Study design and sample population
During the 2014–2017 academic years, we reviewed a cross-sectional component of the FUPRECOL (in Spanish Asociación de la Fuerza Prensil con Manifestaciones Tempranas de Riesgo Cardiovascular en Adultos Colombianos) Adults study, which investigated the association between muscular strength and cardiometabolic risk factors in a sample of Colombian university students. We recently published a complete description of the FUPRECOL Adults study design, methods, and primary outcomes for our current cohort [15]. The original sample consisted of adults (men: n = 706; women: n = 1126). From this subgroup, 784 university students (78.6% women) had valid data in AC and all components included in the cardiometabolic variables and AC survey. There were no differences in the study key characteristics (i.e., age, sex distribution, BMI, and MetS components) between the current study sample and the original FUPRECOL Adults Study sample (n = 1832, all p > 0.100). Data were collected in Tunja, a city in the Eastern Range of the Colombian Andes in a region known as the Altiplano Cundiboyacense, located 130 km northeast of Bogotá. In 2016, this city had an estimated population of 191,878 inhabitants. The city center is at an elevation of 2820 m (9,250 ft) above sea level. Tunja is an important educational center and is home to several well-known universities.
Measurements
Anthropometry and body fatness
Subjects were tested while wearing light clothing (shoes were removed). Height (Seca® 274, Hamburg, Germany), body mass (Model Tanita® BC-420®, Tokyo, Japan) and waist circumference (WC, Lufkin W606 PM®, Parsippany, NJ, USA) were assessed according to international standards for anthropometric assessment [16]. The height and body mass measurements were used to calculate the BMI = body mass (kg)/height(m)2]. Trained researchers performed the measurements according to standardized procedures. The technical error of measurement values was less than 2% for all anthropometric variables. BF% was determined by a tetrapolar whole body impedance (Tanita Model BC-420®, Tokyo, Japan). A detailed description of the bioelectrical impedance analysis technique was presented in a previous study [17]. The corresponding intra-observer technical error (% reliability) of the measurements was 95%.
Cardiometabolic variables
Blood pressure was obtained using an automatic monitor (Omrom® HEM 705 CP, Health-care Co, Kyoto, Japan) following a previously described protocol for the European Heart Society (on the right arm with participants in a supine position and subjects rested quietly for 10 min in a comfortable chair). The mean arterial blood pressure (MAP) was calculated as: (2 x diastolic)+systolic]/3 [18].
Blood samples (40 μL) were drawn between 07:00 and 09:00, after 10–12 h of fasting (11.2 h on average). Hematological entities, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG), were measured by using an automated biochemical analyzer Cardiocheck® equipment (Mexglobal SA, Parsippany, NJ, USA). Low-density lipoprotein-cholesterol (LDL-C) was calculated using Friedewald’s Formula when triglyceride values were ≤ 400 mg/dL [19]. Glucose was measured using Accu-Chek® Aviva Plus system (Roche®, Mexglobal SA, Terrytown, NY, USA).
MetS was defined in accordance with the updated harmonized criteria of the International Diabetes Federation/National Heart, Lung and Blood Institute/American Heart Association (IDF/NHLBI/AHA-2009) [20]. Participants were considered to have MetS if they showed three or more of the following: (1) central obesity in WC (♀ ≥ 80 cm and ♂ ≥90 cm); (2) TG (≥150 g/dL); (3) low HDL-C (♀ < 50 mg/dL and ♂ < 40 mg/dL); (4) high blood pressure (systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 85 mmHg); (5) high TG (≥100 mg/dL). The latest (IDF/NHLBI/AHA-2009) consensus stated that WC was measured according to Country/Specific values which, for Latin Americans, were set to be equal to South Asian parameters, specifically WC ≥90 cm for males and ≥ 80 cm for women [20].
Modes of commuting to/from the university
The mode of commuting to and from school was measured using a questionnaire developed and validated in Spanish by the University of Granada (Spain) through the project “PACO: pedalea y anda al colegio” (http://profith.ugr.es/paco). This questionnaire has been validated in a Spanish population [21, 22]. The usual mode of commuting to and from campus was categorized into “active” commuting (active walker to campus) and non-active commuting (non/infrequent active walker to campus: car, motorcycle, or bus). Although this particular question for assessing commuting to/from university has not been formally validated, it is highly similar to other 1-item questionnaires on a students’ commuting to university that have been demonstrated to be acceptably reliable and valid in this age group [23]. For commuting distance from home to their university participants could choose any of the following options: 0 to 2 km, 2 to 5 km, and > 5 km. In our sample, the results of analysis internal consistency reveal that Colombian version of the project “PACO: pedalea y anda al colegio” scale have adequate to good values (commuting to/from university and barriers domain α Cronbach = 0.761, and total commuting distance from home to their university or vice versa domain α Cronbach = 0.995). Finally, due to a limited number of students who cycle to the university (n = 9), we have removed these individuals from the study population.
Lifestyle covariates
A validated questionnaire, the “FANTASTIC” lifestyle, was used to collect comprehensive information about substance use via a personal interview with participants. Alcohol consumption (No or 1 to 10 cigarettes per day), smoking status (No or 1 to 9 times per week), and physical activity levels (5 times a week for > 30 min or ≥ 150 min per week were categorized as “physically active”) has been previously described by Ramírez-Vélez et al. [24].
The seven-day recall dietary assessment tool was used to complete the MetDiet. As suggested by Thanapoulou et al. [25], the total score was divided into two categories of Mediterranean diet quality: ≤8 points = poor diet quality and ≥ 9 points = good diet quality (optimal Mediterranean diet style). Participants who had ≥9 points were categorized as having an ideal healthy diet, whereas those with 8 points or less were classified as having a non-ideal diet. Personal, family history of CVD, and medication use was used as covariables.
Ethics statement
The study was approved by the Research Ethics Committee at the Universidad Manuela Beltrán (UMB Code N° 01–1802-2013) in according the Helsinki Declaration Accord (World Medical Association for Human Subjects, 2000). Informed consent was obtained from each participant before being enrolled in the study.
Statistical analysis
Anthropometric and body composition components and cardiometabolic risk factors of the study sample are presented as the mean (SD) or relative frequency, n (%). The normality of the variables was verified using histograms and Q-Q plots. Differences on cardiometabolic parameters between walking and non-walking groups were assessed using an ANOVA or X2 test. Finally, to examine the OR and 95% CI of having an unhealthy profile (MetS components), we used multinomial logistic regression by sex. The exposure variable was categorized into AC (active walker to campus) and non-AC (non/infrequent active walker to campus: car, motorcycle, or bus) to and from the university on a typical day. These analyses were adjusted by age, BMI (only when obesity or waist circumference were not included as dependent variable), PA, alcohol and tobacco intake, diet, and distance and were performed using SPSS version 21.0 for Windows (IBM, Armonk, New York). Statistical significance was established at p < 0.05.