AB013. Major depressive disorder and its risk factors in low- and middle-income countries
Bibliographic record
Abstract
Background: Major depressive disorder (MDD) currently ranks as the third leading cause of the global disease burden, with projections indicating it could become the foremost cause by 2030. Despite this alarming trajectory, research on the burden of MDD in low- and middle-income countries (LMICs) remains limited. This study aims to examine the disease burden, risk factors, and temporal trends of MDD from 1990 to 2019. Methods: Data were collected from the Global Burden of Disease (GBD) databases for 135 LMICs. Disability-adjusted life years (DALYs) with 95% uncertainty intervals (UIs) were used to estimate the burden of MDD, and risk factors for MDD were analyzed. LMICs were grouped based on the World Bank’s income classification. Results: In 2019, the total number of MDD DALYs in LMICs was 30.04 (95% UI: 20.58–41.51) million, accounting for 80.76% of the global burden. The DALYs rate of MDD generally increased with age across all income groups in LMICs, showing a negative relationship with income level. Females experienced a higher disease burden than males. From 1990 to 2019, the burden of MDD was inversely associated with the income level of LMICs. The leading risk factors for MDD in 2019 were bullying victimization and childhood sexual assault. The impact of these risk factors varied by age, with bullying victimization affecting individuals aged 15–29 and childhood sexual assault having the most significant impact on individuals aged 0–29 in upper-middle-income countries and around age 59 in low-income and upper-middle income countries. Conclusions: MDD remains a significant health concern in LMICs, particularly among females, youth, and the elderly. It is crucial to prioritize interventions and allocate healthcare resources to effectively reduce the burden of MDD in these vulnerable populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".