DASH Score and Subsequent Risk of Coronary Artery Disease: The Findings From Million Veteran Program

While adherence to healthful dietary patterns has been associated with a lower risk of coronary artery disease (CAD) in the general population, limited data are available among US veterans. We tested the hypothesis that adherence to Dietary Approach to Stop Hypertension (DASH) food pattern is associated with a lower risk of developing CAD among veterans. We analyzed data on 153 802 participants of the Million Veteran Program enrolled between 2011 and 2016. Information on dietary habits was obtained using a food frequency questionnaire at enrollment. We used electronic health records to assess the development of CAD during follow-up. Of the 153 802 veterans who provided information on diet and were free of CAD at baseline, the mean age was 64.0 (SD=11.8) years and 90.4% were men. During a mean follow-up of 2.8 years, 5451 CAD cases occurred. The crude incidence rate of CAD was 14.0, 13.1, 12.6, 12.3, and 11.1 cases per 1000 person-years across consecutive quintiles of Dietary Approach to Stop Hypertension score. Hazard ratios (95% confidence interval) for CAD were 1.0 (ref), 0.91 (0.84-0.99), 0.87 (0.80-0.95), 0.86 (0.79-0.94), and 0.80 (0.73-0.87) from the lowest to highest quintile of Dietary Approach to Stop Hypertension score controlling for age, sex, body mass index, race, smoking, exercise, alcohol intake, and statin use (P linear trend, <0.0001). Our data are consistent with an inverse association between Dietary Approach to Stop Hypertension diet score and incidence of CAD among US veterans

Alcohol Consumption and Risk of Coronary Artery Disease (from the Million Veteran Program)

Moderate alcohol consumption has been associated with a lower risk of coronary artery disease (CAD) in the general population but has not been well studied in US veterans. We obtained self-reported alcohol consumption from Million Veteran Program participants. Using electronic health records, CAD events were defined as 1 inpatient or 2 outpatient diagnosis codes for CAD, or 1 code for a coronary procedure. We excluded participants with prevalent CAD (n = 69,995) or incomplete alcohol information (n = 8,449). We used a Cox proportional hazards model to estimate hazard ratios and 95% confidence intervals for CAD, adjusting for age, gender, body mass index, race, smoking, education, and exercise. Among 156,728 participants, the mean age was 65.3 years (standard deviation = 12.1) and 91% were men. There were 6,153 CAD events during a mean follow-up of 2.9 years. Adjusted hazard ratios (95% confidence intervals) for CAD were 1.00 (reference), 1.02 (0.92 to 1.13), 0.83 (0.74 to 0.93), 0.77 (0.67 to 0.87), 0.71 (0.62 to 0.81), 0.62 (0.51 to 0.76), 0.58 (0.46 to 0.74), and 0.95 (0.85 to 1.06) for categories of never drinker; former drinker; current drinkers of ≤0.5 drink/day, >0.5 to 1 drink/day, >1 to 2 drinks/day, >2 to 3 drinks/day, and >3 to 4 drinks/day; and heavy drinkers (>4 drinks/day) or alcohol use disorder, respectively. For a fixed amount of ethanol, intake at ≥3 days/week was associated with lower CAD risk compared with ≤1 day/week. Beverage preference (beer, wine, or liquor) did not influence the alcohol-CAD relation. Our data show a lower risk of CAD with light-to-moderate alcohol consumption among US veterans, and drinking frequency may provide a further reduction in risk

Gender Differences in Demographic and Health Characteristics of the Million Veteran Program Cohort

BackgroundThe Department of Veterans Affairs Million Veteran Program (MVP) is the largest ongoing cohort program of its kind, with 654,903 enrollees as of June 2018. The objectives of this study were to examine gender differences in the MVP cohort with respect to response and enrollment rates; demographic, health, and health care characteristics; and prevalence of self-reported health conditions.MethodsThe MVP Baseline Survey was completed by 415,694 veterans (8% women), providing self-report measures of demographic characteristics, health status, and medical history.ResultsRelative to men, women demonstrated a higher positive responder rate (23.0% vs. 16.0%), slightly higher enrollment rate (13.5% vs. 12.9%), and, among enrollees, a lower survey completion rate (59.7% vs. 63.8%). Women were younger, more racially diverse, had higher educational attainment, and were less likely to be married or cohabitating with a partner than men. Women were more likely to report good to excellent health status but poorer physical fitness, and less likely to report lifetime smoking and drinking than men. Compared with men, women veterans showed an increased prevalence of musculoskeletal conditions, thyroid problems, gastrointestinal conditions, migraine headaches, and mental health disorders, as well as a decreased prevalence of gout, cardiovascular diseases, high cholesterol, diabetes, and hearing problems.ConclusionsThese results revealed some substantial gender differences in the research participation rates, demographic profile, health characteristics, and prevalence of health conditions for veterans in the MVP cohort. Findings highlight the need for tailoring recruitment efforts to ensure representation of the increasing women veteran population receiving care through the Veterans Health Administration

Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies

Large-scale multi-ethnic cohorts offer unprecedented opportunities to elucidate the genetic factors influencing complex traits related to health and disease among minority populations. At the same time, the genetic diversity in these cohorts presents new challenges for analysis and interpretation. We consider the utility of race and/or ethnicity categories in genome-wide association studies (GWASs) of multi-ethnic cohorts. We demonstrate that race/ethnicity information enhances the ability to understand population-specific genetic architecture. To address the practical issue that self-identified racial/ethnic information may be incomplete, we propose a machine learning algorithm that produces a surrogate variable, termed HARE. We use height as a model trait to demonstrate the utility of HARE and ethnicity-specific GWASs