United States US: Unmet Need for Contraception: % of Married Women Aged 15-49 data was reported at 9.000 % in 2014. This records an increase from the previous number of 8.000 % for 2010. United States US: Unmet Need for Contraception: % of Married Women Aged 15-49 data is updated yearly, averaging 6.000 % from Dec 1988 (Median) to 2014, with 7 observations. The data reached an all-time high of 9.000 % in 2014 and a record low of 4.000 % in 1988. United States US: Unmet Need for Contraception: % of Married Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Unmet need for contraception is the percentage of fertile, married women of reproductive age who do not want to become pregnant and are not using contraception.; ; Household surveys, including Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Largely compiled by United Nations Population Division.; Weighted Average; Unmet need for contraception measures the capacity women have in achieving their desired family size and birth spacing. Many couples in developing countries want to limit or postpone childbearing but are not using effective contraception. These couples have an unmet need for contraception. Common reasons are lack of knowledge about contraceptive methods and concerns about possible side effects.

United States US: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data was reported at 13.300 % in 2016. This records an increase from the previous number of 12.400 % for 2015. United States US: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data is updated yearly, averaging 9.100 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 13.300 % in 2016 and a record low of 7.700 % in 2001. United States US: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of anemia among women of reproductive age refers to the combined prevalence of both non-pregnant with haemoglobin levels below 12 g/dL and pregnant women with haemoglobin levels below 11 g/dL.; ; World Health Organization, Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/gho/data/node.main.1?lang=en).; Weighted Average;

Prevalence of anemia among women of reproductive age (% of women ages 15-49) in North America was reported at 11.66 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. North America - Prevalence of anemia among women of reproductive age (% of women ages 15-49) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

This dataset includes birth rates for unmarried women by age group, race, and Hispanic origin in the United States since 1970. Methods for collecting information on marital status changed over the reporting period and have been documented in: • Ventura SJ, Bachrach CA. Nonmarital childbearing in the United States, 1940–99. National vital statistics reports; vol 48 no 16. Hyattsville, Maryland: National Center for Health Statistics. 2000. Available from: http://www.cdc.gov/nchs/data/nvsr/nvsr48/nvs48_16.pdf. • National Center for Health Statistics. User guide to the 2013 natality public use file. Hyattsville, Maryland: National Center for Health Statistics. 2014. Available from: http://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm. National data on births by Hispanics origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; for New Hampshire and Oklahoma in 1990; for New Hampshire in 1991 and 1992. 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.) All birth data by race before 1980 are based on race of the child. Starting in 1980, birth data by race are based on race of the mother. SOURCES CDC/NCHS, National Vital Statistics System, birth data (see http://www.cdc.gov/nchs/births.htm); public-use data files (see http://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm); and CDC WONDER (see http://wonder.cdc.gov/). REFERENCES Curtin SC, Ventura SJ, Martinez GM. Recent declines in nonmarital childbearing in the United States. NCHS data brief, no 162. Hyattsville, MD: National Center for Health Statistics. 2014. Available from: http://www.cdc.gov/nchs/data/databriefs/db162.pdf. 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.

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).

Prevalence of anemia among women of reproductive age (% of women ages 15-49) in United States was reported at 11.8 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Prevalence of anemia among women of reproductive age (% of women ages 15-49) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

United States US: Fertility Rate: Total: Births per Woman data was reported at 1.800 Ratio in 2016. This records a decrease from the previous number of 1.843 Ratio for 2015. United States US: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 2.002 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 3.654 Ratio in 1960 and a record low of 1.738 Ratio in 1976. United States US: Fertility Rate: Total: Births per Woman data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average; Relevance to gender indicator: it can indicate the status of women within households and a woman’s decision about the number and spacing of children.

United States US: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 data was reported at 72.700 % in 2014. This records a decrease from the previous number of 74.100 % for 2012. United States US: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 data is updated yearly, averaging 72.800 % from Dec 1965 (Median) to 2014, with 15 observations. The data reached an all-time high of 79.000 % in 1975 and a record low of 66.500 % in 1965. United States US: Contraceptive Prevalence: Any Methods: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Contraceptive prevalence rate is the percentage of women who are practicing, or whose sexual partners are practicing, any form of contraception. It is usually measured for women ages 15-49 who are married or in union.; ; UNICEF's State of the World's Children and Childinfo, United Nations Population Division's World Contraceptive Use, household surveys including Demographic and Health Surveys and Multiple Indicator Cluster Surveys.; Weighted average; Contraceptive prevalence amongst women of reproductive age is an indicator of women's empowerment and is related to maternal health, HIV/AIDS, and gender equality.

