Economic and Humanistic Burden Associated with Depression and Anxiety Among Adults with Non-Communicable Chronic Diseases (NCCDs) in the United States
Bibliographic record
Abstract
INTRODUCTION: Patients with both major depressive disorder (MDD) and generalized anxiety disorder (GAD) in addition to one or multiple comorbid non-communicable chronic diseases (NCCDs) face unique challenges. However, few studies have characterized how the burden of co-occurring MDD and GAD differs from that of only MDD or only GAD among patients with NCCDs. METHODS: In this study, we used Medical Expenditures Panel Survey data from 2010-2017 to understand how the economic and humanistic burden of co-occurring MDD and GAD differs from that of MDD or GAD alone among patients with NCCDs. We used generalized linear models to investigate this relationship and controlled for patient sociodemographics and clinical characteristics. RESULTS: Co-occurring MDD and GAD was associated with increases in mean annual per patient inpatient visits, office visits, emergency department visits, annual drug costs, and total medical costs. Among patients with 3+ NCCDs, MDD or GAD only was associated with lower odds ratios (ORs) of limitations in activities of daily living (ADLs; 0.532 and 0.508, respectively) and social (0.503, 0.526) and physical limitations (0.613, 0.613) compared to co-occurring MDD and GAD. Compared to patients with co-occurring MDD and GAD, having MDD only or GAD only was associated with significantly lower odds of cognitive limitations (0.659 and 0.461, respectively) in patients with 1-2 NCCDs and patients with 3+ NCCDs (0.511, 0.416). DISCUSSION: Comorbid MDD and GAD was associated with higher economic burden, lower quality of life, and greater limitations in daily living compared to MDD or GAD alone. Health-related economic and humanistic burden increased with number of NCCDs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".