McNallan, Sheila M

Objective: To determine if the implementation of smoke-free workplace laws reduced the incidence of the acute coronary events including myocardial infarction (MI) and sudden cardiac death (SCD). Background: Nonsmokers chronically exposed to second-hand smoke (SHS) are at increased risk of death from heart disease. However, a nonlinear dose relationship exists between SHS exposure and coronary heart disease (CHD) such that the relative risk of CHD is 1.31 for nonsmokers and 1.78 for smokers. Reductions in admissions for MI in locales where smoke-free workplace laws have been implemented have been observed, but none have assessed SCD. On January 1, 2002, a smoke-free restaurant law (Ordinance #1) was implemented in Olmsted County, Minnesota, and on October 1, 2007, all workplaces became smoke-free (Ordinance #2). Methods: Under the auspices of the Rochester Epidemiology Project, we measured the incidence of MI and SCD during the 18-month calendar period before and after implementation of each smoke-free ordinance. All MI were validated using biomarkers, cardiac pain, and Minnesota coding of the ECG. SCD was defined as out-of-hospital deaths assigned to CHD (ICD-9 codes 410 through 414). Results: For the overall study period of the 18 months before the implementation of the smoke-free restaurant ordinance and 18 months after the implementation of the smoke-free workplace ordinance, we observed a 45% decline in the incidence for MI (p <0.01) and a 50% decline in the incidence for SCD (p <0.01). See Table. During this same period, the prevalence of hypertension, diabetes, hypercholesterolemia, and obesity either remained constant or increased while the prevalence of smoking among adults declined by 23% (22% to 17%). Conclusion: In the Olmsted County population, substantial declines in the incidence of MI and SCD were observed after smoke-free laws were implemented. Smoke-free workplace laws may not only be associated with a decrease in MI but SCD as well.

Background: The increasing prevalence of heart failure (HF) and high associated costs has spurred investigation of factors related to adverse outcomes in these patients. Reports to date present discrepant evidence regarding the link between depression and HF outcomes, and only scarce data related to healthcare utilization in the form of emergency department (ED) visits are available. Purpose: To evaluate the relationship of depression with healthcare utilization and death among HF patients in the community. Methods: Residents of Olmsted, Dodge, and Fillmore, MN counties with HF were prospectively recruited between October 2007 and December 2010, and completed a 9-item Patient Health Questionnaire (PHQ-9) for depression categorized as: none-minimal (PHQ-9 score 0-4), mild (5-9), or moderate-severe (≥10). Anderson-Gill models were used to determine if depression predicted hospitalizations and ED visits while proportional hazards regression estimated hazard ratios for death. Results: Among 411 HF patients (mean age 73±13, 58% male), 15% had moderate-severe depression, 27% mild, and 58% none-minimal. Over a mean follow-up of 1.5 years, 613 hospitalizations, 786 ED visits, and 75 deaths occurred. The risk of all adverse outcomes increased stepwise with increasing severity of depression (Table). After adjustment for key clinical characteristics, moderate-severe depression was associated with nearly a 2-fold increased risk of hospitalization and ED visits, and almost a 4-fold increased risk of death. These results are independent of coexisting comorbidities. Conclusions: Depression is frequent among HF patients in the community and independently predicts a significant increase in the use of healthcare resources and mortality. Greater attention to the recognition and management of depression in HF may improve clinical outcomes and decrease healthcare utilization and expenditures in these patients. Hazard Ratios (95%CI) for Hospitalizations and All-Cause Mortality by Severity of Depression None-Minimal Mild Moderate-Severe P for trend Hospitalizations Crude 1.00 (ref) 1.23 (0.91-1.66) 2.01 (1.39-2.89) <0.001 Fully-Adjusted * 1.00 (ref) 1.15 (0.86-1.54) 1.93 (1.37-2.71) 0.001 Emergency Department Visits Crude 1.00 (ref) 1.42 (1.03-1.96) 1.99 (1.42-2.79) <0.001 Fully-Adjusted * 1.00 (ref) 1.39 (1.00-1.93) 1.98 (1.40-2.79) <0.001 All-Cause Mortality Crude 1.00 (ref) 1.53 (0.87-2.68) 3.33 (1.95-5.70) <0.001 Fully-Adjusted * 1.00 (ref) 1.55 (0.88-2.74) 3.84 (2.21-6.68) <0.001 * Adjusted for age, sex, and Charlson comorbidity index

