2 potential negative consequences. While several studies sup- port light-to-moderate alcohol consumption as a protective factor against CVD and all-cause mortality, excessive alcohol intake has been associated with increased triglycerides, high blood pressure, risk of some cancers, liver cirrhosis, heart failure, and all-cause mortality [9, 12, 18]. Also, certain cancers (e.g., breast) may be associated with increased risk at low doses, but no dose response thereafter [19–21]. As a result of these conﬂicting messages, the public may be confused about the relationship between alcohol and health outcomes. The purpose of this study was to analyze the rela- tionship between alcohol consumption and all-cause and CVD mortality in a cohort of men while considering a variety of potential confounding and modifying risk factors. Additionally, diﬀerential eﬀects of types of alcohol on these health outcomes were investigated. 2. Materials and Methods 2.1. Study Participants. Study participants were from the Aerobics Center Longitudinal Study (ACLS) [22], a prospec- tive epidemiological study of health outcomes in USA adults. The sample for the current analyses was limited to men, the majority of whom were white, middle to upper income, received a baseline examination at the Cooper Clinic in Dallas, Texas between 1974 and 2002 with at least one year of followup, were aged ≥20 years at baseline, were free of known CVD, cancer, or abnormal ECG, and had complete information on alcohol intake and maximal exercise treadmill test. Individuals participating in the ACLS were either referred to the clinic by their employers or physicians or through self-referral. The study was annually reviewed and approved by the Cooper Institute Institutional Review Board, and all participants gave written informed consent for the baseline clinical examination and follow-up. 2.2. Primary Exposure Variable. Alcohol intake in drinks per week among participants was self-reported at baseline. Participants were asked, “How many 12-ounce drinks of beer, 3-ounce drinks of wine (5-ounce drinks of wine during more recent data collection cycles), and/or 1.5-ounce drinks of hard liquor do you consume per week?” Self-report alcohol intake has been previously validated against dietary records in men (r = 0.86) [23, 24]. Participants were then classiﬁed either as nondrinkers, or in quartiles of drinkers based on baseline alcohol drinking reports. 2.3. Outcome Variables. All participants were followed from the date of their baseline examination until their death or December 31, 2003. Mortality surveillance was primarily through the National Death Index. CVD mortality was deﬁned as the International Classiﬁcation of Diseases, Ninth Revision codes 390 to 449.9 before 1999 and Tenth Revision codes I00 to I78 during 1999–2003. 2.4. Covariates. The baseline clinical assessment has been previously described in detail [22, 25, 26]. At the baseline Journal of Aging Research visit patients completed a written survey and anthropomet- ric, blood pressure, blood chemistry, and electrocardiogram measures. Body Mass Index [BMI = weight (kg)/height (m)2] was calculated from height and weight. Resting blood pres- sure was assessed via ascultatory method [27]. Blood samples were drawn after a 12-hour overnight fast, and analyzed for fasting glucose and cholesterol using automated bioassays according to the Centers for Disease Control and Prevention Lipid Standardization Program. Hypertension, hypercholes- terolemia, and diabetes were deﬁned according to clinical thresholds or self-reported as a previous diagnosis from a physician. Hypertension was deﬁned as resting systolic or diastolic blood pressure ≥140/90 mmHg, hypercholes- terolemia was deﬁned as total cholesterol ≥240 mg/dL [28], and diabetes was deﬁned as fasting glucose ≥126 mg/dL [29]. The questionnaire included questions on smoking habits, family history of CVD, and the presence of neuropsychiatric conditions including anxiety, depression, suicidal thoughts, or psychological counseling. Cardiorespiratory ﬁtness (CRF) was assessed using symptom-limited maximal treadmill time during the modiﬁed Balke Protocol [22, 30]. Test termination occurred by participant volition or physician determined medical reasons. Test duration has been strongly correlated with maximal oxygen uptake (r = 0.92) [31]. Cardiorespiratory ﬁtness is a quantiﬁable, objective measure with stronger associations to future health outcomes than self-reported physical activity [32]. Treadmill times were classiﬁed into ﬁtness quintiles with the ﬁrst quintile classiﬁed as unﬁt and the remaining four quintiles as ﬁt [33]. 2.5. Statistical Analysis. Cox proportional hazards models were used to calculate hazard ratios (HRs) and associated 95% conﬁdence intervals. Alcohol consumption was the primary exposure of interest. All-cause and CVD mortality were ﬁt as the outcomes (i.e., death or not, and time to event or censoring) for survival analysis. Nondrinkers were used as the referent group and those classiﬁed as drinkers were categorized into quartiles of exposure. Linear and quadratic trends were tested by ﬁtting the continuous variable of alcohol consumption in the basic model for both all-cause and cardiovascular disease mortality. The basic model was adjusted for age (in years), year of examination, BMI, smoking (current smoker or not), family history of CVD (yes or no), and treadmill time (minutes). Because blood pressure [34], insulin sensitivity [35], and lipid levels [36] have been shown to mediate the relationship between alcohol and CVD mortality, they were added individually and then simultaneously into the basic model. Finally, the full model was adjusted for psychological variables [15, 16]. To examine eﬀect modiﬁcation due to other health risk factors, multivariate stratiﬁed analyses were conducted for dichotomies based on age (<60 and ≥60 years), BMI (<25 and ≥25 kg/m2), health status (healthy and unhealthy deﬁned as having at least one of the following diseases: hypertension, diabetes, or hyperlipidemia), and ﬁtness (least ﬁt 20% and most ﬁt 80%) to test for eﬀect modiﬁcation. These models were adjusted for year of examination, smok- ing, family history of CVD, and age, BMI, health status, and ﬁtness where appropriate.