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Prevalence of mental disorders

by disorder, sex and age
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Mental Health
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Prevalence of mental disorders

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What you should know about this indicator

  • These estimates come from the Institute for Health Metrics and Evaluation's (IHME) Global Burden of Disease study. They are based on representative surveys, medical data and statistical modelling, and include people who have not been diagnosed.
  • Age-standardized figures adjust for differences in the age structure of populations, so they can be compared between countries and over time. Crude figures show the actual share of the population with the disorder.
Share of people with depression
IHME
Estimated age-standardized prevalence of individuals with depressive disorders, per 100 people.
Source
IHME, Global Burden of Disease (2025) – with major processing by Our World in Data
Last updated
February 7, 2026
Next expected update
February 2030
Date range
1990–2023
Unit
%

Related research and writing

How are mental illnesses defined?

Saloni Dattani

Sources and processing

This data is based on the following sources

IHME, Global Burden of Disease – Global Burden of Disease – Mental Health Prevalence

The Global Burden of Disease (GBD) study provides a comprehensive assessment of global health trends. This dataset contains the prevalence of mental health conditions for a range of age-groups across males and females.

Retrieved on
February 7, 2026
Retrieved from
https://vizhub.healthdata.org/gbd-results/
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.
"Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2023 (GBD 2023). Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2025. Available from https://vizhub.healthdata.org/gbd-results/."

The Global Burden of Disease (GBD) study provides a comprehensive assessment of global health trends. This dataset contains the prevalence of mental health conditions for a range of age-groups across males and females.

Retrieved on
February 7, 2026
Retrieved from
https://vizhub.healthdata.org/gbd-results/
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.
"Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2023 (GBD 2023). Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2025. Available from https://vizhub.healthdata.org/gbd-results/."

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: Share of people with depression”, part of the following publication: Saloni Dattani, Lucas Rodés-Guirao, Hannah Ritchie, and Max Roser (2023) - “Mental Health”. Data adapted from IHME, Global Burden of Disease. Retrieved from https://archive.ourworldindata.org/20261027-151940/grapher/prevalence-of-mental-disorders.html [online resource] (archived on October 27, 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:

IHME, Global Burden of Disease (2025) – with major processing by Our World in Data

Full citation

IHME, Global Burden of Disease (2025) – with major processing by Our World in Data. “Share of people with depression – IHME” [dataset]. IHME, Global Burden of Disease, “Global Burden of Disease – Mental Health Prevalence” [original data]. Retrieved October 27, 2026 from https://archive.ourworldindata.org/20261027-151940/grapher/prevalence-of-mental-disorders.html (archived on October 27, 2026).

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

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

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