1213 Sleepfect Tracker: A Crossplatform Mobile Researchkit App For Sleep Self-management

Introduction

We created Sleepfect Tracker, a researchkit-based cross platform app to explore the feasibility and acceptability of a sleep tracking app for sleep self-management.

Methods

We developed Sleepfect Tracker app on Appbakery, a DIY app making platform using ResearchKit for iOS and ResearchDroid for Android users. Sleepfect allows participants to track their sleep behavior (weekly via sleep diary) and environment (monthly), as well as their total sleep time and step counts data via Apple’s HealthKit, Android step count sensors, or Fitbit (wearable). Three hundred and ninety-five (395) individual from around the globe downloaded the app and 163 unique users answered surveys on their sleep behavior, environment, and architecture. In total we collected 6429 sleep and 2882 step data points and provided insights into user sleep behavior and sleep environment. We also analyzed whether sleep duration was associated with steps.

Results

Regarding immediate sleep environment and behavior, 11.1% worked or studied in bed, 27.0% reported having pets in bed, 39.7% red in bed prior to sleep, 40.3% watched TV in bed prior to sleep, 11.3% drank alcohol prior to bed, 9.8% smoked prior to bed or wake during night, 8.1% ate snack at bedtime, and 6.5% ate when they awake at night. 74.3% of the participants used electronic devices in their bedroom. Of the participants who used electronic devices in the bedroom, 52.1% had an average sleep duration of 6-8 hours and 29.8% reported sleeping 4-6 hours. Of the participants who did not use electronic devices in bedroom, 30.1% slept 4-6 hours, 31.8% slept 6-8 hours, and 32.45% slept 8-10 hours, on average. The relationship between steps count and sleep hours was trending, r=.16, p=.07.

Conclusion

Users can evaluate their sleep habits, monitor daily sleep-related behaviors through Sleepfect tracker. The app demonstrated initial usability and feasibility, but long-term usability and effectiveness must be evaluated. Further investigations on which functions will be more useful to help user to improve their sleep and engage users should be considered.

Support

K01HL135452, R01MD007716, R01HL142066, and K07AG052685

0621 Utilization of the Ares to Predict OSA Among Blacks Using Home-Based Watchpat Recording

Introduction

In two waves of data we collected in Brooklyn New York, we observed blacks were at high risk for obstructive sleep apnea (OSA). In the NIH-funded study ‘Metabolic Syndrome Outcome Study (MetSO), blacks enrolled from primary-care settings had a 59% risk of OSA. Similarly, blacks surveyed in churches and barbershops had a 43% risk of OSA. While these studies showed higher than expected risk as noted in the general population (29%), it remains uncertain how many of those blacks would be diagnosed with OSA in that population. The purpose of this study was to explore the rate of OSA using the WatchPat device in a community-based setting.

Methods

Data were collected from an NIH-funded study ‘Peer-Enhanced Education to Reduce Sleep Ethnic Disparities, designed to navigate blacks at risk of OSA to receive timely diagnosis and treatment using peer-delivered linguistically and culturally tailored sleep health education. Blacks were screened for OSA using the Apnea Risk Evaluation System (ARES) Questionnaire; a score ≥6 denoted moderate-high OSA risk. Individuals were asked to wear the WatchPAT 200 for one night during a week-long sleep assessment. WatchPat 200 measures SaO2 to determine respiratory-related arousals, defined as an Apnea-Hypopnea Index (AHI) ≥5, which is used to identify and diagnose OSA. We used SPSS 25.0 to perform logical regression analysis to assess associations between ARES and WatchPat AHI.

Results

A sample of 111 blacks provided valid ARES and WatchPat data for the present analyses. Of the sample, the mean age was 62.26 (SD=13.52 years; female = 55%); 49% reported annual income >20K and 79.5% reported a high school education. Moreover, 27% reported high blood pressure, 13%, diabetes, and 65% were overweight/obese. Multivariate-adjusted logical regression analyses indicated that blacks at risk for OSA were 66% more likely to receive an OSA diagnosis based on WatchPat AHI data (OR = 1.662, p < 0.01). The model adjusted for age, sex, income, and education.

