The fertility rate of a country is the average number of children that women from that country would have throughout their reproductive years. In the United Kingdom in 1800, the average woman of childbearing age would have five children over the course of their lifetime. Over the next 35 years the fertility rate was quite sporadic, rising to over 5.5 in the 1810s and 1820s, then dropping to 4.9 by 1835. This was during and after the Napoleonic Wars and the War of 1812 with the US, which was a time of increased industrialization, economic depression and high unemployment after the war. As things became more stable, and the 'Pax Britannica' (a period of relative, international peace and economic prosperity for the British Empire) came into full effect, the fertility rate plateaued until 1880, before dropping gradually until the First World War. The fertility rate then jumped from 2.6 to 3.1 children per woman between 1915 and 1920, as many men returned from the war. It then resumed it's previous trajectory in the interwar years, before increasing yet again after the war (albeit, for a much longer time than after WWI), in what is known as the 'Baby Boom'. Like the US, the Baby Boom lasted until around 1980, where it then fell to 1.7 children per woman, and it has remained around this number (between 1.66 and 1.87) since then.

The data collection contains population projections for UK ethnic groups and all local area by age (single year of age up to 100+) and sex. Included in the data set are also input data to the cohort component model that was used to project populations into the future-fertility rates, mortality rates, international migration flows and internal migration probabilities. Also included in data set are output data: Number of deaths, births and internal migrants. All data included are for the years 2011 to 2061. We have produced two ethnic population projections for UK local authorities, based on information on 2011 Census ethnic populations and 2010-2011-2012 ethnic components. Both projections align fertility and mortality assumptions to ONS assumptions. Where they differ is in the migration assumptions. In LEEDS L1 we employ internal migration rates for 2001 to 2011, including periods of boom and bust. We use a new assumption about international migration anticipating that the UK may leave the EU (BREXIT). In LEEDS L2 we use average internal migration rates for the 5 year period 2006-11 and the official international migration flow assumptions with a long term balance of +185 thousand per annum. This project aims to understand and to forecast the ethnic transition in the United Kingdom's population at national and sub-national levels. The ethnic transition is the change in population composition from one dominated by the White British to much greater diversity. In the decade 2001-2011 the UK population grew strongly as a result of high immigration, increased fertility and reduced mortality. Both the Office for National Statistics (ONS) and Leeds University estimated the growth or decline in the sixteen ethnic groups making up the UK's population in 2001. The 2011 Census results revealed that both teams had over-estimated the growth of the White British population and under-estimated the growth of the ethnic minority populations. The wide variation between our local authority projected populations in 2011 and the Census suggested inaccurate forecasting of internal migration. We propose to develop, working closely with ONS as our first external partner, fresh estimates of mid-year ethnic populations and their components of change using new data on the later years of the decade and new methods to ensure the estimates agree in 2011 with the Census. This will involve using population accounting theory and an adjustment technique known as iterative proportional fitting to generate a fully consistent set of ethnic population estimates between 2001 and 2011. We will study, at national and local scales, the development of demographic rates for ethnic group populations (fertility, mortality, internal migration and international migration). The ten year time series of component summary indicators and age-specific rates will provide a basis for modelling future assumptions for projections. We will, in our main projection, align the assumptions to the ONS 2012-based principal projection. The national assumptions will need conversion to ethnic groups and to local scale. The ten years of revised ethnic-specific component rates will enable us to study the relationships between national and local demographic trends. In addition, we will analyse a consistent time series of local authority internal migration. We cannot be sure, at this stage, how the national-local relationships for each ethnic group will be modelled but we will be able to test our models using the time series. Of course, all future projections of the population are uncertain. We will therefore work to measure the uncertainty of component rates. The error distributions can be used to construct probability distributions of future populations via stochastic projections so that we can define confidence intervals around our projections. Users of projections are always interested in the impact of the component assumptions on future populations. We will run a set of reference projections to estimate the magnitude and direction of impact of international migrations assumptions (net effect of immigration less emigration), of internal migration assumptions (the net effect of in-migration less out-migration), of fertility assumptions compared with replacement level, of mortality assumptions compared with no change and finally the effect of the initial age distribution (i.e. demographic potential). The outputs from the project will be a set of technical reports on each aspect of the research, journal papers submitted for peer review and a database of projection inputs and outputs available to users via the web. The demographic inputs will be subject to quality assurance by Edge Analytics, our second external partner. They will also help in disseminating these inputs to local government users who want to use them in their own ethnic projections. In sum, the project will show how a wide range of secondary data sources can be used in theoretically refined demographic models to provide us with a more reliable picture of how the UK population is going to change in ethnic composition. Base year data (2011) are derived from the 2011 census, vital statistics and ONS migration data. Subsequent population data are computed with a cohort component model.

