In our recent paper Why do per capita COVID-19 Case Rates Differ Between U . S. States? we established that U.S. states with a Democratic governor and a Democratic legislature have lower COVID-19 per capita case rates than states with a Republican governor and a Republican legislature, and case rates of states with a mixed government fall between the two. This difference remained after accounting for differences between states in several demographic and socio-economic variables. In a recent working paper The Changing Political Geographies of COVID-19 in the U . S . it was found that that early in the pandemic U.S. counties at higher levels of percentage Democratic vote in the 2016 presidential election had higher weekly per capita COVID-19 rates, but that the situation was in the opposite direction by August 2020. We show here that counties with a higher percentage of Democratic vote in the 2016 presidential election have a lower mean cumulative per capita rate of COVID-19 cases and of COVID-19 deaths, adjusted for county demographic and socio-economic characteristics, but only for counties in states that currently have a Democratic governor and both chambers of the legislature Democratic or in states that have a mixed government, but not for states that currently have a Republican governor and both chambers in the legislature Republican. One possible contributor to this difference is that some state Republican governments have restricted local action to fight the spread of COVID-19.

Background The popular press has explored the differences among U.S. states in rates of COVID-19 cases, mostly focusing on political party differences, and often mentioning that political party differences in health outcomes are confounded by demographic and socio-economic differences between Democratic areas and Republican areas. The purpose of this paper is to present a thorough analysis of these issues. Design and Methods State-specific COVID-19 cases per 100,000 people was the main outcome studied, with explanatory variables from Bureau of Census surveys, including percentages of the state population that were Hispanic, black, below poverty level, had at least a bachelor’s degree, or were uninsured, along with median age, median income, population density, and degree of urbanization. We also included political party in power as an explanatory variable in multiple linear regression. The units of analysis in this study are the 50 U.S. states. Results All explanatory variables were at least marginally statistically significantly associated with case rate in univariate regression analysis, except for population density and urbanization. All the census characteristics were at least marginally associated with party in power in one factor analysis of variance, except for percentage black. In a forward stepwise procedure in a multivariable model for case rate, percentages of the state population that were Hispanic or black, median age, median income, population density, and (residual) percentage poverty were retained as statistically significant and explained 62% of the variation between states in case rates. In a model with political party in power included, along with any additional variables that notably affected the adjusted association between party in power and case rate, 69% of the variance between states in case rates was explained, and adjusted case rates per 100,000 people were 2155 for states with Democratic governments, 2269 for states with mixed governments, and 2738 for Republican-led states. These estimates are based on data through October 8, 2020. Conclusions U.S. state-specific demographic and socio-economic variables are strongly associated with the states’ COVID-19 case rates, so must be considered in analysis of variation in case rates between the states. Adjusting for these factors, states with Democrats as the party in power have lower case rates than Republican-led states.

Introduction and aim: There are limited comparative data on social inequalities in stroke morbidity across Europe. We aimed to assess the magnitude of educational class inequalities in stroke mortality, incidence and 1-year case-fatality in European populations. Methods: The MORGAM study comprised 45 cohorts from Finland, Denmark, Sweden, Northern Ireland, Scotland, France, Germany, Italy, Lithuania, Poland and Russia, mostly recruited in mid 1980s-early 90s. Baseline data collection and follow-up (median 12 years) for fatal and non-fatal strokes adhered to MONICA-like procedures. Stroke mortality was defined according to the underlying cause of death (ICD-IX codes 430-438 or ICD-X I60-I69). We derived 3 educational classes from population-, sex- and birth year-specific tertiles of years of schooling. We estimated the age-adjusted difference in event rates, and the age- and risk factor-adjusted hazard ratios (HRs), between the bottom and the top of the educational class distribution from sex- and population-specific Poisson and Cox regression models, respectively. The association between 1-year case-fatality and education was estimated through logistic models adjusted for risk factors. Results: Among the 91,563 CVD-free participants aged 35-74 at baseline, 1037 stroke deaths and 3902 incident strokes occurred during follow-up. Low education accounted for 26 additional stroke deaths per 100,000 person-years in men (95%CI: 9 to 42), and 19 (7 to 32) in women. In both genders, inequalities in fatal stroke rates were larger in the East EU and in the Nordic Countries populations. The age-adjusted pooled HRs of first stroke, fatal or non-fatal, for the least educated men and women were 1.52 (95%CI: 1.29-1.78) and 1.51 (1.25-1.81), respectively, consistently across populations. Adjustment for smoking, blood pressure, HDL-cholesterol and diabetes attenuated the pooled HRs to 1.34 (95%CI: 1.14-1.57) in men and 1.29 (1.07-1.55) in women. A significant association between low education and increased 1-year case-fatality was observed in Northern Sweden only. Conclusions: Social inequalities in stroke incidence are widespread in most European populations, and less than half of the gap is explained by major risk factors.

