According to the 2021 Census, London was the most ethnically diverse region in England and Wales – 63.2% of residents identified with an ethnic minority group.

In 2011, 87.2 percent of the total population of the United Kingdom were white British. A positive net migration in recent years combined with the resultant international relationships following the wide-reaching former British Empire has contributed to an increasingly diverse population. Varied ethnic backgrounds Black British citizens, with African and/or African-Caribbean ancestry, are the largest ethnic minority population, at three percent of the total population. Indian Britons are one of the largest overseas communities of the Indian diaspora and make up 2.3 percent of the total UK population. Pakistani British citizens, who make up almost two percent of the UK population, have one of the highest levels of home ownership in Britain. Racism in the United Kingdom Though it has decreased in comparison to the previous century, the UK has seen an increase in racial prejudice during the first decade and a half of this century. Racism and discrimination continues to be part of daily life for Britain’s ethnic minorities, especially in terms of work, housing, and health issues. Moreover, the number of hate crimes motivated by race reported since 2012 has increased, and in 2017/18, there were 3,368 recorded offenses of racially or religiously aggravated assault with injury, almost a thousand more than in 2013/14.

Number of people belonging to a visible minority group as defined by the Employment Equity Act and, if so, the visible minority group to which the person belongs. The Employment Equity Act defines visible minorities as 'persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour.' The visible minority population consists mainly of the following groups: South Asian, Chinese, Black, Filipino, Latin American, Arab, Southeast Asian, West Asian, Korean and Japanese.

The South East London Community Health (SELCoH) study aims to examine the impact socioeconomic factors such as income or education have on people’s health, as well to understand if other demographic factors such as age, culture, ethnicity and/or residence make a difference for people’s wellbeing. The population of Southwark and Lambeth is highly diverse in terms of ethnicity and wealth, ensuring that the study encompasses as wide a range of health service users as possible.

The study is a community survey of psychiatric and physical morbidity of 1,698 adults, aged 16 years and over from 1,075 randomly selected households in the south London boroughs of Southwark and Lambeth. In the two boroughs, there is higher deprivation than the England average, but similar proportions of economically active and inactive residents in comparison to greater London. The boroughs are also ethnically diverse, with a greater number of Black Caribbean residents but fewer South Asian residents than other areas of London. The SELCoH sample resided in a community setting served by South London and Maudsley National Health Service Foundation Trust (SLaM), and the partnership between King's College London and SLaM allows this and other research to inform and benefit clinical treatment.

T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmö-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The London Life Sciences Population Study (LOLIPOP) contributed 530 cases and 538 controls to T2D-GENES Project 1.

39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.

In 2024, the population of the United Kingdom reached 69.3 million, compared with 68.5 million in 2023. The UK population has more than doubled since 1871 when just under 31.5 million lived in the UK and has grown by around 10.4 million since the start of the twenty-first century. For most of the twentieth century, the UK population steadily increased, with two noticeable drops in population occurring during World War One (1914-1918) and in World War Two (1939-1945). Demographic trends in postwar Britain After World War Two, Britain and many other countries in the Western world experienced a 'baby boom,' with a postwar peak of 1.02 million live births in 1947. Although the number of births fell between 1948 and 1955, they increased again between the mid-1950s and mid-1960s, with more than one million people born in 1964. Since 1964, however, the UK birth rate has fallen from 18.8 births per 1,000 people to a low of just 10.2 in 2020. As a result, the UK population has gotten significantly older, with the country's median age increasing from 37.9 years in 2001 to 40.7 years in 2022. What are the most populated areas of the UK? The vast majority of people in the UK live in England, which had a population of 58.6 million people in 2024. By comparison, Scotland, Wales, and Northern Ireland had populations of 5.5 million, 3.2 million, and 1.9 million, respectively. Within England, South East England had the largest population, at over 9.6 million, followed by the UK's vast capital city of London, at almost 9.1 million. London is far larger than any other UK city in terms of urban agglomeration, with just four other cities; Manchester, Birmingham, Leeds, and Glasgow, boasting populations that exceed one million people.

Patient counts and true population rates in subgroups stratified by gender and ethnicity.

This collection consists of transcripts of paired interviews of 127 speakers aged 4–40, 5 age groups; working-class Londoners from Hackney, Haringey and Islington of different ethnicities, c. 1.6 million words. Multi-ethnic and multilingual cities throughout northern Europe are spawning new varieties of their national languages. ‘Multicultural London English’ (MLE) is a case in point. Baptised ‘Jafaican’ by the media, this new variety of English combines pronunciations from the immigrants’ languages with features we can trace to Cockney, as well as to general developments in the South of England. Young people of all ethnicities tend to say ‘fehs’ and ‘coht’ for face and coat, instead of the traditional ‘fice’ and ‘cowt’. Like young speakers everywhere, Londoners say ‘I WAS LIKE “that’s stupid”. But they also use ‘THIS IS ME: “let’s go home”’, rarely found elsewhere. We wanted to establish how MLE arose. We recorded not only teenagers but also children as young as 4 and adults. Unexpectedly, MLE was quite well established among the youngest children, suggesting they acquired it from peers and older children, not their parents, who were mostly not first-language English speakers. Young adults used it, but less consistently than teenagers. Older adults did not, probably because they grew up before it had become established. We investigated whether MLE was similar across ethnicities and districts: perceptually, listeners could not distinguish ethnicity with any certainty, while more MLE-sounding voices were likely to be thought to be from London. We conclude that this multi-ethnic variety emerges because children select from a ‘pool’ of linguistic features they hear around them, giving rise to a new, possibly permanent, way of speaking. We argue this is a distinct form of language change.

