Abstract Biopsychosocial frailty, integrating physical, psychological, and social dimensions, significantly affects health outcomes in older adults. Hospitalization, a major contributor to healthcare burden, is strongly associated with frailty. However, the role of socioeconomic determinants within frailty trajectories remains insufficiently explored. This study aimed to evaluate the association between biopsychosocial frailty trajectories and hospitalization rates, with a focus on social determinants. We conducted a retrospective cohort study involving 6086 individuals (mean age 83.6 ± 4.9 years; 65.9% women). They underwent serial frailty assessments between 2016 and 2024 using the Short Functional Geriatric Evaluation (SFGE). Frailty trajectories were categorized as improved, stable, or worsened. Hospitalization rates were analyzed through parametric/non-parametric tests and negative binomial regression models adjusted for age, baseline frailty, and psycho-physical status. Hospitalization rates increased with frailty severity: 84‰ in robust, 97‰ in pre-frail, 149‰ in frail, and 136‰ in very frail individuals (P < 0.001). Improved or stable financial conditions significantly reduced hospitalization risk (rate ratio [RR] 0.24 and 0.41, respectively), as did stable or restored informal support networks (RR 0.45 and 0.79, respectively). Improved living arrangements were also associated with reduced hospital admissions. Robust and pre-frail individuals accounted for ∼50% of all admissions. Social and economic stability are key protective factors against hospitalization in older adults, independent of physical frailty. Community-based interventions addressing social isolation and financial vulnerability could substantially reduce hospital admissions, particularly among robust and pre-frail individuals. A holistic approach integrating social, economic, and physical frailty dimensions is recommended to optimize public health strategies for aging populations.

Social support and hospitalization in the elderly: investigating the role of frailty trajectories

Anna Maria Doro Altan;
2026-01-01

Abstract

Abstract Biopsychosocial frailty, integrating physical, psychological, and social dimensions, significantly affects health outcomes in older adults. Hospitalization, a major contributor to healthcare burden, is strongly associated with frailty. However, the role of socioeconomic determinants within frailty trajectories remains insufficiently explored. This study aimed to evaluate the association between biopsychosocial frailty trajectories and hospitalization rates, with a focus on social determinants. We conducted a retrospective cohort study involving 6086 individuals (mean age 83.6 ± 4.9 years; 65.9% women). They underwent serial frailty assessments between 2016 and 2024 using the Short Functional Geriatric Evaluation (SFGE). Frailty trajectories were categorized as improved, stable, or worsened. Hospitalization rates were analyzed through parametric/non-parametric tests and negative binomial regression models adjusted for age, baseline frailty, and psycho-physical status. Hospitalization rates increased with frailty severity: 84‰ in robust, 97‰ in pre-frail, 149‰ in frail, and 136‰ in very frail individuals (P < 0.001). Improved or stable financial conditions significantly reduced hospitalization risk (rate ratio [RR] 0.24 and 0.41, respectively), as did stable or restored informal support networks (RR 0.45 and 0.79, respectively). Improved living arrangements were also associated with reduced hospital admissions. Robust and pre-frail individuals accounted for ∼50% of all admissions. Social and economic stability are key protective factors against hospitalization in older adults, independent of physical frailty. Community-based interventions addressing social isolation and financial vulnerability could substantially reduce hospital admissions, particularly among robust and pre-frail individuals. A holistic approach integrating social, economic, and physical frailty dimensions is recommended to optimize public health strategies for aging populations.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14085/54801
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