Anthropometric parameters, lower limb functionality and quality of life after high-intensity interval training in healthy young people versus older adults / Parámetros antropométricos, funcionalidad de miembros inferiores y calidad de vida posterior al entrenamiento interválico de alta intensidad en jóvenes versus personas mayores

SUMMARY: The aim of this study was to determine the effects of High-intensity interval training (HIIT) on the quality of life in healthy young people (YNG) and older adults (OLD)and its correlation with physical health status (anthropometric parameters and lower limb functionality) YNG (21 ? 2 years, BMI 26.37 ? 2.69 n = 12) and OLD (67 ? 5 years, BMI 27.16 ? 3.04 n = 12) groups underwent 12weeks of HIIT. Before and after the HIIT, anthropometric assessments, lower limb functionality tests, and SF-36 quality-of-life questionnaire were performed. There were no significant changes in the SF-36 dimensions (P>0.05). After HIIT, there were improvement percentage changes in Mental Component Summary (MCS) (YNG, +8.51 ? 25.80 % vs. OLD, +2.30 ? 9.05 %) and in Physical Component Summary (PCS) (YNG, +2.66 ? 20.54 % vs. OLD, +4.34 ? 22.71 %). Negative correlations were observed between body mass index (BMI) with PCS (R=-0.570, P=0.009) and with MCS (R=-0.649, P=0.002) in OLD as well as between MCS and waist circumference (R=-0.557, P?0.001) in both groups. Also, correlations were observed between PCS and the sit-to-stand test (R=-0.424, P=0.006) in both groups and gait speed (R=0.458, P=0.042) only in YNG. HIIT promotes positive percentage changes in quality of life, with YNG showing better results in PCS and OLD in MCS. Quality of life and physical health status were correlated in both groups.

RESUMEN: Determinar los efectos del entrenamiento interválico de alta intensidad (HIIT) sobre la calidad de vida en jóvenes sanos (YNG) y personas mayores (OLD) y su correlación con el estado de salud física (parámetros antropométricos y funcionalidad de miembros inferiores). Ambos grupos, YNG (21 ? 2 años, IMC 26,37 ? 2,69 n = 12) y OLD (67 ? 5 años, IMC 27,16 ? 3,04 n = 12) realizaron 12 semanas de HIIT. Antes y después del HIIT, se realizaron evaluaciones antropométricas, pruebas de funcionalidad de miembros inferiores y cuestionario de calidad de vida SF-36. No hubo cambios significativos en las dimensiones del SF-36 (P >0,05). Después del HIIT, hubo cambios porcentuales de mejora en el componente sumario mental (MCS) (YNG, +8.51 ? 25.80 % vs. OLD, +2.30 ? 9.05 %) y el componente sumario física (PCS) (YNG, +2,66 ? 20,54 % vs. OLD, +2,30 ? 9,05 %), correspondientes a la calidad de vida. Se observaron correlaciones negativas entre el índice de masa corporal (IMC) con PCS (R=-0,570; P=0,009) y con MCS (R=0,649; P=0,002) en OLD, así como entre MCS y circunferencia de cintura (R = - 0,557, P?0,001) en ambos grupos. Además, se observaron correlaciones entre PCS y la prueba de sentarse y levantarse (R = -0,424; P = 0,006) en ambos grupos y la velocidad de la marcha (R = 0,458; P = 0,042) solo en YNG. HIIT promueve cambios porcentuales positivos en la calidad de vida, con YNG mostrando mejores resultados en PCS y OLD en MCS. La calidad de vida y el estado de salud física se correlacionaron en ambos grupos.

Alta prevalencia de dislipidemias y riesgo aterogénico en una población infanto-juvenil / High prevalence of dyslipidemia and high atherogenic index of plasma in children and adolescents

Background: Dyslipidemias in childhood increase the risk of cardiovascular events in adult life. Aim: To evaluate the prevalence of dyslipidemia and risk of atherogenicity based in the atherogenic index of plasma (AIP) in a sample of school children and adolescents. Material and Methods: Cross-sectional study of 208 children aged 10.4 ± 1.0 years (107 women). Demographic data were obtained, and a clinical evaluation was conducted, including pubertal development according to Tanner and anthropometric parameters. A fasting blood sample was obtained to measure total cholesterol (CT), HDL cholesterol (cHDL) and triglycerides (TG), glucose and insulin. LDL cholesterol (cLDL), Non-HDL cholesterol and the indices CT/cHDL, cLDL/cHDL and AIP (log[TG/cHDL]) were calculated. Risk categories according to AIP for the pediatric population were also determined (low: AIP < 0.11, intermediate: AIP 0.11-0.21, high: AIP > 0.21). Results: Thirty eight percent of participants had dyslipidemia, without differences by gender and pubertal development. The frequency of dyslipidemia was significantly higher in children with obesity (54%, p < 0.01) and a waist circumference over percentile 90 (61%; p < 0.01). The later conditions had also higher CT/cHDL, cLDL/cHDL and AIP. According to AIP, 54% of children had a high atherogenicity risk along with alterations in anthropometric parameters and insulin resistance. All anthropometric and insulin resistance parameters were significantly correlated with the AIP. Conclusions: There is a high prevalence of dyslipidemia in the studied population, which is associated with an increased cardiometabolic risk. The indices of atherogenicity and particularly AIP are correlated with nutritional status, abdominal obesity and parameters of insulin resistance.

Estrés psicológico y síndrome metabólico / Longitudinal association between chronic psychological stress and metabolic syndrome

Background: Psychological stress and depressive symptoms are variables associated with metabolic syndrome (MetS). Aim: To determine the longitudinal association between psychological stress, depressive symptoms and MetS, and whether these variables predict MetS and its component trajectories. Material and Methods: Four hundred and twenty-three participants aged 44 ± 9 years (59% women), free of cardiovascular disease at baseline were enrolled into the Chilean study of psychological stress, obesity and MetS. Participants were followed-up for three years (three waves). Each year, they completed psychological questionnaires, anthropometric variables were measured, and blood samples were obtained. Results: Hierarchical linear regression showed that chronic psychological stress at baseline predicted the total number of MetS components (MetS score) during the third assessment wave (β = 0.147; p < 0.01). Growth curve modeling allowed to determine that participants who scored +1 standard deviation (SD) at baseline over the mean in psychological stress (βchronic stress = 0.903; 95% confidence intervals (CI) = 0.065; 1.741), and depressive symptoms (βdepressive symptoms = 2.482; 95% CI = 0.040; 4.923) had a higher waist circumference trajectory, as compared to those scoring −1 SD above the mean. Conclusions: Chronic psychological stress is longitudinally associated with the MetS score. Further, psychological stress and depressive symptoms at baseline predicted elevated MetS score trajectories, and a highest waist circumference.