There are 3 datasets within this publication showing key aspects of Ethnic Minority Populations in Lincolnshire: Ethnic Groups, Proficiency in English, and Religion. The datasets show 2011 Census estimates of the total resident population with breakouts for those population categories.

These three Census 2011 datasets are sourced from the Office for National Statistics (ONS) Nomis website - see the Source link below. Different geographies and more detailed breakouts of these and other useful datasets, are also available at the Source link.

This dataset is updated every 10 years with the next update due from the Census 2021.

This study was the fourth in a series of national surveys of ethnic minorities. The main objectives were:to describe the social and economic conditions of Britain's main ethnic minority groups, including their health, and to compare these with the social and economic conditions of the white majorityto assess changes over time through comparisons with other workto show how the position of ethnic minority groups is related to the social and ethnic compositions of the areas in which they liveto explore diversity among different ethnic minority groupsto describe perceptions and experience of racial discrimination and social harassment Main Topics: Topics covered include household structure, neighbourhoods and quality of housing, education, employment, health, racial harassment and discrimination, and ethnic identity. Multi-stage stratified random sample 1991 Census material was added to the dataset. Face-to-face interview Compilation or synthesis of existing material

In 2023, 17.9 percent of Black people living in the United States were living below the poverty line, compared to 7.7 percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was 11.1 percent. Poverty in the United States Single people in the United States making less than 12,880 U.S. dollars a year and families of four making less than 26,500 U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

Census 2021 data: 19 tick-box ethnic groups, by age, sex, and age and sex.

In 2019 white people in England and Wales had an average hourly income that was 2.3 percent larger than that of ethnic minority groups. This was the lowest percentage difference recorded during this time period, with the highest difference recorded in 2014, when the average difference in hourly earnings was 8.4 percent.

The project generated several key findings, in line with the original project themes: 1) The project demonstrates that ethnic diversity alone does not appear to be a key driver of Brexit support, despite much of the public/political narrative in the area. Instead, we demonstrate that it is patterns of segregation which determine when diversity drove Brexit support. Thus, how increasing ethnic diversity of society appears to trigger tensions is in more segregated forms. Where diverse communities are integrated relations actually appear to improve. 2) The project uniquely demonstrates that residential segregation is a significant negative driver of mental health among ethnic minority groups in the UK. Mental health policy in the UK acknowledges that ethnic minorities often suffer worse mental health than their majority group counterparts. This work demonstrates that community characteristics need to be considered in mental health policy; in particular, how patterns of residential segregation are a key determinant of minority group mental health. 3) We demonstrate that, as expected, the ethnic mix of a community is a strong predictor of patterns of interethnic harassment. However, we also demonstrate that, even controlling for this, how residentially segregated an area is a stronger and consistent predictor of greater harassment. This will help societies better identify potential drivers of harassment and areas where focus should be on minimising hate crime. 4) The project demonstrates the key role sites of youth engagement can play in building positive intergroup relations among young people. In particular, their efficacy for overcoming key obstacles to integration such as residential segregation.

The project has generated several other impacts related to the project themes of social capital/social cohesion and mental health, as relates to the Covid-19 pandemic: 1) The paper explores the potential impact of the Covid-19 pandemic on people’s perceptions of cohesion in their local communities; particularly for vulnerable groups/communities, such as ethnic minorities or those living in highly deprived neighbourhoods. To this end, we examine both trends over time in overall levels of cohesion as well as patterns of positive and negative changes experienced by individuals using nationally representative data from Understanding Society Study. We test whether rates of positive-/negative-change in cohesion over the pandemic-period differed across socio-demographic groups and neighbourhood characteristics. These trends are then compared to patterns of positive-/negative-change over time experienced in earlier periods to test whether the pandemic was uniquely harmful. We show that the overall levels of social cohesion are lower in June 2020 compared to all of the examined pre-pandemic periods. The decline of perceived-cohesion is particularly high in the most deprived communities, among certain ethnic minority groups and among the lower-skilled. Our findings suggest that the pandemic put higher strain on social-resources among vulnerable groups and communities, who also experienced more negative changes in other areas of life. 2) The study examines the impact of coronavirus-related restrictions on mental health among American adults, and how this relationship varies as a function of time and two measures of vulnerability (preexisting physical symptoms and job insecurity). We draw on data from two waves of Corona Impact Survey, which were fielded in late April and early of May 2020. Multilevel models were used to analyze the hierarchically nested data. Experiencing coronavirus disease-2019 restrictions significantly raise mental distress. This association is stronger for individuals with preexisting health conditions and those who worry about job prospects. These findings hold with the inclusion of region-wave covariates (number of deaths, wave dummy and aggregate measure of restrictions). Finally, there is a cross-level interaction: the restriction-distress connection is more pronounced in the second wave of data. Our research indicates that people who are more physically and/or financially vulnerable suffer more from the imposed restrictions, i.e. ‘social isolation’. The mental health impact of coronavirus pandemic is not constant but conditional on the level of vulnerability.

Rising ethnic diversity across countries is becoming a highly-charged issue. This is leading to intense academic, policy, and public debate, amid concerns that diversity may pose a threat to social cohesion. Within these debates, residential communities are increasingly seen as key sites across which both fractures may emerge, but also where opportunities for building cohesion exist. In light of this, research showing diverse communities weaken cohesion is worrying. Yet, there is a potentially key omission from this work: the role of residential segregation. While studies largely focus on the size of ethnic groups in an area they rarely...

There are clear patterns of under- and over-representation of ethnic minority groups in the youth justice system. Black and mixed race teenagers are over-represented, relative to their representation in the overall population. Other minority groups are not generally over-represented and some are under-represented.

This study examined whether teenagers from ethnic minorities are treated differently to white teenagers by the youth justice system. It investigated how young people are drawn into the youth justice system, and traced whether disproportionality at the point of entry was preserved, amplified or reduced as they passed through the system.

The data available from the UK Data Archive comprise a database of young offenders. Data were collected from the Youth Offending Information System (YOIS), an electronic system used by most YOTs in the country to case-manage and report on young offenders. A purposive sample of 12 YOTs was used to yield relatively high proportions of offenders from the larger ethnic minority groups. YOIS data on all offenders who had committed an offence in 2006 and their disposals recorded up to December 2007 have been extracted.

Further information is available on the Ethnic Minority Young People: differential treatment in the Youth Justice System ESRC award web page.

Do ethnic majorities and minorities have diverging preferences for fiscal capacity? Do these preferences converge during national emergencies such as interstate war? In this paper, we provide evidence from a natural experiment to demonstrate that politically salient minority-majority divisions undermine the development of fiscal capacity. In addition, we show that the pressure of interstate war is insufficient to supersede differences in support for the expansion of state's capacity for taxation between majority and minority groups. More specifically, we employ a regression discontinuity design using a natural border that separates linguistic groups and municipality outcomes of a popular vote on the introduction of direct taxation at federal level in Switzerland during the First World War. The findings suggest that salient minority-majority divisions have a negative effect on the expansion of states' capacity for taxation even during periods of interstate war.

Relative concentration of the Southern California region's Black/African American population. The variable HSPBIPOC is equivalent to all individuals who select a combination of racial and ethnic identity in response to the Census questionnaire EXCEPT those who select "not Hispanic" for the ethnic identity question, and "white race alone" for the racial identity question. This is the most encompassing possible definition of racial and ethnic identities that may be associated with historic underservice by agencies, or be more likely to express environmental justice concerns (as compared to predominantly non-Hispanic white communities). Until 2021, federal agency guidance for considering environmental justice impacts of proposed actions focused on how the actions affected "racial or ethnic minorities." "Racial minority" is an increasingly meaningless concept in the USA, and particularly so in California, where only about 3/8 of the state's population identifies as non-Hispanic and white race alone - a clear majority of Californians identify as Hispanic and/or not white. Because many federal and state map screening tools continue to rely on "minority population" as an indicator for flagging potentially vulnerable / disadvantaged/ underserved populations, our analysis includes the variable HSPBIPOC which is effectively "all minority" population according to the now outdated federal environmental justice direction. A more meaningful analysis for the potential impact of forest management actions on specific populations considers racial or ethnic populations individually: e.g., all people identifying as Hispanic regardless of race; all people identifying as American Indian, regardless of Hispanic ethnicity; etc. "Relative concentration" is a measure that compares the proportion of population within each Census block group data unit that identify as HSPBIPOC alone to the proportion of all people that live within the 13,312 block groups in the Southern California RRK region that identify as HSPBIPOC alone. Example: if 5.2% of people in a block group identify as HSPBIPOC, the block group has twice the proportion of HSPBIPOC individuals compared to the Southern California RRK region (2.6%), and more than three times the proportion compared to the entire state of California (1.6%). If the local proportion is twice the regional proportion, then HSPBIPOC individuals are highly concentrated locally.

We use data from Airbnb to identify the mechanisms underlying discrimination against ethnic-minority hosts. Within the same neighbourhood, hosts from minority groups charge 3.2% less for comparable listings. Since ratings provide guests with increasingly rich information about a listing's quality, we can measure the contribution of statistical discrimination, building upon Altonji and Pierret (2001). We find that statistical discrimination can account for the whole ethnic price gap: ethnic gaps would disappear if all unobservables were revealed. Also, three quarters (2.5 points) of the initial ethnic gap can be attributed to inaccurate beliefs by potential guests about hosts' average group quality.

