Identifying an Acceptable Number of Ambulatory Blood Pressure Measurements for Accuracy of Average Blood Pressure and Nocturnal Dipping Status.

OBJECTIVE: We aimed to identify the minimum number of ABP measures to accurately determine daytime and nighttime systolic BP averages and nocturnal dipping status (i.e., relative daytime:nighttime change). METHODS: Forty-three midlife participants wore an ABP monitor for 24 hours with measurements every 20/30 minutes during the daytime/nighttime, as identified by a sleep diary. We calculated daytime/nighttime systolic BP average and dipping status from all available measurements per participant (i.e., normative data). We then calculated daytime and nighttime BP per participant based on a random selection of 8-20 and 4-10 measurements and replicated random selections 1000 times. We calculated accuracy by checking the proportion from 1000 different randomly selected samples for a particular number of measurements that systolic BP was ±5 mmHg of normative data, and dipping status remained unchanged for each participant compared to the normative value. The best fit for the regression model estimated the minimal number of measurements for an accuracy of 95% in BP averages. RESULTS: For a 95% accuracy in estimating daytime and nighttime systolic BP, 11 daytime and 8 nighttime measurements were required. The highest accuracy for dipping status was 91.6±13.4% using 20 daytime and 10 nighttime measures, while the lowest was (83.4±15.1%) using 8 daytime and 4 nighttime measures. CONCLUSION: Eleven daytime and eight nighttime measurements are likely enough to calculate average systolic BPs accurately. However, no minimum number is suggested to accurately calculate dipping status.

Belonging, endurance, and resistance: Black placemaking theory in primary care.

Black-Americans continue to experience pervasive health disparities. Factors contributing to increased disease risk include a general mistrust of biomedical institutions among Black Americans. The purpose of this focus group study was to identify, among Black patients who regularly seek care from a primary provider, salient themes regarding barriers to 1) receiving quality primary care; and 2) adhering to medical recommendations. We examined transcripts of eight focus groups held remotely with 29 Black patients (aged 30-60 years) who had established primary care providers. Using grounded theory and an inductive thematic analysis of the transcripts, we identified three themes (belonging, endurance, and resistance) consistent with Black placemaking theory. Our findings suggest that reducing health disparities for Black Americans will require clinical initiatives that emphasize: 1) attention to social influences on health behavior and to features of medical institutions that mark them as White spaces (belonging); 2) recognition of, as well as sensitivity to, community awareness of the systemic and interpersonal barriers to health and safety that many Black adults endure; and 3) reframing avoidant (resistant) behaviors as protective strategies among Black patients. Examining primary care in this way-through the lens of Black placemaking theory-reveals how culturally meaningful approaches to harnessing the specialized knowledge and resilience that clearly exists among many Black communities can improve health care delivery.

Obesity alters the circadian profiles of energy metabolism and glucose regulation in humans.

OBJECTIVE: Given the complex interaction among the circadian system, energy metabolism, and obesity, the authors tested whether having obesity impacts the circadian variation in energy and glucose metabolism in humans. METHODS: Participants with BMI either in the healthy weight or obesity ranges were studied in a 5-day, in-laboratory protocol that equally distributed behaviors (i.e., sleep, eating, exercise) across 24 h. Energy metabolism was measured at rest and during a standardized exercise bout and blood was sampled before and after each identical study meal to assess glucose and insulin levels. RESULTS: In those with a healthy weight, the circadian nadir of energy expenditure, during both rest and exercise, occurred when participants would normally be asleep. However, in those with obesity, this nadir appears to occur during the habitual wake period. Differences in glucose regulation also depended on the circadian phase, such that individuals with obesity appeared to have relatively greater glucose intolerance during the circadian day and produced less insulin during the circadian night. CONCLUSIONS: Obesity is associated with altered circadian energy and glucose metabolism. Understanding and addressing these associations could lead to strategies that improve body weight and metabolic health in people with obesity.

