Dra. Mardones-Leiva, Lorena

Background: Fat-mass-associated-gene (FTO) is associated with higher energy intake and specific food preferences. Aim: To investigate the association of the FTO genotype with energy intake, macronutrient and alcohol consumption. Material and Methods: Four hundred and nine participants of the GENADIO (Genes, Environment, Diabetes and Obesity) study were included. Energy intake, macronutrient and alcohol consumption were the outcomes of interest. The association of FTO (rs9939609) genotype with these outcomes was investigated using linear regression analyses, adjusting for confounding variables. Results: After adjusting for socio-demographic factors, being a carrier of the risk allele for the FTO gene was associated with a higher energy intake (173 kcal per each extra copy of the risk variant [95% confidence intervals (CI): 45; 301], (P = 0.008). After adjusting for lifestyle factors and body mass index, the association was slightly attenuated but remained significant (144 kcal [95% CI: 14; 274], p = 0.030). Conclusions: The FTO genotype is associated with a higher energy intake. (Rev Med Chile 2018; 146: 1252-1260)

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.