The impact of place on multimorbidity: A systematic scoping review
Bibliographic record
Abstract
Multimorbidity, commonly defined as the co-existence of two or more long-term conditions, is a major global public health challenge with significant impacts for health and social care systems. There is a substantial body of work identifying different individual- and household-level determinants of multimorbidity, yet the role of place-based characteristics in affecting multimorbidity remains limited. This systematic scoping review identifies place-based risk factors for multimorbidity and further synthesises the potential pathways explaining these relationships using longitudinal evidence. By systematically searching seven major databases, such as Medline, Embase, and Web of Science, using relevant search terms (e.g., MeSH) relating to place-based risk factors and multimorbidity, 76 out of 7761 studies were included for evidence synthesis. We include studies exploring the relationship between place-based risk factors and multimorbidity among the general population older than 18 years old in the setting of community-dwelling, primary, and secondary care. We identified 12 types of place-based risk factors, with the impacts of area-level deprivation/SES, pollution, and urban/rurality on multimorbidity being most frequently considered and with the most consistent findings, with people living in more deprived/low SES, highly polluted, or more urbanised areas having increased risks of multimorbidity. Further, the impact of these place-based risk factors on multimorbidity varied according to the operationalisation of the multimorbidity measure. We also identified that the impacts of other types of place-based factors on multimorbidity remain underexplored, such as social cohesion and greenspace. Finally, using these longitudinal findings, we propose a conceptual framework linking place and multimorbidity. We suggest that future studies explore a wider range of place-level environmental exposures and use more precise measures, exploit electronic health records to implement more consistent and reproducible measurements of multimorbidity, moreover, make greater use of longitudinal study designs or analytical approaches better suited to identifying causal processes.
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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 | 0.014 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".