中国全科医学 ›› 2023, Vol. 26 ›› Issue (26): 3297-3302.DOI: 10.12114/j.issn.1007-9572.2023.0096

• 论著 • 上一篇    下一篇

主观认知下降老年人睡眠分型的潜在剖面分析及其影响因素研究

田萌, 宋玉磊, 张薛晴, 马云云, 梁晓, 石佳瑞, 殷海燕, 罗丹, 徐桂华, 柏亚妹*()   

  1. 210023 江苏省南京市,南京中医药大学护理学院
  • 收稿日期:2023-02-22 修回日期:2023-04-01 出版日期:2023-09-15 发布日期:2023-04-20
  • 通讯作者: 柏亚妹

  • 作者贡献:田萌负责论文起草、书写和修改,参与数据收集、整理与统计学分析;宋玉磊指导论文撰写与统计学分析,参与研究方案设计;张薛晴、马云云、梁晓、石佳瑞负责研究过程的实施,包括数据收集与初步整理;殷海燕、罗丹、徐桂华参与研究方案设计、论文修订及审校;柏亚妹提出研究构思与设计、负责论文最终版本修订,对论文负责。
  • 基金资助:
    国家自然科学基金面上项目(72174095); 江苏省社会科学基金一般项目(20GLB018); 江苏省社会发展面上项目(BE2022802)

Latent Profile Analysis of Sleep Subtypes in Older Adults with Subjective Cognitive Decline and Its Influencing Factors

TIAN Meng, SONG Yulei, ZHANG Xueqing, MA Yunyun, LIANG Xiao, SHI Jiarui, YIN Haiyan, LUO Dan, XU Guihua, BAI Yamei*()   

  1. School of Nursing, Nanjing University of Chinese Medicine, Nanjing 210023, China
  • Received:2023-02-22 Revised:2023-04-01 Published:2023-09-15 Online:2023-04-20
  • Contact: BAI Yamei

摘要: 背景 伴睡眠障碍的主观认知下降(SCD)老年人认知衰退及痴呆转化风险增高,但SCD老年人睡眠问题尚未引起足够重视,SCD老年人睡眠分型及其影响因素有待进一步研究。 目的 探究SCD老年人潜在睡眠分型,并分析不同睡眠分型的影响因素。 方法 2022年5—8月,采用分层便利抽样法,选取江苏省南京市、常州市、南通市、徐州市社区SCD老年人为研究对象。使用一般资料调查表、主观认知下降问卷(SCD-Q9)、北京版蒙特利尔认知评估量表(MoCA)、简易智能精神状态检查量表(MMSE)、匹兹堡睡眠质量指数量表(PSQI)、病人健康问卷抑郁量表(PHQ-9)、衰弱筛查量表(FRAIL量表)进行调查。根据PSQI各维度得分对SCD老年人睡眠分型进行潜在剖面分析,采用无序多分类Logistic回归分析探究SCD老年人睡眠分型的影响因素。 结果 本研究共纳入287例SCD老年人,潜在剖面分析结果显示,SCD老年人睡眠可分为3个潜在类别:睡眠相对良好型(69.7%,200/287)、睡眠不足型(21.9%,63/287)、入睡困难-药物催眠型(8.4%,24/287)。不同睡眠分型SCD老年人性别、智能手机使用、PHQ-9得分、FRAIL量表得分比较,差异有统计学意义(P<0.05)。以睡眠相对良好型为参照,无序多分类Logistic回归分析结果显示,性别〔睡眠不足型:女性,OR=2.479,95%CI(1.279,4.808)〕、智能手机使用〔睡眠不足型:是,OR=0.269,95%CI(0.090,0.808)〕、PHQ-9得分〔睡眠不足型:OR=1.755,95%CI(1.416,2.175);入睡困难-药物催眠型:OR=1.992,95%CI(1.540,2.576)〕是SCD老年人睡眠分型的影响因素(P<0.05)。 结论 SCD老年人睡眠存在明显的群体异质性,且应多关注女性、使用智能手机、有抑郁倾向SCD老年人的睡眠状况,早期开展不同睡眠分型的精准化干预,以改善睡眠质量,预防和延缓认知障碍发生。

关键词: 认知障碍, 主观认知下降, 睡眠, 睡眠质量, 潜在剖面分析, 影响因素分析, Logistic回归分析

Abstract:

Background

Sleep disorders combined with subjective cognitive decline (SCD) in older adults are associated with an increased risk of cognitive decline and dementia conversion. However, sleep problems in older adults with SCD have not received sufficient attention, the sleep subtypes of older adults with SCD and their influencing factors need to be further investigated.

Objective

To explore potential sleep subtypes in older adults with SCD and analyze the influencing factors of different sleep subtypes.

Methods

From May to August 2022, older adults with SCD were selected as subjects from the communities in Nanjing, Changzhou, Nantong, and Xuzhou in Jiangsu Province using a stratified convenience sampling method. The general information questionnaire, Subjective Cognitive Decline Questionnaire (SCD-Q9), Beijing Version of the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Pittsburgh Sleep Quality Index (PSQI), Patient Health Questionnaire-9 (PHQ-9) and Fatigue, Resistance, Ambulation, Illness and Loss of Weight Index (FRAIL) were used to conduct the survey. The latent profile analysis of sleep in older adults with SCD was performed based on the dimension scores of the PSQI scale, unordered multinomial Logistic regression analysis was used to examine the influencing factors of sleep subtypes in older adults with SCD.

Results

A total of 287 older adults with SCD were enrolled, and the results of the latent profile analysis showed that sleep in older adults with SCD can be classified into 3 potential subtypes: relatively good sleep subtype (n=200), sleep deprivation subtype (n=63), and difficulty falling asleep-medicated hypnosis subtype (n=24), accounting for 69.7%, 21.9%, and 8.4% of all respondents, respectively. There were significant differences in gender, smart phone use, PHQ-9 scores and FRAIL scores among different sleep subtypes (P<0.05). Using the relatively good sleep type as a reference, the unordered multinomial Logistic regression analysis showed that gender 〔sleep deprivation subtype: female, OR=2.479, 95%CI (1.279, 4.808) 〕, smart phone use 〔sleep deprivation subtype: yes, OR=0.269, 95%CI (0.090, 0.808) 〕, PHQ-9 score 〔sleep deprivation subtype: OR=1.755, 95%CI (1.416, 2.175); difficulty falling asleep-medicated hypnosis subtype: OR=1.992, 95%CI (1.540, 2.576) 〕were influencing factors of sleep subtyping (P<0.05) .

Conclusion

Sleep in older adults with SCD showed significant population heterogeneity, and more attention should be paid to the sleep status of older adults with SCD who are female, use smart phones, and have depressive tendencies. Early and precise interventions for different sleep subtypes need to be performed early to improve sleep quality and prevent or delay the development of cognitive impairment.

Key words: Cognition disorders, Subjective cognitive decline, Sleep, Sleep quality, Latent profile analysis, Root cause analysis, Logistic regression