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Data

Coverage of underlying data on the prevalence of major depression

About this data

Source
Baxter et al. (2013) – processed by Our World in Data
Last updated
February 14, 2024
Date range
2008–2008
Unit
%

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Sources and processing

This data is based on the following sources

Baxter et al. – Global epidemiology of mental disorders: what are we missing?

This dataset shows the coverage of each country for which mental health data has been collected, by age and sex, between 1980 and 2008 using DSM or ICD diagnostic criteria. For example, if mental health data has been collected for men and women across all adult age groups from a country, then its coverage would be given as 100%. Mental health data was defined as any studies on disease epidemiology in the general population. For schizophrenia, bipolar disorder and eating disorder, this also included remission and mortality studies based on clinical samples with naturalistic follow-up, due to a lack of community studies on the topic. For studies with subnational data, coverage was considered as the population coverage of that subnational region, then the population of that subnational region relative to the country. These were calculated for GBD world regions.

Retrieved on
February 14, 2024
Retrieved from
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0065514
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.
Baxter, A. J., Patton, G., Scott, K. M., Degenhardt, L., & Whiteford, H. A. (2013). Global Epidemiology of Mental Disorders: What Are We Missing? PLoS ONE, 8(6), e65514.

This dataset shows the coverage of each country for which mental health data has been collected, by age and sex, between 1980 and 2008 using DSM or ICD diagnostic criteria. For example, if mental health data has been collected for men and women across all adult age groups from a country, then its coverage would be given as 100%. Mental health data was defined as any studies on disease epidemiology in the general population. For schizophrenia, bipolar disorder and eating disorder, this also included remission and mortality studies based on clinical samples with naturalistic follow-up, due to a lack of community studies on the topic. For studies with subnational data, coverage was considered as the population coverage of that subnational region, then the population of that subnational region relative to the country. These were calculated for GBD world regions.

Retrieved on
February 14, 2024
Retrieved from
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0065514
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.
Baxter, A. J., Patton, G., Scott, K. M., Degenhardt, L., & Whiteford, H. A. (2013). Global Epidemiology of Mental Disorders: What Are We Missing? PLoS ONE, 8(6), e65514.

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: Coverage of underlying data on the prevalence of major depression”. Our World in Data (2026). Data adapted from Baxter et al.. Retrieved from http://staging-site-master:8789/20260512-000143/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.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:

Baxter et al. (2013) – processed by Our World in Data

Full citation

Baxter et al. (2013) – processed by Our World in Data. “Coverage of underlying data on the prevalence of major depression” [dataset]. Baxter et al., “Global epidemiology of mental disorders: what are we missing?” [original data]. Retrieved May 15, 2026 from http://staging-site-master:8789/20260512-000143/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.html (archived on May 12, 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://data-bump-dependabot-deps.owid.pages.dev/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://data-bump-dependabot-deps.owid.pages.dev/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.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://data-bump-dependabot-deps.owid.pages.dev/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://data-bump-dependabot-deps.owid.pages.dev/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.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://data-bump-dependabot-deps.owid.pages.dev/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://data-bump-dependabot-deps.owid.pages.dev/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://data-bump-dependabot-deps.owid.pages.dev/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://data-bump-dependabot-deps.owid.pages.dev/grapher/adult-population-covered-in-primary-data-on-the-prevalence-of-major-depression.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear