Background: Analyzing actigraphy data using standard circadian parametric models and aggregated nonparametric indices may obscure temporal information that may be a hallmark of the circadian impairment in psychiatric disorders. Functional data analysis (FDA) may overcome such limitations by fully exploiting the richness of actigraphy data and revealing important relationships with mental health outcomes. To our knowledge, no studies have extensively used FDA to study the relationship between sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics and daily motor activity patterns assessed with actigraphy in a sample of individuals with and without depression/anxiety. Objective: We aimed to study the association between daily motor activity patterns assessed via actigraphy and (1) sociodemographic, health and lifestyle, and sampling factors, and (2) psychiatric clinical characteristics (ie, presence and severity of depression/anxiety disorders). Methods: We obtained 14-day continuous actigraphy data from 359 participants from the Netherlands Study of Depression and Anxiety with current (n=93), remitted (n=176), or no (n=90) depression/anxiety diagnosis, based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition. Associations between patterns of daily motor activity, quantified via functional principal component analysis (fPCA), and sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics were assessed using generalized estimating equation regressions. For exploratory purposes, function-on-scalar regression (FoSR) was applied to quantify the time-varying association of sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics on daily motor activity. Results: Four components of daily activity patterns captured 77.4% of the variability in the data: overall daily activity level (fPCA1, 34.3% variability), early versus late morning activity (fPCA2, 16.5% variability), biphasic versus monophasic activity (fPCA3, 14.8% variability), and early versus late biphasic activity (fPCA4, 11.8% variability). A low overall daily activity level was associated with a number of sociodemographic, health and lifestyle, and psychopathology variables: older age (P<.001), higher education level (P=.005), higher BMI (P=.009), greater number of chronic diseases (P=.02), greater number of cigarettes smoked per day (P=.02), current depressive and/or anxiety disorders (P=.05), and greater severity of depressive symptoms (P<.001). A high overall daily activity level was associated with work/school days (P=.02) and summer (reference: winter; P=.03). Earlier morning activity was associated with older age (P=.02), having a partner (P=.009), work/school days (P<.001), and autumn and spring (reference: winter; P=.02 and P<.001, respectively). Monophasic activity was associated with older age (P=.005). Biphasic activity was associated with work/school days (P<.001) and summer (reference: winter; P<.001). Earlier biphasic activity was associated with older age (P=.005), work/school days (P<.001), and spring and summer (reference: winter; P<.001 and P=.005, respectively). In FoSR analyses, age, work/school days, and season were the main determinants having a time-varying association with daily motor activity (all P<.05). Conclusions: Features of daily motor activity extracted with fPCA reflect commonly studied factors such as the intensity of daily activity and preference for morningness/eveningness. The presence and severity of depression/anxiety disorders were found to be associated mainly with a lower overall activity pattern but not with the time of the activity. Age, work/school days, and season were the variables most strongly associated with patterns and time of activity, and thus future epidemiological studies on motor activity in depression/anxiety should take these variables into account.

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中文翻译：

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24小时运动活动模式的社会人口统计学，健康和生活方式，抽样和心理健康决定因素：观察性研究

背景：使用标准的昼夜节律参数模型和汇总的非参数索引分析书法数据可能会模糊时间信息，这可能是精神疾病中昼夜节律障碍的标志。功能数据分析（FDA）可以通过充分利用书法数据的丰富性并揭示与心理健康结果的重要关系来克服此类限制。据我们所知，没有研究广泛地使用FDA来研究在有或没有抑郁/焦虑症的个体中，社会人口统计学，健康和生活方式，抽样和精神病学临床特征与通过行为描记法评估的每日运动活动模式之间的关系。目的：我们旨在研究通过书法记录评估的日常运动活动模式与（1）社会人口统计学，健康和生活方式，以及抽样因素，以及（2）精神科的临床特征（即抑郁症/焦虑症的存在和严重程度）。方法：我们从荷兰抑郁和焦虑研究的359名参与者中获得了14天连续体动描记数据，当前为（n = 93），已缓解（n = 176）或没有（n = 90）抑郁/焦虑诊断，基于精神疾病诊断和统计手册，第四版的标准。使用广义估计方程回归评估通过功能性主成分分析（fPCA）量化的日常运动活动模式与社会人口统计学，健康和生活方式，抽样以及精神病学临床特征之间的关联。出于探索目的，标量函数回归（FoSR）用于量化社会人口统计学，健康和生活方式，抽样以及每日运动活动的精神病学临床特征随时间变化的关联。结果：日常活动模式的四个组成部分捕获了数据中77.4％的变化：总体日常活动水平（fPCA1，变化34.3％），早晚活动（fPCA2，变化16.5％），双相与单相活动（fPCA3， 14.8％的变异性）以及早期和晚期双相活动（fPCA4，11.8％的变异性）。总体活动水平低与许多社会人口统计学，健康和生活方式以及心理病理学变量有关：年龄较大（P <.001），高等教育水平（P = .005），BMI较高（P = .009），更多的慢性病（P = .02），每天吸烟的卷烟数量更多（P = .02），当前的抑郁和/或焦虑症（P = .05）以及抑郁症状的严重程度更高（P <.001）。较高的总体日常活动水平与工作/上学日（P = .02）和夏季（参考：冬季； P = .03）相关。较早的活动与年龄较大（P = .02），有伴侣（P = .009），工作/上学日（P <.001）和秋季和春季（参考：冬季； P = .02和P <.001）。单相活动与年龄较大有关（P = .005）。双相活动与工作/上学日（P <.001）和夏季（参考：冬季； P <.001）相关。早期的双相活动与年龄较大（P = .005），工作/上学日（P <.001）以及春季和夏季（参考：冬季；分别为P <.001和P = .005）相关。在FoSR分析中，年龄，工作/上学日和季节是与每日运动活动之间存在时变关联的主要决定因素（所有P <.05）。结论：用fPCA提取的日常运动活动的特征反映了经常研究的因素，例如日常活动的强度和对早晨/晚上的偏好。发现抑郁症/焦虑症的存在和严重程度主要与较低的总体活动模式有关，但与活动时间无关。年龄，工作/上学日和季节是与活动方式和时间最相关的变量，因此，未来有关抑郁/焦虑中的运动活动的流行病学研究应考虑这些变量。用fPCA提取的日常运动活动的特征反映了常用的因素，例如日常活动的强度和对早晨/晚上的偏爱。发现抑郁症/焦虑症的存在和严重程度主要与较低的总体活动模式有关，但与活动时间无关。年龄，工作/上课日和季节是与活动方式和时间最相关的变量，因此，未来有关抑郁/焦虑中的运动活动的流行病学研究应考虑这些变量。用fPCA提取的日常运动活动的特征反映了常用的因素，例如日常活动的强度和对早晨/晚上的偏爱。发现抑郁症/焦虑症的存在和严重程度主要与较低的总体活动模式有关，但与活动时间无关。年龄，工作/上学日和季节是与活动方式和时间最相关的变量，因此，未来有关抑郁/焦虑中的运动活动的流行病学研究应考虑这些变量。发现抑郁症/焦虑症的存在和严重程度主要与较低的总体活动模式有关，但与活动时间无关。年龄，工作/上学日和季节是与活动方式和时间最相关的变量，因此，未来有关抑郁/焦虑中的运动活动的流行病学研究应考虑这些变量。发现抑郁症/焦虑症的存在和严重程度主要与较低的总体活动模式有关，但与活动时间无关。年龄，工作/上学日和季节是与活动方式和时间最相关的变量，因此，未来有关抑郁/焦虑中的运动活动的流行病学研究应考虑这些变量。

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