Background: Although sufficient and healthy sleep is inversely associated with cardiovascular disease (CVD) and its risk factors, the American Heart Association's Life's Simple 7 (LS7), as a measure of cardiovascular health (CVH), did not include sleep. We evaluated an expanded measure of CVH that includes sleep as an eighth metric in relation to CVD risk. Methods and Results: The analytic sample consisted of MESA (Multi‐Ethnic Study of Atherosclerosis) Sleep Study participants who had complete data on sleep characteristics from overnight polysomnography, 7‐day wrist actigraphy, validated questionnaires, and the outcome. We computed the LS7 score and 4 iterations of a new CVH score: score 1 included sleep duration, score 2 included sleep characteristics linked to CVD in the literature (sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnea), scores 3 and 4 included sleep characteristics associated with CVD in MESA (score 3: sleep duration and efficiency, daytime sleepiness, and obstructive sleep apnea; score 4: score 3+sleep regularity). Multivariable‐adjusted logistic and Cox proportional hazards models evaluated associations of the LS7 and CVH scores 1 to 4 with CVD prevalence and incidence. Among 1920 participants (mean age: 69±9 years; 54% female), there were 95 prevalent CVD events and 93 incident cases (mean follow‐up, 4.4 years). Those in the highest versus lowest tertile of the LS7 score and CVH scores 1 to 4 had up to 80% lower odds of prevalent CVD. The LS7 score was not significantly associated with CVD incidence (hazard ratio, 0.62 [95% CI, 0.37–1.04]). Those in the highest versus lowest tertile of CVH score 1, which included sleep duration, and CVH score 4, which included multidimensional sleep health, had 43% and 47% lower incident CVD risk (hazard ratio, 0.57 [95% CI, 0.33–0.97]; and hazard ratio, 0.53 [95% CI, 0.32–0.89]), respectively. Conclusions: CVH scores that include sleep health predicted CVD risk in older US adults. The incorporation of sleep as a CVH metric, akin to other health behaviors, may enhance CVD primordial and primary prevention efforts. Findings warrant confirmation in larger cohorts over longer follow‐up.

The menopausal transition period in aging women is strongly associated with weight gain. Evidence shows that weight changes during menopause increases the risk of developing cardiovascular disease (CVD) in postmenopausal women. However, the potential mechanisms that cause weight gain and adverse changes to body composition specifically during the menopausal transition period remain to be elucidated. In this contemporary review, we examined recent evidence for adverse changes in body composition at midlife during the menopausal transition and the link to increased CVD risk and described factors that may contribute to these changes, including normal chronological aging, hormonal factors (decreased estrogen, etc.), behavioral factors (changes in diet, physical activity), or other emerging factors (e.g., sleep). This review focused on identifying factors that make the menopausal transition period a critical window for prevention of CVD. Future study is needed to decipher the extent to which hormonal changes, age-related factors, and behavioral factors interact with and contribute to increased CVD risk in women undergoing menopause. Understanding the causes of weight gain during the menopausal transition may help to inform strategies to mitigate adverse CVD outcomes for women transitioning through menopause.

Background: Poor sleep increases cardiovascular disease risk, and diet likely contributes to this relationship. However, there are limited epidemiological data on the relationship between measures of sleep quality and habitual dietary patterns. This study examined these associations in a diverse sample of women. Methods and Results: Baseline data from 495 participants in the AHA Go Red for Women prospective cohort study (age: 20–76 years; 61% racial/ethnic minority) were examined. Sleep quality and sleep‐onset latency were measured using the Pittsburgh Sleep Quality Index ( PSQI ) and insomnia using the Insomnia Severity Index. The validated Block Brief Food Frequency Questionnaire was used to assess diet quantity and quality. Linear regression models adjusted for confounding variables tested relationships between sleep and diet variables. Results showed that higher PSQI scores, indicative of poorer sleep quality, were associated with lower unsaturated fat intake (β=−0.14, P 60 minutes had higher intakes of food by weight (β=235.2, P< 0.01) and energy (β=426, P <0.01), and lower intakes of whole grains (β=−0.37, P =0.01) than women with sleep‐onset latency ≤15 minutes. Greater insomnia severity was associated with higher food weight (β=9.4, P =0.02) and energy (β=17, P =0.01) consumed and lower total (β=−0.15, P =0.01) and unsaturated fat intakes (β=−0.11, P <0.01). Conclusions: Poor sleep quality was associated with greater food intake and lower‐quality diet, which can increase cardiovascular disease risk. Future studies should test whether promoting sleep quality could augment efforts to improve cardiometabolic health in women.

