Skip to main content
Journal of Central South University Medical Sciences logoLink to Journal of Central South University Medical Sciences
. 2023 Apr 28;48(4):621–627. [Article in Chinese] doi: 10.11817/j.issn.1672-7347.2023.220544

老年人睡眠与衰弱双轨迹

Dual trajectory of sleep and frail in elderly people

ZHENG Yu 1,2, ZHOU Bingqian 1, GONG Ni 2,, CHEN Xingli 1
Editor: 田 朴
PMCID: PMC10930250  PMID: 37385626

Abstract

The high incidence of dual sleep and frail disorders in the elderly people, often occurring together, seriously affects the physical and mental health of the older people, effective research on the dynamics of dual sleep and frail disorders is important for improving the quality of life for the older people and responding to global ageing trend. While trajectory studies provide a unique practical scientific perspective to grasp the dynamics of development, dual trajectories unite dual barriers provide an opportunity to study the dynamic dependence of both sleep and frailty simultaneously sleep trajectories and frailty trajectories in older people are interrelated and interacted through deeper mechanisms. Therefore, it is necessary for the study not only focus on the ongoing development of health problems, but also needs to consider multiple aspects and propose targeted intervention program.

Keywords: older people, sleep, frail, dual trajectory


随着社会不断发展,人口老龄化已成为全球面临的重大公共卫生问题。据世界卫生组织报告,2050年中国老年人口将达4亿,高龄人口不断增加[1]。随着年龄的增长,睡眠与衰弱相关问题逐渐凸显,衰弱是与衰老相关的生理储备的多维度下降,使机体对外界应激能力减弱,导致认知功能下降、抑郁发生率增加、病死率升高等负面健康结果[2]。研究[3]显示中国老年人群衰弱患病率为12.8%~44.3%,高于亚洲总体老年人衰弱患病率(20.5%)[4]。老年人群是睡眠障碍的高发人群,发生率高达50.0%[5],包括慢性失眠、白天嗜睡等,可导致记忆力下降、易激惹、抑郁焦虑风险增加等不良结局。睡眠障碍随衰弱程度的加重而恶化[6]。目前鲜有学者研究二者之间的动态发展关系,且多集中于横断面研究,故有必要探索睡眠与衰弱之间动态发展的相互依存关系,将睡眠轨迹与衰弱轨迹纳入研究范围,以揭示睡眠与衰弱之间多维的依存关系,也有助于准确地评估老年人日益增长的健康保健需求。总结睡眠与衰弱双轨迹的研究进展具有重要意义。

1. 健康轨迹概述

1.1. 健康轨迹的定义与内涵

健康轨迹是指随时间推移的健康模式,时间是健康轨迹研究中的基本预测变量,而健康指标是作为时间的函数进行绘制和建模的主要对象[7]。随着时间的推移,健康受遗传、生物、行为、社会、文化、环境、政治和经济环境中的多种因素影响,这些因素随着人群的发展而不断变化[8]。了解随时间推移健康变化的过程和原因,掌握发展的规律,可以预测不良结果的轨迹和事件风险的易感人群。

1.2. 健康轨迹模式

常用的轨迹分析方法包括生长混合模型(growth mixture modelling,GMM)、基于组轨迹模型(group-based trajectory modelling,GBTM)、潜在类别分析(latent class analysis,LCA)和潜在转移分析(latent transition analysis,LTA)。一项对该4种方法进行比较的研究[9]显示:GMM适合连续纵向数据,GBTB适合连续、分类纵向数据,LTA适合分类纵向数据,而LCA适合横断面分类数据。

1.3. 健康轨迹分析方法

GBTM能够识别目标群体结局指标中不同的发展轨迹,研究轨迹与影响因素或结局间的联系。GBTM的双轨迹及多轨迹模型可以探索2个或多个纵向数据变量之间的关系。首先对每个单独的变量进行轨迹分析,建立轨迹模型,然后通过不同变量轨迹之间的两两关联概率使轨迹之间的关系可视化[10-11]。该方法允许数据之间存在异质性,无需整个样本遵循单一轨迹的假设,且该数据驱动的方法可识别随时间推移变化模式相似的集群[12]