This is the code replication archive for the paper, "The COVID-19 Baby Bump in the United States," published in the Proceedings of the National Academy of Sciences. The underlying natality microdata are restricted, so this archive contains only the code to replicate our analysis.We use natality microdata covering the universe of U.S. births for 2015-2021 and California births from 2015 through February 2023 to examine childbearing responses to the COVID-19 pandemic. We find that 60% of the 2020 decline in U.S. fertility rates was driven by sharp reductions in births to foreign-born mothers although births to this group comprised only 22% of all U.S. births in 2019. This decline started in January 2020. In contrast, the COVID-19 recession resulted in an overall “baby bump” among U.S.-born mothers which marked the first reversal in declining fertility rates since the Great Recession. Births to U.S.-born mothers fell by 31,000 in 2020 relative to a pre-pandemic trend but increased by 71,000 in 2021. The data for California suggest that U.S. births remained elevated through February 2023. The baby bump was most pronounced for first births and women under age 25, suggesting that the pandemic led some women to start families earlier. Above age 25, the baby bump was most pronounced for women ages 30-34 and women with a college education. The 2021-2022 baby bump is especially remarkable given the large declines in fertility rates that would have been projected by standard statistical models.

Abstract

During the early 1990s Romania was faced with the reproductive health consequences of an aberrant pronatalist policy enforced for several decades by the Ceausescu's regime. Health policy makers tried to rapidly respond to these consequences by adopting new health strategies to reduce maternal and infant mortality. These strategies included development of the first national family planning program; introduction of new technologies in neonatal and maternal health services; implementation of active measurements to control the HIV/AIDS epidemic; and development of social programs for abandoned, institutionalized, and drug-using children and for domestic violence.

Such a rapidly changing array of critical reproductive health issues could not have been documented and addressed with only the help of vital records. More information was needed to assess the reproductive health status of the Romanian population during a period of rapid change in health care that influenced the health of women and children.

In 1993, the Romanian Ministry of Health, with technical assistance provided by the Division of Reproductive Health of the Centers for Disease Control and Prevention (DRH/CDC), conducted the first national population-based survey of women's reproductive health (93RRHS). The survey was designed to provide the Ministry of Health, international agencies, and nongovernmental organizations active in women's and children's health with essential information on fertility, women's reproductive practices, maternal care, maternal and child mortality, health behaviors, and attitudes toward selected reproductive health issues. The 93RRHS was instrumental in developing, evaluating, and fine-tuning the national family planning program and other reproductive health policies.

In 1996, a representative sample survey of women and men aged 15-24 was implemented to document young adult's sex education, attitudes, sexual behavior and use of contraception. Such survey had never before been carried out in Eastern Europe. Survey results were used to plan effective information campaigns, policies and programs targeting young people, and to monitor and evaluate the impact of programs already in place.

In 1999, a new nationwide reproductive health survey was designed and implemented in Romania (99RRHS) using the same methodology to allow for the study of reproductive health trends among the women aged 15-44 and to document the reproductive health of men aged 15-49. The surveys employed two separate probability samples to allow independent estimates for males and females. The survey's Final Report improves the already impressive contribution of the previous two studies because: a) documents reproductive health aspects among both women and men of reproductive age (men were selected from different households than women); and b) by oversampling three target judet (Constanta, Iasi and Cluj) documents the impact of region-wide interventions, implemented with USAID support, that consists of the establishment of modern women's health clinics, training of health professionals, development of IEC messages, social marketing, and provision of highquality contraceptive supplies.

In conclusion, the results of these large nationwide cross-sectional studies implemented in 1993 (sample size of 4,861 women aged 15-44), 1996 (sample size of 2025 women and 2047 men aged 15-24), and 1999 (sample size of 6,888 women aged 15-44 and 2,434 men aged 15-49), allow for generalizing the results to the entire reproductive age population of Romania. Although the surveys did not interview the same households, by applying similar questionnaires, the same sampling and field work methodology, they allow for a) a longitudinal examination of reproductive health issues among women, b) a detailed image of specific aspects of reproductive and sexual behaviors among men and c) a programmatic evaluation of reproductive health services in three regions.

Geographic coverage

The 99RRHS was designed to collect information from a representative sample of women and men of reproductive age throughout Romania.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 99RRHS was designed to collect information from a representative sample of women and men of reproductive age throughout Romania. Respondents were selected from the universe of all females aged 15-44 years and all males aged 15-49 years, regardless of marital status, who were living in Romania when the survey was conducted. The desired sample for females was 6,500, including an oversample of women in the three US AID priority judets (Cluj, Constanta, and Iasi).

The desired sample size for males was 2,500. The female and male samples were selected independently.

