Generalized additive mixed models to discern data-driven theoretically informed strategies for public brain, cognitive and mental health.

Social isolation is recognized as a public health emergency. However, major guidelines provide vastly different recommendations on how to target it, and no strategy has been substantiated on firm theoretical or empirical grounds, yet. Rose's seminal The Strategy of Preventive Medicine provided a theoretical framework for such arbitrations between approaches. Therein, determining the shape of the relationship between risk factor and outcome is of paramount importance. However, quantitative approaches immediately applying this theory to evidence are still lacking. Thus, in this pre-registered analysis, we pursued a novel approach and employed generalized additive mixed models to model the shape of social isolation's Links to brain, cognitive and mental health outcomes in a well-characterised population-based sample. We derived brain measures from 3T MRIs, assessed cognitive functions with extensive neuropsychological testing and measured social isolation and mental health outcomes using established questionnaires. Overall, we studied over 10,000 (mean age 58a, 53% women) participants at baseline and over 5500 (mean age 64a, 53% women) at follow-up after ~ 6 years. The relationship of social contact with almost all outcomes was firmly linear and did not differ above and below the standard threshold for social isolation. Only for processing speed did we detect a steeper slope amongst socially isolated individuals. Hence, most of the health effects of social contact were observed in individuals that would not be categorised as socially isolated. Applying advanced statistical methods to a large and well-characterised dataset we provide evidence in support of a shift in focus away from individual-level and towards population-level preventive approaches.