US Births by County and State

1985-2015 Aggregated Data

By data.world's Admin [source]

About this dataset

This dataset contains an aggregation of birth data from the United Statesbetween 1985 and 2015. It consists of information on mothers' locations by state (including District of Columbia) and county, as well as information such as the month they gave birth, and aggregates giving the sum of births during that month. This data has been provided by both the National Bureau for Economic Research and National Center for Health Statistics, whose shared mission is to understand how life works in order to aid individuals in making decisions about their health and wellbeing. This dataset provides valuable insight into population trends across time and location - for example, which states have higher or lower birthrates than others? Which counties experience dramatic fluctuations over time? Given its scope, this dataset could be used in a number of contexts--from epidemiology research to population forecasting. Be sure to check out our other datasets related to births while you're here!

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How to use the dataset

This dataset could be used to examine local trends in birth rates over time or analyze births at different geographical locations. In order to maximize your use of this dataset, it is important that you understand what information the various columns contain.

The main columns are: State (including District of Columbia), County (coded using the FIPS county code number), Month (numbering from 1 for January through 12 for December), Year (4-digit year) countyBirths (calculated sum of births that occurred to mothers living in a county for a given month) and stateBirths (calculated sum of births that occurred to mothers living in a state for a given month). These fields should provide enough information for you analyze trends across geographic locations both at monthly and yearly levels. You could also consider combining variables such as Year with State or Year with Month or any other grouping combinations depending on your analysis goal.

In addition, while all data were downloaded on April 5th 2017, it is worth noting that all sources used followed privacy guidelines as laid out by NCHC so individual births occurring after 2005 are not included due to geolocation concerns.
We hope you find this dataset useful and can benefit from its content! With proper understanding of what each field contains, we are confident you will gain valuable insights on birth rates across counties within the United States during this period

Research Ideas

• Establishing county-level trends in birth rates for the US over time.
• Analyzing the relationship between month of birth and health outcomes for US babies after they are born (e.g., infant mortality, neurological development, etc.).
• Comparing state/county-level differences in average numbers of twins born each year

Acknowledgements

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

License

See the dataset description for more information.

Columns

File: allBirthData.csv | Column name | Description | |:-----------------|:-----------------------------------------------------------------------------------------------------------------| | State | The numerical order of the state where the mother lives. (Integer) | | Month | The month in which the birth took place. (Integer) | | Year | The year of the birth. (Integer) | | countyBirths | The calculated sum of births that occurred to mothers living in that county for that particular month. (Integer) | | stateBirths | The aggregate number at the level of entire states for any given month-year combination. (Integer) | | County | The county where the mother lives, coded using FIPS County Code. (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 data.world's Admin.

This dataset contains counts of live births for California counties based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

US Monthly Birth Data

US Monthly Birth Data by State and County

By data.world's Admin [source]

About this dataset

The data was obtained from multiple sources. Data from 1985-2002 were downloaded from the National Bureau for Economic Research through the National Center for Health Statistics' National Vital Statistics System. Data from 2003-2015 were sourced using aggregators provided by CDC's WONDER tool, utilizing Year, Month, State, and County filters. It is worth noting that geolocation information for individual babies born after 2005 is not released due to privacy concerns; therefore, all data has been aggregated by month.

The spatial applicability of this dataset is limited to the United States at the county level. It covers a temporal range spanning January 1, 1985 - December 31, 2015. Each row in the dataset represents aggregated birth counts within a specific county for a particular month and year.

Additional notes highlight that this dataset expands on data presented in an essay called The Timing of Baby Making published by The Pudding website in May 2017. While only data ranging from1995-2015 were displayed in the essay itself, this dataset includes an extra ten years of birth data. Furthermore, any non-US residents have been excluded from this dataset.

The provided metadata gives a detailed breakdown of the columns in the dataset, including their descriptions and data types. The included variables allow researchers to analyze births at both individual county and state levels over time. Finally, the dataset is available under the MIT License for public use

How to use the dataset

Here is a guide on how to effectively use this dataset:

Step 1: Understanding the Columns

The dataset consists of several columns that provide specific information about each birth record. Let's understand what each column represents:

• State: The state (including District of Columbia) where the mother lives.
• County: The county where the mother lives, coded using the FIPS County Code.
• Month: The month in which the birth took place (1 = January, 2 = February, etc.).
• Year: The four-digit year of the birth.
• countyBirths: The calculated sum of births that occurred to mothers living in a county for a given month. If the sum was less than 9, it is listed as NA as per NCHS reporting guidelines.
• stateBirths: The calculated sum of births that occurred to mothers living in a state for a given month. It includes all birth counts, even those from counties with fewer than 9 births.

