Markers of endothelial damage in patients with chronic kidney disease on hemodialysis

Patients with Stage 5 chronic kidney disease who are on hemodialysis (HD) remain in a chronic inflammatory state, characterized by the accumulation of uremic toxins that induce endothelial damage and cardiovascular disease (CVD). Our aim was to examine microvesicles (MVs), monocyte subpopulations, and angiopoietins (Ang) to identify prognostic markers in HD patients with or without diabetes mellitus (DM). A total of 160 prevalent HD patients from 10 centers across Spain were obtained from the Biobank of the Nephrology Renal Network (Madrid, Spain): 80 patients with DM and 80 patients without DM who were matched for clinical and demographic criteria. MVs from plasma and several monocyte subpopulations (CD142+/CD16+, CD14+/CD162+) were analyzed by flow cytometry, and the plasma concentrations of Ang1 and Ang2 were quantified by ELISA. Data on CVD were gathered over the 5.5 yr after these samples were obtained. MV level, monocyte subpopulations (CD14+/CD162+ and CD142+/CD16+), and Ang2-to-Ang1 ratios increased in HD patients with DM compared with non-DM patients. Moreover, MV level above the median (264 MVs/µl) was associated independently with greater mortality. MVs, monocyte subpopulations, and Ang2-to-Ang1 ratio can be used as predictors for CVD. In addition, MV level has a potential predictive value in the prevention of CVD in HD patients. These parameters undergo more extensive changes in patients with DM.Support for this work was provided by Plan Nacional de IDi Proyectos de Investigación en Salud of Instituto de Salud Carlos III (ISCIII)–Subdirección General de Evaluación, Fondos de desarrollo regional (FEDER; PI11/01536, PI12/01489, PI14/00806, PI15/01785); Junta de Andalucía grants (P010-CTS-6337, P11-CTS-7352); and Fundación Nefrológica. P. Buendía, A. Carmona, and C. Luna-Ruiz are fellows from Consejería de Innovacion, Ciencia y Empresa, Junta de Andalucía

Attitudes and beliefs about obesity among healthcare professionals in Spain : European Congress on Obesity (ECO Online 2021). 28th Congress, 10-13 May, 2021. ABSTRACTS

Introduction: Excess use of digital devices and time spent with screens might negatively influence several lifestyle behaviors in adolescents which in turn can cumulatively increase the risk of obesity(1-3). A better understanding of these associations will help to focus interventions to improve present and future health outcomes of adolescents. We conducted this study to examine the associations of screen time with eating habits, physical activity levels, sleep patterns, and adiposity measures in a sample of 10-17 years old adolescents in Mumbai, India. Methods: Cross-sectional study design. Adolescents (n=772) were selected from six public and six private schools and two junior colleges using a stratified random sampling method. Screen time, physical activity levels, and sleep patterns were assessed using a researcher-designed screen time questionnaire, Physical Activity Questionnaire for Children and Adolescents (PAQ-C/-A), and Pittsburg Sleep Quality Index (PSQI) respectively. Two non-consecutive 24h dietrecalls and a 35-item validated food frequency questionnaire determined the eating habits and energy and nutrient intakes. Body mass index (BMI) z scores > 1 and waist to height ratio (WHtR) > 0.5 were defined as measures of adiposity. Multivariate logistic regression models predicted the associations between screen time and lifestyle factors, stratified by sex. Results: The mean age of adolescents was 14.6 (2.4) years, 28.4% were overweight, 47.8% had WHtR > 0.5 and 76.1% reported their daily screen time to be > 2 hours. The PAQ scores were significantly higher in boys (p 0.032) and the mean sleep duration declined with age (p 2h/d was associated with unhealthy snack consumption (OR = 1.34, 95% CI = 1.03-1.72), lower fruit consumption (OR = 1.8, 95% CI = 1.54-2.01) and higher mean carbohydrate intakes (OR = 1.51, 95% CI = 1.44-1.67). The odds of insufficient sleep duration (2h/d and an overall screen time > 4 h/d predicted lower mean PAQ summary scores (OR = 4.1, 95% CI = 3.78-4.24). Attending private schools (OR = 1.63 (95% CI = 1.04-1.99), watching television while eating > 2h/d (OR = 1.34 (95% CI = 1.03-1.72) and having higher sleep related daytime dysfunction scores (OR = 1.25 (95% CI = 1.13-2.09) predicted higher WHtR. Additionally, being overweight was significantly associated with higher screen addiction scores (p < 0.001). Conclusion: In adolescents, excess screen time predicted unhealthy eating habits, reduced sleep duration, and greater adiposity. Results support a need to develop interventions targeted at reducing screen time to leverage better lifestyle behaviors and lower obesity risk in adolescents