BackgroundCardiovascular disease is the leading cause of death in the United States, making improving cardiovascular health a key population health goal. As part of efforts to achieve this, the American Heart Association has developed the first comprehensive cardiovascular health index (CVHI). Our objective was to investigate the changes in CVHI in US states from 2003 to 2011.Methods and ResultsCVHI was examined using Behavioral Risk Factor Surveillance System data between 2003 and 2011 (odd-numbered years). Total CVHI decreased from 3.73±0.01 in 2003 to 3.65±0.01 in 2009. The majority of states (88%) experienced a decline in CVHI and an increase in the prevalence of “poor” CVHI between 2003 and 2009. Among CVHI components, the highest prevalence of “ideal” was observed for blood glucose followed by smoking, whereas the lowest prevalence of “ideal” was observed for physical activity and diet. Between 2003 and 2009, prevalence of “ideal” smoking and diet status increased, while “ideal” prevalence of blood pressure, cholesterol, blood glucose, body mass index, and physical activity status decreased. We observed statistically significant differences between 2009 and 2011, outside the scope of the 2003–2009 trend, which we hypothesize are partially attributable to differences in sample demographic characteristics related to changes in Behavioral Risk Factor Surveillance System methodology.ConclusionsOverall, CVHI decreased, most likely due to decreases in “ideal” blood pressure, body mass index, and cholesterol status, which may stem from low prevalence of “ideal” physical activity and diet status. These findings can be used to inform state-specific strategies and targets to improve cardiovascular health.

BackgroundCurrent primary prevention guidelines for cardiovascular disease (CVD) prioritize risk identification, risk stratification using clinical and risk scores, and risk reduction with lifestyle interventions and pharmacotherapy. Subclinical atherosclerosis is an early indicator of atherosclerotic burden and its timely recognition can slow or prevent progression to CVD. Thus, individuals with subclinical atherosclerosis are a priority for primary prevention. This study takes a practical approach to answering a challenge commonly faced by primary care practitioners: in patients with no known CVD, how can individuals likely to have subclinical atherosclerosis be easily identified using existing clinical data and/or information provided by the patient?MethodsUsing NHANES (1999–2004), 6091 men and women aged ≥40 years without any CVD comprised the primary prevention population for this study. Subclinical atherosclerosis was determined via ankle-brachial index (ABI) using established cutoffs (subclinical atherosclerosis defined as ABI (0.91–0.99); normal defined as ABI (1.00–1.30)). Three common scores were calculated: the Framingham Risk Score (FRS), the Metabolic Syndrome (MetS), and the Cardiovascular Health Index (CVHI). Logistic regression analysis assessed the association between these scores and subclinical atherosclerosis. The sensitively and specificity of these scores in identifying subclinical atherosclerosis was determined.ResultsIn eligible participants, 3.8% had subclinical atherosclerosis. Optimum and average CVHI was associated with decreased odds for subclinical atherosclerosis. High, but not intermediate-risk, FRS was associated with increased odds for subclinical atherosclerosis. MetS was not associated with subclinical atherosclerosis. Of the 3 scores, CVHI was the most sensitive in identifying subclinical atherosclerosis and had the lowest number of missed cases. The FRS was the most specific but least sensitive of the 3 scores, and had almost 10-fold more missed cases vs. the CVHI. The MetS had “middle” sensitivity and specificity, and 10-fold more missed cases vs. the CVHI.ConclusionsResults from this study suggest that routine administration of the CVHI in a primary prevention population would yield the benefits of identifying patients with existing subclinical CVD not identified through traditional CVD risk factors or scores, and bring physical activity and nutrition to the forefront of provider-patient discussions about lifestyle factors critical to maintaining and prolonging cardiovascular health.

BackgroundAlthough the increased prevalence and severity of clinical depression and elevated cardiovascular disease risk represent 2 vexing public health issues, the growing awareness of their combined presentation compounds the challenge. The obese Zucker rat, a model of the metabolic syndrome, spontaneously develops significant depressive symptoms in parallel with the progression of the metabolic syndrome and, thus, represents a compelling model for study. The primary objective was to assess the impact on both cardiovascular outcomes, specifically vascular structure and function, and depressive symptoms in obese Zucker rats after aggressive treatment for cardiovascular disease risk factors with long‐term exercise or targeted pharmacological interventions.Methods and ResultsWe chronically treated obese Zucker rats with clinically relevant interventions against cardiovascular disease risk factors to determine impacts on vascular outcomes and depressive symptom severity. While most of the interventions (chronic exercise, anti‐hypertensive, the interventions (long‐term exercise, antihypertensive, antidyslipidemia, and antidiabetic) were differentially effective at improving vascular outcomes, only those that also resulted in a significant improvement to oxidant stress, inflammation, arachidonic acid metabolism (prostacyclin versus thromboxane A2), and their associated sequelae were effective at also blunting depressive symptom severity. Using multivariable analyses, discrimination between the effectiveness of treatment groups to maintain behavioral outcomes appeared to be dependent on breaking the cycle of inflammation and oxidant stress, with the associated outcomes of improving endothelial metabolism and both cerebral and peripheral vascular structure and function.ConclusionsThis initial study provides a compelling framework from which to further interrogate the links between cardiovascular disease risk factors and depressive symptoms and suggests mechanistic links and potentially effective avenues for intervention.

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ObjectiveThe objective of this study is to examine the magnitude and pattern of small-area geographic variation in rates of preventable hospitalisations for ambulatory care-sensitive conditions (ACSC) across Canada (excluding Québec).Design and settingA cross-sectional study conducted in Canada (excluding Québec) using data from the 2006 Canadian Census Health and Environment Cohort (CanCHEC) linked prospectively to hospitalisation records from the Discharge Abstract Database (DAD) for the three fiscal years: 2006–2007, 2007–2008 and 2008–2009.Primary outcome measurePreventable hospitalisations (ACSC).ParticipantsThe 2006 CanCHEC represents a population of 22 562 120 individuals in Canada (excluding Québec). Of this number, 2 940 150 (13.03%) individuals were estimated to be hospitalised at least once during the 2006–2009 fiscal years.MethodsAge-standardised annualised ACSC hospitalisation rates per 100 000 population were computed for each of the 190 Census Divisions. To assess the magnitude of Census Division-level geographic variation in rates of preventable hospitalisations, the global Moran’s I statistic was computed. ‘Hot spot’ analysis was used to identify the pattern of geographic variation.ResultsOf all the hospitalisation events reported in Canada during the 2006–2009 fiscal years, 337 995 (7.10%) events were ACSC-related hospitalisations. The Moran’s I statistic (Moran’s I=0.355) suggests non-randomness in the spatial distribution of preventable hospitalisations. The findings from the ‘hot spot’ analysis indicate a cluster of Census Divisions located in predominantly rural and remote parts of Ontario, Manitoba and Saskatchewan and in eastern and northern parts of Nunavut with significantly higher than average rates of preventable hospitalisation.ConclusionThe knowledge generated on the small-area geographic variation in preventable hospitalisations can inform regional, provincial and national decision makers on planning, allocation of resources and monitoring performance of health service providers.