The impact of place on multimorbidity: A systematic scoping review

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.