Dr. Matus-Castillo, Carlos

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: 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.