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在体力活动和久坐行为研究中,将时间使用构成作为因变量进行分析:不同的成分数据分析方法。

Analysing time-use composition as dependent variables in physical activity and sedentary behaviour research: different compositional data analysis approaches.

作者信息

von Rosen Philip

机构信息

Department of Neurobiology, Care Sciences, and Society (NVS) Division of Physiotherapy, Karolinska Institutet, Alfred Nobels Allé 23, Huddinge, SE-141 83, Sweden.

出版信息

J Act Sedentary Sleep Behav. 2023 Nov 2;2(1):23. doi: 10.1186/s44167-023-00033-5.

Abstract

Recently, there has been a paradigm shift from considering physical activity and sedentary behaviour as "independent" risk factors of health to acknowledging their co-dependency and compositional nature. The focus is now on how these behaviours relate to each other rather than viewing them in isolation. Compositional data analysis (CoDA) is a methodology that has been developed specifically for compositional data and the number of publications using CoDA in physical activity and sedentary behaviour research has increased rapidly in the past years. Yet, only a small proportion of the published studies in physical activity and sedentary behaviour research have investigated the time-use composition as dependent variables. This could be related to challenges regarding the interpretation of the results and the lack of guidelines for deciding which statistical approach to use. Therefore, in this paper, four different approaches for analysing the time-use composition as dependent variables are presented and discussed. This paper advocates that the aim of research should guide how the dependent variable is defined and which data analysis approach is selected, and it encourages researchers to consider analysing time-use components as dependent variables in physical activity and sedentary behaviour research.

摘要

最近,出现了一种范式转变,即从将身体活动和久坐行为视为健康的“独立”风险因素,转变为认识到它们的相互依存性和构成性质。现在的重点是这些行为如何相互关联,而不是孤立地看待它们。成分数据分析(CoDA)是一种专门为成分数据开发的方法,在过去几年中,在身体活动和久坐行为研究中使用CoDA的出版物数量迅速增加。然而,在身体活动和久坐行为研究中,只有一小部分已发表的研究将时间使用构成作为因变量进行了调查。这可能与结果解释方面的挑战以及缺乏关于选择哪种统计方法的指导方针有关。因此,本文提出并讨论了四种将时间使用构成作为因变量进行分析的不同方法。本文主张研究目的应指导因变量的定义方式以及选择哪种数据分析方法,并鼓励研究人员在身体活动和久坐行为研究中考虑将时间使用成分作为因变量进行分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9285/11960251/8fd59915245c/44167_2023_33_Fig1_HTML.jpg

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