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浙江大学学报(医学版)  2021, Vol. 50 Issue (6): 741-747    DOI: 10.3724/zdxbyxb-2021-0296
2019冠状病毒病     
2019冠状病毒病爆发期间城市居民午睡与抑郁情绪的关系研究
林文慧1,白冠男2,何威1,杨菲1,李伟1,闵燕3,LU Ying4,HSING Ann3,朱善宽1,*()
1.浙江大学公共卫生学院,浙江 杭州 310058
2.浙江大学医学院附属儿童医院 国家儿童健康与疾病临床医学研究中心 国家儿童区域医疗中心,浙江 杭州 310052
3.美国斯坦福大学医学院流行病学与人口健康学系,美国 斯坦福 94305
4.美国斯坦福大学医学院生物医学数据科学系,美国 斯坦福 94305
Association between napping status and depressive symptoms in urban residents during the COVID-19 epidemic
LIN Wenhui1,BAI Guannan2,HE Wei1,YANG Fei1,LI Wei1,MIN Yan3,LU Ying4,HSING Ann3,ZHU Shankuan1,*()
1. School of Public Health, Zhejiang University, Hangzhou 310058, China;
2. Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Hangzhou 310052, China;
3. Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford 94305, USA;
4. Department of Biomedical Data Science, Stanford University School of Medicine, Stanford 94305, USA
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摘要:

目的:探索2019冠状病毒病(COVID-19)爆发期间城市居民午睡与抑郁情绪的关系,为突发公共卫生事件期间城市居民抑郁情绪的预防提供科学依据。方法:基于WELL中国队列人群,于2020年4月8日至2020年5月29日通过电话访谈获取COVID-19爆发期间被调查者的健康与生活方式信息,最终纳入3075名18~80岁杭州市拱墅区城市居民的调查资料。采用世界卫生组织五项身心健康指标测量抑郁情绪,多元logistic回归模型分析调查对象午睡状况与抑郁情绪的关系。结果:COVID-19爆发期间约有20.6%的城市居民出现抑郁情绪;在一般人群中,有午睡行为尤其是午睡时长不超过30?min与抑郁情绪发生风险(OR=0.61,95%CI:0.47~0.79,P<0.01)、新发抑郁情绪风险(OR=0.66,95%CI:0.50~0.88,P<0.01)较低相关;在有抑郁情绪的城市居民中,仅午睡时长不超过30?min有利于抑郁情绪改善(OR=0.42,95%CI:0.21~0.82,P<0.05)。结论:2019冠状病毒病爆发期间,约有1/5的城市居民存在抑郁情绪,短时间的午睡可能是抑郁情绪的保护因素。

关键词: 2019冠状病毒病抑郁情绪午睡城市居民队列研究    
Abstract:

Objective: To explore the association between napping status and depressive symptoms in urban residents during the coronavirus disease 2019 (COVID-19) epidemic. Methods: The survey was embedded in the Wellness Living Laboratory-China (WELL China) cohort study. Health and lifestyle information during the COVID-19 epidemic were obtained via the telephone interview from April 8, 2020 to May 29, 2020. A total of 3075 residents aged 18 to 80?years from Gongshu district of Hangzhou city with complete data were included in the analyses. The World Health Organization-Five Well-being Index (WHO-5) was used to measure depressive symptoms. Multiple logistic regression model was used to assess the association between napping status and depressive symptoms in the participants. Results: The prevalence of depressive symptoms was 20.6% in the participants during the COVID-19 epidemic. Daytime napping behavior, especially napping time ≤30?min, was associated with a lower risk of prevalent depressive symptoms (OR=0.61, 95%CI: 0.47–0.79, P<0.01) and incident depressive symptoms in the population (OR=0.66, 95%CI: 0.50–0.88, P<0.01). Among those with depressive symptoms at baseline, napping time ≤ 30?min was beneficial for the outcome of depressive symptoms (OR=0.42, 95%CI: 0.21–0.82, P<0.05).Conclusion: One in five urban residents have depressive symptoms during the COVID-19 epidemic, and a short nap during the day may be a protective factor against depressive symptoms.