Later circadian timing and increased sleep timing variability are associated with attenuations in overnight blood pressure dipping among chronic nightshift workers.

OBJECTIVE: Determine relationships between overnight blood pressure, circadian phase, and sleep variability among dayshift and chronic nightshift nurses. METHODS: Twenty participants working dayshift (n = 10) or nightshift (n = 10) schedules participated in a 7-day cross-sectional study. Participants underwent an evening in-laboratory melatonin assessment and wore ambulatory blood pressure devices to assess 24-hour blood pressure patterns. Overnight blood pressure dipping was calculated from sleeping/waking systolic blood pressure ratio and salivary dim-light melatonin onset determined circadian phase. Sleep variability was assessed using the standard deviation of 7-day sleep onset. RESULTS: Nightshift workers had later circadian phase, greater sleep onset variability, and an attenuated overnight blood pressure dipping pattern. Later circadian phase was associated with attenuated dipping patterns and sleep onset variability was negatively correlated with blood pressure dipping magnitude in nightshift, but not dayshift workers. CONCLUSIONS: Chronic circadian disruption via higher sleep onset variability among nightshift workers may contribute to attenuated blood pressure dipping and cardiovascular risk in this population.

Chronological distribution of readings in ambulatory blood pressure monitoring exams affects the nighttime average and the magnitude of blood pressure dipping.

STUDY OBJECTIVES: Averaged nighttime blood pressure (BP) is superior to daytime BP for cardiovascular risk stratification, and the relative change between daytime/nighttime BP (dipping%) significantly predicts cardiovascular risk. Newer reports suggest that 4 measurements at night may be enough for cardiovascular risk stratification. Since BP oscillates across the night, the temporal distribution of measurements across the night may impact nighttime BP and dipping%. Therefore, we compared average nighttime BP and dipping% when using measurements in the first half (1st-half), second (2nd-half), and a combination of both (combined). METHODS: Forty-three (17 females and twenty-six males) midlife adults aged 50±10 years old wore an ambulatory BP monitor for 24 hours at home, programmed to measure BP every 20 minutes when scheduled for daytime and every 30 minutes during a self-selected 8-hour nighttime for time-in-bed. We compared the nighttime BP averages and dipping% when using either the first four measurements from the 1st-half or 2nd-half of the nighttime and combined. RESULTS: Nighttime Systolic BP was significantly different across 1st-half, 2nd-half, and combined (111±9 vs.107±11 vs. 109±9 mmHg, p<0.01), respectively, with significant pairwise differences across all categories (p<0.01 for each). Systolic BP dipping% was significantly different across 1st-half, 2nd-half, and combined (9.9±5.5 vs.13.5±6.4 vs. 11.7±5.0 %, p<0.01), respectively, with significant pairwise differences across all categories (p<0.01 for each. Diastolic BP and diastolic dipping% were similar across the three different bins. CONCLUSION: In midlife adults, systolic nighttime BP and dipping% may depend upon when BP measurements are taken during the night.

Multidimensionality of the PROMIS sleep disturbance 8b short form in working adult populations.

OBJECTIVES: The Patient-Reported Outcomes Measurement Information System sleep disturbance measures were developed using item response theory assumptions of unidimensionality and local independence. Given that sleep health is multidimensional, we evaluate the factor structure of the Patient-Reported Outcomes Measurement Information System sleep disturbance 8b short form to examine whether it reflects a unidimensional or multidimensional construct. METHODS: Six full-time working adult samples were collected from civilian and military populations. Exploratory and confirmatory factor analyses were conducted. Single-factor and two-factor models were performed to evaluate the dimensionality of sleep disturbance using the 8b short form. Sleep duration and subjective health were examined as correlates of the sleep disturbance dimensions. RESULTS: Across six working adult samples, single-factor models consistently demonstrated poor fit, whereas the two-factor models, with insomnia symptoms (ie, trouble sleeping) and dissatisfaction with sleep (ie, subjective quality of sleep) dimensions demonstrated sufficient fit that was significantly better than the single-factor models. Across each sample, dissatisfaction with sleep was more strongly correlated with sleep duration and subjective health than insomnia symptoms, providing additional evidence for distinguishability between the two sleep disturbance factors. CONCLUSIONS: In working adult populations, the Patient-Reported Outcomes Measurement Information System sleep disturbance 8b short form is best modeled as two distinguishable factors capturing insomnia symptoms and dissatisfaction with sleep, rather than as a unidimensional sleep disturbance construct.

