chinese diaspora community is living in Indonesia, numbering more than ten million people. Most of these people are descendants from migrants born in China, who have moved to Indonesia a long time ago. On the contrary, a large part of overseas Chinese living in Canada and Australia have arrived in these countries only during the last two decades. China as an emigration country Many Chinese people have emigrated from their home country in search of better living conditions and educational chances. The increasing number of Chinese emigrants has benefited from loosened migration policies. On the one hand, the attitude of the Chinese government towards emigration has changed significantly. Overseas Chinese are considered to be strong supporters for the overall strength of Chinese culture and international influence. On the other hand, migration policies in the United States and Canada are changing with time, expanding migration opportunities for non-European immigrants. As a result, China has become one of the world’s largest emigration countries as well as the country with the highest outflows of high net worth individuals. However, the mass emigration is causing a severe loss of homegrown talents and assets. The problem of talent and wealth outflow has raised pressing questions to the Chinese government, and a solution to this issue is yet to be determined. Popular destinations among Chinese emigrants Over the last decades, English speaking developed countries have been popular destinations for Chinese emigrants. In 2022 alone, the number of people from China naturalized as U.S. citizens had amounted to over 27,000 people, while nearly 68,000 had obtained legal permanent resident status as “green card” recipients. Among other popular immigration destinations for Chinese riches are Canada, Australia, Europe, and Singapore.

This statistic displays the annual population of Chinese-born inhabitants that lived in the United Kingdom between 2009 and 2017. The number of Chinese–born inhabitants in the UK increased overall during this period, from almost 198 thousand in 2009 to over 220 thousand by 2017.

This statistic displays the estimated Asian population of the United Kingdom (UK), by region in 2016. London had the highest estimated Asian population of any region, at approximately 1.63 million people, followed by the West Midlands with an estimated Asian population of 737 thousand people.

This dataset represents ethnic group (19 tick-box level) by highest level qualification, for England and Wales combined. The data are also broken down by age and by sex.

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021. This dataset shows population counts for usual residents aged 16+ Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.

These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.

For quality information in general, please read more from here.

Ethnic Group (19 tick-box level)

These are the 19 ethnic group used in this dataset:

• Asian, Asian British or Asian Welsh
  • Bangladeshi
  • Chinese
  • Indian
  • Pakistani
  • Other Asian
• Black, Black British, Black Welsh, Caribbean or African
  • African
  • Caribbean
  • Other Black
• Mixed or Multiple ethnic groups
  • White and Asian
  • White and Black African
  • White and Black Caribbean
  • Other Mixed or Multiple ethnic groups
• White
  • English, Welsh, Scottish, Northern Irish or British
  • Gypsy or Irish Traveller
  • Irish
  • Roma
  • Other White
• Other ethnic group
  • Arab
  • Any other ethnic group

No qualifications

No qualifications

Level 1

Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills

Level 2

5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma

Apprenticeship

Apprenticeship

Level 3

2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma

Level 4 +

Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)

Other

Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)

This dataset represents ethnic group (19 tick-box level) by economic activity status and by occupation, for England and Wales combined. The census data are also broken down by age and by sex for each subtopic.

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

This dataset shows population counts for usual residents aged between 16 to 64 years old only. This is to focus on ethnic groups differences among the working age. Population counts in these tables may be different from other publications which use different age breakdowns.

"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

For quality information in general, please read more from here.

For specific quality information about labour market, please read more from here

Ocupation counts classifiy people who were in employment between 15 March and 21 March 2021, by the SOC code that represents their current occupation. (Occupation is classified using the Standard Occupation Classification 2020 version). Details of SOC code can be found here.

Ethnic Group (19 tick-box level)

These are the 19 ethnic group used in this dataset:

• Asian, Asian British or Asian Welsh
  • Bangladeshi
  • Chinese
  • Indian
  • Pakistani
  • Other Asian
• Black, Black British, Black Welsh, Caribbean or African
  • African
  • Caribbean
  • Other Black
• Mixed or Multiple ethnic groups
  • White and Asian
  • White and Black African
  • White and Black Caribbean
  • Other Mixed or Multiple ethnic groups
• White
  • English, Welsh, Scottish, Northern Irish or British
  • Gypsy or Irish Traveller
  • Irish
  • Roma
  • Other White
• Other ethnic group
  • Arab
  • Any other ethnic group

In 2019, people from most ethnic minority groups were more likely than White British people to live in the most deprived neighbourhoods.

Mental health service users complete the SCOPE-C, the Everyday discrimination scale and the SF12. these are all standardised published instruments. They were self-completed or completed with the assistance of research staff. Over 160 patients were assessed.