2. 睡眠轨迹与衰弱轨迹

关于睡眠轨迹与衰弱轨迹的研究是指对个人、家庭、群体等维度下老年人群睡眠质量与衰弱状态随时间变化的纵向调查[13],主要表现为以时间为横轴,以睡眠质量、衰弱状态为纵轴的函数模型,即老年人群在自然状态下健康状况的动态变化,检视睡眠与衰弱的动态变化将帮助阐明老年共病机制,为应对逐年加剧的老年共病态势提供决策依据。

2.1. 睡眠轨迹的研究现状

睡眠主要由内稳态及昼夜节律机制介导,辅以环境因素[14],疾病和治疗相关因素将影响睡眠的变化方向[15]。Gebara等[16]采用GBTM拟合680名抑郁症老年人的睡眠评分,拟合持续最小睡眠障碍、睡眠障碍消退、中度持续睡眠障碍及严重持续睡眠障碍等5条轨迹,并指出通过给予相应干预措施可改善睡眠状况,将低质量的睡眠轨迹转化为高质量的睡眠轨迹,但并未具体描述,难以推广。而另一项研究[17]采用LCA模型拟合养老机构老年人睡眠评分,结果得到了睡眠良好、失眠加重、失眠改善、持续严重失眠4条轨迹,虽针对睡眠质量探索其纵向变化轨迹,但仅以睡眠质量为结局指标,忽略了机体伴随的其他健康问题,且睡眠质量测量工具与以往研究不同。此外,美国一项针对老年人群1周内睡眠轨迹的研究[18]分析不同睡眠模式与心血管疾病之间的关系,明晰睡眠模式变化过快可增加心血管疾病风险,但时间仅为1周,忽视了睡眠的长期变化特点。一项中国纵向健康长寿调查(Chinese longitudinal healthy longevity survey,CLHLS)的研究[19]表明睡眠持续时间增加的模式轨迹与轻微认知能力下降的发展轨迹有关,但尚未深入探索其作用机制。

综上,尽管上述有研究开始探索老年人群睡眠纵向发展模式,但仅从单一视角出发,得到不同发展趋势的睡眠轨迹,并未深入探讨,且指标测量工具、统计分析方法多种多样,尽管数据类型基本一致,仍然降低了研究之间的可比性。

2.2. 衰弱轨迹的研究现状

衰弱是一个动态发展的过程,本质上随年龄的增长衰弱状态加重,男女之间衰弱程度不一。由于与衰老、性别等因素相关的衰弱无法消除,延缓衰弱进展尤为重要。目前,横断面研究未能解释如何出于干预目的延迟或缓解衰弱过程,纵向数据及其模型的建立更适合于衰弱的实证研究[20]。一项纳入18项队列的荟萃分析[21]结果显示:老年人衰弱程度与死亡风险呈正相关,即衰弱程度越重,死亡风险越高,该研究以某时点衰弱状态老年人为研究对象,探索其后续结局,忽略了衰弱是各组织器官长期累积的结果,具有动态发展特点。北京市的一项调查[22]结果显示:老年人群基线衰弱患病率为23.0%,在2年内增加到41.8%,38.3%的老年人进展到更加严重的状态,仅8.6%的人衰弱状态改善。由此看出,老年人的衰弱是一个可逆转的过程,给予针对性干预措施或可有效减轻老年人衰弱程度甚至逆转衰弱[23]。衰弱指数是基于累积缺陷理论的老年人群衰弱评估体系,变化幅度随着年龄和衰弱程度的增加而增加,在妇女、社会经济地位低、教育程度较低和在随访期间死亡的人群中波动更大[24]。王宇[25]将GBTM模型与衰弱指数联合分析,结果显示:不同年龄组老年人衰弱轨迹不同,中高龄年龄组老年人存在3条异质性轨迹,高龄年龄组老年人存在4条异质性轨迹。

衰弱的动态变化逐渐引起学者重视,已陆续开展老年人衰弱轨迹的探索,然而目前衰弱轨迹研究仅限于探索年龄、性别等一般资料及认知能力、自理能力等影响衰弱轨迹变化趋势的因素,视角较单一。

2.3. 睡眠轨迹与衰弱轨迹之间的相互关系

系统深入地研究睡眠与衰弱之间动态依存关系,是制定干预老年共病趋势的前提基础。该方面研究成果有助于识别睡眠与衰弱纵向变化特点,挖掘依存变化的多维机制,确定睡眠轨迹与衰弱轨迹双向关系,可为后续老年共病机制研究提供决策依据。

2.3.1. 睡眠与衰弱的关联

相比年轻人,老年人更早醒来、经历更多的碎片化睡眠和白天嗜睡,与较低的睡眠效率有关[26]。一项希腊的大型横断面调查[27]显示与睡眠较好的老年人相比,睡眠障碍的老年人衰弱风险增加了2~4倍。在老年人群中,11%的老年人难以进入睡眠,6%难以维持睡眠,为老年人衰弱的危险关联因素[28]。老年群体生理储备能力及身体机能随着年龄的增长不断下降,可同时出现睡眠不佳、衰弱状态等健康事件。一项荟萃分析[29]显示失眠与老年人的衰弱状态呈正相关。另一项研究[30]表明慢性疼痛通过介导睡眠情况影响衰弱老年人的不良结局。以上研究均表明睡眠障碍与衰弱具有动态发展规律,且两者的相互作用主要是通过神经内分泌系统的过度激活(下丘脑-垂体-肾上腺轴)、增强的炎症反应(慢性炎症)及心理因素(抑郁、焦虑、恐惧等)等机制[31]。睡眠负责生物机体的代谢稳态、记忆维持及大脑功能[32],老年人衰弱与多种认知障碍之间的关系主要由睡眠障碍介导,包括回忆、执行功能等情况[33]。因此,睡眠障碍可使老年人身体机能休息、恢复等进程被阻滞或打断,机体各部分系统、机制未能得到充分持久的血液循坏供应,免疫、代谢等能力下降[34],从而显著加剧老年人群衰弱的严重程度。

2.3.2. 睡眠与衰弱双轨迹的发展

“双重障碍”较为常见,且衰弱与睡眠不佳经常同时发生,双重轨迹模型为这种现象提供了机会及独特的实践科学视角[35]。Yuan等[36]先单独拟合衰弱轨迹与认知轨迹,分别得到5种衰弱轨迹与3种认知障碍轨迹,再采用双轨迹模型量化衰弱轨迹与认知障碍轨迹之间的关联,结果显示1/5的老年人群同时遵循“持续衰弱”和“持续严重认知障碍”的轨迹。因此,双轨迹模型的探索不仅能够识别睡眠质量和衰弱发展的不同轨迹,而且还为2种结果的不同轨迹之间的多维关系提供见解[37]。个体受试者之间的轨迹异质性更为明显,即使在快速恶化的睡眠质量轨迹中,衰弱状态的改善仍然是可能的[38]。有证据[39]指出,双轨迹模型满足了多维、动态的整体视角,并有学者将其应用于老年领域,不仅能检验生理维度听力障碍与心理维度认知功能轨迹之间的共存关系[35],还能探讨社会维度社会孤立与生理维度痴呆轨迹之间作用机制,其发展愈发成熟[40]。越来越多的证据[41]支持睡眠与衰弱之间有联系,常同时存在于同一老年个体中。然而双轨迹模型在睡眠与衰弱领域中的应用仍处于空白阶段,目前轨迹研究大多为横截面研究,即某一时点变量与另一变量纵向变化轨迹的关系,仅有部分研究考虑了睡眠和衰弱的积累效应及动态发展,结果显示睡眠障碍不仅对衰弱变化有加速作用[42],而且睡眠障碍亦随着衰弱严重程度的增加而增加[6]。因此,建议未来的研究关注睡眠与衰弱在老年人中多维动态的相互作用。

2.3.3. 睡眠与衰弱双轨迹的影响因素

2.3.3.1. 人格特质

人格指影响行为、思想和感受的一组基本稳定的特征,是老年人群睡眠障碍与衰弱状态同时出现的危险因素[43]。人格特质的5因素模型包括5个维度:责任心(条理性、负责任、遵纪律)、外向性(与人相处、善于沟通、精力充沛)、神经质(体验负面情绪)、开放性(好奇心、创造力、智力)和宜人性(善良、热情、宽容)[44]。低水平责任心、高水平神经质及外向性的老年人衰弱进展明显增快[45]。另一研究[46]表明较高的神经质和较低的外向性和责任心与老年人睡眠质量较差有关,包括入睡后更频繁的醒来、更多的碎片睡眠和更少的休息感。高水平神经质、低水平责任心的老年人同时出现睡眠障碍与衰弱状态可能性较高,可增快衰弱发展进程,加重睡眠不佳的严重程度。

