Given the evidence of multi-parameter risk factors in shaping cognitive outcomes in aging, including sleep, inflammation, cardiometabolism, and mood disorders, multidimensional investigations of their impact on cognition are warranted. We sought to determine the extent to which self-reported sleep disturbances, metabolic syndrome (MetS) factors, cellular inflammation, depressive symptomatology, and diminished physical mobility were associated with cognitive impairment and poorer cognitive performance.

This is a cross-sectional study.

Participants with elevated, well-controlled blood pressure were recruited from the local community for a Tai Chi and healthy-aging intervention study.

One hundred forty-five older adults (72.7 ± 7.9 years old; 66% female), 54 (37%) with evidence of cognitive impairment (CI) based on Montreal Cognitive Assessment (MoCA) score ≤24, underwent medical, psychological, and mood assessments.

CI and cognitive domain performance were assessed using the MoCA. Univariate correlations were computed to determine relationships between risk factors and cognitive outcomes. Bootstrapped logistic regression was used to determine significant predictors of CI risk and linear regression to explore cognitive domains affected by risk factors.

The CI group were slower on the mobility task, satisfied more MetS criteria, and reported poorer sleep than normocognitive individuals (all p < 0.05). Multivariate logistic regression indicated that sleep disturbances, but no other risk factors, predicted increased risk of evidence of CI (OR = 2.00, 95% CI: 1.26–4.87, 99% CI: 1.08–7.48). Further examination of MoCA cognitive subdomains revealed that sleep disturbances predicted poorer executive function (β = –0.26, 95% CI: –0.51 to –0.06, 99% CI: –0.61 to –0.02), with lesser effects on visuospatial performance (β = –0.20, 95% CI: –0.35 to –0.02, 99% CI: –0.39 to 0.03), and memory (β = –0.29, 95% CI: –0.66 to –0.01, 99% CI: –0.76 to 0.08).

Our results indicate that the deleterious impact of self-reported sleep disturbances on cognitive performance was prominent over other risk factors and illustrate the importance of clinician evaluation of sleep in patients with or at risk of diminished cognitive performance. Future, longitudinal studies implementing a comprehensive neuropsychological battery and objective sleep measurement are warranted to further explore these associations.

Sleep disturbances negatively impact the quality of life of patients with Parkinson’s disease (PD). While persons living in regional areas are at higher risk of PD, PD is poorly managed in regional communities. This study examined factors associated with sleep problems in PD in a regional context.

A mixed-methods cross-sectional design was used.

Patients with PD were recruited from the Queensland Parkinson’s Project database.

Those who agreed to participate were sent a questionnaire assessing aspects of sleep, depression, anxiety, quality of life, and PD severity. Qualitative information was also gathered. Correlations between variables were examined; thematic analyses were performed for qualitative data.

All participants (n = 49) reported sleep disturbances, with 73% (n = 36) reporting sleep disturbance to be problematic. Global sleep dysfunction positively correlated with daytime napping (r = .34, p = .01), watching the clock when unable to sleep (r = .38, p = <.01), staying in bed when unable to sleep (r = .43, p = <.01), and going to bed hungry (r = .31, p = .03) and negatively correlated with daytime exercise (r = -.32, p = .02). Positive correlations were observed between global sleep dysfunction and depression (r = .55, p = <.01), anxiety (r = .31, p = .04), and dysfunctional sleep beliefs (r = .39, p = <.01).

There is a clear need for identifying factors related to sleep disturbances in PD for effective management.

Nearly 40% of care home residents who are living with dementia also have symptoms of disturbed sleep. However, the impact of these disturbances is relatively unknown and is needed to indicate whether interventions are warranted; therefore, we aimed to investigate the impact.

One-to-one semi-structured interviews.

Four UK care homes.

We interviewed 18 nurses and care assistants about residents with sleep disturbances.

We used a topic guide to explore staff experience of sleep disturbance in residents with dementia. The interviews were audio recorded and transcribed and then analyzed thematically by two researchers independently.