The survey used a three-stage sampling design, which allows independent estimates for the female and male samples. An updated master sampling frame (EMZOT), based on the 1992 census enumeration areas, was used as the sampling frame (National Commission for Statistics, 1996). The EMZOT master sample represents 3% of the population in each judet. In the female sample, the US AID priority judets were oversampled in both urban and rural areas to allow for independent estimates with adequate precision for women's health behaviors in these judets.

Except for the three oversampled judets (in which all available census sectors in the sample were retained), the first stage of the sample design was a selection of census sectors with probability proportional to the number of households recorded in the EMZOT. This step was accomplished by using a systematic sample with a random start for the female sample. A 50% subsample of the census sectors selected in the female sample (not including the oversample in the priority judets) constituted the first stage of the male sample. Thus, the first-stage selection included 317 sectors for the female sample and 128 sectors for the male sample. In the second stage of sampling, clusters of households were randomly selected in each census sector chosen in the first stage (separate households were selected for the female and male samples). Finally, in each of the households in the female sample, one woman aged 15—44 years was selected at random for interviewing and in the male sample one man aged 15-49 years was randomly selected in each household.

Because only one woman was selected from each household with women of reproductive age, and one male was selected from households with men of reproductive age, all results have been weighted to compensate for the fact that some households included more than one eligible female or male respondent. Survey results were also weighted to adjust for oversampling of households in the three US AID priority judets, and two more weights were added to adjust for non-response and for urban-rural distribution of the population.

Cluster size was determined based on the number of households required to obtain an average of 20 completed interviews per cluster. The number of households in each cluster took into account estimates of unoccupied households, average number of women aged 15-44 per household (men aged 15-49 for the male sample), the interview of only one respondent per household, and an estimated response rate of 90% in urban areas and 92% in rural areas for women and of 85% overall for men. Cluster size was determined to be 51 households in urban areas and 59 households in rural areas for the female sample and 49 and 55 households, respectively, for the male sample.

Mode of data collection

Face-to-face [f2f]

Response rate

Of the 17,349 households selected in the female sample and 6,310 households selected in the male sample, 7,645 and 2,812 included at least one eligible respondent (a woman aged 15-44 or a man aged 15-49). Of these, 6,888 women and 2,434 men were successfully interviewed, yielding response rates of 90% and 87%, respectively. As many as four visits were placed to each household with eligible respondents who were not at home during the initial household approach.

Almost all respondents who were selected to participate and who could be reached agreed to be interviewed. Only 2% of respondents (regardless of gender) refused to be interviewed, and 7% of women and 11% of men could not be located. Response rates were not significantly different by residence, except for Bucharest, where the participation rate was slightly lower. Even though the overall response rate was similar in urban and rural areas, eligible respondents in urban areas were somewhat more likely to refuse to be interviewed; in rural areas eligible respondents were more likely to not be found at home.

Graph and download economic data for Fertility Rate, Total for the United States (SPDYNTFRTINUSA) from 1960 to 2023 about fertility, rate, and USA.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES FERTILITY - DP02 Universe - Women 15 to 50 years old who had a birth in the past 12 months Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 The question asked if the person had given birth in the past 12 months, and was asked of all women 15 to 50 years old regardless of marital status. From this question, we are able to determine geographies with high numbers of women with births and the characteristics of these women, such as age and marital status. When fertility was not reported, it was imputed according to the woman’s age and marital status and the possibility there was an infant in the household.

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows fertility in past 12 months by age of mother. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. The calculated percentages are slightly different from traditional age-specific fertility rates in that the total number of live births (due to twins or higher-order multiple births) is not available in this table. Note: Data are not available for all geographies within this layer due to data suppression done by the American Community Survey. Since there was a data collection error in the 2011 and 2012 surveys, this impacts the 2010-2014 5-year estimates. To learn more and to see a list of the affected geographies, visit this page about Errata 119.This layer is symbolized to show the percent of women age 15 to 50 who had a birth in the past 12 months. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B13016 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 11, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Historical chart and dataset showing U.S. fertility rate by year from 1950 to 2025.

Analysis of ‘NCHS - Birth Rates for Unmarried Women by Age, Race, and Hispanic Origin: United States’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/05adf260-cbad-4811-996b-35427e1c800c on 27 January 2022.

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

This dataset includes birth rates for unmarried women by age group, race, and Hispanic origin in the United States since 1970.

Methods for collecting information on marital status changed over the reporting period and have been documented in:

• Ventura SJ, Bachrach CA. Nonmarital childbearing in the United States, 1940–99. National vital statistics reports; vol 48 no 16. Hyattsville, Maryland: National Center for Health Statistics. 2000. Available from: http://www.cdc.gov/nchs/data/nvsr/nvsr48/nvs48_16.pdf. • National Center for Health Statistics. User guide to the 2013 natality public use file. Hyattsville, Maryland: National Center for Health Statistics. 2014. Available from: http://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm.

National data on births by Hispanics origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; for New Hampshire and Oklahoma in 1990; for New Hampshire in 1991 and 1992. 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.)

All birth data by race before 1980 are based on race of the child. Starting in 1980, birth data by race are based on race of the mother.

SOURCES

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

REFERENCES

1. Curtin SC, Ventura SJ, Martinez GM. Recent declines in nonmarital childbearing in the United States. NCHS data brief, no 162. Hyattsville, MD: National Center for Health Statistics. 2014. Available from: http://www.cdc.gov/nchs/data/databriefs/db162.pdf.

2. 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.

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

Analysis of ‘🤰 Pregnancy, Birth & Abortion Rates (1973 - 2016)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/pregnancy-birth-abortion-rates-in-the-united-stae on 13 February 2022.

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

About this dataset

Source: OSF | Downloaded on 29 October 2020

This data source is a subset of the original data source. The data has been split by State, Metric and Age Range. It has been limited to pregnancy rate, birth rate and abortion rate per 1,000 women. The original data contains many more measures.

The data was prepared with Tableau Prep.

Summary via OSF -

A data set of comprehensive historical statistics on the incidence of pregnancy, birth and abortion for people of all reproductive ages in the United States. National statistics cover the period from 1973 to 2016, the most recent year for which comparable data are available; state-level statistics are for selected years from 1988 to 2016. For a report describing key highlights from these data, as well as a methodology appendix describing our methods of estimation and data sources used, see https://guttmacher.org/report/pregnancies-births-abortions-in-united-states-1973-2016.

​

This dataset was created by Andy Kriebel and contains around 20000 samples along with Age Range, Events Per 1,000 Women, technical information and other features such as: - State - Year - and more.

How to use this dataset

• Analyze Metric in relation to Age Range
• Study the influence of Events Per 1,000 Women on State
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Andy Kriebel

Start A New Notebook!

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

In 2023, around 85 percent of infants in the United States were being breastfed at discharge from the hospital, highlighting a strong trend towards early breastfeeding. This statistic shows select medical and health characteristics of mothers during pregnancy and birth in the United States in 2023.

Maternal health and birth characteristics The data reveals that 59.7 percent of delivering mothers in the U.S. were overweight or obese in 2023, a concerning statistic for maternal health. Additionally, 32.3 percent of births were via cesarean delivery, while only 1.5 percent were home births. Home birth rates vary by state, with Idaho having the highest at 4.7 percent. Despite the low overall rate of home births, some women choose this option for reasons including less medical intervention, location preference, cost, and cultural or religious factors. Declining birth rates and changing demographics The overall birth rate in the United States has been steadily declining over the past few decades. In 2022, there were 11 births per 1,000 population, down from 16.7 in 1990. This decline is influenced by various factors, including financial concerns and increased focus on careers among women. Interestingly, birth rates vary significantly across different ethnic groups, with Native Hawaiian and Pacific Islander women having the highest birth rates, while Asian and white women have the lowest.

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..When information is missing or inconsistent, the Census Bureau logically assigns an acceptable value using the response to a related question or questions. If a logical assignment is not possible, data are filled using a statistical process called allocation, which uses a similar individual or household to provide a donor value. The "Allocated" section is the number of respondents who received an allocated value for a particular subject..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.

For current version see: https://data.sandiegocounty.gov/Health/2021-Non-Communicable-Chronic-Diseases/v7dt-rwpx

Basic Metadata Note: Definition includes Uterine, Ovarian, and Cervical Cancers. *Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population.

**Blank Cells: Rates not calculated for fewer than 5 events. Rates not calculated in cases where zip code is unknown.

***API: Asian/Pacific Islander. ***AIAN: American Indian/Alaska Native.

Prepared by: County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2019.

Code Source: ICD-9CM - AHRQ HCUP CCS v2015. ICD-10CM - AHRQ HCUP CCS v2018. ICD-10 Mortality - California Department of Public Health, Group Cause of Death Codes 2013; NHCS ICD-10 2e-v1 2017.

Data Guide, Dictionary, and Codebook: https://www.sandiegocounty.gov/content/dam/sdc/hhsa/programs/phs/CHS/Community%20Profiles/Public%20Health%20Services%20Codebook_Data%20Guide_Metadata_10.2.19.xlsx

Fertility rate, total (births per woman) in United States was reported at 1.6165 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Fertility rate, total (births per woman) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.