As of 2022, South Africa's population increased and counted approximately 60.6 million inhabitants in total, of which the majority (roughly 49.1 million) were Black Africans. Individuals with an Indian or Asian background formed the smallest population group, counting approximately 1.56 million people overall. Looking at the population from a regional perspective, Gauteng (includes Johannesburg) is the smallest province of South Africa, though highly urbanized with a population of nearly 16 million people.

Increase in number of households

The total number of households increased annually between 2002 and 2022. Between this period, the number of households in South Africa grew by approximately 65 percent. Furthermore, households comprising two to three members were more common in urban areas (39.2 percent) than they were in rural areas (30.6 percent). Households with six or more people, on the other hand, amounted to 19.3 percent in rural areas, being roughly twice as common as those in urban areas.

Main sources of income

The majority of the households in South Africa had salaries or grants as a main source of income in 2019. Roughly 10.7 million drew their income from regular wages, whereas 7.9 million households received social grants paid by the government for citizens in need of state support.

Information about the ethnic affiliation(s) and characteristics of a human population. Includes, for example, information about: the ethnic groups located within a geographic region, their community social structures, their mutual associations and conflicts with other groups, their historic roles and influence, and the physical distribution of their members. Ethnic groups are human populations whose members identify with each other, usually on the basis of having a common cultural traditions and heritage (for example: as distinguished by customs, language, religious practices, or common history) or a presumed common genealogy or ancestry.

This multi-scale map shows the predominant (most numerous) race/ethnicity living within an area. Map opens at the state level, centered on the lower 48 states. Data is from U.S. Census Bureau's 2020 PL 94-171 data for state, county, tract, block group, and block.The map's colors indicate which of the eight race/ethnicity categories have the highest total count.Race and ethnicity highlights from the U.S. Census Bureau:White population remained the largest race or ethnicity group in the United States, with 204.3 million people identifying as White alone. Overall, 235.4 million people reported White alone or in combination with another group. However, the White alone population decreased by 8.6% since 2010.Two or More Races population (also referred to as the Multiracial population) has changed considerably since 2010. The Multiracial population was measured at 9 million people in 2010 and is now 33.8 million people in 2020, a 276% increase.“In combination” multiracial populations for all race groups accounted for most of the overall changes in each racial category.All of the race alone or in combination groups experienced increases. The Some Other Race alone or in combination group (49.9 million) increased 129%, surpassing the Black or African American population (46.9 million) as the second-largest race alone or in combination group.The next largest racial populations were the Asian alone or in combination group (24 million), the American Indian and Alaska Native alone or in combination group (9.7 million), and the Native Hawaiian and Other Pacific Islander alone or in combination group (1.6 million).Hispanic or Latino population, which includes people of any race, was 62.1 million in 2020. Hispanic or Latino population grew 23%, while the population that was not of Hispanic or Latino origin grew 4.3% since 2010.View more 2020 Census statistics highlights on race and ethnicity.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in South Africa: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

In 2020, roughly 7.4 million inhabitants aged three or older spoke an indigenous language in Mexico. In the case of Afro-descendants or Afro-Mexicans, a total of 2.6 million people defined themselves as such.

Indigenous families in Mexico Mexico is one of the countries with the largest share of indigenous language speakers in Latin America. The number of indigenous households stood at 2.9 million in 2020. This figure includes all family units where at least one member or their ancestors declared speaking an indigenous language. Native ethnicities in Mexico generally endure higher and more severe poverty levels. Indigenous people are also in a more vulnerable socio-economic situation. For instance, more than 30 percent of the indigenous population in Mexico lagged in education, almost double the share of non-indigenous population.

Mexico's Afro-descendants Thanks to its millennia-long indigenous ancestry, Mexico is a multiethnic country that amasses one of the richest cultural heritages in the world. During colonial times, millions of slaves from the African continent were brought to Mexican territory. Their contribution to today's Mexican identity is sometimes overlooked. In 2020, around one million households in the country had at least one member who self-perceived as an Afro-descendant, or had ancestors with this ethnicity. Guerrero and Oaxaca are nowadays the states with the largest share of Afro-Mexicans.

Author: E Black, educator, Minnesota Alliance for Geographic EducationGrade/Audience: grade 8, high schoolResource type: lessonSubject topic(s): politics, history, mapsRegion: africaStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.