Step 2: Exploring Birth Trends by State and County

You can analyze birth trends by focusing on specific states or counties within specific time frames. Here's how you can do it:

• Filter by State or County:

  • Select rows based on your chosen state using the State column. Each number corresponds to a specific state (e.g., 01 = Alabama).
  • Further narrow down your analysis by selecting specific counties using their respective FIPS codes mentioned in the County column.

• Analyze Monthly Variation:

  • Calculate monthly total births within your desired location(s) by grouping data based on the Month column.
  • Compare the number of births between different months to identify any seasonal trends or patterns.

• Visualize Birth Trends:

  • Create line charts or bar plots to visualize how the number of births changes over time.
  • Plot a line or bar for each month across multiple years to identify any significant changes in birth rates.

Step 3: Comparison and Calculation

You can utilize this dataset to compare birth rates between states, counties, and regions. Here are a few techniques you can try:

• State vs. County Comparison:
  • Calculate the total births within each state by aggregating

Research Ideas

• Analyzing birth trends: This dataset can be used to analyze and understand the trends in birth rates across different states and counties over the period of 1985 to 2015. Researchers can study factors that may influence these trends, such as socioeconomic factors, healthcare access, or cultural changes.
• Identifying seasonal variations: The dataset includes information on the month of birth for each entry. This data can be utilized to identify any seasonal variations in births across different locations in the US. Understanding these variations can help in planning resources and healthcare services accordingly.
• Studying geographical patterns: By analyzing the county-level data, researchers can explore geographical patterns of childbirth throughout the United States. They can identify regions with high or low birth rates and...

This dataset contains counts of live births for California as a whole based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

Number and percentage of live births, by month of birth, 1991 to most recent year.

The world population has grown rapidly, particularly over the past century: in 1900, there were fewer than 2 billion people on the planet. The world population is around 8045311488 in 2023.

Two metrics determine the change in the world population: the number of babies born and the number of people dying. How many babies are born each year?

There were 133.99 million births in 2022, compared to 92.08 million births in 1950

Birth Statistics (i) Number of Known Births for Different Sexes and Crude Birth Rate for the Period from 1981 to 2024 (ii) Percentage Distribution of Live Births by Birth Weight for the Period from 2012 to 2023

Collective data of Japan's birth-related statistics from 1899 to 2022. Some data are missing between the years 1944 and 1946 due to records lost during World War II.

For use case and analysis reference, please take a look at this notebook Japan Birth Demographics Analysis

Feature Descriptions

• year: The year.
• birth_total: The total number of births.
• birth_male: The total number of male births.
• birth_female: The total number of female births.
• birth_rate: The birth rate. Equation is birth_total / population_total * 1,000
• birth_gender_ratio: The birth gender ratio. Equation is birth_male / birth_female * 1,000
• total_fertility_rate: The average number of children that are born to a woman over her lifetime.
• population_total: The total population.
• population_male: The total male population.
• population_female: The total female population.
• infant_death_total: The total infant deaths.
• infant_death_male: The total male infant deaths.
• infant_death_female: The total female infant deaths.
• infant_death_unknown_gender: The total unknown gender infant deaths.
• infant_death_rate: The infant death rate. Equation is infant_death_total / birth_total * 1,000
• infant_death_gender_ratio: The infant death gender ratio. Equation is infant_death_male / infant_death_female * 1,000
• infant_deaths_in_total_deaths: The infant death ratio among other deaths.
• stillbirth_total: The total number of stillbirths (dead born).
• stillbirth_male: The total number of male stillbirths.
• stillbirth_female: The total number of female stillbirths.
• stillbirth_unknown_gender: The total number of unknown gender stillbirths.
• stillbirth_rate: The stillbirth rate. Equation is stillbirth_total / (birth_total + stillbirth_total) * 1,000
• stillbirth_gender_ratio: The stillbirth gender ratio. Equation is stillbirth_male / stillbirth_female * 1,000
• firstborn: The number of firstborns.
• secondborn: The number of secondborns.
• thirdborn: The number of thirdborns.
• forthborn: The number of forthborns.
• fifthborn_and_above: The number of fifthborns and above.
• weeks_under_28: The number of births occurred under week 28. Early terms.
• weeks_28-31: The number of births occurred between weeks 28 and 31. Early terms.
• weeks_32-36: The number of births occurred between weeks 32 and 36. Early terms.
• weeks_37-41: The number of births occurred between weeks 37 and 41. Full terms.
• weeks_over_42: The number of births occurred over week 42. Late terms.
• mother_age_avg: The mother's average age.
• mother_age_firstborn: The mother's average age of the firstborn.
• mother_age_secondborn: The mother's average age of the secondborn.
• mother_age_thirdborn: The mother's average age of the thirdborn.
• mother_age_under_19: The number of births by mothers under age 19.
• mother_age_20-24: The number of births by mothers between age 20 and 24.
• mother_age_25-29: The number of births by mothers between age 25 and 29.
• mother_age_30-34: The number of births by mothers between age 30 and 34.
• mother_age_35-39: The number of births by mothers between age 35 and 39.
• mother_age_40-44: The number of births by mothers between age 40 and 44.
• mother_age_over_45: The number of births by mothers over 45.
• father_age_avg: The father's average age.
• father_age_firstborn: The father's average age of the firstborn.
• father_age_secondborn: The father's average age of the secondborn.
• father_age_thirdborn: The father's average age of the thirdborn.
• legitimate_child: The Number of births under married parents.
• illegitimate_child: The number of births under non-married parents.

