Dr. Poblete-Valderrama, Felipe

Los factores del estilo de vida podrían promover un envejecimiento saludable. Objetivo: Investigar la asociación entre la actividad física (PA), comportamiento sedentario y deterioro cognitivo en chilenos mayores adultos. Material y Métodos: Se incluyeron 1.390 participantes de la Encuesta Nacional de Salud (2009-2010). El Mini-mental El examen estatal se utilizó para diagnosticar el deterioro cognitivo. La actividad física y el comportamiento sedentario fueron evaluados con Cuestionario Global de Actividad Física (GPAQ). Regresión Logística se realizó para investigar las asociaciones. Resultados: Comparados con adultos mayores con niveles más bajos de PA (< 48 min/día), aquellos con niveles medios (48-248 min/día) y más altos (>248 min/día) de PA tuvieron menores probabilidades de deterioro cognitivo (Odds ratio (OR): 0,57 [95% IC: 0,32; 0,83], p < 0,01, respectivamente). Los participantes que informaron que pasaban más de 8 horas al día sentados tenían una alta probabilidad de deterioro cognitivo en comparación con aquellos que pasaban < 4 horas/ día (OR: 3,70 [IC 95%: 1,37; 6,03], p = 0,01). Conclusiones: Tanto la PA como el comportamiento sedentario se asociaron independientemente con el deterioro cognitivo independiente de los principales factores de confusión en adultos mayores chilenos.

Background: A higher educational level is associated with healthier lifestyles. Aim: To assess the association between the level of compliance with physical activity recommendations and years of formal education in Chilean adults. Material and Methods: Analysis include 6,174 participants from the National Health Survey 2016-2017. Physical activity levels were assessed through the Global Physical Questionnaire (GPAQ v2). Physical inactivity was defined as < 600 MET/minute/week. Results: Among subjects without education, 44% and 27% of women and men respectively, were physically inactive. Among women and men with the highest number of years of education (> 16) the figures for physical inactivity were 27% and 15% respectively. The odds for not meeting the physical activity recommendations was 2.3 [95% confidence intervals (CI): 1.57; 3.38] and 3.9 [95% CI: 2.27; 6.95] in women and men without any formal education respectively, as compared with those who reported 12 years of education. Women and men who reported a high level of education ≥ (16 years) did not show significant differences compared to the reference group. Conclusions: People with low levels of education are were likely to be physically inactive.

Background: Walking speed is a strong predictor of non-communicable diseases and mortality. Aim: To investigate the association of self-reported walking pace with adiposity, metabolic and cardiovascular markers in the Chilean population. Material and Methods: Analysis of data from 5,077 participants of the 2009-2010 National Health Survey (ENS 2009-2010). Walking speed was self-reported as average or slow pace. Body mass index (BMI), waist circumference (WC), blood pressure, blood glucose, glycosylated hemoglobin and lipid profile were the outcome. Results: In Chile, 11% (95% confidence intervals [CI]: 10.0; 12.7) of the population reported a slow walking pace. Compared with average walking people, those reporting a slow pace had a higher body weight (difference (∆) 5.65 kg [95% CI: 3.22; 8.09], p < 0.01), BMI (D 2.48 kg/m 2 [95% CI: 1.53; 3.44], p < 0.01), WC (D 6.23 cm [95% CI: 4.12; 8.34], p < 0.01), serum triglycerides (D 30,9 mg/dl [95% CI: 5,31; 57,5], p = 0.018), and lower HDL cholesterol (D -2.32 mg/dl [95% CI: -4,24; -0,34], p = 0.022). Those reporting a slow pace had also a higher odd of being obese (odds ratio (OR): 2.46 [95% CI: 1.82; 3.33], p < 0.01), being diabetic (OR: 1.54 [95% CI: 1.02; 2.40], p = 0.018) and having metabolic syndrome (OR: 2.03 [95% CI: 1.30; 3.18], p = 0.002). Conclusions: In Chilean adults, slow walking pace is associated with and unfavorable adiposity and lipid profile, including a higher probability of being obese, diabetic and having metabolic syndrome.

Background: The Chilean population reports high levels of physical inactivity. The relationship between income level, physical activity (PA) and sedentary behaviors is not well known. Aim: To describe the levels of PA and sedentary time, according to income levels in the Chilean population. Material and Methods: Analysis of data from the Chilean National Health Survey 2016-2017, which included 5,130 participants (52.9% women). The levels of PA and sedentary time were measured by the Global Physical Activity Questionnaire. Income levels were established according to the self-reported income per capita of the households and presented as quintiles. PA levels according to income levels were estimated by linear regression analyses. Results: Transport-related PA was higher in the lowest income quintiles (p = 0.039). There were no trends for income levels and PA domains including moderate, vigorous, total, occupational and leisure PA. The prevalence of leisure and occupational physical inactivities were higher in the lowest quintiles of income. Sitting time was higher in the higher income levels (p < 0.01). Conclusions: People in the lowest quintile for income spent more time in transport-related PA and less time sitting. However, physical inactivity prevalence during leisure and work time were higher in people with lower income.

Background: Cardiorespiratory fitness is a strong predictor of mortality and chronic diseases. However, its estimation is costly and time consuming which may limit it broad use in population-based studies. Aim: To estimate the cardiorespiratory fitness of the Chilean population by using equations and to characterize fitness levels of the Chilean population by sociodemographic factors. Material and Methods: This cross-sectional study included 5,958 adults from the Chilean Health Survey conducted between 2016 and 2017. Cardiorespiratory fitness was estimated from sex-specific equations for men and women and expressed as METs (Energy Metabolic Equivalent). Fitness levels were characterized by sociodemographics factors (age, sex, education, income and area of residency). Results: Fitness levels were higher in men (9.01 METs) than in women (6.76 METs) and in average decrease by 0.59 and 0.34 METs per each year increment in age for men and women, respectively. Fitness levels were 12.7 METs and 7.8 METs for 20-year-old men and women, respectively. However, fitness levels decreased to 7.8 METs and 4.3 METs in 90-year-old men and women, respectively. Fitness levels were also higher in individuals living in urban setting, those with higher education or income levels and lean individuals. Conclusions: This study reports fitness levels in a nationally representative sample of Chile. Fitness levels were higher in men than women however, its decline with age was more pronounce in men than women.