Standard 7. The characteristics, distribution and complexity of the earth’s cultures influence human systems (social, economic and political systems).

Standard 8. Processes of cooperation and conflict among people influence the division and control of the earth’s surface.

Standard 11. Industrialization ushered in wide-spread population growth and migration, new colonial empires and revolutionary ideas about government and political power.

Standard 13. Post- World War II political reorganization produced the Cold War balance of power and new alliances that were based on competing economic and political doctrines.

Standard 13. Post- World War II geopolitical reorganization produced the Cold War balance of power and new alliances that were based on competing economic and political doctrines.Objectives: Students will be able to:

1. Describe how Africa’s colonial boundaries were established.
2. Identify specific countries where political boundaries do not correspond with cultural, ethnic, and linguistic boundaries.
3. Summarize the impact of imperialism and colonial boundaries on current African conflicts.
4. Analyze the role of protected human rights in establishing an ethnically diverse societySummary: In this lesson students will contrast historical maps of African tribes, kingdoms, and ethnicities with the colonial and contemporary political boundaries in Africa. Students will investigate the source of these discrepancies, as well as the current impact on ethnic conflicts throughout Africa. Finally, students will discuss what they learned about making boundaries and the significance of human rights in establishing ethnic diversity.

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.

Table showing ethnic group statistics by aggregated groupings. Categories covered: White - includes White British, Irish, Gypsy or Irish Traveller, and Other Black - includes Black African, Caribbean, and Other Asian - includes Indian, Pakistani, Bangladeshi, Chinese and Other Mixed/Other - includes White and Black Caribbean, White and Asian, White and Black African, Other Mixed, Arab and any Other ethnicity not covered above. Figures may not add exactly due to rounding. Numbers rounded to the nearest thousand. Data is from the Annual Population Survey.

The population of the world, allocated to 1 arcsecond blocks. This refines CIESIN’s Gridded Population of the World project, using machine learning models on high-resolution worldwide Digital Globe satellite imagery. More information.

There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.

This map shows the percentage of Black or African American population, alone or in combination with any other race and independent of ethnicity, throughout the US according to the 2020 decennial Census. The people represented in this map chose "Black or African American" alone or in combination with another race in the survey (see the Census form here).For more information about the racial categories included on the 2020 Census, visit this resource from the U.S. Census Bureau. The pattern is shown by states, counties, tracts, block groups, and blocks. Zoom or search for anywhere in the US to see a local pattern. Click on an area to learn more. Filter to your area and save a new version of the map to use for your own mapping purposes.The data is from the decennial 2020 Census, and is sourced by the U.S. Census Bureau for all states plus D.C. and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables. For full metadata including data processing notes, visit this group of ArcGIS Living Atlas layers.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteAdditional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

The population of some areas in the United States is dominated heavily by one racial or ethnic group. These areas stand out on this map. In other areas, one group may be the majority, but the population is much more evenly balanced. Still other areas have one group claiming a plurality, but not a majority.In each neighborhood, county, and state, this map shows which race or ethnicity is predominant and by how much. It uses map colors to identify the predominant racial or ethnic group in specific areas by county and tract. The strength of the color indicates the extent to which one group is dominant over the next most populous.The data shown is from the U.S. Census Bureau's SF1 and TIGER data sets for 2010, and Esri. Concept and colors by Andrew Skinner.Original data sourced from: https://nation.maps.arcgis.com/apps/OnePane/splash/index.html?appid=602849530f5d4b6781ba37393144728c

The statistic shows the share of U.S. population, by race and Hispanic origin, in 2016 and a projection for 2060. As of 2016, about 17.79 percent of the U.S. population was of Hispanic origin. Race and ethnicity in the U.S. For decades, America was a melting pot of the racial and ethnical diversity of its population. The number of people of different ethnic groups in the United States has been growing steadily over the last decade, as has the population in total. For example, 35.81 million Black or African Americans were counted in the U.S. in 2000, while 43.5 million Black or African Americans were counted in 2017.

The median annual family income in the United States in 2017 earned by Black families was about 50,870 U.S. dollars, while the average family income earned by the Asian population was about 92,784 U.S. dollars. This is more than 15,000 U.S. dollars higher than the U.S. average family income, which was 75,938 U.S. dollars.

The unemployment rate varies by ethnicity as well. In 2018, about 6.5 percent of the Black or African American population in the United States were unemployed. In contrast to that, only three percent of the population with Asian origin was unemployed.

According to estimations from 2018, Nigeria's major ethnic groups are Hausa, Yoruba, Igbo (Ibo), and Fulani. Hausa people are estimated to make up 30 percent of the country's population. Hausa is an ethnic group of people speaking the Hausa language. The Hausa are mainly present in West Africa, most of them living between Nigeria and Niger. Another 30 percent of Nigeria's population is constituted by Yoruba and Igbo (Ibo), while about six percent of Nigerians are Fulani.

This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

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

Dataset population: Persons aged 16 and over

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.

Economic activity

Economic activity relates to whether or not a person who was aged 16 and over was working or looking for work in the week before census. Rather than a simple indicator of whether or not someone was currently in employment, it provides a measure of whether or not a person was an active participant in the labour market.

A person's economic activity is derived from their 'activity last week'. This is an indicator of their status or availability for employment - whether employed, unemployed, or their status if not employed and not seeking employment. Additional information included in the economic activity classification is also derived from information about the number of hours a person works and their type of employment - whether employed or self-employed.

The census concept of economic activity is compatible with the standard for economic status defined by the International Labour Organisation (ILO). It is one of a number of definitions used internationally to produce accurate and comparable statistics on employment, unemployment and economic status.

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.

The number of genes in Oromo’s list is shown for each trait (Genes in set). Gene’s names can be found in S2 Dataset.

Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File.

BackgroundA significantly higher proportion of UK Black ethnic adults live with overweight or obesity, compared to their White British counterparts. The role of obesity in excess infection rates and mortality from COVID-19 has increased the need to understand if weight management interventions are appropriate and effective for Black ethnic groups. There is a paucity of existing research on weight management services in Black populations, and whether anticipated or experienced institutional and interpersonal racism in the healthcare and more widely affects engagement in these services. Understanding the lived experience of target populations and views of service providers delivering programmes is essential for timely service improvement.MethodsA qualitative study using semi-structured interviews was conducted in June–October 2021 among 18 Black African and Black Caribbean men and women interested in losing weight and 10 weight management service providers.ResultsThe results highlighted a positive view of life in the United Kingdom (UK), whether born in the UK or born abroad, but one which was marred by racism. Weight gain was attributed by participants to unhealthy behaviours and the environment, with improving appearance and preventing ill health key motivators for weight loss. Participants relied on self-help to address their overweight, with the role of primary care in weight management contested as a source of support. Anticipated or previously experienced racism in the health care system and more widely, accounted for some of the lack of engagement with services. Participants and service providers agreed on the lack of relevance of existing services to Black populations, including limited culturally tailored resources. Community based, ethnically matched, and flexibly delivered weight management services were suggested as ideal, and could form the basis of a set of recommendations for research and practice.ConclusionCultural tailoring of existing services and new programmes, and cultural competency training are needed. These actions are required within systemic changes, such as interventions to address discrimination. Our qualitative insights form the basis for advancing further work and research to improve existing services to address the weight-related inequality faced by UK Black ethnic groups.

We examined the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identified 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observed a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a low overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups.

Methods A total of 15 cohorts (N=16,265) from the epigenetics working group in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium participated in this study. These included the Old Order Amish (OOA), Atherosclerosis Risk in Communities (ARIC), Bogalusa Heart Study (BHS), Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), Genetic Epidemiology Network of Arteriopathy (GENOA), Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), Hypertension Genetic Epidemiology Network (HyperGEN), Cooperative health research in the Region of Augsburg (KORA), Normative Aging Study (NAS), Prospective Investigation of Vascularity of Uppsala Elders Study (PIVUS), Rotterdam Study (RS), UK Adult Twin Registry (TwinsUK), Women’s Health Initiative Broad Agency Announcement 23 (WHI-BA23), and the Women’s Health Initiative Epigenetic Mechanisms of PM-Mediated CVD (WHI-EMPC) cohorts. Four cohorts, BHS, CHS, WHI-BA23, and WHI-EMPC, examined more than one racial/ethnic group. The total number of cohorts in the European (EA), African (AA), and Hispanic (HA) study populations is 12 (N=11,114), 9 (N=4,452), and 2 (N=699), respectively.

High-density-lipoprotein (HDL, mg per dl) and triglycerides (TG, mg per dl) were directly measured in blood samples taken from participants after at least an 8 hour fast. Low-density-lipoprotein (LDL, mg per dl) was inferred using the Friedewald’s formula in all cohorts except for GOLDN, HyperGEN, and KORA where LDL was measured directly. We did not infer LDL in subjects with triglycerides > 400 mg per dL and we excluded lipid measure from subjects who did not fast for at least 8 hours. We also excluded outliers as defined by >5 standard deviations from the mean of a blood lipid in each cohort. To reduce skewness, HDL and triglycerides were natural log-transformed.

DNA methylation was produced by investigators from each cohort independently. Levels were measured from peripheral blood leukocytes isolated from whole blood in all studies except GOLDN where only CD4 + T cells were examined. The EZ DNA Methylation Gold Kit (Zymo Research, Orange CA) was used for bisulfite conversion. The Illumina® Infinium HumanMethylation450 BeadChip and the Illumina BeadXpress reader were used to perform the methylation assays. Either the SWAN method in the minfi R package, the Beta Mixture Quantile method (BMIQ), the DASEN method in the wateRmelon R package, or the GenomeStudio® Methylation Module was used for pre-processing and normalization of the data in each cohort. For each CpG site, a beta-value was calculated representing the percent methylation at that CpG site. Any single value with a detection p-value > 0.01 was set to missing. In each cohort, we excluded probes with a detection p-value > 0.01 in greater than 5% of samples. In addition, we excluded samples with a detection p-value > 0.01 in greater than 5% of probes. To avoid spurious signals in DNA methylation data, we excluded 29,233 CpGs that co-hybridize to alternate genomic sequences (highly homologous to the intended targets)

Epigenome-wide association analyses (EWAS) were performed in each cohort stratified by racial/ethnic group (European, African, and Hispanic). For Model 1, a linear mixed effects model was used to study the association between the DNA methylation level of a CpG (dependent variable) and each of the lipid measures (independent variable; HDL, LDL, or TG), adjusting for age, sex (reference = male), smoking variable (never/previous/current, reference = never), lipid medication (Yes or No, reference = No), the top four principal components from genotypes (SNPs), and the proportion of 5 types of cells estimated with the Houseman method (CD8 T lymphocytes, CD4 T lymphocytes, natural killer cells, B cells, and monocytes). We added random effects for plate, row, and column. We also included family structure as a random effect among family-based studies. For Model 2, we further adjusted for BMI in addition to Model 1 covariates. We also ran Model 3 and Model 4 which were analogous to Model 1 and 2, respectively, in the subset of individuals not taking lipid lowering medication.

We performed meta-analyses of all the participating cohorts (N=16,265) and also stratified by racial/ethnic group: European Americans (12 cohorts, N=11,114), African Americans (7 cohorts, N=4,452), and Hispanics (2 cohorts, N=699). These meta-analyses were performed for each of the 4 models, respectively. We used a random effects meta-analysis implemented in METASOFT 33 to take into account the heterogeneity of the effect sizes of different cohorts while achieving a higher or comparable statistical power compared to fixed effects meta-analysis. To avoid spurious findings from population substructure, we applied genomic control.

We investigated the association between either imputed or genotyped SNPs located within 25kb upstream or downstream of each CpG and DNA methylation levels to identify cis-acting methylation quantitative trait loci (mQTL). For imputed SNP data, we restricted the mQTL analysis to SNPs with a good quality imputation (IMPUTE info>=0.4 or MACH r^2>=0.3). Subjects taking lipid lowering medications were excluded from this analysis. Beta-values of DNA methylation levels were inverse-normal transformed and regressed on age, sex, smoking (current/former/never), BMI, at least 4 SNP PCs, cell proportions (WBC count and/or estimated WBC proportions (granulocytes as a reference)), and technical covariates (plate, row, and column as random effects) (two-sided test). Family information was also included as a random effect if a cohort was a family-based study. We then regressed the residuals on each SNP of interests stratified by racial/ethnic group. Five out of the 15 cohorts provided genetic data for this analysis including ARIC (NAA=1,717), GOLDN (NEA=713), KORA (NEA=1,379), WHI-BA23 (NEA=790, NAA=540, and NHISP=324), and WHI-EMPC (NEA=494, NAA=424, and NHISP=221). We restricted our analysis to SNPs located within 25 kilobases up- or downstream of the CpGs with a minor allele frequency (MAF) > 0.01 in each cohort and implemented a fixed effects meta-analysis within each of the three racial/ethnic groups.