Background: We examined the accuracy of Medicare heart failure (HF) diagnostic codes in the identification of acute decompensated (ADHF and chronic stable (CSHF) HF.Methods and Results: Hospitalizations were identified from medical discharge records for Atherosclerosis Risk in Communities (ARIC) study participants with linked Medicare Provider Analysis and Review (MedPAR) files for the years 2005-2009. The ARIC study classification of ADHF and CSHF, based on adjudicated review of medical records, was considered to be the criterion standard. A total 8,239 ARIC medical records and MedPAR records meeting fee-for-service (FFS) criteria matched on unique participant ID and date of discharge (68.5% match). Agreement between HF diagnostic codes from the 2 data sources found in the matched records for codes in any position (K > 0.9) was attenuated for primary diagnostic codes (K < 0.8). Sensitivity of HF diagnostic codes found in Medicare claims in the identification of ADBF and CSHF was low, especially for the primary diagnostic codes.Conclusion: Matching of hospitalizations from Medicare claims with those obtained from abstracted medical records is incomplete, even for hospitalizations meeting FT'S criteria. Within matched records, HF diagnostic codes from Medicare show excellent agreement with HF diagnostic codes obtained from medical record abstraction. The Medicare data may, however, overestimate the occurrence of hospitalized ADHF or CSHF. (J Cardiac Fail 2016;22:48-55)

Background and aims: Biomarkers and atherosclerosis imaging have been studied individually for association with incident cardiovascular disease (CVD); however, limited data exist on whether the biomarkers are associated with events with a similar magnitude in the presence of atherosclerosis. In this study, we assessed whether the presence of atherosclerosis as measured by carotid intima media thickness (cIMT) affects the association between biomarkers known to be associated with coronary heart disease (CHD) and incident cardiovascular disease (CVD) in a primary prevention cohort.Methods: 8127 participants from the ARIC study (4th visit, 1996-1998) were stratified as having minimal, mild, or substantial atherosclerosis by cIMT. Levels of C-reactive protein, lipoprotein-associated phospholipase A2, cardiac troponin T, N-terminal pro-brain natriuretic peptide, lipoprotein(a), cystatin C, and urine albumin to creatinine ratio were measured in each participant. Hazard ratios were used to determine the relationship between the biomarkers and incident CHD, stroke, and CVD in each category of atherosclerosis.Results: While each of the biomarkers was significantly associated with risk of events overall, we found no significant differences noted in the strength of association of biomarkers with CHD, stroke, and CVD when analyzed by degree of atherosclerosis.Conclusions: These findings suggest that the level of atherosclerosis does not significantly influence the association between biomarkers and CVD. Published by Elsevier Ireland Ltd.