The Tech4Rest Randomized Controlled Trial: Applying the Hierarchy of Controls to Advance the Sleep, Health, and Well-being of Team Truck Drivers.

OBJECTIVE: The aim of the study was to evaluate the effectiveness of interventions to improve sleep, reduce fatigue, and advance the well-being of team truck drivers. METHODS: In a randomized controlled trial ( k = 24 teams; N = 49 drivers; 61.3% of planned sample), intervention teams were exposed to baseline (3-4 weeks), cab enhancements (active suspension seat, therapeutic mattress; 3-4 weeks), and cab enhancements plus a behavioral sleep-health program (1-2 months). Control teams worked as usual during the same period. RESULTS: Trends in sleep-related outcomes favored the intervention. Large and statistically significant intervention effects were observed for objectively measured physical activity (a behavioral program target). The discussion of results addresses effect sizes, statistical power, intervention exposure, and work organization. CONCLUSIONS: Trends, effect sizes, and significant findings in this rare trial provide valuable guidance for future efforts to improve working conditions and outcomes for team drivers.

Daily cannabis use is associated with sleep duration differentially across ages.

OBJECTIVE: To assess the relationship between frequency of cannabis use and sleep duration across age in a large US population (235,667 people). METHODS: Multinomial logistic regression was used to evaluate the association between the frequency of cannabis use and sleep duration using cross sectional data from the 2016-2018 Behavioral Risk Factor Surveillance System. RESULTS: When adjusted for sociodemographic factors, health related variables, and stratified by age we found that young adults (18-44 years) who reported daily-use (≥16 uses a month) had an increased risk ratio (RR [95% CI]) for either short or long sleep (1.22 [1.06-1.40] and 1.52 [1.07-2.16]); midlife adults (45-64 years) who reported daily-use had an increased prevalence of long sleep (1.71 [1.03-2.82]); and older adults (≥65 years) who reported daily-use had an increased prevalence of short sleep (1.61 [1.05-2.49]). CONCLUSIONS: Compared to those who reported no cannabis use, individuals who reported daily cannabis use demonstrated a greater prevalence for either short or long sleep duration.

Keeping an eye on circadian time in clinical research and medicine.

BACKGROUND: Daily rhythms are observed in humans and almost all other organisms. Most of these observed rhythms reflect both underlying endogenous circadian rhythms and evoked responses from behaviours such as sleep/wake, eating/fasting, rest/activity, posture changes and exercise. For many research and clinical purposes, it is important to understand the contribution of the endogenous circadian component to these observed rhythms. CONTENT: The goal of this manuscript is to provide guidance on best practices in measuring metrics of endogenous circadian rhythms in humans and promote the inclusion of circadian rhythms assessments in studies of health and disease. Circadian rhythms affect all aspects of physiology. By specifying minimal experimental conditions for studies, we aim to improve the quality, reliability and interpretability of research into circadian and daily (i.e., time-of-day) rhythms and facilitate the interpretation of clinical and translational findings within the context of human circadian rhythms. We describe protocols, variables and analyses commonly used for studying human daily rhythms, including how to assess the relative contributions of the endogenous circadian system and other daily patterns in behaviours or the environment. We conclude with recommendations for protocols, variables, analyses, definitions and examples of circadian terminology. CONCLUSION: Although circadian rhythms and daily effects on health outcomes can be challenging to distinguish in practice, this distinction may be important in many clinical settings. Identifying and targeting the appropriate underlying (patho)physiology is a medical goal. This review provides methods for identifying circadian effects to aid in the interpretation of published work and the inclusion of circadian factors in clinical research and practice.

