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. 2023 May;23(3):487-493.
doi: 10.1111/psyg.12959. Epub 2023 Mar 26.

Sleep profile in a population of community-dwelling nonagenarians: data from the Mugello study

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Sleep profile in a population of community-dwelling nonagenarians: data from the Mugello study

Barbara Binazzi et al. Psychogeriatrics. 2023 May.

Abstract

Background: Very few studies have investigated sleep characteristics in the oldest-old individuals (aged ≥85 years) and data collected often rely on self-reported information. This study had three aims: (i) to objectively assess, using a wearable device, the sleep characteristics of a large community of oldest-old subjects; (ii) to assess differences in sleep parameters between self-reported 'good sleepers' and 'bad sleepers'; (iii) to assess whether there was a relationship between sleep parameters and cognitive status in this community-dwelling population.

Methods: There were 178 subjects (74.2% women, median age 92 years) included in the 'Mugello study', who wore an armband 24 h/day for at least two consecutive nights to estimate sleep parameters. The perceived sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), the cognitive status through the Mini-Mental State Examination. Continuous variables were compared between men/women, and good/bad sleepers with the independent t-test or Mann-Whitney U-test, according to data distribution. Chi-square test was used for categorical/dichotomous variables. An ordinal logistic regression model was used to study the possible association between sleep parameters and cognitive function.

Results: Participants spent in bed nearly 9 h, with a total sleep time of 7 h, a sleep onset latency of 17 min, and a sleep efficiency of 83%. Sleep onset latency was significantly associated with different cognitive levels when age and education level were considered. No significant difference in sleep parameters estimated using the SenseWear armband were found between poor (n = 136, 76.4%) and good sleepers (n = 42, 23.6%), identified according to the PSQI.

Conclusions: In this study, actigraphic measurements revealed that subjects with a cognitive decline were more prone to increased sleep onset latency. Sleep quality assessed using the PSQI was not coherent with actigraphic measurements in this sample, supporting the need for objective measures when investigating sleep quality in the oldest-old population.

Keywords: Mini-Mental State Examination; actigraphy; nonagenarians; sleep; sleep quality.

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