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Low levels of engagement in implementation science (IS) among health researchers is a multifaceted issue. With the aim of guiding efforts to increase engagement in IS research, we sought to identify barriers to engagement in IS within the health research community. We performed an online survey of health researchers in the United States in 2018. Basic science researchers were excluded from the sample. IS engagement was measured by self-reported conduct of or collaboration on an IS study in the past 5 years. Potential barriers tested were (a) knowledge and awareness of IS, (b) attitudes about IS research, (c) career benefits of IS, (d) research community support, and (e) research leadership support. We performed simple logistic regressions and tested multivariable logistic regression models of researcher characteristics and potential barriers as predictors of IS engagement. Of the 1,767 health researchers, 49.7% indicated they engaged in an implementation study. Being able to define IS (aOR 3.42, 95%CI 2.68-4.36, p < .001) and having attended IS training (aOR 3.77, 95%CI 2.96-4.81, p < .001) were associated with engaging in IS research. Among other potential barriers tested, perceptions that engaging in IS would not be good for their career (aOR 0.29, 95%CI 0.2-0.41, p < .001) was strongly associated with decreased engagement in IS research. Efforts to increase researcher familiarity with IS methods and foster support for IS within research communities, along with decreasing barriers to funding and publishing, are likely to be most effective for increasing engagement in IS research., (© Society of Behavioral Medicine 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Increased left ventricular (LV) mass and endothelial dysfunction are important risk factors for cardiovascular mortality and morbidity. However, it is not clear whether endothelial dysfunction is associated with increased LV mass. We tested the hypothesis that impaired flow-mediated vasodilatation (FMD) is associated with increased LV mass in a population-based multiethnic cohort., Methods: As a part of the Northern Manhattan Study (NOMAS), we performed two-dimensional echocardiography and FMD assessment during reactive hyperemia by high-resolution ultrasonography in 867 stroke-free community participants. LV mass was calculated according to an established method. LV hypertrophy was defined as the 90th percentile of sex-specific LV mass indexed for body surface area among normal subjects. Multivariable models were used to test the association of FMD with LV mass., Results: In multiple linear regression analysis adjusting for age, sex, body mass index, systolic blood pressure, antihypertensive medications, low-density lipoprotein cholesterol, diabetes, smoking, hematocrit, and race-ethnicity, FMD was inversely associated with LV mass (beta = -1.21 +/- 0.56, P = 0.03). The association persisted after further adjustment for any component of blood pressure (systolic, mean, and pulse pressure). In univariate logistic regression analysis, each 1% decrease in FMD was associated with an 8% higher risk of LV hypertrophy (odds ratio 1.08, 95% confidence interval 1.03-1.13 per each FMD point P < 0.01)., Conclusions: Impaired FMD is associated with LV mass, independent of other factors associated with increased LV mass. Endothelial dysfunction might be a potential risk factor for LV hypertrophy.

Background: Although inflammatory markers may be associated with risk of cardiovascular events, few data are available regarding these markers and their association with left ventricular hypertrophy (LVH). We sought to evaluate whether inflammatory markers were independently associated with LVH in a multiethnic population in northern Manhattan., Methods: A population-based cross-sectional study was conducted in 660 participants without stroke, who had undergone both transthoracic echocardiography and testing for soluble tumor necrosis factor receptor (sTNFR) 1, interleukin (IL)-6, and high-sensitivity C-reactive protein (hsCRP). LV mass was calculated according to an established formula. LVH was defined as LV mass >90th percentile of the participants., Results: The mean age was 67.4 +/- 8.8 years, 35.5% were men, 61.7% were Hispanic, 19.7% were black, and 18.6% were white. In univariate analyses, hsCRP, IL-6, and sTNFR1 were significantly associated with LV mass. Multiple linear regression analyses demonstrated that sTNFR1 (P = 0.0008) was associated with LV mass after adjusting for demographic and medical risk factors, but hsCRP and IL-6 were not. When all markers were included in the same model, sTNFR1 remained significant, but hsCRP and IL-6 did not. Compared with the lowest quartile of sTNFR1, those in the highest quartile were more likely to have LVH (odds ratio = 1.84, 95% confidence interval, 0.97-3.64, P = 0.06)., Conclusions: sTNFR1, but not hsCRP nor IL-6, is independently associated with increased LV mass. Chronic subclinical inflammation including the TNFR1-associated system may contribute to LVH.

Study Objectives: To explore age differences in the relationship between sleep duration and mortality by conducting analyses stratified by age. Both short and long sleep durations have been found to be associated with mortality. Short sleep duration is associated with negative health outcomes, but there is little evidence that long sleep duration has adverse health effects. No epidemiologic studies have published multivariate analyses stratified by age, even though life expectancy is 75 years and the majority of deaths occur in the elderly., Design: Multivariate longitudinal analyses of the first National Health and Nutrition Examination Survey using Cox proportional hazards models., Setting: Probability sample (n = 9789) of the civilian noninstitutionalized population of the United States between 1982 and 1992., Participants: Subjects aged 32 to 86 years., Measurements and Results: In multivariate analyses controlling for many covariates, no relationship was found in middle-aged subjects between short sleep of 5 hours or less and mortality (hazards ratio [HR] = 0.67, 95% confidence interval [CI] 0.43-1.05) or long sleep of 9 hours or more and mortality (HR = 1.04, 95% CI 0.66-1.65). A U-shaped relationship was found only in elderly subjects, with both short sleep duration (HR = 1.27, 95% CI 1.06-1.53) and long sleep duration (HR = 1.36, 95% CI 1.15-1.60) having significantly higher HRs., Conclusions: The relationship between sleep duration and mortality is largely influenced by deaths in elderly subjects and by the measurement of sleep durations closely before death. Long sleep duration is unlikely to contribute toward mortality but, rather, is a consequence of medical conditions and age-related sleep changes.

Study Objectives: To explore the relationship between sleep duration and diabetes incidence over an 8- to 10-year follow-up period in data from the First National Health and Nutrition Examination Survey (NHANES I). We hypothesized that prolonged short sleep duration is associated with diabetes and that obesity and hypertension act as partial mediators of this relationship. The increased load on the pancreas from insulin resistance induced by chronically short sleep durations can, over time, compromise beta-cell function and lead to type 2 diabetes. No plausible mechanism has been identified by which long sleep duration could lead to diabetes., Design: Multivariate longitudinal analyses of the NHANES I using logistic regression models., Setting: Probability sample (n=8992) of the noninstitutionalized population of the United States between 1982 and 1992., Participants: Subjects between the ages of 32 and 86 years., Measurements and Results: Between 1982 and 1992, 4.8% of the sample (n=430) were determined by physician diagnosis, hospital record, or cause of death to be incident cases of diabetes. Subjects with sleep durations of 5 or fewer hours (odds ratio = 1.47, 95% confidence interval 1.03-2.09) and subjects with sleep durations of 9 or more hours (odds ratio = 1.52, 95% confidence interval 1.06-2.18) were significantly more likely to have incident diabetes over the follow-up period after controlling for covariates., Conclusions: Short sleep duration could be a significant risk factor for diabetes. The association between long sleep duration and diabetes incidence is more likely to be due to some unmeasured confounder such as poor sleep quality.

Study Objectives: Sleep deprivation has been hypothesized to contribute toward obesity by decreasing leptin, increasing ghrelin, and compromising insulin sensitivity. This study examines cross-sectional and longitudinal data from a large United States sample to determine whether sleep duration is associated with obesity and weight gain., Design: Longitudinal analyses of the 1982-1984, 1987, and 1992 NHANES I Followup Studies and cross-sectional analysis of the 1982-1984 study., Setting: Probability sample of the civilian noninstitutionalized population of the United States., Participants: Sample sizes of 9,588 for the cross-sectional analyses, 8,073 for the 1987, and 6,981 for the 1992 longitudinal analyses., Measurements and Results: Measured weight in 1982-1984 and self-reported weights in 1987 and 1992. Subjects between the ages of 32 and 49 years with self-reported sleep durations at baseline less than 7 hours had higher average body mass indexes and were more likely to be obese than subjects with sleep durations of 7 hours. Sleep durations over 7 hours were not consistently associated with either an increased or decreased likelihood of obesity in the cross-sectional and longitudinal results. Each additional hour of sleep at baseline was negatively associated with change in body mass index over the follow-up period, but this association was small and statistically insignificant., Conclusions: These findings support the hypothesis that sleep duration is associated with obesity in a large longitudinally monitored United States sample. These observations support earlier experimental sleep studies and provide a basis for future studies on weight control interventions that increase the quantity and quality of sleep.

Stroke mortality is reported to be greater in blacks than in whites, but stroke incidence data for blacks and Hispanics are sparse. The aim of this study was to determine and compare stroke incidence rates among whites, blacks, and Hispanics living in the same urban community. A population-based incidence study was conducted to identify all cases of first stroke occurring in northern Manhattan, New York City, between July 1, 1993, and June 30, 1996. The population of this area was approximately 210,000 at that time, based on 1990 US Census data. Surveillance for hospitalized and nonhospitalized stroke consisted of daily screening of all admissions, discharges, and computed tomography logs at Columbia-Presbyterian Medical Center, the only hospital in the region, and review of discharge lists from outside hospitals, telephone surveys of random households, and contacts with community physicians, Visiting Nurses' Services, and community agencies. Stroke incidence increased with age and was greater in men than in women. The average annual age-adjusted stroke incidence rate at age > or =20 years, per 100,000 population, was 223 for blacks, 196 for Hispanics, and 93 for whites. Blacks had a 2.4-fold and Hispanics a twofold increase in stroke incidence compared with whites. Cerebral infarct accounted for 77 percent of all strokes, intracerebral hemorrhage for 17 percent, and subarachnoid hemorrhage for 6 percent. These data from the Northern Manhattan Stroke Study suggest that part of the reported excess stroke mortality among blacks in the United States may be a reflection of racial/ethnic differences in stroke incidence.