In 2023, the population of the United Kingdom reached 68.3 million, compared with 67.6 million in 2022. The UK population has more than doubled since 1871 when just under 31.5 million lived in the UK and has grown by around 8.2 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 57.7 million people in 2023. By comparison, Scotland, Wales, and Northern Ireland had populations of 5.44 million, 3.13 million, and 1.9 million, respectively. Within England, South East England had the largest population, at over 9.38 million, followed by the UK's vast capital city of London, at 8.8 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.

2023 Tract-level Indicators of Potential Disadvantage for the DVRPC Region Title VI of the Civil Rights Act states that "no person in the United States, shall, on the grounds of race, color, or national origin be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any program or activity receiving federal financial assistance.” Under Title VI of the Civil Rights Act, Metropolitan Planning Organizations (MPOs) are directed to create a method for ensuring that Title VI compliance issues are investigated and evaluated in transportation decision-making. There is additional guidance from the FHWA’s Title VI and Additional Nondiscrimination requirements (2017), and FTA’s Title VI requirements and guidelines (2012). The Indicators of Potential Disadvantage (IPD) analysis is used throughout DVRPC to demonstrate compliance with Title VI of the Civil Rights Act.

This assessment, called the Indicators of Potential Disadvantage Methodology, is utilized in a variety of DVRPC plans and programs. DVRPC currently assesses the following population groups, defined by the U.S. Census Bureau:

