研究生: |
黃婉綺 Huang, Wan-Chi |
---|---|
論文名稱: |
成年人睡眠型態與身體活動和靜態行為之關聯性研究 Association of Sleep Pattern with Physical Activity and Sedentary Behavior in Adults |
指導教授: |
廖邕
Liao, Yung |
口試委員: |
楊建銘
Yang, Chien-Ming 李子奇 Lee, Charles Tzu-Chi 薛名淳 Hsueh, Ming-Chun 廖邕 Liao, Yung |
口試日期: | 2022/01/19 |
學位類別: |
碩士 Master |
系所名稱: |
健康促進與衛生教育學系 Department of Health Promotion and Health Education |
論文出版年: | 2022 |
畢業學年度: | 110 |
語文別: | 英文 |
論文頁數: | 109 |
中文關鍵詞: | 加速規 、久坐 、睡眠變動性 、社交時差 |
英文關鍵詞: | accelerometer, prolonged sitting, sleep variability, social jet lag |
研究方法: | 觀察研究 |
DOI URL: | http://doi.org/10.6345/NTNU202200689 |
論文種類: | 學術論文 |
相關次數: | 點閱:192 下載:19 |
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研究目的:目前已有文獻探討成年人的睡眠與其靜態行為及身體活動時間之關係,然過去研究多數針對一至二項睡眠指標進行探討,且較少研究有討論睡眠與靜態行為時間的關係,再者工作成年人和高齡者的族群特徵可能會影響到睡眠和身體活動、靜態行為的關係,但是僅有有限的證據是對這兩個族群進行討論;因此,本研究旨在探討工作成年人和高齡者中,不同面向的睡眠指標(長度、時間點及規律性)與靜態行為及身體活動時間是否有關聯性,並進一步討論當晚睡眠和隔日醒來後靜態行為及身體活動時間的關係。參與者和研究方法:在高齡者族群,本研究於2020年8月至2021年8月招募正常認知功能且具獨立行走能力者參加,共136名高齡者(平均年齡: 80.01 ± 7.23歲)納入本研究;此外,本研究亦於2019年8月至2020年12月針對工作成年人進行招募,最後納入192名員工 (平均年齡: 38.56 ± 8.89歲)的資料進行分析。研究工具使用三軸加速規(GT3X+ ActiGraph)進行靜態行為、輕度身體活動和中高強度身體活動時間的測量,期間受試者需記錄每日睡眠時間(起床及就寢時間),依照其記錄作為各項睡眠指標的計算基準,本研究之睡眠型態指標如下包含睡眠長度、睡眠中間點、睡眠長度變動性和睡眠時間點變動性,再者,在工作成年人中會進一步測量社交時差。本研究運用線性迴歸針對平均睡眠型態和睡眠規律性與結果變項(靜態行為及身體活動時間)之關係進行分析,廣義估計方程式(generalized estimating equations, GEE)則應用於分析每日睡眠型態和各項清醒行為時間之關聯性。結果:高齡者族群樣本中研究結果顯示如下:(1)平均睡眠狀況:睡眠長度與靜態行為時間呈負向關係(B= -25.69;p = 0.001),與輕度身體活動則是呈現正向關係(B= 23.17;p = 0.001);(2)睡眠規律性:睡眠長度及睡眠時間點變動性皆未發現顯著關聯性:(3)每日睡眠型態:當晚的睡眠中間點較晚,與清醒後當天較少的中高強度身體活動時間有關(p = 0.024)。在工作成年人中,研究結果指出:(1)平均睡眠狀況:較遲的平均睡眠中間點與靜態行為時間具有正向關聯性(B= 0.20;p = 0.048);(2)睡眠規律性:睡眠長度變動性越大與較多的輕度身體活動時間有關(B= 0.32;p = 0.038),較大的社交時差與較多的靜態行為時間(B= 0.24;p = 0.005)和較少的輕度身體活動時間(B= -0.19; p = 0.016)有關;(3)每日睡眠型態:當晚較長的睡眠長度(p = 0.026)和較遲的睡眠中間點(p = 0.029),皆與清醒後較少的中高強度身體活動時間有關聯性。結論:本研究發現高齡者與工作成年人的睡眠型態與靜態行為和身體活動時間的關係,且兩個族群的結果顯示不盡相同,據此,本研究結果可提供設計促進成年人動態生活型態介入作為參考,並建議依據不同年齡族群特性制定合適的方案,在高齡者族群中,建議以適當地增加平均睡眠長度和維持每晚較早的睡眠時間點進行介入,而針對有工作的成年人,則是建議減少社交時差和提早睡眠時間點的策略。
Purpose: Some previous research has investigated associations of sleep pattern with sedentary behavior (SB) time and physical activity (PA) time in adults. However, most studies only investigated the relationship with one or two sleep indicators and only a few of them discussed associations with SB time. Besides, limited studies investigate the relationship in adults with regular work schedule and older adults while the characteristics of the two groups might influence sleep-PA and sleep-SB relationship. Therefore, the research aimed to examine whether sleep pattern (duration, timing, and regularity) is associated with SB/PA time, as well as investigate the daily relationship between nighttime sleep and SB/PA on the following day in older adults and working adults.
Methods: A total of 136 older adults without cognitive impairment (age: 80.01 ± 7.23 years) and able to walk independently were recruited from August 2020 to August 2021, and data of 192 working adults (age: 38.56 8.89 years) was collected from August 2019 to December 2020. Triaxial accelerometers (Actigraph wGT3x-BT) were used to assess time spent on SB, light-intensity physical activity (LPA), and moderate-to-vigorous intensity physical activity (MVPA). Daily bedtime and wake up time were recorded by each participant. According to sleep records, indicators of sleep were calculated, including sleep duration, mid-sleep time, and sleep variability. Besides, social jet lag was measured in working adults for examining the relationship. Linear regression was applied to examine the associations of average sleep pattern and sleep regularity with SB/LPA/MVPA time, and GEE models were conducted for the daily relationship between nighttime sleep and SB/LPA/MVPA time on the following day.
Results: In older adults, the results were listed as follows; (1) average sleep pattern: a negative association was found between average sleep duration and SB time (B= -25.69, p = 0.001), while longer sleep duration in average was related to more LPA time (B = 23.17, p = 0.001) after adjusting for covariates; (2) sleep regularity: no evidence revealed associations between indicators of sleep variability and SB/LPA/MVPA time; (3) nighttime sleep and following SB/LPA/MVPA time: later mid-sleep time at previous night was shown an association with spending less time on MVPA on the following day (p = 0.024). Additionally, some findings in working adults was demonstrated; (1) average sleep pattern: later mid-sleep time in average was related to more SB time (B = 0.20, p = 0.048); (2) sleep regularity: greater social jet lag was associated with more SB time (B = 0.24, p = 0.005) and less LPA time (B = -0.19, p = 0.016), as well as an positive association was found between variability in sleep duration and LPA time (B = 0.32, p = 0.038); (3) nighttime sleep and following SB/LPA/MVPA time: longer nighttime sleep duration (p = 0.026) and delayed mid-sleep time (p = 0.029) at night was linked to decreased MVPA time on the following day.
Conclusion: The present study observed relationships between sleep pattern and SB/PA time in older adults and working adults, as some associations might be inconsistent in different adult groups. Accordingly, these results provided some evidence for developing sleep-related strategies for promoting active life as well as decreasing sedentary behavior in adults. Specialized interventions based on the characteristics of adult group. In older adults, increasing average sleep duration in appropriate range and maintaining earlier night-to-night sleep timing were suggested. In working adults, interventions for decreasing social jet lag and advancing sleep timing were recommended.
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