Individuals with diminished social connections are at higher risk of mental disorders, dementia, circulatory conditions and musculoskeletal conditions. However, evidence is limited by a disease-specific focus and no systematic examination of sex differences or the role of pre-existing mental disorders.

We conducted a cohort study using data on social disconnectedness (loneliness, social isolation, low social support and a composite measure) from the 2013 and 2017 Danish National Health Survey linked with register data on 11 broad categories of medical conditions through 2021. Poisson regression was applied to estimate incidence rate ratios (IRRs), incidence rate differences (IRDs), and explore sex differences and interaction with pre-existing mental disorders.

Among 162,497 survey participants, 7.6%, 3.5% and 14.8% were classified as lonely, socially isolated and with low social support, respectively. Individuals who were lonely and with low social support had a higher incidence rate in all 11 categories of medical conditions (interquartile range [IQR] of IRRs, respectively 1.26–1.49 and 1.10–1.14), whereas this was the case in nine categories among individuals who were socially isolated (IQR of IRRs, 1.01–1.31). Applying the composite measure, the highest IRR was 2.63 for a mental disorder (95% confidence interval [CI], 2.38–2.91), corresponding to an IRD of 54 (95% CI, 47–61) cases per 10,000 person-years. We found sex and age differences in some relative and absolute estimates, but no substantial deviations from additive interaction with pre-existing mental disorders.

This study advances our knowledge of the risk of medical conditions faced by individuals who are socially disconnected. In addition to the existing evidence, we found higher incidence rates for a broad range of medical condition categories. Contrary to previous evidence, our findings suggest that loneliness is a stronger determinant for subsequent medical conditions than social isolation and low social support.

A preregistered analysis plan and statistical code are available at Open Science Framework (https://osf.io/pycrq).