Dra. Troncoso-Pantoja, Claudia

Background: Housewives represent a important proportion of the Chilean population. However, there is limited evidence about their lifestyles. Aim: To characterize lifestyles and determine the level of compliance with healthy lifestyles guidelines of housewives in Chile. Material and Methods: Housewives from the 2009-2010 National Health Survey were included. The variables studied included levels of physical activity (PA), sedentary behavior, diet, hours of sleep and smoking. Compliance with healthy lifestyle behaviors was evaluated through logistic regression, granting a value of 1 for compliance and 0 for non-compliance. A healthy lifestyle was defined as meeting at least four healthy behaviors. Results: Housewives aged > 55 years had a higher BMI and waist circumference compared to those aged < 40 years. Housewives were also more likely to report moderate alcohol consumption and were more likely to meet a healthier lifestyle score (Odds ratio = 1.52 [95% confidence intervals: 1.09 to 2.11], p = 0.013). No significant age trends were observed for other lifestyle behaviors. Conclusions: Housewives had high levels of central obesity, excess body weight and high levels of salt intake but low alcohol intake. Their healthy lifestyles behaviors increased along with increasing age.

Background: Healthy lifestyles are associated with a better metabolic and cardiovascular health profile. Aim: To investigate the association between a lifestyle score and cardiovascular risk in Chilean adults. Material and Methods: A healthy lifestyle score was derived for 2,774 participants in the Chilean National Health Survey 2009-2010 and based on seven modifiable behaviors (salt intake, fruit and vegetable intake, alcohol consumption, sleep duration, smoking, physical activity and sedentary behaviors). A high score represented a healthier lifestyle whereas a low score represents an unhealthy lifestyle. The association between the lifestyle score and cardiovascular risk factors (obesity, hypertension, diabetes, dyslipidemia and metabolic syndrome), was explored using logistic regression models. Results: One quartile increment in the healthy lifestyle score was associated with a lower risk for obesity (Odds ratio (OR): 0.82 [95% confidence intervals (CI): 0.75 to 0.90], p < 0.01), central obesity (OR: 0.88 [95% CI: 0.81 to 0.96], p < 0.01), diabetes (OR: 0.84 [95% CI: 0.75 to 0.95], p < 0.04) and dyslipidemia (OR: 0.90 [95% CI: 0.83 to 0.98], p = 0.01). These results were independent of major confounding factors. Conclusions: The adherence to a healthy lifestyle is associated with lower cardiovascular risk.

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.