Staff described that sleep disturbances in most, but not all, residents impacted negatively on the resident, other residents, staff, and relatives. Residents became more irritable or agitated if they had slept badly. They slept in the daytime after a bad night, which then increased their chances of being awake the following night. For some, being sleepy in the day led to falls, missing medication, drinks, and meals. Staff perceived hypnotics as having low efficacy, but increasing the risk of falls and drowsiness. Other residents were disturbed by noise, and staff described stress when several residents had sleep disturbance. Some of the strategies reported by staff to deal with sleep disturbances such as feeding or providing caffeinated tea at night might be counterproductive.

Sleep disturbances in care home residents living with dementia negatively affect their physical and psychological well-being. These disturbances also disturb other residents and increase stress in staff.

Daytime sleepiness is associated with multiple negative outcomes in older adults receiving long-term services and supports (LTSS) including reduced cognitive performance, need for greater assistance with activities of daily living and decreased social engagement. The purpose of this study was to identify predictors of change in subjective daytime sleepiness among older adults during their first 2 years of receiving LTSS.

Secondary analysis of data from a prospective longitudinal study of older adults who received LTSS in their homes, assisted living communities or nursing homes interviewed at baseline and every 3 months for 24 months.

470 older adults (60 years and older) newly enrolled in LTSS (mean = 81, SD = 8.7; range 60–98; 71% women).

Subjective daytime sleepiness was assessed every 3 months through 2 years using the Epworth Sleepiness Scale. Multiple validated measures were used to capture health-related quality of life characteristics of enrollees and their environment, including symptom status (Symptom Bother Scale), cognition (Mini Mental Status Exam), physical function (Basic Activities of Daily Living), physical and mental general health, quality of life (Dementia Quality of Life, D-QoL), depressive symptoms (Geriatric Depression Scale) and social support (Medical Outcomes Survey-Social Support).

Longitudinal mixed effects modeling was used to examine the relationship between independent variables and continuous measure of daytime sleepiness. Increased feelings of belonging, subscale of the D-QoL (effect size = −0.006, 95% CI: −0.013 to −0.0001, p = 0.045) and higher number of depressive symptoms (effect size = −0.002, 95% CI: −0.004 to −0.001, p = 0.001) at baseline were associated with slower rates of increase in daytime sleepiness over time.

Comprehensive baseline and longitudinal screening for changes in daytime sleepiness along with depression and perceived quality of life should be used to inform interventions aimed at reducing daytime sleepiness among older adults receiving LTSS.

Given the increased risk of malnutrition in residential care homes, we studied how specific aspects of the mealtime environment are associated with residents’ eating challenges and energy intake in general and dementia care units of these homes.

Cross-sectional study.

624 residents and 82 dining rooms.

32 residential care homes across Canada.

Eating challenges were measured using the Edinburgh Feeding Evaluation in Dementia Questionnaire (Ed-FED-q). Energy intake was estimated over nine meals. Physical, social, person-centered, functional, and homelike aspects of the mealtime environment were scored using standardized, valid measures. Effects of interactions between dining environment scores and eating challenges on daily energy intake were assessed using linear regression.

More eating challenges were associated with decreased energy intake on the general (β = −36.5, 95% confidence interval [CI] = −47.8, −25.2) and dementia care units (β = −19.9, 95% CI = −34.6, −5.2). Among residents living on general care units, the functional (β = 48.5, 95% CI = 1.8, 95.2) and physical (β = 56.9, 95% CI = 7.2, 106.7) environment scores were positively and directly associated with energy intake; the social and person-centered aspects of the mealtime environment moderated the relationship between eating challenges and energy intake.

Resident eating challenges were significantly associated with energy intake on both dementia care and general care units; however on general care units, when adjusting for eating challenges, the functional and physical aspects of the environment also had a direct effect on energy intake. Furthermore, the social and person-centered aspects of the dining environment on general care units moderated the relationship between eating challenges and energy intake. Dementia care unit environments had no measurable effect on the association between resident eating challenges and energy intake.