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Data

Registered vehicles per 1,000 people

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Global Health

What you should know about this indicator

Registered vehicles per 1,000 people are calculated by Our World in Data based on vehicle registration from the World Health Organization's Global Health Observatory, and population estimates from the United Nations World Population Prospects.

How is this data described by its producer?

The total number of registered vehicles (i.e. vehicles reported to a government agency and given some form of registration) in each country. Data were collected from a number of different sectors and stakeholders in each country and were submitted to the World Health Organization after consensus meetings, facilitated by national data coordinators. All legislative documents were analysed by lawyers at WHO headquarters who extracted the relevant information. The legal analysis was then shared with National Data Coordinators and a validation process resolved any data conflicts through discussion and submission of new legal documents.

Registered vehicles per 1,000 people
Total number of registered vehicles (i.e., vehicles reported to a government agency and given some form of registration) per 1,000 people in each country.
Source
World Health Organization - Global Health Observatory (2025); Population based on various sources (2024) – with minor processing by Our World in Data
Last updated
May 19, 2025
Next expected update
May 2026
Date range
2007–2017
Unit
vehicles per 1,000 people

Sources and processing

This data is based on the following sources

World Health Organization – Global Health Observatory

The GHO data repository is WHO's gateway to health-related statistics for its 194 Member States. It provides access to over 1000 indicators on priority health topics including mortality and burden of diseases, the Millennium Development Goals (child nutrition, child health, maternal and reproductive health, immunization, HIV/AIDS, tuberculosis, malaria, neglected diseases, water and sanitation), non communicable diseases and risk factors, epidemic-prone diseases, health systems, environmental health, violence and injuries, equity among others.

Retrieved on
May 19, 2025
Retrieved from
https://www.who.int/data/gho
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.
World Health Organization. 2025. Global Health Observatory data repository. http://www.who.int/gho/en/.

The GHO data repository is WHO's gateway to health-related statistics for its 194 Member States. It provides access to over 1000 indicators on priority health topics including mortality and burden of diseases, the Millennium Development Goals (child nutrition, child health, maternal and reproductive health, immunization, HIV/AIDS, tuberculosis, malaria, neglected diseases, water and sanitation), non communicable diseases and risk factors, epidemic-prone diseases, health systems, environmental health, violence and injuries, equity among others.

Retrieved on
May 19, 2025
Retrieved from
https://www.who.int/data/gho
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.
World Health Organization. 2025. Global Health Observatory data repository. http://www.who.int/gho/en/.

Various sources – Population

Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on various sources.

You can find more information on these sources and how our time series is constructed on this page: https://ourworldindata.org/population-sources

Retrieved on
March 31, 2026
Retrieved from
https://ourworldindata.org/population-sources
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.
The long-run data on population is based on various sources, described on this page: https://ourworldindata.org/population-sources

Our World in Data builds and maintains a long-run dataset on population by country, region, and for the world, based on various sources.

You can find more information on these sources and how our time series is constructed on this page: https://ourworldindata.org/population-sources

Retrieved on
March 31, 2026
Retrieved from
https://ourworldindata.org/population-sources
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.
The long-run data on population is based on various sources, described on this page: https://ourworldindata.org/population-sources

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

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: Registered vehicles per 1,000 people”, part of the following publication: Esteban Ortiz-Ospina and Max Roser (2016) - “Global Health”. Data adapted from World Health Organization, Various sources. Retrieved from https://archive.ourworldindata.org/20260402-164039/grapher/registered-vehicles-per-1000-people.html [online resource] (archived on April 2, 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:

World Health Organization - Global Health Observatory (2025); Population based on various sources (2024) – with minor processing by Our World in Data

Full citation

World Health Organization - Global Health Observatory (2025); Population based on various sources (2024) – with minor processing by Our World in Data. “Registered vehicles per 1,000 people” [dataset]. World Health Organization, “Global Health Observatory”; Various sources, “Population” [original data]. Retrieved April 6, 2026 from https://archive.ourworldindata.org/20260402-164039/grapher/registered-vehicles-per-1000-people.html (archived on April 2, 2026).

Download

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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/registered-vehicles-per-1000-people.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/registered-vehicles-per-1000-people.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/registered-vehicles-per-1000-people.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/registered-vehicles-per-1000-people.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/registered-vehicles-per-1000-people.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/registered-vehicles-per-1000-people.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/registered-vehicles-per-1000-people.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/registered-vehicles-per-1000-people.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear