Depression as a Risk Factor for Physical Illness and Multimorbidity in a Cohort with No Prior Comorbidity
Bibliographic record
Abstract
OBJECTIVE: This study examines whether depression is associated with the development of physical illness and multimorbidity, after controlling for socioeconomic, behavioral, and other potential confounders. METHODS: This is a retrospective cohort study in which adult respondents to three nationally representative population health surveys were linked to health administrative databases in Ontario, Canada, and followed for 10 years from survey index. Respondents with any of the study outcome conditions at baseline were excluded to create a final cohort of 29,838 participants. The main exposure of interest was depression, measured using the Composite International Diagnostic Interview-Short Form for Major Depression. We controlled for age, body mass index, marital status, immigrant status, annual household income, smoking, alcohol consumption, physical activity, health status, and having a regular doctor. The outcome measure was the development of physical illness over 10 years of follow-up, defined as 1 of 15 common chronic conditions using administrative data. RESULTS: Among the 29,838 participants (15,259 [51%] female), 8% of females and 4% of males had depression at baseline. In this cohort with no comorbidities at baseline, even in the fully adjusted model, depression increased the risk of developing a first physical illness for females (hazard ratio [HR] 1.16; 95% CI, 1.07 to 1.26) and males (HR 1.20; 95% CI, 1.07 to 1.36) and increased the risk of developing a second physical illness for females (HR 1.16; 95% CI, 1.02 to 1.33) over 10 years of follow-up. CONCLUSIONS: For individuals with no prior comorbidities, depression is associated with a greater risk of developing subsequent physical illness and multimorbidity over time. Thus, depression identifies a population of people who may benefit from early identification, additional screening, and intervention. Further study needs to be done to determine whether interventions to manage and support people with depression can prevent or delay the increased risk of multimorbidity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 |
| 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".