The circadian system modulates the cortisol awakening response in humans.

Background: In humans, circulating cortisol usually peaks 30-60 min after awakening from nocturnal sleep, this is commonly referred to as the cortisol awakening response (CAR). We examined the extent to which the CAR is influenced by the circadian system, independent of behaviors including sleep. Materials and methods: We examined the CAR in 34 adults (20 female) using two complementary multiday in-laboratory circadian protocols performed in dim light, throughout which behavioral factors were uniformly distributed across the 24-hour circadian cycle. Protocol 1 consisted of 10 identical consecutive 5-hour 20-minute sleep/wake cycles, and protocol 2 consisted of 5 identical consecutive 18-hour sleep/wake cycles. Salivary melatonin was used as the circadian phase marker (0° = dim light melatonin onset). During each sleep/wake cycle, salivary cortisol was measured upon scheduled awakening and 50-minutes later, with the change in cortisol defined as the CAR. Cosinor analyses were used to detect any significant circadian rhythmicity in the CAR. In secondary analyses, we adjusted the models for time awake before lights on, total sleep time, percent of rapid eye movement (REM) sleep, and percent of non-rapid eye movement (NREM) sleep. Results: Both protocols revealed a similar circadian rhythm in the CAR, with peaks occurring at a circadian phase corresponding to 3:40-3:45 a.m., with no detectable CAR during the circadian phases corresponding to the afternoon. In addition to the sinusoidal component of the circadian rhythm, total sleep time was also associated with the CAR for protocol 1. The percent of sleep spent in REM or NREM sleep were not associated with the CAR in either protocol. Conclusion: Our results show that the CAR exhibits a robust circadian rhythm that persists even after adjusting for prior sleep. Presuming that the CAR optimizes physiological responses to the anticipated stressors related to awakening, these findings may have implications for shift workers who wake up at unusual circadian phases. A blunted CAR in shift workers upon awakening in the evening may result in diminished responses to stressors.

Chronobiology of Exercise: Evaluating the Best Time to Exercise for Greater Cardiovascular and Metabolic Benefits.

Physiological function fluctuates across 24 h due to ongoing daily patterns of behaviors and environmental changes, including the sleep/wake, rest/activity, light/dark, and daily temperature cycles. The internal circadian system prepares the body for these anticipated behavioral and environmental changes, helping to orchestrate optimal cardiovascular and metabolic responses to these daily changes. In addition, circadian disruption, caused principally by exposure to artificial light at night (e.g., as occurs with night-shift work), increases the risk for both cardiovascular and metabolic morbidity and mortality. Regular exercise is a countermeasure against cardiovascular and metabolic risk, and recent findings suggest that the cardiovascular benefits on blood pressure and autonomic control are greater with evening exercise compared to morning exercise. Moreover, exercise can also reset the timing of the circadian system, which raises the possibility that appropriate timing of exercise could be used to counteract circadian disruption. This article introduces the overall functional relevance of the human circadian system and presents the evidence surrounding the concepts that the time of day that exercise is performed can modulate the cardiovascular and metabolic benefits. Further work is needed to establish exercise as a tool to appropriately reset the circadian system following circadian misalignment to preserve cardiovascular and metabolic health. © 2022 American Physiological Society. Compr Physiol 12:3621-3639, 2022.

Sleep and Executive Functioning in Pediatric Traumatic Brain Injury Survivors after Critical Care.