Objective: To determine among community heart failure (HF) patients whether frailty is associated with an increased risk of hospitalization, emergency department (ED) visits and death, independently of comorbidities. Background: Frailty is associated with adverse outcomes in some populations; however the prognostic value of frailty among HF patients is not fully documented, particularly for healthcare utilization. Methods: Olmsted, Dodge and Fillmore County residents with HF between 10/2007 and 12/2010 were prospectively recruited to undergo frailty assessment. Frailty was defined as 3 or more of the following: unintentional weight loss >10 lbs. in 1 year, physical exhaustion, weak grip strength, and slowness and low activity measured by the SF-12 physical component score. Intermediate frailty was defined as having 1-2 components. To account for repeated events, Anderson-Gill modeling was used to determine if frailty predicted hospitalization or ED visits. Cox proportional hazards regression examined associations between frailty and death. Results: Among 409 patients (mean age 73±13, 58% male), 19% were frail and 55% had intermediate frailty. Within one year, 449 hospitalizations, 523 ED visits and 34 deaths occurred. There was a positive graded association between frailty and hospitalization and ED visits (Table). After adjustment for age, sex, ejection fraction and comorbidity, frailty was associated with an 80% increased risk of hospitalization and a 60% increased risk of ED visits. Frailty was also associated with more than a 2-fold increased risk of death after adjustment. Conclusion: In the community, frailty is prevalent and is a strong and independent predictor of hospitalizations, ED visits and death among HF patients. As it is independent from coexisting comorbidities, frailty defines new avenues for intervention and should be formally assessed clinically. Hazard Ratios (95% CI) for Hospitalizations, Emergency Department Visits and Death by Frailty Status Not Frail Intermediate Frail Frail P for trend Hospitalization Crude 1.00 1.46 (1.05-2.02) 2.15 (1.45-3.19) <0.001 Fully-adjusted 1.00 1.29 (0.94-1.77) 1.82 (1.22-2.73) 0.005 Emergency Department Visits Crude 1.00 1.59 (1.14-2.21) 1.88 (1.22-2.90) 0.002 Fully-adjusted 1.00 1.46 (1.05-2.05) 1.58 (1.01-2.48) 0.034 Death Crude 1.00 1.40 (0.73-2.69) 3.98 (2.01-7.90) <0.001 Fully-adjusted 1.00 0.87 (0.44-1.73) 2.42 (1.19-4.95) 0.003

Background: We recently developed an index of socioeconomic status (SES) termed HOUSES ( HOU sing-based index of S ocio E conomic S tatus) to overcome the absence of SES measures in common data sources. HOUSES has been associated with various childhood health outcomes to a similar extent as other measures of SES. Whether it is associated with outcomes in adults is unknown. To address this question, we assessed whether HOUSES was associated with mortality after MI. Methods: We conducted a population-based cohort study among all Olmsted County, MN residents with MI who were prospectively identified using predetermined criteria from November 1, 2002 to May 31, 2006. HOUSES was formulated based on a z-score for housing value, actual square footage, and numbers of bedrooms and bathrooms and categorized into quartiles. The 1-year mortality rate post MI was compared among subjects with different SES by HOUSES based on a log-rank test. Results: Among 696 patients with MI; 623 (90%) were successfully geo-coded to address and real property data. Of these 623 subjects, 594 (95%) were white and 263 (42%) female; the mean age was 68±15 years. Spearman correlation coefficient between HOUSES and education level was 0.23 (p<0.001). Mortality rates at 1 year following MI were 20% (95%CI: 13 - 26), 18% (11 - 24), 14% (8 - 19), and 16% (10 - 21) for patients in the first (lowest SES), second, third, and fourth quartiles (highest SES) of the HOUSES index, respectively (p=0.032). This association between HOUSES and mortality after MI was primarily explained by age and comorbid conditions which were associated with HOUSES. Cardioprotective drugs such as aspirin, beta-blocker, and statins were not associated with HOUSES nor accounted for the association between HOUSES and mortality after MI. Conclusions: Despite the lack of a strong correlation with other SES measure (i.e. no redundancy), HOUSES may be useful for overcoming the paucity of conventional SES measures in commonly used datasets in epidemiological research concerning cardiovascular disease among adults.

