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The Epidemiological Modelling of Major Depressive Disorder: Application for the Global Burden of Disease Study 2010
Open accessAbstract
BACKGROUND: Although the detrimental impact of major depressive disorder (MDD) at the individual level has been described, its global epidemiology remains unclear given limitations in the data. Here we present the modelled epidemiological profile of MDD dealing with heterogeneity in the data, enforcing internal consistency between epidemiological parameters and making estimates for world regions with no empirical data. These estimates were used to quantify the burden of MDD for the Global Burden of Disease Study 2010 (GBD 2010). METHOD: Analyses drew on data from our existing literature review of the epidemiology of MDD. DisMod-MR, the latest version of the generic disease modelling system redesigned as a Bayesian meta-regression tool, derived prevalence by age, year and sex for 21 regions. Prior epidemiological knowledge, study- and country-level covariates adjusted sub-optimal raw data. RESULTS: There were over 298 million cases of MDD globally at any point in time in 2010, with the highest proportion of cases occurring between 25 and 34 years. Global point prevalence was very similar across time (4.4% (95% uncertainty: 4.2-4.7%) in 1990, 4.4% (4.1-4.7%) in 2005 and 2010), but higher in females (5.5% (5.0-6.0%) compared to males (3.2% (3.0-3.6%) in 2010. Regions in conflict had higher prevalence than those with no conflict. The annual incidence of an episode of MDD followed a similar age and regional pattern to prevalence but was about one and a half times higher, consistent with an average duration of 37.7 weeks. CONCLUSION: We were able to integrate available data, including those from high quality surveys and sub-optimal studies, into a model adjusting for known methodological sources of heterogeneity. We were also able to estimate the epidemiology of MDD in regions with no available data. This informed GBD 2010 and the public health field, with a clearer understanding of the global distribution of MDD.
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“This finding was driven by high prevalence estimates with 298 million MDD cases in 2010 [2] and 106 million cases of dysthymia [3].”
From Burden of depressive disorders by country, sex, age, and year: findings from the Global Burden of Disease Study 2010 (2013) · cites this paper as [2]
In the citing paper
“GBD 2010's capacity to generate country-level burden as well as regional estimates was especially relevant for MDD, which has been linked to risk factors such as conflict [2],[37], intimate partner violence, and child sexual abuse [15], the levels of which vary between countries.”
From Burden of depressive disorders by country, sex, age, and year: findings from the Global Burden of Disease Study 2010 (2013) · cites this paper as [2]
In the citing paper
“We found evidence for an elevated risk for mortality in those diagnosed with MDD [2],[25]; however, since a health outcome could only occur once in the GBD cause list, MDD related deaths from suicide and ischemic heart disease were captured under the headings of intentional injuries and cardiovascular disease in the GBD capstone papers [14],[18].”
From Burden of depressive disorders by country, sex, age, and year: findings from the Global Burden of Disease Study 2010 (2013) · cites this paper as [2]
In the citing paper
“GBD 2010's capacity to generate country-level burden as well as regional estimates was especially relevant for MDD, which has been linked to risk factors such as conflict [2],[37], intimate partner violence, and child sexual abuse [15], the levels of which vary between countries.”
From Burden of depressive disorders by country, sex, age, and year: findings from the Global Burden of Disease Study 2010 (2013) · cites this paper as [2]
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Whiteford, H. A., Degenhardt, L., Rehm, J., Baxter, A. J., Ferrari, A. J., Erskine, H. E., Charlson, F. J., Norman, R. E., Flaxman, A. D., Johns, N., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(13)61611-6 · Cited by 6,006
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Metadata
- Authors
- Ferrari, A. J., Charlson, F. J., Norman, R. E., Flaxman, A. D., Patten, S. B., Vos, T., & Whiteford, H. A.
- Affiliations
- The University of Queensland (AU)
- University of Washington (US)
- University of Calgary (CA)
- Corresponding author
- Ferrari, Alize J.
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-07-29
- Volume
- 8
- Issue
- 7
- Pages
- e69637
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3726670
- OpenAlex
- W1504574652
- Cited by
- 330
- References
- 58
- Citations by year
- 2026: 12 · 2025: 25 · 2024: 27 · 2023: 20 · 2022: 38 · 2021: 32 · 2020: 25 · 2019: 30 · 2018: 25 · 2017: 28 · 2016: 24 · 2015: 20 · 2014: 19 · 2013: 5
- FWCI
- 33.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Faculty of Health; Institute of Health and Biomedical Innovation
- Funders
- Bill and Melinda Gates Foundation
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Keywords
- major depressive disorder, global burden of disease, disease prevalence, incidence, depression duration, sex differences, conflict zones, age distribution, Bayesian meta-regression, global epidemiology
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Major Depressive Disorder, Female, Humans, Infant, Infant, Newborn, Male, Middle Aged, Models, Theoretical, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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