Key words: Coronavirus disease 2019    Depressive symptoms    Daytime napping    Urban residents    Cohort study
收稿日期: 2021-09-27 出版日期: 2022-03-22
CLC:  R183.3  
基金资助: 纽崔莱斯坦福大学WELL项目基金(519000-X11501);浙江大学教育基金(100000-11320);唐仲英基金(419600-11102);Hsun K Chou基金(419600-11107)
通讯作者: 朱善宽     E-mail: zsk@zju.edu.cn
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引用本文:

林文慧,白冠男,何威,杨菲,李伟,闵燕,LU Ying,HSING Ann,朱善宽. 2019冠状病毒病爆发期间城市居民午睡与抑郁情绪的关系研究[J]. 浙江大学学报(医学版), 2021, 50(6): 741-747.

LIN Wenhui,BAI Guannan,HE Wei,YANG Fei,LI Wei,MIN Yan,LU Ying,HSING Ann,ZHU Shankuan. Association between napping status and depressive symptoms in urban residents during the COVID-19 epidemic. J Zhejiang Univ (Med Sci), 2021, 50(6): 741-747.

链接本文:

https://www.zjujournals.com/med/CN/10.3724/zdxbyxb-2021-0296        https://www.zjujournals.com/med/CN/Y2021/V50/I6/741

变量

总人群(n=3075)

有无午睡

χ2/t

P

无(n=1702)

有(n=1373)

平均年龄(岁)

56 ± 13

54 ± 13

58± 13

–7.787

< 0.01

年龄分布(岁)18~<45

590 (19.2)

371 (21.8)

219 (16.0)

61.285

< 0.01

45~<60

1140 (37.1)

693 (40.7)

447 (32.6)

?

≥60

1345 (43.7)

638 (37.5)

707 (51.5)

?

性别构成男性

1158 (37.7)

576 (33.8)

582 (42.4)

23.643

< 0.01

女性

1917 (62.3)

1126 (66.2)

791 (57.6)

?

文化程度小学及以下

642 (20.9)

346 (20.3)

296 (21.6)

6.710

< 0.05

初中/高中

1767 (57.5)

958 (56.3)

809 (58.9)

?

大专、本科及以上

666 (21.7)

398 (23.4)

268 (19.5)

?

婚姻状况已婚/再婚

2746 (89.3)

1524 (89.5)

1222 (89.0)

0.231

>0.05

未婚/离婚/丧偶

329 (10.7)

178 (10.5)

151 (11.0)

?

慢性病史无

1119 (36.4)

668(39.2)

451 (32.8)

13.448

< 0.01

1956 (63.6)

1034 (60.8)

922 (67.2)

?

COVID-19爆发前BMI(kg/m2

23.9 ± 3.2

23.9 ± 3.2

23.9 ± 3.2

0.065

>0.05

COVID-19爆发前有无午睡无

1616 (52.6)

1185 (69.6)

431 (31.4)

445.500

< 0.01

1459 (47.4)

517 (30.4)

942 (68.6)

?

COVID-19爆发前抑郁情绪无

2655 (86.3)

1462 (85.9)

1193 (86.9)

0.633

>0.05

420 (13.7)

240 (14.1)

180 (13.1)

?

COVID-19爆发期间抑郁情绪无

2442 (79.4)

1313 (77.1)

1129 (82.2)

12.016

< 0.01

633 (20.6)

389 (22.9)

244 (17.8)

?

COVID-19爆发期间夜间睡眠质量很好

1111 (36.1)

641 (37.7)

470 (34.2)

9.463

< 0.05

较好

1547 (50.3)

821 (48.2)

726 (52.9)

?

较差

358 (11.6)

200 (11.8)

158 (11.5)

?

很差

59 (1.9)

40 (2.4)

19 (1.4)

?

