Abstracts / Annals of Epidemiology 22 (2012) 661e680
P26. Breaking the Paradigm of Clinic-Based Cohort Studies: the Reasons for Geographic and Racial Differences in Stroke (Regards) Study V.J. Howard, L. Pulley, M. Cushman, L.A. McClure, V. Wadley, G. Howard. Dept. of Epidemiology, Univ of Alabama at Birmingham, Birmingham, AL Purpose: A national cohort study focusing on stroke was needed to address black-white and geographic disparities in stroke mortality. A barrier was costs of large sample size required to generate large number of events for reliable estimates of associations with risk factors. Most large populationbased cohort studies in the US have been conducted in pre-dominantly white regions, are clinic-based, and limited to a few geographic regions. Methods: A novel study design recruited participants aged > 45, black and white, from national, well-characterized lists. Potential participants were mailed a letter/brochure followed by a telephone call. After verbal consent, telephone interview assessed demographics, cardiovascular health and cognitive status. During in-home visit, physical measurements, blood and urine samples, ECG, and written consent were obtained. Participants are followed by phone every 6-months for suspected strokes with medical records retrieval and central adjudication. Annually and biennially, brief and comprehensive assessments of global cognitive function are conducted. Results: 30,239 participants (42% black, 55% women, 56% southeast US) were recruited (2003-2007) and examined at a 5-year cost of < $800 per participant (direct costs). Physical measures were obtained on > 99%; 462,309 cryovials of biological samples were collected. Through April 2012, retention is 85%, mean follow-up for stroke events is 5.8 + 1.9 years. Conclusion: The novel aspects of the study allow for fiscally-feasible creation and maintenance of a national cohort to address geographic and racial differences in stroke.
P27. Quanitfying the Contributions of Behavioral and Biological Risk Factors to Socioeconomic Disparities in Coronary Heart Disease Incidence K.N. Kershaw, M. Droomers, W.R. Robinson, M.R. Carnethon, M.L. Daviglus, W.M.M. Verschuren. Northwestern University Feinberg School of Medicine, Chicago, IL Purpose: Previous studies have used analytic approaches that limit our ability to disentangle the relative contributions of behavioral and biological risk factors to coronary heart disease (CHD) disparities. In this study we used path analysis to assess mediation of the effect of low education on incident CHD by multiple risk factors simultaneously. Methods: We used data from the Dutch Monitoring Project on Risk Factors for Chronic Diseases. Analyses are based on 15,067 participants aged 20-65 years examined 1994-1997 and followed for events until January 1, 2008. The product of coefficients method was used to quantify and test mediation of the low education-CHD association by behavioral (current cigarette smoking, heavy alcohol use, poor diet, and physical inactivity) and biological (obesity, hypertension, diabetes, and hypercholesterolemia) risk factors. Results: Behavioral and biological risk factors accounted for 40.4% (95% CI: 29.6%-52.3%) of the low education-incident CHD association. Obesity was the strongest mediator, accounting for 12.9% (95% CI: 8.1%- 19.0%) of the association, followed by physical inactivity (8.2%; 95% CI: 4.4%-12.4%) and current smoking (8.2%; 95% CI: 5.4%-11.3%). Conclusion: Obesity, physical inactivity, and current smoking were the strongest mediators of the association between low education and incident CHD in this cohort. Path analysis may provide further insight into population-specific pathways linking low SES to higher CHD risk.
P28. Prevalence and Predictors of Cardiovascular Health: Findings From the Survey of the Health of Wisconsin K.C.M. Malecki, P. Peppard, M.A. Palta, M.A. Walsh, F.J. Nieto. Department of Population Health Sciences, University of Wisconsin, Madison, WI Purpose: In 2010, the American Health Association identified seven risk factors and health behaviors (body mass index, cholesterol, glucose, diet, physical activity, blood pressure and smoking) that can be combined to
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indicate “ideal,” “intermediate,” or “poor” cardiovascular (CV) health. The purpose of this study is to estimate the population prevalence and disparities of ideal CV health and to identify correlations of CV health factors with selfreported health and mental well-being. Methods: We used data from the Survey of the Health of Wisconsin (SHOW) a geographically diverse (urban and rural) population-based research study of adults, age 21-74 years, to estimate the prevalence of ideal cardiovascular health between 2008-2010. Contextual neighborhood level predictors of CV health and health disparities were examined along with correlations of CV health, self-reported health status and measures of mental well-being using the Depression, Anxiety and Stress, Scale (DASS). Results: Of the 1570 participants; 1170 had complete data. Of these only 1.03% had ideal CV health for all 7 metrics while at least 98% had at least one of the 7 metrics. Personal income and age were the strongest predictors of having one or more ideal CV health factors. Conclusion: Population prevalence of ideal and intermediate CV health is low. Research shows that ideal CV health reduces risk of adverse CV events and thus increases in primordial individual and community level interventions to improve CV health are needed.
P29-S. Insufficient Sleep and Cardiovascular Disease: Is BMI an Effect Modifier? Results From a National, Multiethnic Sample J.L. Smith, V.K. Cheruvu, M.D. Zullo. College of Public Health, Kent State University, Kent, OH Purpose: This research examined the association between insufficient sleep and cardiovascular disease (CVD), coronary heart disease (CHD), and stroke by categories of body mass index (BMI). Methods: Cross-sectional study using data from the 2009 Behavioral Risk Factor Surveillance System (n¼429,917). Insufficient sleep was categorized as zero (reference), 1-13, 14-29, and 30 days. Three outcomes were examined using multivariable logistic regression: CVD, CHD, and stroke. Relationships were examined overall and for varying race/ethnicity. Results: The prevalence of insufficient sleep was 31%, 41%, 16%, and 11% for zero, 1-13, 14-29, and 30 days, respectively. Increasing categories of insufficient sleep were associated with increasing odds for CVD (odds ratio (OR): 1.0, 95% confidence interval (CI): 0.95, 1.1; OR: 1.3, CI: 1.2, 1.4; OR: 1.6, CI: 1.5, 1.8, respectively) and CHD (OR: 1.0, CI: 0.95, 1.1; OR: 1.4, CI: 1.3, 1.5; OR: 1.7, CI: 1.6, 1.9, respectively) compared to reference. Effects were not modified by BMI (trend: p>0.05). Increasing effects were observed within sleep categories between race/ethnicity (white, non-Hispanic; black, non-Hispanic; and Hispanic, respectively) for the CVD and CHD outcomes only. No effect was observed for stroke except for within the 30 day insufficient sleep category across racial/ethnic group. Conclusion: Associations between insufficient sleep and CVD and CHD were not modified by increasing categories of BMI. These results were consistent across racial/ethnic group. Furthermore, CHD and not stroke accounted for the observed association between insufficient sleep and CVD.
P30-S. Association Between Illicit Drug Use and Cardiometabolic Disease Risk: an Analysis of 2005- 2008 Nhanes Data D.C. Vidot, D.C. Vidot, K. Arheart, W.M. Hlaing, E.S. Bandstra, S.E. Messiah. Dept. of Epidemiology, University of Miami Miller School of Medicine, Miami, FL Purpose: The association between illicit drug use (DU) and cardiometabolic disease risk (CMDR) has been largely unexplored, yet both conditions are highly prevalent in the United States. We explored this association using nationally representative data in a sample of young adults. Methods: The 2005-2008 NHANES data among 20-45 year olds (N¼8,738) was used to analyze the relationship between DU (ever used, used > 1 time, never used) and abnormal/elevated CMDR factors (CMDRF) (hyperlipidemia, hyperinsulimia, hypertension, c-reactive protein, body mass index [kg/m2], waist circumference [WC], and cigarette use) via chi square and logistic regression procedures. Results: Over half (57%) reported DU at least once in lifetime (OL). Males (32%) were significantly more likely to report DU than females (26%) (p < 0.0001). Mean BMI fell into “overweight” (>25 kg/m2) category for DU and