Echoes of solitude: systematic review and meta-analysis revealing mortality risks in older adults due to loneliness, social isolation, and living alone
Bibliographic record
Abstract
Introduction Loneliness, social isolation, and living alone are emerging as significant risk factors for mortality, especially in older adults. Objectives Loneliness, social isolation, and living alone are recognized as significant risk factors for mortality in older adults. This study aimed to quantify their associations with all-cause and cause-specific mortality, extending the scope of previous research by considering a broader range of social factors. Methods A systematic search was conducted in PubMed, APA PsycINFO, and CINAHL databases up to December 31,2023, adhering to PRISMA 2020 and MOOSE guidelines. Inclusion criteria comprised prospective cohort or longitudinal studies examining the relationship between loneliness, social isolation, living alone, and mortality. Quality assessment was performed using the Newcastle-Ottawa Scale. Meta-analyses utilized random-effects models with the Restricted Maximum Likelihood method, while subgroup and meta-regression analyses explored further relationships. Results Out of 11,964 studies screened, 86 met the inclusion criteria. Loneliness was associated with a 14% increase in all-cause mortality risk, social isolation with a 35% increase, and living alone with a 21% increase. However, substantial heterogeneity was observed across studies, influenced by various factors including gender, age, geographical region, chronic diseases, and study quality. Meta-regression analysis identified predictors such as longer follow-up periods, female sex, validated social network indices, cognitive function adjustments, and study quality. Conclusions Loneliness, social isolation, and living alone significantly increase mortality risk in older adults, emphasizing the urgency of public health interventions targeting these factors to enhance health outcomes among the aging population. However, due to study variations, further research is needed to understand their cumulative effect on mortality risks and inform tailored interventions. Disclosure of Interest None Declared
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".