Multimorbidity of overweight and obesity alongside anxiety and depressive disorders in individuals with spinal cord injury
Bibliographic record
Abstract
OBJECTIVE: To compare the prevalence of anxiety/depression and overweight/obesity (Aim 1) and the multimorbidity of these conditions (Aim 2) in a sample of adults with and without spinal cord injury (SCI). Aim 3 was to examine whether overweight/obese individuals with SCI differ on the prevalence of anxiety/depressive disorders compared to non-overweight/obese individuals with SCI. DESIGN: Retrospective cohort study. PARTICIPANTS: Individuals ≥16 years old who had patient encounters between January 1, 2011, and February 28, 2018. In total, 761 598 individuals were included, of which 3136 had SCI. MAIN OUTCOME MEASURES: Individuals were identified as diagnosed with SCI, anxiety and/or depressive disorders, and overweight/obesity using the International Classification of Diseases. RESULTS: Age-adjusted odds ratios (ORs) were calculated using logistic regression. In contrast to non-SCI individuals, those with SCI had increased odds of anxiety disorders (OR: 3.58, 95% CI [3.29-3.90]), depressive disorders (OR: 4.33, 95% CI [3.95-4.74]), and overweight/obesity (OR: 3.08, 95% CI [2.80-3.38]). Pertaining to multimorbidity, individuals with SCI had increased odds of having overweight/obesity alongside anxiety disorders (OR: 4.30, 95% CI [3.71-4.98]) and overweight/obesity alongside depressive disorders (OR: 4.69, 95% CI [4.01-5.47]) compared to those without SCI. Individuals with SCI who were diagnosed as overweight/obese had increased odds of having anxiety disorders (OR: 2.54, 95% CI [2.06-3.13]), and depressive disorders (OR: 2.70, 95% CI [2.18-3.36]), relative to non-overweight/obese individuals with SCI. CONCLUSIONS: This work is among the first to find evidence that individuals with SCI are at heightened odds of overweight/obesity alongside anxiety and/or depressive disorders. This early work holds clinical implications for treating these interrelated comorbidities in SCI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".