Youth

Older Adults

Female

Racial Minority

Ethnic Minority

Foreign-Born

Disabled

Limited English Proficiency

Low-Income Census tables used to gather data from the 2019-2023 American Community Survey 5-Year Estimates Using U.S. Census American Community Survey data, the population groups listed above are identified and located at the census tract level. Data is gathered at the regional level, combining populations from each of the nine counties, for either individuals or households, depending on the indicator. From there, the total number of persons in each demographic group is divided by the appropriate universe (either population or households) for the nine-county region, providing a regional average for that population group. Any census tract that meets or exceeds the regional average level, or threshold, is considered an EJ-sensitive tract for that group. Census tables used to gather data from the 2019-2023 American Community Survey 5-Year Estimates. For more information and for methodology, visit DVRPC's website:http://www.dvrpc.org/GetInvolved/TitleVI/ For technical documentation visit DVRPC's GitHub IPD repo: https://github.com/dvrpc/ipd Source of tract boundaries: 2020 US Census Bureau, TIGER/Line Shapefiles Note: Tracts with null values should be symbolized as "Insufficient or No Data". Data Dictionary for Attributes: (Source = DVRPC indicates a calculated field) Field Alias Description Source year IPD analysis year DVRPC geoid20 11-digit tract GEOID Census tract identifier ACS 5-year statefp 2-digit state GEOID FIPS Code for State ACS 5-year countyfp 3-digit county GEOID FIPS Code for County ACS 5-year tractce Tract number Tract Number ACS 5-year name Tract number Census tract identifier with decimal places ACS 5-year namelsad Tract name Census tract name with decimal places ACS 5-year d_class Disabled percentile class Classification of tract's disabled percentage as: well below average, below average, average, above average, or well above average calculated d_est Disabled count estimate Estimated count of disabled population ACS 5-year d_est_moe Disabled count margin of error Margin of error for estimated count of disabled population ACS 5-year d_pct Disabled percent estimate Estimated percentage of disabled population ACS 5-year d_pct_moe Disabled percent margin of error Margin of error for percentage of disabled population ACS 5-year d_pctile Disabled percentile Tract's regional percentile for percentage disabled calculated d_score Disabled percentile score Corresponding numeric score for tract's disabled classification: 0, 1, 2, 3, 4 calculated em_class Ethnic minority percentile class Classification of tract's Hispanic/Latino percentage as: well below average, below average, average, above average, or well above average calculated em_est Ethnic minority count estimate Estimated count of Hispanic/Latino population ACS 5-year em_est_moe Ethnic minority count margin of error Margin of error for estimated count of Hispanic/Latino population ACS 5-year em_pct Ethnic minority percent estimate Estimated percentage of Hispanic/Latino population calculated em_pct_moe Ethnic minority percent margin of error Margin of error for percentage of Hispanic/Latino population calculated em_pctile Ethnic minority percentile Tract's regional percentile for percentage Hispanic/Latino calculated em_score Ethnic minority percentile score Corresponding numeric score for tract's Hispanic/Latino classification: 0, 1, 2, 3, 4 calculated f_class Female percentile class Classification of tract's female percentage as: well below average, below average, average, above average, or well above average calculated f_est Female count estimate Estimated count of female population ACS 5-year f_est_moe Female count margin of error Margin of error for estimated count of female population ACS 5-year f_pct Female percent estimate Estimated percentage of female population ACS 5-year f_pct_moe Female percent margin of error Margin of error for percentage of female population ACS 5-year f_pctile Female percentile Tract's regional percentile for percentage female calculated f_score Female percentile score Corresponding numeric score for tract's female classification: 0, 1, 2, 3, 4 calculated fb_class Foreign-born percentile class Classification of tract's foreign born percentage as: well below average, below average, average, above average, or well above average calculated fb_est Foreign-born count estimate Estimated count of foreign born population ACS 5-year fb_est_moe Foreign-born count margin of error Margin of error for estimated count of foreign born population ACS 5-year fb_pct Foreign-born percent estimate Estimated percentage of foreign born population calculated fb_pct_moe Foreign-born percent margin of error Margin of error for percentage of foreign born population calculated fb_pctile Foreign-born percentile Tract's regional percentile for percentage foreign born calculated fb_score Foreign-born percentile score Corresponding numeric score for tract's foreign born classification: 0, 1, 2, 3, 4 calculated le_class Limited English proficiency percentile class Classification of tract's limited english proficiency percentage as: well below average, below average, average, above average, or well above average calculated le_est Limited English proficiency count estimate Estimated count of limited english proficiency population ACS 5-year le_est_moe Limited English proficiency count margin of error Margin of error for estimated count of limited english proficiency population ACS 5-year le_pct Limited English proficiency percent estimate Estimated percentage of limited english proficiency population ACS 5-year le_pct_moe Limited English proficiency percent margin of error Margin of error for percentage of limited english proficiency population ACS 5-year le_pctile Limited English proficiency percentile Tract's regional percentile for percentage limited english proficiency calculated le_score Limited English proficiency percentile score Corresponding numeric score for tract's limited english proficiency classification: 0, 1, 2, 3, 4 calculated li_class Low-income percentile class Classification of tract's low income percentage as: well below average, below average, average, above average, or well above average calculated li_est Low-income count estimate Estimated count of low income (below 200% of poverty level) population ACS 5-year li_est_moe Low-income count margin of error Margin of error for estimated count of low income population ACS 5-year li_pct Low-income percent estimate Estimated percentage of low income (below 200% of poverty level) population calculated li_pct_moe Low-income percent margin of error Margin of error for percentage of low income population calculated li_pctile Low-income percentile Tract's regional percentile for percentage low income calculated li_score Low-income percentile score Corresponding numeric score for tract's low income classification: 0, 1, 2, 3, 4 calculated oa_class Older adult percentile class Classification of tract's older adult percentage as: well below average, below average, average, above average, or well above average calculated oa_est Older adult count estimate Estimated count of older adult population (65 years or older) ACS 5-year oa_est_moe Older adult count margin of error Margin of error for estimated count of older adult population ACS 5-year oa_pct Older adult percent estimate Estimated percentage of older adult population (65 years or older) ACS 5-year oa_pct_moe Older adult percent margin of error Margin of error for percentage of older adult population ACS 5-year oa_pctile Older adult percentile Tract's regional percentile for percentage older adult calculated oa_score Older adult percentile score Corresponding numeric score for tract's older adult classification: 0, 1, 2, 3, 4 calculated rm_class Racial minority percentile class Classification of tract's non-white percentage as: well below average, below average, average, above average, or well above average calculated rm_est Racial minority count estimate Estimated count of non-white population ACS 5-year rm_est_moe Racial minority count margin of error Margin of error for estimated count of non-white population ACS 5-year rm_pct Racial minority percent estimate Estimated percentage of non-white population calculated rm_pct_moe Racial minority percent margin of error Margin of error for percentage of non-white population calculated rm_pctile Racial minority percentile Tract's regional percentile for percentage non-white calculated rm_score Racial minority percentile score Corresponding numeric score for tract's non-white classification: 0, 1, 2, 3, 4 calculated tot_pp Total population estimate Estimated total population of tract (universe [or denominator] for youth, older

Title VI of the Civil Rights Act and the Executive Order on Environmental Justice (#12898) do not provide specific guidance to evaluate EJ issues within a region's transportation planning process. Therefore, MPOs must devise their own methods for ensuring that EJ issues are investigated and evaluated in transportation decision-making. In 2001, DVRPC developed an EJ technical assessment to identify direct and disparate impacts of its plans, programs, and planning process on defined population groups in the Delaware Valley region. This assessment, called the Indicators of Potential Disadvantage Methodology, is utilized in a variety of DVRPC plans and programs. DVRPC currently assesses the following population groups, defined by the U.S. Census Bureau:

Youth

Older Adults

Female

Racial Minority

Ethnic Minority

Foreign-Born

Disabled

Limited English Proficiency

Low-Income Census tables used to gather data from the 2017-2021 American Community Survey 5-Year Estimates Using U.S. Census American Community Survey data, the population groups listed above are identified and located at the census tract level. Data is gathered at the regional level, combining populations from each of the nine counties, for either individuals or households, depending on the indicator. From there, the total number of persons in each demographic group is divided by the appropriate universe (either population or households) for the nine-county region, providing a regional average for that population group. Any census tract that meets or exceeds the regional average level, or threshold, is considered an EJ-sensitive tract for that group. Census tables used to gather data from the 2017-2021 American Community Survey 5-Year Estimates. For more information and for methodology, visit DVRPC's website: https://www.dvrpc.org/GetInvolved/TitleVI/ For technical documentation visit DVRPC's GitHub IPD repo: https://github.com/dvrpc/ipd Source of tract boundaries: US Census Bureau. The TIGER/Line Files Note: Tracts with null values should be symbolized as "Insufficient or No Data". Data Dictionary for Attributes: (Source = DVRPC indicates a calculated field) Field Alias Description Source geoid20 GEOID20 Census tract identifier (text) Census statefp20 State FIPS FIPS Code for State Census countyfp20 County FIPS FIPS Code for County Census name20 Tract Number Tract Number Census d_class Disabled Classification Classification of tract's disabled percentage as: well below average, below average, average, above average, or well above average DVRPC d_cntest Disabled Count Estimate Estimated count of disabled population Census d_cntmoe Disabled Count MOE Margin of error for estimated count of disabled population Census d_pctest Disabled Percentage Estimate Estimated percentage of disabled population DVRPC d_pctile Disabled Percentile Tract's regional percentile for percentage disabled DVRPC d_pctmoe Disabled Percentage MOE Margin of error for percentage of disabled population DVRPC d_score Disabled Score Corresponding numeric score for tract's disabled classification: 0, 1, 2, 3, 4 DVRPC em_class Ethnic Minority Classification Classification of tract's Hispanic/Latino percentage as: well below average, below average, average, above average, or well above average DVRPC em_cntest Ethnic Minority Count Estimate Estimated count of Hispanic/Latino population Census em_cntmoe Ethnic Minority Count MOE Margin of error for estimated count of Hispanic/Latino population Census em_pctest Ethnic Minority Percentage Estimate Estimated percentage of Hispanic/Latino population DVRPC em_pctile Ethnic Minority Percentile Tract's regional percentile for percentage Hispanic/Latino DVRPC em_pctmoe Ethnic Minority Percentage MOE Margin of error for percentage of Hispanic/Latino population DVRPC em_score Ethnic Minority Score Corresponding numeric score for tract's Hispanic/Latino classification: 0, 1, 2, 3, 4 DVRPC f_class Female Classification Classification of tract's female percentage as: well below average, below average, average, above average, or well above average DVRPC f_cntest Female Count Estimate Estimated count of female population Census f_cntmoe Female Count MOE Margin of error for estimated count of female population Census f_pctest Female Percentage Estimate Estimated percentage of female population DVRPC f_pctile Female Percentile Tract's regional percentile for percentage female DVRPC f_pctmoe Female Percentage MOE Margin of error for percentage of female population DVRPC f_score Female Score Corresponding numeric score for tract's female classification: 0, 1, 2, 3, 4 DVRPC fb_class Foreign Born Classification Classification of tract's foreign born percentage as: well below average, below average, average, above average, or well above average DVRPC fb_cntest Foreign Born Count Estimate Estimated count of foreign born population Census fb_cntmoe Foreign Born Count MOE Margin of error for estimated count of foreign born population Census fb_pctest Foreign Born Percentage Estimate Estimated percentage of foreign born population DVRPC fb_pctile Foreign Born Percentile Tract's regional percentile for percentage foreign born DVRPC fb_pctmoe Foreign Born Percentage MOE Margin of error for percentage of foreign born population DVRPC fb_score Foreign Born Score Corresponding numeric score for tract's foreign born classification: 0, 1, 2, 3, 4 DVRPC lep_class Limited English Proficiency Count Estimate Estimated count of limited english proficiency population Census lep_cntest Limited English Proficiency Count MOE Margin of error for estimated count of limited english proficiency population Census lep_cntmoe Limited English Proficiency Percentage Estimate Estimated percentage of limited english proficiency population DVRPC lep_pctest Limited English Proficiency Percentage MOE Margin of error for percentage of limited english proficiency population DVRPC lep_pctile Limited English Proficiency Percentile Tract's regional percentile for percentage limited english proficiency DVRPC lep_pctmoe Limited English Proficiency Classification Classification of tract's limited english proficiency percentage as: well below average, below average, average, above average, or well above average DVRPC lep_score Limited English Proficiency Score Corresponding numeric score for tract's limited english proficiency classification: 0, 1, 2, 3, 4 DVRPC li_class Low Income Classification Classification of tract's low income percentage as: well below average, below average, average, above average, or well above average DVRPC li_cntest Low Income Count Estimate Estimated count of low income (below 200% of poverty level) population Census li_cntmoe Low Income Count MOE Margin of error for estimated count of low income population Census li_pctest Low Income Percentage Estimate Estimated percentage of low income (below 200% of poverty level) population DVRPC li_pctile Low Income Percentile Tract's regional percentile for percentage low income DVRPC li_pctmoe Low Income Percentage MOE Margin of error for percentage of low income population DVRPC li_score Low Income Score Corresponding numeric score for tract's low income classification: 0, 1, 2, 3, 4 DVRPC oa_class Older Adult Classification Classification of tract's older adult percentage as: well below average, below average, average, above average, or well above average DVRPC oa_cntest Older Adult Count Estimate Estimated count of older adult population (65 years or older) Census oa_cntmoe Older Adult Count MOE Margin of error for estimated count of older adult population Census oa_pctest Older Adult Percentage Estimate Estimated percentage of older adult population (65 years or older) DVRPC oa_pctile Older Adult Percentile Tract's regional percentile for percentage older adult DVRPC oa_pctmoe Older Adult Percentage MOE Margin of error for percentage of older adult population DVRPC oa_score Older Adult Score Corresponding numeric score for tract's older adult classification: 0, 1, 2, 3, 4 DVRPC rm_class Racial Minority Classification Classification of tract's non-white percentage as: well below average, below average, average, above average, or well above average DVRPC rm_cntest Racial Minority Count Estimate Estimated count of non-white population DVRPC rm_cntmoe Racial Minority Count MOE Margin of error for estimated count of non-white population DVRPC rm_pctest Racial Minority Percentage Estimate Estimated percentage of non-white population DVRPC rm_pctile Racial Minority Percentile Tract's regional percentile for percentage non-white DVRPC rm_pctmoe Racial Minority Percentage MOE Margin of error for percentage of non-white population DVRPC rm_score Racial Minority Score Corresponding numeric score for tract's non-white classification: 0, 1, 2, 3, 4 DVRPC y_class Youth Classification Classification of tract's youth percentage as: well below average, below average, average, above average, or well above average DVRPC y_cntest Youth Count Estimate Estimated count of youth population (under 18 years) Census y_cntmoe Youth Count MOE Margin of error for estimated count of youth population Census y_pctest Youth Percentage Estimate Estimated percentage of youth population (under 18 years) DVRPC y_pctile Youth Percentile Tract's regional percentile for percentage youth DVRPC y_pctmoe Youth Percentage MOE Margin of error for percentage of youth population DVRPC y_score Youth Score Corresponding numeric score for tract's youth classification: 0, 1, 2, 3, 4 DVRPC ipd_score Composite Score Overall score adding the classification scores across all nine variables DVRPC u_tpopest Total Population Estimate Estimated total population of tract (universe [or denominator] for youth, older adult, female, racial minoriry, ethnic minority, & foreign born) Census u_tpopmoe Total Population MOE Margin of error for estimated total population of tract Census u_pop6est Population 6+ Estimated population over five years of age (universe [or