A number of cross-cultural translation guides have become available over the years which provide guidance about adapting measures for other cultures. Taking into consideration the various available guides, for the purposes of this research we are adopting the guidance from a leading French research institute, which suggests that we proceed as follows. First we need to speak to groups of people in HK to see to what extent their views about the nature of the concept are similar or dissimilar to those in the UK. To do this we use a method known as 'concept mapping'. We then have experts examine the extent to which the items in the UK measure capture these ideas. At this point it may be necessary to add additional items to the new version. We then translate the UK version into Chinese, and back again, and reconcile and clarify any difference. The new version is then piloted in the Chinese communities, and any difficulties ironed out. Once we have obtained an acceptable version of the measure, following piloting we will then apply the measure to different samples. One will be of discharged mental patients in HK and these will be compared to similar patients in the UK to see if their nature and levels of inclusion are similar or not. Another will be of Chinese immigrants to the UK to see if their levels of inclusion are more similar to UK population or HK residents and immigrants. Finally, we will assess whether the new measure compares in the way it should with a widely used standardised measure, and a measure of recovery. The measure and these findings will provide the basis for further community research in Hong Kong, mainland China and in Chinese immigrant communities in other parts of the world. Social inclusion policy impact could be evaluated in these contexts and social interventions could demonstrate how they have helped people to become more included in society.

This study is going to explore whether an English language measure of social inclusion can be translated into an equivalent Chinese measure of inclusion that can be used to assess inclusion in disadvantaged groups such as immigrant groups and people with mental health problems. We will compare some new results for the Chinese version with results from the original research in the UK in several samples: people with mental health problems in the Hong Kong (HK) resident and immigrant populations, and Chinese immigrants in the UK. The advantages of cross-cultural comparison have been reported as testing the boundaries of knowledge and stretching methodological parameters; highlighting important similarities and differences; and the promotion of institutional and intercultural exchange and understanding. The present proposal looks at these matters in relation to the concept of social inclusion in the UK and HK. While we recognise that the concept of social inclusion is a contested one, for the purposes of the current proposal we accept the World Bank definition. Social Inclusion (SI) refers to promoting equal access to opportunities, enabling everyone to contribute to social and economic program and share in its rewards. Interest in cross-cultural measurement issues has grown rapidly since the turn of the century. Although psychologists have taken the lead on measurement issues social work researchers have recognised the importance of developing crosscultural measurement for the profession, especially for work with minority and immigrant groups. Most authors agree on the fundamental areas in which the new questionnaire should be shown to be equivalent to the original one. These include the concept itself, the questions used to assess it, the precise wording of these questions, and the meaning of the words used in the different languages. Technically, the way each of the items (or variables) relate to each other and to the underlying concepts should be the same in both cultures, for full equivalence to be demonstrated.

Between 2018 and 2022, people in households in the ‘other’, Asian and black ethnic groups were the most likely to be in persistent low income, both before and after housing costs, out of all ethnic groups.

This dataset represents ethnic group (19 tick-box level) by dwelling tenure and by occupancy rating, for England and Wales combined. The data are also broken down by age and by sex.

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

All housing data in these tables do not include commual establishments.

For quality information in general, please read more from here.

For specific quality information about housing, please read more from here

Ethnic Group (19 tick-box level)

These are the 19 ethnic group used in this dataset:

• Asian, Asian British or Asian Welsh
  • Bangladeshi
  • Chinese
  • Indian
  • Pakistani
  • Other Asian
• Black, Black British, Black Welsh, Caribbean or African
  • African
  • Caribbean
  • Other Black
• Mixed or Multiple ethnic groups
  • White and Asian
  • White and Black African
  • White and Black Caribbean
  • Other Mixed or Multiple ethnic groups
• White
  • English, Welsh, Scottish, Northern Irish or British
  • Gypsy or Irish Traveller
  • Irish
  • Roma
  • Other White
• Other ethnic group
  • Arab
  • Any other ethnic group

Occupancy rating of bedrooms: 0 or more

A household’s accommodation has an ideal number of bedrooms or more bedrooms than required (under-occupied)

Occupancy rating of bedrooms: -1 or less

A household’s accommodation has fewer bedrooms than required (overcrowded)

In 2019, the Indian and White ethnic groups had the lowest percentage of recent internet users (90.4% and 90.5%). The Chinese group had the highest (98.6%).

Abstract copyright UK Data Service and data collection copyright owner.

