Data

Number of countries with underlying data on the prevalence of mental illnesses

About this data

Source
IHME, Global Burden of Disease (2020)processed by Our World in Data
Last updated
November 26, 2024
Date range
2019–2019

Sources and processing

IHME, Global Burden of Disease – Global Burden of Disease Study

Dataset showing the number of countries with primary data on the prevalence of mental illnesses. These were found after a systematic review, grey literature search and expert consultation, to identify studies with data on the prevalence of each mental illness.

'The GBD inclusion criteria stipulated that: (1) the diagnostic criteria must be from 1980 onward; (2) "caseness" must be based on clinical threshold as established by the DSM, ICD, Chinese Classification of Mental Disorders (CCMD), or diagnosed by a clinician using established tools; (3) sufficient information must be provided on study method and sample characteristics to assess the quality of the study; and (4) study samples must be representative of the general population (i.e., case studies, veterans, or refugee samples were excluded). No limitation was set on the language of publication.'

Retrieved on
November 26, 2024
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.
Vos, T., Lim, S. S., Abbafati, C., Abbas, K. M., Abbasi, M., Abbasifard, M., Abbasi-Kangevari, M., Abbastabar, H., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., Abolhassani, H., Aboyans, V., Abrams, E. M., Abreu, L. G., Abrigo, M. R. M., Abu-Raddad, L. J., Abushouk, A. I., … Murray, C. J. L. (2020). Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1204–1222.

Dataset showing the number of countries with primary data on the prevalence of mental illnesses. These were found after a systematic review, grey literature search and expert consultation, to identify studies with data on the prevalence of each mental illness.

'The GBD inclusion criteria stipulated that: (1) the diagnostic criteria must be from 1980 onward; (2) "caseness" must be based on clinical threshold as established by the DSM, ICD, Chinese Classification of Mental Disorders (CCMD), or diagnosed by a clinician using established tools; (3) sufficient information must be provided on study method and sample characteristics to assess the quality of the study; and (4) study samples must be representative of the general population (i.e., case studies, veterans, or refugee samples were excluded). No limitation was set on the language of publication.'

Retrieved on
November 26, 2024
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.
Vos, T., Lim, S. S., Abbafati, C., Abbas, K. M., Abbasi, M., Abbasifard, M., Abbasi-Kangevari, M., Abbastabar, H., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., Abolhassani, H., Aboyans, V., Abrams, E. M., Abreu, L. G., Abrigo, M. R. M., Abu-Raddad, L. J., Abushouk, A. I., … Murray, C. J. L. (2020). Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1204–1222.

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

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: Number of countries with underlying data on the prevalence of mental illnesses”. Our World in Data (2026). Data adapted from IHME, Global Burden of Disease. Retrieved from https://archive.ourworldindata.org/20260512-000143/grapher/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.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:

IHME, Global Burden of Disease (2020) – processed by Our World in Data

Full citation

IHME, Global Burden of Disease (2020) – processed by Our World in Data. “Number of countries with underlying data on the prevalence of mental illnesses” [dataset]. IHME, Global Burden of Disease, “Global Burden of Disease Study GBD 2019” [original data]. Retrieved May 13, 2026 from https://archive.ourworldindata.org/20260512-000143/grapher/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.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/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.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/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.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/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.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/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/number-of-countries-with-primary-data-on-prevalence-of-mental-illnesses-in-the-global-burden-of-disease-study.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear