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

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.

Note: This dataset is historical only and there are not corresponding datasets for more recent time periods. For that more-recent information, please visit the Chicago Health Atlas at https://chicagohealthatlas.org.

This dataset contains the annual number of births and crude birth rate (births per 1,000 residents) with corresponding 95% confidence intervals, by Chicago community area, for the years 1999 – 2009. See the full dataset description for more information: https://data.cityofchicago.org/api/assets/8C4E8E51-6162-4DF3-9C29-D3F205FA2FB4

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

The dataset contains the birth rates calculated with municipal detail for 1,000 residents in the period January - October of the year 2022. The source of the data is Istat - Demographic Report

The Russian Fertility Database of the International Laboratory for Population and Health of HSE University contains fertility rates in Russia for the period from 1946 to 2022 and for women born in 1932-1988. The Russian Fertility Database is primarily oriented to the experts involved in demographic analysis. The data are presented in *.xlsx format.

All indicators presented in the database are calculated on the basis of population statistics data from the Federal State Statistics Service. Birth rates for 1946-1958 are calculated on the basis of the numbers of births by birth order and mother's age for 1946-1958 and population data for 1946-1958 presented in the book Andreev E.M., Darsky L.E., Kharkova T.L. (1998) Demographic History of Russia: 1927-1959. M.: Informatika. 187 p. Birth rates for 1959-2022 are calculated on the basis of the numbers of births by birth order and mother's age for 1959-2022 and data on the age distribution of the population for 1959-2023.

Purpose:This dataset contains the Crude Rate of Low Weight Births (Singleton) / All Singleton Births Per Colorado Census Tract (2019-2023). Numerator and denominator data are calculated from the 2019-2023 Colorado Department of Public Health and Environment Colorado Live Birth Statistics.Update Schedule and URL:This dataset is updated annually (September) and is provided using death data directly assembled from the Colorado Department of Public Health and Environment Colorado Live Birth Statistics. For inquiries about vital statistics or for data requests contact cdphe.healthstatistics@state.co.us, or use the data request system.Fields Description:GEOID: 11-digit Census Tract FIPS Identifier COUNTY: County NameNAME: Census Tract NameLWB_ADJRATE: Crude Low Weight Birth Rate (2019-2023, Colorado Live Birth Statistics)LWB_L95CI: Low Weight Birth Rate Lower 95% Confidence IntervalLWB_U95CI: Low Weight Birth Rate Upper 95% Confidence IntervalLWB_STATEADJRATE: Statewide Crude Low Weight Birth Rate (2019-2023, Colorado Live Birth Statistics)LWB_SL95CI: Statewide Low Weight Birth Rate Lower 95% Confidence IntervalLWB_SU95CI: Statewide Low Weight Birth Rate Upper 95% Confidence IntervalLWB_DISPLAY: Low Weight Birth Rate Census Tract Map Display Designation (Estimate is Higher Than State Average Confidence Interval, Lower Than State Average Confidence Interval, Not Different Than State Average Confidence Interval, No Events or Data Suppressed)

About this dataset

Context

The dataset tabulates the population of San Bernardino County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for San Bernardino County. The dataset can be utilized to understand the population distribution of San Bernardino County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in San Bernardino County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for San Bernardino County.

Key observations

Largest age group (population): Male # 10-14 years (87,550) | Female # 30-34 years (81,852). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the San Bernardino County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the San Bernardino County is shown in the following column.
• Population (Female): The female population in the San Bernardino County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in San Bernardino County for each age group.

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 San Bernardino County Population by Gender. You can refer the same here

These summary metadata refer to the first results on the main demographic developments in the year of reference.

Member States send to Eurostat the first results on the main demographic developments in the year of reference (T), containing the total population figure on 31 December of year T (further published by Eurostat as Population on 1 January of year T+1), total births and total deaths during year T. This data collection is defined under http://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32013R1260&from=EN" target="_blank">Regulation 1260/2013 on European demographic statistics. Countries may also transmit to Eurostat, on voluntary basis, provisional data on total immigration, emigration and net migration during the year (T).

Eurostat's data collection on the above figures is called DEMOBAL and it is carried out in June of each year. Eurostat publishes these first demographic estimates in July of each year in the online database, in the table Population change - Demographic balance and crude rates (demo_gind).