Hypothesis: We hypothesized that outpatient management of patients at risk for a HF hospitalization is associated with lower mortality following an incident HF hospitalization. Methods: Patterns of outpatient visits prior to incident HF hospitalization were assessed among CMS Medicare beneficiaries with continuous fee-for-service eligibility residing during 2003-2006 in four geographic areas of CVD surveillance conducted by the ARIC Study. Incident HF hospitalization was defined as hospitalization with ICD9 code 428.x with no HF hospitalizations in preceding 2 years. Outpatient visits to primary care physicians, general internists, or cardiologists were identified from Carrier files. A comorbidity score was calculated from ICD9 codes at the time of incident HF hospitalization. Cox proportional hazard models adjusted for age, comorbidity score, gender, and race were used to estimate mortality. Results: Mean age among beneficiaries with observed incident HF hospitalization (n=2006; 90.4% white, 45.1% male) was 79.8 years (SD 7.4). Mean comorbidity score was 3.6 (SD 1.9). Mean number of outpatient physician visits occurring in two years preceding the incident HF hospitalization, was 9.6 (SD 9.0); 19.6% beneficiaries had no observed prior outpatient physician visits. Risk of death within one year of incident HF hospitalization was greater among those with no preceding outpatient physician visits as compared to those with at least one physician visit (adjusted HR=1.81 (95% CI 1.50, 2.18); Figure). Adjustment for the presence of an outpatient visit within 2 weeks following the HF hospitalization attenuated the risk of death (HR=1.56 (1.29, 1.89)). Conclusion: Lack of outpatient care in two years prior to a HF-related hospitalization is associated with increased mortality within one year following hospitalization. Further inquiry is warranted to assess whether the association reflects diversity in causes/manifestations of HF, ambulatory care received in ED settings, or benefits associated with outpatient care.

Background: Recent animal studies suggest that artificially sweetened beverage (ASB) consumption increases diabetes risk.Objective: We examined the relation of ASB intake with newly diagnosed diabetes and measures of glucose homeostasis in a large Brazilian cohort of adults.Methods: We used cross-sectional data from 12,884 participants from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). ASB use was assessed by questionnaire and newly diagnosed diabetes by a 2-h 75-g oral glucose tolerance test and/or glycated hemoglobin. Logistic and linear regression analyses were performed to examine the association of ASB consumption with diabetes and continuous measures of glucose homeostasis, respectively.Results: Although ASB consumption was not associated with diabetes in logistic regression analyses after adjustment for body mass index (BMI; in kg/m(2)) overall, the association varied across BMI categories (P-interaction = 0.04). Among those with a BMI <25, we found a 15% increase in the adjusted odds of diabetes for each increase in the frequency of ASB consumption per day (P = 0.001); compared with nonusers, ASB users presented monotonic increases in the adjusted ORs (95% Cls) of diabetes with increased frequency of consumption: 1.03 (0.60, 1.77), 1.43 (0.93, 2.20), 1.62 (1.08, 2.44), and 2.51 (1.40, 4.50) for infrequent, 1-2, 3-4, and >4 times/d, respectively. In linear regression analyses, among normal-weight individuals, greater ASB consumption was also associated with increased fasting glucose concentrations (P= 0.01) and poorer beta-cell function (P= 0.009). No such associations were seen for those with BMI In fact, in overweight or obese participants, greater ASB consumption was significantly associated with improved indexes of insulin resistance and 2-h postload glucose.Conclusions: Normal-weight, but not excess-weight, individuals with greater ASB consumption presented diabetes more frequently and had higher fasting glucose and poorer beta-cell function.

The prevalence of the metabolic syndrome is rising worldwide. Its association with alcohol intake, a major lifestyle factor, is unclear, particularly with respect to the influence of drinking with as opposed to outside of meals. We investigated the associations of different aspects of alcohol consumption with the metabolic syndrome and its components. In cross-sectional analyses of 14,375 active or retired civil servants (aged 35-74 years) participating in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), we fitted logistic regression models to investigate interactions between the quantity of alcohol, the timing of its consumption with respect to meals, and the predominant beverage type in the association of alcohol consumption with the metabolic syndrome. In analyses adjusted for age, sex, educational level, income, socioeconomic status, ethnicity, smoking, body mass index, and physical activity, light consumption of alcoholic beverages with meals was inversely associated with the metabolic syndrome (≤4 drinks/week: OR = 0.85, 95%CI 0.74-0.97; 4 to 7 drinks/week: OR = 0.75, 95%CI 0.61-0.92), compared to abstention/occasional drinking. On the other hand, greater consumption of alcohol consumed outside of meals was significantly associated with the metabolic syndrome (7 to 14 drinks/week: OR = 1.32, 95%CI 1.11-1.57; ≥14 drinks/week: OR = 1.60, 95%CI 1.29-1.98). Drinking predominantly wine, which occurred mostly with meals, was significantly related to a lower syndrome prevalence; drinking predominantly beer, most notably when outside of meals and in larger quantity, was frequently associated with a greater prevalence. In conclusion, the alcohol-metabolic syndrome association differs markedly depending on the relationship of intake to meals. Beverage preference-wine or beer-appears to underlie at least part of this difference. Notably, most alcohol was consumed in metabolically unfavorable type and timing. If further investigations extend these findings to clinically relevant endpoints, public policies should recommend that alcohol, when taken, should be preferably consumed with meals.

Aims: To compare the magnitude of educational classes inequalities in CHD morbidity in Europe, and to assess to what extent they are explained by major risk factors. Methods: The MORGAM study comprised 45 cohorts from Finland, Denmark, Sweden, Northern Ireland, Scotland, France, Germany, Northern Italy, Lithuania, Poland and Russia. Baseline data collection and follow-up (median 12 years) of fatal and non-fatal CHD events adhered to MONICA-like procedures. We derived 3 educational classes from population-, sex- and birth year-specific tertiles of years of schooling. We estimated the age-adjusted difference in event rates, and the age- and risk factors-adjusted hazard ratio (HR), between the bottom and the top of the educational classes distribution from sex- and population-specific Poisson and Cox regression models, respectively. We provided pooled HR estimates too, and tested the hypothesis of homogeneity of inequalities adding population*education interaction terms. We defined the contribution of risk f...

Background: Estimation of disease incidence from administrative data requires an adequate look-back (prevalence) period to exclude pre-existing conditions from the incidence risk set. We characterized optimal lengths of the prevalence period to minimize misclassification of incident heart failure (HF) hospitalization, a proxy for incident HF. Methods: Data for participants of the ARIC Study (a prospective longitudinal cohort of 15,792 individuals sampled from 4 US communities) were linked with CMS Medicare claims from the years 2000-2012. We included only participants with >36 months of continuous CMS Medicare fee for service (FFS) enrollment. Each participant’s time-in-observation was divided into two phases. The first 36 months were the prevalence period. Observation time after an index date 36 months following the date of enrollment was the incidence period. HF hospitalizations were identified from CMS MedPAR records using ICD-9 code 428.xx in any position. Patients were classified as having a HF hospitalization in (a) both the prevalence and incidence periods, (b) in the prevalence period only, (c) in the incidence period only, or (d) neither. Incident HF was defined as the first HF hospitalization in the incidence period not preceded by a HF hospitalization in the prevalence period. The proportion of events misclassified as incident HF hospitalization was estimated from incremental reductions of the prevalence period to start 36, 30, 24, 18, 12, or 6 months before the index date. The impact of misclassification was estimated as differences in incidence per 1,000 patients at risk. Results: Of 11,054 ARIC participants enrolled in Medicare FFS, 9,568 met the study inclusion criteria. A total of 1,129 incident HF hospitalizations were identified based on the 36 month prevalence period, considered as the referent (incidence rate 118 HF hospitalizations per 1,000 patients at risk). Shortening the prevalence period to 24 months increased the HF incidence rate to 123 per 1,000, overestimating the number of incident HF hospitalizations by 4.2% while retaining over 90% of the sample. A 12 month prevalence period yielded an overestimation of the number of incident HF hospitalizations by 11% (incidence rate 129 per 1,000 patients at risk) while retaining 95% of the sample. Conclusions: Selection of too short of a prevalence period to define incident hospitalized HF from CMS Medicare claims data can introduce substantial misclassification. Consideration of several prevalence periods indicates that a 24 month prevalence period reduces the potential for bias in the estimation of incident hospitalized HF while retaining most observations.

