TY - JOUR
T1 - Proximal correlates of metabolic phenotypes during 'at-risk' and 'case' stages of the metabolic disease continuum
AU - Haren, M. T.
AU - Misan, G.
AU - Grant, J. F.
AU - Buckley, J. D.
AU - Howe, P. R.C.
AU - Taylor, A. W.
AU - Newbury, J.
AU - McDermott, R. A.
N1 - Funding Information:
We acknowledge the continued support, guidance and perspective of the WISH Community Advisory Group and all the participants who have given their time to the study. The clinic staff Kate Warren, Tracey Patterson, Deb Misan, Leanne Gibbons, Chris Creber, Corey Beinke-Heath and Helen Mills and administrative staff Stephanie Coombes and Hayley-Maree Ewbank. We acknowledge also the participant recruitment efforts of Helen Pickhaver, Olivia Grove-Jones, Sarah Murray, Mick Jong, Delys and Wayne Champion. We gratefully acknowledge the contribution of the North West Adelaide Health Study team in their intellectual input into the processes, protocols and measurement methods included in this study and for the training of staff. We are particularly grateful to Janet Grant and Alicia Montgomerie. The WISH investigators thank Professor Graham Giles of the Cancer Epidemiology Centre of the Cancer Council Victoria, for permission to use the Dietary Questionnaire for Epidemiological Studies (Versions 3 and 3.1): The Cancer Council Victoria, 2007. We acknowledge the Premiers Science Research Fund as the public source of funds for this study through the South Australian Population Health Intergenerational Research (SAPHIRe) collaborative. We acknowledge our collaboration partners, the North West Adelaide Health Study, Florey Adelaide Male Ageing Study and the Australian Longitudinal Study of Ageing. MTH is supported by a Post-doctoral Training Fellowship (Public Health) from the National Health and Medical Research Council (NHMRC) of Australia (no. 511345). RAM is supported by a NHMRC Practitioner Fellowship.
PY - 2012/1
Y1 - 2012/1
N2 - 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.
AB - 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.
KW - Abdominal obesity
KW - Metabolic trait expression
KW - Principal components analysis
KW - Sleep disordered breathing symptoms
UR - http://www.scopus.com/inward/record.url?scp=84950170718&partnerID=8YFLogxK
U2 - 10.1038/nutd.2011.20
DO - 10.1038/nutd.2011.20
M3 - Article
AN - SCOPUS:84950170718
SN - 2044-4052
VL - 2
JO - Nutrition and Diabetes
JF - Nutrition and Diabetes
IS - JANUARY
M1 - e24
ER -