Data

Share of women who have undergone female genital mutilation

What you should know about this indicator

How is this data described by its producer?

Percentage of women aged 15–49 who have gone through partial or total removal of the female external genitalia or other injury to the female genital organs for cultural or other non-therapeutic reasons.

Statistical concept and methodology:

Methodology: The indicator is calculated by the number of women ages 15-49 who have undergone FGM divided by the total number of women ages 15-49 in the population multiplied by 100. The primary sources for this indicator are the Multiple Indicator Cluster Surveys (MICS) and the Demographic and Health Surveys (DHS). The majority of the data are compiled by UNICEF, which coordinates with countries to gather the information. Statistical concept(s): Female genital mutilation (FGM) encompasses all practices that involve the partial or total removal of the external female genitalia, or other injury to the female genital organs, for non-medical reasons. Typically, this procedure is carried out on minors.

Development relevance:

FGM is a harmful practice involving the cutting or removal of the external female genitalia. It does not have any health benefits but rather causes serious risks to women’s physical and psychological health, including chronic infections, pain, menstrual problems, and complications during childbirth. FGM has been practiced mainly in the western, eastern, and north-eastern regions of Africa and some countries in the Middle East and Asia. It is reported that FGM is also found in western countries such as United Kingdom, United States, and Canada.

FGM is a violation of girls’ and women’s human rights, as well as a violation of women’s rights to health, security, and physical integrity. However, its eradication is now becoming a global concern and has even been set as one the SDGs, specifically as SDG target 5.3.

Limitations and exceptions:

The data on FGM should be interpreted with caution for several reasons. Women may be reluctant to disclose undergoing FGM due to its sensitivity or illegal status, and some may be unaware of the procedure, especially if performed at an early age. The data is retrospective, not reflecting recent changes, with reports from girls aged 15 to 19 years referring to events 14 to 18 years earlier. Surveys like MICS and DHS only include FGM questions in countries where the practice is prevalent, meaning FGM may still exist in countries without data, including high-income countries with migrant populations and certain low- and middle-income countries. National-level estimates may be misleading as FGM is often practiced by specific ethnic groups in certain locations, thus not accurately representing the prevalence. Reference: A Generation to Protect: Monitoring violence exploitation and abuse of children within the SDG framework (UNICEF 2020). https://data.unicef.org/wp-content/uploads/2020/06/A-Generation-to-Protect-publication-English_2020.pdf

Other notes:

This is the Sustainable Development Goal indicator 5.3.2[https://unstats.un.org/sdgs/metadata/].

Source
UNICEF, Demographic and Health Surveys (DHS), and Multiple Indicator Cluster Surveys (MICS), via World Bank (2026)processed by Our World in Data
Last updated
February 27, 2026
Next expected update
February 2027
Date range
1990–2023
Unit
%

Sources and processing

UNICEF, Demographic and Health Surveys (DHS), and Multiple Indicator Cluster Surveys (MICS), 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
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.
UNICEF DATA, UN Children's Fund (UNICEF), uri: https://sdmx.data.unicef.org/overview.html, note: Indicator code from the original source: PT_F_15-49_FGM; 	Indicator name from the original source: Percentage of girls and women (aged 15-49 years) who have undergone female genital mutilation (FGM), type: API, date accessed: 2023-12-07;
Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS) and other surverys, DHS Program (ICF), uri: https://sdmx.data.unicef.org/overview.html, note: Indicator code from the original source: PT_F_15-49_FGM; 	Indicator name from the original source: Percentage of girls and women (aged 15-49 years) who have undergone female genital mutilation (FGM), publisher: The DHS Program (ICF), type: API, date accessed: 2023-12-07;
DHS API, DHS Program (ICF), uri: https://api.dhsprogram.com/#/index.html, note: Indicator code from the original source: PT_F_15-49_FGM; 	Indicator name from the original source: Percentage of girls and women (aged 15-49 years) who have undergone female genital mutilation (FGM), date accessed: 2023-12-07. Indicator SH.STA.FGMS.ZS (https://data.worldbank.org/indicator/SH.STA.FGMS.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
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.
UNICEF DATA, UN Children's Fund (UNICEF), uri: https://sdmx.data.unicef.org/overview.html, note: Indicator code from the original source: PT_F_15-49_FGM; 	Indicator name from the original source: Percentage of girls and women (aged 15-49 years) who have undergone female genital mutilation (FGM), type: API, date accessed: 2023-12-07;
Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS) and other surverys, DHS Program (ICF), uri: https://sdmx.data.unicef.org/overview.html, note: Indicator code from the original source: PT_F_15-49_FGM; 	Indicator name from the original source: Percentage of girls and women (aged 15-49 years) who have undergone female genital mutilation (FGM), publisher: The DHS Program (ICF), type: API, date accessed: 2023-12-07;
DHS API, DHS Program (ICF), uri: https://api.dhsprogram.com/#/index.html, note: Indicator code from the original source: PT_F_15-49_FGM; 	Indicator name from the original source: Percentage of girls and women (aged 15-49 years) who have undergone female genital mutilation (FGM), date accessed: 2023-12-07. Indicator SH.STA.FGMS.ZS (https://data.worldbank.org/indicator/SH.STA.FGMS.ZS). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.

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.

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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 who have undergone female genital mutilation”. Our World in Data (2026). Data adapted from UNICEF, Demographic and Health Surveys (DHS), and Multiple Indicator Cluster Surveys (MICS), via World Bank. Retrieved from https://archive.ourworldindata.org/20260512-185716/grapher/female-genital-mutilation-prevalence.html [online resource] (archived on May 12, 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:

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

Full citation

UNICEF, Demographic and Health Surveys (DHS), and Multiple Indicator Cluster Surveys (MICS), via World Bank (2026) – processed by Our World in Data. “Share of women who have undergone female genital mutilation” [dataset]. UNICEF, Demographic and Health Surveys (DHS), and Multiple Indicator Cluster Surveys (MICS), via World Bank, “World Development Indicators 125” [original data]. Retrieved May 17, 2026 from https://archive.ourworldindata.org/20260512-185716/grapher/female-genital-mutilation-prevalence.html (archived on May 12, 2026).

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.

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/female-genital-mutilation-prevalence.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/female-genital-mutilation-prevalence.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/female-genital-mutilation-prevalence.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/female-genital-mutilation-prevalence.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/female-genital-mutilation-prevalence.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/female-genital-mutilation-prevalence.csv?v=1&csvType=full&useColumnShortNames=false")

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