2.3.3.2. 机体共病

共病患者由于机体易感性增加,衰弱与睡眠障碍常同时存在。共病是指同时存在2种或2种以上慢性疾病的状态,包括心脏病、高血压、糖尿病等,而多种疾病共存一体可使机体功能退化,压力阈值降低,对外界易感性增加,微小的刺激便可引起机体内外稳态失衡[47]。研究[48]显示:共病与衰弱虽属不同的概念,但衰弱能预测共病,共病可诱发衰弱同时能加速衰弱进展,共病患者衰弱发生率高达56.1%,而共病患者服药种类较多,药物间不良反应可致失眠、嗜睡等睡眠障碍。

2.3.3.3. 居家状态

居家老年人睡眠与衰弱存在一定联系,二者相互依存,且随着居家状态的改变而增快、阻滞或逆转两者进展。居家状态是日常活动受限在家中的情况,通常具有健康状况不佳、功能残疾、社会剥夺等特点,可加快衰弱进程的发展[49],影响老年人的身体健康。有研究[50]指出,居家的老年人衰弱发生率更高,可将居家状态作为衰弱的预测指标。而通过减少居家状态,使老年人每天外出,可显著改善睡眠问题[51]

2.3.3.4. 社会认知

衰弱与睡眠并非临床常规诊断,较难出现明显症状。老年人、照护人员缺乏衰弱、睡眠障碍相关知识,当机体衰弱或存在睡眠障碍时易被认为是正常老化过程,难以引起重视,任由其恶化发展,严重影响老年人的生活质量。一项质性研究[52]表明:大部分受访者睡眠质量不佳,表示“我整天都睡不着,每天晚上只睡1~2 h就醒了,醒后再也睡不着。晚上要吃安眠药才入睡,不吃安眠药睡不着”,且对衰弱概念缺乏全面的认知,将其视为正常生理老龄化状态,该学者指出睡眠质量下降可导致体能消耗将无法及时补给,对衰弱造成不良影响。

2.3.4. 睡眠与衰弱双轨迹的干预现状

目前老年人中睡眠与衰弱相关干预措施较多,包括运动干预、营养干预、心理干预和药物干预。运动干预有多组分运动、有氧运动、抗阻力运动[53],营养干预则包括补充蛋白质、地中海饮食、改善饮食习惯等[54]。运动干预不仅能影响衰弱,对睡眠亦有显著影响[55],运动干预与营养干预联合应用效果最佳。然而,这些干预措施一般针对某个时间点,于特定时间段内进行干预,缺乏动态变化特点,且目前睡眠轨迹、衰弱轨迹、睡眠与衰弱双轨迹的动态变化干预措施在国内外均较少,难以满足目前研究态势发展。因此,以睡眠与衰弱的双轨迹研究为焦点来检视老年人共病现状研究,将推动逐渐加剧的老年共病态势的证据整合,丰富老年健康领域的研究成果,为制定老年睡眠与衰弱共病的干预与实践提供依据。

3. 展 望

老年人群睡眠质量与衰弱状态的双轨迹探索目前正在起步阶段,两者动态依存变化均可显著影响老年人群生活质量、健康状况。未来研究可以此为切入点,深入探讨二者作用机制,分析除两者的独立效应外是否存在未知的叠加效应,在仅知晓一种结局指标时如何合理推测另一指标动态变化规律(即由睡眠轨迹推测衰弱轨迹或由衰弱轨迹预测睡眠轨迹),以便更全面地掌握老年人群相关发展规律,更有效地应对逐年加剧的全球老龄化态势,为中国积极应对老龄化和推动老年群体的非医疗健康干预模式提供理论依据,提升老年人的幸福感。

基金资助

湖南省自然科学基金(2022JJ70066)。

This work was supported by the Natural Science Foundation of Hunan Province, China (2022JJ70066).