The aims of this project were to:

• understand the demographic changes that United Kingdom local ethnic populations are presently experiencing and are likely to experience in the remainder of the 21st century
• understand the impact that international migration is having on the size and ethnic composition of UK local populations
• understand the role that differences in fertility between the UK's ethnic groups plays in shaping current and future trends
• understand the role that mortality differences between ethnic groups is playing in the changing demography of the UK's local populations
• understand how the ethnic diversity of UK local populations is changing and likely to change in the future
• deliver the projections as a resource for use by social science in the UK
• build capacity in the analysis of demographic change through the development of young and middle career researchers
• tap into the best practice internationally to benefit the UK social science community.

To achieve the project aims, the objectives were to:

• build projections of the populations of ethnic groups for UK local areas
• use the population projection model to explore alternative futures.

The project built a model for projecting the ethnic group populations of UK Local Authorities (LAs), which handles 352 LAs, 16 ethnic groups, 102 ages and 2 sexes. To drive the projections, estimates of the components of ethnic change were prepared for 2001-7. A new method produced UK estimates of ethnic life expectancy, ranging from 82 years for Chinese women to 77 for Pakistani. A future 2% decline in mortality per annum was assumed. Ethnic fertility estimates showed that only Indians, Pakistanis and Bangladeshis had total fertility rates above replacement. Small declines in fertility were forecast. New estimates of the local distribution of immigration were made, using administrative data, because of concerns about official figures. The ethnicity of both immigrants and emigrants for local areas was projected. Estimates were constructed of the ethnic group probabilities for internal in- and out-migration for LAs using 2001 Census data. These probabilities were assumed constant in the future, as migration was stable between 2001 and 2008. Five projections were produced. Two benchmark projections, using constant inputs from 2001-2, forecast the UK population would be 62 and 56 million in 2051.The official projection reports 77 million. The Trend projection, aligned to ONS assumptions projected 78 million for 2051. Using revised assumptions 80 million was projected in a fourth projection. When the model for emigration was changed the projected population was only 71 million. All projections showed ageing and dispersion of ethnic minorities. By 2051 the UK will have a larger, more diverse and integrated population.

For further information about the project, see documentation and the What happens when international migrants settle? Ethnic group population trends and projections for UK local areas under alternative scenarios ESRC award page.


Main Topics:

For full details of the individual files (and topics covered) within the study, see documentation files '6777_list_of_files.xlsx' and '6777_fileinformation.pdf' in the Documentation table below.

Users should note that this study is very large - c.8GB. Multiple files have been created for download, according to the type of compilation - benchef, bencher, trendef, uptapef and uptaper (see 6777_fileinformation.pdf for details). To obtain all files contained within the study, users should download all zip files.

Dataset population: Persons

Ethnic group

Ethnic group classifies people according to their own perceived ethnic group and cultural background.

This topic contains ethnic group write-in responses without reference to the five broad ethnic group categories, e.g. all Irish people, irrespective of whether they are White, Mixed/multiple ethnic groups, Asian/Asian British, Black/African/Caribbean/Black British or Other ethnic group, are in the "Irish" response category. This topic was created as part of the commissioned table processing.

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'.

This is a cross-national survey of Chinese international students in the UK, Germany and Japan, with comparison groups of domestic students in the UK, Germany, and Japan, as well as a comparison group of domestic students in China. The study population are taught (undergraduate and postgraduate) students of the listed groups. Areas covered in the questionnaires: Socio-demographic characteristics and course details; family background (parental education, occupation, household income, siblings); prior education (academic achievement and educational migration); motivations for studying abroad and decision-making processes; individuality traits and values (e.g., achievement orientation, risk-taking attitude); study experience in current course; health and wellbeing; future life course aspirations; cosmopolitan vs national orientations.

Young people moving away from home to seek 'bright futures' through higher education are a major force in the urbanization of China and the internationalization of global higher education. Chinese students constitute the largest single group of international students in the richer OECD countries in the world, making up 20 percent of total student migration to these countries. Yet systematic research into a representative sample of these student migrants is scarce, and, more generally, theoretical frameworks for migration may not always be relevant to students moving for higher education reasons. Bright Futures is a pioneering study that investigates key dimensions of this educational mobility through large-scale representative survey research in China, the UK and Germany. We explore this phenomenon in terms of two related aspects: the migration of students from the People's Republic of China to the UK and Germany for higher education reasons, and internal migration in order to study within China. This research design provides a rare opportunity for direct comparisons between those who stay and those who migrate, both within China and beyond its borders. We also compare Chinese students in the UK and Germany with domestic students in the same two countries. Through such comparisons we are able to address a number of theoretical questions such as selectivity in educational migrations, aspirations beyond returns, the impact of transnationalization of higher education on individual orientations and life-course expectations, and the link between migration and the wellbeing of the highly educated. Bright Futures is a collaborative project (ESRC project number ES/L015633/1), involving researchers from the University of Essex, the University of Edinburgh, UNED, the University of Bielefeld and Tsinghua University. The research was funded by the Economic and Social Research Council (ESRC, UK), the German Research Foundation (DFG, Germany) and the National Natural Science Foundation (China). A related project, Asian Educational Mobilities: A Comparative Study of International Migration of Japanese and Chinese Higher Education Students (ESRC project number ES/N019024/1, funded by the ESRC and the DFG) collected data for a smaller-scale survey of Chinese and Japanese students in Japan which supplements the other surveys. This survey provides data on Chinese international students in another destination country and includes domestic students for comparison.