Acknowledgement

E-Stat Demographic Survey

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

This dataset is about countries per year in Trinidad and Tobago. It has 64 rows. It features 4 columns: country, birth rate, and individuals using the Internet.

This dataset is about countries per year in St. Kitts and Nevis. It has 64 rows. It features 4 columns: country, birth rate, and individuals using the Internet.

Annual UK and constituent country figures for births, deaths, marriages, divorces, civil partnerships and civil partnership dissolutions.

This dataset includes crude birth rates and general fertility rates in the United States since 1909. The number of states in the reporting area differ historically. In 1915 (when the birth registration area was established), 10 states and the District of Columbia reported births; by 1933, 48 states and the District of Columbia were reporting births, with the last two states, Alaska and Hawaii, added to the registration area in 1959 and 1960, when these regions gained statehood. Reporting area information is detailed in references 1 and 2 below. Trend lines for 1909–1958 are based on live births adjusted for under-registration; beginning with 1959, trend lines are based on registered live births. 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 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. 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. 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. 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. 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. 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.

Context

There's a story behind every dataset and here's your opportunity to share yours.

Content

This Data consists of some world statistics published by the World Bank since 1961

Variables:

1) Agriculture and Rural development - 42 indicators published on this website. https://data.worldbank.org/topic/agriculture-and-rural-development

2) Access to electricity (% of the population) - Access to electricity is the percentage of the population with access to electricity. Electrification data are collected from industry, national surveys, and international sources.

3) CPIA gender equality rating (1=low to 6=high) - Gender equality assesses the extent to which the country has installed institutions and programs to enforce laws and policies that promote equal access for men and women in education, health, the economy, and protection under law.

4) Mineral rents (% of GDP) - Mineral rents are the difference between the value of production for a stock of minerals at world prices and their total costs of production. Minerals included in the calculation are tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.

5) GDP per capita (current US$) - GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars.

6) Literacy rate, adult total (% of people ages 15 and above)- Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.

7) Net migration - Net migration is the net total of migrants during the period, that is, the total number of immigrants less the annual number of emigrants, including both citizens and noncitizens. Data are five-year estimates.

8) Birth rate, crude (per 1,000 people) - Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.

9) Death rate, crude (per 1,000 people) - Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.

10) Mortality rate, infant (per 1,000 live births) - Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.

11) Population, total - Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.

Acknowledgements

These datasets are publicly available for anyone to use under the following terms provided by the Dataset Source https://www.worldbank.org/en/about/legal/terms-of-use-for-datasets

Banner photo by https://population.un.org/wpp/Maps/

Inspiration

Subsaharan Africa and east Asia record high population total, actually Subsaharan Africa population bypassed Europe and central Asia population by 2010, has this been influenced by crop and food production, large arable land, high crude birth rates(influx), low mortality rates(exits from the population) or Net migration.

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2023-24, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2024. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019, the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fifth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with a breakdown for the mother's smoking status at the booking appointment by age group. It also provides counts of live born term babies with breakdowns for the general condition of newborns (via Apgar scores), skin-to-skin contact and baby's first feed type - all immediately after birth. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. For the first time information on 'Smoking at Time of Delivery' has been presented using annual data from the MSDS. This includes national data broken down by maternal age, ethnicity and deprivation. From 2025/2026, MSDS will become the official source of 'Smoking at Time of Delivery' information and will replace the historic 'Smoking at Time of Delivery' data which is to become retired. We are currently undergoing dual collection and reporting on a quarterly basis for 2024/25 to help users compare information from the two sources. We are working with data submitters to help reconcile any discrepancies at a local level before any close down activities begin. A link to the dual reporting in the SATOD publication series can be found in the links below. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

This dataset is about countries per year in Turkey. It has 64 rows. It features 4 columns: country, birth rate, and individuals using the Internet.

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Number and percentage of live births, by age group of mother, 1991 to most recent year.

Number of babies born in the province of Alberta, by residency status, age of mother, and type of birth (single birth, twins, triplets and quadruplets).

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.