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Data

Share of women using contraceptives

What you should know about this indicator

How is this data described by its producer?

Contraceptive prevalence, any method is the percentage of married women ages 15-49 who are practicing, or whose sexual partners are practicing, any method of contraception (modern or traditional). Modern methods of contraception include female and male sterilization, oral hormonal pills, the intra-uterine device (IUD), the male condom, injectables, the implant (including Norplant), vaginal barrier methods, the female condom and emergency contraception. Traditional methods of contraception include rhythm (e.g., fertility awareness based methods, periodic abstinence), withdrawal and other traditional methods.

Limitations and exceptions:

While the data availability on contraceptive use has increased, in many countries the contraceptive use data are available only for married women.

The time frame used to assess contraceptive prevalence may vary. In many surveys, it is left to the respondent to determine what is meant by “currently using” a method of contraception.

Statistical concept and methodology:

Contraceptive prevalence rates are obtained mainly from nationally representative household surveys, including: Demographic and Health Surveys; Multiple Indicator Cluster Surveys; Contraceptive Prevalence Surveys; Gender and Generations Survey; Reproductive Health Surveys; and World Fertility Surveys. Additional information was provided by other international survey programs and national surveys.

Married women refer to women who are married (defined in relation to the marriage laws or customs of a country) and to women in a union, which refers to women living with their partner in the same household (also referred to as cohabiting unions, consensual unions, unmarried unions, or “living together”).

Source
Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and UN Population Division, via World Bank (2026) – processed by Our World in Data
Last updated
February 27, 2026
Next expected update
February 2027
Date range
1961–2024
Unit
% of women ages 15-49

Related research and writing

The global decline of the fertility rate

Max Roser

Explore charts that include this data

Sources and processing

This data is based on the following sources

Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and UN Population Division, via World Bank – World Development Indicators

The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades.WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability.The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization.WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally.Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.

Retrieved on
February 27, 2026
Retrieved from
https://data.worldbank.org/indicator/SP.DYN.CONU.ZS
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.
Household surveys, United Nations (UN), note: Household surveys, including Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Largely compiled by United Nations Population Division., publisher: UN Population Division. Indicator SP.DYN.CONU.ZS (https://data.worldbank.org/indicator/SP.DYN.CONU.ZS). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.

The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades.WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability.The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization.WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally.Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.

Retrieved on
February 27, 2026
Retrieved from
https://data.worldbank.org/indicator/SP.DYN.CONU.ZS
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.
Household surveys, United Nations (UN), note: Household surveys, including Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Largely compiled by United Nations Population Division., publisher: UN Population Division. Indicator SP.DYN.CONU.ZS (https://data.worldbank.org/indicator/SP.DYN.CONU.ZS). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.

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

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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: Share of women using contraceptives”. Our World in Data (2026). Data adapted from Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and UN Population Division, via World Bank. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/contraceptive-prevalence-any-methods-of-women-ages-15-49.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:

Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and UN Population Division, via World Bank (2026) – processed by Our World in Data

Full citation

Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and UN Population Division, via World Bank (2026) – processed by Our World in Data. “Share of women using contraceptives” [dataset]. Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and UN Population Division, via World Bank, “World Development Indicators 125” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/contraceptive-prevalence-any-methods-of-women-ages-15-49.html (archived on March 4, 2026).

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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/contraceptive-prevalence-any-methods-of-women-ages-15-49.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/contraceptive-prevalence-any-methods-of-women-ages-15-49.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/contraceptive-prevalence-any-methods-of-women-ages-15-49.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/contraceptive-prevalence-any-methods-of-women-ages-15-49.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/contraceptive-prevalence-any-methods-of-women-ages-15-49.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/contraceptive-prevalence-any-methods-of-women-ages-15-49.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/contraceptive-prevalence-any-methods-of-women-ages-15-49.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/contraceptive-prevalence-any-methods-of-women-ages-15-49.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear