gms | German Medical Science

Background: Studies showed a positive link between social inclusion and health, with greater network diversity reducing the risk of mortality in older adults. Loneliness and social isolation are considered serious health risks, comparable to well-known factors such as smoking or obesity. Research also suggests that social activities and networks have a protective effect on cognitive function. Poor cognitive function is in turn associated with an increased risk of mortality, particularly in dementia patients, due to associated health problems. Despite intensive research, the combined effects of social networks and cognition on mortality in older people are not yet fully understood. The aim of this study is to investigate the effects of the social network and cognitive function (CF) on mortality in older people.

Methods: We used data from the NAKO Health Study (N=200.000), a Germany-wide prospective epidemiological study. We included all people aged 60 and older (N=55,194). All study participants were randomly selected by age and gender. The sample provided information on demographics, genetic characteristics, health conditions, lifestyle factors, environmental exposures, and social networks. The NAKO mortality follow-up provided information on the mortality status of all patients until the end of 2023. Social networks were assessed using the Social Network Index and categorized as isolated or non-isolated, and cognitive function was measured using patient self-reports ((very) good vs. average vs. (very) poor). We examined the association of social networks and CF with mortality using logistic regression models. The potential moderation by cognitive function was then analyzed using an interaction effect.

Results: After adjusting for age, sex and education, lack of a social network was significantly associated with an increased risk of death (OR=1.72, p-value<0.001). This effect did not change after adjustment for self-rated CF and comorbidities. With decreasing self-rated CF, the risk of death increased, but not significantly.

The interaction between the social network and self-related CF showed a significant increase in mortality risk for isolated persons regardless of self-related CF (isolated and CF (very) good: OR=1.69, p-value<0.001; isolated and CF average: OR=1.59, p-value=0.001; isolated and CF (very) poor: OR=1.84, p-value=0.045) and no effect for persons with a social network (not isolated and CF average: OR=0.97, p-value=0.631; not isolated and CF (very) poor: OR=1.06, p-value=0.753).

Conclusion/outlook: Social isolation has a negative effect on mortality risk, regardless of self-related CF. Social networks may compensate for the increased mortality risk of people with average/(very) poor CF. Nevertheless, it is essential to conduct a more in-depth analysis of social networks, with a firmer focus on the diversity and size of these networks. In addition, analyses with clinical cognitive parameters are needed to capture not only self-rated CF but also clinical CF and to analyze its influence. Due to the large sample size and the comprehensive study program, the NAKO data is an excellent source for investigating the influence of the social network and CF on mortality in Germany.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.