Susan Malone

Abstract

The purpose of this review is to synthesize results from studies examining the association between time-of-day for eating, exercise, and sleep with blood pressure (BP) in adults with elevated BP or hypertension. Six databases were searched for relevant publications from which 789 were identified. Ten studies met inclusion criteria. Four studies examined time-of-day for eating, five examined time-of-day for exercise, and one examined time-of-day for sleep and their associations with BP. Results suggested that later time-of-day for eating (n = 2/4) and later sleep mid-point (n = 1/1) were significantly related to higher BP in multivariable models, whereas morning (n = 3/5) and evening (n = 4/5) exercise were associated with significantly lower BP. Although this small body of work is limited by a lack of prospective, randomized controlled study designs and underutilization of 24 h ambulatory BP assessment, these results provide preliminary, hypothesis-generating support for the independent role of time-of-day for eating, exercise, and sleep with lower BP.

Abstract

Background: The prevalence of short sleep duration is rising and is linked to chronic comorbidities, such as metabolic syndrome (MetS). Sleep extension interventions in adults with MetS comorbidities and short sleep duration are limited and vary widely in terms of approach and duration. Objectives: This pilot study aimed to test the feasibility and acceptability of a personalized 12-week systematic sleep time extension intervention on post-intervention sleep outcomes in middle-aged adults at risk forMetSwith actigraphy-estimated short sleep duration. Methods: A single-arm, 12-week, 12-session systematic sleep time extension intervention was delivered weekly via videoconferencing. Feasibility and acceptability were assessed using retention rates and mean sleep diary completions. Sleep was estimated for 14 consecutive days prior to and immediately following the 12-week intervention using wrist actigraphy. Daytime sleepiness was assessed using the Epworth Sleepiness Scale. Paired sample t-tests modeled changes in study outcomes. Results: Study participants (N = 41) had a mean age of 52 years and were mostly female and White; 86% attended >80% of sessions, and mean sleep diary completion was 6.7 diaries/week. Significant improvements in sleep from pre- to post-intervention included increased total sleep time, earlier sleep onsets, more regular sleep onsets, a higher sleep regularity index, and reduced daytime sleepiness. Extending sleep, as well as improving sleep timing and regularity in middle-aged adults with actigraphy-estimated short sleep duration and at risk for MetS, is feasible and acceptable. Discussion: Behavioral sleep characteristics may be modifiable and present a novel behavioral paradigm for mitigating MetS risk. This pilot study provides a proof of concept for the feasibility, acceptability, and preliminary effectiveness of a systematic sleep time extension for middle-aged adults at risk for MetS with actigraphy-estimated short sleep duration.

Abstract

Background: This study assessed changes in actigraphy-estimated sleep and glycemic outcomes after initiating automated insulin delivery (AID). Methods: Ten adults with long-standing type 1 diabetes and impaired awareness of hypoglycemia (IAH) participated in an 18-month clinical trial assessing an AID intervention on hypoglycemia and counter-regulatory mechanisms. Data from eight participants (median age = 58 years) with concurrent wrist actigraph and continuous glucose monitoring (CGM) data were used in the present analyses. Actigraphs and CGM measured sleep and glycemic control at baseline (one week) and months 3, 6, 9, 12, 15, and 18 (three weeks) following AID initiation. HypoCount software integrated actigraphy with CGM data to separate wake and sleep-associated glycemic measures. Paired sample t-tests and Cohen’s d effect sizes modeled changes and their magnitude in sleep, glycemic control, IAH (Clarke score), hypoglycemia severity (HYPO score), hypoglycemia exposure (CGM), and glycemic variability (lability index [LI]; CGM coefficient-of-variation [CV]) from baseline to 18 months. Results: Sleep improved from baseline to 18 months (shorter sleep latency [P <.05, d = 1.74], later sleep offset [P <.05, d = 0.90], less wake after sleep onset [P <.01, d = 1.43]). Later sleep onset (d = 0.74) and sleep midpoint (d = 0.77) showed medium effect sizes. Sleep improvements were evident from 12 to 15 months after AID initiation and were preceded by improved hypoglycemia awareness (Clarke score [d = 1.18]), reduced hypoglycemia severity (HYPO score [d = 2.13]), reduced sleep-associated hypoglycemia (percent time glucose was < 54 mg/dL, < 60 mg/dL,< 70 mg/dL; d = 0.66-0.81), and reduced glucose variability (LI, d = 0.86; CV, d = 0.62). Conclusion: AID improved sleep initiation and maintenance. Improved awareness of hypoglycemia, reduced hypoglycemia severity, hypoglycemia exposure, and glucose variability preceded sleep improvements. This trial is registered with ClinicalTrials.gov NCT03215914 https://clinicaltrials.gov/ct2/show/NCT03215914.

