探索与体育锻炼有关的个人、社会和环境因素:网络分析。

IF 3.9 Q1 SPORT SCIENCES BMJ Open Sport & Exercise Medicine Pub Date : 2024-08-03 eCollection Date: 2024-01-01 DOI:10.1136/bmjsem-2024-001983
Takeyuki Oba, Keisuke Takano, Kentaro Katahira, Kenta Kimura
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引用次数: 0

摘要

目的:体力活动不足(PA)长期以来一直是一个全球性的健康问题,许多研究探讨了体力活动的相关因素,以确定不活跃生活方式的内在机制。在文献中,从不同层面(如个人、环境)发现了数十种相关因素,但很少或没有直接证据表明这些相关因素之间存在相互关联。本研究分析了 44 个在理论和经验上与 PA 相关的变量,以明确与 PA 直接或间接相关的因素:分析了 19 005 名日语成年人(平均年龄为 53.50 岁,SD=17.40;女性 9 706 人)的横断面调查数据集。数据包括人口统计学和人体测量变量;自我报告的锻炼水平;感知到的社会支持和环境(如对城市锻炼设施的认识);心理特征和健康行为特征(如个性、动机、自我效能、决策平衡、改变策略过程);以及技术使用(如移动健康应用程序):进行了网络分析,以选择变量之间有意义的关联(部分相关),结果发现有九个变量与运动负荷直接正相关:工作/就业状况、自我效能感、感知到的社会支持、内在动机、改变阶段、逆向调节、自我评价、环境和技术使用。在 44 个变量中,有 40 个变量存在间接关联(两步相邻关系),这意味着大多数已知的活动量相关因素都与活动量有关联--至少是间接关联:这些已确定的关联反映了多层次视角在理解人们如何保持(不)积极生活方式方面的重要性。对体育锻炼的干预可以有混合层面的目标,包括个体内部特征、社会支持以及物理和数字环境。
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Exploring individual, social and environmental factors related to physical activity: a network analysis.

Objectives: Insufficient physical activity (PA) has long been a global health issue, and a number of studies have explored correlates of PA to identify the mechanisms underlying inactive lifestyles. In the literature, dozens of correlates have been identified at different (eg, individual, environmental) levels, but there is little or no direct evidence for the mutual associations of these correlates. This study analysed 44 variables identified as theoretically and empirically relevant for PA to clarify the factors directly and indirectly associated with PA.

Methods: A cross-sectional survey dataset of 19 005 Japanese-speaking adults (mean age=53.50 years, SD=17.40; 9706 women) was analysed. The data encompassed demographic and anthropometric variables; self-reported PA levels; perceived social support and environments (eg, awareness of urban facilities for PA); psychological traits and health-behaviour characteristics (eg, personality, motivation, self-efficacy, decisional balance, process of change strategies); and technology use (eg, mobile health apps).

Results: Network analyses were performed to select meaningful associations (partial correlations) among variables, which identified nine variables directly positively associated with PA: job/employment status, self-efficacy, perceived social support, intrinsic motivation, stage of change, counter conditioning, self-reevaluation, environment and technology use. Indirect associations (two-step neighbourhood) were identified for 40 (out of 44) variables, implying that most of the known PA-correlates are associated with PA-at least indirectly.

Conclusion: These identified associations echo the importance of the multilevel perspective in understanding how people maintain (in)active lifestyles. Interventions for PA could have mixed-level targets, including intraindividual characteristics, social support and physical and digital environments.

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来源期刊
CiteScore
7.10
自引率
4.20%
发文量
106
审稿时长
20 weeks
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