The Chinese water deer (Hydropotes inermis) belongs to a relatively early-divergence lineage of Cervidae and is thought to have retained some ancestral features of the group. This species is classified as Vulnerable on the IUCN Red List (accessed 2020), and populations in its native range have declined drastically in recent years. However, a number of individuals were introduced to the UK about a century ago; these have flourished and now make up over 40% of global numbers. To infer the population genetic structure and genetic diversity of Chinese water deer both in their native China and in populations introduced to the UK and France, mitochondrial DNA sequence variation was investigated (control region and cytochrome B) for near 100 individuals. The distribution of haplotypes among the regions shows distinct geographic structure, and only one cytochrome B haplotype was common to both China and European populations. Our results reveal lower levels of genetic diversity in the British populations, differentiation between native and introduced populations, and that the source population of British deer is likely to be extinct. Some recommendations are made for the conservation of different populations.

Young people from the Chinese (4.5%) and Indian (7.3%) ethnic groups were less likely than the UK average (11.5%) to be not in employment, education or training.

Demographic, socio-economic and other factors.

This dataset represents ethnic group (19 tick-box level) by general health, by disabled and non-disabled populations, and provision of unpaid care, for England and Wales combined. The data are also broken down by age and sex for each subtopic.

The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.

Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.

"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.

Read more about this quality notice.

The population base for unpaid care is usual residents aged 5 and above. 5-year age bands have been used for the majority of analysis; however, age groups "5 to 17" and "18 to 24" have been used to allow commentary on young carers and young working age carers.

Ethnic Group (19 tick-box level)

These are the 19 ethnic group used in this dataset:

• Asian, Asian British or Asian Welsh
  • Bangladeshi
  • Chinese
  • Indian
  • Pakistani
  • Other Asian
• Black, Black British, Black Welsh, Caribbean or African
  • African
  • Caribbean
  • Other Black
• Mixed or Multiple ethnic groups
  • White and Asian
  • White and Black African
  • White and Black Caribbean
  • Other Mixed or Multiple ethnic groups
• White
  • English, Welsh, Scottish, Northern Irish or British
  • Gypsy or Irish Traveller
  • Irish
  • Roma
  • Other White
• Other ethnic group
  • Arab
  • Any other ethnic group

_General health _

A person's assessment of the general state of their health from very good to very bad. This assessment is not based on a person's health over any specified period of time.

_Disability _

The definition of disability used in the 2021 Census is aligned with the definition of disability under the Equality Act (2010). A person is considered disabled if they self-report having a physical or mental health condition or illness that has lasted or is expected to last 12 months or more, and that this reduces their ability to carry out day-to-day activities.

Unpaid care

An unpaid carer may look after, give help or support to anyone who has long-term physical or mental ill-health conditions, illness or problems related to old age. This does not include any activities as part of paid employment. This help can be within or outside of the carer's household.

Cultural evolutionary models have identified a range of conditions under which social learning (copying others) is predicted to be adaptive relative to asocial learning (learning on one's own), particularly in humans where socially learned information can accumulate over successive generations. However, cultural evolution and behavioural economics experiments have consistently shown apparently maladaptive under-utilization of social information in Western populations. Here we provide experimental evidence of cultural variation in people's use of social learning, potentially explaining this mismatch. People in mainland China showed significantly more social learning than British people in an artefact-design task designed to assess the adaptiveness of social information use. People in Hong Kong, and Chinese immigrants in the UK, resembled British people in their social information use, suggesting a recent shift in these groups from social to asocial learning due to exposure to Western culture. Finally, Chinese mainland participants responded less than other participants to increased environmental change within the task. Our results suggest that learning strategies in humans are culturally variable and not genetically fixed, necessitating the study of the 'social learning of social learning strategies' whereby the dynamics of cultural evolution are responsive to social processes, such as migration, education and globalization.