COVID-19爆发期间夜间睡眠 时长(h)

7.1 ± 1.3

7.2 ± 1.3

7.0 ± 1.3

3.965

< 0.01

表 1  调查对象一般情况及COVID-19爆发期间午睡状况分布

变量

模型1

模型2

模型3

OR (95%CI

P

OR (95%CI

P

OR (95%CI

P

有无午睡无

1.00

1.00

1.00

0.75 (0.62~0.90)

< 0.01

0.73 (0.60~0.89)

< 0.01

0.72 (0.59~0.88)

< 0.01

午睡时长(min)0

1.00

1.00

1.00

≤30

0.63 (0.49~0.80)

< 0.01

0.62 (0.48~0.80)

< 0.01

0.61 (0.47~0.79)

< 0.01

>30~60

0.81 (0.63~1.03)

> 0.05

0.79 (0.61~1.02)

> 0.05

0.78 (0.60~1.01)

> 0.05

> 60

1.09 (0.75~1.59)

> 0.05

1.08 (0.73~1.58)

> 0.05

1.02 (0.69~1.51)

> 0.05

表 2  2019冠状病毒病爆发期间居民午睡状况与抑郁情绪的多元logistic回归分析结果

变量

模型1

模型2

模型3

OR (95%CI

P

OR (95%CI

P

OR (95%CI

P

有无午睡无

1.00

1.00

1.00

0.75 (0.61~0.91)

<0.01

0.76 (0.61~0.94)

<0.05

0.75 (0.60~0.93)

<0.05

午睡时长(min)0

1.00

1.00

1.00

≤30

0.67 (0.51~0.87)

<0.01

0.67 (0.51~0.88)

<0.01

0.66 (0.50~0.88)

<0.01

>30~60

0.77 (0.59~1.02)

>0.05

0.78 (0.59~1.04)

>0.05

0.78 (0.58~1.04)

>0.05

> 60

1.02 (0.67~1.56)

>0.05

1.06 (0.69~1.64)

>0.05

1.00 (0.64~1.56)

>0.05

表 3  2019冠状病毒病爆发期间午睡状况与新发抑郁情绪的多元logistic回归分析结果

变量

模型1

模型2

模型3

OR(95%CI

P

OR (95%CI

P

OR (95%CI

P

有无午睡无

1.00

1.00

1.00

0.74 (0.47~1.17)

>0.05

0.67 (0.42~1.08)

>0.05

0.64 (0.39~1.05)

>0.05

午睡时长(min)0

1.00

1.00

1.00

≤30

0.46 (0.24~0.88)

<0.05

0.43 (0.22~0.83)

<0.05

0.42 (0.21~0.82)

<0.05

>30~60

0.95 (0.52~1.73)

>0.05

0.85 (0.46~1.60)

>0.05

0.81 (0.42~1.53)

>0.05

> 60

1.29 (0.55~3.00)

>0.05

1.16 (0.49~2.75)

>0.05

1.11 (0.46~2.67)

