Social disconnectedness and the rate of medical conditions: a Danish population-based cohort study

Abstract Background Lack of social connections has a serious impact on health, increasing the risk of medical conditions such as depression, dementia, and coronary heart disease. However, evidence is limited by a disease-specific focus. We aimed to provide a comprehensive overview of differences in incidence rates of a broad range of medical conditions according to social disconnectedness (i.e., loneliness, social isolation, and low social support). Methods We conducted a cohort study using data on loneliness, social isolation, low social support, and a composite measure from the 2013 and 2017 Danish National Health Survey. Survey data was linked with register data on 11 categories of medical conditions through 2021. Poisson regression was applied to estimate incidence rate ratios (IRRs), incidence rate differences, and explore interaction with pre-existing mental disorders. Results Among 162,497 survey participants, 7.6%, 3.5%, and 14.8% were identified as lonely, socially isolated, and with low social support, respectively. Lonely individuals and individuals with low social support had a higher incidence rate of all 11 categories of medical conditions (interquartile range of IRRs, loneliness 1.22-1.49 and low social support 1.10-1.14), whereas this was the case for nine categories among socially isolated individuals (interquartile range of IRRs, 1.01-1.31). Applying the composite measure, the highest IRR was 2.61 (95% CI, 2.34-2.88) for a mental disorder and the lowest 1.03 (95% CI, 0.95-1.10) for cancer. We found neither major sex differences nor substantial interaction with pre-existing mental disorders. Conclusions Our study confirms and extends the available evidence on social disconnectedness and the risk of medical conditions. The attained knowledge may be of significance for mapping group-specific preventative needs and guiding interventions and health practitioners aiming to reduce the disease burden among socially disconnected individuals. Key messages • Based on survey and register data from 162,497 individuals, our study suggests that social disconnectedness, especially loneliness, is a determinant of a broad range of medical conditions. • The findings may be of importance for identifying and targeting the disease burden among socially disconnected individuals.

Authors

Institutions

Publication Details

Journal
European Journal of Public Health
Published
2024-10-28
DOI
https://doi.org/10.1093/eurpub/ckae144.344
Primary Topic
Health disparities and outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Social disconnectedness and the rate of medical conditions: a Danish population-based cohort study

Natalie C. Momen, Jaimie L. Gradus, Lisbeth Mølgaard Laustsen, Mathias Lasgaard et al.
European Journal of Public Health
Health disparities and outcomes
article

Social disconnectedness and the rate of medical conditions: a Danish population-based cohort study

Natalie C. Momen, Jaimie L. Gradus, Lisbeth Mølgaard Laustsen, Mathias Lasgaard, Mette Munk Jensen, Oleguer Plana‐Ripoll, Marie Grønkjær, Dong Chen
article en

Abstract

Abstract Background Lack of social connections has a serious impact on health, increasing the risk of medical conditions such as depression, dementia, and coronary heart disease. However, evidence is limited by a disease-specific focus. We aimed to provide a comprehensive overview of differences in incidence rates of a broad range of medical conditions according to social disconnectedness (i.e., loneliness, social isolation, and low social support). Methods We conducted a cohort study using data on loneliness, social isolation, low social support, and a composite measure from the 2013 and 2017 Danish National Health Survey. Survey data was linked with register data on 11 categories of medical conditions through 2021. Poisson regression was applied to estimate incidence rate ratios (IRRs), incidence rate differences, and explore interaction with pre-existing mental disorders. Results Among 162,497 survey participants, 7.6%, 3.5%, and 14.8% were identified as lonely, socially isolated, and with low social support, respectively. Lonely individuals and individuals with low social support had a higher incidence rate of all 11 categories of medical conditions (interquartile range of IRRs, loneliness 1.22-1.49 and low social support 1.10-1.14), whereas this was the case for nine categories among socially isolated individuals (interquartile range of IRRs, 1.01-1.31). Applying the composite measure, the highest IRR was 2.61 (95% CI, 2.34-2.88) for a mental disorder and the lowest 1.03 (95% CI, 0.95-1.10) for cancer. We found neither major sex differences nor substantial interaction with pre-existing mental disorders. Conclusions Our study confirms and extends the available evidence on social disconnectedness and the risk of medical conditions. The attained knowledge may be of significance for mapping group-specific preventative needs and guiding interventions and health practitioners aiming to reduce the disease burden among socially disconnected individuals. Key messages • Based on survey and register data from 162,497 individuals, our study suggests that social disconnectedness, especially loneliness, is a determinant of a broad range of medical conditions. • The findings may be of importance for identifying and targeting the disease burden among socially disconnected individuals.

European Journal of Public HealthVol. 34(Supplement_3)
Boston University (US), University of Southern Denmark (DK), Aarhus University (DK), Frederiksberg Hospital (DK), Aarhus University Hospital (DK), Copenhagen University Hospital (DK), Center for Clinical Research and Prevention (DK), Central Denmark Region (DK)
Reduced inequalities
Openalex Percentile: Top 76%
Health disparities and outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.