利益冲突声明

作者声称无任何利益冲突。

作者贡献

郑宇 论文构思、撰写与修改;周冰倩、陈星利 论文修改;龚妮 论文构思、修改与审阅。所有作者阅读并同意最终的文本。

原文网址

http://xbyxb.csu.edu.cn/xbwk/fileup/PDF/202304621.pdf

参考文献

  • 1. WHO . China country assessment report on ageing and health[EB/OL]. [2020-01-14]. https://www.who.int/ageing/publications/ china-country-assessment/en/.
  • 2. Wilson S, Sutherland E, Razak A, et al. Implementation of a frailty assessment and targeted care interventions and its association with reduced postoperative complications in elderly surgical patients[J]. J Am Coll Surg, 2021, 233(6): 764-775. 10.1016/j.jamcollsurg.2021.08.677. [DOI] [PubMed] [Google Scholar]
  • 3. 田鹏, 杨宁, 郝秋奎, 等. 中国老年衰弱患病率的系统评价[J]. 中国循证医学杂志, 2019, 19(6): 656-664. 10.7507/1672-2531.201901056. [DOI] [Google Scholar]; TIAN Peng, YANG Ning, HAO Qiukui, et al. Epidemiological characteristics of frailty in Chinese elderly population: a systematic review[J]. Chinese Journal of Evidence-Based Medicine, 2019, 19(6): 656-664. 10.7507/1672-2531.201901056. [DOI] [Google Scholar]
  • 4. To TL, Doan TN, Ho WC, et al. Prevalence of frailty among community-dwelling older adults in Asian countries: a systematic review and meta-analysis[J]. Healthcare (Basel), 2022, 10(5): 895. 10.3390/healthcare10050895. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Brewster GS, Riegel B, Gehrman PR. Insomnia in the older adult[J]. Sleep Med Clin, 2018, 13(1): 13-19. 10.1016/j.jsmc.2017.09.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Baniak LM, Yang K, Choi J, et al. Long sleep duration is associated with increased frailty risk in older community-dwelling adults[J]. J Aging Health, 2020, 32(1): 42-51. 10.1177/0898264318803470. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Henly SJ, Wyman JF, Findorff MJ. Health and illness over time: the trajectory perspective in nursing science[J]. Nurs Res, 2011, 60(3 Suppl): S5-S14. 10.1097/NNR.0b013e318216dfd3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Wyman JF, Henly SJ. Advancing nursing science through health trajectory research: an introduction[J]. Nurs Res, 2011, 60(3 Suppl): S1-S4. 10.1097/NNR.0b013e31821b1480. [DOI] [PubMed] [Google Scholar]
  • 9. Nguena Nguefack HL, Pagé MG, Katz J, et al. Trajectory modelling techniques useful to epidemiological research: a comparative narrative review of approaches[J]. Clin Epidemiol, 2020, 12: 1205-1222. 10.2147/CLEP.S265287. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. 张晨旭, 谢峰, 林振, 等. 基于组轨迹模型及其研究进展[J]. 中国卫生统计, 2020, 37(6): 946-949. 10.3969/j.issn.1002-3674.2020.06.039. [DOI] [Google Scholar]; ZHANG Chenxu, XIE Feng, LIN Zhen, et al. Group trajectory model and its research progress[J]. Chinese Journal of Health Statistics, 2020, 37(6): 946-949. 10.3969/j.issn.1002-3674.2020.06.039. [DOI] [Google Scholar]
  • 11. Jones BL. Advances in group-based trajectory modeling and an SAS procedure for estimating them[J]. Sociol Methods Res, 2007, 35(4): 542-571. [Google Scholar]
  • 12. Smagula SF, Butters MA, Anderson SJ, et al. Antidepressant response trajectories and associated clinical prognostic factors among older adults[J]. JAMA Psychiatry, 2015, 72(10): 1021-1028. 10.1001/jamapsychiatry.2015.1324. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. 段应龙, 谢建飞, 李丽君, 等. 癌症患者心理痛苦变化轨迹的研究进展[J]. 中国现代医药杂志, 2021, 23(11): 100-104. 10.3969/j.issn.1672-9463.2021.11.028. [DOI] [Google Scholar]; DUAN Yinglong, XIE Jianfei, LI Lijun, et al. Research progress on the change track of psychological pain of cancer patients[J]. Modern Medicine Journal of China, 2021, 23(11): 100-104. 10.3969/j.issn.1672-9463.2021.11.028. [DOI] [Google Scholar]