Conclusion

The present study demonstrated that blacks at risk for OSA at the community level have a significant likelihood of receiving an OSA diagnosis using home-based recordings.

Support

NIH Support (T32HL129953, RO1MD007716, K01HL135452 and K07AG052685).

1114 Urbanicity And The Sleep-mental Health Relationship

Introduction

Inadequate sleep has been found to be associated with poor mental health. This is especially true in low-income and minority populations, who are concentrated in cities. It is not understood to what degree living in a city vs. a rural environment affects sleep and resulting mental health outcomes. This study seeks to understand how living in an urban environment affects the relationship between inadequate sleep and mental health.

Methods

The study used data from the 2018 US Behavioral Risk Factor Surveillance System (BRFSS,) a nationwide health dataset collected by telephone. Respondents were classified as living in either an urban or rural environment based on their zip code. Respondents reported hours of sleep per night and mental health status. This study classified mental health status based on whether the respondent reported one or more incidences of poor mental health in the previous 30 days.

Results

After filtration, 348,540 respondents were split into urban and rural groups. Binary logistic regression was run in each group to compare how much living in an urban environment contributed to the relationship between sleep duration and mental health. Sleep in the analysis was found to significantly contribute to both models; urban X2(15, N=295,796) = 11,485.70, p <0.001 rural X2(15, N=52,744) = 2,465.64, p <0.001. The estimated odds ratio resulted in a decrease of 13.9% [Exp(B) = 0.861] in reported poor mental health for every unit increase of sleep in the urban population, and decrease of 14.9% [Exp(B) = 0.851] in the rural population.

Conclusion

In urban and rural dwellers, sleep duration predicted poor mental health. Contrary to expectations, sleep was more strongly tied to mental health in rural than urban populations. This was true even after controlling for sex, income, and education level. Further research should seek to understand how environment affects sleep and mental health.

Support

This study was supported by funding from the NIH: R01MD007716, R01HL142066, R01AG056531, K01HL135452, and K07AG052685.

1046 Assessing Sleep-Related Hypertension Risks Using JNC 8 Guidelines: Analysis Of The National Health And Nutrition Examination Survey Data

Introduction

Associations between self-reported sleep duration and risk of hypertension (HTN) are well established. The level of sleep-related HTN risk based on the new JNC 8 classification guidelines requires further research. In this study, we modeled the associations of insufficient sleep with HTN using the National Health and Nutrition Examination Survey (NHANES).

Methods

Data were extracted from the 2006-2016 NHANES (n=38,540), a nationally representative study of the US civilian population. Self-reported demographic and sleep duration were determined from household interview questions. Insufficient sleep was categorized as sleeping <7hrs. Using 2017 ACC/AHA guidelines, HTN was classified as elevated (SBP:120-129mmHg and DBP <80mmHg, Stage I (SBP:130-139mmHg and DBP:80-89mmHg), or Stage II (SBP ≥140mmHg and DBP ≥90mmHg). Logistic regression modeling was performed using R.

Results

Participants’ ages ranged from 18-85 years. Of the sample, 51% were female, 41% white, 22% black, 26% Hispanic, 8% others; 46% were married, and 25% completed <high school. The model showed strong age and BMI-adjusted associations of insufficient sleep with HTN at all levels: (elevated: OR=1.079, CI=1.03-1.13; Stage I: OR=1.127, CI=1.07-1.18, and Stage II: OR=1.334, CI=1.17-1.52). Important sex and race/ethnicity differences in sleep-related HTN risks were observed: males (elevated: OR=1.024, CI=0.95-1.10; Stage I: OR=1.077, CI=1.01-1.15, and Stage II: OR=1.254, CI=1.06-1.48); females (elevated: OR=1.125, CI=1.05-1.21; Stage I: OR=1.170, CI=1.08-1.26, and Stage II: OR=1.445, CI=1.17-1.79); whites (elevated: OR=1.007, CI=0.93-1.08; Stage I: OR=1.030, CI=0.95-1.12, and Stage II: OR=1.131, CI=0.90-1.43); blacks (elevated: OR=1.047, CI=0.94-1.16; Stage I: OR=1.080, CI=0.97-1.20, and Stage II: OR=1.179, CI=0.95-1.46); and Hispanics (elevated: OR=1.066, CI=0.94-1.21; State I: OR=1.089, CI=0.96-1.24, and Stage II: OR=1.337, CI=0.92-1.92).

