Susan Malone

Abstract

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

Abstract

Introduction:Misalignment between lifestyle behaviors and endogenous circadian rhythms is associated with elevated nocturnal blood pressure (BP) in experimental studies; however, less is known about free-living (i.e. nonlaboratory) circadian disruption and nocturnal BP. Additionally, sex-specific cardiovascular implications of circadian disruption are unclear.Objective:To examine the associations between rest - activity rhythms (RAR), a field-based estimate of circadian disruption, and nocturnal BP characteristics in young men and women.Methods:Fifty participants (20 ± 1 years; 20 men/30 women) underwent 24-h ambulatory BP monitoring following 14 days of wrist actigraphy. RAR variables of interdaily stability (day-to-day consistency in RAR), intradaily variability (within-day fragmentation of RAR), and relative amplitude (difference between peak vs. trough activity) were derived from actigraphy. Multivariable regression models of mean nocturnal SBP, DBP, and SBP dipping were generated to test main associations with RAR variables, and sex × RAR interactions. Daytime BP, race, BMI, physical activity, sleep duration, alcohol, caffeine, and sodium intake were considered as covariates.Results:In the full sample, no main associations between RAR and nocturnal BP characteristics were found. Sex interacted with RAR such that in women, higher interdaily stability (β = -5.39, 95% CI = -10.04 to -0.73, P = 0.024) and relative amplitude (β = -4.78, 95% CI = -9.22 to -0.34, P = 0.036) were both associated with lower nocturnal SBP. Sex-stratified multivariable models of nocturnal BP also revealed associations between interdaily stability and relative amplitude with SBP dipping in women (all P ≤ 0.01). No associations were apparent in men.Conclusion:Consistent and high-amplitude RAR are favorably associated with nocturnal BP characteristics in young women.

Abstract

Nocturnal hypoglycemia is life threatening for individuals with type 1 diabetes (T1D) due to loss of hypoglycemia symptom recognition (hypoglycemia unawareness) and impaired glucose counter regulation. These individuals also show disturbed sleep, which may result from glycemic dysregulation. Whether use of a hybrid closed loop (HCL) insulin delivery system with integrated continuous glucose monitoring (CGM) designed for improving glycemic control, relates to better sleep across time in this population remains unknown. The purpose of this study was to describe long-term changes in glycemic control and objective sleep after initiating hybrid closed loop (HCL) insulin delivery in adults with type 1 diabetes and hypoglycemia unawareness. To accomplish this, six adults (median age=58 y) participated in an 18-month ongoing trial assessing HCL effectiveness. Glycemic control and sleep were measured using continuous glucose monitoring and wrist accelerometers every 3 months. Paired sample t-tests and Cohen's d effect sizes modeled glycemic and sleep changes and the magnitude of these changes from baseline to 9 months. Reduced hypoglycemia (d=0.47-0.79), reduced basal insulin requirements (d=0.48), and a smaller glucose coefficient of variation (d=0.47) occurred with medium-large effect sizes from baseline to 9 months. Hypoglycemia awareness improved from baseline to 6 months with medium-large effect sizes (Clarke score (d=0.60), lability index (d=0.50), HYPO score (d=1.06)). Shorter sleep onset latency (d=1.53; p<0.01), shorter sleep duration (d=0.79), fewer total activity counts (d=1.32), shorter average awakening length (d=0.46), and delays in sleep onset (d=1.06) and sleep midpoint (d=0.72) occurred with medium-large effect sizes from baseline to 9 months. HCL led to clinically significant reductions in hypoglycemia and improved hypoglycemia awareness. Sleep showed a delayed onset, reduced awakening length and onset latency, and maintenance of high sleep efficiency after initiating HCL. Our findings add to the limited evidence on the relationships between diabetes therapeutic technologies and sleep health. This trial is registered with ClinicalTrials.gov (NCT03215914).

Abstract

Physical inactivity is a leading determinant of noncommunicable diseases. Yet, many adults remain physically inactive. Physical activity guidelines do not account for the multidimensionality of physical activity, such as the type or variety of physical activity behaviors. This study identified patterns of physical activity across multiple dimensions (e.g., frequency, duration, and variety) using a nationally representative sample of adults. Sociodemographic characteristics, health behaviors, and clinical characteristics associated with each physical activity pattern were defined. Multivariate finite mixture modeling was used to identify patterns of physical activity among 2003-2004 and 2005-2006 adult National Health and Nutrition Examination Survey participants. Chi-square tests were used to identify sociodemographic differences within each physical activity cluster and test associations between the physical activity clusters with health behaviors and clinical characteristics. Five clusters of physical activity patterns were identified: (a) low frequency, short duration (n = 730, 13%); (b) low frequency, long duration (n = 392, 7%); (c) daily frequency, short duration (n = 3,011, 55%); (d) daily frequency, long duration (n = 373, 7%); and (e) high frequency, average duration (n = 964, 18%). Walking was the most common form of activity; highly active adults engaged in more varied types of activity. High-activity clusters were comprised of a greater proportion of younger, White, nonsmoking adult men reporting moderate alcohol use without mobility problems or chronic health conditions. Active females engaged in frequent short bouts of activity. Data-driven approaches are useful for identifying clusters of physical activity that encompass multiple dimensions of activity. These activity clusters vary across sociodemographic and clinical subgroups.

