Mild sleep restriction increases 24-hour ambulatory blood pressure in premenopausal women with no indication of mediation by psychological effects.

BACKGROUND: Studies assessing the impact of sleep restriction (SR) on blood pressure (BP) are limited by short study length, extreme SR (<4 hours a night), and lack of attention to psychological distress as a possible mediator. METHODS: A community-based cohort was assembled with 237 women (age 34.1 ±â€¯13.5 years; body mass index 25.4 ±â€¯5.4 kg/m2), and a randomized, crossover, intervention study was conducted in 41 women (24 completed: age 30.2 ±â€¯6.5 years; body mass index 24.3 ±â€¯2.8 kg/m2) to determine the causal effect of SR on BP. Sleep was maintained as usual (HS) or reduced by 1.5 hours a night (SR) for 6 weeks. In the cohort, associations between sleep and psychosocial factors were evaluated using multivariable models adjusted for demographic and clinical confounders. In the intervention study, in-office BP was measured weekly; ambulatory BP was measured at end point. Psychological factors were assessed at baseline and end point. Mixed-model analyses with total sleep time (TST, main predictor), week and fraction of time spent in physical activity (covariates), and subject (random effect) were performed. RESULTS: Among the community cohort, higher perceived stress, stressful events and distress, and lower resilience were associated with shorter sleep, worse sleep quality, and greater insomnia symptoms (P < .05). In the intervention, systolic BP increased as TST decreased (TST × week interaction, [coefficient ±â€¯standard error] -0.0097 ±â€¯0.0046, P = .036). Wake ambulatory diastolic blood pressure (-0.059 ±â€¯0.022, P = .021) and mean arterial pressure (-0.067 ±â€¯0.023, P = .018) were higher after SR versus HS. Psychological distress variables were not affected by TST and did not mediate the effects of SR on BP. CONCLUSIONS: These results suggest that SR influences CVD risk in women via mechanisms independent of psychological stressors.

Impact of change in bedtime variability on body composition and inflammation: secondary findings from the Go Red for Women Strategically Focused Research Network.

Variability in daily sleep patterns is an emerging factor linked to metabolic syndrome. However, whether reducing bedtime variability improves markers of disease risk has not been tested. Here, we assessed whether body composition and inflammation were impacted by changes in bedtime variability over a 6-week period, during which, women were instructed to maintain healthy, habitual sleep (HS) patterns (one arm of a randomized trial). Data were available for 37 women (age 34.9 ± 12.4 years, BMI 24.7 ± 2.9 kg/m2, sleep duration 7.58 ± 0.49 h/night). Body composition and leukocyte platelet aggregates (LPA) were measured at baseline and endpoint using magnetic resonance imaging and flow cytometry, respectively. Sleep data were collected daily using wrist actigraphy. Change in bedtime variability was calculated as the difference in the standard deviation (SD) of bedtimes measured during the 2-week screening period and the 6-week intervention period. Results showed that women who reduced their bedtime variability (n = 29) during the intervention had reductions in total (P < 0.001) and subcutaneous adipose tissue (P < 0.001) relative to women who increased/maintained (n = 8) bedtime variability. Similar effects were observed for LPA levels between women who reduced vs increased/maintained bedtime variability (P = 0.011). Thus, reducing bedtime variability, without changing sleep duration, could improve cardiometabolic health by reducing adiposity and inflammation.

Building a consensus on community health workers' scope of practice: lessons from New York.

OBJECTIVES: We evaluated efforts in New York to build a consensus between community health workers (CHWs) and employers on CHWs' scope of practice, training standards, and certification procedures. METHODS: We conducted multiple-choice surveys in 2008 and 2010 with 226 CHWs and 44 employers. We compared CHWs' and employers' recommendations regarding 28 scope of practice elements. The participatory ranking method was used to identify consensus scope of practice recommendations. RESULTS: There was consensus on 5 scope of practice elements: outreach and community organizing, case management and care coordination, home visits, health education and coaching, and system navigation. For each element, 3 to 4 essential skills were identified, giving a total of 27 skills. These included all skills recommended in national CHW studies, along with 3 unique to New York: computer skills, participatory research methods, and time management. CONCLUSIONS: CHWs and employers in New York were in consensus on CHWs' scope of practice on virtually all of the detailed core competency skills. The CHW scope of practice recommendations of these groups can help other states refine their scope of practice elements.

Information on Bedtimes and Wake Times Improves the Relation Between Self-Reported and Objective Assessments of Sleep in Adults.

STUDY OBJECTIVES: To investigate the correlation between self-reported and objective measures of total sleep time (TST) in adults and examine whether sex, race/ethnicity, and weight status influence this association. METHODS: Participants were individuals who screened for sleep intervention studies, providing > 7 days of wrist actigraphy sleep data (TSTobj) and reporting sleep duration (TSTPSQI) using the Pittsburgh Sleep Quality Index (PSQI) questionnaire (n = 53 men, 60 women; 59% minority/Hispanics; age 30.9 ± 9.7 years; body mass index 26.2 ± 3.2 kg/m2). In addition, TSTbed/wake was calculated as the difference between bedtime and waketime, minus the time to fall asleep, from the PSQI. Univariate regression analyses were performed to assess the relation between TSTobj and TSTPSQI and TSTbed/wake and compare the relation by sex, race, and ethnicity. Bland-Altman tests were done to assess bias by sex, race/ethnicity, weight status, and sleep quality. RESULTS: TSTbed/wake correlated with TSTobj (r = .57, P < .0001). TSTPSQI and TSTbed/wake were greater than TSTobj (0.63 ± 0.99 hours and 0.79 ± 0.76 hours, respectively, both P < .0001). The difference between TSTPSQI and TSTobj did not vary by sex (ß = .12, P = .52), race/ethnicity (ß = .15, P = .48), age (ß = -.01, P = .27), or body mass index (ß = .04, P = .13) whereas that between TSTbed/wake and TSTobj varied by age (ß = -.020, P = .0051), BMI (ß = .054, P = .0021), race/ethnicity (ß = .36, P = .021), and sleep efficiency (ß = -.089, P < .0001). CONCLUSIONS: Calculating TST using self-reported bedtimes and wake times provided TST estimate that correlated with TSTobj but greater over-reporting occurred in younger and heavier individuals, non-whites or Hispanics, and those with low sleep efficiency. In clinical and research settings, asking individuals to report bedtimes, wake times, and length of time to fall asleep may more accurately estimate TST than asking about sleep duration alone.