  • 14. de Almondes KM, Castro EAS, Paiva T. Sleep habits, quality of life and psychosocial aspects in the older age: before and during COVID-19[J]. Front Neurosci, 2022, 16: 694894. 10.3389/fnins.2022.694894. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Dean GE, Ziegler P, Chen HB, et al. Trajectory of insomnia symptoms in older adults with lung cancer: using mixed methods[J]. Support Care Cancer, 2019, 27(6): 2255-2263. 10.1007/s00520-018-4488-3. [DOI] [PubMed] [Google Scholar]
  • 16. Gebara MA, Kasckow J, Smagula SF, et al. The role of late life depressive symptoms on the trajectories of insomnia symptoms during antidepressant treatment[J]. J Psychiatr Res, 2018, 96: 162-166. 10.1016/j.jpsychires.2017.10.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. 杨臻华, 赵梦, 杨媛, 等. 养老机构老年人睡眠轨迹及其预测因素研究[J]. 中国护理管理, 2021, 21(4): 503-508. 10.3969/j.issn.1672-1756.2021.04.006. [DOI] [Google Scholar]; YANG Zhenhua, ZHAO Meng, YANG Yuan, et al. Trajectories and predicting factors of sleep among the elderly in nursing homes[J]. Chinese Nursing Management, 2021, 21(4): 503-508. 10.3969/j.issn.1672-1756.2021.04.006. [DOI] [Google Scholar]
  • 18. Chen JS, Patel SR, Redline S, et al. Weekly sleep trajectories and their associations with obesity and hypertension in the Hispanic/Latino population[J]. Sleep, 2018, 41(10): zsy150. 10.1093/sleep/zsy150. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Zhu Q, You YY, Fan L, et al. Associations between sleep duration patterns and cognitive decline trajectories in older Chinese adults[J]. Aging Clin Exp Res, 2021, 33(11): 3057-3063. 10.1007/s40520-021-01851-w. [DOI] [PubMed] [Google Scholar]
  • 20. Liu HY, Chen BZ, Li YK, et al. Neighborhood resources associated with frailty trajectories over time among community-dwelling older adults in China[J]. Health Place, 2022, 74: 102738. 10.1016/j.healthplace.2021.102738. [DOI] [PubMed] [Google Scholar]
  • 21. Kojima G, Iliffe S, Walters K. Frailty index as a predictor of mortality: a systematic review and meta-analysis[J]. Age Ageing, 2018, 47(2): 193-200. 10.1093/ageing/afx162. [DOI] [PubMed] [Google Scholar]
  • 22. Liu S, Kang L, Liu XH, et al. Trajectory and correlation of intrinsic capacity and frailty in a Beijing elderly community[J]. Front Med (Lausanne), 2021, 8: 751586. 10.3389/fmed.2021.751586. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Guida JL, Alfini AJ, Gallicchio L, et al. Association of objectively measured sleep with frailty and 5-year mortality in community-dwelling older adults[J]. Sleep, 2021, 44(7): zsab003. 10.1093/sleep/zsab003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Stolz E, Mayerl H, Freidl W. Fluctuations in frailty among older adults[J]. Age Ageing, 2019, 48(4): 547-552. 10.1093/ageing/afz040. [DOI] [PubMed] [Google Scholar]
  • 25. 王宇. 老年人衰弱轨迹与全死因死亡率的纵向关联研究[D]. 青岛: 青岛大学, 2020. [Google Scholar]; WANG Yu. Association between frailty trajectory and all-cause mortality in the elderly[D]. Qingdao: Qingdao University, 2020. [Google Scholar]
  • 26. Martinez-Nicolas A, Madrid JA, García FJ, et al. Circadian monitoring as an aging predictor[J]. Sci Rep, 2018, 8(1): 15027. 10.1038/s41598-018-33195-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Balomenos V, Ntanasi E, Anastasiou CA, et al. Association between sleep disturbances and frailty: evidence from a population-based study[J]. J Am Med Dir Assoc, 2021, 22(3): 551-558. 10.1016/j.jamda.2020.08.012. [DOI] [PubMed] [Google Scholar]
  • 28. Liu M, Hou T, Nkimbeng M, et al. Associations between symptoms of pain, insomnia and depression, and frailty in older adults: a cross-sectional analysis of a cohort study[J]. Int J Nurs Stud, 2021, 117: 103873. 10.1016/j.ijnurstu.2021.103873. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. 余静雅, 高静, 刘洁, 等. 老年人睡眠障碍与衰弱关系的meta分析[J]. 中国心理卫生杂志, 2019, 33(4): 289-295. 10.3969/j.issn.1000-6729.2019.04.010. [DOI] [Google Scholar]; YU Jingya, GAO Jing, LIU Jie, et al. A meta-analysis of association between sleep disorders and frailty in the elderly[J]. Chinese Mental Health Journal, 2019, 33(4): 289-295. 10.3969/j.issn.1000-6729.2019.04.010. [DOI] [Google Scholar]