Aims. To explore the magnitude of educational-class inequalities in ischemic stroke incidence in European populations, and to assess to what extent they can be explained by major risk factors. Methods. The MORGAM study comprised 45 cohorts from Nordic Countries (Finland, Denmark, Sweden), UK (Northern Ireland, Scotland), Central EU (France, Germany, Northern Italy) and East EU (Lithuania, Poland) and Russia. Only cohorts with both fatal and non-fatal ischemic strokes during follow-up (median 12 years, IQR 10-19 years) were included. Baseline data were collected adhering to MONICA-like procedures. Stroke subtype was attributed based on hospital records and death codes. We derived 3 educational classes from population-, sex- and birth year-specific tertiles of years of schooling. We used Poisson regression models to estimate the age-adjusted difference in event rates between the bottom and the top educational classes distribution (Slope Index of Inequality, SII) and the proportion of events to be redistributed to achieve equality in event rates among educational classes (Relative Concentration Index, RCI). We estimated the pooled age- and risk factors-adjusted hazard ratios for bottom to top education (Relative Index of Inequality, RII) from sex-specific Cox models with a dummy variable for each population . We also tested the hypothesis of homogeneity of inequalities across populations by adding population*education interaction terms. The contribution of risk factors to RII was measured by: (lnRII[RFadj]- lnRII[AGEadj]) / lnRII[AGEadj] Results. The cohorts included 66,052 CVD-free subjects aged 35-64 years (37,181 men) at baseline. In men, the age-adjusted inequalities in ischemic stroke rates (SIIs) were 125 events per 100,000 person-years in the Nordic Countries, 156 in the UK and 178 in Central EU; the RCIs were 6%, 13% and 21%, respectively. In women, an inverse gradient (higher rates among more educated subjects) was present in Northern Sweden; in the remaining populations, the SII (RCI) ranged between 4 (1%) in Northern Italy and 278 (23%) events in Germany. Age-adjusted pooled RIIs for bottom to top education were 1.7 (95%CI: 1.4-2.1) in men and 1.5 (1.2-1.9) in women, with some variability across populations (homogeneity test p-value=0.06 in men and 0.07 in women) and gender groups. Together, total- and HDL-cholesterol, systolic blood pressure, anti-hypertensive treatment, smoking and diabetes explained 26% of hazard excess in men, and 40% in women. Main contributors were smoking (13%) and systolic blood pressure (9%) in men; and systolic blood pressure (13%), HDL-cholesterol (12%) and smoking (11%) in women. Conclusions. Less educated men and women had a higher ischemic stroke incidence risk in most European populations; in men, such inequalities followed a clear North-South geographic gradient. Traditional risk factors accounted for a minor part of risk excess in men.

ABO blood groups are known to influence the plasma level of von Willebrand factor (VWF), but little is known about the relationship between ABO and coagulation factor VIII (FVIII). We analyzed the influence of ABO genotypes on VWF antigen, FVIII activity, and their quantitative relationship in 11,673 participants in the Atherosclerosis Risk in Communities (ARIC) study. VWF, FVIII, and FVIII/VWF levels varied significantly among O, A (A1 and A2), B and AB subjects, and the extent of which varied between Americans of European (EA) and African (AA) descent. We validated a strong influence of ABO blood type on VWF levels (15.2%), but also detected a direct ABO influence on FVIII activity (0.6%) and FVIII/VWF ratio (3.8%) after adjustment for VWF. We determined that FVIII activity changed 0.54% for every 1% change in VWF antigen level. This VWF-FVIII relationship differed between subjects with O and B blood types in EA, AA, and in male, but not female subjects. Variations in FVIII activity were primarily detected at low VWF levels. These new quantitative influences on VWF, FVIII and the FVIII/VWF ratio help understand how ABO genotypes differentially influence VWF, FVIII and their ratio, particularly in racial and gender specific manners.

