Association between living arrangement and psychological well-being among patients with major depressive disorder: the moderating role of body mass index
Bibliographic record
Abstract
BACKGROUND: Major depressive disorder (MDD) is highly prevalent globally, significantly impacting psychological well-being (PWB). Herein, we aim to evaluate the impact of different living arrangements on PWB in individuals with MDD and explore the potential moderating role of BMI in this relationship. METHODS: Participants with MDD were recruited from a specialist mental health hospital between December 2019 and April 2023. The diagnosis of MDD was assessed by trained psychiatrists using the Mini-International Neuropsychiatric Interview (M.I.N.I.). Psychological well-being was evaluated using the World Health Organization-Five Well-Being Index. Univariable and multivariable logistic regression models were used to examine the association between different living arrangements and PWB at the 12-month follow-up. The Participants were categorized into underweight, normal weight, and overweight groups based on BMI, followed by conducting stratified analysis. RESULTS: After adjusting for covariates, living with family (AOR = 1.80, 95%CI = 1.14-2.87, P = 0.026) was associated with a higher PWB. There was significant moderating effect of BMI on the association of living arrangements with PWB (P = 0.049). The stratification analyses revealed significant associations between living arrangements and PWB in the normal weight group, while no significant associations were found in the underweight and overweight groups. CONCLUSIONS: Living with family was significantly associated with higher levels of PWB in individuals with MDD, especially among those with a normal BMI. These findings highlight the synergistic effect of living with family and maintaining a healthy BMI on improving PWB in depressed individuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".