Abstract

Emerging adulthood (18–25 years) represents a window of opportunity to modify the trajectory of cardiometabolic disease risk into older adulthood. Not known is the extent to which rest-activity rhythms (RAR) may be related to biomarkers of cardiometabolic health in this population. In this cross-sectional, observational study, 52 healthy emerging adults wore wrist accelerometers (14 consecutive days; 24 h/day) for assessment of nonparametric RAR metrics, including interdaily stability (IS; day-to-day RAR consistency), intradaily variability (IV; within-day RAR fragmentation), and relative amplitude (RA; robustness of RAR), as well as autocorrelation (correlation of rest/activity levels at 24-h lag-times). Cardiometabolic biomarkers, including body mass index (BMI), body fat percentage, blood pressure (BP), fasting lipids, glucose, and C-reactive protein (CRP) were assessed. Additional measures including physical activity, sleep duration, and habitual caffeine and alcohol consumption were also evaluated. A series of multivariable regression models of cardiometabolic biomarkers were used to quantify associations with RAR metrics. On average, participants were 20 ± 1 years of age (21 males, 31 females), non-obese, and non-hypertensive. All were nonsmokers and free of major diseases or conditions. In separate models, which adjusted for sex, BMI, moderate-vigorous physical activity, sleep duration, caffeine, and alcohol consumption, IS was inversely associated with total cholesterol (p ≤ 0.01) and non-HDL cholesterol (p < .05), IV was positively associated with CRP (p < .05), and autocorrelation was inversely associated with total cholesterol (p < .05) and CRP (p < .05). Conversely, associations between RA and cardiometabolic biomarkers were nonsignificant after adjustment for BMI, alcohol, and caffeine consumption. In conclusion, RAR metrics, namely, a higher IS, lower IV, and higher autocorrelation, emerged as novel biomarkers associated with more favorable indices of cardiometabolic health in this sample of apparently healthy emerging adults.

Abstract

Background Medical interns are at risk for sleep deprivation from long and often rotating work schedules. However, the effects of specific rotations on sleep are less clear. Objective To examine differences in sleep duration and alertness among internal medicine interns during inpatient intensive care unit (ICU) compared to general medicine (GM) rotations. Methods This secondary analysis compared interns during a GM or ICU rotation from a randomized trial (2015–2016) of 12 internal medicine residency programs assigned to different work hour limit policies (standard 16-hour shifts or no shift-length limits). The primary outcome was sleep duration/24-hour using continuous wrist actigraphy over a 13-day period. Secondary outcomes assessed each morning during the concomitant actigraphy period were sleepiness (Karolinska Sleepiness Scale [KSS]), alertness (number of Brief Psychomotor Vigilance Test [PVT-B] lapses), and self-report of excessive sleepiness over past 24 hours. Linear mixed-effect models with random program intercept determined associations between each outcome by rotation, controlling for age, sex, and work hour policy followed. Results Of 398 interns, 386 were included (n = 261 GM, n = 125 ICU). Average sleep duration was 7.00+0.08h and 6.84+0.10h, and number of PVT lapses were 5.5+0.5 and 5.7+0.7 for GM and ICU, respectively (all P >.05). KSS was 4.8+0.1 for both rotations. Compared to GM, ICU interns reported more days of excessive sleepiness from 12AM–6AM (2.6 vs 1.7, P < .001) and 6AM–12PM (2.6 vs 1.9, P = .013) and had higher percent of days with sleep duration < 6 hours (27.6% vs 23.4%, P, .001). GM interns reported more days with no excessive sleepiness (5.3 vs 3.7, P < .001). Conclusions Despite ICU interns reporting more excessive sleepiness in morning hours and more days of insufficient sleep (<6 hours), overall sleep duration and alertness did not significantly differ between rotations.

