Living alone and 12-month major depressive episode in men and women from 2005 to 2021
Bibliographic record
Abstract
Objective The objective of the present study is to determine whether living alone is associated with major depression among men and women after adjusting for sociodemographics known to be associated with depression. Methods Data from the 2005, 2010, 2017, and 2021 nationally representative cross-sectional French Health Barometer surveys were pooled covering n = 71,168 adults ages 18 to 75. Logistic regressions were performed to identify associations between 12-month major depressive episode and living alone overall, and stratified by sex. Results An increasing portion of adults 18 to 75 lives alone in France: 11.2 % in 2005, 16.7 % in 2010, 17.4 % in 2017, and 19.0 % in 2021. Among men, in our study, those living alone represented 10.3 % in 2005 to 20.0 % in 2021, among women, 12.1 % in 2005 and 18.0 % in 2021. Men are more likely than women to live alone before age 55, the reverse is true thereafter. In parallel, the prevalence of depression has increased from 8.0 % in 2005 to 13.3 % in 2021. In multivariable models adjusting for age, sex, education, occupation, income level, urbanicity and study wave, living alone was associated with higher odds of depression (AOR=1.50, 95 %CI=1.41–1.60). No significant interactions were found for living alone x sex, while living alone was significantly associated with depression only among those 25 or older. Limitations Cross-sectional surveys. Conclusion Living alone is becoming more frequent and is a strongly associated with major depression. This finding should raise attention to groups of men and women at increased risk of mental health problems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".