Background: There is growing awareness of an association between cardiovascular disease (CVD) and fractures, and a temporal increase in fracture risk after myocardial infarction has been noted but the mechanisms are not delineated. To evaluate this relationship, we systematically examined the association of hip fracture with all disease categories and assessed related secular trends. Methods: Using resources of the Rochester Epidemiology Project, a population-based incident case-control study was conducted. Disease history was compared between all Olmsted County, Minnesota, residents aged 50 years or older with a first hip fracture in 1985–2006 and community control subjects individually matched (1:1) to cases on age, sex, and index year (n=3,808; mean age [SD], 82 [9] years; 76% women). Results: All CVD and numerous non-CVD categories (e.g., infectious diseases, nutritional and metabolic diseases, mental disorders, diseases of the nervous system and sense organs, and diseases of the respiratory system) were associated with fracture risk. However, increasing temporal trends were almost exclusively detected in categories of CVD (Figure). The largest increases in association were observed for ischemic heart disease, other forms of heart disease (including heart failure), hypertension, and diabetes and were more pronounced among elderly women than other demographic groups. Conclusions: While the association with hip fracture was not specific to CVD, temporal increases were mainly detected in cardio-metabolic diseases, all of which have also been linked previously to frailty. This could delineate a common pathway that warrants further investigation.

Background: The goal of heart failure (HF) performance measures is to improve the quality of care by enabling the practice implementation of guidelines. The guidelines define the population eligible for each measure. Little is known about the proportion of eligible patients to which these measures are applicable in the community. Methods: We determined the eligibility for and the adherence to performance measures and beta-blocker therapy in a community-based cohort of hospitalized patients diagnosed with incident HF from January 2005 to April 2011. Results: Of 294 inpatients with first ever HF (mean age 72 ± 15 years, 48% men), ejection fraction was measured in 292 (99%) patients during hospitalization. Of these, 97 (33%) had an ejection fraction <40% and were thus candidates for beta-blocker and angiotensin converting enzyme (ACE) inhibitors or angiotensin receptor blocker (ARB) therapy. After excluding individuals with absolute contraindications, 71 patients were eligible to receive ACE inhibitors or ARB, and 86 were eligible to receive beta-blockers (figure). Among those eligible, 83% received ACEI/ARB and 91% received beta-blockers. Excluding those with relative contraindications, 70 patients were eligible for beta-blockers and 90% of them received it. Among the 139 (47%) individuals with HF and atrial fibrillation, 35 were eligible for warfarin and 49% received it. Of the 36 current smokers, 22 (61%) received cessation counseling during hospitalization. Conclusions: In the community, among patients hospitalized with HF eligible for performance measures, the implementation of performance measures varies by measure and can be improved for some. However, most community HF patients are not eligible for performance measures and other approaches should be identified to improve their care and outcomes.

Objective: To compare two measures of frailty in a community cohort of heart failure (HF) patients. Background: Frailty is increasingly recognized as an important prognostic indicator in HF. Several methods have been proposed to measure frailty. Some conceptualize frailty as a biological phenotype, while others define it as an accumulation of deficits (impairments, disabilities, comorbid diseases), termed the Cumulative Deficit Index (CDI). Each approach has conceptual strengths and limitations; a distinct feature of the CDI is the ability to extract data from medical records. These two methods have never been compared in a community HF cohort. Methods: Olmsted, Dodge and Fillmore County, MN residents with HF between 10/2007 and 12/2010 were prospectively recruited to assess the frailty phenotype. The biological frailty phenotype was defined as ≥3 of the following: unintentional weight loss >10 lbs. in 1 year, physical exhaustion, weak grip strength, and slowness and low activity measured by the SF-12 physical component score. Intermediate frailty was defined as having 1–2 components. The CDI was based on 33 deficits and defined as the proportion of deficits present for each patient. Results: Among 131 patients (mean age 70.5±14, 62% male), according to the biological frailty phenotype definition 18% were frail, 50% intermediate frail and 31% not frail. The CDI ranged from 0.03–0.70, with a mean (SD) of 0.22 (0.12). The CDI was significantly correlated with the frailty phenotype (r=0.59, p<0.001). The mean (SD) of the CDI was 0.35 (0.14), 0.21 (0.10) and 0.15 (0.07) among the frail, intermediate frail and not frail phenotypes (Figure). Conclusion: The CDI is significantly associated with the biological frailty phenotype and can thus be used as an alternative approach to measure frailty in HF. As the components of the biological frailty phenotype are not routinely assessed clinically, the CDI, which can be ascertained from medical records, is a feasible approach to ascertain frailty in large cohorts.