Conclusion

Our analyses showed that sleep-related HTN risks vary as a function of individual’s sex and race/ethnicity. Increasing sleep duration at all HTN severity level is important and males and Hispanics at Stage II HTN might benefit the most.

Support

This study was supported by funding from the NIH: R01MD007716,R01HL142066, R01AG056531, T32HL129953, K01HL135452 and K07AG052685

1093 Population-level Suicide Ideation: Impact Of Combined Roles Of Sleep Duration, Sleep Disturbance, And Daytime Sleepiness

Introduction

Poor sleep has been shown to be related to suicide ideation and depressed mood, but population-level studies have not been done to explore the specific issues within sleep that effect mood, specifically leading to suicide ideation.

Methods

Data from adults 18 and older in the 2015-2016 National Health and Nutrition Examination Survey (NHANES) who provided complete data were used (N=5,123). Suicide ideation was recorded as the presence of thinking that “you would be better off dead” in the past 2 weeks. Sleep duration was recorded in half-hour increments and transformed to represent absolute distance from 7 hours (to model u-shaped association). Sleep disturbance was recorded as presence of “difficulty falling asleep, staying asleep, or sleeping too much” non, several days, or more than half the days of the past 2 weeks. Sleepiness was frequency feeling “overly sleepy during the day” in the past 12 months. Covariates included age, sex, race/ethnicity, and presence of depressed mood in the past 2 weeks. Additional impact of difficulty thinking/concentrating in the past 2 weeks was explored. NHANES sample weights were used in analyses.

Results

In adjusted analyses, increase likelihood of suicide ideation was associated with distance from 7hrs (OR=1.24/hr, p=0.008), sleep difficulties most of the time (OR=2.46, p=0.001), but not sleepiness. When both sleep variables were adjusted for each other, results remained significant for U-shaped sleep duration (OR=1.21/hr, p=0.02) and sleep disturbance (OR=2.31, p=0.003). These were attenuated but remained significant when difficulty thinking/concentrating was introduced; a significant sobel test (p<0.0001) suggested partial mediation, with this variable accounting for approximately 13% of the variance of the relationship to sleep.

Conclusion

In the population, improper and poor sleep was associated with a greater risk of suicide ideation.

Support

Dr. Grandner is supported by R01MD011600

0140 Dietary Macronutrients and Sleep Duration, Sleep Disturbance, and Daytime Fatigue

Introduction

We examined nationally-representative data on macronutrients associated with multiple dimensions of sleep health.

Methods

Data were obtained from the 2015–2016 National Health and Nutrition Examination Survey, (N=5,266 adults). Standard 24-h dietary recall procedures were analyzed to establish daily consumption of protein, carbohydrates, sugar, fiber, total fat, and saturated fat. Self-reported habitual sleep duration was categorized as very short (<5h), short (5–6.5h), normal (7-8h), and long (>8h). Sleep disturbance and daytime tiredness/fatigue were self-reported as either none, mild, moderate, or severe. Weighted multinomial logistic regressions with sleep variables as outcome/dependent variable and percent of each macronutrient as independent variable were adjusted for age, sex, race/ethnicity, education, and body mass index.

Results

Increased protein was associated with a decreased likelihood of very short sleep (RRR=0.01, p=0.019) and severe fatigue (RRR=0.06, p=0.020). Increased carbohydrates was associated with an increased likelihood of very short (RRR=61.17, p=0.001), short (RRR=3.96, p=0.017), and long (RRR=2.58, p=0.041) sleep, severe sleep disturbance (RRR=9.37, p=0.010) and fatigue (RRR=7.61, p=0.009). Increased sugar was associated with an increased likelihood of very short (RRR=24.17, p=0.001), short (RRR=3.29, p=0.017), and long (RRR=2.22, p=0.046) sleep, as well as mild (RRR=2.36, p=0.041) and severe (RRR=10.70, p=0.001) sleep disturbance, and severe fatigue (RRR=12.98, p<0.0005). Increased fiber was associated with a decreased likelihood of long (RRR=0.01, p=0.032) sleep and severe sleep disturbance (RRR<0.01, p<0.0005), as well as moderate (RRR<0.01, p=0.026) and severe (RRR<0.01, p<0.0005) fatigue. Increased fat was associated with a decreased likelihood of very short sleep (RRR=0.01, p=0.010). Increased saturated fat was associated with a decreased likelihood of very short sleep (RRR<0.01, p=0.017).

