Lifestyle patterns and dysglycaemic risk in urban Sri Lankan women

摘要

Specific dietary patterns are associated with the risk of chronic disease. An in-depth understanding more reflective of lifestyle would be possible when assessing the synergistic effects of both diet and physical activity in pattern analysis. In the present study, we examined the biochemical markers of dysglycaemia and cardiometabolic risk in relation to lifestyle patterns using principal component analysis (PCA). Urban women (n 2800) aged 30-45 years were screened for dysglycaemia using cluster sampling from the Colombo Municipal Council area. All the 272 dysglycaemic women detected through screening and 345 randomly selected normoglycaemic women were enrolled. The International Physical Activity Questionnaire and a quantitative FFQ were used to assess physical activity and diet, respectively. Anthropometric measurements, bioelectrical impedance analysis and biochemical estimations were carried out. Lifestyle patterns were identified based on dietary and physical activity data using exploratory factor analysis. PCA was used for the extraction of factors. A total of three lifestyle patterns were identified. Women who were predominantly physically inactive and consumed snacks and dairy products had the greatest cardiometabolic risk, with a higher likelihood of having unfavourable obesity indices (increased waist circumference, fat mass percentage and BMI and decreased fat-free mass percentage), glycaemic indices (increased glycosylated Hb (HbA1c) and fasting blood sugar concentrations) and lipid profile (increased total cholesterol/TAG and decreased HDL-cholesterol concentrations) and increased high-sensitivity C-reactive protein concentrations. For the first time, we report lifestyle patterns and demonstrate the synergistic effects of physical activity/inactivity and diet and their relative association with cardiometabolic risk in urban women. Lifestyle pattern analysis greatly increases our understanding of high-risk behaviours occurring within real-life complexities