Background: Contemporary data on survival after incident acute coronary syndrome (ACS), including both myocardial infarction (MI) and unstable angina (UA), are limited. Objective: To describe survival after incident ACS, to determine if it differs by ACS type (MI or UA) and to determine whether it has improved over time. Methods: Olmsted County, MN residents hospitalized between 1/1/2005-12/31/2010 were screened for incident ACS. ACS was defined as either MI validated by standard epidemiological criteria or UA validated by the Braunwald classification. Patients were followed for death from any cause. Cox proportional hazards regression was used to determine whether survival differed by ACS type, while adjusting for year of diagnosis, age, sex and comorbidities. Results: Among 1,160 incident ACS cases (mean±SD age 66.9±14.8, 60% male), 35% were UA and 65% were MI. After a mean (SD) follow up of 3.7 (2.1) years, 274 deaths occurred. The 3-year Kaplan-Meier survival estimate for MI was 79.6% (95% CI: 76.7%-82.6%) and for UA was 84.9% (95% CI: 81.3%-88.6%) (log-rank p=0.011). The association of ACS type with survival differed by age (p=0.056). After adjustment for year of diagnosis, sex and comorbidities, no difference in survival was observed between ACS types among those aged <60 (HR for MI vs. UA: 0.64, 95% 0.29-1.42). By contrast, among patients aged 60-79, those with an MI had 2 times the risk of death compared to those with UA (HR: 2.04, 95% CI: 1.24-3.37). Patients aged 80 or older who had an MI had a 40% increased risk of death compared to patients of the same age who had UA (HR: 1.42, 95% CI: 1.02-1.98). There was no difference in survival over time (HR for 2010 vs. 2005: 0.91, 95% CI: 0.61-1.36). Conclusions: Survival did not differ between UA and MI patients younger than 60, however among patients 60 or older, survival was worse among those with an MI. Survival after ACS did not change over the study period.

Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice, causes substantial morbidity, and is associated with an excess risk of mortality. However, information on contemporary time trends in survival after AF is lacking. Thus, we aimed to determine whether survival after incident AF has changed over the last decade in a community-based cohort of 3413 individuals with incident AF between 2000 and 2010. Methods: Olmsted County, MN residents 18 years of age and older with a first-ever AF or atrial flutter event between 2000 and 2010 were identified using inpatient and outpatient diagnostic codes and electrocardiograms. Deaths from any cause were ascertained through August 31, 2012 and time trends in survival after AF were examined using Kaplan-Meier curves and Cox proportional hazards regression. Results: Among 3413 individuals with incident AF (52% men, age range 18-104) between 2000 and 2010, 1561 deaths were observed over a median follow-up of 3.4 years. Survival did not differ by year of AF diagnosis (figure). In addition, the proportion of cardiovascular disease-related deaths compared to non-cardiovascular deaths did not differ over time. After adjustment for age, sex, and Charlson comorbidity index, the hazard ratios for all-cause mortality were 1.09 (95% CI 0.97-1.23) for those diagnosed with AF in 2004-2007 vs. 2000-2003 and 1.04 (95% CI 0.90-1.12) for 2008-2010 vs. 2000-2003. Furthermore, the risk of death did not differ by sex after adjustment for age and comorbidity (HR 1.00, 95% CI 0.90-1.11 for men vs. women). Conclusions: In the community, survival after AF has remained constant over the last decade despite substantial changes in the recommendations for treatment of AF. This underscores the importance of identification of prognostic factors and continued surveillance of outcomes in AF, as well as a better understanding of how to optimize the management of AF to improve outcomes in these patients.

Objectives: To determine the prevalence and relationship of frailty and health-related quality of life (HRQOL) among residents of long-term care [nursing homes (NH) and assisted living (AL)] facilities. Methods: Residents of NH and AL facilities in La Crosse County, Wisconsin, were recruited 1/2009-6/2010 and assessed for frailty (gait speed, unintended weight loss, grip strength), comorbidity (Charlson index), and HRQOL [Short Form (SF)-36]. Results: Among 137 participants, 85% were frail. Frail residents were older, had more comorbidities (2.0 vs. 0, p < .001) and lower mean SF-36 Physical Component Score (PCS, 32 vs. 48, p < .001). Following adjustments for age, sex, and comorbidities, compared to nonfrail residents, frail residents had lower SF-36 PCS (mean difference −14.7, 95% CI. −19.3,−10.1, p < .001). Frailty, comorbidity, and HRQOL did not differ between NH and AL facilities. Discussion: Frail residents had lower HRQOL, suggesting that preventing frailty may lead to better HRQOL among residents of long-term care facilities.