Background: Chronotype is the behavioral manifestation of an individual’s innate circadian rhythm. Evening chronotype (i.e. being a “night owl”) is linked to elevated chronic disease and mortality risk in European and Asian populations. Evidence from US cohorts is limited, particularly among women, in whom evening chronotype prevalence becomes higher from midlife onward, coinciding with life stages and hormonal changes associated with higher cardiovascular disease (CVD) risk. Hypothesis: Being a definite evening chronotype would be associated with poor cardiovascular health (CVH) and elevated cardiometabolic risk factors. Methods: Participants were 506 diverse women (mean age=37±16y, 62% racial/ethnic minority) in the AHA Go Red for Women Strategically Focused Research Network at Columbia University. Chronotype was measured using the Morningness-Eveningness Questionnaire (MEQ), the most widely used validated tool by circadian biologists to ascertain chronotype. Higher scores reflected greater morningness. Participants were also categorized as “evening” vs. “intermediate/morning” chronotypes based on their MEQ scores. Health behaviors (diet, physical activity, sleep, and sedentary time) were assessed using validated questionnaires. Health factors (BMI, blood pressure, fasting glucose, and cholesterol) were assessed at the clinic visit. Overall CVH was evaluated using the AHA Life’s Simple 7 (LS7) score (0-8: poor, 9-14: moderate to high). Linear and logistic regression models adjusted for age, race/ethnicity, education, health insurance, and menopause were used to examine associations of chronotype with CVH, clinical risk factors, and health behaviors. Results: Overall, 13% of women identified as being evening chronotypes. Higher MEQ scores (i.e. greater morningness) were associated with higher AHA LS7 scores (β=0.02, p=0.01), indicative of more favorable CVH. Higher MEQ scores were also associated with having a lower Pittsburgh Sleep Quality Index, i.e. better sleep quality, (β=-0.07, p<0.0001), a lower Insomnia Severity Index (β=-0.14, p<0.0001), shorter time to fall asleep (β=-0.28, p=0.04), and less sedentary time (β=-0.11, p=0.001). In contrast, being an evening chronotype was associated with higher odds of poor CVH (OR (95%CI): 2.41 (1.20-4.85)), not meeting AHA diet (OR (95%CI): 2.89 (1.59-5.23)) and physical activity guidelines, (OR (95%CI): 1.78 (1.03-3.07)), and having short sleep (<7h) (OR (95%CI): 2.15 (1.24-3.73)) or insomnia symptoms (OR (95%CI): 2.69 (1.53-4.75)). Conclusions: Women with evening chronotypes have greater odds of having poor CVH and adverse health behaviors after adjustment for sociodemographic factors and menopausal status. Chronotype may be important to consider and target in lifestyle interventions aimed at CVD prevention, particularly among middle-aged and older women who are prone to sleep changes.

Background: Insufficient sleep increases blood pressure. However, the effects of milder, highly prevalent but frequently neglected sleep disturbances, including poor sleep quality and insomnia, on vascular health in women are unclear. We investigated whether poor sleep patterns are associated with blood pressure and endothelial inflammation in a diverse sample of women. Methods and Results: Women who participated in the ongoing American Heart Association Go Red for Women Strategically Focused Research Network were studied (n=323, 57% minority, mean age=39±17 years, range=20–79 years). Sleep duration, sleep quality, and time to sleep onset were assessed using the Pittsburgh Sleep Quality Index (score ≥5=poor sleep quality). Risk for obstructive sleep apnea was evaluated using the Berlin questionnaire, and insomnia was assessed using the Insomnia Severity Index. In a subset of women who participated in the basic study (n=26), sleep duration was assessed objectively using actigraphy, and endothelial inflammation was assessed directly in harvested endothelial cells by measuring nuclear translocation of nuclear factor kappa B. Vascular reactivity was measured by brachial artery flow‐mediated dilation (n=26). Systolic and diastolic blood pressure were measured by trained personnel (n=323). Multivariable linear regressions were used to evaluate associations between sleep patterns and blood pressure, nuclear factor kappa B, and flow‐mediated dilation. Mean sleep duration was 6.8±1.3 hours/night in the population study and 7.5±1.1 hour/night in the basic study. In the population study sample, 50% had poor sleep quality versus 23% in the basic study, and 37% had some level of insomnia versus 15% in the basic study. Systolic blood pressure was associated directly with poor sleep quality, and diastolic blood pressure was of borderline significance with obstructive sleep apnea risk after adjusting for confounders ( P =0.04 and P =0.08, respectively). Poor sleep quality was associated with endothelial nuclear factor kappa B activation (β=30.6; P =0.03). Insomnia and longer sleep onset latency were also associated with endothelial nuclear factor kappa B activation (β=27.6; P =0.002 and β=8.26; P =0.02, respectively). No evidence was found for an association between sleep and flow‐mediated dilation. Conclusions: These findings provide direct evidence that common but frequently neglected sleep disturbances such as poor sleep quality and insomnia are associated with increased blood pressure and vascular inflammation even in the absence of inadequate sleep duration in women. Clinical Trial Registration: URL : https://www.clinicaltrials.gov . Unique identifier: NCT 02835261.