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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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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
YearwithStateorYearwithMonthor 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
- 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
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
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) |
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.
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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
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
- 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...
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The average for 2022 based on 196 countries was 18.19 births per 1000 people. The highest value was in the Central African Republic: 45.42 births per 1000 people and the lowest value was in Hong Kong: 4.4 births per 1000 people. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.
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The graph illustrates the number of babies born in the United States from 1995 to 2025. The x-axis represents the years, labeled from '95 to '25, while the y-axis shows the annual number of births. Over this 30-year period, birth numbers peaked at 4,316,233 in 2007 and reached a low of 3,596,017 in 2023. The data reveals relatively stable birth rates from 1995 to 2010, with slight fluctuations, followed by a gradual decline starting around 2017. The information is presented in a line graph format, effectively highlighting the long-term downward trend in U.S. birth numbers over the specified timeframe.
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TwitterNumber and percentage of live births, by month of birth, 1991 to most recent year.
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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
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Italy IT: Fertility Rate: Total: Births per Woman data was reported at 1.350 Ratio in 2016. This stayed constant from the previous number of 1.350 Ratio for 2015. Italy IT: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 1.440 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 2.650 Ratio in 1964 and a record low of 1.190 Ratio in 1995. Italy IT: 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 Italy – Table IT.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.
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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.
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TwitterBetween 1939 and 1950, the Soviet Union's fertility rate underwent the most drastic change of all the major Allied Powers; falling from 4.9 births per woman in 1939 to just 1.7 births in 1943. In Russia alone, this decline was even greater, falling from 4.9 to 1.3 births in the same time period. After the war's conclusion in 1945, there was an observable increase in fertility in all the given countries, and this marked beginning of the global baby boom of the mid-twentieth century.
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Graph and download economic data for Crude Birth Rate for the United States (SPDYNCBRTINUSA) from 1960 to 2023 about birth, crude, rate, and USA.
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Ukraine UA: Fertility Rate: Total: Births per Woman data was reported at 1.466 Ratio in 2016. This records a decrease from the previous number of 1.506 Ratio for 2015. Ukraine UA: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 1.930 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 2.240 Ratio in 1960 and a record low of 1.085 Ratio in 2001. Ukraine UA: 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 Ukraine – Table UA.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.
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Greenland GL: Fertility Rate: Total: Births per Woman data was reported at 2.000 Ratio in 2016. This records a decrease from the previous number of 2.010 Ratio for 2015. Greenland GL: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 2.323 Ratio from Dec 1975 (Median) to 2016, with 42 observations. The data reached an all-time high of 2.690 Ratio in 1997 and a record low of 2.000 Ratio in 2016. Greenland GL: 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 Greenland – Table GL.World Bank.WDI: 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.
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TwitterDefinition:The crude birth rate is the annual number of live births per 1,000 population.Method of measurementThe crude birth rate is generally computed as a ratio. The numerator is the number of live births observed in a population during a reference period and the denominator is the number of person-years lived by the population during the same period. It is expressed as births per 1,000 population. Method of estimation:Data are taken from the most recent UN Population Division's "World Population Prospects". Other possible data sources:Population censusHousehold surveysPreferred data sources:Civil registration with complete coverageExpected frequency of data dissemination:Biennial (Two years)Data collected March 5, 2021 from: https://www.who.int/data/maternal-newborn-child-adolescent-ageing/indicator-explorer-new/mca/crude-birth-rate-(births-per-1000-population)
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TwitterThis dataset presents the estimated percentage of babies born alive before 37 weeks of pregnancy are completed, by country. Preterm birth is a leading cause of neonatal morbidity and mortality. Understanding national rates supports efforts to improve antenatal care, timely interventions, and newborn outcomes. These estimates are adapted from Liang et al. (2024), based on the Global Burden of Disease Study 2021, and provide a globally comparable measure of preterm birth burden.Data Source:The Lancet: https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(24)00419-X/fulltext Data Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hub the following codes are also possible values: not reported does not apply don’t know This is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.
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TwitterWhile 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.