Over 50,000 children are hospitalized annually for traumatic brain injury (TBI) and face long-term cognitive morbidity. Over 50% develop sleep/wake disturbances (SWDs) that can affect brain development and healing. We hypothesized SWDs would portend worse executive function outcomes in children aged 3−18 years with TBI 1−3 months after hospital discharge. SWDs were defined using the Sleep Disturbances Scale for Children (t-scores ≥ 60). Outcomes included the Global Executive Composite (GEC, t-score) from the Behavior Rating Inventory of Executive Function, Second and Preschool Editions, and multiple objective executive function assessments combined through Principal Components Analysis into a Neurocognitive Index (NCI, z-score). Multiple linear regression evaluated associations between SWDs and executive function outcomes, controlling for covariates. Among 131 children, 68% had clinically significant SWDs, which were associated with significantly worse median scores on the GEC (56 vs. 45) and NCI (−0.02 vs. 0.42; both p < 0.05). When controlling for baseline characteristics and injury severity in multivariable analyses, SWDs were associated with worse GEC (ß-coefficient = 7.8; 95% Confidence Interval = 2.5, 13.1), and worse NCI (ß-coefficient = −0.4; 95% Confidence Interval = −0.8, −0.04). SWDs in children with TBI are associated with worse executive function outcomes after hospital discharge, and may serve as modifiable targets to improve outcomes.

Slow wave synchronization and sleep state transitions.

Spontaneous synchronization over large networks is ubiquitous in nature, ranging from inanimate to biological systems. In the human brain, neuronal synchronization and de-synchronization occur during sleep, with the greatest degree of neuronal synchronization during slow wave sleep (SWS). The current sleep classification schema is based on electroencephalography and provides common criteria for clinicians and researchers to describe stages of non-rapid eye movement (NREM) sleep as well as rapid eye movement (REM) sleep. These sleep stage classifications have been based on convenient heuristic criteria, with little consideration of the accompanying normal physiological changes across those same sleep stages. To begin to resolve those inconsistencies, first focusing only on NREM sleep, we propose a simple cluster synchronization model to explain the emergence of SWS in healthy people without sleep disorders. We apply the empirical mode decomposition (EMD) analysis to quantify slow wave activity in electroencephalograms, and provide quantitative evidence to support our model. Based on this synchronization model, NREM sleep can be classified as SWS and non-SWS, such that NREM sleep can be considered as an intrinsically bistable process. Finally, we develop an automated algorithm for SWS classification. We show that this new approach can unify brain wave dynamics and their corresponding physiologic changes.

Rapid changes in overnight blood pressure after transitioning to early-morning shiftwork.

Risk for adverse cardiovascular events increases when blood pressure does not decrease at night ("non-dipping," <10% decrease from daytime blood pressure). Shiftwork alters relationships between behaviors and endogenous circadian rhythms (i.e., circadian disruption along with variable sleep timing), and chronic shiftwork increases cardiovascular disease risk. To determine whether transitioning into shiftwork changes the overnight blood pressure dipping pattern, we leveraged a natural experiment that occurs when newly-hired bus operators transition from a daytime training schedule into an early-morning shiftwork or daywork schedule. Twenty participants were studied in a 90-day protocol upon new employment and underwent cardio-metabolic health assessments, including ambulatory blood pressure monitoring, and weekly sleep-wake diaries. Measurements were repeated after ~30 and 90 days after transitioning to a day or an early-morning shiftwork schedule. Newly-hired shiftworkers displayed dramatic changes in overnight blood pressure, with 62% converting from a healthy dipping blood pressure to the nondipping pattern, resulting in 93% of shiftworkers displaying a nondipping phenotype at 90-days. In contrast, 50% of dayworkers had a nondipping profile at baseline and this decreased to 0% at 90-days, a significant difference from shiftworkers (p = .001). At 90-days, overnight blood pressure dipping was ~7% less in shiftworkers than dayworkers (-6.3% [95%CI -3.7 to -8.8%] vs -13.1% [-10.3 to -15.9%]: p < .01), with changes in dipping associated with changes in sleep timing variability (r2 = .28, p = .03). The observed changes in overnight blood pressure dipping in newly-hired early-morning shiftworkers, which were associated with sleep timing variability, may be an early warning sign of increased cardiovascular risk among shiftworkers.

Daytime eating prevents internal circadian misalignment and glucose intolerance in night work.

