Literature DB >> 31313420

Longitudinal sleep efficiency in the elderly and its association with health.

Altug Didikoglu1, Asri Maharani1, Gindo Tampubolon2, Maria Mercè Canal1, Antony Payton3, Neil Pendleton1.   

Abstract

The relationships between older age and sleep efficiency have traditionally been assessed using cross-sectional studies that ignore changes within individuals as they age. This research examines the determinants of sleep efficiency, the heterogeneity in an individual's sleep efficiency trajectory across a period of up to 27 years in later life and its associations with health. The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age cohort (n = 6,375; age 42-94 years) was used in this study. Depression and health data were collected using self-report validated instruments (Cornell Medical Index, Beck Depression Inventory and Geriatric Depression Scale). Longitudinal sleep and sociodemographic data were collected using a study-specific self-report questionnaire. A mixed-effect model was performed for sleep efficiency with adjustments for time-invariant and time-variant predictors. Latent class analysis was used to demonstrate subgroups of sleep efficiency trajectories and associations between sleep efficiency clusters and health history of the participants were investigated. Older adults have decreased sleep efficiency over time, with 18.6% decline between 40 and 100 years of age. Three sleep efficiency trajectory clusters were identified: high (32%), medium (50%) and low sleep efficiency (18%). Belonging to the high sleep efficiency cluster was associated with having lower prevalence of hypertension, circulatory problems, general arthritis, breathing problems and recurrent episodes of depression compared to the low efficiency cluster. Overall, ageing decreases sleep efficiency. However, there are detectable subgroups of sleep efficiency that are related to prevalence of different diseases.
© 2019 European Sleep Research Society.

Entities:  

Keywords:  ageing; latent class analysis; older adults; physical and mental health; sleep efficiency; sleep trajectory

Mesh:

Year:  2019        PMID: 31313420     DOI: 10.1111/jsr.12898

Source DB:  PubMed          Journal:  J Sleep Res        ISSN: 0962-1105            Impact factor:   3.981


  7 in total

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Authors:  Ahmad H Alghadir; Masood Khan; Mohammed Mansour Alshehri; Abdulfattah S Alqahtani; Mishal Aldaihan
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Authors:  Sergej Kmetec; Zvonka Fekonja; Adam Davey; Nataša Mlinar Reljić; Mateja Lorber
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6.  Sex differences in subjective age-associated changes in sleep: a prospective elderly cohort study.

Authors:  Seung Wan Suh; Ji Won Han; Ji Hyun Han; Jong Bin Bae; Woori Moon; Hye Sung Kim; Dae Jong Oh; Kyung Phil Kwak; Bong Jo Kim; Shin Gyeom Kim; Jeong Lan Kim; Tae Hui Kim; Seung-Ho Ryu; Seok Woo Moon; Joon Hyuk Park; Seonjeong Byun; Jiyeong Seo; Jong Chul Youn; Dong Young Lee; Dong Woo Lee; Seok Bum Lee; Jung Jae Lee; Jin Hyeong Jhoo; Ki Woong Kim
Journal:  Aging (Albany NY)       Date:  2020-11-07       Impact factor: 5.682

7.  Sleep Disturbances Are Associated With Depressive Symptoms in a Chinese Population: The Rugao Longevity and Aging Cohort.

Authors:  Chunhong Qiao; Hui Zhang; Qi Song; Xi Wang; Xiaofeng Wang; Yin Yao
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  7 in total

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