This dataset includes estimates of U.S. life expectancy at birth by state and census tract for the period 2010-2015 (1). Estimates were produced for 65,662 census tracts, covering the District of Columbia (D.C.) and all states, excluding Maine and Wisconsin, representing 88.7% of all U.S. census tracts (see notes). These estimates are the result of the collaborative project, “U.S. Small-area Life Expectancy Estimates Project (USALEEP),” between the National Center for Health Statistics (NCHS), the National Association for Public Health Statistics and Information Systems (NAPHSIS), and the Robert Wood Johnson Foundation (RWJF) (2).

While the standard image of the nuclear family with two parents and 2.5 children has persisted in the American imagination, the number of births in the U.S. has steadily been decreasing since 1990, with about 3.6 million babies born in 2023. In 1990, this figure was 4.16 million. Birth and replacement rates A country’s birth rate is defined as the number of live births per 1,000 inhabitants, and it is this particularly important number that has been decreasing over the past few decades. The declining birth rate is not solely an American problem, with EU member states showing comparable rates to the U.S. Additionally, each country has what is called a “replacement rate.” The replacement rate is the rate of fertility needed to keep a population stable when compared with the death rate. In the U.S., the fertility rate needed to keep the population stable is around 2.1 children per woman, but this figure was at 1.67 in 2022. Falling birth rates Currently, there is much discussion as to what exactly is causing the birth rate to decrease in the United States. There seem to be several factors in play, including longer life expectancies, financial concerns (such as the economic crisis of 2008), and an increased focus on careers, all of which are causing people to wait longer to start a family. How international governments will handle falling populations remains to be seen, but what is clear is that the declining birth rate is a multifaceted problem without an easy solution.

This dataset assembles all final birth data for females aged 15–19, 15–17, and 18–19 for the United States and each of the 50 states.

Data are based on 100% of birth certificates filed in all 50 states. All the teen birth rates in this dashboard reflect the latest revisions to Census populations (i.e., the intercensal populations) and thus provide a consistent series of accurate rates for the past 25 years. The denominators of the teen birth rates for 1991–1999 have been revised to incorporate the results of the 2000 Census. The denominators of the teen birth rates for 2001–2009 have revised to incorporate the results of the 2010 Census.

This collection provides information on live births in the United States during calendar year 2010. The natality data in these files are a component of the vital statistics collection effort maintained by the federal government. Birth data is limited to births occurring in the United States to United States residents and nonresidents. Births occurring to United States citizens outside of the United States are not included in this data collection. Dataset 1 contains data on births occurring within the United States, while dataset 2 contains data on births occurring in the United States territories of Puerto Rico, the Virgin Islands, Guam, American Samoa, and the Commonwealth of the Northern Mariana Islands. Variables describe the place of delivery, who was in attendance, and medical and health data such as the method of delivery, prenatal care, tobacco use during pregnancy, pregnancy history, medical risk factors, and infant health characteristics. Birth and fertility rates, and other statistics related to this study can be found in an Appendix to the User Guide under Detailed Technical Notes. Demographic variables include the child's sex and month and year of birth and the parents' ages, races, ethnicities, education levels, as well as the mother's marital status and residency status.

This data set contains estimated teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) by county and year.

DEFINITIONS

Estimated teen birth rate: Model-based estimates of teen birth rates for age group 15–19 (expressed per 1,000 females aged 15–19) for a specific county and year. Estimated county teen birth rates were obtained using the methods described elsewhere (1,2,3,4). These annual county-level teen birth estimates “borrow strength” across counties and years to generate accurate estimates where data are sparse due to small population size (1,2,3,4). The inferential method uses information—including the estimated teen birth rates from neighboring counties across years and the associated explanatory variables—to provide a stable estimate of the county teen birth rate. Median teen birth rate: The middle value of the estimated teen birth rates for the age group 15–19 for counties in a state. Bayesian credible intervals: A range of values within which there is a 95% probability that the actual teen birth rate will fall, based on the observed teen births data and the model.

NOTES

Data on the number of live births for women aged 15–19 years were extracted from the National Center for Health Statistics’ (NCHS) National Vital Statistics System birth data files for 2003–2015 (5).

Population estimates were extracted from the files containing intercensal and postcensal bridged-race population estimates provided by NCHS. For each year, the July population estimates were used, with the exception of the year of the decennial census, 2010, for which the April estimates were used.

Hierarchical Bayesian space–time models were used to generate hierarchical Bayesian estimates of county teen birth rates for each year during 2003–2015 (1,2,3,4).

The Bayesian analogue of the frequentist confidence interval is defined as the Bayesian credible interval. A 100*(1-α)% Bayesian credible interval for an unknown parameter vector θ and observed data vector y is a subset C of parameter space Ф such that 1-α≤P({C│y})=∫p{θ │y}dθ, where integration is performed over the set and is replaced by summation for discrete components of θ. The probability that θ lies in C given the observed data y is at least (1- α) (6).

County borders in Alaska changed, and new counties were formed and others were merged, during 2003–2015. These changes were reflected in the population files but not in the natality files. For this reason, two counties in Alaska were collapsed so that the birth and population counts were comparable. Additionally, Kalawao County, a remote island county in Hawaii, recorded no births, and census estimates indicated a denominator of 0 (i.e., no females between the ages of 15 and 19 years residing in the county from 2003 through 2015). For this reason, Kalawao County was removed from the analysis. Also , Bedford City, Virginia, was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. For consistency, Bedford City was merged with Bedford County, Virginia, for the entire 2003–2015 period. Final analysis was conducted on 3,137 counties for each year from 2003 through 2015. County boundaries are consistent with the vintage 2005–2007 bridged-race population file geographies (7).