These first demographic estimates may either be confirmed or updated by Eurostat's demographic data collection taking place in December each year (called Unidemo), whereby countries submit detailed breakdowns (e.g. by age and sex) of their yearly population data, including data on migration, both at national and at regional level. The online table Population change - Demographic balance and crude rates (demo-gind) will be accordingly updated. This table includes the latest updates on total population, births and deaths reported by the countries, while the detailed breakdowns by various characteristics included in the rest of the tables of the Eurostat database (Demography domain and Migration, for example the Population by citizenship and by country of birth table) may be transmitted to Eurostat at a subsequent date.

The online table Population change - Demographic balance and crude rates (demo-gind) contains time series going back to 1960; data before 2013 were collected by Eurostat from the national statistical offices on voluntary basis.

The individual metadata files reported by the countries are attached to this metadata file.

About this dataset

Context

The dataset tabulates the population of Orange County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Orange County. The dataset can be utilized to understand the population distribution of Orange County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Orange County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Orange County.

Key observations

Largest age group (population): Male # 25-29 years (59,150) | Female # 25-29 years (58,241). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Orange County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Orange County is shown in the following column.
• Population (Female): The female population in the Orange County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Orange County for each age group.

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 Orange County Population by Gender. You can refer the same here

Annual average birth data by zip code from the Michigan Department of Community Health, Vital Statistics. Covers years 2009-11, 2010-12, and 2011-13. Birth rates were calculated by Kurt Metzger. Birth Rate = Number of births per 1,000 Women 15-44 years of age (2010 Census).

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated 8/14/2024.

Number of live births and birth rate per 1,000 population by year.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

This table provides statistics on the Number of Births, Percent of Low/High Birth Weight, Birth Rate, Fertility Rate, Teen Birth Rate, Percent Maternal Prenatal Smoking . This indicator dataset contains information at both Local Geographic Area (for example, Lacombe, Red Deer - North, Calgary - West Bow, etc.) and Alberta levels. Local geographic area refers to 132 geographic areas created by Alberta Health (AH) and Alberta Health Services (AHS) based on census boundaries. This table is the part of "Alberta Health Primary Health Care - Community Profiles" report published March 2015.

About this dataset

Context

The dataset tabulates the population of Hampshire by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Hampshire. The dataset can be utilized to understand the population distribution of Hampshire by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Hampshire. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Hampshire.

Key observations

Largest age group (population): Male # 50-54 years (450) | Female # 10-14 years (670). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Hampshire population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Hampshire is shown in the following column.
• Population (Female): The female population in the Hampshire is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Hampshire for each age group.

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 Hampshire Population by Gender. You can refer the same here

This dataset is a comprehensive resource for analyzing key socio-economic and health indicators related to gender across various countries worldwide. It serves as an example dataset for the R programming package 'genderstat'. The dataset encompasses crucial metrics including life expectancy, education, gross national income per capita, maternal mortality rates, adolescent birth rates, and labor force participation. It has been meticulously curated from reputable sources such as the UNDP Human Development Reports and the World Bank Gender Data Portal.

About this dataset

Context

The dataset tabulates the population of Pueblo by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Pueblo. The dataset can be utilized to understand the population distribution of Pueblo by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Pueblo. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Pueblo.

Key observations

Largest age group (population): Male # 25-29 years (4,255) | Female # 60-64 years (3,836). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Pueblo population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Pueblo is shown in the following column.
• Population (Female): The female population in the Pueblo is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Pueblo for each age group.

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 Pueblo Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Niagara County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Niagara County. The dataset can be utilized to understand the population distribution of Niagara County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Niagara County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Niagara County.

Key observations

Largest age group (population): Male # 55-59 years (8,367) | Female # 60-64 years (8,580). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Niagara County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Niagara County is shown in the following column.
• Population (Female): The female population in the Niagara County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Niagara County for each age group.

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 Niagara County Population by Gender. You can refer the same here

Fetal mortality occurs after 20 weeks of gestation and before labor. Infant mortality occurs before the first year of age and is a sum of Neonatal (the first 28 days after birth) and Postneonatal (from 28 days up to 1 year) mortality. Rates are calculated per every 1000 births; rates are not available for disaggregated race/ethnicities. Fetal and infant mortality values are available for given race/ethnicities. Connecticut Department of Public Health collects and reports data annually. CTData.org carries 1-, 3- and 5-Year aggregations.

In 2023, the crude birth rate in live births per 1,000 inhabitants in India stood at 16.15. Between 1960 and 2023, the figure dropped by 26.75, though the decline followed an uneven course rather than a steady trajectory.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

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