>0.05

表 4  2019冠状病毒病爆发期间午睡状况与持续抑郁情绪的多元logistic回归分析结果
1 XUS, LIY. Beware of the second wave of COVID-19[J]Lancet, 2020, 395( 10233): 1321-1322.
doi: 10.1016/S0140-6736(20)30845-X
2 HOSSAINM M, TASNIMS, SULTANAA, et al.Epidemiology of mental health problems in COVID-19: a review[J]F1000Res, 2020, 636.
doi: 10.12688/f1000research.24457.1
3 XIONGJ, LIPSITZO, NASRIF, et al.Impact of COVID-19 pandemic on mental health in the general population: a systematic review[J]J Affective Disord, 2020, 55-64.
doi: 10.1016/j.jad.2020.08.001
4 AFONSOP, FONSECAM, TEODOROT. Evaluation of anxiety, depression and sleep quality in full-time teleworkers[J]J Public Health, 2021, online,
doi: 10.1093/pubmed/fdab164
5 MISHRAR, PARKC, YORKM K, et al.Decrease in mobility during the COVID-19 pandemic and its association with increase in depression among older adults: a longitudinal remote mobility monitoring using a wearable sensor[J]Sensors, 2021, 21( 9): 3090.
doi: 10.3390/s21093090
6 AL MUTAIRA, AL MUTAIRIA, AMBANIZ, et al.The impact of COVID-19 pandemic on the level of depression among health care workers: cross-sectionalstudy[J/OL]PeerJ, 2021, e11469.
doi: 10.7717/peerj.11469
7 MILNERC E, COTEK A. Benefits of napping in healthy adults: impact of nap length, time of day, age, and experience with napping[J]J Sleep Res, 2009, 18( 2): 272-281.
doi: 10.1111/j.1365-2869.2008.00718.x
8 DHAND R, SOHAL H. Good sleep, bad sleep! The role of daytime naps in healthy adults[J]. Curr Opin Pulm Med, 2006, 12(6): 379-382
9 TIETZELA J, LACKL C. The recuperative value of brief and ultra-brief naps on alertness and cognitive performance[J]J Sleep Res, 2002, 11( 3): 213-218.
doi: 10.1046/j.1365-2869.2002.00299.x
10 BROOKSA, LACKL. A brief afternoon nap following nocturnal sleep restriction: which nap duration is most recuperative?[J]Sleep, 2006, 29( 6): 831-840.
doi: 10.1093/sleep/29.6.831
11 MINY, ZHAOX, STAFFORDR S, et al.Cohort Profile: WELL living laboratory in China (WELL-China)[J]Int J Epidemiol, 2021, 50( 5): 1432-1443.
doi: 10.1093/ije/dyaa283
12 世界卫生组织. WHO 世界卫生组织五项身心健康指标(1998年版)[EB/OL]. [2021-07-12]. https://www.psykiatri-regionh.dk/who-5/Documents/WHO5_Chinese_PR.pdf
World Health Organization. WHO-Five Well-Being Index(1998 edition)[EB/OL]. [2021-07-12]. https://www.psykiatri-regionh.dk/who-5/Documents/WHO5_Chinese_PR. pdf. (in Chinese)
13 TOPPC W, ?STERGAARDS D, S?NDERGAARDS, et al.The WHO-5 Well-Being Index: a systematic review of the literature[J]Psychother Psychosom, 2015, 84( 3): 167-176.
doi: 10.1159/000376585
14 SHI L, LU Z A, QUE J Y, et al. Prevalence of and risk factors associated with mental health symptoms among the general population in China during the coronavirus disease 2019 pandemic[J/OL]. JAMA Netw Open, 2020, 3(7): e2014053
15 LIUY, PENGT, ZHANGS, et al.The relationship between depression, daytime napping, daytime dysfunction, and snoring in 0.5 million Chinese populations: exploring the effects of socio-economic status and age[J]BMC Public Health, 2018, 18( 1): 759.
doi: 10.1186/s12889-018-5629-9
16 THEADOMA, CROPLEYM, KANTERMANNT. Daytime napping associated with increased symptom severity in fibromyalgia syndrome[J]BMC Musculoskelet Disord, 2015, 16( 1): 13.
doi: 10.1186/s12891-015-0464-y
17 黄满仙, 沈郁, 夏木斯叶·木依都力, 等. 孕早期午睡和夜间睡眠质量对焦虑抑郁的关联研究[J]. 中国妇幼保健, 2020, 35(10): 1781-1785
HUANG Manxian, SHEN Yu, XIAMUSIYE Muyiduli, et al. Study on the correlations between the quality of afternoon nap, nocturnal sleep during the first trimester of pregnancy and anxiety, depression[J]. Maternal and Child Health Care of China, 2020, 35(10): 1781-1785. (in Chinese)
18 TAMAKIM, SHIROTAA, TANAKAH, et al.Effects of a daytime nap in the aged[J]Psychiatry Clin Neuroscis, 1999, 53( 2): 273-275.
doi: 10.1046/j.1440-1819.1999.00548.x
19 CHELLAPPAS L, SCHR?DERC, CAJOCHENC. Chronobiology, excessive daytime sleepiness and depression: Is there a link?[J]Sleep Med, 2009, 10( 5): 505-514.
doi: 10.1016/j.sleep.2008.05.010
20 LAGROTTEC, FERNANDEZ-MENDOZAJ, CALHOUNS L, et al.The relative association of obstructive sleep apnea, obesity and excessive daytime sleepiness with incident depression: a longitudinal, population-based study[J]Int J Obes, 2016, 40( 9): 1397-1404.
doi: 10.1038/ijo.2016.87
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