Conclusion

Protein and fiber were associated with better sleep profiles overall and carbohydrate and sugar were associated with worse sleep, as well as increased prevalence of sleep disturbances and fatigue.

Support

Dr. Grandner is supported by R01MD011600

0235 Sleep Duration and Timing Associated with Eating Behaviors: Data from NHANES 2015–2016

Introduction

Previous studies have shown that, in the laboratory, sleep deprivation leads to unhealthy eating patterns. In real-world samples, lack of sleep is associated with obesity. Few real-world studies of sleep and food intake patterns exist, especially from nationally-representative samples.

Methods

Data from the 2015–2016 National Health and Nutrition Examination Survey (NHANES) were used. NHANES is a national-representative survey collected by the CDC. N=6,291 participants provided data about dietary behaviors and sleep timing. Dietary behaviors included the number of meals not made at home in the past 7 days (NOTHOME), number of fast food/pizza meals in the past 7 days (FASTFOOD), number of pre-made meals in the past 30 days (PREMADE), and number of frozen meals in the past 30 days (FROZEN). Linear regression models examined these as outcomes and predictors including bedtime (minutes), waketime (minutes), sleep duration (hours), and daytime tiredness/fatigue (never, rarely, sometimes, often). Covariates included age, sex, education, income/poverty ratio, race/ethnicity, and body mass index.

Results

Number of meals not made at home (NOTHOME) was associated with a later bedtime (B=2.25, p=0.01) and shorter sleep duration (B=-0.12, p=0.01). FASTFOOD was associated with shorter sleep (B=-0.13,p=0.003) and tiredness/sleepiness sometimes (B=0.77, p=0.007) and often (B=0.55, p=0.03). FROZEN meals were associated with a later waketime (B=3.31, p=0.003) and tiredness/sleepiness sometime (B=1.20, p=0.025) and often (B=1.60, p=0.04). A sleep duration by bedtime interaction was not significant for any outcomes. In models that included overall levels of anxiety, these relationships were maintained.

Conclusion

This is one of the largest studies to show that habitual sleep patterns are associated with real-world food choices. In particular, shorter sleep duration and tiredness/sleepiness are associated with more ready-made and fast food meals. It is possible that lack of sleep leads to worse food choices, or that stress leads to both lack of sleep and easier food options. Given the often poor nutritive value of foods consumed outside the home and pre-prepared foods, these associations may in part explain the influence of sleep on cardiometabolic risk factors.

Support

Dr. Grandner is supported by R01MD011600

Four-Year Trends in Sleep Duration and Quality: A Longitudinal Study Using Data from a Commercially Available Sleep Tracker

Background

Population estimates of sleep duration and quality are inconsistent because they rely primarily on self-reported data. Passive and ubiquitous digital tracking and wearable devices may provide more accurate estimates of sleep duration and quality.

Objective

This study aimed to identify trends in sleep duration and quality in New York City based on 2 million nights of data from users of a popular mobile sleep app.

Methods

We examined sleep duration and quality using 2,161,067 nights of data captured from 2015 to 2018 by Sleep Cycle, a popular sleep-tracking app. In this analysis, we explored differences in sleep parameters based on demographic factors, including age and sex. We used graphical matrix representations of data (heat maps) and geospatial analyses to compare sleep duration (in hours) and sleep quality (based on time in bed, deep sleep time, sleep consistency, and number of times fully awake), considering potential effects of day of the week and seasonality.

Results

Women represented 46.43% (1,003,421/2,161,067) of the sample, and men represented 53.57% (1,157,646/2,161,067) of individuals in the sample. The average age of the sample was 31.0 years (SD 10.6). The mean sleep duration of the total sample was 7.11 hours (SD 1.4). Women slept longer on average (mean 7.27 hours, SD 1.4) than men (mean 7 hours, SD 1.3; P<.001). Trend analysis indicated longer sleep duration and higher sleep quality among older individuals than among younger (P<.001). On average, sleep duration was longer on the weekend nights (mean 7.19 hours, SD 1.5) than on weeknights (mean 7.09 hours, SD 1.3; P<.001).

