Brain Structure and Function Predict Adherence to an Exercise Intervention in Older Adults.
Brain Structure and Function Predict Adherence to an Exercise Intervention in Older Adults.
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DOI：
10.1249/mss.0000000000002949
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发表时间：
2022-09-01
影响因子：
4.1
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老年人大脑结构和功能的个体差异是大脑储备或维护的潜在代理，并可能提供坚持锻炼的机械预测。我们假设，多模态神经影像学特征将预测对131名老年人（年龄65.79（4.65）岁，63%为女性）进行的为期6个月的随机对照运动试验的依从性，单独和与心理社会，认知和健康措施相结合。应用嵌套交叉验证框架内的正则化弹性网络回归来预测三个独立模型（仅大脑结构和功能，仅心理社会，健康和人口统计数据以及多模态模型）中对干预的依从性。较高的皮质厚度在躯体感觉和下额叶区域和表面积较小的主要视觉和下额叶区域预测遵守。较高的节点功能连接（度计数）默认，额顶叶和注意力网络，以及初级视觉和颞顶网络的节点强度较低预测运动坚持性（r = 0.24，p = 0.004）。步态和行走自我效能、生物性别和感知压力的调查和临床测量也预测了依从性（r = 0.17，p = 0.056），但当对零检验统计量进行检验时，该预测不显著。组合的多模态模型实现了最高的预测强度（r = 0.28，p = 0.001）。我们的研究结果表明，在未来的研究中，使用基于大脑的措施对老年人进行精确和个性化的运动干预具有重要的实用性。
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. 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). 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). Our results suggest there is substantial utility of using brain-based measures in future research into precision and individualized exercise interventions older adults.