The synthesis, secretion and clearance of von Willebrand factor (VWF) are regulated by genetic variations in coding and promoter regions of the VWF gene. We have previously identified 19 single nucleotide polymorphisms (SNPs), primarily in introns that are associated with VWF antigen levels in subjects of European descent. In this study, we conducted race by gender analyses to compare the association of VWF SNPs with VWF antigen among 10,434 healthy Americans of European (EA) or African (AA) descent from the Atherosclerosis Risk in Communities (ARIC) study. Among 75 SNPs analyzed, 13 and 10 SNPs were associated with VWF antigen levels in EA male and EA female subjects, respectively. However, only one SNP (RS1063857) was significantly associated with VWF antigen in AA females and none was in AA males. Haplotype analysis of the ARIC samples and studying racial diversities in the VWF gene from the 1000 genomes database suggest a greater degree of variations in the VWF gene in AA subjects as compared to EA subjects. Together, these data suggest potential race and gender divergence in regulating VWF expression by genetic variations.

OBJECTIVE:We assessed predictive abilities and clinical utility of CVD risk algorithms including ApoB and ApoAI among non-diabetic subjects with metabolic syndrome (MetS). METHODS:Three independent population-based cohorts (3677 35-74 years old) were enrolled in Northern Italy, adopting standardized MONICA procedures. Through Cox models, we assessed the associations between lipid measures and first coronary events, as well as the changes in discrimination and reclassification (NRI) when standard lipids or apolipoproteins were added to the CVD risk algorithm including non-lipids risk factors. Finally, the best models including lipids or apolipoproteins were compared. RESULTS:During the 14.5 years median follow-up time, 164 coronary events were validated. All measures showed statistically significant associations with the endpoint, while in the MetS subgroup HDL-C and ApoAI (men, HR = 1.59; 95%CI: 0.96-2.65) were not associated. Models including HDL-C plus TC and ApoB plus ApoAI for lipids and apolipoproteins, respectively, showed the best predictive values. When ApoB plus ApoAI replaced TC plus HDL-C, NRI values improved in subjects with MetS (13.8; CI95%: -5.1,53.1), significantly in those previously classified at intermediate risk (44.5; CI95% 13.8,129.6). In this subgroup, 5.5% of subjects was moved in the high (40.0% of expected events) and 17.0% in the low risk class (none had an event at 10 years). CONCLUSIONS:ApoB and ApoAI could improve coronary risk prediction when used as second level biomarkers in non-diabetic subjects with MetS classified at intermediate risk. The absence of cases moved downward suggests the gain in avoiding treatments in non-cases and favor the use of apolipoproteins for risk assessment.

Objective To examine the survival benefit of multiple medical therapies in a large, community-based population of validated myocardial infarction (MI) events.Design Retrospective observational cohort study.Setting Population-based sample of 30 986 definite or probable MIs in residents of four US communities aged 35-74 years randomly sampled between 1987 and 2008 as part of the Atherosclerosis Risk in Communities Surveillance Study.Interventions None.Main outcome measures All-cause mortality 30, 90 and 365 days after discharge.Results We used unadjusted and propensity score (PS) adjusted models to examine the relationship between medical therapy use and mortality. In unadjusted models, each medication and procedure was inversely associated with 30-day mortality. After PS adjustment, the crude survival benefits were attenuated for all therapies except for intravenous tissue plasminogen activator therapy (IV-tPA) and stent use. After inclusion of other therapies received during the event in regression models, risk ratio effect estimates (RR; (95% CI)) were attenuated for aspirin (0.66; (0.58 to 0.76) to 0.91 (0.80 to 1.03)), non-aspirin antiplatelets (0.74; (0.59 to 0.92) to 0.92 (0.72 to 1.18)), IV-tPA (0.50; (0.41 to 0.62) to 0.65 (0.52 to 0.80)) and stents (0.53 (0.40 to 0.69) to 0.68 (0.49 to 0.94)). Effect estimates remained stable for all other therapies and were similar for 90- and 365-day mortality endpoints.Conclusions We observed inverse associations between receipt of six medications and procedures for MI and all-cause mortality at 30, 90 and 365 days after adjustment for PS. The mortality benefits observed in this population-based setting are consistent with those reported in clinical trials.