Conclusions

Our study of data from a commercially available sleep tracker showed that women experienced longer sleep duration and higher sleep quality in nearly every age group than men, and a low proportion of young adults obtained the recommended sleep duration. Future research may compare sleep measures obtained via wearable sleep trackers with validated research-grade measures of sleep.

Sleep tracking: A systematic review of the research using commercially available technology

PURPOSE OF REVIEW

To systematically review the available research studies that characterize the benefits, uncertainty, or weaknesses of commercially-available sleep tracking technology.

RECENT FINDINGS

Sleep is a vital component of health and well-being. Research shows that tracking sleep using commercially available sleep tracking technology (e.g., wearable or smartphone-based) is increasingly popular in the general population.

METHODS

Systematic literature searches were conducted using PubMed/Medline, Embase (Ovid) the Cochrane Library, PsycINFO (Ovid), CINAHL, and Web of Science Plus (which included results from Biosis Citation Index, INSPEC, and Food, Science & Technology Abstracts) (n=842).

STUDY INCLUSION AND EXCLUSION CRITERIA

Three independent reviewers reviewed eligible articles that administered a commercially-available sleep tracker to participants and reported on sleep parameters as captured by the tracker, including either sleep duration or quality. Eligible articles had to include sleep data from users for >=4 nights.

The Impact of Daytime Sleepiness on Dietary Intake in Overweight/Obese Individuals with Diabetes and Chronic Kidney Disease (P08-019-19)

Objectives

Sleep disturbances have been recognized as risk factors in the etiology of chronic disease and obesity. Although multifactorial, the link may be due to dietary intake, mediated by appetite hormones, hedonic feeding, altered intake times, and extended intake hours. The purpose of this study was to examine daytime sleepiness and dietary intake in overweight/obese individuals with diabetes and chronic kidney disease.

Methods

Three-day food records were completed at baseline from 133 participants in an ongoing lifestyle intervention study, and analyzed using the Nutrition Data System for Research (2014). Daily dietary intakes were summarized for energy (kcal), carbohydrate (g), fat (g), alcohol (g), added sugars (g), and refined grains (ounce equivalents). Self-reported measures of daytime sleepiness were measured using the Epworth Sleepiness Scale (ESS). Participants rated their level of sleepiness (scale 0–3) in eight different situations, which were summed to provide a total score. The ESS scores were dichotomized with 0–10 indicating “normal daytime sleepiness” (NDS) and 11–24 indicating “excessive daytime sleepiness” (EDS). IBM SPSS Statistics (version 25.0) was utilized to complete the descriptive and inferential analyses. Independent sample t-tests examined differences between the two sleepiness groups. Results were considered significant at p ≤ 0.05.

Results

The participants were 53.4% male, 89.5% non-Hispanic, 65.4% white, and 65.0 ± 9.4SD years of age with a mean body mass index of 34.0 ± 5.1SD kg/m2. Although there were no differences between sleepiness groups for fat and alcohol intakes, the EDS group reported a higher mean intake of carbohydrate (EDS: 247 ± 148SD g, NDS: 183 ± 76SD g; P = 0.048) and refined grains (EDS: 7.0 ± 6.5SD ounce, NDS: 4.2 ± 3.0SD ounce; P = 0.048). Although not statistically significant, the EDS group exhibited a trend toward having a higher energy intake (EDS: 2130 ± 1083SD kcal, NDS: 1776 ± 618SD kcal; P = 0.133) and added sugar intake (EDS: 44 ± 53SD g, NDS: 28 ± 26SD g, P = 0.179).

Conclusions

Similar to other reports, sleep disturbances, as noted by EDS, were associated with a higher intake of carbohydrate and refined grains. The results of this study support the role of sleep, alongside diet and physical activity, as important modifiable risk factors for chronic disease and obesity.

