IJCS | Volume 31, Nº4, July / August 2018

407 Alvim et al. Prevalence of peripheral artery disease Int J Cardiovasc Sci. 2018;31(4)405-413 Original Article Information regarding medical history (angina pectoris, myocardial infarction, stroke, kidney failure, and depression) and environmental risk factors such as smoking and alcohol use were evaluated through a questionnaire completed by each participant. The questionnaire was based on the World Health Organization’s Multinational Monitoring Trends and Determinants in Cardiovascular Disease (MONICA) 31 project epidemiological instrument, and was applied and filled out by research assistants specifically trained for this task. Screening of peripheral artery disease The screening of PAD was performed with the ankle- brachial index (ABI), which was measured by a single trained examiner using a sphygmomanometer (Heidji, Brazil) with a cuff suitable for the circumference of the limbs and a 10 MHz portable Doppler device (DV 610B, MEDMEGA, SP, Brazil). The ABI was determined for each leg by the ratio between the highest SBP obtained at the ankle (posterior tibial and dorsalis pedis arteries) and highest SBP obtained in the arms (brachial artery). 12-14 The methodology of the test and the ABI classification were based on recommendations of the American College of Cardiology / American Heart Association (ACC/ AHA). 12,13 ABI values between 0.91 and 1.39 were considered normal. Values ≤ 0.90 were considered compatible with PAD and values ≥ 1.40 were considered inconclusive for PAD and were excluded from the analysis. Statistical analysis Categorical variables were compared using the chi-square test and are presented as percentage, while continuous variables are presented as mean ± standard deviation. The normality of the data was confirmed with the Kolmogorov-Smirnov test. Unpaired Student t test was performed to analyze demographic, hemodynamic, and biochemical data according to PAD status. Since the cutoff value for PAD diagnosis based on ABI is well-established in the literature, we carried out univariate and multivariate logistic regression analyses to determine the association between PAD (ABI < 0.9) as the dependent variable and age, hypertension, diabetes, myocardial infarction, smoking, and sedentary lifestyle as predictor variables. Statistical analyses were carried out using SPSS (version 19) software (Chicago, IL, USA), with the level of significance set at 5%. Results A total of 1,634 individuals were screened for PAD. Seven individuals presented an ABI above 1.4 and were excluded from the analysis. Therefore, 1,627 volunteers were included in the study. The age of the participants ranged from 18 to 102 years (mean 44.9 ± 16.4 years). Table 1 shows the demographic, anthropometric, biochemical, and hemodynamic characteristics of the individuals with and without PAD, defined as an ABI equal to or lower than 0.9. Age, BMI, HbA1c, and SBP were higher in volunteers with PAD. The presence of PAD was also more frequent in elderly compared with younger individuals, and in blacks compared with whites. Figure 1 presents the data related to the prevalence of PAD using the ABI in different age groups. Overall, the prevalence was very low (1.05%). Only one case of PAD was observed below the age of 30 years, and the prevalence of PAD increased after the fifth decade, peaking at the age of 70 years, when it reached 5.2%. The frequency of PAD by decade is presented in the Table 2. Table 3 presents the data related to the lifestyle characteristics of the volunteers. The frequency and amount of smokingwere higher in individuals with PAD. There was also a higher frequency of physically inactive volunteers in the PAD group. Table 4 presents a comparison of clinical characteristics in individuals with and without PAD. A higher prevalence of hypertension, diabetes, and obesity was observed in individuals with a diagnosis of PAD. The presence of hypercholesterolemia was not different between groups. Also, a prior history of myocardial infarction was more frequent in the PAD group. Table 5 presents univariate and multivariate logistic regression models for PAD. In multivariate analysis, age, diabetes, smoking, and physical inactivity were significantly and independently associated with PAD. Discussion In terms of the number of individuals included, the present study is the largest investigation of the prevalence of PAD in a Brazilian population. The Baependi Heart Study is a Brazilian cohort study investigating cardiovascular risk factors and heritability in residents of