  • 30. Honda H, Ashizawa R, Kiriyama K, et al. Chronic pain in the frail elderly mediates sleep disorders and influences falls[J]. Arch Gerontol Geriatr, 2022, 99: 104582. 10.1016/j.archger.2021.104582. [DOI] [PubMed] [Google Scholar]
  • 31. Liu X, Wang C, Qiao X, et al. Sleep quality, depression and frailty among Chinese community-dwelling older adults[J]. Geriatr Nurs, 2021, 42(3): 714-720. 10.1016/j.gerinurse.2021.02.020. [DOI] [PubMed] [Google Scholar]
  • 32. Anafi RC, Kayser MS, Raizen DM. Exploring phylogeny to find the function of sleep[J]. Nat Rev Neurosci, 2019, 20(2): 109-116. 10.1038/s41583-018-0098-9. [DOI] [PubMed] [Google Scholar]
  • 33. Kaur S, Banerjee N, Miranda M, et al. Sleep quality mediates the relationship between frailty and cognitive dysfunction in non-demented middle aged to older adults[J]. Int Psychogeriatr, 2019, 31(6): 779-788. 10.1017/S1041610219000292. [DOI] [PubMed] [Google Scholar]
  • 34. van den Ende ES, van Veldhuizen KDI, Toussaint B, et al. Hospitalized COVID-19 patients were five times more likely to suffer from total sleep deprivation compared to non-COVID-19 patients; an observational comparative study[J]. Front Neurosci, 2021, 15: 680932. 10.3389/fnins.2021.680932. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Tran Y, Tang D, Lo C, et al. Co-occurring hearing loss and cognitive decline in older adults: a dual group-based trajectory modeling approach[J]. Front Aging Neurosci, 2021, 13: 794787. 10.3389/fnagi.2021.794787. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Yuan YY, Lapane KL, Tjia J, et al. Trajectories of physical frailty and cognitive impairment in older adults in United States nursing homes[J]. BMC Geriatr, 2022, 22(1): 339. 10.1186/s12877-022-03012-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Chang LY, Chang HY, Wu WC, et al. Dual trajectories of sleep duration and cigarette smoking during adolescence: relation to subsequent internalizing problems[J]. J Abnorm Child Psychol, 2018, 46(8): 1651-1663. 10.1007/s10802-018-0414-x. [DOI] [PubMed] [Google Scholar]
  • 38. Hwang AC, Lee WJ, Huang N, et al. Longitudinal changes of frailty in 8 years: comparisons between physical frailty and frailty index[J]. BMC Geriatr, 2021, 21(1): 726. 10.1186/s12877-021-02665-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Xie HY, Mchugo GJ, He XF, et al. Using the group-based dual trajectory model to analyze two related longitudinal outcomes[J]. J Drug Issues, 2010, 40(1): 45-62. 10.1177/002204261004000104. [DOI] [Google Scholar]
  • 40. Xiang XL, Lai PHL, Bao LM, et al. Dual trajectories of social isolation and dementia in older adults: a population-based longitudinal study[J]. J Aging Health, 2021, 33(1/2): 63-74. 10.1177/0898264320953693. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Pourmotabbed A, Boozari B, Babaei A, et al. Sleep and frailty risk: a systematic review and meta-analysis[J]. Sleep Breath, 2020, 24(3): 1187-1197. 10.1007/s11325-020-02061-w. [DOI] [PubMed] [Google Scholar]
  • 42. Mandelblatt JS, Zhou XT, Small BJ, et al. Deficit accumulation frailty trajectories of older breast cancer survivors and non-cancer controls: the thinking and living with cancer study[J]. J Natl Cancer Inst, 2021, 113(8): 1053-1064. 10.1093/jnci/djab003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Stephan Y, Sutin AR, Canada B, et al. Five-factor model personality traits and grip strength: Meta-analysis of seven studies[J]. J Psychosom Res, 2022, 160: 110961. 10.1016/j.jpsychores.2022.110961. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. McCrae RR, John OP. An introduction to the five-factor model and its applications[J]. J Pers, 1992, 60(2): 175-215. 10.1111/j.1467-6494.1992.tb00970.x. [DOI] [PubMed] [Google Scholar]