Night work increases diabetes risk. Misalignment between the central circadian "clock" and daily behaviors, typical in night workers, impairs glucose tolerance, likely due to internal misalignment between central and peripheral circadian rhythms. Whether appropriate circadian alignment of eating can prevent internal circadian misalignment and glucose intolerance is unknown. In a 14-day circadian paradigm, we assessed glycemic control during simulated night work with either nighttime or daytime eating. Assessment of central (body temperature) and peripheral (glucose and insulin) endogenous circadian rhythms happened during constant routine protocols before and after simulated night work. Nighttime eating led to misalignment between central and peripheral (glucose) endogenous circadian rhythms and impaired glucose tolerance, whereas restricting meals to daytime prevented it. These findings offer a behavioral approach to preventing glucose intolerance in shift workers.

Understanding Circadian Mechanisms of Sudden Cardiac Death: A Report From the National Heart, Lung, and Blood Institute Workshop, Part 1: Basic and Translational Aspects.

Sudden cardiac death (SCD), the unexpected death due to acquired or genetic cardiovascular disease, follows distinct 24-hour patterns in occurrence. These 24-hour patterns likely reflect daily changes in arrhythmogenic triggers and the myocardial substrate caused by day/night rhythms in behavior, the environment, and endogenous circadian mechanisms. To better address fundamental questions regarding the circadian mechanisms, the National Heart, Lung, and Blood Institute convened a workshop, Understanding Circadian Mechanisms of Sudden Cardiac Death. We present a 2-part report of findings from this workshop. Part 1 summarizes the workshop and serves to identify research gaps and opportunities in the areas of basic and translational research. Among the gaps was the lack of standardization in animal studies for reporting environmental conditions (eg, timing of experiments relative to the light dark cycle or animal housing temperatures) that can impair rigor and reproducibility. Workshop participants also pointed to uncertainty regarding the importance of maintaining normal circadian rhythmic synchrony and the potential pathological impact of desynchrony on SCD risk. One related question raised was whether circadian mechanisms can be targeted to reduce SCD risk. Finally, the experts underscored the need for studies aimed at determining the physiological importance of circadian clocks in the many different cell types important to normal heart function and SCD. Addressing these gaps could lead to new therapeutic approaches/molecular targets that can mitigate the risk of SCD not only at certain times but over the entire 24-hour period.

Understanding Circadian Mechanisms of Sudden Cardiac Death: A Report From the National Heart, Lung, and Blood Institute Workshop, Part 2: Population and Clinical Considerations.

Sudden cardiac death (SCD) is the sudden, unexpected death due to abrupt loss of heart function secondary to cardiovascular disease. In certain populations living with cardiovascular disease, SCD follows a distinct 24-hour pattern in occurrence, suggesting day/night rhythms in behavior, the environment, and endogenous circadian rhythms result in daily spans of increased vulnerability. The National Heart, Lung, and Blood Institute convened a workshop, Understanding Circadian Mechanisms of Sudden Cardiac Death to identify fundamental questions regarding the role of the circadian rhythms in SCD. Part 2 summarizes research gaps and opportunities in the areas of population and clinical research identified in the workshop. Established research supports a complex interaction between circadian rhythms and physiological responses that increase the risk for SCD. Moreover, these physiological responses themselves are influenced by several biological variables, including the type of cardiovascular disease, sex, age, and genetics, as well as environmental factors. The emergence of new noninvasive biotechnological tools that continuously measure key cardiovascular variables, as well as the identification of biomarkers to assess circadian rhythms, hold promise for generating large-scale human data sets that will delineate which subsets of individuals are most vulnerable to SCD. Additionally, these data will improve our understanding of how people who suffer from circadian disruptions develop cardiovascular diseases that increase the risk for SCD. Emerging strategies to identify new biomarkers that can quantify circadian health (eg, environmental, behavioral, and internal misalignment) may lead to new interventions and therapeutic targets to prevent the progression of cardiovascular diseases that cause SCD.