The effect of prior walking on coronary heart disease risk markers in South Asian and European men.

Purpose: Heart disease risk is elevated in South Asians possibly due to impaired postprandial metabolism. Running has been shown to induce greater reductions in postprandial lipaemia in South Asian than European men but the effect of walking in South Asians is unknown. Methods: Fifteen South Asian and 14 White European men aged 19-30 years completed two, 2-d trials in a randomised crossover design. On day 1, participants rested (control) or walked for 60 min at approximately 50% maximum oxygen uptake (exercise). On day 2, participants rested and consumed two high fat meals over a 9h period during which 14 venous blood samples were collected. Results: South Asians exhibited higher postprandial triacylglycerol (geometric mean (95% confidence interval) 2.29(1.82 to 2.89) vs. 1.54(1.21 to 1.96) mmol·L-1·hr-1), glucose (5.49(5.21 to 5.79) vs. 5.05(4.78 to 5.33) mmol·L-1·hr-1), insulin (32.9(25.7 to 42.1) vs. 18.3(14.2 to 23.7) µU·mL-1·hr-1) and interleukin-6 (2.44(1.61 to 3.67) vs. 1.04(0.68 to 1.59) pg·mL-1·hr-1) than Europeans (all ES ≥ 0.72, P≤0.03). Between-group differences in triacylglycerol, glucose and insulin were not significant after controlling for age and percentage body fat. Walking reduced postprandial triacylglycerol (1.79(1.52 to 2.12) vs. 1.97(1.67 to 2.33) mmol·L-1·hr-1) and insulin (21.0(17.0 to 26.0) vs. 28.7(23.2 to 35.4) µU·mL-1·hr-1) (all ES ≥ 0.23. P≤0.01), but group differences were not significant. Conclusions: Healthy South Asians exhibited impaired postprandial metabolism compared with White Europeans, but these differences were diminished after controlling for potential confounders. The small-moderate reduction in postprandial triacylglycerol and insulin after brisk walking was not different between the ethnicities

Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

Extent: 11p.OBJECTIVE: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk’ and ‘case’ stages of the metabolic disease continuum. DESIGN: Cross-sectional study of a random population sample. PARTICIPANTS: A total of 718 community-dwelling adults (57% female), aged 18--92 years from a regional South Australian city. MEASUREMENTS: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. RESULTS: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases’), otherwise were classified as the ‘at-risk’ population. In both ‘at-risk’ and ‘cases’, four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases’, whereas all phenotypes were inter-correlated in the ‘at-risk’. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases’ and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk’. CONCLUSION: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction interventions. Prospective studies are required to examine this hypothesis.MT Haren, G Misan, JF Grant, JD Buckley, PRC Howe, AW Taylor, J Newbury and RA McDermot

Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

Extent: 11p.OBJECTIVE: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk’ and ‘case’ stages of the metabolic disease continuum. DESIGN: Cross-sectional study of a random population sample. PARTICIPANTS: A total of 718 community-dwelling adults (57% female), aged 18--92 years from a regional South Australian city. MEASUREMENTS: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. RESULTS: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases’), otherwise were classified as the ‘at-risk’ population. In both ‘at-risk’ and ‘cases’, four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases’, whereas all phenotypes were inter-correlated in the ‘at-risk’. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases’ and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk’. CONCLUSION: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction interventions. Prospective studies are required to examine this hypothesis.MT Haren, G Misan, JF Grant, JD Buckley, PRC Howe, AW Taylor, J Newbury and RA McDermot

Dyslipidemia and Cardiovascular Risk in Obesity

Description of major dyslipidemias in obese people, their underlying pathophysiological mechanisms and the therapeutic approache