Native Hawaiian and Pacific Islander women had the highest fertility rate of any ethnicity in the United States in 2022, with about 2,237.5 births per 1,000 women. The fertility rate for all ethnicities in the U.S. was 1,656.5 births per 1,000 women. What is the total fertility rate? The total fertility rate is an estimation of the number of children who would theoretically be born per 1,000 women through their childbearing years (generally considered to be between the ages of 15 and 44) according to age-specific fertility rates. The fertility rate is different from the birth rate, in that the birth rate is the number of births in relation to the population over a specific period of time. Fertility rates around the world Fertility rates around the world differ on a country-by-country basis, and more industrialized countries tend to see lower fertility rates. For example, Niger topped the list of the countries with the highest fertility rates, and Taiwan had the lowest fertility rate.

United States Total Fertility Rate: Black data was reported at 1,581.000 % in 2023. This records a decrease from the previous number of 1,639.000 % for 2022. United States Total Fertility Rate: Black data is updated yearly, averaging 2,062.000 % from Dec 1985 (Median) to 2023, with 39 observations. The data reached an all-time high of 2,480.000 % in 1990 and a record low of 1,581.000 % in 2023. United States Total Fertility Rate: Black data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G013: Fertility Rate.

In 2023, around 50 children were born per thousand Asian women in the United States. The highest birth rate was among Native Hawaiian and other Pacific Islander mothers, at 79 percent during the same year.

This dataset includes teen birth rates for females by age group, race, and Hispanic origin in the United States since 1960.

Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison.

National data on births by Hispanic origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; New Hampshire and Oklahoma in 1990; and New Hampshire in 1991 and 1992. Birth and fertility rates for the Central and South American population includes other and unknown Hispanic. Information on reporting Hispanic origin is detailed in the Technical Appendix for the 1999 public-use natality data file (see ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/DVS/natality/Nat1999doc.pdf).

This graph displays the African-American fertility rate in the United States in 2014, distinguished by region. In 2014, the fertility rate among African-American women, aged 15 to 44 years, was 59 births per 1,000 women in New England.

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 includes live births, birth rates, and fertility rates by race of mother in the United States since 1960.

Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison.

SOURCES

NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/).

REFERENCES

1. National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf.

2. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf.

3. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf.

4. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf.

5. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf.

6. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.

Analysis of ‘NCHS - Teen Birth Rates for Females by Age Group, Race, and Hispanic Origin: United States’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/681175bb-4c25-4876-9afc-4b55fd9e6920 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset includes teen birth rates for females by age group, race, and Hispanic origin in the United States since 1960.

Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison.

National data on births by Hispanic origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; New Hampshire and Oklahoma in 1990; and New Hampshire in 1991 and 1992. Birth and fertility rates for the Central and South American population includes other and unknown Hispanic. Information on reporting Hispanic origin is detailed in the Technical Appendix for the 1999 public-use natality data file (see ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/DVS/natality/Nat1999doc.pdf).

SOURCES

NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/).

REFERENCES

1. National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf.

2. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf.

3. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf.

4. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf.

5. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf.

6. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.

--- Original source retains full ownership of the source dataset ---

In the United States, non-Hispanic Black women currently have higher rates of twin births than any other ethnicity or race with **** per 1,000 live births being twins. There are two types of twins, identical and fraternal. Identical twins form when one fertilized egg splits and develops two babies, while fraternal twins form from two eggs that are fertilized by two sperm. Fraternal twins, although born at the same time, are no more alike than siblings born at different times. Twin births in the United States The birth rate for twins in the United States has increased over the past few decades, with around **** twin births per 1,000 live births in 2023. Factors that increase the odds of having a twin birth include race, genetics, the number of previous pregnancies, assisted reproductive techniques, and the age of the mother. Those aged 45 to 54 years have a significantly higher twin birth rate than younger women in the United States. The states with the highest average twin birth rates include Michigan, Mississippi, and Connecticut. Birth rates in the United States As is the case in many other developed countries, the birth rate in the United States has steadily decreased. In 2023, there were just **** births per 1,000 population, compared to **** births per 1,000 population in the year 1990. Unsurprisingly, the birth rate is highest among women aged 20 to 34 years, however women are increasingly having birth later in life.

Analysis of ‘NCHS - Natality Measures for Females by Race and Hispanic Origin: United States’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e96cb229-a501-4633-8635-386ec77fe5a1 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset includes live births, birth rates, and fertility rates by race of mother in the United States since 1960.

