The association between anthropometric parameters, the metabolic syndrome and microalbuminuria in black Africans: the SABPA study.
We aimed to determine which surface anthropometric and metabolic syndrome (MS) markers could be associated with the development of microalbuminuria (MA), and assessed 200 urban Africans (25-60 years) stratified into low (< or = 0.90 and < or = 0.85) and high ( > 0.90 and > 0.85) waist-tohip ratio (WHR) groups from the North-West province. Anthropometric and fasting MS markers, such as systolic and diastolic blood pressure (BP), and glucose, triglyceride (TG) and high-density lipoprotein (HDL) levels, as well as MA markers were measured. Males revealed higher lifestyle risk factors (body mass index, smoking, alcohol consumption, low physical activity), anthropometric and MS markers compared to the females. The same overall trend was seen for high-WHR males but not for high-WHR females compared to their low-WHR counterparts. Both high-WHR groups revealed increased glucose values (males, 6.34 mmol/l; females, 6.13 mmol/l). Multiple linear regression analysis, independent of confounders, showed positive associations between diastolic blood pressure (DBP) (high WHR and all males), TG, waist circumference (WC) and development of MA in all males. In high-WHR females, positive associations existed only between WC and the development of MA, while neck circumference (NC) was associated with MA development in all females. To conclude, vascular BP, TG and WC were associated with risk of renal impairment in males, while in females, NC and WC circumferences were associated with this risk.
School of Biokinetics, Recreation and Sport Science, and School for Physiology, Nutrition and Consumer Sciences North-West University, Potchefstroom Campus, Potchefstroom, South Africa.
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S
Hoebel
J H
JH
de Ridder
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L
Malan
D000328:Adult; D000419:Albuminuria / Q000097:blood / Q000208:ethnology* / Q000503:physiopathology; D000886:Anthropometry; D015415:Biomarkers / Q000097:blood; D044383:Black People / Q000706:statistics & numerical data*; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D049628:Body Size / Q000208:ethnology*; D016009:Chi-Square Distribution; D005260:Female; D006801:Humans; D008055:Lipids / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000208:ethnology* / Q000503:physiopathology; D008875:Middle Aged; D009333:Neck; D018570:Risk Assessment; D012307:Risk Factors; D013019:South Africa / Q000453:epidemiology; D055105:Waist Circumference / Q000208:ethnology; D049629:Waist-Hip Ratio; D055815:Young Adult
D015415:Biomarkers; D001786:Blood Glucose; D008055:Lipids