Abstract

There is an inconsistent conclusion regarding the relationship of social isolation and loneliness with poor sleep. We investigated the associations of social isolation and loneliness with new-onset insomnia symptoms in a nationally-representative sample of 9,430 adults aged ≥50 who were free of any insomnia symptoms/sleep disorders at baseline (wave 12/13) and followed up to 4 years from the Health and Retirement Study. Social isolation was measured by Steptoe's Social Isolation Index. Loneliness was measured by the revised 3-item UCLA-Loneliness Scale. Insomnia symptoms were quantified using the modified Jenkins Sleep Questionnaire. During a mean follow-up of 3.52 years, 1,522 (16.1%) participants developed at least one insomnia symptom. Cox models showed that loneliness was associated with the onset of difficulties initiating or maintaining sleep, early-morning awakening, nonrestorative sleep, and at least one of these symptoms after adjusting for potential covariates; while social isolation was not associated with the onset of difficulties maintaining sleep, early-morning awakening, or at least one insomnia symptom after adjusting for health indicators. These results are consistent in sensitivity analyses and stratified analyses by age, sex, race/ethnicity, and obesity. Public health interventions aimed at fostering close emotional relationships may reduce the burden of poor sleep among middle-aged and older adults.

Abstract

Objective: Automated insulin delivery (AID) may benefit individuals with long-standing type 1 diabetes where frequent exposure to hypoglycemia impairs counterregulatory responses. This study assessed the effect of 18 months AID on hypoglycemia avoidance and glucose counterregulatory responses to insulin-induced hypoglycemia in long-standing type 1 diabetes complicated by impaired awareness of hypoglycemia. Methods: Ten participants mean ± standard deviation age 49 ± 16 and diabetes duration 34 ± 16 years were initiated on AID. Continuous glucose monitoring was paired with actigraphy to assess awake- and sleep-associated hypoglycemia exposure every 3 months. Hyperinsulinemic hypoglycemic clamp experiments were performed at baseline, 6, and 18 months postintervention. Hypoglycemia exposure was reduced by 3 months, especially during sleep, with effects sustained through 18 months (P ≤ 0.001) together with reduced glucose variability (P < 0.01). Results: Hypoglycemia awareness and severity scores improved (P < 0.01) with severe hypoglycemia events reduced from median (interquartile range) 3 (3-10) at baseline to 0 (0-1) events/person·year postintervention (P = 0.005). During the hypoglycemic clamp experiments, no change was seen in the endogenous glucose production (EGP) response, however, peripheral glucose utilization during hypoglycemia was reduced following intervention [pre: 4.6 ± 0.4, 6 months: 3.8 ± 0.5, 18 months: 3.4 ± 0.3 mg/(kg·min), P < 0.05]. There were increases over time in pancreatic polypeptide (Pre:62 ± 29, 6 months:127 ± 44, 18 months:176 ± 58 pmol/L, P < 0.01), epinephrine (Pre: 199 ± 53, 6 months: 332 ± 91, 18 months: 386 ± 95 pg/mL, P = 0.001), and autonomic symptom (Pre: 6 ± 2, 6 months: 6 ± 2, 18 months: 10 ± 2, P < 0.05) responses. Conclusions: AID led to a sustained reduction of hypoglycemia exposure. EGP in response to insulin-induced hypoglycemia remained defective, however, partial recovery of glucose counterregulation was evidenced by a reduction in peripheral glucose utilization likely mediated by increased epinephrine secretion and, together with improved autonomic symptoms, may contribute to the observed clinical reduction in hypoglycemia.

Abstract

BACKGROUND: Day-to-day variability in sleep patterns and eating timing may disrupt circadian rhythms and has been linked with various adverse cardiometabolic outcomes. However, the extent to which variability in sleep patterns and eating timing relate to atherosclerotic development in subclinical stages remains unclear. METHODS AND RESULTS: Generally healthy adults (N=62, 29.3±7.3 years, 66% female) completed 14 days of sleep and dietary assessments via wrist accelerometry and photo-assisted diet records, respectively. Variability in sleep duration, sleep onset, eating onset (time of first caloric consumption), eating offset (time of last caloric consumption), and caloric midpoint (time at which 50% of total daily calories are consumed) were operationalized as the SD across 14 days for each variable. Separate regression models evaluated the cross-sectional associations between sleep and eating variability metrics with end-diastolic carotid intima-media thickness (CIMT) measured via ultrasonography. Models adjusted for age, sex, systolic blood pressure, sleep duration, and total energy intake. Each 60-minute increase in sleep duration SD and sleep onset SD were associated with a 0.049±0.016 mm (P=0.003) and 0.048±0.017 mm (P=0.007) greater CIMT, respectively. Variability in eating onset and offset were not associated with CIMT; however, each 60-minute increase in caloric midpoint SD was associated with a 0.033±0.015 mm greater CIMT (P=0.029). Exploratory post hoc analyses suggested that sleep duration SD and sleep onset SD were stronger correlates of CIMT than caloric midpoint SD. CONCLUSIONS: Variability in sleep patterns and eating timing are positively associated with clinically relevant increases in CIMT, a biomarker of subclinical atherosclerosis, in early adulthood.

