Dataset Information

The epidemiological modelling of major depressive disorder: application for the Global Burden of Disease Study 2010.

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.

SUBMITTER: Ferrari AJ

PROVIDER: S-EPMC3726670 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The epidemiological modelling of major depressive disorder: application for the Global Burden of Disease Study 2010.

Ferrari Alize J AJ Charlson Fiona J FJ Norman Rosana E RE Flaxman Abraham D AD Patten Scott B SB Vos Theo T Whiteford Harvey A HA

PloS one 20130729 7

<h4>Background</h4>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 ...[more]

PMID: 23922765

Similar Datasets

Project description:BackgroundThe incremental economic burden of US adults with major depressive disorder (MDD) was estimated at $US210.5 billion in 2010 (year 2012 values).ObjectiveFollowing a similar methodology, this study updates the previous findings with more recent data to report the economic burden of adults with MDD in 2018.MethodThis study used a framework for evaluating the incremental economic burden of adults with MDD in the USA that combined original and literature-based estimates, focusing on key changes between 2010 and 2018. The prevalence rates of MDD by sex, age, employment, and treatment status over time were estimated based on the National Survey on Drug Use and Health (NSDUH). The incremental direct and workplace costs per individual with MDD were primarily derived from administrative claims data and NSDUH data using comparative analyses of individuals with and without MDD. Societal direct and workplace costs were extrapolated by multiplying NSDUH estimates of the number of people with MDD by the direct and workplace cost estimates per patient. The suicide-related costs were estimated using a human capital method.ResultsThe number of US adults with MDD increased by 12.9%, from 15.5 to 17.5 million, between 2010 and 2018, whereas the proportion of adults with MDD aged 18-34 years increased from 34.6 to 47.5%. Over this period, the incremental economic burden of adults with MDD increased by 37.9% from $US236.6 billion to 326.2 billion (year 2020 values). All components of the incremental economic burden increased (i.e., direct costs, suicide-related costs, and workplace costs), with the largest growth observed in workplace costs, at 73.2%. Consequently, the composition of 2018 costs changed meaningfully, with 35% attributable to direct costs (47% in 2010), 4% to suicide-related costs (5% in 2010), and 61% to workplace costs (48% in 2010). This increase in the workplace cost share was consistent with more favorable employment conditions for those with MDD. Finally, the proportion of total costs attributable to MDD itself as opposed to comorbid conditions remained stable at 37% (38% in 2010).ConclusionWorkplace costs accounted for the largest portion of the growing economic burden of MDD as this population trended younger and was increasingly likely to be employed. Although the total number of adults with MDD increased from 2010 to 2018, the incremental direct cost per individual declined. At the same time, the proportion of adults with MDD who received treatment remained stable over the past decade, suggesting that substantial unmet treatment needs remain in this population. Further research is warranted into the availability, composition, and quality of MDD treatment services.

Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.

Project description:BackgroundDepressive disorders were a leading cause of burden in the Global Burden of Disease (GBD) 1990 and 2000 studies. Here, we analyze the burden of depressive disorders in GBD 2010 and present severity proportions, burden by country, region, age, sex, and year, as well as burden of depressive disorders as a risk factor for suicide and ischemic heart disease.Methods and findingsBurden was calculated for major depressive disorder (MDD) and dysthymia. A systematic review of epidemiological data was conducted. The data were pooled using a Bayesian meta-regression. Disability weights from population survey data quantified the severity of health loss from depressive disorders. These weights were used to calculate years lived with disability (YLDs) and disability adjusted life years (DALYs). Separate DALYs were estimated for suicide and ischemic heart disease attributable to depressive disorders. Depressive disorders were the second leading cause of YLDs in 2010. MDD accounted for 8.2% (5.9%-10.8%) of global YLDs and dysthymia for 1.4% (0.9%-2.0%). Depressive disorders were a leading cause of DALYs even though no mortality was attributed to them as the underlying cause. MDD accounted for 2.5% (1.9%-3.2%) of global DALYs and dysthymia for 0.5% (0.3%-0.6%). There was more regional variation in burden for MDD than for dysthymia; with higher estimates in females, and adults of working age. Whilst burden increased by 37.5% between 1990 and 2010, this was due to population growth and ageing. MDD explained 16 million suicide DALYs and almost 4 million ischemic heart disease DALYs. This attributable burden would increase the overall burden of depressive disorders from 3.0% (2.2%-3.8%) to 3.8% (3.0%-4.7%) of global DALYs.ConclusionsGBD 2010 identified depressive disorders as a leading cause of burden. MDD was also a contributor of burden allocated to suicide and ischemic heart disease. These findings emphasize the importance of including depressive disorders as a public-health priority and implementing cost-effective interventions to reduce its burden. Please see later in the article for the Editors' Summary.

Dataset Information

The epidemiological modelling of major depressive disorder: application for the Global Burden of Disease Study 2010.

Publications

The epidemiological modelling of major depressive disorder: application for the Global Burden of Disease Study 2010.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets