RESUMEN
(1) Background: Due to the pandemic caused by COVID-19, mandatory confinement was declared, which generated a decrease in the practice of physical activity (PA). Based on this problem, it was proposed to study the associations between PA in relation to depressive symptoms, quality of sleep, and the quality of life of middle-aged people who work in the university context during compulsory confinement as a result of COVID-19. (2) Methods: A total of 336 middle-aged people (48 ± 6.67) participated in this analytical cross-sectional study. The variable levels of PA, quality of sleep, symptoms of depression, and quality of life were measured with the International Physical Activity Questionary (IPAQ), the Pittsburgh Sleep Quality Index (PSQI), the Zung Self-Rating Depression Scale (ZSDS), and the SF-12v2 questionnaire, respectively. (3) Results: A logistic regression model was used to analyze the relationships between the level of PA and depressive symptoms (OR = 2.053), total sleep duration (OR = 0.495), sleep disturbances (OR = 2.414), quality of sleep (OR = 2.471), use of sleep medication (OR = 0.348), daytime dysfunction (OR = 1.809), general health (OR = 0.949), and physical functioning (OR = 0.987). (4) Conclusions: In middle-aged people, during compulsory confinement, being insufficiently active is a risk for depressive symptoms and disturbances in sleep quality.
RESUMEN
During the COVID-19 pandemic, psychological disorders have been documented in the population, and their exacerbation in vulnerable populations such as those with Cardiometabolic Diseases (CD) might challenge health systems. This study determined psychological factors associated with CD in Colombian adults during the COVID-19 pandemic. For this purpose, 284 persons were evaluated, 142 without CD and 142 with CD. Sociodemographic data were collected, and the International Physical Activity Questionnaire (IPAQ), the SF-12v2, the Pittsburgh Sleep Quality Index (PSQI) and the Zung Self-Rating Depression Scale (ZSDS), which were integrated into an online form, were used. Through a simple and multiple logistic regression model, it was shown that CD was associated with low sleeping quality (LSQ) (OR = 3.51) and with depressive symptoms (DS) (OR = 1.98). In addition, in the group with CD, the presence of DS was related to BMI (OR = 2.45), and LSQ was related to living with persons at risk for COVID-19 (OR = 3.64) and BMI (OR = 5.88). In conclusion, this study showed that people with CD have a higher chance of presenting DS and LSQ. Furthermore, living with people at risk for COVID-19 was related to the presence of LSQ.
RESUMEN
PURPOSE: Obesity and high body fat are related to diabetes and metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of the present study was to compare body adiposity indexes (BAIs) and to assess their various cutoff values for the prediction of MetS in university students from Colombia. METHODS: A cross-sectional study was conducted on 886 volunteers (51.9% woman; age mean 21.4 years). Anthropometric characteristics (height, weight, waist circumference [WC], and hip circumference [HC]) were measured, and body composition was assessed by bioelectrical impedance analysis. MetS was defined as including ≥3 of the metabolic abnormalities (WC, high-density lipoprotein cholesterol [HDL-C], triglycerides, fasting glucose, and systolic and diastolic blood pressure [BP]) in the definition provided by the IDF. The BAIs (i.e., BAI-HC [BAI], BAI-WC [BAI-w], and [BAI-p]) were calculated from formulas taking into account, height, weight, and WC, and for the visceral adiposity indexes, a formula, including WC, HDL-C, and triglycerides, was used. RESULTS: The overall prevalence of MetS was 5.9%, higher in men than in women. The most prevalent components were low HDL-C, high triglyceride levels, WC, and BP levels. The receiver operating characteristic curves analysis showed that BAI, BAI-w, and BAI-p could be useful tools to predict MetS in this population. CONCLUSION: For women, the optimal MetS threshold was found to be 30.34 (area under curve [AUC] = 0.720-0.863), 19.10 (AUC = 0.799-0.925), and 29.68 (AUC = 0.779-0.901), for BAI, BAI-w, and BAI-p, respectively. For men, the optimal MetS threshold was found to be 27.83 (AUC = 0.726-0.873), 21.48 (AUC = 0.755-0.906), and 26.18 (AUC = 0.766-0.894), for BAI, BAI-w, and BAI-p, respectively. The three indexes can be useful tools to predict MetS according to the IDF criteria in university students from Colombia. Data on larger samples are needed.