The impact of comorbid pain and depression in the United States: results from a nationally representative survey
Bibliographic record
Abstract
Background and aims The co-morbidity between pain and depression is a target of interest for treatment. However most of the published literature on the topic has used clinical cohorts as the population of interest. The goal of this study was to use a nationally representative sample to explore how health outcomes varied across pain and depression status in a cohort sampled from the general US population. Methods This was a cross-sectional analysis of adults ≥18 years in the 2009-2010 National Health and Nutrition Examination Survey. The cohort was stratified into: no pain/depression, pain alone, depression alone, and pain with depression. The primary outcome was self-reported general health status, and secondary outcomes were healthcare visits, overnight hospital stays and functional limitation. Survey weighted logistic regression was used to adjust for potential confounders. Results The cohort consisted of 4,213 individuals, of which 186 (4.4%) reported concurrent pain and depression. 597 (14.2%) and 253 (6.0%) were classified with either pain or depression alone, respectively. The majority of individuals with co-morbid pain and depression reported poor health (65.1%, p<0.001) and were significantly more likely than those with neither condition to rate their health as poor after adjustment (OR: 7.77, 95% CI: 4.24-14.26, p<0.001). Those with pain only or depression only were also more likely to rate their health as poor, albeit to a lesser extent (OR: 2.21, 95% CI: 1.21-2.34, p<0.001; OR: 3.75, 95% CI: 2.54-5.54, p<0.001, respectively). A similar pattern was noted across all secondary outcomes. Most notably, those with co-morbid pain and depression were the most likely to endorse functional limitation (OR: 13.15, 95% CI: 8.00-21.61, p<0.001). Comparatively, a similar trend was noted amongst those with pain only or depression only, though with a reduced effect size (OR: 4.23, 95% CI: 3.12-4.77, p<0.001; OR: 5.13, 95% CI: 3.38-7.82, p<0.001). Conclusions Co-morbid pain and depression in the general population resulted in markedly worse outcomes versus isolated pain or depression. Further, the effect appears to be synergistic. Given the substantial burdens of pain and depression, future treatments should aim to address both conditions simultaneously. Implications As a result of the co-morbidity between pain and depression, patients presenting with either condition should increase the index of suspicion among clinicians and prompt screening for the reciprocal condition. Early intervention for co-morbid pain and depression has the potential to mitigate future incidence of chronic pain and major depression.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".