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

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)

About this dataset

Context

The dataset tabulates the population of New Britain by race. It includes the population of New Britain across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Britain across relevant racial categories.

Key observations

The percent distribution of New Britain population by race (across all racial categories recognized by the U.S. Census Bureau): 82.88% are white, 4.57% are Black or African American, 0.35% are American Indian and Alaska Native, 5.78% are Asian, 0.39% are some other race and 6.02% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the New Britain
• Population: The population of the racial category (excluding ethnicity) in the New Britain is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of New Britain total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Britain Population by Race & Ethnicity. You can refer the same here

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.

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)

Background: Obesity is a multifaceted condition influenced by genetic, lifestyle, and cultural factors. The prevalence of obesity has risen globally, with distinct challenges faced by South Asian populations in the UK, due to genetic predispositions and dietary shifts. This study evaluated the impact of an educational intervention designed for medical students to increase understanding of obesity in the South Asian community.Approach: Participants were recruited via the medical school online platform and signed written consent forms. The study did not require ethics approval. Participants completed a Likert confidence scale questionnaire before the small group teaching intervention, and then after it, to assess the impact of the session. Written free text comments after the session illustrated participant thoughts on the intervention and how well they felt the medical school taught on ethnic minority health. The dataset is a spreadsheet that records participants' responses to questionnaireEvaluation: The intervention significantly improved participant confidence in understanding and awareness of obesity in the South Asian community. Free text comments highlighted positive engagement and suggested areas for improvement. All participants believed their medical school lacked sufficient teaching on obesity in ethnic minorities and expressed an ardent desire for more teaching in this area.Implications: This study underscores the need for tailored undergraduate medical teaching on obesity in diverse ethnic groups, particularly South Asians. It highlights the inadequacies of a one-size-fits-all approach in addressing obesity within ethnic minority communities. Future work should explore the readiness of medical students across the UK to study obesity and the management of it in ethnic minorities.The data set includes the consent form and feedback form used for the study, as well as anonymised feedback data from the study. The Wilcoxon signed rank test is also included, as well as evidence that an ethics application was not needed for the study.

Dataset population: Dependent children

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.

Sex

The classification of a person as either male or female.

These datasets provide a breakdown of ethnic group by age and sex, ethnic group by age and ethnic group by sex

Information from Census 2021 on the sex and age characteristics of ethnic groups and how this has changed since 2011 in England and Wales.

Since 1991, the census for England and Wales has included a question about ethnic group.

In 2021, the ethnic group question had two stages. Firstly, a person identified through one of the following five high-level ethnic groups:

• "Asian, Asian British, Asian Welsh"

• "Black, Black British, Black Welsh, Caribbean or African"

• "Mixed or Multiple ethnic groups"

• "White"

• "Other ethnic group"

Secondly, a person identifies through 1 of the 19 available response options, which include categories with write-in response options.

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.

These data are modelled using the OMOP Common Data Model v5.3.Correlated Data SourceNG tube vocabulariesGeneration RulesThe patient’s age should be between 18 and 100 at the moment of the visit.Ethnicity data is using 2021 census data in England and Wales (Census in England and Wales 2021) .Gender is equally distributed between Male and Female (50% each).Every person in the record has a link in procedure_occurrence with the concept “Checking the position of nasogastric tube using X-ray”2% of person records have a link in procedure_occurrence with the concept of “Plain chest X-ray”60% of visit_occurrence has visit concept “Inpatient Visit”, while 40% have “Emergency Room Visit”NotesVersion 0Generated by man-made rule/story generatorStructural correct, all tables linked with the relationshipWe used national ethnicity data to generate a realistic distribution (see below)2011 Race Census figure in England and WalesEthnic Group : Population(%)Asian or Asian British: Bangladeshi - 1.1Asian or Asian British: Chinese - 0.7Asian or Asian British: Indian - 3.1Asian or Asian British: Pakistani - 2.7Asian or Asian British: any other Asian background -1.6Black or African or Caribbean or Black British: African - 2.5Black or African or Caribbean or Black British: Caribbean - 1Black or African or Caribbean or Black British: other Black or African or Caribbean background - 0.5Mixed multiple ethnic groups: White and Asian - 0.8Mixed multiple ethnic groups: White and Black African - 0.4Mixed multiple ethnic groups: White and Black Caribbean - 0.9Mixed multiple ethnic groups: any other Mixed or multiple ethnic background - 0.8White: English or Welsh or Scottish or Northern Irish or British - 74.4White: Irish - 0.9White: Gypsy or Irish Traveller - 0.1White: any other White background - 6.4Other ethnic group: any other ethnic group - 1.6Other ethnic group: Arab - 0.6

Dataset population: Persons

Country of birth

Country of birth is the country in which a person was born. This topic records whether the person was born in or if they were not born in a country.

For the full country of birth classification in England and Wales, please see the National Statistics Country Classification.

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.

About this dataset

Context

The dataset tabulates the population of New Britain by race. It includes the population of New Britain across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Britain across relevant racial categories.

Key observations

The percent distribution of New Britain population by race (across all racial categories recognized by the U.S. Census Bureau): 53.28% are white, 13.17% are Black or African American, 0.56% are American Indian and Alaska Native, 2.32% are Asian, 0.31% are Native Hawaiian and other Pacific Islander, 15.72% are some other race and 14.64% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the New Britain
• Population: The population of the racial category (excluding ethnicity) in the New Britain is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of New Britain total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Britain Population by Race & Ethnicity. You can refer the same here

Our research methodology is informed by structuration theory, practice theory and ethnographic methodology. An online survey was distributed to expatriate organisations and individual contacts and the sample was achieved through simple snowball techniques. The survey was ‘live’ through April to November 2012, and obtained 112 responses (57 from Malaysia, 54 from Thailand, and one who did not specify where he lived). Using the survey we were able to gather interesting demographic information. We also asked about migration histories, social lives, social networks and uses of technology for maintaining social ties, personal values and goals, and relationships with other ethnic groups. We understand this survey as contributing to the task of immersing oneself in the context – a key principle of ethnographic work. The fieldwork in Malaysia and Thailand took place between July and November 2012 during which time we undertook a total of 65 recorded interviews (Malaysia: 31; Thailand: 34). We used a variety of interview methods, including face-to-face, email, skype and telephone interviewing. Most of the interviews were conducted with British lifestyle migrants in Penang, Malaysia and in Hua Hin, Thailand. The rest were conducted through digital channels with respondents in other parts of Thailand and Malaysia. These included ‘expert’ interviews with consular staff and migration intermediaries, such as property developers and ‘expat’ magazine publishers. Not all interviews are archivable. Many other interviews were also undertaken within participant observation.This project examined the motivations, experiences and outcomes of Lifestyle Migration, as a contemporary form of social mobility, in South-East Asian contexts. The main research questions were: How are mobility and quality of life understood within eastern and western migrants’ everyday lives and with what consequences for the ways in which they make sense of themselves and their relationships with others? How, in the light of the above, can a more integrated and informed understanding of lifestyle migration and flexible citizenship be developed and how might this set an agenda for further research? These were addressed through an empirical study of British migrants to Malaysia, Thailand and Hong Kong, and Hong Kong migrants to mainland China. The project was informed by strong structuration theory and employed virtual and visual ethnographic methods and life history interviews with migrant men and women. The research aimed to: increase the effectiveness of services and public policy (in UK, China, Hong Kong, Thailand and Malaysia); enhance UK economic competitiveness by encouraging effective help for, and mobilising resources of, British abroad; enhance quality of life through improved health and social welfare; to enhance mutual understanding in lifestyle destinations. Online survey distributed to expatriate organisations and individual migrants who live in Asia. Sample was achieved through simple snowball techniques. The survey obtained 112 responses. Fieldwork in Malaysia and Thailand between July and November 2012. Total of 65 recorded interviews (Malaysia: 31; Thailand: 34). We used a variety of interview methods, including face-to-face, email, skype and telephone interviewing. Most of the interviews were conducted with British lifestyle migrants in Penang, Malaysia and in Hua Hin, Thailand. The rest were conducted through digital channels with respondents in other parts of Thailand and Malaysia. These included ‘expert’ interviews with consular staff and migration intermediaries, such as property developers and ‘expat’ magazine publishers. The study also included analysis of online forums and of visual data. Many further interviews were conducted as part of participant observation. These are not included in the archive.

The Maritime Asia Heritage Survey works to systematically inventory and document endangered tangible cultural heritage in the Maldives and Indonesia – including historical structures, archaeological sites, manuscripts and physical objects. The documentation produced in the course of our work includes site, feature, and object records with geospatial data, digital photography, LiDAR point clouds, orthophotomaps, 3D models, CAD site plans and architectural elevations, IIIF digitized manuscripts, and oral history video interviews The materials documented through this work are critically endangered, facing both natural and human threats. Our work thus creates a digital archive of multimedia source material for the history of the Indian Ocean world. All data is also made open-access available on our project website: https://maritimeasiaheritage.cseas.kyoto-u.ac.jp The Maritime Asia Heritage Survey is based at Kyoto University’s Center for Southeast Asian Studies. It is led by Prof. R. Michael Feener (PI and Director), together with Dr Patrick Daly (Co-PI) and Prof. Noboru Ishikawa (Co-PI). The project is financially supported by the Arcadia Fund, a charitable fund of Lisbet Rausing and Peter Baldwin (project number 4309). The MAHS Digital Heritage Documentation Lab is hosted by the Kyoto University Center for Southeast Asian Studies. Work in the Maldives is done in partnership with the Maldives National Center for Cultural Heritage, Ministry of Arts, Culture and Heritage, and in Indonesia with the Directorate General of Culture, Ministry of Education, Culture, Research and Technology. NB: This is a large dataset, and may require considerable time and bandwidth to download. For help in facilitating this data transfer please contact the MAHS Digital Heritage Documentation Lab at: mahsadmin@cseas.kyoto-u.ac.jp

Dataset population: 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.

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.

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.

For Northern Ireland, 'General health' refers to a person's health over the 12 months prior to Census day (27 March 2011).

Sex

The classification of a person as either male or female.

Image: Snapshot from the Map of Community Views To understand different communities’ experiences during the COVID-19 pandemic, Deputy Mayor for Social Integration, Social Mobility and Community Engagement, Dr Debbie Weekes-Bernard and the GLA Community Engagement Team convened a series of virtual roundtable conversations and community meetings with groups and community leaders between April and September 2020. These conversations covered a range of complex issues. We heard about the overexposure of Black and Asian Minority Ethnic communities to the pandemic because they often work in frontline roles; the upsurge in hate crime against East and South East Asian Londoners; heightened need for domestic abuse support and better community language translations including specific dialects; the deep impact the virus has had on specific groups such as Somali, Bengali and Pakistani Londoners, particularly because of challenges with housing arrangements; the challenges for families around education for many groups including Gypsy, Roma, Traveller communities; concerns for LGBT+, Younger and Older Londoners; the impact of the Black Lives Matter movement; faith communities having to adapt their services and facing loss of income as a result, and much more. It was clear throughout that grassroots Faith and Community groups have played a crucial role meeting essential needs. The map of community views does not name specific groups but captures themes that can be addressed at policy level in close partnership with those affected, by recognising the strength of London’s community sector. 21 Roundtables and Community Meetings 250 Civil society and community groups reached

Shows the current housing register for those waiting for social housing by ethnicity.To join a housing register you must have a housing need. This means that your current accommodation is not suitable for you or a family member of your household.The data shows how many joined the register each year via submission of an application. It does not portray those who are no longer active on the register.Small number suppression has been applied to those detailed ethnicities which are less than 10. All those individuals will be listed as a group called Data disclosure protection.

