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Data

Birth rate

total – HMD, UN WPP
See all data and research on:
Fertility Rate

What you should know about this indicator

This indicator has been constructed by combining data from two sources:

  • Before 1950: Historical estimates by Human Mortality Database (2025).
  • 1950-2023: Population records by the UN World Population Prospects (2024 revision).
Birth rate
total – HMD, UN WPP
The total number of births per 1,000 people in a given year.
Source
Human Mortality Database (2025); UN, World Population Prospects (2024) – processed by Our World in Data
Last updated
October 22, 2025
Next expected update
October 2026
Date range
1751–2023
Unit
births per 1,000 people

Sources and processing

This data is based on the following sources

Human Mortality Database

The Human Mortality Database (HMD) is a research resource that provides detailed mortality and population data for national populations with high-quality vital statistics. It includes original calculations of death rates and life tables, as well as the underlying data — such as birth counts, death counts, and census-based population estimates — used to produce these metrics.

Its scope is limited to countries with virtually complete death registration and census coverage, mostly wealthy and industrialized nations. The database’s core mission is to document the historical rise in human longevity and support research into its causes and implications. HMD follows a rigorous, uniform methodology focused on transparency, reproducibility, and comparability, while acknowledging limitations such as age misreporting and data coverage issues.

Each country’s dataset is curated and quality-checked by dedicated researchers, ensuring reliability for demographic and public health analysis.

Retrieved on
October 22, 2025
Retrieved from
https://www.mortality.org/Data/ZippedDataFiles
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
HMD. Human Mortality Database. Max Planck Institute for Demographic Research (Germany), University of California, Berkeley (USA), and French Institute for Demographic Studies (France). Available at www.mortality.org.
See also the methods protocol:
Wilmoth, J. R., Andreev, K., Jdanov, D., Glei, D. A., Riffe, T., Boe, C., Bubenheim, M., Philipov, D., Shkolnikov, V., Vachon, P., Winant, C., & Barbieri, M. (2021). Methods protocol for the human mortality database (v6). Available online (needs log in to mortality.org).

The Human Mortality Database (HMD) is a research resource that provides detailed mortality and population data for national populations with high-quality vital statistics. It includes original calculations of death rates and life tables, as well as the underlying data — such as birth counts, death counts, and census-based population estimates — used to produce these metrics.

Its scope is limited to countries with virtually complete death registration and census coverage, mostly wealthy and industrialized nations. The database’s core mission is to document the historical rise in human longevity and support research into its causes and implications. HMD follows a rigorous, uniform methodology focused on transparency, reproducibility, and comparability, while acknowledging limitations such as age misreporting and data coverage issues.

Each country’s dataset is curated and quality-checked by dedicated researchers, ensuring reliability for demographic and public health analysis.

Retrieved on
October 22, 2025
Retrieved from
https://www.mortality.org/Data/ZippedDataFiles
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
HMD. Human Mortality Database. Max Planck Institute for Demographic Research (Germany), University of California, Berkeley (USA), and French Institute for Demographic Studies (France). Available at www.mortality.org.
See also the methods protocol:
Wilmoth, J. R., Andreev, K., Jdanov, D., Glei, D. A., Riffe, T., Boe, C., Bubenheim, M., Philipov, D., Shkolnikov, V., Vachon, P., Winant, C., & Barbieri, M. (2021). Methods protocol for the human mortality database (v6). Available online (needs log in to mortality.org).

United Nations – World Population Prospects

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

Retrieved on
July 11, 2024
Retrieved from
https://population.un.org/wpp/downloads/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

World Population Prospects 2024 is the 28th edition of the official estimates and projections of the global population that have been published by the United Nations since 1951. The estimates are based on all available sources of data on population size and levels of fertility, mortality and international migration for 237 countries or areas. If you have questions about this dataset, please refer to their FAQ. You can also explore data sources for each country or visit their main page for more details.

Retrieved on
July 11, 2024
Retrieved from
https://population.un.org/wpp/downloads/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
United Nations, Department of Economic and Social Affairs, Population Division (2024). World Population Prospects 2024, Online Edition.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator

The birth data is constructed by combining data from multiple sources:

  • Before 1950: Historical estimates by Human Mortality Database (2025).

  • 1950-2023: Population records by the UN World Population Prospects (2024 revision).

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Birth rate”, part of the following publication: Saloni Dattani, Lucas Rodés-Guirao, and Max Roser (2025) - “Fertility Rate”. Data adapted from Human Mortality Database, United Nations. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/long-run-birth-rate.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Human Mortality Database (2025); UN, World Population Prospects (2024) – processed by Our World in Data

Full citation

Human Mortality Database (2025); UN, World Population Prospects (2024) – processed by Our World in Data. “Birth rate – HMD, UN WPP – total” [dataset]. Human Mortality Database, “Human Mortality Database”; United Nations, “World Population Prospects” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/long-run-birth-rate.html (archived on March 4, 2026).

Download

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/long-run-birth-rate.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/long-run-birth-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/long-run-birth-rate.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/long-run-birth-rate.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/long-run-birth-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/long-run-birth-rate.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/long-run-birth-rate.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/long-run-birth-rate.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear