Med Sci Sports Exerc. 2022 Apr 25. doi: 10.1249/MSS.0000000000002949. Online ahead of print.
ABSTRACT
INTRODUCTION: Individual differences in brain structure and function in older adults are potential proxies of brain reserve or maintenance and may provide mechanistic predictions of adherence to exercise. We hypothesized that multimodal neuroimaging features would predict adherence to a six-month randomized controlled trial of exercise in 131 older adults (aged 65.79 (4.65) years, 63 percent female), alone and in combination with psychosocial, cognitive and health measures.
METHODS: Regularized elastic net regression within a nested cross-validation framework was applied to predict adherence to the intervention in three separate models (brain structure and function only, psychosocial, health and demographic data only, and a multimodal model).
RESULTS: Higher cortical thickness in somatosensory and inferior frontal regions and less surface area in primary visual and inferior frontal regions predicted adherence. Higher nodal functional connectivity (degree count) in default, frontoparietal and attentional networks, and less nodal strength in primary visual and temporoparietal networks predicted exercise adherence (r = 0.24, p = 0.004). Survey and clinical measures of gait and walking self-efficacy, biological sex and perceived stress also predicted adherence (r = 0.17, p = 0.056), however this prediction was not significant when tested against a null test statistic. A combined multimodal model achieved the highest predictive strength (r = 0.28, p = 0.001).
CONCLUSIONS: Our results suggest there is substantial utility of using brain-based measures in future research into precision and individualized exercise interventions older adults.
PMID:35482769 | DOI:10.1249/MSS.0000000000002949