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Hungary HU: Fertility Rate: Total: Births per Woman data was reported at 1.450 Ratio in 2016. This stayed constant from the previous number of 1.450 Ratio for 2015. Hungary HU: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 1.800 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 2.350 Ratio in 1975 and a record low of 1.230 Ratio in 2011. Hungary HU: 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 Hungary – Table HU.World Bank.WDI: 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.
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Description
This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.
Key Features
Country: Name of the country.
Density (P/Km2): Population density measured in persons per square kilometer.
Abbreviation: Abbreviation or code representing the country.
Agricultural Land (%): Percentage of land area used for agricultural purposes.
Land Area (Km2): Total land area of the country in square kilometers.
Armed Forces Size: Size of the armed forces in the country.
Birth Rate: Number of births per 1,000 population per year.
Calling Code: International calling code for the country.
Capital/Major City: Name of the capital or major city.
CO2 Emissions: Carbon dioxide emissions in tons.
CPI: Consumer Price Index, a measure of inflation and purchasing power.
CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
Currency_Code: Currency code used in the country.
Fertility Rate: Average number of children born to a woman during her lifetime.
Forested Area (%): Percentage of land area covered by forests.
Gasoline_Price: Price of gasoline per liter in local currency.
GDP: Gross Domestic Product, the total value of goods and services produced in the country.
Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
Largest City: Name of the country's largest city.
Life Expectancy: Average number of years a newborn is expected to live.
Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
Minimum Wage: Minimum wage level in local currency.
Official Language: Official language(s) spoken in the country.
Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
Physicians per Thousand: Number of physicians per thousand people.
Population: Total population of the country.
Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
Tax Revenue (%): Tax revenue as a percentage of GDP.
Total Tax Rate: Overall tax burden as a percentage of commercial profits.
Unemployment Rate: Percentage of the labor force that is unemployed.
Urban Population: Percentage of the population living in urban areas.
Latitude: Latitude coordinate of the country's location.
Longitude: Longitude coordinate of the country's location.
Potential Use Cases
Analyze population density and land area to study spatial distribution patterns.
Investigate the relationship between agricultural land and food security.
Examine carbon dioxide emissions and their impact on climate change.
Explore correlations between economic indicators such as GDP and various socio-economic factors.
Investigate educational enrollment rates and their implications for human capital development.
Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
Study labor market dynamics through indicators such as labor force participation and unemployment rates.
Investigate the role of taxation and its impact on economic development.
Explore urbanization trends and their social and environmental consequences.
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Romania RO: Fertility Rate: Total: Births per Woman data was reported at 1.580 Ratio in 2016. This stayed constant from the previous number of 1.580 Ratio for 2015. Romania RO: Fertility Rate: Total: Births per Woman data is updated yearly, averaging 1.910 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 3.660 Ratio in 1967 and a record low of 1.270 Ratio in 2002. Romania RO: 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 Romania – Table RO.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.
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Graph and download economic data for Fertility Rate, Total for the United States (SPDYNTFRTINUSA) from 1960 to 2023 about fertility, rate, and USA.
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This dataset contains US baby names from the Social Security Administration dating back to 1879. With over 150 years of data, this is one of the most comprehensive datasets on baby names in the US. The data includes the name, year of birth, sex, and number of babies with that name for each year. This dataset is a great resource for anyone interested in studying baby naming trends over time
This dataset is a compilation of over 140 years of data from the Social Security Administration. It includes data on baby names, year of birth, and sex. There are also columns for the number of babies with that name born in that year.
This dataset can be used to track changes in baby naming trends over time, or to study how popular names have changed in popularity. It can also be used to study how naming trends differ between sexes, or between different years
This dataset could be used for a number of things, including: 1. Determining baby name trends over time 2. Finding out what the most popular baby names are in the US 3. Analyzing how baby name popularity has changed over the years
If you use this dataset in your research, please credit @nickgott, @rflprr and the Social Security Administration via Data.gov
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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!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
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
YearwithStateorYearwithMonthor 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
- 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
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
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) |
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.