Cited by 331Mental Health Treatment and AccessTreatment of Major DepressionHealth Systems, Economic Evaluations, Quality of Life

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The Epidemiological Modelling of Major Depressive Disorder: Application for the Global Burden of Disease Study 2010

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Ferrari, Alize J., Charlson, Fiona J., Norman, Rosana E., Flaxman, Abraham D., Patten, Scott B., Vos, Theo, Whiteford, Harvey A.·2013·PLoS ONE

DOI 10.1371/journal.pone.0069637PMC PMC3726670

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Abstract

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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Figure 1 Incidence-prevalence-mortality model. Illustrates the generic relationship between epidemiological parameters used by DisMod-MR to model epidemiological data.CC BY · PubMed Central

Figure 2 Summary of the raw data on prevalence (P), incidence (I), duration (D) and excess mortality (EM) of MDD. Summarises the available epidemiological data used as inputs in the DisMod-MR modelling of MDD.CC BY · PubMed Central

Figure 3 Country- and study-level covariate adjustments for MDD. Illustrates the effect of the covariates used in the DisMod-MR modelling of prevalence data.CC BY · PubMed Central

Figure 4 Prevalence of MDD before and after covariate adjustments for females from North Africa/Middle East, 2010. Compares the raw prevalence estimates to the final pooled prevalence output generated by DisMod-MR for females from North Africa/Middle East, for 2010.CC BY · PubMed Central

Figure 5 Prevalence, incidence, duration and excess mortality of MDD in females from North America, High income, 2010. Compares the raw prevalence, incidence, duration and excess mortality estimates to the final pooled prevalence, incidence, duration and excess mortality output generated by DisMod-MR for females from North America, High income, for 2010.CC BY · PubMed Central

Figure 6 Regional point prevalence of MDD by age and sex, 2010. Presents the prevalence of MDD (as derived by DisMod-MR) by region, age and sex for 2010.CC BY · PubMed Central

Figure 7 The overall point prevalence of MDD and 95% uncertainty by region and age, 2010. Presents the prevalence of MDD (as derived by DisMod-MR) by region and age for 2010.CC BY · PubMed Central

Figure 8 The number of point prevalent cases (in millions) of MDD by region, age and sex, 2010. Presents the prevalent cases of MDD (as derived by DisMod-MR) by region, age and sex for 2010.CC BY · PubMed Central

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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: Ferrari, Alize J.
Charlson, Fiona J.
Flaxman, Abraham D.
Patten, Scott B.
Vos, Theo
Whiteford, Harvey A.
Venue: PLoS ONE
Publisher: Public Library of Science (PLoS)
Published: 2013-07-29
Volume: 8
Issue: 7
Pages: e69637
ISSN: 1932-6203 (ISSN-L)
DOI: 10.1371/journal.pone.0069637
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
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
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

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The Epidemiological Modelling of Major Depressive Disorder: Application for the Global Burden of Disease Study 2010

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