Funding Sources

National Institutes of Health (NIDDK, NINR)

Feasibility and Acceptability of a Culturally Tailored Website to Increase Fruit and Vegetable Intake and Physical Activity Levels in African American Mother-Child Dyads: Observational Study

BACKGROUND

African American youth (aged 8-14 years) do not adhere to national dietary and physical activity guidelines. Nonadherence to these recommendations contributes to disproportionate rates of obesity compared with their white counterparts. Culturally tailored electronic health (eHealth) solutions are needed to communicate nutrition and physical activity messages that resonate with this target population.

OBJECTIVE

This study aimed to identify the impact of exposure to a website hosting culturally tailored cartoons to inspire fruit and vegetable uptake and physical activity levels in African American mother-child dyads.

METHODS

Statistical analysis included paired sample t tests to evaluate knowledge gains, self-efficacy, and readiness to change. Adapted items from Prochaska's Stages of Change toward the following 4 behaviors were assessed with pre- and posttest surveys: (1) fruit and vegetable selection on my plate, (2) meal preparation, (3) fruit and vegetable selection outside of home, and (4) physical activity. Open-ended comments on videos from mother-child dyads were used to determine user acceptance. Observations of repeated responses during content analysis informed coding and development of key themes.

RESULTS

A final sample size of 93 mother-child dyads completed the study. Mothers reported significant improvement from precontemplation or contemplation stages to preparation or action stages for (1) fruit and vegetable selection on her plate (P=.03), (2) meal preparation for her family (P=.01), (3) fruit and vegetable selection outside the home (P<.001), and (4) physical activity (P<.001). Significant improvements were found in knowledge, stage of change, and self-efficacy for the 4 target behaviors of interest (P<.001). Children's open-ended commentary reported vicarious learning and positive character identification with brown-skinned cartoons exhibiting healthful food and exercise behaviors. Mothers commented on the lack of accessible produce in their neighborhoods not depicted in the cartoon videos.

CONCLUSIONS

Culturally adapted cartoons that incorporate tailored preferences by African American families, such as race or demography, may help increase adherence to target health behaviors when developing eHealth behavior solutions.

Differences in Insomnia Symptoms between Immigrants and Non-Immigrants in Switzerland attributed to Emotional Distress: Analysis of the Swiss Health Survey

Migration can be a stressful experience and may lead to poor health and behavioral changes. The immigrant population in Switzerland is disproportionately burdened by several negative health outcomes, chief among these is mental health issues. The aim of the study was to investigate whether sleep disturbances are more prevalent among immigrants compared to non-immigrants and whether emotional distress might explain sleep differences. Based on the Swiss Health Survey 2012 dataset, we analyzed the data of 17,968 people, of which 3406 respondents were immigrants. We examined variables including insomnia symptoms, emotional distress and clinical and socio-demographic data using unadjusted and adjusted generalized linear models. Compared to non-immigrants, immigrants suffer significantly more often from insomnia symptoms. Immigrants also endured higher levels of emotional distress. Higher values of emotional distress are related to other symptoms of sleep disorders. Immigrants with emotional distress were at significant risk of sleep disturbances. Sleep disparities between immigrants and non-immigrants may be influenced by emotional distress. Migration health care should address emotional distress, a more proximal and modifiable factor, as a possible cause of insomnia symptoms in immigrants.

The nature and scope of patient-sharing network research: a novel, important area for network science

A robust literature exists that draws on social network approaches to understand connections among individuals, and healthcare and behavior-related implications. This article offers commentary on the scoping review conducted by Dugoff et al. that examines "patient-sharing" networks, their characteristics, and various methodological approaches. The scoping review conducted by Dugoff et al. examines the characteristics and methods employed in patient-sharing network studies. It identified the most common measures used in patient-sharing network research, as well as theories used in patient-sharing network studies. Dugoff et al. also identified many studies that examined healthcare utilization considerations for patient sharing. Understanding the connections between providers and the flow of patients between providers could lend insight into barriers and enablers to efficient healthcare systems.

Sleep Disorders and Symptoms in Blacks with Metabolic Syndrome: The Metabolic Syndrome Outcome Study (MetSO)

Introduction

Sleep disturbance is a major public health issue and is comorbid with the cluster of conditions associated with metabolic syndrome (MetS). Our study explored the presence of sleep disturbance, including daytime sleepiness, the risk for obstructive sleep apnea (OSA), and insomnia symptoms, in a cohort of adult Black men and women with MetS.