In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

In the past four centuries, the population of the Thirteen Colonies and United States of America has grown from a recorded 350 people around the Jamestown colony in Virginia in 1610, to an estimated 346 million in 2025. While the fertility rate has now dropped well below replacement level, and the population is on track to go into a natural decline in the 2040s, projected high net immigration rates mean the population will continue growing well into the next century, crossing the 400 million mark in the 2070s. Indigenous population Early population figures for the Thirteen Colonies and United States come with certain caveats. Official records excluded the indigenous population, and they generally remained excluded until the late 1800s. In 1500, in the first decade of European colonization of the Americas, the native population living within the modern U.S. borders was believed to be around 1.9 million people. The spread of Old World diseases, such as smallpox, measles, and influenza, to biologically defenseless populations in the New World then wreaked havoc across the continent, often wiping out large portions of the population in areas that had not yet made contact with Europeans. By the time of Jamestown's founding in 1607, it is believed the native population within current U.S. borders had dropped by almost 60 percent. As the U.S. expanded, indigenous populations were largely still excluded from population figures as they were driven westward, however taxpaying Natives were included in the census from 1870 to 1890, before all were included thereafter. It should be noted that estimates for indigenous populations in the Americas vary significantly by source and time period. Migration and expansion fuels population growth The arrival of European settlers and African slaves was the key driver of population growth in North America in the 17th century. Settlers from Britain were the dominant group in the Thirteen Colonies, before settlers from elsewhere in Europe, particularly Germany and Ireland, made a large impact in the mid-19th century. By the end of the 19th century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. It is also estimated that almost 400,000 African slaves were transported directly across the Atlantic to mainland North America between 1500 and 1866 (although the importation of slaves was abolished in 1808). Blacks made up a much larger share of the population before slavery's abolition. Twentieth and twenty-first century The U.S. population has grown steadily since 1900, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. Since WWII, the U.S. has established itself as the world's foremost superpower, with the world's largest economy, and most powerful military. This growth in prosperity has been accompanied by increases in living standards, particularly through medical advances, infrastructure improvements, clean water accessibility. These have all contributed to higher infant and child survival rates, as well as an increase in life expectancy (doubling from roughly 40 to 80 years in the past 150 years), which have also played a large part in population growth. As fertility rates decline and increases in life expectancy slows, migration remains the largest factor in population growth. Since the 1960s, Latin America has now become the most common origin for migrants in the U.S., while immigration rates from Asia have also increased significantly. It remains to be seen how immigration restrictions of the current administration affect long-term population projections for the United States.