2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The global gap in treatment coverage for major depressive disorder in 84 countries from 2000–2019: A systematic review and Bayesian meta-regression analysis

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The treatment coverage for major depressive disorder (MDD) is low in many parts of the world despite MDD being a major contributor to disability globally. Most existing reviews of MDD treatment coverage do not account for potential sources of study-level heterogeneity that contribute to variation in reported treatment rates. This study aims to provide a comprehensive review of the evidence and analytically quantify sources of heterogeneity to report updated estimates of MDD treatment coverage and gaps by location and treatment type between 2000 and 2019.

          Methods and findings

          A systematic review of the literature was conducted to identify relevant studies that provided data on treatment rates for MDD between January 1, 2000, and November 26, 2021, from 2 online scholarly databases PubMed and Embase. Cohort and cross-sectional studies were included if treatment rates pertaining to the last 12 months or less were reported directly or if sufficient information was available to calculate this along with 95% uncertainty intervals (UIs). Studies were included if they made use of population-based surveys that were representative of communities, countries, or regions under study. Studies were included if they used established diagnostic criteria to diagnose cases of MDD. Sample and methodological characteristics were extracted from selected studies. Treatment rates were modeled using a Bayesian meta-regression approach and adjusted for select covariates that quantified heterogeneity in the data. These covariates included age, sex, treatment type, location, and choice of MDD assessment tool. A total of 149 studies were included for quantitative analysis. Treatment coverage for health service use ranged from 51% [95% UI 20%, 82%] in high-income locations to 20% [95% UI 1%, 53%] in low- and lower middle-income locations. Treatment coverage for mental health service use ranged from 33% [95% UI 8%, 66%] in high-income locations to 8% [95% UI <1%, 36%] in low- and lower middle-income countries. Minimally adequate treatment (MAT) rates ranged from 23% [95% UI 2%, 55%] in high-income countries to 3% [95% UI <1%, 25%]) in low- and lower middle-income countries. A primary methodological limitation was the lack of sufficient data from low- and lower middle-income countries, which precluded our ability to provide more detailed treatment rate estimates.

          Conclusions

          In this study, we observed that the treatment coverage for MDD continues to be low in many parts of the world and in particular in low- and lower middle-income countries. There is a continued need for routine data collection that will help obtain more accurate estimates of treatment coverage globally.

          Abstract

          In a systematic review and Bayesian meta-regression analysis, Modhurima Moitra and colleagues estimate major depressive disorder treatment coverage in 84 countries.

          Author summary

          Why was this study done?
          • ➢ Major depressive disorder (MDD) is one of the major contributors to disability worldwide, but treatment rates for this condition are remarkably low.

          • ➢ To the best of our knowledge, previous systematic reviews on this topic provide more descriptive summaries of treatment rates without accounting for differences in study attributes that may contribute to variation in reported treatment rates.

          • ➢ An updated systematic review that is more reflective of the recent literature on treatment rates as well as an improved analytical approach may provide more accurate estimates of treatment rates by resource setting and geography.

          What did the researchers do and find?
          • ➢ We conducted a systematic review and meta-regression analysis using data on treatment rates for MDD from 149 studies and 84 countries between 2000 and 2021.

          • ➢ We estimated pooled treatment rates adjusted for parameters of interest including age, sex, treatment type, study methods, and location.

          • ➢ Mental health service use ranged from 33% (95% uncertainty interval (UI) 8, 66) in high-income countries to 8% (95% UI <1, 36) in low- and lower middle-income countries.

          • ➢ Minimally adequate treatment (MAT) ranged from 23% (95% UI 2, 55) in high-income countries to 3% (95% UI <1, 25) in low- and lower middle-income countries.

          What do these findings mean?
          • ➢ This systematic review provides updated evidence on treatment rates for MDD, and results suggest that there are wide disparities in treatment rates by resource setting.

          • ➢ More high-quality data on depression treatment coverage and adequacy are needed from low- and lower middle-income countries.

          • ➢ These findings may help prioritize efforts to scale up depression treatment in locations with clearly identified treatment gaps.

          Related collections

          Most cited references31

          • Record: found
          • Abstract: not found
          • Article: not found

          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            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

            Summary Background In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding Bill & Melinda Gates Foundation.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Estimating the true global burden of mental illness.

              We argue that the global burden of mental illness is underestimated and examine the reasons for under-estimation to identify five main causes: overlap between psychiatric and neurological disorders; the grouping of suicide and self-harm as a separate category; conflation of all chronic pain syndromes with musculoskeletal disorders; exclusion of personality disorders from disease burden calculations; and inadequate consideration of the contribution of severe mental illness to mortality from associated causes. Using published data, we estimate the disease burden for mental illness to show that the global burden of mental illness accounts for 32·4% of years lived with disability (YLDs) and 13·0% of disability-adjusted life-years (DALYs), instead of the earlier estimates suggesting 21·2% of YLDs and 7·1% of DALYs. Currently used approaches underestimate the burden of mental illness by more than a third. Our estimates place mental illness a distant first in global burden of disease in terms of YLDs, and level with cardiovascular and circulatory diseases in terms of DALYs. The unacceptable apathy of governments and funders of global health must be overcome to mitigate the human, social, and economic costs of mental illness.
                Bookmark

                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SoftwareRole: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                15 February 2022
                February 2022
                : 19
                : 2
                : e1003901
                Affiliations
                [1 ] Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
                [2 ] Department of Global Health, University of Washington, Seattle, Washington, United States of America
                [3 ] The University of Queensland, School of Public Health, Brisbane, Queensland, Australia
                [4 ] Queensland Centre for Mental Health Research, Brisbane, Queensland, Australia
                [5 ] Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, United States of America
                [6 ] Harvard T H Chan School of Public Health, Harvard University, Boston, Massachusetts, United States of America
                Addis Ababa University / King’s College London, ETHIOPIA
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-8238-4906
                https://orcid.org/0000-0002-6630-5435
                https://orcid.org/0000-0003-3956-448X
                https://orcid.org/0000-0002-5690-5365
                https://orcid.org/0000-0001-9385-0212
                https://orcid.org/0000-0002-7863-9117
                Article
                PMEDICINE-D-21-02355
                10.1371/journal.pmed.1003901
                8846511
                35167593
                cf57fdea-21ec-41c2-8968-165bc2724d86
                © 2022 Moitra et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 May 2021
                : 22 December 2021
                Page count
                Figures: 3, Tables: 6, Pages: 16
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000865, Bill and Melinda Gates Foundation;
                Funded by: funder-id http://dx.doi.org/10.13039/100010230, Department of Health, Queensland;
                Funded by: National Health and Medical Research Council Early Career Fellowship Grant
                Award ID: APP1121516
                This research was supported by the Institute for Health Metrics and Evaluation which receives funding from the Bill & Melinda Gates Foundation. AJF is supported by a National Health and Medical Research Council Early Career Fellowship Grant (APP1121516). AJF, DS and HW are employed by the Queensland Centre for Mental Health Research which receives core funding from the Queensland Department of Health, (Queensland Australia). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mental Health Therapies
                Medicine and Health Sciences
                Public and Occupational Health
                Global Health
                Research and Analysis Methods
                Research Assessment
                Systematic Reviews
                Medicine and Health Sciences
                Health Care
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Public and Occupational Health
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Pharmaceutics
                Drug Therapy
                Medicine and Health Sciences
                Epidemiology
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files

                Medicine
                Medicine

                Comments

                Comment on this article