Predicting pre-frailty and Onset of frailty through postural Stability Testing and Unsteadiness Risk Evaluation (POSTURE): secondary and coordinated analysis of cohort data

• Applicant: Professorin Dr. Eva Grill
• Subject Area: Epidemiology and Medical Biometry/Statistics
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 552890532

Although life expectancy is rising, healthy life expectancy, the years spent in good health, is projected to decrease in most high-income countries, making this a concern for health systems and societies. Ageing involves an increase in loss of function, but individuals of the same age vary greatly in their trajectories of health status, risk for chronic disease and frailty. Early detection of health states that may be indicative of the onset of frailty is therefore important to reverse imminent frailty, and thus to prevent disability. The prodromal signs of frailty, pre-frailty, may be discernible much earlier in life. Yet, there is no reliable definition or measurement of pre-frailty. Also, various physical, lifestyle related, sociodemographic and environmental factors have been identified as risk factors for the progression from pre-frailty to frailty. The single contribution of these risk factors is still incompletely understood. We argue that balance and postural stability (BPS) may be suitable candidates to indicate pre-frailty. BPS are important for daily functioning. Independent of age, they predict risk of chronic disease, disability and death. Objective of this project is therefore to investigate measures of balance and postural stability as indicators of a pre-frailty phenotype in middle-aged populations and as predictors of frailty in older populations. We will use available data from large cohort studies while considering the complex temporal and causal associations of BPS and lifestyle and environmental factors. To increase the external validity and reproducibility of our research, we plan to apply the framework of coordinated analysis. Coordinated analysis allows to jointly analyse existing data from different source cohort studies while allowing differing variable definitions in these cohorts. We will first systematically search and acquire data, and harmonise BPS measures and frailty outcomes. Reuse of existing data is ethical, and ecologically and economically sustainable. Cross-sectional and longitudinal multivariable analyses of these data will yield measures of effect. Where possible, we will summarise estimates from single studies by meta-analysis using a random effects model that allows to investigate heterogeneity of studies. We include studies based on maximum variation to explore heterogeneity and to increase generalisability of out results. Ultimately, we expect our results to contribute to the early detection and prevention of disability, thus expanding healthy life expectancy in populations.

• DFG Programme: Research Grants