In 2010, the American Heart Association defined a novel construct of cardiovascular health to promote a paradigm shift from a focus solely on disease treatment to one inclusive of positive health promotion and preservation across the life course in populations and individuals. Extensive subsequent evidence has provided insights into strengths and limitations of the original approach to defining and quantifying cardiovascular health. In response, the American Heart Association convened a writing group to recommend enhancements and updates. The definition and quantification of each of the original metrics (Life’s Simple 7) were evaluated for responsiveness to interindividual variation and intraindividual change. New metrics were considered, and the age spectrum was expanded to include the entire life course. The foundational contexts of social determinants of health and psychological health were addressed as crucial factors in optimizing and preserving cardiovascular health. This presidential advisory introduces an enhanced approach to assessing cardiovascular health: Life’s Essential 8. The components of Life’s Essential 8 include diet (updated), physical activity, nicotine exposure (updated), sleep health (new), body mass index, blood lipids (updated), blood glucose (updated), and blood pressure. Each metric has a new scoring algorithm ranging from 0 to 100 points, allowing generation of a new composite cardiovascular health score (the unweighted average of all components) that also varies from 0 to 100 points. Methods for implementing cardiovascular health assessment and longitudinal monitoring are discussed, as are potential data sources and tools to promote widespread adoption in policy, public health, clinical, institutional, and community settings.

Background: The American Heart Association (AHA) recently published an updated algorithm for quantifying cardiovascular health (CVH)—the "Life's Essential 8™" score. We quantified US levels of CVH using the new score. Methods: We included non-pregnant, non-institutionalized individuals ages 2 through 79 years who were free of cardiovascular disease from the National Health and Nutrition Examination Surveys in 2013-2018. For all participants, we calculated the overall CVH score (range 0 [lowest] to 100 [highest]), as well as the score for each component of diet, physical activity (PA), nicotine exposure, sleep duration, body mass index (BMI), blood lipids, blood glucose, and blood pressure (BP), using published AHA definitions. Sample weights and design were incorporated in calculating prevalence estimates and standard errors using standard survey procedures. CVH scores were assessed across strata of age, sex, race/ethnicity, family income, and depression. Results There were 23,409 participants, representing 201,728,000 adults and 74,435,000 children. The overall mean CVH score was 64.7 (95% confidence interval [CI], 63.9-65.6) among adults using all 8 metrics, and it was 65.5 (95% CI, 64.4-66.6) for the 3 metrics available (diet, PA, and BMI) among children/adolescents ages 2 through 19 years. For adults, there were significant differences in mean overall CVH scores by sex (women: 67.0 vs. men: 62.5), age (range of mean values 62.2-68.7), and racial/ethnic group (range 59.7-68.5). Mean scores were lowest for diet, PA, and BMI metrics. There were large differences in mean scores across demographic groups for diet (range 23.8-47.7), nicotine exposure (range 63.1-85.0), blood glucose (range 65.7-88.1) and BP (range 49.5-84.0). In children, diet scores were low (mean 40.6) and were progressively lower in higher age groups (from 61.1 at ages 2-5 to 28.5 at ages 12-19); large differences were also noted in mean PA (range 63.1-88.3) and BMI (range 74.4-89.4) scores by sociodemographic group. Conclusions: The new Life's Essential 8 score helps identify large group and individual differences in CVH. Overall CVH in the US population remains well below optimal levels, and there are both broad and targeted opportunities to monitor, preserve, and improve CVH across the life course in both individuals and the population.

In rehabilitation nursing, the patient classification systems or acuity models and nurse‐staffing ratios are not supported by empirical evidence. Moreover, there are no studies published characterizing nursing hours per patient day, proportion of RN staff, and impact of agency nurses in inpatient rehabilitation settings. The purpose of this prospective observational study was to describe rehabilitation nurse staffing patterns, to validate the impact of rehabilitation nursing on patient outcomes, and to test whether existing patient measures on severity and outcomes in rehabilitation could be used as a proxy for burden of care to predict rehabilitation nurse staffing ceilings and daily nurse staffing requirements. A total of 54 rehabilitation facilities in the United States, stratified by geography, were randomly selected to participate in the study.

The purpose of the study described in this article was to identify the factors that have an impact on stroke patients' discharge destination. Two hundred thirty-four stroke patients admitted to a rehabilitation facility over a 2-year period were examined. Functional Independence Measure (FIM) data were used to examine functional status, demographic characteristics, and the discharge destination of patients admitted to the facility's program. The relationship between patients' FIM scores at discharge and their discharge locations was analyzed using the chi-square statistic. The results showed that a discharge FIM score of 80 or above had a high specificity and sensitivity with patients' discharge to their homes. In addition, outliers were analyzed, and the results showed that family members of only 20% of the patients who were discharged to their homes were working, in contrast to 65% of the family members of patients who were discharged to a skilled nursing facility. The availability of a nonworking family member and the ability of a family to provide supervision and physical assistance were more likely to be factors related to discharge of patients to their homes. Ninety percent of the families of patients discharged to their homes were able to provide supervision and to provide physical assistance. Thus, both functional status and social factors, such as family availability and support, are critical elements in predicting the discharge destination of this patient population.