Methods

Patients (n=1,013) from the Metabolic Syndrome Outcome Study (MetSO), 2009-2012, met criteria for MetS based on guidelines from the National Cholesterol Education Program's Adult Treatment Panel and provided sociodemographic data and the Apnea Risk Evaluation System (ARES) questionnaire to assess OSA risk, sleep characteristics, and physician-reported diagnosis of a sleep disorder.

Results

Prevalence of the components of MetS included: diabetes (60%); obesity (67%); hypertension (94%); and dyslipidemia (74%). Based on the ARES, 49% were at risk for OSA. Of all study patients, slightly more than half (53%) reported feeling sleepy during the day, and 10% reported an insomnia diagnosis. The most common sleep disturbance reported by 46% of the patients was early morning awakenings (EMA). This was closely followed by 42% who reported difficulty staying asleep (DSA) and 38% reporting difficulty falling asleep (DFA). Seventy percent reported short sleep (≤ 6 hours), whereas a minority (19%) reported long sleep (≥ 9 hours). Only 12% used sleep aids. Women, compared with men, reported greater daytime sleepiness, greater DFA, and greater DSA (57% vs 45%; 41% vs 32.4%; 45% vs 37%), respectively.

Conclusion

Blacks with MetS reported insomnia symptoms and insomnia disorder, use of sleep aids, feeling sleepy during the day, and inadequate sleep durations. The presence of these sleep characteristics suggests that patients with MetS should be referred for further sleep assessment.

Peptidase inhibitors in tick physiology

Peptidase inhibitors regulate a wide range of physiological processes involved in the interaction between hematophagous parasites and their hosts, including tissue remodeling, the immune response and blood coagulation. In tick physiology, peptidase inhibitors have a crucial role in adaptation to improve parasitism mechanisms, facilitating blood feeding by interfering with defense-related host peptidases. Recently, a larger number of studies on this topic led to the description of several new tick inhibitors displaying interesting novel features, for example a role in pathogen transmission to the host. A comprehensive review discussing these emerging concepts can therefore shed light on peptidase inhibitor functions, their relevance to tick physiology and their potential applications. Here, we summarize and examine the general characteristics, functional diversity and action of tick peptidase inhibitors with known physiological roles in the tick-host-pathogen interaction.

National patterns of physician management of sleep apnea and treatment among patients with hypertension

STUDY OBJECTIVES

Sleep apnea is associated with hypertension, and treatment may improve outcomes. We examine national burden of sleep apnea, rates of sleep apnea treatment, and whether racial/ethnic disparities exist among patients with hypertension.

METHODS

Data from the National Ambulatory Medical Care Survey/National Hospital Ambulatory Medical Care Survey (NAMCS/NHAMCS), 2005-2012, were analyzed (N = 417,950). We identified hypertension patient visits where sleep apnea diagnosis or complaint was recorded. Primary outcome measures were sleep study, medication, or behavioral therapy (diet, weight loss, or exercise counseling). We used multivariate logistic regression to examine treatment by demographic/clinical factors.

RESULTS

Among patients with hypertension, sleep apnea was identified in 11.2-per-1,000 visits. Overall, patients with hypertension and a sleep disorder were referred for sleep study in 14.4% of visits, prescribed sleep medication in 11.2% of visits, and offered behavioral therapy in 34.8% of visits. Adjusted analyses show behavioral therapy more likely to be provided to obese patients than normal/overweight (OR = 4.96, 95%CI[2.93-8.38]), but less likely to be provided to smokers than nonsmokers (OR = 0.54, 95%CI[0.32-0.93]). Non-Hispanic blacks were less likely to receive medications than non-Hispanic whites (OR = 0.19, 95% CI[0.06-0.65]).

CONCLUSIONS

In the U.S., sleep apnea were observed in a small proportion of hypertension visits, a population at high-risk for the disorder. One explanation for the low prevalence of sleep apnea observed in this patient population at high risk for the disorder is under-diagnosis of sleep related breathing disorders. Behavioral therapy was underutilized, and non-Hispanic Blacks were less likely to receive medications than non-Hispanic Whites.