Data availability varies by race and ethnicity groups. All birth data by race before 1980 are based on race of the child. Since 1980, birth data by race are based on race of the mother. For race, data are available for Black and White births since 1960, and for American Indians/Alaska Native and Asian/Pacific Islander births since 1980. Data on Hispanic origin are available since 1989. Teen birth rates for specific racial and ethnic categories are also available since 1989. From 2003 through 2015, the birth data by race were based on the “bridged” race categories (5). Starting in 2016, the race categories for reporting birth data changed; the new race and Hispanic origin categories are: Non-Hispanic, Single Race White; Non-Hispanic, Single Race Black; Non-Hispanic, Single Race American Indian/Alaska Native; Non-Hispanic, Single Race Asian; and, Non-Hispanic, Single Race Native Hawaiian/Pacific Islander (5,6). Birth data by the prior, “bridged” race (and Hispanic origin) categories are included through 2018 for comparison.

SOURCES

NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/).

REFERENCES

1. National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf.

2. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf.

3. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf.

4. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf.

5. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf.

6. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.

--- Original source retains full ownership of the source dataset ---

In 2024, the fertility rate in Africa was *** children per woman. The average number of newborn infants per woman on the continent decreased compared to 2000, when women had approximately **** children throughout their reproductive years. By 2030, fertility in Africa is projected to decline to around *** births per woman, yet it will remain high. The highest fertility rate worldwide Despite its gradually declining rate, fertility in Africa is the highest in the world. In 2021, the average fertility rate on the continent stood at **** children per woman, compared to a global average of **** births per woman. In contrast, Europe and North America were the continents with the lowest proportion of newborns, each registering a fertility rate below two children per woman. Additionally, Africa records the highest fertility rate among the young female population aged 15 to 19 years. In 2021, West and Central Africa had an adolescent fertility rate of *** children per 1,000 girls, the highest value worldwide. Lower fertility in Northern Africa Fertility levels vary significantly across Africa. In 2021, Niger, Somalia, Chad, and the Democratic Republic of Congo were the countries with the highest fertility rates on the continent. In those countries, women had an average of over *** children in their reproductive years. The number of adolescent girls giving birth also differed within Africa. For instance, the adolescent fertility rate in North Africa stood at around **** children per 1,000 young women in 2023. On the other hand, Sub-Saharan Africa registered a higher rate of ****** children per 1,000 girls in 2021. In general, higher poverty levels, inadequate social and health conditions, and increased infant mortality are some main drivers of higher fertility rates.

Education- and age-specific fertility rates for 50 African and Latin American countries between 1970 and 2020.

The fertility rates are consistent with the United Nation's World Population Prospects (UN WPP) 2022 fertility rates.

The Bayesian model developed to reconstruct the fertility rates using Demographic and Health Surveys and the UN WPP is published in a working paper.

Abstract:

Consistent and reliable time series of education- and age-specific fertility rates for the past are difficult to obtain in developing countries, although they are needed to evaluate the impact of women’s education on fertility along periods and cohorts. In this paper, we propose a Bayesian framework to reconstruct age-specific fertility rates by level of education using prior information from the birth history module of the Demographic and Health Surveys (DHS) and the UN World Population Prospects. In our case study regions, we reconstruct age- and education-specific fertility rates which are consistent with the UN age specific fertility rates by four levels of education for 50 African and Latin American countries from 1970 to 2020 in five-year steps. Our results show that the Bayesian approach allows for estimating reliable education- and age-specific fertility rates using multiple rounds of the DHS surveys. The time series obtained confirm the main findings of the literature on fertility trends, and age and education specific differentials.

Funding:

These data sets are part of the BayesEdu Project at Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna) funded from the “Innovation Fund Research, Science and Society” by the Austrian Academy of Sciences (ÖAW).

Variables:

Country: Country names

Education: Four education levels, No Education, Primary Education, Secondary Education and Higher Education.

Age group: Five-year age groups between 15-19 and 45-49.

Year: Five-year periods between 1970 and 2020.

Median: Median education and age-specific fertility rate estimate

Upper_CI: 95% Upper Credible Interval

Lower_CI: 95% Lower Credible Interval

List of countries:

Angola

Benin

Brazil

Burkina Faso

Burundi

Cameroon

Central African Republic

Chad

Colombia

Comoros

Congo

Côte D'Ivoire

DR Congo

Ecuador

Egypt

Eswatini

Ethiopia

Gabon

Gambia

Ghana

Guatemala

Guinea

Honduras

Kenya

Lesotho

Liberia

Madagascar

Malawi

Mali

Mexico

Morocco

Mozambique

Namibia

Nicaragua

Niger

Nigeria

Paraguay

Peru

Rwanda

Sao Tome and Principe

Senegal

Sierra Leone

South Africa

Sudan

Tanzania

Togo

Tunisia

Uganda

Zambia

Zimbabwe

Infant mortality rates in the United States reveal significant disparities among racial and ethnic groups. In 2023, Black mothers faced the highest rate at nearly 11 deaths per 1,000 live births, more than double the rate for white mothers. This stark contrast persists despite overall improvements in healthcare and highlights the need for targeted interventions to address these inequalities. Birth rates and fertility trends While infant mortality rates vary, birth rates also differ across ethnicities. Native Hawaiian and Pacific Islander women had the highest fertility rate in 2022, with about 2,237.5 births per 1,000 women, far exceeding the national average of 1,656.5. In 2023, this group maintained the highest birth rate at 79 births per 1,000 women. Asian women, by contrast, had a much lower birth rate of around 50 per thousand women. These differences in fertility rates can impact overall population growth and demographic shifts within the United States. Hispanic birth trends and fertility decline The Hispanic population in the United States has experienced significant changes in birth trends over recent decades. In 2021, 885,916 babies were born to Hispanic mothers, with a birth rate of 14.1 per 1,000 of the Hispanic population. This represents a slight increase from the previous year. However, the fertility rate among Hispanic women has declined dramatically since 1990, dropping from 108 children per 1,000 women aged 15-44 to 63.4 in 2021. This decline aligns with broader trends of decreasing fertility rates in more industrialized nations.

This dataset contains California’s adolescent birth rate (ABR) by county, age group and race/ethnicity using aggregated years 2014-2016. The ABR is calculated as the number of live births to females aged 15-19 divided by the female population aged 15-19, multiplied by 1,000. Births to females under age 15 are uncommon and thus added to the numerator (total number of births aged 15-19) in calculating the ABR for aged 15-19. The categories by age group are aged 18-19 and aged 15-17; births occurring to females under aged 15 are added to the numerator for aged 15-17 in calculating the ABR for this age group. The race and ethnic groups in this table utilized five mutually exclusive race and ethnicity categories. These categories are Hispanic and the following Non-Hispanic categories of Multi-Race, Black, American Indian (includes Eskimo and Aleut), Asian and Pacific Islander (includes Hawaiian) combined, and White. Note that there are birth records with missing race/ethnicity or categorized as “Other” and not shown in the dataset but included in the ABR calculation overall.

Birth rate is number of live births per 1,000 people in a year. Data are for Santa Clara County residents. The measure is summarized for total county population by race/ethnicity. Data trends are from year 2000 to 2015. Source: Santa Clara County Public Health Department, 2000-2015 Birth Statistical Master File; U.S. Census Bureau, 2010 Census.METADATA:Notes (String): Lists table title, notes, sourcesYear (Numeric): Year of birthCategory (String): Lists the category representing the data: Santa Clara County is for total population, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only).Rate per 1,000 people (Numeric): Birth rate is number of live births per 1,000 people in a year.

In 2023, the birth rate among Hispanic teenagers aged 15 to 19 years was **** per 1,000 women. In comparison, the birth rate among non-Hispanic Asian teens was just *** per 1,000. This statistic shows birth rates among teenagers and young adult women in the U.S. aged 15 to 19 in 1991 to 2023, by race/ethnicity.

About this dataset

Context

The dataset tabulates the data for the Black, AL population pyramid, which represents the Black population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Black, AL, is 74.3.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Black, AL, is 33.8.
• Total dependency ratio for Black, AL is 108.1.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Black, AL is 3.0.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Black population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Black for the selected age group is shown in the following column.
• Population (Female): The female population in the Black for the selected age group is shown in the following column.
• Total Population: The total population of the Black for the selected age group is shown in the following column.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Black Population by Age. You can refer the same here

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Counts of and rates based on fewer than 10 births are suppressed for privacy reasons.

Source: Center for Policy Planning and Evaluation, DC Department of Health

Why This Matters

Preterm birth is a leading cause of infant deaths in the United States. Babies born preterm are also at an increased risk of breathing problems, feeding difficulties, cerebral palsy, developmental delay, vision problems, and hearing problems.

Nationally, approximately one in ten babies are born preterm. Factors such as maternal age, pregnancy history, medical conditions, lifestyle, and access to health care contribute to preterm births.

Preterm birth rates are highest among infants born to Black and Native American mothers. These disparities are associated with racism-related stress and structural barriers to education, quality health care, affordable housing, and sustainable income that disproportionately affect communities of color.

The District Response

Enhancements to District healthcare programs. Medicaid expansion provides greater access to prenatal care, extended postpartum Medicaid coverage for a full year, and reimbursement for doula services through all District programs. For a list of local and national resources on pregnancy and related topics, click here.

Supports mother and infant health outcomes through DC Women, Infants and Children (WIC) and various perinatal health programs, partnering with community-based organizations, healthcare institutions, and District agencies.

Paid family leave program provides 12 weeks to bond with a new child or care for a serious health condition, and 2 weeks specifically for prenatal care.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.