London has long been considered by linguists as a motor of change in the English language in Britain. The investigators’ ESRC-funded studies from the early 90s to 2007 show that, while there is widespread ‘levelling’ in the south-east, leading to greater uniformity in accent and grammar, there are new, largely minority ethnic-based changes emerging in inner-city London. The present project investigates whether and how young children acquire these new features, how they are maintained or accentuated in adolescence, and whether they are maintained in adulthood. If they are, this will have consequences for the development of spoken English in Britain. The research asks: Are there different ‘ethnic’ Englishes in London, or is the new variety, dubbed ‘Multicultural London English’ (MLE), relatively uniform across ethnicities, including ‘Anglos’? Do Londoners change their speech across the lifespan? What features enter into MLE, and which don’t? Do Londoners detect any ethnic affiliation for the features? Are there rhythmic differences in the speech of Londoners? The project will record, mainly in pairs, at least 112 people from the northern inner city, ages ranging from 4 to 40 and the ethnic balance reflecting the local population. Both quantitative and qualitative analyses will be performed.

M-Male; F-Female; W-White; B-Black; A-Asian; O-Other ethnicities; ‘-’—no significant difference. Shown gender is associated with higher recorded rates per diagnosis. Ethnicities mentioned in capitals have relative count for the diagnosis above the average across all 4 ethnicities, while lower case letters represent ethnicities with relative count below the average.

BackgroundMental health professionals play a crucial role in promoting the physical well-being of people with mental illness. Awareness of HIV status can enable professionals in mental health services to provide more comprehensive care. However, it remains uncertain whether mental health professionals consistently document HIV status in mental health records.AimsTo investigate the extent to which mental health professionals document previously established HIV diagnoses of people with mental illness in mental health records, and to identify the clinical and demographic factors associated with documentation or lack thereof.MethodsA retrospective cohort study was conducted using an established data linkage between routinely collected clinical data from secondary mental health services in South London, UK, and national HIV surveillance data from the UK Health Security Agency. Individuals with an HIV diagnosis prior to their last mental health service contact were included. Documented HIV diagnosis in mental health records was assessed.ResultsAmong the 4,032 individuals identified as living with HIV, 1,281 (31.8%) did not have their diagnosis recorded in their mental health records. Factors associated with the absence of an HIV diagnosis included being of Asian ethnicity, having certain primary mental health diagnoses including schizophrenia, being older, being with a mental health service for longer, having more clinical mental health appointments, and living in a less deprived area.ConclusionsA significant number of individuals living with HIV who are receiving mental healthcare in secondary mental health services did not have their HIV diagnosis documented in their mental health records. Addressing this gap could allow mental healthcare providers to support those living with HIV and severe mental illness to manage the complexity of comorbidities and psychosocial impacts of HIV. Mental health services should explore strategies to increase dialogue around HIV in mental health settings.

Multivariate analysis of demographic and clinical factors associations with recorded HIV diagnosis.

BackgroundBioelectrical Impedance Analysis (BIA) has the potential to be used widely as a method of assessing body fatness and composition, both in clinical and community settings. BIA provides bioelectrical properties, such as whole-body impedance which ideally needs to be calibrated against a gold-standard method in order to provide accurate estimates of fat-free mass. UK studies in older children and adolescents have shown that, when used in multi-ethnic populations, calibration equations need to include ethnic-specific terms, but whether this holds true for younger children remains to be elucidated. The aims of this study were to examine ethnic differences in body size, proportions and composition in children aged 5 to 11 years, and to establish the extent to which such differences could influence BIA calibration.MethodsIn a multi-ethnic population of 2171 London primary school-children (47% boys; 34% White, 29% Black African/Caribbean, 25% South Asian, 12% Other) detailed anthropometric measurements were performed and ethnic differences in body size and proportion were assessed. Ethnic differences in fat-free mass, derived by deuterium dilution, were further evaluated in a subsample of the population (n = 698). Multiple linear regression models were used to calibrate BIA against deuterium dilution.ResultsIn children <11 years of age, Black African/Caribbean children were significantly taller, heavier and had larger body size than children of other ethnicities. They also had larger waist and limb girths and relatively longer legs. Despite these differences, ethnic-specific terms did not contribute significantly to the BIA calibration equation (Fat-free mass = 1.12+0.71*(height2/impedance)+0.18*weight).ConclusionAlthough clear ethnic differences in body size, proportions and composition were evident in this population of young children aged 5 to 11 years, an ethnic-specific BIA calibration equation was not required.

IRR, incidence rate ratio (XLSX)