Ratio: Number of live births to resident females aged 15-17

Definition: The number of live births to resident females aged 15-17, per 1,000 females in the age group.

Data Sources:

(1) Birth Certificate Database, Office of Vital Statistics and Registry, New Jersey Department of Health;

(2) National Center for Health Statistics and U.S. Census Bureau. Vintage 2014 bridged-race postcensal population estimates;

(3) National Center for Health Statistics and U.S. Census Bureau. Revised 2000-2009 bridged-race intercensal population estimates.

Live births and stillbirths annual summary statistics, by sex, age of mother, whether within marriage or civil partnership, percentage of non-UK-born mothers, birth rates and births by month and mothers' area of usual residence.

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.

https://www.cdc.gov/nchs/data-visualization/births-to-unmarried-women/in...

This dataset tracks the updates made on the dataset "U.S. Life Expectancy at Birth by State and Census Tract - 2010-2015" as a repository for previous versions of the data and metadata.

This dataset of U.S. mortality trends since 1900 highlights the differences in age-adjusted death rates and life expectancy at birth by race and sex.

Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below).

Life expectancy data are available up to 2017. Due to changes in categories of race used in publications, data are not available for the black population consistently before 1968, and not at all before 1960. More information on historical data on age-adjusted death rates is available at https://www.cdc.gov/nchs/nvss/mortality/hist293.htm.

SOURCES

CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov).

REFERENCES

1. National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm.

2. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm.

3. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf.

4. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf.

5. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

Number of live births, by place of residence of mother (Canada, province or territory, and outside Canada) and place of occurrence (Canada, province or territory, and the United States), 1991 to most recent year.

Crude birth rates, age-specific fertility rates and total fertility rates (live births), 2000 to most recent year.

This dataset tracks the updates made on the dataset "NCHS - Pregnancy and Live Birth Rates, by Marital Status and Race and Hispanic Origin: United States, 1990-2010" as a repository for previous versions of the data and metadata.

Estimated annual number of births by gender for Canada, provinces and territories.

United States US: Low-Birthweight Babies: % of Births data was reported at 8.100 % in 2010. This records an increase from the previous number of 8.000 % for 2002. United States US: Low-Birthweight Babies: % of Births data is updated yearly, averaging 8.050 % from Dec 2002 (Median) to 2010, with 2 observations. The data reached an all-time high of 8.100 % in 2010 and a record low of 8.000 % in 2002. United States US: Low-Birthweight Babies: % of Births 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. Low-birthweight babies are newborns weighing less than 2,500 grams, with the measurement taken within the first hours of life, before significant postnatal weight loss has occurred.; ; UNICEF, State of the World's Children, Childinfo, and Demographic and Health Surveys.; Weighted average;

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_6150f21b0892b3fdde546d2a1af2af82/view

Babies with Low Birth Weight - This indicator shows the percentage of live births that are a low birth weight (2500 grams or less). Babies born with a low birth weight are at increased risk for serious health consequences including disabilities and death. Low birth weight babies weigh less than 2,500 grams (5.5 pounds). Maryland’s low birth weight percentage is higher than the national average.

Baltimore City Child Health

An Exploration of 2010 Birth, Prenatal Visit, Lead Exposure and Teen Birth Rates

By City of Baltimore [source]

About this dataset

This Baltimore City Child and Family Health Indicators dataset provides us with crucial information that can support the health and well-being of Baltimore City residents. It contains 13 indicators such as low birth weight, prenatal visits, teen births, and more. This data is sourced from the Maryland Department of Health & Mental Hygiene (DHMH), Baltimore Substance Abuse Systems (BSAS), theBaltimore City Health Department, and the US Census Bureau. Through this data set we can gain a better understanding of how Baltimore City citizens’ health compares to other areas and how it has changed over time. By investigating this dataset we are given an opportunity to create potential strategies for providing better care for our community. With discoveries from these indicators, together as a city we can bring about lasting change in protecting public health within Baltimore

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How to use the dataset

This dataset provides valuable information about the health and wellbeing of children and families in Baltimore City in 2010. The data is organized by CSA (Census Statistical Area) and includes stats on term births, low birth weight births, prenatal visits, teen births, and lead testing. This dataset can be used to analyze trends in children's health over time as well as identify potential areas that need more attention or resources.

To use this dataset: - Read through the data dictionary to understand what each column represents.
- Choose which columns you would like to explore further.
- Filter or subset the data as you see fit then visualize it with graphs or maps to better understand how conditions vary across neighborhoods in Baltimore City.
- Consider comparing the data from this year with prior years if available for deeper analysis of changes over time.
- Look for correlations among columns that could help explain disparities between neighborhoods and create strategies for improving outcomes through policy interventions or other programs designed specifically for those areas needs

Research Ideas

• Mapping health disparities in high-risk areas to target public health interventions.
• Identifying neighborhoods in need of additional resources for prenatal care, infant care, and lead testing and create specific programs to address these needs.
• Creating an online dashboard that displays real time data on Baltimore City’s population health indicators such as birth weight, teenage pregnancies, and lead poisoning for the public to access easily

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: BNIA_Child_Fam_Health_2010.csv | Column name | Description | |:---------------|:----------------------------------------------------------| | the_geom | Geometry of the Census Statistical Area (CSA) (Geometry) | | CSA2010 | Census Statistical Area (CSA) (String) | | termbir10 | Total number of term births in 2010 (Integer) | | birthwt10 | Total number of low birth weight births in 2010 (Integer) | | prenatal10 | Total number of prenatal visits in 2010 (Integer) | | teenbir10 | Total number of teen births in 2010 (Integer) | | leadtest10 | Total number of lead tests conducted in 2010 (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit City of Baltimore.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

This table contains data on the country of birth of foreign born individuals from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).