  • 45. Gale CR, Mõttus R, Deary IJ, et al. Personality and risk of frailty: the English longitudinal study of ageing[J]. Ann Behav Med, 2017, 51(1): 128-136. 10.1007/s12160-016-9833-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Sutin AR, Gamaldo AA, Stephan Y, et al. Personality traits and the subjective and objective experience of sleep[J]. Int J Behav Med, 2020, 27(4): 481-485. 10.1007/s12529-019-09828-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. 孙柳, 王艳玲, 陈少华, 等. 慢性病共病空巢老年配偶压力感知和应对体验的质性研究[J]. 军事护理, 2022, 39(7): 33-36. 10.3969/j.issn.2097-1826.2022.07.009. [DOI] [Google Scholar]; SUN Liu, WANG Yanling, CHEN Shaohua, et al. Stress perception and coping experience of empty-nest elderly spouses caring for partners with multiple chronic conditions: a qualitative study[J]. Military Nursing, 2022, 39(7): 33-36. 10.3969/j.issn.2097-1826.2022.07.009. [DOI] [Google Scholar]
  • 48. 陶代娣, 顾朋颖, 丁西平, 等. 住院共病老年患者衰弱现状及其危险因素研究[J]. 中国临床保健杂志, 2022, 25(2): 179-183. 10.3969/J.issn.1672-6790.2022.02.010. [DOI] [Google Scholar]; TAO Daidi, GU Pengying, DING Xiping, et al. Frail status and risk factors in elderly inpatients with comorbidity[J]. Chinese Journal of Clinical Healthcare, 2022, 25(2): 179-183. 10.3969/J.issn.1672-6790.2022.02.010. [DOI] [Google Scholar]
  • 49. Sun XC, Tang SY, Miyawaki CE, et al. Longitudinal association between personality traits and homebound status in older adults: results from the National Health and Aging Trends Study[J]. BMC Geriatr, 2022, 22(1): 93. 10.1186/s12877-022-02771-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Herr M, Latouche A, Ankri J. Homebound status increases death risk within two years in the elderly: results from a national longitudinal survey[J]. Arch Gerontol Geriatr, 2013, 56(1): 258-264. 10.1016/j.archger.2012.10.006. [DOI] [PubMed] [Google Scholar]
  • 51. Jacobs JM, Cohen A, Hammerman-Rozenberg R, et al. Going outdoors daily predicts long-term functional and health benefits among ambulatory older people[J]. J Aging Health, 2008, 20(3): 259-272. 10.1177/0898264308315427. [DOI] [PubMed] [Google Scholar]
  • 52. 郭萍, 罗尧岳, 蒲海旭, 等. 养老机构老年人对衰弱认知和体验的质性研究[J]. 中国医药科学, 2022, 12(10): 116-120. 10.3969/j.issn.2095-0616.2022.10.030. [DOI] [Google Scholar]; GUO Ping, LUO Yaoyue, PU Haixu, et al. A qualitative study on perceptions and experiences of frailty among elderly people in pension facilities[J]. China Medicine and Pharmacy, 2022, 12(10): 116-120. 10.3969/j.issn.2095-0616.2022.10.030. [DOI] [Google Scholar]
  • 53. Kojima G. Frailty as a predictor of nursing home placement among community-dwelling older adults: a systematic review and meta-analysis[J]. J Geriatr Phys Ther, 2018, 41(1): 42-48. 10.1519/JPT.0000000000000097. [DOI] [PubMed] [Google Scholar]
  • 54. Veronese N, Stubbs B, Noale M, et al. Adherence to a Mediterranean diet is associated with lower incidence of frailty: a longitudinal cohort study[J]. Clin Nutr, 2018, 37(5): 1492-1497. 10.1016/j.clnu.2017.08.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Tuna F, Üstündağ A, Başak Can H, et al. Rapid geriatric assessment, physical activity, and sleep quality in adults aged more than 65 years: a preliminary study[J]. J Nutr Health Aging, 2019, 23(7): 617-622. 10.1007/s12603-019-1212-z. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Central South University Medical Sciences are provided here courtesy of Central South University

RESOURCES