Most population-based estimates of incident hospitalized heart failure (HF) have not differentiated acute decompensated heart failure (ADHF) from chronic stable HF nor included racially diverse populations. The Atherosclerosis Risk in Communities Study conducted surveillance of hospitalized HF events (age ≥55 years) in 4 US communities. We estimated hospitalized ADHF incidence and survival by race and gender. Potential 2005 to 2009 HF hospitalizations were identified by International Classification of Diseases, Ninth Revision, Clinical Modification, codes; 6,168 records were reviewed to validate ADHF cases. Population estimates were derived from US Census data; 50% of eligible hospitalizations were classified as ADHF, of which 63.6% were incident ADHF and 36.4% were recurrent ADHF. The average incidence of hospitalized ADHF was 11.6 per 1,000 persons, aged ≥55 years, per year, and recurrent hospitalized ADHF was 6.6 per 1,000 persons/yr. Age-adjusted annual ADHF incidence was highest for black men (15.7 per 1,000), followed by black women (13.3 per 1,000), white men (12.3 per 1,000), and white women (9.9 per 1,000). Of incident ADHF events with heart function assessment (89%), 53% had reduced the ejection fraction (heart failure with reduced ejection fraction [HFrEF]) and 47% had preserved ejection fraction (heart failure with preserved ejection fraction [HFpEF]). Black men had the highest proportion of acute HFrEF events (70%); white women had the highest proportion of acute HFpEF (59%). Age-adjusted 28-day and 1-year case fatality after an incident ADHF was 10.4% and 29.5%, respectively. Survival did not differ by race or gender. In conclusion, ADHF hospitalization and HF type varied by both race and gender, but case fatality rates did not. Further studies are needed to explain why black men are at higher risk of hospitalized ADHF and HFrEF.

Dietary intake among other lifestyle factors influence blood pressure. We examined the associations of an "a priori" diet score with incident high normal blood pressure (HNBP; systolic blood pressure (SBP) 120-139 mmHg, or diastolic blood pressure (DBP) 80-89 mmHg and no antihypertensive medications) and hypertension (SBP ≥ 140 mmHg, DBP ≥ 90 mmHg, or taking antihypertensive medication). We used proportional hazards regression to evaluate this score in quintiles (Q) and each food group making up the score relative to incident HNBP or hypertension over nine years in the Atherosclerosis Risk of Communities (ARIC) study of 9913 African-American and Caucasian adults aged 45-64 years and free of HNBP or hypertension at baseline. Incidence of HNBP varied from 42.5% in white women to 44.1% in black women; and incident hypertension from 26.1% in white women to 40.8% in black women. Adjusting for demographics and CVD risk factors, the "a priori" food score was inversely associated with incident hypertension; but not HNBP. Compared to Q1, the relative hazards of hypertension for the food score Q2-Q5 were 0.97 (0.87-1.09), 0.91 (0.81-1.02), 0.91 (0.80-1.03), and 0.86 (0.75-0.98); p(trend) = 0.01. This inverse relation was largely attributable to greater intake of dairy products and nuts, and less meat. These findings support the 2010 Dietary Guidelines to consume more dairy products and nuts, but suggest a reduction in meat intake.