This dataset is about book series and is filtered where the books is Reducing poverty by promoting more diverse social networks for diasadvantaged people from ethnic minority groups, featuring 10 columns including authors, average publication date, book publishers, book series, and books. The preview is ordered by number of books (descending).

Ethnic group projections were produced consistent with the published development-linked population projections.

These projections have been produced on the basis of ten aggregated ethnic groups and were consistent with the available results from the 2001 Census.

An overview of the results of these projections is available in the accompanying Update.

ObjectiveEthnic minority groups in high income countries in North America, Europe, and elsewhere are disproportionately affected by T2DM with a higher risk of mortality and morbidity. The use of community health workers and peer supporters offer a way of ensuring the benefits of self-management support observed in the general population are shared by those in minoritized communities.Materials and methodsThe major databases were searched for existing qualitative evidence of participants’ experiences and perspectives of self-management support for type 2 diabetes delivered by community health workers and peer supporters (CHWPs) in ethnically minoritized populations. The data were analysed using Sekhon’s Theoretical Framework of Acceptability.ResultsThe results are described within five domains of the framework of acceptability collapsed from seven for reasons of clarity and concision: Affective attitude described participants’ satisfaction with CHWPs delivering the intervention including the open, trusting relationships that developed in contrast to those with clinical providers. In considering Burden and Opportunity Costs, participants reflected on the impact of health, transport, and the responsibilities of work and childcare on their attendance, alongside a lack of resources necessary to maintain healthy diets and active lifestyles. In relation to Cultural Sensitivity participants appreciated the greater understanding of the specific cultural needs and challenges exhibited by CHWPs. The evidence related to Intervention Coherence indicated that participants responded positively to the practical and applied content, the range of teaching materials, and interactive practical sessions. Finally, in examining the impact of Effectiveness and Self-efficacy participants described how they changed a range of health-related behaviours, had more confidence in dealing with their condition and interacting with senior clinicians and benefitted from the social support of fellow participants and CHWPs.ConclusionMany of the same barriers around attendance and engagement with usual self-management support interventions delivered to general populations were observed, including lack of time and resource. However, the insight of CHWPs, their culturally-sensitive and specific strategies for self-management and their development of trusting relationships presented considerable advantages.

Regular attendance at school, measures the percentage of students who have attended more than 90% of the term, Historically attendance data were collected for Term 2, however, from 2019 attendance data have been collected for each term.

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.

Seven out of ten Romanians did not trust people of Roma ethnicity. This attitude towards Roma minority groups led to several forms of discrimination during the years. By contrast, the German minority in Romania benefited from the trust of nearly two thirds of respondents.

In 2023, according to the most recent national data, approximately 46 percent of people living in Brazil identified as Pardo Brazilian, making it the largest ethnic group in the country. In 2012, whites were the largest group, accounting for 46 percent of the population.

PIONEER: The impact of ethnicity and multi-morbidity on COVID-related outcomes; a primary care supplemented hospitalised dataset Dataset number 3.0

Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 65million cases and more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) and death. Evidence suggests that older patients, those from some ethnic minority groups and those with multiple long-term health conditions have worse outcomes. This secondary care COVID dataset contains granular demographic and morbidity data, supplemented from primary care records, to add to the understanding of patient factors on disease outcomes.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 and 2.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date.

Scope: All COVID swab confirmed hospitalised patients to UHB from January – May 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes but also primary care records and clinic letters. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT, MRI, ultrasound).

Available supplementary data: Health data preceding and following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Key Stage 4 is the stage of the National Curriculum between ages 14 and 16 years. This indicator relates to examinations taken at the end of the Key Stage. Minority ethnic groups measured for the purposes of this indicator include any ethnic group where there are over 30 pupils from that group in any particular cohort. Good performance is typified by higher percentages of pupils attaining 5 A*-C, including English and mathematics, accompanied by a narrowing of the attainment gap between minority ethnic pupils and all pupils.

Key Stage (KS) 2 is the stage of the National Curriculum between ages 8 and 11 years. This indicator relates to tests taken by 11 year olds at the end of KS2. Minority ethnic groups measured for the purposes of this indicator include any ethnic group where there are over 30 pupils from that group in any particular cohort. Pupils attainment is assessed in relation to the National Curriculum and pupils are awarded levels on the National Curriculum scale to reflect their attainment. Good performance is typified by higher percentages accompanied by a narrowing of the attainment gap between minority ethnic pupils and all pupils.