Dra. Troncoso-Pantoja, Claudia

There has not been much study of risk profiles in older people according to different levels of practice in physical activity. For this reason, the aim of this research was to evaluate whether the elements that influence the quality of life and factors such as gender and education can predict the level of physical activity in the physically active elderly population. The Fernández–Ballesteros quality of life questionnaire and the WHO International Physical Activity Questionnaire were applied to a sample of 397 people with a mean age of 69.65 years (SD = 4.71). The results revealed the following predictive factors of practicing a low level of physical activity (p < 0.05): being a woman; having a low educational level; and low scores in activity and leisure and in functional skills. In conclusion, gender, education, functional skills, activity and leisure, and health are elements of quality of life that predict the level of physical activity performed by the elderly, where it is necessary to use leisure activities (visiting friends, playing games, running errands) as an indirect way to increase participation in physical activity.

The purpose of this study was to investigate healthy lifestyle behaviours across age categories in the older population in Chile. Data from 1390 older adults (≥60 years), in the 2009–2010 Chilean National Health Survey were analyzed. We derived the following age categories: 60–65, 66–70, 71–75, 76–80 and >80 years. The associations between age and compliance with healthy lifestyle behaviours (smoking, sitting time, physical activity, sleep duration and intake of salt, alcohol, fruit and vegetables) were investigated using logistic regression. The probability of meeting the guidelines for alcohol intake (OR trend: 1.35 [95% CI: 1.11; 1.64], p = 0.001) and smoking (OR trend: 1.23 [95% CI: 1.13; 1.33], p < 0.0001) increased with age, whereas spending <4 h per day sitting time or engaging in at least 150 min of physical activity per week or sleep on average between 7 and 9 h per day were less likely to be met with increasing age (OR trend: 0.77 [95% CI: 0.71; 0.83], p < 0.000; OR trend: 0.73 [95% CI: 0.67; 0.79], p < 0.0001, and OR trend: 0.89 [95% CI: 0.82; 0.96], p = 0.002, respectively). No significant trend across age categories was observed for fruit and vegetables, and salt intake. The probability of meeting at least 3 out of 7 healthy lifestyle behaviours across the age categories was also lower in older age categories compared to those aged 60 to 65 years. Overall, in older adults the probability of having the healthy lifestyle behaviours of physical activity, sitting time and sleeping behaviours was low but not for smoking or alcohol consumption. With an increasingly ageing population, these findings could inform stakeholders on which lifestyle behaviours could be targeted in the older adults and therefore which interventions should take place to promote healthy ageing.