Abstract

Sleep health becomes an important component of global public health. The incidence of sleep disorders is increasing rapidly worldwide, which seriously affects people's quality of life. In China, the lack of professional sleep physicians and technicians, the distribution of sleep centers and the unbalanced development of medical resources have seriously restricted the development of sleep medicine and the improvement of sleep health guarantee level. In Europe and America and other developed countries, sleep medicine has become a new interdisciplinary discipline. The development of nurses as sleep coordinator has become an irresistible trend. Nurses have been trained to become the main force of sleep technicians. These successful attempts in the field of sleep medicine provide reference for promoting the development of nursing care in China from the aspects of medical care, teaching and research.

Abstract

BackgroundWe tested if an adjunctive sleep health (SH) intervention improved smoking cessation treatment response by increasing quit rates. We also examined if baseline sleep, and improvements in sleep in the first weeks of quitting, were associated with quitting at the end of treatment.MethodsTreatment-seeking smokers (N = 29) aged 21-65 years were randomized to a SH intervention (n = 16), or general health (GH) control (n = 13) condition. Participants received six counseling sessions across 15-weeks: SH received smoking cessation + SH counseling; GH received smoking cessation + GH counseling. Counseling began 4-weeks before the target quit date (TQD), and varenicline treatment began 1-week prior to TQD. Smoking status and SH were assessed at baseline (week 1), TQD (week 4), 3 weeks after cessation (week 7), week 12, and at the end of treatment (EOT; week 15).ResultsSH versus GH participants had higher Carbon Monoxide (CO) -verified, 7-day point prevalence abstinence at EOT (69% vs. 54%, respectively; adjusted odds ratio (aOR) = 2.10, 95% confidence interval (CI) = 0.40-10.69, P = 0.77). Higher baseline sleep efficiency (aOR = 1.42, 95% CI = 1.03-1.96, P = 0.03), predicted higher EOT cessation. Models were adjusted for age, sex, education, and baseline nicotine dependence.ConclusionsImproving SH in treatment-seeking smokers prior to cessation warrants further examination as a viable strategy to promote cessation.

Abstract

About 11% of the adult global populations is estimated to be living with type 2 diabetes mellitus (T2DM) by 2040. T2DM requires people to make decisions regarding complex therapeutic regimes, to maintain their well-being and quality of life, to manage symptoms and to reduce disease complications. All these behaviours, requiring knowledge, motivation, experience, and skills, have been referred to the concept of self-care. The intricacy and multidimensionality of T2DM self-care requires a complex approach to its overall comprehension. This Embedded Mixed Method study aims to investigate the experience of self-care in Type 2 Diabetes Mellitus adult patients. It comprises a prospective observational design, and an interpretive description. Quantitative data will be collected with validated questionnaires from 300 patients at baseline and once a year for two years on: diabetes self-care, quality of life, diabetes related distress, and sleep quality. Socio-demographic and clinical data will be collected from medical records. Qualitative data will be collected using semi-structured interviews on circa 10-20 patients, at baseline and once a year for two years, analysed according to interpretive description. Quantitative and qualitative data will be analysed separately and then merged and interpreted. This study will expand our understanding of self-care in people with T2DM. The expected outcome will be a better understanding of the effect of self-care on glycaemic control and therefore clinical outcomes and costs.

Abstract

Background: Some, but not all, studies report associations between shift work and hypertension, suggesting that particular subgroups may be at risk. We examined moderating effects of sleep duration and circadian preference on the relationship between shift work and new blood pressure (BP) medicine use at follow-up. Methods and Results: Baseline and 5-year follow-up data from the UK Biobank cohort (N=9200) were used to generate logistic regression models for shift workers and nonshift workers. The moderating effects of sleep duration (short ≤6 hours; adequate 7–8 hours; long ≥9 hours) and circadian preference (morning “larks;” intermediate; evening “owls”) at baseline were examined with new BP medicine use at follow-up, adjusting for age, sex, race, education, employment, urban/rural, cardiovascular disease family history, depression, alcohol intake, physical activity, diet, smoking, and body mass index. The sample was predominately middle aged (55.3±7.4), female (57.3%), and white (97.9%). Most reported adequate sleep duration (7–8 hours, 73.7%) and were intermediate type (65.3%); 8.0% were shift workers at baseline. Only 6.5% reported new BP medicine use at follow-up. Short sleep duration was a significant moderator of new BP medicine use in shift workers. Among short sleepers, shift workers had a 2.1-fold increased odds of new BP medicine use compared with nonshift workers (odds ratio=2.08, 95% CI=1.21–3.58, P=0.008). In those reporting adequate (odds ratio=0.82, 95% CI=0.54–1.25, P=0.35) and long sleep (odds ratio=0.64, 95% CI=0.11–3.54, P=0.60), this relationship was protective but nonsignificant. Interaction between circadian preference and shift work on BP medicine use was nonsignificant. Conclusions: Shift workers with short sleep duration may be at risk for hypertension.