BACKGROUND Among the various cardiovascular diseases, heart failure (HF) is projected to have the largest increases in incidence over the coming decades; therefore, improving HF prediction is of significant value. We evaluated whether cardiac troponin T (cTnT) measured with a high-sensitivity assay and N-terminal pro–B-type natriuretic peptide (NT-proBNP), biomarkers strongly associated with incident HF, improve HF risk prediction in the Atherosclerosis Risk in Communities (ARIC) study. METHODS Using sex-specific models, we added cTnT and NT-proBNP to age and race (“laboratory report” model) and to the ARIC HF model (includes age, race, systolic blood pressure, antihypertensive medication use, current/former smoking, diabetes, body mass index, prevalent coronary heart disease, and heart rate) in 9868 participants without prevalent HF; area under the receiver operating characteristic curve (AUC), integrated discrimination improvement, net reclassification improvement (NRI), and model fit were described. RESULTS Over a mean follow-up of 10.4 years, 970 participants developed incident HF. Adding cTnT and NT-proBNP to the ARIC HF model significantly improved all statistical parameters (AUCs increased by 0.040 and 0.057; the continuous NRIs were 50.7% and 54.7% in women and men, respectively). Interestingly, the simpler laboratory report model was statistically no different than the ARIC HF model. CONCLUSIONS cTnT and NT-proBNP have significant value in HF risk prediction. A simple sex-specific model that includes age, race, cTnT, and NT-proBNP (which can be incorporated in a laboratory report) provides a good model, whereas adding cTnT and NT-proBNP to clinical characteristics results in an excellent HF prediction model.

We examined the relationship between forced expiratory volume in 1 s (FEV1), airflow obstruction, and incident heart failure (HF) in black and white, middle-aged men and women in four US communities.Lung volumes by standardized spirometry and information on covariates were collected on 15 792 Atherosclerosis Risk in Communities (ARIC) cohort participants in 198789. Incident HF was ascertained from hospital records and death certificates up to 2005 in 13 660 eligible participants. Over an average follow-up of 14.9 years, 1369 (10) participants developed new-onset HF. The age- and height-adjusted hazard ratios (HRs) for HF increased monotonically over descending quartiles of FEV1 for both genders, race groups, and smoking status. After multivariable adjustment for traditional cardiovascular risk factors and height, the HRs [95 confidence intervals (CIs)] of HF comparing the lowest with the highest quartile of FEV1 were 3.91 (2.406.35) for white women, 3.03 (2.124.33) for white men, 2.11 (1.333.34) for black women, and 2.23 (1.373.59) for black men. The association weakened but remained statistically significant after additional adjustment for systemic markers of inflammation. The multivariable adjusted incidence of HF was higher in those with FEV1/forced vital capacity 70 vs. epsilon 70: HR 1.44 (95 CI 1.201.74) among men and 1.40 (1.131.72) among women. A consistent and positive association with HF was seen for self-reported diagnosis of emphysema and chronic obstructive pulmonary disease, but not for asthma.In this large population-based cohort with long-term follow-up, low FEV1 and an obstructive respiratory disease were strongly and independently associated with the risk of incident HF.

Background— Knowledge of trends in the incidence of and survival after myocardial infarction (MI) in a community setting is important to understanding trends in coronary heart disease (CHD) mortality rates. Methods and Results— We estimated race- and gender-specific trends in the incidence of hospitalized MI, case fatality, and CHD mortality from community-wide surveillance and validation of hospital discharges and of in- and out-of-hospital deaths among 35- to 74-year-old residents of 4 communities in the Atherosclerosis Risk in Communities (ARIC) Study. Biomarker adjustment accounted for change from reliance on cardiac enzymes to widespread use of troponin measurements over time. During 1987–2008, a total of 30 985 fatal or nonfatal hospitalized acute MI events occurred. Rates of CHD death among persons without a history of MI fell an average 4.7%/y among men and 4.3%/y among women. Rates of both in- and out-of-hospital CHD death declined significantly throughout the period. Age- and biomarker-adjusted average annual rate of incident MI decreased 4.3% among white men, 3.8% among white women, 3.4% among black women, and 1.5% among black men. Declines in CHD mortality and MI incidence were greater in the second decade (1997–2008). Failure to account for biomarker shift would have masked declines in incidence, particularly among blacks. Age-adjusted 28-day case fatality after hospitalized MI declined 3.5%/y among white men, 3.6%/y among black men, 3.0%/y among white women, and 2.6%/y among black women. Conclusions— Although these findings from 4 communities may not be directly generalizable to blacks and whites in the entire United States, we observed significant declines in MI incidence, primarily as a result of downward trends in rates between 1997 and 2008.