IJCS | Volume 31, Nº6, November / December 2018

596 Rissardi et al. Effects of physical inactivity on blood glucose Int J Cardiovasc Sci. 2018;31(6)594-602 Original Article borderline BP values, a new measurement was taken on a different day at the same hour of the last measurement. The socioeconomic status was divided into classes A, B, C, D and E, and later into groups AB, C and DE (based on family income and assets). Groups AB had a monthly income higher than 10 minimumwages; Group C, between 3 and 5 minimum wages; and Groups DE, lower than 3 minimumwages. 12,16 Formal education was defined by the number of years of study, considering two levels: Level 1: 0-11 school years; and Level 2: > 11 school years, including university degrees. 12 The short version of the International Physical Activity Questionnaire was used to assess the overall physical activity (OPA), including work-related physical activity (WPA), transport-related physical activity (TPA), domestic activities (DA) and leisure time physical activity (LTPA). The level of physical activity was classified as physically active individuals (PA), who performedmore than 150 minutes of physical activity per week (including manual labor jobs, walking, running, swimming and cycling) and physically inactive individuals (PI), who performed < 150 minutes per week. Clinical variables The BMI was obtained by the weight/height 2 ratio (kg/m 2 ). A calibrated portable scale was used for weight measurements. Individuals were classified as normal weight (18.5 to 24.9), overweight (25 to 29.9) and obese (≥ 30 kg/m 2 ). 17 The diagnosis of type T2DM was established based on the patient’s medical history, on hypoglycemic medication and blood glucose measurements. 18 The levels of blood glucose, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c) and triglycerides (TG) were analyzed after 12 hours of fasting by the colorimetric method. An RXL analyzer and the Dade Behringer reagent were used for the analysis. The low-density lipoprotein cholesterol (LDL-c) levels were calculated using Friedewald formula: LDL-c = TC - (HDL-c + TG /5) for TG < 400mg/dL. 19 Metabolic syndrome (MetS) was classified according to the following diagnostic criteria: waist circumference (men ≥ 102 cm and women ≥ 88 cm), TG ≥ 150 mg/ dL, HDL-c [< 40 mg/dL (for male) and < 50 mg/dL (for female)], BP (Systolic BP ≥ 130 or Diastolic BP ≥ 85 mmHg), fasting blood glucose (≥ 100 mg/dL or T2DM) or specific treatment for these conditions. 20 Statistical analysis Statistical analysis was carried out using the Minitab programs version 12.22 and R 2.4.1. Estimated frequency of physical activity according to factors (education, age, gender and socioeconomic status), characteristics (BMI, HT, MetS), and metabolic parameters (cholesterol, HDL-c, LDL-c, TG and blood glucose) was performed by estimation and population association testing by means of the method of weighted least squares. Correction for the weight of the population was made according to the age group: 55.33% for 18-39 years, 18.45% for 40-49 years, 12.29% for 50-59 years, 8.20% for 60-69 years and 5.73% for 70 years or more. The bootstrap statistical method (simulationmethod of convex combinations with the same weights used for the analysis of frequencies, where 1,000 bootstrap samples are generated for each comparison) was used to assess the physical activity, associated with serum lipid and glucose levels. This method (resampling technique) attempts to accomplish what would be desirable to do in practice if it were possible: to repeat the experiment. The observations are chosen at random and the estimates recalculated for the purpose of improving the final estimate. 21 The level of significance was 5%. Results Baseline characteristics A sample of 1,717 urban adults (≥ 18 years) was evaluated in this study. Table 1 shows the distribution of the studied sample and the prevalence of PI individuals adjusted for the population according to age groups (in years) and the expected number of PI in the population. In the general population, the prevalence of PI individuals was 65.8% (95% CI: 62.2%-69.5%) and 34.2% (95% CI: 30.5%-37.8%) for the PA group. Regarding gender and age range, there was a higher prevalence of PI among women in both age groups 18 to 39 years and ≥ 70 years (women 73.9% and men 56.3%; p = 0.006 and women 83.1% and men 72.7%; p = 0.03, respectively). No differences were found between genders in the other age groups. Table 2 demonstrates the levels of physical activity estimated for the population and related to demographic data (age, gender, education and socioeconomic status), as well as risk factors (HT, obesity andMetS). Table 2 also shows the prevalence ratios among the studied variables in the PI individuals.