48 Variable Sleep Hours and Restfulness Ratings Across Days Predict Daily Functioning in Community-Dwelling Older Adults

Abstract

Objective:Certain contextual factors, including non-restorative sleep (Niermeyer & Suchy, 2020), sleep deprivation (Lim & Dinges, 2010), burdensome emotion regulation (Franchow & Suchy, 2017), and pain interference (Boselie, Vancleef, & Peters, 2016) have been shown to contribute to temporary declines in executive functioning (EF). Contextually-induced decrements in EF in turn have been associated with temporary decrements in performance of instrumental activities of daily living (IADLs) among healthy older adults (Brothers & Suchy, 2021; Suchy et al., 2020; Niermeyer & Suchy 2020). Furthermore, some evidence suggests that higher variability in levels of contextual factors across days (i.e., deviations from routine) may contribute to IADL lapses above and beyond average, albeit high, levels of these contextual burdens (Bielak, Mogle, & Sliwinksi, 2019; Brothers & Suchy, 2021). Taken together, these findings highlight the importance of accounting for transient contextual burdens when assessing EF and IADL abilities in older adults.Poor sleep quality has been associated with poor IADL performance (Fung et al., 2012; Holfeld & Ruthing, 2012) when assessed in a single visit. However, the potential contributions of variable sleep quantity and quality on IADL performance have not been assessed in healthy older adults using longitudinal methods. Accordingly, the aim of this study was to examine the impact of fluctuations in sleep quantity and quality, assessed daily, above and beyond average levels, on at-home IADL performance across 18 days in a group of community-dwelling older adults.Participants and Methods:Fifty-two non-demented community-dwelling older adults (M age = 69 years, 65% female) completed 18 days of at-home IADL tasks, as well as daily ecological momentary assessment (EMA) measures of EF, sleep hours, and restfulness questions. An 18-day mean EMA EF score was computed controlling for practice effects. Mean levels of and variability in EMA sleep hours and EMA restfulness ratings were computed. IADL scores were computed for timeliness and accuracy across the 18 days.Results:A series of hierarchical linear regressions were run using separate IADL timeliness and accuracy as the dependent variable. In the first step, demographics (age, sex, education) were entered. Then, EMA EF was entered, followed by mean EMA sleep hours and EMA mean restfulness, and lastly, variability in EMA sleep hours and EMA restfulness. EMA EF was found to significantly predict both IADL accuracy (B = .46, p = .001) and timeliness (B = .45, p = .005). Variability in EMA sleep hours (B = .40, p = .008) and restfulness (B = -.29, p = .043) both predicted IADL accuracy beyond other variables, while mean levels did not. Additionally, variability in sleep hours and restfulness substantially improved the prediction of IADL accuracy above and beyond other variables in the model, accounting for an additional 16% of variance (F (2) = 3.80, ∆ R2 = .16, p = .006). Neither mean levels of or variability in sleep hours or restfulness predicted IADL timeliness.Conclusions:Results suggest that greater fluctuations in the amount and quality of sleep across days may render healthy older adults more susceptible to lapses in daily functioning abilities, particularly the accuracy with which IADL tasks are completed.