Abstract

Background: Social isolation is prevalent and associated with dementia, yet the directionality and mechanisms are less understood. This study examined the association between social isolation and cognitive functioning and explored the mediating role of sleep disturbance on the social isolation–cognition relationship. Methods: Data from 5 753 dementia-free Americans aged ≥50 of 2006 (T1), 2010 (T2), and 2014 (T3) waves of the Health and Retirement Study. Social isolation was measured by the Steptoe Social Isolation Index. Cognitive functioning was measured by the Telephone Interview of Cognitive Status. Sleep disturbance was measured with the modified Jenkins Sleep Scale. We used cross-lagged panel models to determine the associations between social isolation, sleep disturbance, and cognitive functioning. Results: Social isolation is significantly associated with subsequent cognitive functioning (T1 to T2: β = −0.055, standard error [SE] = 0.014, p < .001; T2 to T3: β = −0.044, SE = 0.016, p < .001). Lower cognitive functioning is significantly associated with greater subsequent social isolation (T1 to T2: β = −0.101, SE = 0.020, p < .001; T2 to T3: β = −0.058, SE = .011, p < .001). Sleep disturbance at T2 partially mediated the effect of social isolation (T1) on cognitive functioning (T3), accounting for 6.2% of the total effect (β = −0.003, SE = 0.001, p < .01). Conclusions: Social isolation may deteriorate cognitive functioning and vice versa. The association between social isolation and cognition is partially explained by sleep disturbance.

Abstract

Study Objectives: This study aimed to quantify the temporal associations between nightly sleep quantity and timing with daytime eating behavior and activity levels in free-living (i.e. non-experimental) settings. Methods: Generally healthy young adults (N = 63; 28.9 ± 7.1 years) completed concurrent sleep (wrist actigraphy), eating (photo-assisted diet records), and activity (waist actigraphy) assessments over 14 days. Multilevel models quantified the associations between nightly sleep (total sleep time, timing of sleep and wake onset) with next-day eating behavior (diet quality, caloric intake, timing of eating onset/offset, eating window duration) and activity levels (total physical activity, sedentary time). Associations in the reverse direction (i.e. eating and activity predicting sleep) were explored. Models adjusted for demographic and behavioral confounders and accounted for multiple testing. Results: At within- and between-subject levels, nights with greater-than-average total sleep time predicted a shorter eating window the next day (all p ≤ 0.002). Later-than-average sleep and wake timing predicted within- and between-subject delays in next-day eating onset and offset, and between-subject reductions in diet quality and caloric intake (all p ≤ 0.008). At within- and between-subject levels, total sleep time was bidirectionally, inversely associated with sedentary time (all p < 0.001), while later-than-average sleep and wake timing predicted lower next-day physical activity (all p ≤ 0.008). Conclusions: These data underscore the complex interrelatedness between sleep, eating behavior, and activity levels in free-living settings. Findings also suggest that sleep exerts a greater influence on next-day behavior, rather than vice versa. While testing in more diverse samples is needed, these data have potential to enhance health behavior interventions and maximize health outcomes.

Abstract

Background Improving the recruitment and retention of underrepresented groups in all research areas is essential for health equity. However, achieving and retaining diverse samples is challenging. Barriers to recruitment and retention of diverse participants include socioeconomic and cultural factors and practical challenges (e.g., time and travel commitments). Objectives The purpose of this article is to describe the successful recruitment and retention strategies used by two related studies within a P20 center funded by the National Institute of Nursing Research focused on precision health research in diverse populations with multiple chronic conditions, including metabolic syndrome. Methods To address the complexity, biodiversity, and effect of metabolic syndrome and multiple chronic conditions, we developed culturally appropriate, multipronged recruitment and retention strategies for a pilot intervention study and a longitudinal observational pilot study within our P20 center. The following are the underlying principles that guided the recruitment and retention strategies: (a) flexibility, (b) active listening and bidirectional conversations, and (c) innovative problem solving. Results The intervention study (Pilot 1) enrolled 49 participants. The longitudinal observational study (Pilot 2) enrolled 45 participants. Women and racial/ethnic minorities were significantly represented in both. In Pilot 1, most of the participants completed the intervention and all phases of data collection. In Pilot 2, most participants completed all phases of data collection and chose to provide biorepository specimens. Discussion We developed a recruitment and retention plan building on standard strategies for a general medical population. Our real-world experiences informed the adaption of these strategies to facilitate the participation of individuals who often do not participate in research - specifically, women and racial/ethnic populations. Our experience across two pilot studies suggests that recruiting diverse populations should build flexibility in the research plan at the outset.

Abstract

The bioethical concept of best interest standard is cited in courts across America and considered to be an effective method of managing pediatric health care decision-making. Although the best interest standard is referred to in an abundance of nursing, medical, legal, and bioethical literature, refinement and a clear definition of the concept are lacking in the context of school health. An exhaustive and methodical search was conducted across six databases revealing 41 articles from the past decade. The Wilsonian methodology was used to analyze, refine, and clarify the concept of best interest standard by presenting original case vignettes (model, contrary, related, and borderline) and an innovative conceptual model as it applies to school nursing. This concept analysis provides school nurses with a deeper understanding of the best interest standard to navigate the complex nature of making school health care decisions.