The database of chemical composition of Central Asian forage plants contains just under 1000 desert and steppe species with information such as Latin and Russian names and family and related records of chemical composition from various sources including percentages by weight of protein, ash, cellulose and fat. Where available, it also includes data on digestible protein content, metabolisable energy and Soviet Feed Units (SFU). Records also include information on the country, location, season or month and phenological phase at time of collection of each sample. As one of the original uses of the database was for modelling food and energy intake by the saiga antelope, it also includes information identifying saiga food plant species along with sources of this information. Data on the edibility of many species for livestock in different seasons are also available. See the detailed documentation available here for more information on the data types, definitions and sources. NB The database is in text format and must be imported e.g. into relational database software, as Unicode (UTF-8) in order to convert the Cyrillic characters in Russian names. Full details about this dataset can be found at https://doi.org/10.5285/6a5a9a2a-730b-49f7-9e42-2295040aee56

Availability of sophisticated statistical modelling for developing robust reference equations has improved interpretation of lung function results. In 2012, the Global Lung function Initiative(GLI) published the first global all-age, multi-ethnic reference equations for spirometry but these lacked equations for those originating from the Indian subcontinent (South-Asians). The aims of this study were to assess the extent to which existing GLI-ethnic adjustments might fit South-Asian paediatric spirometry data, assess any similarities and discrepancies between South-Asian datasets and explore the feasibility of deriving a suitable South-Asian GLI-adjustment.MethodsSpirometry datasets from South-Asian children were collated from four centres in India and five within the UK. Records with transcription errors, missing values for height or spirometry, and implausible values were excluded(n = 110).ResultsFollowing exclusions, cross-sectional data were available from 8,124 children (56.3% male; 5–17 years). When compared with GLI-predicted values from White Europeans, forced expired volume in 1s (FEV1) and forced vital capacity (FVC) in South-Asian children were on average 15% lower, ranging from 4–19% between centres. By contrast, proportional reductions in FEV1 and FVC within all but two datasets meant that the FEV1/FVC ratio remained independent of ethnicity. The ‘GLI-Other’ equation fitted data from North India reasonably well while ‘GLI-Black’ equations provided a better approximation for South-Asian data than the ‘GLI-White’ equation. However, marked discrepancies in the mean lung function z-scores between centres especially when examined according to socio-economic conditions precluded derivation of a single South-Asian GLI-adjustment.ConclusionUntil improved and more robust prediction equations can be derived, we recommend the use of ‘GLI-Black’ equations for interpreting most South-Asian data, although ‘GLI-Other’ may be more appropriate for North Indian data. Prospective data collection using standardised protocols to explore potential sources of variation due to socio-economic circumstances, secular changes in growth/predictors of lung function and ethnicities within the South-Asian classification are urgently required.

This data collection comprises interview transcripts from Tokyo (34), Shanghai(36) and Hong Kong(27). Rising home ownership rates, volatile property markets and deregulated financial systems are increasingly important ingredients in the shaping of advantage and opportunity in contemporary societies. This cross-national, comparative research examines how the role of housing assets influences relationships within the family and across generations in East Asian societies. The different pattern and pace of economic and social change mean that the distribution of housing wealth may vary substantially across societies in the region. In some countries, it is an older generation of home owners which has benefited from extraordinary levels of house price inflation. In other countries, it is a younger, emergent middle class which is accumulating housing wealth on a scale far removed from the experiences of their parents and grandparents. The fieldwork was conducted in three dynamic cities in East Asia. The research will involve interviews with three generations (grandparents, parents and adult children) in 12 families in each city; and will highlight how work, entry to home ownership, and asset accumulation play out over the life course.