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

Haren, M.T., Misan, G., Grant, J.F., Buckley, J.D., Howe, P.R.C., Taylor, A.W., Newbury, J., and McDermott, Robyn (2012) Proximal correlates of metabolic phenotypes during 'at-risk' and 'case' stages of the metabolic disease continuum. Nutrition and Diabetes, 2. e24. pp. 1-11.

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Abstract

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.

Item ID: 36800
Item Type: Article (Research - C1)
ISSN: 2044-4052
Keywords: metabolic trait expression, abdominal obesity, sleep disordered breathing symptoms, principal components analysis
Additional Information:

This work is licensed under the Creative Commons Attribution- NonCommercial-No Derivative Works 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

Funders: Premiers Science Research Fund, National Health and Medical Research Council (NHMRC)
Projects and Grants: NHMRC 511345
Date Deposited: 08 Jul 2015 05:19
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1117 Public Health and Health Services > 111706 Epidemiology @ 100%
SEO Codes: 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920104 Diabetes @ 100%
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