为了健康,我们应该更聪明地工作还是更努力地工作?比较强度和基于领域的时间使用组合及其与认知和心脏代谢健康的关系

Maddison L Mellow, Dorothea Dumuid, Alexandra Wade, Timothy Olds, Ty Stanford, Hannah Keage, Montana Hunter, Nicholas Ware, Felicity M Simpson, Frini Karayanidis, Ashleigh E Smith
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引用次数: 0

摘要

背景 每天都有大量的 "时间使用行为"。这些行为可按强度(如轻度或中度剧烈运动 (PA))或领域(如家务、社交)进行分类。基于强度的时间使用行为与老年人的认知功能和心脏代谢健康有关,但这些关系是否因行为领域(或类型/背景)的不同而有所差异,目前尚不清楚。方法 这项研究包括来自澳大利亚阿德莱德和纽卡斯尔的 397 名老年人(65.5 ± 3.0 岁,69% 为女性,16.0 ± 3.0 年教育程度)。使用儿童和成人多媒体活动回忆(MARCA)记录了时间使用行为,使用Addenbrooke认知检查III(ACE-III)和剑桥神经心理测试自动电池(CANTAB)测量了认知功能,还记录了收缩压和舒张压、总胆固醇和腰臀比。从每位受试者的 MARCA 中得出了两个 24 小时时间使用构成,包括由四个部分组成的强度构成(睡眠、久坐行为、轻度和中度剧烈活动)和由八个部分组成的领域构成(睡眠、自理、家务、屏幕时间、安静时间、家务管理、运动/锻炼和社交)。结果 线性回归发现,领域构成与 ACE-III (p=0.010) 和腰臀比 (p=0.009) 之间以及强度构成与腰臀比 (p=0.025) 之间均存在显著关联。等时替代模型表明,久坐行为和活动量影响了它们与 ACE-III 的关系,而任何活动量似乎都有利于腰臀比。结论 研究结果表明,在支持认知功能时应考虑行为领域,而对于心血管代谢健康而言,促进任何类型的活动量似乎就足够了。
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Should we work smarter or harder for our health? A comparison of intensity and domain-based time-use compositions and their associations with cognitive and cardiometabolic health
BACKGROUND Each day is made up of a composition of ‘time-use behaviours’. These can be classified by their intensity (e.g., light or moderate-vigorous physical activity (PA)) or domain (e.g., chores, socialising). Intensity-based time-use behaviours are linked with cognitive function and cardiometabolic health in older adults, but it is unknown whether these relationships differ depending on the domain (or type/context) of behaviour. METHODS This study included 397 older adults (65.5 ± 3.0 years, 69% female, 16.0 ± 3.0 years education) from Adelaide and Newcastle, Australia. Time-use behaviours were recorded using the Multimedia Activity Recall for Children and Adults (MARCA), cognitive function was measured using the Addenbrooke’s Cognitive Examination III (ACE-III) and Cambridge Neuropsychological Test Automated Battery (CANTAB), and systolic and diastolic blood pressure, total cholesterol and waist-hip ratio were also recorded. Two 24-hr time-use compositions were derived from each participant’s MARCA, including a four-part intensity composition (sleep, sedentary behaviour, light and moderate-vigorous PA) and an eight-part domain composition (Sleep, Self-Care, Chores, Screen Time, Quiet Time, Household Administration, Sport/Exercise, and Social). RESULTS Linear regressions found significant associations between the domain composition and both ACE-III (p=0.010) and waist-hip ratio (p=0.009), and between the intensity composition and waist-hip ratio (p=0.025). Isotemporal substitution modelling demonstrated that the domains of sedentary behaviours and PA impacted their associations with ACE-III, whilst any PA appeared beneficial for waist-hip ratio. CONCLUSIONS Findings suggest the domain of behaviour should be considered when aiming to support cognitive function, whereas for cardiometabolic health, it appears sufficient to promote any type of PA
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